@article {paper41,
	title = {A-posteriori error estimation and adaptivity for multiple-network poroelasticity},
	journal = {ESIAM: Mathematical Modelling and Numerical Analysis },
	volume = {57},
	number = {4},
	year = {2023},
	month = {07/2023},
	pages = {1921 - 1952},
	publisher = {ESAIM},
	doi = {10.1051/m2an/2023033},
	url = {https://doi.org/10.1051/m2an/2023033},
	author = {Eliseussen, Emilie and Marie E. {Rognes} and Travis B. {Thompson}}
}
@article {paper46,
	title = {Are brain displacements and pressures within the parenchyma induced by surface pressure differences? A computational modelling study},
	journal = {PLOS ONE},
	year = {2023},
	publisher = {PLOS },
	doi = {https://doi.org/10.1101/2022.09.07.506967},
	url = {https://www.biorxiv.org/content/10.1101/2022.09.07.506967v1},
	author = {Piersanti, Eleonora and Marie E. {Rognes} and Vinje, Vegard}
}
@misc {paper70,
	title = {Brains in motion - computational modelling of the brain{\textquoteright}s waterscape},
	howpublished = {Fluid Mechanics, Combustion, \& Engineering Physics Seminar, University of California San Diego, San Diego, US},
	year = {2023},
	author = {Marie E. {Rognes}}
}
@misc {paper68,
	title = {Brains in motion - computational modelling of the brain{\textquoteright}s waterscape},
	howpublished = {Oden Institute Seminar, University of Texas at Austin, TX, US},
	year = {2023},
	author = {Marie E. {Rognes}}
}
@article {paper53,
	title = {Cut finite element discretizations of cell-by-cell EMI electrophysiology models},
	journal = {TBA},
	year = {2023},
	publisher = {TBA},
	doi = {10.48550/arXiv.2306.03001},
	url = {https://doi.org/10.48550/arXiv.2306.03001},
	author = {Berre, Nanna and Marie E. {Rognes} and Massing, Andre}
}
@article {paper52,
	title = {The directional flow generated by peristalsis in perivascular networks - theoretical and numerical reduced-order description},
	journal = {Journal of Applied Physics},
	year = {2023},
	publisher = {AIP Publishing},
	author = {Gjerde, Ingeborg and Marie E. {Rognes} and S{\'a}nchez, Antonio}
}
@inbook {43265,
	title = {Finite element software and performance for mixed-dimensional network models},
	booktitle = {TBA},
	year = {2023},
	pages = {TBA},
	publisher = {Springer},
	organization = {Springer},
	author = {Daversin-Catty, C{\'e}cile and Joseph P. {Dean} and Marie E. {Rognes}}
}
@article {43096,
	title = {Human brain solute transport quantified by glymphatic MRI-informed biophysics during sleep and sleep deprivation},
	journal = {Fluids and Barriers of the Central Nervous System},
	year = {2023},
	month = {08/2023},
	publisher = {Springer Nature},
	abstract = {Human brain homeostasis requires carefully regulated transport of nutrients and waste, but its governing mechanisms are hard to quantify. By combining multi-modal gMRI data over 48 hours with high-fidelity inverse computational modelling, we here identify several potential transport mechanisms that best explain the clinical observations. Our findings support the combined roles of local, vascular and glymphatic-type clearance pathways within human brain tissue with tissue flow velocities on the order of $\mu$m/min, local clearance rates at the order of 10**(-3)/min, and\&nbsp;enhanced diffusion by a factor 3.5, in sleeping and sleep-deprived subjects. Reduced advection fully explains reduced tracer clearance after sleep-deprivation, supporting the role of sleep and sleep deprivation on human brain clearance.},
	doi = {https://doi.org/10.1101/2023.01.01.522190},
	author = {Vinje, Vegard and Zapf, Bastian and Ringstad, Geir and Per Kristian {Eide} and Marie E. {Rognes} and Mardal, Kent-Andre}
}
@article {paper55,
	title = {Modeling excitable cells with the EMI equations: spectral analysis and iterative solution strategy},
	journal = {TBA},
	year = {2023},
	publisher = {TBA},
	doi = {10.48550/arXiv.2308.12145},
	url = {https://doi.org/10.48550/arXiv.2308.12145},
	author = {Benedusi, Pietro and Ferrari, Paola and Marie E. {Rognes} and Serra-Capizzano, Stefano}
}
@article {paper51,
	title = {The modelling error in multi-dimensional time-dependent solute transport models},
	journal = {TBA},
	year = {2023},
	publisher = {TBA},
	url = {https://arxiv.org/abs/2303.17999},
	author = {Masri, Rami and Zeinhofer, Marius and Kuchta, Miroslav and Marie E. {Rognes}}
}
@article {43168,
	title = {Neural activity induces strongly coupled electro-chemo-mechanical interactions and fluid flow in astrocyte networks and extracellular space {\textendash} a computational study},
	journal = {PLoS Computational Biology},
	volume = {19},
	year = {2023},
	month = {07/2023},
	pages = {e1010996},
	publisher = {Public Library of Science},
	doi = {https://doi.org/10.1371/journal.pcbi.1010996},
	url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010996},
	author = {Marte J. {S{\ae}tra} and Ada Johanne {Ellingsrud} and Marie E. {Rognes}}
}
@article {hopf,
	title = {Optimal control of Hopf bifurcation points},
	journal = {SIAM Journal on Scientific Computing},
	volume = {45},
	year = {2023},
	publisher = {SIAM},
	doi = {10.1137/22M14744},
	url = {https://epubs.siam.org/doi/abs/10.1137/22M1474448},
	author = {Boull{\'e}, Nicolas and Patrick E. {Farrell} and Marie E. {Rognes}}
}
@misc {paper67,
	title = {Perivascular pathways and the dimension-2 gap},
	howpublished = {Numerical Analysis and Scientific Computing Seminar, Courant Institute, NY, US},
	year = {2023},
	author = {Marie E. {Rognes}}
}
@misc {paper69,
	title = {Perivascular pathways and the dimension-2 gap},
	howpublished = {CMOR Colloqium Series, Rice University, Houston, TX, US},
	year = {2023},
	author = {Marie E. {Rognes}}
}
@misc {paper66,
	title = {Perivascular pathways and the dimension-2 gap},
	howpublished = {Scientific Computing Seminar, Brown University, Providence, Rhode Island, US},
	year = {2023},
	author = {Marie E. {Rognes}}
}
@article {paper44,
	title = {The role of clearance in neurodegenerative disease},
	journal = {SIAM Journal on Applied Mathematics},
	year = {2023},
	month = {07/2023},
	publisher = {SIAM},
	url = {https://doi.org/10.1101/2022.03.31.486533},
	author = {Georgia S. {Brennan} and Travis B. {Thompson} and Oliveri, Hadrien and Marie E. {Rognes} and Goriely, Alain}
}
@article {paper54,
	title = {SMART: Spatial Modeling Algorithms for Reaction and Transport},
	journal = {Journal of Open Source Software},
	year = {2023},
	publisher = {TBA},
	doi = {https://arxiv.org/abs/2306.07368},
	author = {Justin G. {Laughlin} and J{\o}rgen Schartum {Dokken} and Finsberg, Henrik and Emmet A. {Francis} and Christopher T. {Lee} and Marie E. {Rognes} and Rangamani, Padmini}
}
@misc {42925,
	title = {Cell-based modelling and simulation of excitable tissue},
	howpublished = {Simula Research Laboratory, Oslo, Norway},
	year = {2022},
	type = {Invited lecture},
	author = {Marie E. {Rognes}}
}
@misc {42926,
	title = {Computational brainphatics: coupled models of mechanics and electrophysiology in brain tissue},
	howpublished = {DigiBrain Symposium, Simula Research Laboratory, Oslo, Norway},
	year = {2022},
	author = {Ada Johanne {Ellingsrud} and Marie E. {Rognes}}
}
@article {paper45,
	title = {CSF circulation and dispersion yield rapid clearance from intracranial compartments},
	journal = {Frontiers in Bioengineering and Biotechnology},
	volume = {12},
	year = {2022},
	month = {09/2022},
	publisher = {Frontiers},
	doi = {https://doi.org/10.3389/fbioe.2022.932469},
	url = {https://www.frontiersin.org/articles/10.3389/fbioe.2022.932469/full},
	author = {Hornkj{\o}l, Martin and Lars Magnus {Valnes} and Geir A. {Ringstad} and Marie E. {Rognes} and Per Kristian {Eide} and Mardal, Kent-Andre and Vinje, Vegard}
}
@misc {paper62,
	title = {Finite element adaptivity for human brain mechanics},
	howpublished = {FEniCS{\textquoteright}22, University of California San Diego, La Jolla, US},
	year = {2022},
	type = {Invited presentation },
	author = {Marie E. {Rognes}}
}
@misc {paper72,
	title = {Finite elements and brain multiphysics},
	howpublished = {MAE 207: Finite element analysis in coupled problems, UCSD, La Jolla, US},
	year = {2022},
	type = {Invited guest lecture},
	author = {Marie E. {Rognes}}
}
@article {daversincatty2021geometrically,
	title = {Geometrically reduced modelling of pulsatile flow in perivascular networks},
	journal = {Frontiers in Physics},
	volume = {10},
	year = {2022},
	publisher = {Frontiers},
	abstract = {Flow of cerebrospinal fluid in perivascular spaces is a key mechanism underlying brain transport and clearance. In this paper, we present a mathematical and numerical formalism for reduced models of pulsatile viscous fluid flow in networks of generalized annular cylinders. We apply this framework to study cerebrospinal fluid flow in perivascular spaces induced by pressure differences, cardiac pulse wave-induced vascular wall motion and vasomotion. The reduced models provide approximations of the cross-section average pressure and cross-section flux, both defined over the topologically one-dimensional centerlines of the network geometry. Comparing the full and reduced model predictions, we find that the reduced models capture pulsatile flow characteristics and provide accurate pressure and flux predictions across the range of idealized and image-based scenarios investigated{\textemdash}at a fraction of the computational cost of the corresponding full models. The framework presented thus provides a robust and effective computational approach for large scale in-silico studies of pulsatile perivascular fluid flow and transport.},
	doi = {10.3389/fphy.2022.882260},
	url = {https://www.frontiersin.org/article/10.3389/fphy.2022.882260},
	author = {Daversin-Catty, C{\'e}cile and Gjerde, Ingeborg and Marie E. {Rognes}}
}
@article {paper42,
	title = {Human intracranial pulsatility during the cardiac cycle: a computational modelling framework},
	journal = {Fluids and Barriers of the Central Nervous System},
	volume = {19},
	number = {1},
	year = {2022},
	pages = {1-17},
	publisher = {Springer},
	url = {https://doi.org/10.1101/2022.05.19.492650},
	author = {Causemann, Marius and Vinje, Vegard and Marie E. {Rognes}}
}
@book {27753,
	title = {Mathematical modeling of the human brain: from magnetic resonance images to finite element simulation},
	series = {Simula SpringerBriefs on Computing},
	volume = {10},
	year = {2022},
	pages = {118},
	publisher = {Springer},
	organization = {Springer},
	address = {Cham},
	author = {Mardal, Kent-Andre and Marie E. {Rognes} and Travis B. {Thompson} and Lars Magnus {Valnes}}
}
@misc {paper62,
	title = {Mathematical modelling of human brain transport: from medical images to biophysical simulation},
	howpublished = {UCSD Institute for Neural Computation seminar series, La Jolla, CA, USA},
	year = {2022},
	author = {Marie E. {Rognes}}
}
@misc {paper60,
	title = {Mathematical modelling of human brain transport: from medical images to biophysical simulation},
	howpublished = {Pretty Porous Science Seminar, University of Stuttgart, Stuttgart, Germany},
	year = {2022},
	author = {Marie E. {Rognes}}
}
@misc {paper64,
	title = {Mathematical modelling of human brain transport: from medical images to biophysical simulation},
	howpublished = {ECCOMAS Conference, Oslo, Norway},
	year = {2022},
	month = {06/2022},
	type = {Semi-plenary lecture},
	author = {Marie E. {Rognes}}
}
@misc {paper61,
	title = {Mathematical modelling of human brain transport: from medical images to biophysical simulation},
	howpublished = {Laboratoire Mechnique des Solides, {\'E}cole Polytechnique, Paris, France},
	year = {2022},
	author = {Marie E. {Rognes}}
}
@misc {42855,
	title = {Modeling electrodiffusive, osmotic, and hydrostatic interplay in astrocyte networks},
	year = {2022},
	month = {11/2022},
	publisher = {Society for Neuroscience},
	address = {Neuroscience 2022},
	abstract = {During high neuronal activity, the intra- and extracellular ion concentrations change. These changes affect the osmotic pressure gradients across the membranes of both neurons and astrocytes, leading to water movement and cellular swelling. We asked: Can swelling generate a hydrostatic pressure gradient of sufficient magnitude to drive non-negligible fluid flow within astrocytes or the extracellular space [1]? As it is currently infeasible to measure such intracellular pressure gradients in vivo, computational modeling emerges as a viable alternative to study the interplay between osmotic and hydrostatic forces at the microscale.\&nbsp;\&nbsp;In this study, we present a computational model of ionic electrodiffusion, hydrostatic pressures, and transmembrane- and intracompartmental fluid flow in a homogenized astrocytic syncytium surrounded by extracellular space. The model builds on previous models of ionic electrodiffusion [2,3],\&nbsp;and potassium buffering [4]. Our findings show that increases in extracellular potassium concentrations in response to neuronal activity induce swelling and hydrostatic pressure gradients within the intra- and extracellular spaces. The fluid flow induced by these hydrostatic pressure gradients alone did not have a significant effect on the transport of potassium within any of the compartments. However, when also accounting for fluid flow induced by osmotic gradients within the astrocytic syncytium, convection played a considerable role in potassium clearance. These findings point at a mechanistic understanding of how astrocytic permeability may impact fluid flow in the brain.[1] Halnes, G., Pettersen, K. H., {\O}yehaug, L., Rognes, M. E. \&amp; Einevoll, G. T. Astrocytic ion dynamics: Implications for potassium buffering and liquid flow. In Computational Glioscience, 363{\textendash}391 (Springer, 2019).[2] Mori, Y. A multidomain model for ionic electrodiffusion and osmosis with an application to cortical spreading depression. Phys. D: Nonlinear Phenom. 308, 94{\textendash}108 (2015).[3]\&nbsp; Zhu, Y., Xu, S., Eisenberg, R. S. \&amp; Huang, H. Optic nerve microcirculation: Fluid flow and electrodiffusion. Phys. Fluids 33, 041906 (2021).[4] Halnes, G., {\O}stby, I., Pettersen, K. H., Omholt, S. W. \&amp; Einevoll, G. T. Electrodiffusive model for astrocytic and neuronal ion concentration dynamics. PLoS computational biology 9, e1003386 (2013).},
