Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Mohammad Farazmand"'
Publikováno v:
Fluids, Vol 4, Iss 1, p 55 (2019)
We study the horizontal dispersion of passive tracer particles on the free surface of gravity waves in deep water. For random linear waves with the JONSWAP spectrum, the Lagrangian particle trajectories are computed using an exact nonlinear model kno
Externí odkaz:
https://doaj.org/article/c2a025975c664d428a8b30d6282c3d71
Autor:
Konstantinos Mamis, Mohammad Farazmand
Publikováno v:
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 479
Compartmental models are an important quantitative tool in epidemiology, enabling us to forecast the course of a communicable disease. However, the model parameters, such as the infectivity rate of the disease, are riddled with uncertainties, which h
Autor:
Mohammad Farazmand, Arvind K. Saibaba
Reconstructing high-resolution flow fields from sparse measurements is a major challenge in fluid dynamics. Existing methods often vectorize the flow by stacking different spatial directions on top of each other, hence confounding the information enc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97ded18956d2e59e95a09637e9396e05
Autor:
William Anderson, Mohammad Farazmand
We consider reduced-order modeling of nonlinear dispersive waves described by a class of nonlinear Schrodinger (NLS) equations. We compare two nonlinear reduced-order modeling methods: (i) The reduced Lagrangian approach which relies on the variation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7003f7c97d69ac8c103530e4715dd010
To predict rare extreme events using deep neural networks, one encounters the so-called small data problem because even long-term observations often contain few extreme events. Here, we investigate a model-assisted framework where the training data i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0c18a21403c645d245fc2e7227408ae
http://arxiv.org/abs/2111.04857
http://arxiv.org/abs/2111.04857
Autor:
William Anderson, Mohammad Farazmand
Reduced-order models of time-dependent partial differential equations (PDEs) where the solution is assumed as a linear combination of prescribed modes are rooted in a well-developed theory. However, more general models where the reduced solutions dep
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1f66b51cda04dbb15062b17559397cb
http://arxiv.org/abs/2104.13515
http://arxiv.org/abs/2104.13515
Autor:
K.I. Mamis, Mohammad Farazmand
We consider rare transitions induced by colored noise excitation in multistable systems. We show that undesirable transitions can be mitigated by a simple time-delay feedback control if the control parameters are judiciously chosen. We devise a parsi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7713d6c0e76857b4aea0b9fc93978f5
Autor:
Mohammad Farazmand
Publikováno v:
Chaos (Woodbury, N.Y.). 30(1)
In stochastic multistable systems driven by the gradient of a potential, transitions between equilibria is possible because of noise. We study the ability of linear delay feedback control to mitigate these transitions, ensuring that the system stays
Autor:
Alexander Mendez, Mohammad Farazmand
We study the mitigation of climate tipping point transitions using an energy balance model. The evolution of the global mean surface temperature is coupled with the CO2 concentration through the green house effect. We model the CO2 concentration with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8aa73d11949d033418ec44ae1740dd67