Zobrazeno 1 - 10
of 11 119
pro vyhledávání: '"A. Schillinger"'
Publikováno v:
Brain and Spine, Vol 4, Iss , Pp 103293- (2024)
Externí odkaz:
https://doaj.org/article/b92aa440c9ab47079efbdf57784f4fe1
Autor:
Ebrahem, Adnan, Hohl, Jannes, Jessen, Etienne, Eikelder, Marco F. P. ten, Schillinger, Dominik
We present a framework for modeling liver regrowth on the organ scale that is based on three components: (1) a multiscale perfusion model that combines synthetic vascular tree generation with a multi-compartment homogenized flow model, including a ho
Externí odkaz:
http://arxiv.org/abs/2410.19529
The understanding of the mechanisms driving vascular development is still limited. Techniques to generate vascular trees synthetically have been developed to tackle this problem. However, most algorithms are limited to single trees inside convex perf
Externí odkaz:
http://arxiv.org/abs/2410.06002
We introduce a counting process to model the random occurrence in time of car traffic accidents, taking into account some aspects of the self-excitation typical of this phenomenon. By combining methods from probability and differential equations, we
Externí odkaz:
http://arxiv.org/abs/2410.00446
We present a new framework for the simultaneous optimiziation of both the topology as well as the relative density grading of cellular structures and materials, also known as lattices. Due to manufacturing constraints, the optimization problem falls
Externí odkaz:
http://arxiv.org/abs/2408.00510
We present a novel isogeometric discretization approach for the Kirchhoff-Love shell formulation based on the Hellinger-Reissner variational principle. For mitigating membrane locking, we discretize the independent strains with spline basis functions
Externí odkaz:
http://arxiv.org/abs/2406.16685
Autor:
Liu, Yushi, Qualmann, Alexander, Yu, Zehao, Gabriel, Miroslav, Schillinger, Philipp, Spies, Markus, Vien, Ngo Anh, Geiger, Andreas
Bin picking is an important building block for many robotic systems, in logistics, production or in household use-cases. In recent years, machine learning methods for the prediction of 6-DoF grasps on diverse and unknown objects have shown promising
Externí odkaz:
http://arxiv.org/abs/2405.06336
The prevailing grasp prediction methods predominantly rely on offline learning, overlooking the dynamic grasp learning that occurs during real-time adaptation to novel picking scenarios. These scenarios may involve previously unseen objects, variatio
Externí odkaz:
http://arxiv.org/abs/2403.02495
The macro-element variant of the hybridized discontinuous Galerkin (HDG) method combines advantages of continuous and discontinuous finite element discretization. In this paper, we investigate the performance of the macro-element HDG method for the a
Externí odkaz:
http://arxiv.org/abs/2402.11361
Autor:
Eikelder, M. ten, Schillinger, D.
The prototypical diffuse-interface model that describes multi-component flows is the Navier-Stokes Cahn-Hilliard model (NSCH). Over the last decades many NSCH models have appeared that claim to describe the same physical phenomena, yet are distinct f
Externí odkaz:
http://arxiv.org/abs/2311.09966