Zobrazeno 1 - 10
of 152
pro vyhledávání: '"Nicolas R. Gauger"'
Autor:
Tommaso Dorigo, Andrea Giammanco, Pietro Vischia, Max Aehle, Mateusz Bawaj, Alexey Boldyrev, Pablo de Castro Manzano, Denis Derkach, Julien Donini, Auralee Edelen, Federica Fanzago, Nicolas R. Gauger, Christian Glaser, Atılım G. Baydin, Lukas Heinrich, Ralf Keidel, Jan Kieseler, Claudius Krause, Maxime Lagrange, Max Lamparth, Lukas Layer, Gernot Maier, Federico Nardi, Helge E.S. Pettersen, Alberto Ramos, Fedor Ratnikov, Dieter Röhrich, Roberto Ruiz de Austri, Pablo Martínez Ruiz del Árbol, Oleg Savchenko, Nathan Simpson, Giles C. Strong, Angela Taliercio, Mia Tosi, Andrey Ustyuzhanin, Haitham Zaraket
Publikováno v:
Reviews in Physics, Vol 10, Iss , Pp 100085- (2023)
The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, due to the large dimensionality of the space of possible choices for geometry, detection tech
Externí odkaz:
https://doaj.org/article/226f133fd21c4e9e8e0f30edd0daec70
Publikováno v:
Journal of the Global Power and Propulsion Society, Vol 1, Iss 1 (2017)
Non-Ideal Compressible Fluid-Dynamics (NICFD) has recently been established as a sector of fluid mechanics dealing with the flows of dense vapors, supercritical fluids, and two-phase fluids, whose properties significantly depart from those of the ide
Externí odkaz:
https://doaj.org/article/99899f3c693848c49b22c2a06fa055e5
We propose a novel reconstruction scheme for reconstructing charged particles in digital tracking calorimeters using model-free reinforcement learning aiming to benefit from the rapid progress and success of neural network architectures for tracking
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f252a2098fb93f9ddbaf7e7af90b4508
https://doi.org/10.36227/techrxiv.21717323
https://doi.org/10.36227/techrxiv.21717323
Publikováno v:
Computational Mechanics. 69:589-613
We propose a universal method for the evaluation of generalized standard materials that greatly simplifies the material law implementation process. By means of automatic differentiation and a numerical integration scheme, AutoMat reduces the implemen
Publikováno v:
AIAA Journal. 59:2517-2531
Unsteady aerodynamic shape optimization presents new challenges in terms of sensitivity analysis of time-dependent objective functions. In this work, we consider periodic unsteady flows governed by...
Publikováno v:
AIAA AVIATION 2022 Forum.
Autor:
Thomas D. Economon, Beckett Yx Zhou, Nicolas R. Gauger, Tim Albring, Carlos R. N. da Silva, Juan J. Alonso
Publikováno v:
AIAA Journal. 59:580-595
This paper presents an efficient adjoint-based shape optimization framework for airframe noise reduction in which algorithmic differentiation (AD) is applied to the open-source multiphysics solver ...
Autor:
Tommaso Dorigo, Andrea Giammanco, Pietro Vischia, Max Aehle, Mateusz Bawaj, Alexey Boldyrev, Pablo de Castro Manzano, Denis Derkach, Julien Donini, Auralee Edelen, Federica Fanzago, Nicolas R. Gauger, Christian Glaser, Atılım G. Baydin, Lukas Heinrich, Ralf Keidel, Jan Kieseler, Claudius Krause, Maxime Lagrange, Max Lamparth, Lukas Layer, Gernot Maier, Federico Nardi, Helge E.S. Pettersen, Alberto Ramos, Fedor Ratnikov, Dieter Röhrich, Roberto Ruiz de Austri, Pablo Martínez Ruiz del Árbol, Oleg Savchenko, Nathan Simpson, Giles C. Strong, Angela Taliercio, Mia Tosi, Andrey Ustyuzhanin, Haitham Zaraket
The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, due to the large dimensionality of the space of possible choices for geometry, detection tech
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5260d6e0d4fb24e1e0490ed34d919bb1
http://cds.cern.ch/record/2807001
http://cds.cern.ch/record/2807001
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031073113
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7be0de33282feb0bcc80e9528bcc126d
https://doi.org/10.1007/978-3-031-07312-0_17
https://doi.org/10.1007/978-3-031-07312-0_17