Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Mohammad Amin Nabian"'
Autor:
Hadi Meidani, Mohammad Amin Nabian
Publikováno v:
Probabilistic Engineering Mechanics. 57:14-25
Developing efficient numerical algorithms for the solution of high dimensional random Partial Differential Equations (PDEs) has been a challenging task due to the well-known curse of dimensionality. We present a new solution approach for these proble
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed06988de7d330448245e35d9abedfc8
https://doi.org/10.1016/j.probengmech.2019.05.001
https://doi.org/10.1016/j.probengmech.2019.05.001
Publikováno v:
Transportation Research Record: Journal of the Transportation Research Board. 2673:564-573
Accurate near-term passenger train delay prediction is critical for optimal railway management and providing passengers with accurate train arrival times. In this work, a novel bi-level random forest approach is proposed to predict passenger train de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::444bf2d9e153805908f358c46b659dbd
https://doi.org/10.1177/0361198119840339
https://doi.org/10.1177/0361198119840339
Physics-Informed Neural Networks (PINNs) are a class of deep neural networks that are trained, using automatic differentiation, to compute the response of systems governed by partial differential equations (PDEs). The training of PINNs is simulation-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0aa778c2fa00b114854f9ba4de10925
Autor:
Kaustubh Tangsali, Akshay Subramaniam, Wonmin Byeon, Mohammad Amin Nabian, Zhiwei Fang, Max Rietmann, Susheela Narasimhan, Oliver Hennigh, Sanjay Choudhry
Publikováno v:
Computational Science – ICCS 2021 ISBN: 9783030779764
ICCS (5)
ICCS (5)
We present SimNet, an AI-driven multi-physics simulation framework, to accelerate simulations across a wide range of disciplines in science and engineering. Compared to traditional numerical solvers, SimNet addresses a wide range of use cases - coupl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3817dea67b3657c2e38de8cbd7744929
https://doi.org/10.1007/978-3-030-77977-1_36
https://doi.org/10.1007/978-3-030-77977-1_36
Autor:
Mohammad Amin Nabian, Hadi Meidani
Publikováno v:
Computer-Aided Civil and Infrastructure Engineering. 33:443-458
To optimize mitigation, preparedness, response, and recovery procedures for infrastructure systems, it is essential to use accurate and efficient means to evaluate system reliability again...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc87312c74d326871554d79af215b30d
https://doi.org/10.1111/mice.12359
https://doi.org/10.1111/mice.12359
Autor:
Mohammad Amin Nabian, Leila Farhadi
Publikováno v:
Water
Volume 11
Issue 7
Water, Vol 11, Iss 7, p 1349 (2019)
Volume 11
Issue 7
Water, Vol 11, Iss 7, p 1349 (2019)
A Multi-Resolution Weakly Compressible Moving-Particle Semi-Implicit (MR-WC-MPS) method is presented in this paper for simulation of free-surface flows. To reduce the computational costs, as with the multi-grid schemes used in mesh-based methods, the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0878bc816338c82761d9888ea03f62b4
Autor:
Mohammad Amin Nabian, Hadi Meidani
In this paper, we introduce a physics-driven regularization method for training of deep neural networks (DNNs) for use in engineering design and analysis problems. In particular, we focus on the prediction of a physical system, for which in addition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4052d40f5f12e4c50c763da530189f2
Autor:
Mohammad Amin Nabian, Leila Farhadi
Publikováno v:
Journal of Hydraulic Engineering. 143
The objective of this paper is to develop a straightforward, robust, stable, and accurate mesh-free numerical technique for modeling the dynamic behavior of free surface, incompressible, mu...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85f9f0610f82723bbdb6e83eda9ef359
https://doi.org/10.1061/(asce)hy.1943-7900.0001275
https://doi.org/10.1061/(asce)hy.1943-7900.0001275
Autor:
Mohammad Amin Nabian, Leila Farhadi
Publikováno v:
Volume 7: Fluids Engineering Systems and Technologies.
A mesh-free numerical formulation, known as Moving Particle Semi Implicit (MPS) Method, is used for modeling waves generated by submarine landslides. In this formulation, approximations are provided to the strong form of PDEs on the basis of integral
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07e8d66fe25947309a95fd8abdc89918
https://doi.org/10.1115/imece2014-40419
https://doi.org/10.1115/imece2014-40419