	author = {Marte J. {S{\ae}tra} and Ada Johanne {Ellingsrud} and Marie E. {Rognes}}
}
@misc {43225,
	title = {Modeling fluid flow in perivascular networks},
	howpublished = {ECCOMAS22, Oslo (Norway)},
	year = {2022},
	doi = {https://doi.org/10.5281/zenodo.7848945},
	author = {Daversin-Catty, C{\'e}cile and Vinje, Vegard and Gjerde, Ingeborg and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@misc {42942,
	title = {The pulsating brain: an interface-coupled fluid-poroelastic model of the cranial cavity},
	howpublished = {ECCOMAS Congress 2022, Oslo, Norway},
	year = {2022},
	publisher = {ECCOMAS CONGRESS 2022},
	abstract = {Driven by cardiac and respiratory pulsations, our brain and the cerebrospinal (CSF) fluidsurrounding it exhibit complex fluid flow and displacement patterns. Despite being essen-tial to normal brain function, our understanding of intracranial dynamics is still limited,and various diseases are associated with impaired CSF flow and elevated intracranial pres-sure [1]. Computational models offer further insights into pulsatile intracranial dynamics,but are complicated by the close interplay of arterial inflow, venous outflow, CSF motionand brain tissue movement inside the rigid cranial cavity.In this talk, I will present a new computational model of cardiac-induced pulsatile motioninside the human cranial cavity. The CSF flow in the subarachnoid space and ventricularsystem is modelled using the time-dependent Stokes equations, and coupled with Biot{\textquoteright}sporoelasticity equations in the brain tissue, thus integrating all major intracranial con-stituents into the modelling approach. Employing the pulsatile inflow of blood into braintissue as a driver of motion, the model enables us to study the dynamics of the entireintracranial system.The model is discretized using a coupled/monolithic approach with a mixedTaylor-Hood type finite element scheme and implemented with the finite element frame-work FEniCS. Numerical results obtained with a detailed 3D human head model andphysiological material parameters are presented and compared with experimental data.The new model faithfully replicates the main aspects of intracranial pulsatile motion.},
	keywords = {brain mechanics, Finite element method, interface coupling, multiphysics problems},
	author = {Causemann, Marius and Vinje, Vegard and Marie E. {Rognes}}
}
@article {hong2021robust,
	title = {Robust approximation of generalized Biot-Brinkman problems},
	journal = {Journal on Scientific Computing},
	volume = {93},
	year = {2022},
	month = {11/2022},
	pages = {77},
	publisher = {Springer},
	url = {https://arxiv.org/abs/2112.13618},
	author = {Hong, Q. and Kraus, J. and Kuchta, Miroslav and Lymbery, M. and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@article {paper38,
	title = {A scalable solver for a stochastic, hybrid cellular automaton model of personalized breast cancer therapy},
	journal = {International Journal for Numerical Methods in Biomedical Engineering },
	volume = {38},
	year = {2022},
	month = {10/2021},
	pages = {e3542},
	publisher = {Wiley},
	doi = {10.1002/cnm.3542 },
	url = {https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/cnm.3542},
	author = {Lai, Xiaoran and H{\r a}kon A. {Task{\'e}n} and Mo, Torgeir and Simon W {Funke} and Frigessi, Arnoldo and Marie E. {Rognes} and Kohn-Luque, Alvaro}
}
@misc {marius_causemann_2022_6553790,
	title = {Software and Data for "Human intracranial pulsatility during the cardiac cycle: a computational modelling framework"},
	year = {2022},
	publisher = {Zenodo},
	abstract = {This repository contains the code, meshes and data required to reproduce the results of the article "Human intracranial pulsatility during the cardiac cycle: a computational modelling framework", M. Causemann, V. Vinje and M.E. Rognes (2022).The easiest way of getting the code running is based on snakemake and singularity: Installing both (using .e.g conda:\&nbsp;\&nbsp;conda create -c bioconda -c conda-forge -n snakemake snakemake singularity) and running\&nbsp;snakemake --cores N\&nbsp;will run pull a docker image (mcause/brainsim:openblas) and execute all steps on N cores. Note however, that the required computational resources are quite large and unlikely to be met by a desktop computer. Snakemake also supports submitting jobs on a SLURM cluster via the\&nbsp;--profile profile_folder_name\&nbsp;option. An example of a profile configuration can be found in the\&nbsp;ex3\&nbsp;folder.The complete workflow is defined in the \&nbsp;Snakefile, which hence also provides documentation of the individual steps.},
	doi = {10.5281/zenodo.6553790},
	url = {{https://doi.org/10.5281/zenodo.6553790},
	author = {Causemann, Marius and Vinje, Vegard and Marie E. {Rognes}}
}
@misc {paper71,
	title = {Such stuff as dreams are made on: a computational tale of optimal transport and brain clearance},
	howpublished = {IEEE Brain Discovery Workshop on Brain, Mind and Body: Cognitive Neuroengineering for Health and Wellness},
	year = {2022},
	author = {Marie E. {Rognes}}
}
@misc {paper62,
	title = {Such stuff as dreams are made on: a finite element tale of optimal transport and brain clearance},
	howpublished = {Acta Numerica 30th Birthday Conference, Banach Centre at Bedlewo, Poland},
	year = {2022},
	month = {06/2022},
	author = {Marie E. {Rognes}}
}
@article {ellingsrud2021validating,
	title = {Validating a computational framework for ionic electrodiffusion with cortical spreading depression as a case study},
	journal = {eNeuro},
	volume = {9},
	number = {2},
	year = {2022},
	month = {04/2022},
	publisher = {Society for Neuroscience},
	author = {Ada Johanne {Ellingsrud} and Didrik B. {Dukefoss} and Enger, Rune and Halnes, Geir and Pettersen, Klas and Marie E. {Rognes}}
}
@misc {42811,
	title = {Waterscales: Mathematical and computational foundations for modelling cerebral fluid flow},
	howpublished = {European Mathematical Society Magazine},
	volume = {126},
	year = {2022},
	month = {01/2022},
	pages = {1-10},
	publisher = {European Mathematical Society},
	type = {Magazine article},
	author = {Marie E. {Rognes}}
}
@article {paper31,
	title = {Abstractions and automated algorithms for mixed-dimensional finite element methods},
	journal = {ACM Transactions on Mathematical Software},
	volume = {47},
	year = {2021},
	month = {09/2021},
	pages = {1-36},
	publisher = {ACM},
	author = {Daversin-Catty, C{\'e}cile and Chris N. {Richardson} and Ada Johanne {Ellingsrud} and Marie E. {Rognes}}
}
@article {paper35,
	title = {Accurate discretization of poroelasticity without Darcy stability {\textendash} Stokes-Biot revisited},
	journal = {BIT Numerical Mathematics},
	volume = {61},
	year = {2021},
	pages = {941-976},
	publisher = {Springer},
	doi = {https://doi.org/10.1007/s10543-021-00849-0},
	author = {Mardal, Kent-Andre and Marie E. {Rognes} and Thompson, Travis}
}
@misc {28263,
	title = {Accurate numerical simulation of electrodiffusion and water movement in brain tissue with cortical spreading depression as a case study},
	howpublished = {Interpore 13th annual meeting (online)},
	year = {2021},
	type = {Conference talk},
	address = {Online},
	author = {Ada Johanne {Ellingsrud} and Marie E. {Rognes}},
	editor = {Farrell, Patrick and Boull{\'e}, Nicolas and Didrik B. {Dukefoss} and Enger, Rune and Pettersen, Klas and Halnes, Geir}
}
@article {paper36,
	title = {Accurate numerical simulation of electrodiffusion and water movement in brain tissue},
	journal = {IMA Mathematical Medicine and Biology},
	volume = {38},
	year = {2021},
	month = {11/2021},
	pages = {516{\textendash}551},
	publisher = {IMA},
	author = {Ada Johanne {Ellingsrud} and Boull{\'e}, Nicolas and Patrick E. {Farrell} and Marie E. {Rognes}}
}
@misc {27749,
	title = {Brain modelling: from magnetic resonance images to finite element simulation - a lecture series},
	howpublished = {Porous Media Math Seminar Series, University of Bergen, Norway},
	year = {2021},
	note = {6 x 45 min lectures},
	type = {Invited short course  },
	url = {https://github.com/meg-simula/mri2fem-lectures},
	author = {Marie E. {Rognes}}
}
@article {paper37,
	title = {Brain solute transport is more rapid in periarterial than perivenous spaces},
	journal = {Scientific Reports},
	volume = {11},
	number = {16085},
	year = {2021},
	month = {08/2021},
	publisher = {Nature},
	doi = {https://doi.org/10.1038/s41598-021-95306-x},
	url = {https://www.nature.com/articles/s41598-021-95306-x},
	author = {Vinje, Vegard and Erik N. T. P. {Bakker} and Marie E. {Rognes}}
}
@inbook {27254,
	title = {A cell-based model for ionic electrodiffusion in excitable tissue},
	booktitle = {Modeling Excitable Tissue: The EMI Framework},
	number = {7},
	year = {2021},
	pages = {14-27},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	url = {https://www.springer.com/gp/book/9783030611569},
	author = {Ada Johanne {Ellingsrud} and Daversin-Catty, C{\'e}cile and Marie E. {Rognes}},
	editor = {Mardal, Kent-Andre and Marie E. {Rognes} and Tveito, Aslak}
}
@misc {paper52,
	title = {Computational brainphatics},
	howpublished = {2021 SIAM Conference on Computational Science and Engineering},
	year = {2021},
	month = {03/2021},
	type = {Plenary keynote },
	author = {Marie E. {Rognes}}
}
@misc {paper53,
	title = {Depressed brain cells - a numerical perspective},
	howpublished = {6th Oxford International Neuron and Brain Mechanics Workshop, Oxford, UK},
	year = {2021},
	author = {Marie E. {Rognes}}
}
@inbook {27507,
	title = {Derivation of a Cell-Based Mathematical Model of Excitable Cells},
	booktitle = {Modeling Excitable Tissue: The EMI Framework},
	volume = {7},
	year = {2021},
	pages = {1-13},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	chapter = {1},
	address = {Cham},
	abstract = {Excitable cells are of vital importance in biology, and mathematical models have contributed significantly to understand their basic mechanisms. However, classical models of excitable cells are based on severe assumptions that may limit the accuracy of the simulation results. Here, we derive a more detailed approach to modeling that has recently been applied to study the electrical properties of both neurons and cardiomyocytes. The model is derived from first principles and opens up possibilities for studying detailed properties of excitable cells. We refer to the model as the EMI model because both the extracellular space (E), the cell membrane (M) and the intracellular space (I) are explicitly represented in the model, in contrast to classical spatial models of excitable cells. Later chapters of the present text will focus on numerical methods and software for solving the model. Also, in the next chapter, the model will be extended to account for ionic concentrations in the intracellular and extracellular spaces.},
	isbn = {978-3-030-61157-6},
	issn = {2512-1677},
	doi = {10.1007/978-3-030-61157-6_1},
	url = {https://link.springer.com/content/pdf/10.1007\%2F978-3-030-61157-6_1.pdf},
	author = {Karoline Horgmo {J{\ae}ger} and Tveito, Aslak},
	editor = {Tveito, Aslak and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@inbook {27586,
	title = {Improving Neural Simulations with the EMI Model},
	booktitle = {Modeling Excitable Tissue: The EMI Framework},
	year = {2021},
	pages = {87{\textendash}98},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Mathematical modeling of neurons is an essential tool to investigate neuronal activity alongside with experimental approaches. However, the conventional modeling framework to simulate neuronal dynamics and extracellular potentials makes several assumptions that might need to be revisited for some applications. In this chapter we apply the EMI model to investigate the ephaptic effect and the effect of the extracellular probes on the measured potential. Finally, we introduce reduced EMI models, which provide a more computationally efficient framework for simulating neurons with complex morphologies.},
	isbn = {978-3-030-61157-6},
	doi = {10.1007/978-3-030-61157-6_7},
	url = {https://doi.org/10.1007/978-3-030-61157-6_7},
	author = {Alessio Paolo {Buccino} and Kuchta, Miroslav and Schreiner, Jakob and Mardal, Kent-Andre},
	editor = {Tveito, Aslak and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@inbook {27585,
	title = {Iterative Solvers for EMI Models},
	booktitle = {Modeling Excitable Tissue: The EMI Framework},
	year = {2021},
	pages = {70{\textendash}86},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {This chapter deals with iterative solution algorithms for the four EMI formulations derived in (17, Chapter 5). Order optimal monolithic solvers robust with respect to material parameters, the number of degrees of freedom of discretization as well as the time-stepping parameter are presented and compared in terms of computational cost. Domain decomposition solver for the single-dimensional primal formulation is discussed.},
