E
Ellen Kuhl
Researcher at Stanford University
Publications - 349
Citations - 16857
Ellen Kuhl is an academic researcher from Stanford University. The author has contributed to research in topics: Finite element method & Constitutive equation. The author has an hindex of 64, co-authored 323 publications receiving 12857 citations. Previous affiliations of Ellen Kuhl include Washington University in St. Louis & University of Stuttgart.
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Journal ArticleDOI
Mechanical properties of gray and white matter brain tissue by indentation.
Silvia Budday,Richard J. Nay,Rijk de Rooij,Paul Steinmann,Thomas J. Wyrobek,Timothy C. Ovaert,Ellen Kuhl +6 more
TL;DR: It is found that indenting thick, intact coronal slices eliminates the common challenges associated with small specimens: it naturally minimizes boundary effects, dehydration, swelling, and structural degradation.
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Perspectives on biological growth and remodeling
Davide Carlo Ambrosi,Gerard A. Ateshian,Ellen M. Arruda,Stephen C. Cowin,Jacques Dumais,Alain Goriely,Gerhard Holzapfel,Jay D. Humphrey,Ralf Kemkemer,Ellen Kuhl,J.E. Olberding,Larry A. Taber,K. Garikipati +12 more
TL;DR: The state of the field of continuum mechanical treatment of biological growth and remodeling is reviewed and open questions, challenges, and avenues for further development are highlighted.
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Mechanical characterization of human brain tissue.
Silvia Budday,Gerhard Sommer,Christoph Birkl,Christian Langkammer,Johannes Haybaeck,J Kohnert,M Bauer,Friedrich Paulsen,Paul Steinmann,Ellen Kuhl,Gerhard Holzapfel,Gerhard Holzapfel +11 more
TL;DR: This work performs a sequence of experimental tests on the same brain specimen to characterize the regional and directional behavior, and supplements these tests with DTI and histology to explore to which extent the macrostructural response is a result of the underlying microstructure.
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Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences
Mark Alber,Adrian Buganza Tepole,William R. Cannon,Suvranu De,Salvador Dura-Bernal,Krishna Garikipati,George Em Karniadakis,William W. Lytton,Paris Perdikaris,Linda R. Petzold,Ellen Kuhl +10 more
TL;DR: It is demonstrated that machine learning and multiscale modeling can naturally complement each other to create robust predictive models that integrate the underlying physics to manage ill-posed problems and explore massive design spaces.
Journal ArticleDOI
Mechanics of the brain: perspectives, challenges, and opportunities
Alain Goriely,Mgd Marc Geers,Gerhard Holzapfel,Jayaratnam Jayamohan,Antoine Jérusalem,Sivabal Sivaloganathan,W Waney Squier,Jaw Hans van Dommelen,Sarah L. Waters,Ellen Kuhl +9 more
TL;DR: It is shown that classical mechanical concepts including deformations, stretch, strain, strain rate, pressure, and stress play a crucial role in modulating both brain form and brain function.