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pro vyhledávání: '"Walsh, Timothy F."'
In this paper, we introduce a physics and geometry informed neural operator network with application to the forward simulation of acoustic scattering. The development of geometry informed deep learning models capable of learning a solution operator f
Externí odkaz:
http://arxiv.org/abs/2406.03407
Publikováno v:
Engineering with Computers (2024)
This work presents a physics-driven machine learning framework for the simulation of acoustic scattering problems. The proposed framework relies on a physics-informed neural network (PINN) architecture that leverages prior knowledge based on the phys
Externí odkaz:
http://arxiv.org/abs/2403.04094
Publikováno v:
Comput. Methods Appl. Mech. Engrg. 414(2023)116167
This study presents a deep learning based methodology for both remote sensing and design of acoustic scatterers. The ability to determine the shape of a scatterer, either in the context of material design or sensing, plays a critical role in many pra
Externí odkaz:
http://arxiv.org/abs/2302.07504
While elastic metasurfaces offer a remarkable and very effective approach to the subwalength control of stress waves, their use in practical applications is severely hindered by intrinsically narrow band performance. This work introduces the concept
Externí odkaz:
http://arxiv.org/abs/2002.10427
Autor:
Guddati, Murthy N., Walsh, Timothy F.
Publikováno v:
In Mechanical Systems and Signal Processing 15 December 2023 205
Akademický článek
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This letter presents the concept of Total Internal Reflection metasurface (TIR-MS) which supports the realization of structure-embedded subwavelength acoustic shields for elastic waves propagating in thin waveguides. The proposed metasurface design e
Externí odkaz:
http://arxiv.org/abs/1810.11851
Publikováno v:
In Journal of Sound and Vibration 31 March 2022 522
Publikováno v:
In Mechanical Systems and Signal Processing 15 February 2021 149
Publikováno v:
In Journal of Sound and Vibration 15 September 2019 456:162-172