	isbn = {978-3-030-61157-6},
	doi = {10.1007/978-3-030-61157-6_6},
	url = {https://doi.org/10.1007/978-3-030-61157-6_6},
	author = {Kuchta, Miroslav and Mardal, Kent-Andre},
	editor = {Tveito, Aslak and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@inproceedings {28254,
	title = {A mixed framework for topological model reduction of coupled PDEs},
	journal = {9th edition of the International Conference on Computational Methods for Coupled Problems in Science and Engineering},
	year = {2021},
	publisher = {CIMNE},
	doi = {10.23967/coupled.2021.005},
	url = {https://www.scipedia.com/public/Gjerde_Rognes_2021a},
	author = {Gjerde, Ingeborg and Marie E. {Rognes}}
}
@misc {43223,
	title = {Mixed-dimensional coupled finite elements in FEniCS.},
	howpublished = {Indo-Norwegian workshop on computational challenges and modelling of coupled processes in porous media, University of Bergen (Norway)},
	year = {2021},
	doi = {https://doi.org/10.5281/zenodo.7849094},
	author = {Daversin-Catty, C{\'e}cile and Marie E. {Rognes}}
}
@inbook {27570,
	title = {Modeling Cardiac Mechanics on a Sub-Cellular Scale},
	booktitle = {Modeling Excitable Tissue: The EMI Framework},
	volume = {7},
	year = {2021},
	month = {11/2020},
	pages = {28-43},
	publisher = { Springer International Publishing},
	organization = { Springer International Publishing},
	edition = {1},
	chapter = {3},
	address = {Cham},
	abstract = {We aim to extend existing models of single-cell mechanics to the EMI framework, to define spatially resolved mechanical models of cardiac myocytes embedded in a passive extracellular space. The models introduced here will be pure mechanics models employing fairly simple constitutive laws for active and passive mechanics. Future extensions of the models may include a coupling to the electrophysiology and electro-diffusion models described in the other chapters, to study the impact of spatially heterogeneous ion concentrations on the cell and tissue mechanics.},
	author = {Telle, {\r A}shild and Wall, Samuel and Sundnes, Joakim},
	editor = {Tveito, Aslak and Marie E. {Rognes} and Mardal, Kent-Andre}
}
@book {27752,
	title = {Modeling Excitable Tissue: The EMI Framework},
	year = {2021},
	publisher = {Springer},
	editor = {Tveito, Aslak and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@misc {43224,
	title = {Modeling fluid flow in perivascular networks},
	howpublished = {Oslo glymphatics symposium, Oslo (Norway)},
	year = {2021},
	doi = {https://doi.org/10.5281/zenodo.7848945},
	author = {Daversin-Catty, C{\'e}cile and Gjerde, Ingeborg and Mardal, Kent-Andre and Marie E. {Rognes} and Vinje, Vegard}
}
@misc {paper53,
	title = {Modelling intracranial pressure, fluid flow and solute transport in surface perivascular space},
	howpublished = {Brain H20 Symposium, Copenhagen, Denmark (virtual)},
	year = {2021},
	author = {Marie E. {Rognes}}
}
@misc {27808,
	title = { Numerical foundations of the brain{\textquoteright}s waterscape},
	howpublished = {S{\'e}minaire du Laboratoire Jacques-Louis Lions (invited), Sorbonne University, Paris, France},
	year = {2021},
	author = {Marie E. {Rognes}}
}
@inbook {27497,
	title = {Operator Splitting and Finite Difference Schemes for Solving the EMI Model},
	booktitle = {Modeling Excitable Tissue: The EMI Framework},
	volume = {7},
	year = {2021},
	pages = {44 - 55},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	chapter = {4},
	address = {Cham},
	abstract = {We want to be able to perform accurate simulations of a large number of cardiac cells based on mathematical models where each individual cell is represented in the model. This implies that the computational mesh has to have a typical resolution of a few {\textmu}m leading to huge computational challenges. In this paper we use a certain operator splitting of the coupled equations and showthat this leads to systems that can be solved in parallel. This opens up for the possibility of simulating large numbers of coupled cardiac cells.},
	isbn = {978-3-030-61156-9},
	issn = {2512-1677},
	doi = {10.1007/978-3-030-61157-6_4},
	url = {http://link.springer.com/content/pdf/10.1007/978-3-030-61157-6_4},
	author = {Karoline Horgmo {J{\ae}ger} and Kristian Gregorius {Hustad} and Cai, Xing and Tveito, Aslak},
	editor = {Tveito, Aslak and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@article {paper33,
	title = {Parameter robust preconditioning by congruence for multiple-network poroelasticity},
	journal = {SIAM Journal of Scientific Computing},
	volume = {43},
	year = {2021},
	pages = {B984{\textendash}B1007},
	publisher = {SIAM},
	doi = {https://doi.org/10.1137/20M1326751},
	author = {Piersanti, Eleonora and Jeonghun J. {Lee} and Mardal, Kent-Andre and Marie E. {Rognes} and Thompson, Travis}
}
@inproceedings {paper42,
	title = {Parameter robust preconditioning for multi-compartmental Darcy equations},
	journal = {Numerical Mathematics and Advanced Applications ENUMATH 2019},
	volume = {139},
	year = {2021},
	pages = {794{\textendash}797},
	publisher = {Springer International Publishing},
	edition = {1},
	doi = {10.1007/978-3-030-55874-1},
	author = {Piersanti, Eleonora and Marie E. {Rognes} and Mardal, Kent-Andre}
}
@inbook {27588,
	title = {Solving the EMI Equations using Finite Element Methods},
	booktitle = {Modeling Excitable Tissue: The EMI Framework},
	year = {2021},
	pages = {56{\textendash}69},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {This chapter discusses 2 X 2 symmetric variational formulations and associated finite element methods for the EMI equations. We demonstrate that the presented methods converge at expected rates, and compare the approaches in terms of approximation of the transmembrane potential. Overall, the choice of which formulation to employ for solving EMI models becomes largely a matter of desired accuracy and available computational resources.},
	isbn = {978-3-030-61157-6},
	doi = {10.1007/978-3-030-61157-6_5},
	url = {https://doi.org/10.1007/978-3-030-61157-6_5},
	author = {Kuchta, Miroslav and Mardal, Kent-Andre and Marie E. {Rognes}},
	editor = {Tveito, Aslak and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@misc {paper53,
	title = {Understanding the mechanisms of the brain{\textquoteright}s waterscape},
	howpublished = {2021 InterPore Conference (online)},
	year = {2021},
	type = {Invited lecture},
	url = {https://www.youtube.com/watch?v=U3X_KVz1O4M\&t=82s},
	author = {Marie E. {Rognes}}
}
@misc {27750,
	title = {The brain{\textquoteright}s numerical waterscape},
	howpublished = {Oxford Industrial and Applied Mathematics Seminar, Oxford, UK},
	year = {2020},
	author = {Marie E. {Rognes}}
}
@misc {paper50,
	title = {The brain{\textquoteright}s (numerical) waterscape},
	howpublished = {Springer Partial Differential Equations and Applications webinar},
	year = {2020},
	author = {Marie E. {Rognes}}
}
@article {paper31,
	title = {Fast uncertainty quantification of tracer distribution in the brain interstitial fluid with multilevel and quasi Monte Carlo},
	journal = { International Journal for Numerical Methods in Biomedical Engineering},
	volume = {37},
	year = {2020},
	month = {11/2020},
	pages = {e3412},
	publisher = {Wiley},
	url = {https://onlinelibrary.wiley.com/doi/full/10.1002/cnm.3412},
	author = {Croci, Matteo and Vinje, Vegard and Marie E. {Rognes}}
}
@article {paper30,
	title = {Finite element simulation of ionic electrodiffusion in cellular geometries},
	journal = {Frontiers in Neuroinformatics},
	volume = {14},
	year = {2020},
	pages = {11},
	publisher = {Frontiers},
	doi = {https://doi.org/10.3389/fninf.2020.00011},
	author = {Ada Johanne {Ellingsrud} and Solbraa, Andreas and Gaute T. {Einevoll} and Halnes, Geir and Marie E. {Rognes}}
}
@misc {28264,
	title = {Finite element simulation of ionic electrodiffusion in cellular geometries},
	howpublished = {Online},
	year = {2020},
	publisher = {29th annual computational neuroscience meeting},
	type = {Conference talk},
	address = {Online},
	author = {Ada Johanne {Ellingsrud} and Marie E. {Rognes}},
	editor = {Halnes, Geir and Solbr{\r a}, Andreas and Einevoll, Gaute}
}
@article {26683,
	title = {Intracranial pressure elevation alters CSF clearance pathways},
	journal = {Fluids and Barriers of the CNS},
	volume = {17},
	number = {29},
	year = {2020},
	month = {04/2020},
	publisher = {Springer Nature BMC},
	keywords = {brain mechanics, Cerebrospinal Fluid, Intracranial pressure},
	doi = {https://doi.org/10.1186/s12987-020-00189-1},
	author = {Vinje, Vegard and Eklund, Anders and Mardal, Kent-Andre and Marie E. {Rognes} and St{\o}verud, Karen-Helene}
}
@article {27722,
	title = {The mechanisms behind perivascular fluid flow},
	journal = {PLOS ONE},
	volume = {15},
	number = {12},
	year = {2020},
	pages = {1-20},
	publisher = {Public Library of Science},
	abstract = {Flow of cerebrospinal fluid (CSF) in perivascular spaces (PVS) is one of the key concepts involved in theories concerning clearance from the brain. Experimental studies have demonstrated both net and oscillatory movement of microspheres in PVS (Mestre et al. (2018), Bedussi et al. (2018)). The oscillatory particle movement has a clear cardiac component, while the mechanisms involved in net movement remain disputed. Using computational fluid dynamics, we computed the CSF velocity and pressure in a PVS surrounding a cerebral artery subject to different forces, representing arterial wall expansion, systemic CSF pressure changes and rigid motions of the artery. The arterial wall expansion generated velocity amplitudes of 60{\textendash}260\&nbsp;μm/s, which is in the upper range of previously observed values. In the absence of a static pressure gradient, predicted net flow velocities were small (\&lt;0.5\&nbsp;μm/s), though reaching up to 7\&nbsp;μm/s for non-physiological PVS lengths. In realistic geometries, a static systemic pressure increase of physiologically plausible magnitude was sufficient to induce net flow velocities of 20{\textendash}30\&nbsp;μm/s. Moreover, rigid motions of the artery added to the complexity of flow patterns in the PVS. Our study demonstrates that the combination of arterial wall expansion, rigid motions and a static CSF pressure gradient generates net and oscillatory PVS flow, quantitatively comparable with experimental findings. The static CSF pressure gradient required for net flow is small, suggesting that its origin is yet to be determined.},
	doi = {10.1371/journal.pone.0244442},
	url = {https://doi.org/10.1371/journal.pone.0244442},
	author = {Daversin-Catty, C{\'e}cile and Vinje, Vegard and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@misc {26768,
	title = {Advances in conformal finite element methods for generalized poroelasticity: A-posteriori error estimates for the two-field generalized poroelasticity equations and an elliptic-parabolic framework},
	howpublished = {Interpore 2019, Valencia, Spain},
	year = {2019},
	author = {Marie E. {Rognes} and Thompson, Travis}
}
@inbook {23577,
	title = {Astrocytic Ion Dynamics: Implications for Potassium Buffering and Liquid Flow},
	booktitle = {Computational Glioscience  },
	year = {2019},
	publisher = {Springer},
	organization = {Springer},
	address = {Springer Series in Computational Neuroscience},
	author = {Halnes, Geir and Klas H. {Pettersen} and {\O}yehaug, Leiv and Marie E. {Rognes} and Hans Petter {Langtangen} and Gaute T {Einevoll}},
	editor = {Pitta, D{\'e} and Berry, H.}
}
@article {26525,
	title = {Automated adjoints of coupled PDE-ODE systems},
	journal = {SIAM Journal on Scientific Computing},
	volume = {41},
	year = {2019},
	publisher = {SIAM},
	doi = {10.1137/17M1144532},
	url = {http://epubs.siam.org/toc/sjoce3/41/3  },
	author = {Patrick E. {Farrell} and Johan Elon {Hake} and Simon W {Funke} and Marie E. {Rognes}}
}
@misc {26622,
	title = {Intracranial pressure elevation alters CSF clearance pathways},
	howpublished = {The 2019 CSF Symposium, Oslo, Norway},
	year = {2019},
	author = {Vinje, Vegard and St{\o}verud, Karen-Helene and Marie E. {Rognes} and Mardal, Kent-Andre and Eklund, Anders}
}
@article {paper25,
	title = {A mixed finite element method for nearly incompressible multiple-network poroelasticity},
	journal = {SIAM Journal on Scientific Computing},
	volume = {41},
	year = {2019},
	month = {03/2019},
	pages = {A722{\textendash}A747},
	publisher = {SIAM},
	doi = {https://doi.org/10.1137/18M1182395},
	url = {https://epubs.siam.org/doi/10.1137/18M1182395},
	author = {Lee, Jeonghun and Piersanti, Eleonora and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@misc {27011,
	title = {Mixed-dimensional coupled finite elements in FEniCS},
	howpublished = {FEniCS{\textquoteright}19, Washington DC, USA},
	year = {2019},
	author = {Daversin-Catty, C{\'e}cile and Marie E. {Rognes}}
}
@misc {27012,
	title = {Mixed-dimensional coupled finite elements in FEniCS},
	howpublished = {ENUMATH 2019, Egmond aan Zee, The Netherlands},
	year = {2019},
	author = {Daversin-Catty, C{\'e}cile and Marie E. {Rognes}}
}
@misc {paper40,
	title = {Nearly incompressible generalized poroelasticity - discretization and preconditioning},
	howpublished = {International workshop in connection with Ragnar Winther{\textquoteright}s 70th birthday, Oslo, Norway},
	year = {2019},
	author = {Marie E. {Rognes}}
}
@article {25857,
