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This study introduces a hybrid fluid simulation approach that integrates generative diffusion models with physics-based simulations, aiming at reducing the computational costs of flow simulations while still honoring all the physical…

Under many conditions, macroscopic grains flow like a fluid; kinetic theory pred icts continuum equations of motion for this granular fluid. In order to test the theory, we perform event driven molecular simulations of a two-dimensional gas…

Statistical Mechanics · Physics 2009-10-31 C. Bizon , M. D. Shattuck , J. B. Swift , Harry L. Swinney

Recent advances have shown that the circuit simulation algorithms that allow for solving highly nonlinear circuits of over one billion variables can be applicable to power system simulation and optimization problems through the use of an…

Signal Processing · Electrical Eng. & Systems 2019-04-11 Marko Jereminov , Athanasios Terzakis , Martin Wagner , Amritanshu Pandey , Larry Pileggi

Multiphase compressible flows are often characterized by a broad range of space and time scales. Thus entailing large grids and small time steps, simulations of these flows on CPU-based clusters can thus take several wall-clock days.…

Fluid flow through bimodal porous media, characterized by a distinct separation in pore size distribution, is critical in various scientific and engineering applications, including groundwater management, oil and gas production, and carbon…

Fluid Dynamics · Physics 2024-09-06 Yuhe Wang , Yating Wang

In this paper, we are concerned with the simulation of blood flow in microvascular networks and the surrounding tissue. To reduce the computational complexity of this issue, the network structures are modeled by a one-dimensional graph,…

Numerical Analysis · Mathematics 2023-05-01 Ettore Vidotto , Timo Koch , Tobias Köppl , Rainer Helmig , Barbara Wohlmuth

Simulation of multiphase flow in porous media is crucial for the effective management of subsurface energy and environment related activities. The numerical simulators used for modeling such processes rely on spatial and temporal…

Computational Physics · Physics 2022-05-25 Bicheng Yan , Dylan Robert Harp , Rajesh J. Pawar

Hydrodynamics calculations have been successfully used in studies of the bulk properties of the Quark-Gluon Plasma, particularly of elliptic flow and shear viscosity. However, there are areas (for instance event-by-event simulations for…

The transport and manipulation of particles and cells in microfluidic devices has become a core methodology in domains ranging from molecular biology to manufacturing and drug design. The rational design and operation of such devices can…

Computational Engineering, Finance, and Science · Computer Science 2020-07-15 Dmitry Alexeev , Lucas Amoudruz , Sergey Litvinov , Petros Koumoutsakos

In this paper, we describe a numerical algorithm for the self-consistent simulations of surface water and sediment dynamics. The method is based on the original Lagrangian-Eulerian CSPH-TVD approach for solving the Saint-Venant and Exner…

Numerical Analysis · Mathematics 2021-03-30 Sergey Khrapov , Alexander Khoperskov

The numerical simulation of multiphase flows involving dispersed components with large scale disparities, such as the collisions between millimeter-sized bubbles and micron-sized mineral particles in flotation, poses a significant…

Fluid Dynamics · Physics 2026-05-21 Linfeng Jiang , Enrico Calzavarini , Dominik Krug

High-fidelity simulations of unsteady fluid flow are now possible with advancements in high-performance computing hardware and software frameworks. Since computational fluid dynamics (CFD) computations are dominated by linear algebraic…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-02-28 Rahul Sundar , Dipanjan Majumdar , Chhote Lal Shah , Sunetra Sarkar

Processing large graphs with memory-limited GPU needs to resolve issues of host-GPU data transfer, which is a key performance bottleneck. Existing GPU-accelerated graph processing frameworks reduce the data transfers by managing the active…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-01 Qiange Wang , Xin Ai , Yanfeng Zhang , Jing Chen , Ge Yu

A computational method based on the non-linear Gaussian process (GP), known as deep Gaussian processes (deep GPs) for uncertainty quantification & propagation in modelling of flow through heterogeneous porous media is presented. The method…

Machine Learning · Statistics 2020-11-06 A. Daneshkhah , O. Chatrabgoun , M. Esmaeilbeigi , T. Sedighi , S. Abolfathi

This paper introduces open-source computational fluid dynamics software named open computational fluid dynamic code for scientific computation with graphics processing unit (GPU) system (OpenCFD-SCU), developed by the authors for direct…

Fluid Dynamics · Physics 2022-12-21 Guanlin Dang , Shiwei Liu , Tongbiao Guo , Junyi Duan , Xinliang Li

Stochastic modeling has become a popular approach to quantify uncertainty in flows through heterogeneous porous media. The uncertainty in heterogeneous structure properties is often parameterized by a high-dimensional random variable. This…

Numerical Analysis · Mathematics 2013-10-22 Lijian Jiang , J. David Moulton , Jia Wei

Porous media are ubiquitous in energy storage and conversion, catalysis, biomechanics, hydrogeology, as well as many other fields. These materials possess high surface-to-volume ratios and their complex channels can restrict and guide the…

We propose a GPU-accelerated distributed optimization algorithm for controlling multi-phase optimal power flow in active distribution systems with dynamically changing topologies. To handle varying network configurations and enable…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-01-15 Minseok Ryu , Geunyeong Byeon , Kibaek Kim

Fluid flow simulation is a highly active area with applications in a wide range of engineering problems and interactive systems. Meshless methods like the Moving Particle Semi-implicit (MPS) are a great alternative to deal efficiently with…

The increasing use of heterogeneous embedded systems with multi-core CPUs and Graphics Processing Units (GPUs) presents important challenges in effectively exploiting pipeline, task and data-level parallelism to meet throughput requirements…

Signal Processing · Electrical Eng. & Systems 2017-12-01 Shuoxin Lin , Jiahao Wu , Shuvra S. Bhattacharyya