Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Physics-Based Machine Learning"'
Autor:
Thomas Poulet, Pouria Behnoudfar
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 12, Pp n/a-n/a (2024)
Abstract The significant risk associated with fault reactivation often necessitates slip tendency analyses for effective risk assessment. However, such analyses are challenging, particularly in large areas with limited or absent reliable stress measu
Externí odkaz:
https://doaj.org/article/ae11ee613c9b49709570aaf5091d1205
Publikováno v:
Frontiers in Nanotechnology, Vol 6 (2024)
Externí odkaz:
https://doaj.org/article/b193ce8b885c486b8c7d3c84795ad387
Autor:
Ivan Stebakov, Alexei Kornaev, Elena Kornaeva, Nikita Litvinenko, Yuri Kazakov, Oleg Ivanov, Bulat Ibragimov
Publikováno v:
IEEE Access, Vol 12, Pp 169945-169954 (2024)
Artificial neural networks are a powerful tool for spatial and temporal functions approximation. This study introduces a novel approach for modeling non-Newtonian fluid flows by minimizing a proposed power loss metric, which aligns with the variation
Externí odkaz:
https://doaj.org/article/fd1bc629cefc41bcad6c844f069d0af1
Autor:
Alex R. Riensche, Benjamin D. Bevans, Grant King, Ajay Krishnan, Kevin D. Cole, Prahalada Rao
Publikováno v:
Materials & Design, Vol 237, Iss , Pp 112540- (2024)
The long-term goal of this work is to predict and control the microstructure evolution in metal additive manufacturing processes. In pursuit of this goal, we developed and applied an approach which combines physics-based thermal modeling with machine
Externí odkaz:
https://doaj.org/article/26a7b9bb9dfb49f181630b36524083fe
Publikováno v:
Advanced Modeling and Simulation in Engineering Sciences, Vol 10, Iss 1, Pp 1-38 (2023)
Abstract We present a Reduced Order Model (ROM) which exploits recent developments in Physics Informed Neural Networks (PINNs) for solving inverse problems for the Navier–Stokes equations (NSE). In the proposed approach, the presence of simulated d
Externí odkaz:
https://doaj.org/article/f3c02454dcd54e2c81ed3145c95fb1f5
Autor:
Luca Marino, Alice Cicirello
Publikováno v:
Data-Centric Engineering, Vol 4 (2023)
An approach for the identification of discontinuous and nonsmooth nonlinear forces, as those generated by frictional contacts, in mechanical systems that can be approximated by a single-degree-of-freedom model is presented. To handle the sharp variat
Externí odkaz:
https://doaj.org/article/c94e17bab05b4cebbdba1a84b4d63c6c
Publikováno v:
Results in Engineering, Vol 16, Iss , Pp 100659- (2022)
Computational models have been used in conjunction with field data, such as in reinforcement concrete corrosion monitoring. It typically involves evaluating the physical model of the corrosion process. However, computation of the numerical solution f
Externí odkaz:
https://doaj.org/article/d4d8e754265943c39c05a9d4e21a9c87
Akademický článek
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Autor:
Seungik Baek, Amirhossein Arzani
Publikováno v:
Applications in Engineering Science, Vol 10, Iss , Pp 100097- (2022)
Ultrasound imaging has long been playing a central role in detecting abdominal aortic aneurysms (AAAs). With a recent trend of reducing prevalence of AAAs, ultrasound screening is only recommended for men aged 65 to 75 years with previous smoking his
Externí odkaz:
https://doaj.org/article/8df5506749084a2db2e52e0a6d1d2781
Publikováno v:
Results in Engineering, Vol 13, Iss , Pp 100316- (2022)
The recent development of machine learning (ML) and Deep Learning (DL) increases the opportunities in all the sectors. ML is a significant tool that can be applied across many disciplines, but its direct application to civil engineering problems can
Externí odkaz:
https://doaj.org/article/6de9aa8ce1bd4f4e8a2a0da1988950cf