	title = {Respiratory influence on cerebrospinal fluid flow {\textendash} a computational study based on long-term intracranial pressure measurements},
	journal = {Scientific Reports},
	volume = {9},
	year = {2019},
	month = {07/2019},
	pages = {9732},
	publisher = {Springer Nature},
	doi = {https://doi.org/10.1038/s41598-019-46055-5},
	author = {Vinje, Vegard and Geir A. {Ringstad} and Erika Kristina {Lindstr{\o}m} and Lars Magnus {Valnes} and Marie E. {Rognes} and Per Kristian {Eide} and Mardal, Kent-Andre}
}
@article {paper27,
	title = {Towards personalized computer simulation of breast cancer treatment: a multi-scale pharmacokinetic and pharmacodynamic model informed by multi-type patient data},
	journal = {Cancer Research},
	volume = {79},
	year = {2019},
	month = {05/2019},
	pages = {4293-4304},
	publisher = {American Association for Cancer Research},
	doi = {10.1158/0008-5472.CAN-18-1804},
	url = {http://cancerres.aacrjournals.org/content/early/2019/05/22/0008-5472.CAN-18-1804},
	author = {Lai, Xiaoran and Geier, Oliver and Fleischer, Thomas and Garred, {\O}ystein and Elin Faye {Borgen} and Simon W {Funke} and Kumar, Surendra and Marie E. {Rognes} and Seierstad, Therese and Boerresen-Dale, Anne-Lise and Vessela N. {Kristensen} and Engebraaten, Olav and Kohn-Luque, Alvaro and Frigessi, Arnoldo}
}
@article {25766,
	title = {Uncertainty in cardiac myofiber orientation and stiffnesses dominate the variability of left ventricle deformation response},
	journal = { International Journal for Numerical Methods in Biomedical Engineering},
	volume = {35},
	year = {2019},
	pages = {e3178},
	publisher = { Wiley},
	author = {Rodr{\'\i}guez-Cantano, Roc{\'\i}o and Sundnes, Joakim and Marie E. {Rognes}}
}
@misc {26621,
	title = {Uncertainty quantification of parenchymal tracer distribution using random diffusion and convective velocity fields},
	howpublished = {International congress on industrial and applied mathematics, Valencia, Spain},
	year = {2019},
	publisher = {ICIAM},
	author = {Vinje, Vegard and Croci, Matteo and Marie E. {Rognes}}
}
@article {paper28,
	title = {Uncertainty quantification of parenchymal tracer distribution using random diffusion and convective velocity fields},
	journal = {Fluids and Barriers of the Central Nervous System},
	volume = {16},
	number = {1},
	year = {2019},
	month = {09/2019},
	pages = {32},
	publisher = {BMC},
	doi = {10.1186/s12987-019-0152-7},
	url = {https://europepmc.org/articles/pmc6767654},
	author = {Croci, Matteo and Vinje, Vegard and Marie E. {Rognes}}
}
@misc {paper39,
	title = {UQ of parenchymal tracer distribution using random diffusion and convective velocity fields},
	howpublished = {5th biennial CSF Dynamics Symposium, Oslo, Norway},
	year = {2019},
	author = {Marie E. {Rognes}}
}
@article {25856,
	title = {Efficient white noise sampling and coupling for multilevel Monte Carlo with non-nested meshes},
	journal = {SIAM Journal on Uncertainty Quantification},
	volume = {6},
	year = {2018},
	publisher = {SIAM},
	author = {Croci, Matteo and Michael B. {Giles} and Marie E. {Rognes} and Patrick E. {Farrell}}
}
@misc {26014,
	title = {Fluid dynamics in syringomyelia cavities},
	howpublished = {Vancouver, Canada},
	year = {2018},
	type = {Parallel paper session at the 56th annual meeting of the American Society of Neuroradiology},
	author = {Vinje, Vegard and Brucker, Justin and Marie E. {Rognes} and Mardal, Kent-Andre and Haughton, Victor}
}
@article {26045,
	title = {Fluid dynamics in syringomyelia cavities: Effects of heart rate, CSF velocity, CSF velocity waveform and craniovertebral decompression},
	journal = {The Neuroradiology Journal},
	volume = {31},
	year = {2018},
	month = {09/2018},
	pages = {482-489},
	publisher = { SAGE Publications},
	abstract = {Purpose: How fluid moves during the cardiac cycle within a syrinx may affect its development. We measured syrinx fluid velocities before and after craniovertebral decompression in a patient and simulated syrinx fluid velocities for different heart rates, syrinx sizes and CSF flow velocities in a model of syringomyelia.Materials and Methods: With Phase Contrast MR we measured CSF and syrinx fluid velocities in a Chiari patient before and after craniovertebral decompression. With an idealized 2D model of the subarachnoid space (SAS), cord and syrinx, we simulated fluid movement in the SAS and syrinx with the Navier-Stokes equations for different heart rates, inlet velocities and syrinx diameters.Results: In the patient, fluid oscillated in the syrinx at 200 to 210 cycles per minute before and after craniovertebral decompression. Velocities peaked at 3.6 and 2.0 cm/sec respectively in the SAS and the syrinx before surgery and at 2.7 and 1.5 cm/sec after surgery. In the model, syrinx velocity varied between 0.91 and 12.70 cm/sec. Increasing CSF inlet velocities from 1.56 to 4.69 cm/sec increased peak syrinx fluid velocities in the syrinx by 151 to 299\% for the three cycle rates. Increasing cycle rates from 60 to 120 cpm, increased peak syrinx velocities by 160 to 312\% for the three inlet velocities. Peak velocities changed inconsistently with syrinx size.Conclusions: CSF velocity, heart rate and syrinx diameter affect syrinx fluid velocities, but not the frequency of syrinx fluid oscillation. Craniovertebral decompression decreases both CSF and syrinx fluid velocities.},
	url = {http://journals.sagepub.com/doi/10.1177/1971400918795482},
	author = {Vinje, Vegard and Brucker, Justin and Marie E. {Rognes} and Mardal, Kent-Andre and Haughton, Victor}
}
@article {25968,
	title = {In vivo estimation of elastic heterogeneity in an infarcted human heart},
	journal = {Biomechanics and Modeling in Mechanobiology},
	volume = {17},
	year = {2018},
	month = {May-05-2019},
	pages = {1317{\textendash}1329},
	publisher = {Springer},
	address = {Berlin Heidelberg},
	abstract = {In myocardial infarction, muscle tissue of the heart is damaged as a result of ceased or severely impaired blood flow. Survivors have an increased risk of further complications, possibly leading to heart failure. Material properties play an important role in determining post-infarction outcome. Due to spatial variation in scarring, material properties can be expected to vary throughout the tissue of a heart after an infarction. In this study we propose a data assimilation technique that can efficiently estimate heterogeneous elastic material properties in a personalized model of cardiac mechanics. The proposed data assimilation is tested on a clinical dataset consisting of regional left ventricular strains and in vivo pressures during atrial systole from a human with a myocardial infarction. Good matches to regional strains are obtained, and simulated equi-biaxial tests are carried out to demonstrate regional heterogeneities in stress{\textendash}strain relationships. A synthetic data test shows a good match of estimated versus ground truth material parameter fields in the presence of no to low levels of noise. This study is the first to apply adjoint-based data assimilation to the important problem of estimating cardiac elastic heterogeneities in 3-D from medical images.},
	issn = {1617-7959},
	doi = {10.1007/s10237-018-1028-5},
	url = {http://link.springer.com/10.1007/s10237-018-1028-5},
	author = {Balaban, Gabriel and Finsberg, Henrik and Simon W {Funke} and Trine F. {H{\r a}land} and Hopp, Einar and Sundnes, Joakim and Wall, Samuel and Marie E. {Rognes}}
}
@misc {26016,
	title = {The Influence of Breathing on Cerebrospinal Fluid Movement in the Brain},
	howpublished = {Glasgow, United Kingdom},
	year = {2018},
	type = {Minisymposium at the ECCOMAS: ECCM - ECFD conference},
	author = {Vinje, Vegard and Geir Andre {Ringstad} and Marie E. {Rognes} and Per Kristian {Eide} and Mardal, Kent-Andre}
}
@misc {26051,
	title = {Mixed-dimensional coupled finite elements in FEniCS},
	howpublished = {FEniCS18, Oxford, UK},
	year = {2018},
	note = {Best postdoctoral presentation award at the FEniCS{\textquoteright}18},
	author = {Daversin-Catty, C{\'e}cile and Marie E. {Rognes}}
}
@misc {27010,
	title = {Mixed-dimensional coupled finite elements in FEniCS},
	howpublished = {ECCM-ECFD 2018, Glasgow (UK)},
	year = {2018},
	author = {Daversin-Catty, C{\'e}cile and Marie E. {Rognes}}
}
@misc {27013,
	title = {Mixed-dimensional modeling of the brain{\textquoteright}s waterscape},
	year = {2018},
	address = {InterPore 2018, New-Orleans (USA)},
	author = {Daversin-Catty, C{\'e}cile and Marie E. {Rognes}}
}
@misc {25819,
	title = {Mixed-dimensional modeling of the brain{\textquoteright}s waterscape},
	howpublished = {Workshop on solvers for materials with high-aspect-ratio inclusions, Finse, Norway},
	year = {2018},
	author = {Daversin-Catty, C{\'e}cile and Marie E. {Rognes}}
}
@misc {27007,
	title = {Mixed-dimensional models of the brain{\textquoteright}s waterscape with FEniCS},
	howpublished = {InterPore 2018, New-Orleans (USA)},
	year = {2018},
	author = {Daversin-Catty, C{\'e}cile and Marie E. {Rognes}}
}
@misc {26144,
	title = {Parameter-robust discretization and preconditioning of multiple-network poroelasticity equations},
	howpublished = {Glasgow, UK},
	year = {2018},
	author = {Piersanti, Eleonora and Jeonghun J. {Lee} and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@misc {26143,
	title = {Parameter-robust discretization and preconditioning of multiple-network poroelasticity equations},
	howpublished = {University of Oxford, UK},
	year = {2018},
	author = {Piersanti, Eleonora and Jeonghun J. {Lee} and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@mastersthesis {26142,
	title = {A posteriori error estimation for multiple-network poroelasticity},
	journal = {The University of Oslo},
	year = {2018},
	month = {08/2018},
	publisher = {The University of Oslo},
	address = {Oslo, Norway},
	abstract = {The multiple network poroelasticity equations (MPET) describe mechanical deformation and fluid flow in porous media and can be used to understand various biological processes in a physiological setting.\&nbsp; Modeling transportation of fluid within the brain is essential to discover the underlying mechanisms that are currently being investigated concerning various neurodegenerative diseases such as Alzheimer{\textquoteright}s disease.\&nbsp; Mathematical modeling is considered to be more accessible and less expensive than performing advanced medical tests and experiments; however, numerical simulations are still prone to error, making it essential to control and minimize.\&nbsp; Physiological frameworks often include complex geometries which may produce complex error distributions.\&nbsp; A posterior error estimation presents a framework to measure and control the error in specific regions of the computational domain.\&nbsp; This thesis presents the derivation of a posteriori error estimates for MPET with two interacting fluid networks, extending the analysis from on fluid network.\&nbsp; The presented estimates can be extended to the MPET model with an arbitrary number of networks, which is demonstrated with a computational experiment using four networks on a brain mesh with physiologically inspired parameters.},
	keywords = {a posteriori error estimates, generalized poroelasticity, MPET},
	author = {{\O}degaard, Emilie},
	editor = {Marie E. {Rognes}}
}
@misc {26046,
	title = {Respiratory influence on intracranial pressure gradients and aqueductal flow in normal pressure hydrocephalus},
	year = {2018},
	month = {07/2018},
	type = {Poster Presentation at World Congress of Biomechanics},
	address = {Dublin, Ireland},
	abstract = {Phase contrast MRI does not take into account the role of respiration on cerebrospinal fluid (CSF) flow. We used in vivo pressure measurements from two locations in the intracranial space to calculate a pulsatile pressure gradient. This pressure data was used as input to an idealized model of the aqueduct to calculate CSF flow. We found the cardiac and respiratory cycle to contribute equally to CSF flow. The total flow volume was dominated by respiration, and all subjects showed variability in pressure gradients over time resulting also in variability in CSF flow.},
	url = {https://app.oxfordabstracts.com/stages/123/programme-builder/submission/20200?backHref=/events/123/programme-builder/view/sort/topic\&view=published},
	author = {Vinje, Vegard and Ringstad, Geir and Marie E. {Rognes} and Per Kristian {Eide} and Mardal, Kent-Andre}
}
@misc {26138,
	title = {A Robust 3-Field formulation for Generalized Poroelasticity},
	howpublished = {FEniCS 18, Oxford, United Kingdom},
	year = {2018},
	author = {Thompson, Travis and Marie E. {Rognes}}
}
@misc {25823,
	title = {A robust mixed finite element method for generalized poroelasticity},
	howpublished = {Glasgow, UK},
	year = {2018},
	type = {Technical Talk: Numerical Analysis, Scientific Computing},
	abstract = {The classical Biot and Terzaghi soil models, describing flow through a\&nbsp;single fluid network in a porous and elastic medium, were generalized\&nbsp;to equations describing multiple fluid network poroelasticity (MPET)\&nbsp;by Barenblatt and Aifantis.\&nbsp; The MPET equations have been utilized in\&nbsp;geomechanics to simulate multiple fractured strata for a few decades,\&nbsp;but are now also beginning to find their application in\&nbsp;biomechanics. Indeed, the multiple network poroelasticity theory aptly\&nbsp;models the multiple fluid networks encountered in e.g.\&nbsp;the brain: such\&nbsp;as extracellular spaces, vasculature and\&nbsp;paravasculature.\&nbsp;\&nbsp;\&nbsp;In this talk, we propose a new mixed finite element formulation for the multiple-network poroelasticity equations.\&nbsp;The key idea is to introduce the network fluid fluxes as additional variable\&nbsp;targeting a finite element formulation that is robust with respect to\&nbsp;low hydraulic conductivities\&nbsp;and storage coefficients. We will present both theoretical and numerical results regarding\&nbsp;the\&nbsp;robustness and convergence of the new method, together with numerical\&nbsp;demonstrations relating to the topic of cerebral interstitial andparavascular fluid flow.},
