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The ubiquitous deployment of monitoring devices in urban flow monitoring systems induces a significant cost for maintenance and operation. A technique is required to reduce the number of deployed devices, while preventing the degeneration…

Computer Vision and Pattern Recognition · Computer Science 2020-02-07 Kun Ouyang , Yuxuan Liang , Ye Liu , Zekun Tong , Sijie Ruan , Yu Zheng , David S. Rosenblum

Flash floods in urban areas occur with increasing frequency. Detecting these floods would greatlyhelp alleviate human and economic losses. However, current flood prediction methods are eithertoo slow or too simplified to capture the flood…

Signal Processing · Electrical Eng. & Systems 2019-08-28 Kun Qian , Abduallah Mohamed , Christian Claudel

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity…

Computational Physics · Physics 2019-10-18 Han Bao , Jinyong Feng , Nam Dinh , Hongbin Zhang

Unsteady fluid systems are nonlinear high-dimensional dynamical systems that may exhibit multiple complex phenomena both in time and space. Reduced Order Modeling (ROM) of fluid flows has been an active research topic in the recent decade…

Fluid Dynamics · Physics 2020-10-05 Hamidreza Eivazi , Hadi Veisi , Mohammad Hossein Naderi , Vahid Esfahanian

Due to the increasing frequency and severity of storm events, driven by the escalation of anthropogenic climate change and urban expansion, there is a requirement for increasingly efficient flood risk management strategies. While Blue-Green…

Neural and Evolutionary Computing · Computer Science 2026-04-22 James Mckenna , Christos Iliadis , Vassilis Glenis

We present the geospatial methods in conjunction with results of a newly developed storm surge and sub-grid inundation model which was applied in New York City during Hurricane Sandy in 2012. Sub-grid modeling takes a novel approach for…

Geophysics · Physics 2014-12-03 Jon Derek Loftis , Harry V. Wang , Stuart E. Hamilton , David R. Forrest

Lack of conservation has been the biggest drawback in meshfree generalized finite difference methods (GFDMs). In this paper, we present a novel modification of classical meshfree GFDMs to include local balances which produce an approximate…

Numerical Analysis · Mathematics 2018-02-02 Pratik Suchde , Joerg Kuhnert , Simon Schroeder , Axel Klar

This paper is concerned with mixed finite element method (FEM) for solving the two-dimensional, nonlinear fourth-order active fluid equations. By introducing an auxiliary variable $w=-\Delta u$, the original fourth problem is transformed…

Numerical Analysis · Mathematics 2025-07-30 Nan Zheng , Xu Guo , Wenlong Pei , Wenju Zhao

We present and compare third- as well as fifth-order accurate finite difference schemes for the numerical solution of the compressible ideal MHD equations in multiple spatial dimensions. The selected methods lean on four different…

High Energy Astrophysical Phenomena · Physics 2015-05-18 A. Mignone , P. Tzeferacos , G. Bodo

In our earlier work, we proposed a data-driven filtered reduced order model (DDF-ROM) framework for the numerical simulation of fluid flows, which can be formally written as \begin{equation*} \boxed{ \text{ DDF-ROM = Galerkin-ROM +…

Numerical Analysis · Mathematics 2018-12-26 M. Mohebujjaman , L. G. Rebholz , T. Iliescu

Traditional DTA models of large cities suffer from prohibitive computation times and calibration/validation can become major challenges faced by practitioners. The empirical evidence in 2008 in support of the existence of a Macroscopic…

Analysis of PDEs · Mathematics 2018-12-04 Rafegh Aghamohammadi , Jorge A. Laval

Data-driven flood forecasting methods are useful, especially for the rivers that lack hydrological information to build physical models. Although these former methods can forecast river stages using only past water levels and rainfall data,…

Geophysics · Physics 2021-04-07 Shunya Okuno , Koji Ikeuchi , Kazuyuki Aihara

Atmospheric flows exhibit long-range spatiotemporal correlations manifested as the fractal geometry to the global cloud cover pattern concomitant with inverse power-law form for power spectra of temporal fluctuations of all scales ranging…

General Physics · Physics 2007-05-23 A. M. Selvam , S. Fadnavis

In this paper, we consider queueing systems where the dynamics are non-stationary and state-dependent. For performance analysis of these systems, fluid and diffusion models have been typically used. Although they are proven to be…

Probability · Mathematics 2016-09-08 Young Myoung Ko , Natarajan Gautam

Fine classification of city-scale buildings from satellite remote sensing imagery is a crucial research area with significant implications for urban planning, infrastructure development, and population distribution analysis. However, the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Zhiyi He , Wei Yao , Jie Shao , Puzuo Wang

Many species, from single-cell bacteria to advanced animals, use molecular communication (MC) to share information with each other via chemical signals. Although MC is mostly studied in microscale, new practical applications emerge in…

Fluid Dynamics · Physics 2021-03-30 Fatih Gulec , Baris Atakan

The analysis of flow around buildings has gained significant research interest across various domains, including pedestrian safety, pollutant dispersion, natural ventilation, and building energy efficiency. While these domains frequently…

Fluid Dynamics · Physics 2026-03-18 Hojin Lee , Andreas Lintermann , Sangseung Lee , Mario Rüttgers

Simple modifications for higher-order Godunov-type difference schemes are presented which allow for accurate advection of multi-fluid flows in hydrodynamic simulations. The constraint that the sum of all mass fractions has to be equal to…

Astrophysics · Physics 2009-09-25 Tomasz Plewa , Ewald Mueller

Urban wind flow modeling and simulation play an important role in air quality assessment and sustainable city planning. A key challenge for modeling and simulation is handling the complex geometries of the urban landscape. Low order models…

Machine Learning · Computer Science 2025-12-18 Francisco Giral , Álvaro Manzano , Ignacio Gómez , Petros Koumoutsakos , Soledad Le Clainche

Learning dynamical systems from incomplete or noisy data is inherently ill-posed, as a single observation may correspond to multiple plausible futures. While physics-based ensemble forecasting relies on perturbing initial states to capture…

Machine Learning · Computer Science 2026-02-27 Siddharth Rout , Eldad Haber , Stephane Gaudreault