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Gerhard Holzapfel
Researcher at Norwegian University of Science and Technology
Publications - 445
Citations - 29335
Gerhard Holzapfel is an academic researcher from Norwegian University of Science and Technology. The author has contributed to research in topics: Finite element method & Constitutive equation. The author has an hindex of 77, co-authored 410 publications receiving 25410 citations. Previous affiliations of Gerhard Holzapfel include Washington University in St. Louis & Graz University of Technology.
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Journal ArticleDOI
Mechanical characterization of porcine liver properties for computational simulation of indentation on cancerous tissue.
TL;DR: This study measured the deformation locally at the middle of liver specimens and obtained the corresponding stress-stretch curves and constructed computational models of liver tissue with a tumor, finding that the liver specimen with tumor shows a stiffer response if the distance between the tumor and the indenter is small.
Book ChapterDOI
In Vivo Experiments to Characterize the Mechanical Behavior of the Human Uterine Cervix
Edoardo Mazza,Alessandro Nava,Margit Bauer,Raimund Winter,Michael Bajka,Gerhard Holzapfel,Gerhard Holzapfel +6 more
TL;DR: The main purpose of the present study was to test the reliability and sensitivity of mechanical data obtained from human cervices with respect to a possible clinical application for diagnostic purposes.
Journal ArticleDOI
Implementation of collagen fiber dispersion in a growth and remodeling model of arterial walls
TL;DR: In this article, a fiber dispersion model based on the generalized structure tensor approach was implemented into a constrained mixture growth and remodeling model of the aortic wall, and a new definition of the fiber pre-stretch tensor compatible with fiber dispersions was proposed.
Journal ArticleDOI
A methodology to study the morphologic changes in lesions during in vitro angioplasty using MRI and image processing
Martin Auer,Peter Regitnig,Rudolf Stollberger,Franz Ebner,Gerhard Holzapfel,Gerhard Holzapfel +5 more
TL;DR: This methodology provides a basis for studying plaque biomechanics under supra-physiological loading conditions and has the potential to improve and validate finite element models of atherosclerotic plaques which may allow a better prediction of angioplasty procedures.
Posted ContentDOI
Automated model discovery for skin: Discovering the best model, data, and experiment
TL;DR: CANN as discussed by the authors proposes a neural network based approach to automatically discover the best model and parameters to explain experimental data, which is translated into a complex non-convex optimization problem.