	keywords = {brain mechanics, mixed finite element methods, multiple-network poroelasticity},
	author = {Marie E. {Rognes} and Thompson, Travis}
}
@misc {26772,
	title = {Stokes Biot Stability and a Mixed Formulation for Generalized Poroelasticity},
	howpublished = {Lorentz Center, Leiden, Netherlands},
	year = {2018},
	author = {Marie E. {Rognes} and Thompson, Travis}
}
@misc {26770,
	title = {Stokes-Biot Stability and a Mixed Formulation For Generalized Poroelasticity},
	howpublished = {SIAM Life Sciences. Minneapolis, Minnesota},
	year = {2018},
	author = {Marie E. {Rognes} and Thompson, Travis}
}
@misc {26137,
	title = {Stokes-Biot stability and a mixed formulation for generalized proelasticity},
	year = {2018},
	month = {05/2018},
	type = {Workshop poster presentation},
	address = {Lorentz Center, Leiden, Netherlands},
	author = {Thompson, Travis and Marie E. {Rognes}}
}
@misc {26771,
	title = {A Stokes-Biot Stable Hdiv-Based Mixed Method for Generalized Poroelasticity{\textquoteright}},
	howpublished = {ECCM-ECFD. Glasgow, United Kingdom},
	year = {2018},
	author = {Marie E. {Rognes} and Thompson, Travis}
}
@misc {26139,
	title = {A Stokes-Biot Stable H(div)-based mixed method for generalized poroelasticity},
	howpublished = {SIAM Life Sciences 2018, Minneapolis, Minnesota, USA},
	year = {2018},
	author = {Thompson, Travis and Marie E. {Rognes}},
	editor = {Mardal, Kent-Andre}
}
@misc {26769,
	title = {Waterscape of the Brain: Mathematics and Scientific Computing Enabling Clinical Simulation},
	howpublished = {Simula Research Conference, Son, Norway},
	year = {2018},
	author = {Marie E. {Rognes} and Thompson, Travis and Daversin-Catty, C{\'e}cile}
}
@misc {25487,
	title = {Accurate numerical modelling of small collections of cardiac cells},
	howpublished = {FEniCS{\textquoteright}17, Luxembourg City, Luxembourg},
	year = {2017},
	author = {Marie E. {Rognes}}
}
@misc {25706,
	title = {The Brain as a Poroelastic Medium - Simulating pulsatile motion and flow},
	howpublished = {Hamburg, Germany},
	year = {2017},
	abstract = {This talk presents a general overview of the numerical work at the Waterscape group at Simula. First, I present the governing equations, together with standard solving schemes and how to handle discretization in FEniCS. The total pressure formulation is introduced, and an optimal preconditioner for the total pressure formulation is presented.In the last five-ten years, fluid flow and solute transport in the human brain has gained rapid interest in the research community. The discoveries by Iliff and Nedergaard describing a glyphatic network washing solutes out of the brain through a bulk flow of fluid, followed by Xie et al.{\textquoteright}s study claiming that sleep enhances this mechanism was discoveries that also gained significant media attention.The brain has several more or less separated networks allowing for fluid flow; Blood vessels, paravascular spaces and interstitial fluid. The relation between fluid flow in these networks to each other and to the macroscoping displacement of brain tissue can be explained with the multiple network poroelastic theory (MPET). Because there are no consensus of the value of all material parameters the models we use need to be robust within a given parameter regime. In addition, as the number of networks grow, the system of equations becomes larger and the solvers we use must also be fast and efficient within the given range of the parameters.The total pressure formulation, presented in this talk, restores convergence related to the problem of "locking", and allows for a parameter robust preconditioner. Proof that the scheme is stable has been given earlier, and the current work aims to extend this proof to a general number of networks.},
	keywords = {Brain, Poroelasticity, Porous media, Total pressure, Waterscape},
	author = {Vinje, Vegard and Marie E. {Rognes} and Mardal, Kent-Andre and Piersanti, Eleonora}
}
@article {25249,
	title = {cbcbeat: an adjoint-enabled framework for computational cardiac electrophysiology},
	journal = {Journal of Open Source Software},
	volume = {2},
	year = {2017},
	month = {06/2017},
	publisher = {The Journal of Open Source Software, Open Source Initiative},
	doi = {10.21105/joss.00224},
	url = {http://dx.doi.org/10.21105/joss.00224},
	author = {Marie E. {Rognes} and Patrick Emmet {Farrell} and Simon W {Funke} and Johan Elon {Hake} and Maleckar, Molly}
}
@article {25486,
	title = {A cell-based framework for numerical modelling of electrical conduction in cardiac tissue},
	journal = {Frontiers in Physics, Computational Physics},
	volume = {5},
	year = {2017},
	month = {10/2017},
	publisher = {Frontiers},
	doi = {https://doi.org/10.3389/fphy.2017.00048},
	url = {https://www.frontiersin.org/articles/10.3389/fphy.2017.00048/full?\&utm_source=Email_to_authors_\&utm_medium=Email\&utm_content=T1_11.5e1_author\&utm_campaign=Email_publication\&field=\&journalName=Frontiers_in_Physics\&id=289187},
	author = {Tveito, Aslak and Karoline Horgmo {J{\ae}ger} and Kuchta, Miroslav and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@misc {25587,
	title = {Compatible discretizations in our hearts and minds},
	howpublished = {ENUMATH, Voss, Norway},
	year = {2017},
	author = {Marie E. {Rognes}}
}
@misc {25206,
	title = {FEniCS: Sustainable Software Development Practices},
	year = {2017},
	month = {03/2017},
	address = {SIAM CSE17 PP108 Minisymposterium: Software Productivity and Sustainability for CSE and Data Science},
	abstract = {The FEniCS project aims to provide a high productivity environment for development of finite element based simulation software. Techniques applied to achieve this goal include mixed language programming and code generation, which enables writing high performance programs in a high level language. End-user productivity is a high priority goal in our software designs. To sustain the productivity of the multinational team of part-time developers (mainly researchers and students) is paramount to the long term survival of the project. To minimize the developer workload while making the process open and accessible to new contributors and users, we regularly question which tools are the best available for our needs. On this poster we will present our current tool choices and work flows for developers and the wider FEniCS community. This list includes version control, build systems, testing, release management, team communication, documentation, and end user support. The most recent addition to our toolbox are developer curated Docker images. We are investigating their usefulness in testing infrastructure, end user deployment, HPC cluster deployment, and as reproducible software environments to accompany journal publications. We welcome discussion on alternatives that can simplify our lives.},
	keywords = {FEniCS, Poster, Sofware Development},
	doi = {10.6084/m9.figshare.4696318.v1},
	author = {Martin Sandve {Aln{\ae}s} and Blechta, Jan and Jack S. {Hale} and Logg, Anders and Richardson, Chris and Ring, Johannes and Marie E. {Rognes} and Garth N. {Wells}}
}
@article {24721,
	title = {High resolution data assimilation of cardiac mechanics},
	journal = {International journal for numerical methods in biomedical engineering},
	volume = {33},
	number = {11},
	year = {2017},
	month = {04/2017},
	pages = {e2863},
	publisher = {John Wiley \& Sons, Ltd},
	doi = {10.1002/cnm.2863},
	author = {Balaban, Gabriel and Finsberg, Henrik and Hans Henrik {Odland} and Marie E. {Rognes} and Ross, Stian and Sundnes, Joakim and Wall, Samuel}
}
@misc {25108,
	title = {Impact of high abstraction/high performance finite element software in biomedical computing},
	howpublished = {24th International Conference on Domain Decomposition Methods, Svalbard, Norway},
	year = {2017},
	abstract = {The development of numerical software in general and finite elementsoftware in particular is recognized as a challenging and error-proneprocess -- traditionally requiring in-depth expertise from a number ofscientific fields. The FEniCS and Dolfin-adjoint projects target thischallenge by developing generic algorithms and open source softwarefor the automated solution of partial differential equations usingfinite element methods. The FEniCS Project is described by in theFEniCS book [1] and a number of research papers, see e.g. [2].The related Dolfin-adjoint software, winner of the 2015 WilkinsonPrize for Numerical Software, automatically derives discrete adjointand tangent linear models from a forward FEniCS model[3]. Theseadjoint and tangent linear models are key ingredients in manyimportant algorithms, such as data assimilation, optimal control,sensitivity analysis, design optimisation, and error estimation.In this presentation, I{\textquoteright}ll give an overview of the FEniCS andDolfin-adjoint projects focusing on current developments andapplications in biomedical computing.[1] A. Logg, K.-A. Mardal, G. N. Wells et al. (2012). AutomatedSolution of Differential Equations by the Finite Element Method,Springer. [doi:10.1007/978-3-642-23099-8][2] M. S. Aln{\ae}s, J. Blechta, J. Hake, A. Johansson, B. Kehlet,A. Logg, C. Richardson, J. Ring, M. E. Rognes and G. N. Wells(2015). The FEniCS Project Version 1.5, Archive of Numerical Software,3(100), [doi:10.11588/ans.2015.100.20553].[3] P. E. Farrell, D. A. Ham, S. W. Funke and M. E. Rognes(2013). Automated derivation of the adjoint of high-level transientfinite element programs, SIAM Journal on Scientific Computing 35.4,pp. C369-C393. doi:10.1137/120873558.\&nbsp;},
	author = {Marie E. {Rognes}}
}
@article {25388,
	title = {Inverse estimation of cardiac activation times via gradient-based optimization},
	journal = {International Journal for Numerical Methods in Biomedical Engineering},
	volume = {34},
	year = {2017},
	month = {08/2017},
	pages = {e2919},
	publisher = {John Wiley \& Sons},
	doi = {10.1002/cnm.2919},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/cnm.2919/abstract},
	author = {Kallhovd, Siri and Maleckar, Molly and Marie E. {Rognes}}
}
@misc {25589,
	title = {Making models of your brain{\textquoteright}s waterscape},
	year = {2017},
	publisher = {2017 Cutting Edge Festival},
	author = {Marie E. {Rognes}}
}
@misc {25488,
	title = {Mathematics that cures us},
	year = {2017},
	publisher = {TEDxOslo 2017},
	address = {Oslo},
	author = {Marie E. {Rognes}}
}
@misc {25391,
	title = {Modelling pulsatility in the context of Normal-Pressure Hydrocephalus via multiple-network poroelasticity},
	howpublished = {5th International Conference on Computational and Mathematical Biomedical Engineering, Pittsburgh, US},
	year = {2017},
	author = {Piersanti, Eleonora and Jeunghun J. {Lee} and Mardal, Kent-Andre and Marie E. {Rognes}}
}
@article {24720,
	title = {Numerical study of intrathecal drug delivery to a permeable spinal cord: effect of catheter position and angle},
	journal = {Computer Methods in Biomechanics and Biomedical Engineering},
	volume = {20},
	year = {2017},
	pages = {1599-1608},
	publisher = {Taylor \& Francis Online},
	doi = {10.1080/10255842.2017.1393805},
	author = {Pizzichelli, Giulia and Kehlet, Benjamin and Evju, {\O}yvind and Martin, Bryn and Marie E. {Rognes} and Mardal, Kent-Andre and Sinibaldi, Edoardo}
}
@misc {25753,
	title = {The numerical waterscape of the brain},
	howpublished = {Universit{\'e} libre du Bruxelles, Bruxelles, Belgium},
	year = {2017},
	author = {Marie E. {Rognes}}
}
@misc {25588,
	title = {The numerical waterscape of the brain},
	howpublished = {Workshop on Biomechanics of living systems, from cells to organisms, Oslo, Norway},
	year = {2017},
	author = {Marie E. {Rognes}}
}
@misc {25754,
	title = {The numerical waterscape of the brain},
	howpublished = {2nd Workshop on computational aspects of perfusion and flow in live tissue, Bergen, Norway},
	year = {2017},
	author = {Marie E. {Rognes}}
}
@misc {25390,
	title = {The PDEs of our hearts and minds},
	howpublished = {Women in PDEs, Karlsruhe, Germany},
	year = {2017},
	month = {04/2017},
	author = {Marie E. {Rognes}}
}
@misc {25579,
	title = {Is Respiration the main driver of CSF Flow?},
	howpublished = {International Convention Center, Kobe, Japan},
	year = {2017},
	type = {Seminar, Annual Meeting (IHIWG group)},
	abstract = {Recent studies using magnetic resonance imaging (MRI) have suggested cerebrospinal fluid (CSF) motion caused by respiration to play a more important role than previously thought. The cardiac cycle of CSF motion is used clinically, often to predict which hydrocephalus patients will respond to shunting and who will not.This talk asks the question whether CSF flow could also be regulated by the longer respiratory cycle. To assess this question we applied in vivo pressure measurements to a simplification of the spinal canal and the aqueduct. From this we can measure the amplitude of the flow components induced by the cardiac and respiratory cycle respectively.In our study the amplitude of CSF motion was higher for respiration in the spinal canal, and in the aqueduct cardiac the two amplitudes were approximately equal.This is a starting work, so no conclusions can be made yet. We emphasize the point that it is possible for small and long pressure waves in respiration to cause greater flow than a short cardiac pressure wave with a greater amplitude.\&nbsp;},
	keywords = {Brain, Cerebrospinal Fluid, Computational Fluid Dynamics, Pulsation, Respiration, Spinal Cord},
	author = {Vinje, Vegard},
	editor = {Per Kristian {Eide} and Marie E. {Rognes} and Mardal, Kent-Andre}
}
@misc {25818,
	title = {Towards coupled mixed dimensional finite elements in FEniCS},
	howpublished = {FEniCS17 conference, University of Luxembourg, Luxembourg},
	year = {2017},
	author = {Daversin-Catty, C{\'e}cile and Marie E. {Rognes}}
}
@misc {24723,
	title = {A 2-day training course in FEniCS and dolfin-adjoint},
	howpublished = {NGCM Summer Academy, University of Southampton},
	year = {2016},
	author = {Marie E. {Rognes}}
}
@misc {24827,
	title = {On accurate and efficient simulations of multiple-network poroelastic modelling with applications to interstitial fluid flow in the human brain},
	howpublished = {WCCM XII \& APCOM VI, Seoul },
	year = {2016},
	keywords = {Numerical Simulations, Poroelasticity, Preconditioner},
	author = {Jeonghun John {Lee} and Mardal, Kent-Andre and Piersanti, Eleonora and Marie E. {Rognes}}
}
@article {24028,
	title = {Adjoint Multi-Start Based Estimation of Cardiac Hyperelastic Material Parameters using Shear Data},
	journal = {Biomechanics and Modeling in Mechanobiology},
	year = {2016},
	month = {23.03.2013},
	pages = {1-13},
	publisher = {Springer},
	author = {Balaban, Gabriel and Martin Sandve {Aln{\ae}s} and Sundnes, Joakim and Marie E. {Rognes}}
}
@misc {24829,
	title = {Developing simulation technology to solve biomedical problems: analysis, implementation and applications },
	howpublished = {University of Uppsala},
	year = {2016},
	author = {Marie E. {Rognes} and Piersanti, Eleonora and Massing, Andre}
}
@misc {24765,
	title = {The FEniCS and dolfin-adjoint projects},
	howpublished = {Higher-order DG methods and finite element software for modern architectures, University of Bath, UK},
	year = {2016},
	author = {Marie E. {Rognes}}
}
@misc {24722,
	title = {The FEniCS and Dolfin-adjoint Projects},
	howpublished = {NGCM Summer Academy, University of Southampton},
	year = {2016},
	author = {Marie E. {Rognes}}
}
@misc {24930,
	title = {High-level abstractions, algorithms and applications in forward and inverse finite element solution of PDEs},
	howpublished = {Nordic Seminar on Computational Mechanics, Chalmers University of Technology, Sweden},
	year = {2016},
	author = {Marie E. {Rognes}}
}
@misc {24826,
	title = {Modelling and simulation of viscous and poroelastic fluid flow in the brain},
	howpublished = {FEniCS16, Simula Research Laboratory},
	year = {2016},
	keywords = {Finite elements, Numerical Simulations, Poroelasticity},
	author = {Jeonghun John {Lee} and Mardal, Kent-Andre and Piersanti, Eleonora and Marie E. {Rognes}}
}
@misc {24476,
	title = {The Numerical Waterscape of the Brain},
	howpublished = {Norway-Russia workshop on Biot{\textquoteright}s equations and error estimation, Voss, Norway},
	year = {2016},
	month = {09/03/2016},
	type = {Invited },
	author = {Marie E. {Rognes}}
}
@inproceedings {24567,
	title = {Optimization of a Spatially Varying Cardiac Contraction parameter using the Adjoint Method},
	journal = {FEniCS{\textquoteright}16},
	year = {2016},
	abstract = {A cardiac computational model is constrained using clinical measurements such as pressure, volume and regional strain. The problem is formulated as a PDE-constrained optimisation problem where the objective functional represents the misfit between measured and simulated data. The control parameter for the active phase is a spatially varying contraction parameter defined at every vertex in the mesh. This makes gradient calculations using the adjoint approach computationally advantageous over standard finite difference approximations.},
	keywords = {Adjoint Method, Cardiac Mechanics, parameter estimation, PDE-constrained optimization},
	author = {Finsberg, Henrik and Balaban, Gabriel and Marie E. {Rognes} and Sundnes, Joakim and Wall, Samuel}
}
@misc {24417,
	title = {Patient Specific Modeling of Cardiac Mechanics using the Active Strain Formulation},
	howpublished = {Geilo Winter School},
	year = {2016},
	author = {Finsberg, Henrik and Balaban, Gabriel and Wall, Samuel and Sundnes, Joakim and Marie E. {Rognes}}
}
@inproceedings {24991,
	title = {Personalized Cardiac Mechanical Model using a High Resolution Contraction Field},
	journal = {VPH16 Translating VPH to the Clinic},
	year = {2016},
	author = {Finsberg, Henrik and Balaban, Gabriel and Sundnes, Joakim and Marie E. {Rognes} and Hans Henrik {Odland} and Ross, Stian and Wall, Samuel}
}
@misc {24901,
	title = {Simulating Cerebrospinal Fluid Flow and Spinal Cord Movement Associated with Syringomyelia},
	howpublished = {Chalmers Institute of Technology},
	year = {2016},
	publisher = {Chalmers Publication Library},
	address = {Website},
	abstract = {In this study, we tested the hypothesis that fluid velocities within syringes in the spinal cord related to syringomyelia can be explained by fluid-structure interaction (FSI), and that spinal cord movements alter cerebrospinal fluid (CSF) dynamics in the subarachnoid space (SAS). We formulate the coupled fluid-structure interaction problem with an Arbitrary-Lagrangian-Eulerian formulation based on Eulerian coordinates in a moving domain. Our implementation is based on the FEniCS software. The model is then used to investigate FSI effects of syringomyelia in idealized geometries of the spinal cord and SAS.Our results indicate that FSI in a model of a healthy subject yields results quantitatively and qualitatively similar to computational fluid dynamics. In contrast, in the presence of a syrinx, FSI predicts greater displacements of the cord, and a nonlinear pressure distribution is introduced in the CSF along the cord. With a sinusoidally pulsating flow of CSF in the SAS, an opposing sinusoidal flow is seen within the syrinx. With CSF pulsation closer to the natural environment in the SAS, higher frequencies of oscillatory fluid flow are observed within the syrinx.},
	keywords = {Finite elements},
	url = {http://publications.lib.chalmers.se/publication/244480-proceedings-of-29th-nordic-seminar-on-computational-mechanics-nscm29},
	author = {Vinje, Vegard and Mardal, Kent-Andre and Haughton, Victor and Marie E. {Rognes}}
}
@misc {24932,
	title = {Time scales of mathematics: from basic research to societal application},
	howpublished = {RCN Workshop on the Importance of Mathematics for Value Creation, Lysaker, Norway},
	year = {2016},
	author = {Marie E. {Rognes}}
}
@misc {24931,
	title = {Waterscales: mathematical and computational foundations for modelling cerebral fluid flow},
	howpublished = {OBCE-Simula Workshop, Simula Research Laboratory, Norway},
	year = {2016},
	author = {Marie E. {Rognes}}
}
@misc {24828,
	title = {The waterscape of the brain},
	year = {2016},
	month = {09/2016},
	keywords = {Neuroscience, Numerical Simulations, Waterscape},
	author = {Piersanti, Eleonora and Marie E. {Rognes}}
}
@misc {23549,
	title = {A 2-day training course in FEniCS and dolfin-adjoint},
	howpublished = {NGCM Summer Academy, University of Southampton},
	year = {2015},
	type = {Invited},
	author = {Marie E. {Rognes}}
}
@misc {23346,
	title = {Biomedical Computing at Simula Research Laboratory},
	howpublished = {UNICAT Kick-off meeting, Porto, Portugal (Invited)},
	year = {2015},
	month = {01/2015},
	author = {Marie E. {Rognes}}
}
@misc {24607,
	title = {Dolfin-adjoint, automated adjoint models for FEniCS},
	year = {2015},
	note = {Winner of the Best Poster Award},
	publisher = {SIAM Conference on Computational Science and Engineering},
	address = {Salt Lake City, USA},
	author = {Simon W {Funke} and Patrick Emmet {Farrell} and Ham, D.A. and Marie E. {Rognes}}
}
@misc {23582,
	title = {Dolfin-adjoint: Automatic adjoint models for FEniCS},
	howpublished = {The 8th International Congress on Industrial and Applied Mathematics},
	year = {2015},
	publisher = {The 8th International Congress on Industrial and Applied Mathematics},
	address = {Beijing, China},
	abstract = {Adjoint and tangent linear models form the basis of many numerical techniques, including sensitivityanalysis, optimization and stability analysis. The implementation of adjoint models for nonlinear or time-dependent models are notoriously challenging: the manual approach is time-consuming and traditionalautomatic differentiation tools lack robustness and performance.dolfin-adjoint solves this problem by automatically analyzing the high-level mathematical structureinherent in finite element methods. It raises the traditional abstraction of algorithmic differentiationfrom the level of individual floating point operations to that of whole systems of differential equations.This approach delivers a number of advantages over the previous state-of-the-art: robust hands-offautomation of adjoint model derivation, optimal computational efficiency, and native parallel support.},
	author = {Simon W {Funke} and Patrick Emmet {Farrell} and David A. {Ham} and Marie E. {Rognes}}
}
@misc {23855,
	title = {Dyssynchronous Left Ventricular Stress Estimation},
	howpublished = {Workshop on Advanced Numerical Techniques in Biomedical Computing: Simula Research Laboratory},
	year = {2015},
	abstract = {The heart is a muscular pump that moves approximatly 8,000 litres per day through the human body. It manages to this by a combination of contraction/relaxation along muscle fibers and elastic recoil. These two effects are indistinguishable in a medical image, but can be estimated using a computational model.In our work we use adjoint based optimization techniques in order to determine muscle contraction and elastic recoil in a patient specific left ventricular geometry based on echocardiography and pressure catheter data. Possible applications of the technique include mechanical stress estimation and hypothesis testing in cardiac resynchronization therapy research.},
	author = {Balaban, Gabriel},
	editor = {Finsberg, Henrik and Marie E. {Rognes} and Sundnes, Joakim and Wall, Samuel and Hans Henrik {Odland} and Ross, Stian}
}
@misc {23345,
	title = {Effect of Spinal Cord Viscoelasticity on Its Response to CSF Pressure Waves: a Computational Study},
	howpublished = {ASNR 53rd Annual Meeting \& The Foundation of the ASNR Symposium 2015, April 25 {\textendash} 30, Chicago, Illinois},
	year = {2015},
	author = {Kylstad, Nina and Mardal, Kent-Andre and Haughton, Victor and Marie E. {Rognes}}
}
@misc {23550,
	title = {The FEniCS and Dolfin-adjoint Projects},
	howpublished = {NGCM Summer Academy, University of Southampton},
	year = {2015},
	type = {Invited},
	author = {Marie E. {Rognes}}
}
@article {23578,
	title = {The FEniCS Project Version 1.5},
	journal = {Archive of Numerical Software},
	volume = {3},
	year = {2015},
	month = {12/2015},
	publisher = {Open Journal Systems, sponsored by the University of Heidelberg},
	author = {Martin Sandve {Aln{\ae}s} and Blechta, Jan and Johan Elon {Hake} and Johansson, August and Kehlet, Benjamin and Logg, Anders and Richardson, Chris and Ring, Johannes and Marie E. {Rognes} and Garth N. {Wells}}
}
@misc {23581,
	title = {Identifying the Parameters of the Heart: Variational Data Assimilation in Cardiac Mechanics Using Dolfin-Adjoint},
	howpublished = {FEniCS {\textquoteright}15, Imperial College London, UK},
	year = {2015},
	type = {Featured presentation},
	author = {Marie E. {Rognes} and Balaban, Gabriel and Sundnes, Joakim and Martin Sandve {Aln{\ae}s}}
}
@misc {23543,
	title = {Introduction to dolfin-adjoint and its applications in cardiac electrophysiology},
	howpublished = {2015 Summer School in Computational Physiology: Models, Tools, and Techniques for Cardiac Applications},
	year = {2015},
	author = {Marie E. {Rognes}}
}
@misc {24425,
	title = {New simulation technology driven by medical challenges: the Biomedical Computing Department @ Simula},
	howpublished = {Oslo, Simula Research Laboratory},
	year = {2015},
	month = {11/02/2015},
	author = {Marie E. {Rognes}}
}
@article {Simula.simula.2926,
	title = {A Nitsche-based Cut Finite Element Method for a Fluid-Structure Interaction Problem},
	journal = {Communications in Applied Mathematics and Computational Science},
	volume = {10},
	number = {2},
	year = {2015},
	pages = {97-120},
	publisher = {Mathematical Sciences Publishers},
	doi = {10.2140/camcos.2015.10.97},
	author = {Massing, Andre and Mats G. {Larson} and Logg, Anders and Marie E. {Rognes}}
}
@misc {23580,
	title = {Non-Manifold Manifold Simulations Using FEniCS},
	howpublished = {FEniCS {\textquoteright}15, Imperial College London, UK},
	year = {2015},
	author = {Bernstein, David and Marie E. {Rognes}}
}
@inproceedings {23720,
	title = {Personalization of a Cardiac Compuational Model using Clinical Measurements},
	journal = {28th Nordic Seminar on Computational Mechanics},
	volume = {28},
	year = {2015},
	month = {10/2015},
	pages = {47-50},
	publisher = {Proceedings of NSCM-28},
	address = {Tallin, Estonia},
	abstract = {Important features in cardiac mechanics that cannot easily be measured in the clinic, can be computed using a computational model that is calibrated to behave in the same way as a patient{\textquoteright}s heart. To construct such a model, clinical measurements such as strain, volume and cavity pressure are used to personalize the mechanics of a cardiac computational model. The problem is formulated as a PDE-constrained optimization problem where the minimization functional represents the misfit between the measured and simulated data. The target parameters are material parameters and a spatially varying contraction parameter. The minimization is carried out using a gradient based optimization algorithm and an automatically derived adjoint equation. The method has been tested on synthetic data, and is able to reproduce a prescribed contraction pattern on the left ventricle.},
	author = {Finsberg, Henrik and Balaban, Gabriel and Sundnes, Joakim and Marie E. {Rognes} and Wall, Samuel}
}
@misc {23579,
	title = {Towards a Unified Framework for Automated a Posteriori Error Estimation and Adaptivity in Space-Time},
	howpublished = {SIAM CSE, Salt Lake City, USA},
	year = {2015},
	type = {Invited},
	author = {Marie E. {Rognes} and Kehlet, Benjamin and Logg, Anders and Martin Sandve {Aln{\ae}s}}
}
@misc {23337,
	title = {Adaptive Finite Elements: Practice and Implementation},
	howpublished = {Centre for Mathematics for Applications, University of Oslo},
	year = {2014},
	author = {Marie E. {Rognes}}
}
@misc {23338,
	title = {An Adjoint-Enabled Simulation Framework for Cardiac Electrophysiology},
	howpublished = {FEniCS{\textquoteright}14 Workshop, University of Chicago center in Paris, France},
	year = {2014},
	author = {Marie E. {Rognes}}
}
@misc {23343,
	title = {An Adjoint-Enabled Simulation Framework for Cardiac Electrophysiology},
	howpublished = {CBC and CCI Workshop on Cardiac Modelling at Simula Research Laboratory, Fornebu},
	year = {2014},
	author = {Marie E. {Rognes}}
}
@misc {23342,
	title = {Automated Goal-Oriented Error Control and Adaptivity},
	howpublished = {RCN site visit to the CBC, Simula Research Laboratory, Fornebu},
	year = {2014},
	author = {Marie E. {Rognes}}
}
@misc {23341,
	title = {High-Level Advanced Abstractions and Techniques in Finite Element Software},
	howpublished = {CBC Workshop on Computational Modeling with Applications in Biomedicine and Geophysics at Simula Research Laboratory},
	year = {2014},
	author = {Marie E. {Rognes}}
}
@misc {23339,
	title = {In Silico Physiological Flows},
	howpublished = {Seminar in connection with Villani visit at  Simula Research Laboratory, Fornebu},
	year = {2014},
	author = {Marie E. {Rognes}}
}
@inproceedings {Simula.simula.3088,
	title = {Least Squares Fitting of a Cardiac Hyperelasticity Model Using an Automatically Derived Adjoint Equation},
	journal = {Proceedings of NSCM-27: the 27th Nordic Seminar on Computational Mechanics},
	volume = {27},
	year = {2014},
	month = {October},
	pages = {272-275},
	publisher = {KTH Stockholm Royal Institute of Technology},
	type = {Workshop},
	address = {Drottning Kristinas v{\"a}g 53},
	abstract = {A Cardiac hyperelasticity model is successfully calibrated using an adjoint based least squares minimization and synthetic data.},
	keywords = {Conference},
	author = {Balaban, Gabriel and Sundnes, Joakim and Martin Sandve {Aln{\ae}s} and Marie E. {Rognes}},
	editor = {Eriksson, Anders and Kulachenko, Artem and Mihaescu, Mihai and Tibert, Gunnar}
}
@misc {23344,
	title = {Perspectives on the Current State of the Art of Computational Modelling of Fluid Flow in the Brain Parenchyma},
	howpublished = {CBC and CINPLA Workshop on Modelling Liquid Transport in the Brain, Simula Research Laboratory, Fornebu},
	year = {2014},
	author = {Marie E. {Rognes}}
}
@article {Simula.simula.1782,
	title = {A Stabilized Nitsche Fictitious Domain Method for the Stokes Problem},
	journal = {Journal of Scientific Computing},
	volume = {61},
	number = {online},
	year = {2014},
	month = {March},
	pages = {604-628},
	publisher = {  },
	doi = {10.1007/s10915-014-9838-9},
	author = {Massing, Andre and Mats G. {Larson} and Logg, Anders and Marie E. {Rognes}}
}
@article {Simula.simula.2502,
	title = {A Stabilized Nitsche Overlapping Mesh Method for the Stokes Problem},
	journal = {Numerische Mathematik},
	volume = {128},
	number = {online},
	year = {2014},
	month = {January},
	pages = {73-101},
	publisher = { },
	abstract = {We develop a Nitsche-based formulation for a general class of stabilized finite element methods for the Stokes problem posed on a pair of overlapping, non- matching meshes. By extending the least-squares stabilization to the overlap region, we prove that the method is stable, consistent, and optimally convergent. To avoid an ill-conditioned linear algebra system, the scheme is augmented by a least-squares term measuring the discontinuity of the solution in the overlap region of the two meshes. As a consequence, we may prove an estimate for the condition number of the resulting stiffness matrix that is independent of the location of the interface. Finally, we present numerical examples in three spatial dimensions illustrating and confirming the theoretical results.},
	doi = {10.1007/s00211-013-0603-z},
	author = {Massing, Andre and Mats G. {Larson} and Logg, Anders and Marie E. {Rognes}}
}
@article {Simula.simula.2456,
	title = {Unified Form Language: a Domain-Specific Language for Weak Formulations of Partial Differential Equations},
	journal = {ACM Transactions on Mathematical Software},
	volume = {40},
	number = {9},
	year = {2014},
	publisher = {ACM},
	abstract = {We present the Unified Form Language (UFL), which is a domain-specific language for representing weak formulations of partial differential equations with a view to numerical approximation. Features of UFL include support for variational forms and functionals, automatic differentiation of forms and expressions, arbitrary function space hierarchies for multi-field problems, general differential operators and flexible tensor algebra. With these features, UFL has been used to effortlessly express finite element methods for complex systems of partial differential equations in near-mathematical notation, resulting in compact, intuitive and readable programs. We present in this work the language and its construction. An implementation of UFL is freely available as an open-source software library. The library generates abstract syntax tree representations of variational problems, which are used by other software libraries to generate concrete low-level implementations. Some application examples are presented and libraries that support UFL are highlighted.},
	author = {Martin Sandve {Aln{\ae}s} and Logg, Anders and Kristian B. {{\O}lgaard} and Marie E. {Rognes} and Garth N. {Wells}}
}
@misc {Simula.simula.2026,
	title = {An Adjoint-Enabled Simulation Framework for Cardiac Electrophysiology},
	howpublished = {CBC/CCI workshop Advancing numerical technologies in the cardiac domain},
	year = {2013},
	month = {May},
	keywords = {Workshop},
	author = {Marie E. {Rognes}}
}
@article {dolfinadjoint,
	title = {Automated Derivation of the Adjoint of High-Level Transient Finite Element Programs},
	journal = {SIAM Journal on Scientific Computing},
	volume = {35},
	number = {4},
	year = {2013},
	pages = {369-393},
	author = {Patrick Emmet {Farrell} and David A. {Ham} and Simon W {Funke} and Marie E. {Rognes}}
}
@article {Simula.acdc.12,
	title = {Automated Goal-Oriented Error Control I: Stationary Variational Problems},
	journal = {SIAM Journal on Scientific Computing},
	volume = {35},
	number = {3},
	year = {2013},
	month = {June},
	pages = {173-193},
	abstract = {This article presents a general and novel approach to automated goal-oriented error control in the solution of nonlinear stationary finite element variational problems. The approach is based on automated linearization to obtain the linearized dual problem, automated derivation and evaluation of a\~posteriori error estimates, and automated adaptive mesh refinement to control the error in a given goal functional to within a given tolerance. Numerical examples representing a variety of different discretizations of linear and nonlinear partial differential equations are presented, including Poisson{\textquoteright}s equation, a mixed formulation of linear elasticity, and the incompressible Navier-Stokes equations.},
	author = {Marie E. {Rognes} and Logg, Anders}
}
@article {Simula.simula.2030,
	title = {Automating the Solution of PDEs on the Sphere and Other Manifolds in FEniCS 1.2},
	journal = {Geoscientific Model Development},
	number = {6},
	year = {2013},
	month = {June},
	pages = {2099-2119},
	author = {Marie E. {Rognes} and David A. {Ham} and Cotter, Colin and McRae, Andrew}
}
@article {Simula.simula.680,
	title = {Benchmarking FEniCS for Mantle Convection Simulations},
	journal = {Computers \& Geosciences},
	volume = {50},
	number = {1},
	year = {2013},
	note = {Special issue entitled Benchmark problems, datasets and methodologies for the computational geosciences},
	month = {January},
	pages = {95-105},
	publisher = {Elsevier},
	author = {Vynnytska, Lyudmyla and Marie E. {Rognes} and Clark, Stuart}
}
@misc {Simula.simula.2022,
	title = {FEniCS on a Moebius Strip},
	howpublished = {CBC seminar series},
	year = {2013},
	month = {February},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.2024,
	title = {Solving PDEs Over Manifolds With FEniCS},
	howpublished = {FEniCS{\textquoteright}13, Cambridge},
	year = {2013},
	note = {Presentation at FEniCS {\textquoteright}13, Cambridge, UK.},
	month = {March},
	keywords = {Conference},
	author = {Marie E. {Rognes}}
}
@article {Simula.simula.542,
	title = {An Analysis of the Shock Strength Needed to Achieve Defibrillation in a Simplified Mathematical Model of Cardiac Tissue},
	journal = {International Journal of Numerical Analysis and Modeling},
	volume = {9},
	number = {3},
	year = {2012},
	pages = {644-657},
	author = {Tveito, Aslak and Glenn T. {Lines} and Marie E. {Rognes} and Maleckar, Molly}
}
@misc {Simula.simula.1804,
	title = {Automated FEniCS Frameworks for Adjoint Models and Their Applications},
	howpublished = {KAUST},
	year = {2012},
	month = {November},
	author = {Marie E. {Rognes}}
}
@inbook {Simula.simula.1114,
	title = {Automated Testing of Saddle Point Stability Conditions},
	booktitle = {Automated Solution of Differential Equations by the Finite Element Method},
	series = {Lecture Notes in Computational Science and Engineering},
	volume = {84},
	year = {2012},
	pages = {655-670},
	publisher = {Springer},
	organization = {Springer},
	chapter = {36},
	isbn = {978-3-642-23098-1},
	author = {Marie E. {Rognes}},
	editor = {Logg, Anders and Mardal, Kent-Andre and Garth N. {Wells}}
}
@misc {Simula.simula.1808,
	title = {Automatically Generated Solvers for Variational Formulations of Time-Dependent Partial Differential Equations},
	howpublished = {ECCOMAS},
	year = {2012},
	month = {September},
	author = {Marie E. {Rognes}}
}
@inproceedings {Simula.simula.1784,
	title = {Automatically Generated Solvers for Variational Formulations of Time-Dependent Partial Differential Equations},
	journal = {6th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2012},
	year = {2012},
	type = {Conference},
	author = {Marie E. {Rognes} and Kehlet, Benjamin and Logg, Anders},
	editor = {Eberhardsteiner, J.}
}
@inbook {Simula.simula.1070,
	title = {Common and Unusual Finite Elements},
	booktitle = {Automated Solution of Differential Equations by the Finite Element Method},
	series = {Lecture Notes in Computational Science and Engineering},
	volume = {84},
	year = {2012},
	pages = {91-116},
	publisher = {Springer},
	organization = {Springer},
	chapter = {3},
	isbn = {978-3-642-23098-1},
	author = {Robert C. {Kirby} and Logg, Anders and Marie E. {Rognes} and Andy R. {Terrel}},
	editor = {Logg, Anders and Mardal, Kent-Andre and Garth N. {Wells}}
}
@inbook {Simula.simula.396,
	title = {Dynamic Simulations of Convection in the Earth{\textquoteright}s Mantle},
	booktitle = {Automated Solution of Differential Equations by the Finite Element Method},
	series = {Lecture Notes in Computational Science and Engineering},
	volume = {84},
	year = {2012},
	pages = {587-602},
	publisher = {Springer},
	organization = {Springer},
	chapter = {31},
	address = {Berlin Heidelberg},
	abstract = {In this chapter, we model dynamic convection processes in the Earth{\textquoteright}s mantle: linking the geodynamical equations, numerical implementation and Python code tightly together. The convection is generated by heating from below with a compositionally distinct and denser layer at the bottom. The time-dependent nonlinear partial differential equations to be solved are the quasi-static Stokes equations with depth- and temperature-dependent viscosity and advection-diffusion equations for the composition and temperature. We present a numerical algorithm for the simulation of these equations as well as an implementation of this algorithm using the DOLFIN Python interface. The results show the compositional heterogeneities persist, but interact strongly with the convecting system, generating upwellings and moving as material from the surface displaces them. This chapter will be of interest to those seeking to model fluid discontinuities using field methods as well as those interested in mantle convection simulations.},
	isbn = {978-3-642-23098-1},
	author = {Vynnytska, Lyudmyla and Clark, Stuart and Marie E. {Rognes}},
	editor = {Logg, Anders and Mardal, Kent-Andre and Garth N. {Wells}}
}
@misc {Simula.simula.1812,
	title = {The FEniCS Project: a Modern Framework for the Automated Solution of PDEs by FEM},
	howpublished = {Computational Geoscience Workshop},
	year = {2012},
	month = {January},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.1806,
	title = {The FEniCS Project: a Short Course},
	howpublished = {KAUST},
	year = {2012},
	month = {November},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.1810,
	title = {The FEniCS Project: a Tutorial},
	howpublished = {Imperial College},
	year = {2012},
	author = {Marie E. {Rognes}}
}
@inbook {Simula.simula.1084,
	title = {FFC: the FEniCS Form Compiler},
	booktitle = {Automated Solution of Differential Equations by the Finite Element Method},
	series = {Lecture Notes in Computational Science and Engineering},
	volume = {84},
	year = {2012},
	pages = {223-234},
	publisher = {Springer},
	organization = {Springer},
	chapter = {11},
	isbn = {978-3-642-23098-1},
	author = {Logg, Anders and Kristian B. {{\O}lgaard} and Marie E. {Rognes} and Garth N. {Wells}},
	editor = {Logg, Anders and Mardal, Kent-Andre and Garth N. {Wells}}
}
@inproceedings {Simula.simula.1786,
	title = {A Newton Method for Fluid-Structure Interaction Using Full Jacobians Based on Automatic Form Differentiation},
	journal = {6th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2012},
	year = {2012},
	type = {1},
	author = {Balaban, Gabriel and Logg, Anders and Marie E. {Rognes}},
	editor = {Eberhardsteiner, J.}
}
@misc {Simula.simula.1802,
	title = {Techniques for Automated Treatment of Variational Forms Over Arbitrary Dimension Tensor Product Finite Elements},
	howpublished = {CBC Seminar series},
	year = {2012},
	month = {December},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.986,
	title = {Automated Goal-Oriented Error Control},
	howpublished = {Talk at CBC workshop on Biomechanics, November 2011},
	year = {2011},
	month = {November},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.994,
	title = {Automated Goal-Oriented Error Control a Posteriori Error Estimation and Adaptivity in Finite Element Exterior Calculus},
	howpublished = {Talk at USNCCM {\textquoteright}11, Minneapolis},
	year = {2011},
	month = {July},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.996,
	title = {Bringing Error Control to the Non-Expert - Automation of a Posteriori Error Estimation},
	howpublished = {Talk at CBC Workshop on Multiscale Problems and Methods},
	year = {2011},
	month = {June},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.998,
	title = {Error Control and Adaptivity for the Non-Expert},
	howpublished = {Talk at CBC Workshop on Biomedical Modeling},
	year = {2011},
	month = {June},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.988,
	title = {FEniCS After 1.0: Current Trends at CBC@Simula},
	howpublished = {Talk at FEniCS{\textquoteright}11 / Red Raider Minisymposium 2011, Texas Tech University, Lubbock, November 2011},
	year = {2011},
	month = {November},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.990,
	title = {The FEniCS Project},
	howpublished = {Talk at Imperial College},
	year = {2011},
	month = {October},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.1000,
	title = {FEniCS: the Next Generation PDE Software},
	howpublished = {Talk at CBC Workshop on Biomedical Modeling},
	year = {2011},
	month = {June},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.1002,
	title = {Goal-Oriented Error Control Automated!},
	howpublished = {Talk at SIAM CSE Reno, Nevada, USA},
	year = {2011},
	month = {February},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.992,
	title = {More Or Less Shocking: Using Energy Estimates to Answer Scientific Questions},
	howpublished = {Talk at Biocomp Seminar, Simula Research Laboratory, October 2011},
	year = {2011},
	month = {October},
	author = {Marie E. {Rognes}}
}
@misc {Simula.simula.292,
	title = {Automated Goal-Oriented Error Control},
	howpublished = {China-Norway-Sweden Workshop on Computational Mathematics},
	year = {2010},
	author = {Logg, Anders and Marie E. {Rognes}}
}
@misc {Simula.simula.334,
	title = {Automated Goal-Oriented Error Control},
	howpublished = {8th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM), Rhodes, Greece, September 19-25},
	year = {2010},
	author = {Marie E. {Rognes}}
}
@misc {invitedtalkreference.2011-01-10.5280307621,
	title = {Automated Goal-Oriented Error Control},
	howpublished = {China-Norway-Sweden Workshop on Computational Mathematics in Bergen},
	year = {2010},
	author = {Logg, Anders and Marie E. {Rognes}}
}
@misc {Simula.acdc.4,
	title = {Automated Goal-Oriented Error Control for Stationary Variational Problems},
	howpublished = {Talk at FEniCS{\textquoteright}10, KTH Royal Institute of Technology, Stockholm},
	year = {2010},
	month = {May},
	author = {Marie E. {Rognes} and Logg, Anders}
}
@misc {Simula.acdc.6,
	title = {Automated Goal-Oriented Error Control for Stationary Variational Problems},
	howpublished = {Presentation at the European Finite Element Fair 2010, University of Warwick},
	year = {2010},
	month = {May},
	author = {Marie E. {Rognes} and Logg, Anders}
}
@misc {Simula.acdc.14,
	title = {Automated Goal-Oriented Error Control With Applications to Fluid Flow},
	howpublished = {Talk at CBC Workshop on Cerebral Blood Flow and Stroke - Clinical, Experimental and Mathematical Models and Problems},
	year = {2010},
	month = {June},
	author = {Marie E. {Rognes} and Logg, Anders}
}
@misc {Simula.acdc.10,
	title = {Automated Goal-Oriented Error Control With Applications to Nonlinear Elasticity},
	howpublished = {Talk at DSPDEs 2010 - Emerging Topics in Dynamical Systems and Partial Differential Equations, Barcelona},
	year = {2010},
	month = {May},
	author = {Marie E. {Rognes} and Logg, Anders}
}
@inproceedings {Simula.acdc.20,
	title = {Exploring Automated Adaptivity and Error Control},
	journal = {AIP Conference Proceedings},
	volume = {1281},
	number = {1},
	year = {2010},
	pages = {794-797},
	publisher = {AIP},
	type = {Conference},
	abstract = {Goal-oriented adaptive error control provides a multitude of choices with regard to error estimation and discretization refinement strategies. In this note, we investigate the effect of such choices using a flexible framework for automated adaptive goal-oriented error control applied to a specific test case. The efficiency of the adaptive algorithm varies significantly with the choice of parameters. We observe that the optimal parameters match the default parameters provided by the framework.},
	isbn = {978-0-7354-0834-0},
	doi = {10.1063/1.3498603},
	author = {Marie E. {Rognes} and Logg, Anders},
	editor = {Theodore E. {Simos} and Psihoyios, George and Tsitouras, Ch.}
}
@misc {Simula.acdc.16,
	title = {A Framework for Automated Goal-Oriented Error Control},
	howpublished = {Talk at BIT 50 - Trends in Numerical Computing},
	year = {2010},
	author = {Marie E. {Rognes} and Logg, Anders}
}
@article {Simula.SC.566,
	title = {Mixed Finite Element Methods for Viscoelasticity With Weak Symmetry},
	journal = {Mathematical Models and Methods in Applied Sciences (M3AS)},
	volume = {20},
	number = {6},
	year = {2010},
	pages = {955-985},
	abstract = {Small deformations of a viscoelastic body are considered through the linear Maxwell and Kelvin-Voigt models in the quasi-static equilibrium. A robust mixed finite element method, enforcing the symmetry of the stress tensor weakly, is proposed for these equations on simplicial tessellations in two and three dimensions. A priori error estimates are derived and numerical experiments presented. The approach can be applied to general models for linear viscoelasticity and thus offers a unifed framework.},
	doi = {10.1142/S0218202510004490},
	author = {Marie E. {Rognes} and Winther, Ragnar}
}
@misc {Simula.sc.684,
	title = {Automated Error Control. Current Status and Future Ambitions},
	howpublished = {Simula seminar},
	year = {2009},
	author = {Marie E. {Rognes}}
}
@article {Simula.SC.282,
	title = {Efficient Assembly of H(div) and H(curl) Conforming Finite Elements},
	journal = {SIAM Journal on Scientific Computing},
	volume = {36},
	number = {6},
	year = {2009},
	pages = {4130-4151},
	author = {Marie E. {Rognes} and Robert C. {Kirby} and Logg, Anders}
}
@misc {Simula.sc.668,
	title = {Efficient Assembly of H(div) and H(curl) Conforming Variational Forms},
	howpublished = {ICOSAHOM, Norwegian University of Science and Technology},
	year = {2009},
	author = {Marie E. {Rognes}}
}
@misc {Simula.sc.670,
	title = {Mixed Finite Element Methods for Linear Viscoelasticity},
	howpublished = {Compatible and innovative discretizations for PDEs. Algorithms, analysis and implementation. Norwegian Academy of Science and Letters},
	year = {2009},
	note = {Invited talk.},
	author = {Marie E. {Rognes}}
}
@phdthesis {Simula.sc.688,
	title = {Mixed Finite Element Methods With Applications to Viscoelasticity and Gels},
	year = {2009},
	school = {University of Oslo},
	type = {phd},
	isbn = {Q},
	author = {Marie E. {Rognes}}
}
@article {Simula.SC.564,
	title = {Modelling of and Mixed Finite Element Methods for Gels in Biomedical Applications},
	journal = {SIAM Journal on Applied Mathematics},
	volume = {70},
	number = {4},
	year = {2009},
	pages = {1305-1329},
	abstract = {A set of equilibrium equations for a biphasic polymer gel are considered with the end purpose of studying stress and deformation in confinement problems encountered in connection with biomedical implants. The existence of minimizers for the gel energy is established first. Further, the small-strain equations are derived and related to the linear elasticity equations with parameters dependent on the elasticity of the polymer and the mixing of the polymer and solvent. Two numerical methods are considered, namely a two-field displacement-pressure formulation and a three-field stress-displacement-rotation formulation with weakly imposed symmetry. The symmetry of the stress tensor is affected by the residual stress induced by the polymer-solvent mixing. A novel variation of the stress-displacement formulation of linear elasticity with weak symmetry is therefore proposed and analyzed. Finally, the numerical methods are used to simulate the stresses arising in a confined gel implant.},
	doi = {10.1137/090754443},
	author = {Marie E. {Rognes} and Calderer, M.-Carme and Micek, Catherine}
}
@article {Simula.SC.618,
	title = {Stability of Lagrange Elements for the Mixed Laplacian},
	journal = {Calcolo},
	volume = {46},
	number = {4},
	year = {2009},
	month = {December},
	pages = {245-260},
	abstract = {The stability properties of simple element choices for the mixed formulation of the Laplacian are investigated numerically. The element choices studied use vector Lagrange elements, i.e., the space of continuous piecewise polynomials vector fields of degree at most r, for the vector variable, and divergence of this space, which consists of discontinuous piecewise polynomials of one degree lower, for the scalar variable. For polynomial degrees r equal 2 or 3, this pair of spaces was found to be stable for all mesh families tested. In particular, it is stable on diagonal mesh families, in contrast to its behaviour for the Stokes equations. For degree r equal 1, stability holds for some meshes, but not for others. Additionally, convergence was observed precisely for the methods that were observed to be stable. However, it seems that optimal order L^2 estimates for the vector variable, known to hold for r>3, do not hold for lower degrees.},
	doi = {10.1007/s10092-009-0009-6},
	author = {Douglas N. {Arnold} and Marie E. {Rognes}}
}
@misc {Simula.sc.674,
	title = {Compiling H(div) and H(curl) Variational Forms},
	howpublished = {Automating the development of scientific computing software, Louisiana State University},
	year = {2008},
	author = {Marie E. {Rognes}}
}
@misc {Simula.sc.676,
	title = {Introduction to Finite Elements: Saddle Point Problems},
	howpublished = {Ferroelectric phenomena in soft matter systems, American Institute of Mathematics},
	year = {2008},
	author = {Marie E. {Rognes}}
}
@misc {Simula.sc.672,
	title = {Mixed Finite Elements for Viscoelasticity},
	howpublished = {Invited talk at the Computer Science department, University of Chicago},
	year = {2008},
	author = {Marie E. {Rognes}}
}
@misc {Simula.sc.680,
	title = {The Free Energy, the Boundary Value Problem and Then What?},
	howpublished = {Ferroelectric phenomena in liquid crystals, Kent State University},
	year = {2007},
	author = {Marie E. {Rognes}}
}
@misc {Simula.sc.682,
	title = {Mixed Finite Element Methods and Applications to Deformations of Elastic-Like Materials},
	howpublished = {Centre of Mathematics for Applications},
	year = {2007},
	author = {Marie E. {Rognes}}
}
@article {kallhovd2018inverse,
	title = {Inverse estimation of cardiac activation times via gradient-based optimization},
	journal = {International journal for numerical methods in biomedical engineering},
	volume = {34},
	number = {2},
	pages = {e2919},
	publisher = {John Wiley \& Sons Ltd},
	author = {Kallhovd, Siri and Maleckar, Molly and Marie E. {Rognes}}
}
@article {hong2021robust,
	title = {Robust approximation of generalized Biot-Brinkman problems},
	journal = {arXiv preprint arXiv:2112.13618},
	publisher = {arxiv},
	author = {Hong, QINGGUO and Kraus, JOHANNES and Kuchta, Miroslav and Lymbery, MARIA and Mardal, Kent-Andre and Marie E. {Rognes}}
}
