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Membrane filtration is widely used in water treatment to remove foulants from contaminated water. Foulant build-up on the membrane occludes the area open for fluid flow, which impairs the efficiency of the filtration operation by decreasing…

Fluid Dynamics · Physics 2025-10-29 Abigail Rose Drumm , Francesca Bernardi

Computational modeling of the melt pool dynamics in laser-based powder bed fusion metal additive manufacturing (PBF-LB/M) promises to shed light on fundamental mechanisms of defect generation. These processes are accompanied by rapid…

Computational Engineering, Finance, and Science · Computer Science 2026-03-05 Nils Much , Magdalena Schreter-Fleischhacker , Peter Munch , Martin Kronbichler , Wolfgang A. Wall , Christoph Meier

The conditional particle filter (CPF) is a promising algorithm for general hidden Markov model smoothing. Empirical evidence suggests that the variant of CPF with backward sampling (CBPF) performs well even with long time series. Previous…

Computation · Statistics 2019-08-29 Anthony Lee , Sumeetpal S. Singh , Matti Vihola

Accurate representation of interfaces and flux exchange is vital for coupled multiphysics simulations across a broad range of applications. Currently, coupling approaches are limited by the underlying discretization or to specific physical…

Fluid Dynamics · Physics 2026-03-10 Ethan Huff , Savio J. Poovathingal

A filtration procedure was developed to measure the reversibility of fouling during cross-flow filtration based on the square wave of applied pressure. The principle of this method, the apparatus required, and the associated mathematical…

Soft Condensed Matter · Physics 2008-01-18 Benjamin Espinasse , Patrice Bacchin , Pierre Aimar

Conditional particle filters (CPFs) with backward/ancestor sampling are powerful methods for sampling from the posterior distribution of the latent states of a dynamic model such as a hidden Markov model. However, the performance of these…

Computation · Statistics 2023-06-21 Santeri Karppinen , Sumeetpal S. Singh , Matti Vihola

MeanFlow (MF) has recently been established as a framework for one-step generative modeling. However, its ``fastforward'' nature introduces key challenges in both the training objective and the guidance mechanism. First, the original MF's…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Zhengyang Geng , Yiyang Lu , Zongze Wu , Eli Shechtman , J. Zico Kolter , Kaiming He

The Phase-Field Method (PFM) is employed to simulate two-phase flows with the fully-coupled Cahn-Hilliard-Navier-Stokes (CHNS) equations governing the temporal evolution. The methodology minimizes the total energy functional, accounting for…

Generative models based on dynamical equations such as flows and diffusions offer exceptional sample quality, but require computationally expensive numerical integration during inference. The advent of consistency models has enabled…

Machine Learning · Computer Science 2025-06-04 Nicholas M. Boffi , Michael S. Albergo , Eric Vanden-Eijnden

We present a comprehensive comparative study of three generative modeling paradigms: Denoising Diffusion Probabilistic Models (DDPM), Conditional Flow Matching (CFM), and MeanFlow. While DDPM and CFM require iterative sampling, MeanFlow…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Umang Agarwal , Rudraksh Sangore , Sumit Laddha

Microfiltration technology is a widely used engineering strategy for fresh water production and water treatment. The major concern in many applications is the formation of a biological fouling layer leading to increased hydraulic resistance…

Biological Physics · Physics 2021-04-12 V. Luongo , M. R. Mattei , L. Frunzo , B. D'Acunto , K. Gupta , S. Chellam , N. G. Cogan

A computational fluid dynamics (CFD) simulation framework for fluid-flow prediction is developed on the Tensor Processing Unit (TPU) platform. The TPU architecture is featured with accelerated dense matrix multiplication, large high…

Computational Physics · Physics 2022-03-02 Qing Wang , Matthias Ihme , Yi-Fan Chen , John Anderson

We are interested in learning generative models for complex geometries described via manifolds, such as spheres, tori, and other implicit surfaces. Current extensions of existing (Euclidean) generative models are restricted to specific…

Machine Learning · Statistics 2021-11-04 Noam Rozen , Aditya Grover , Maximilian Nickel , Yaron Lipman

Fluid approximations have seen great success in approximating the macro-scale behaviour of Markov systems with a large number of discrete states. However, these methods rely on the continuous-time Markov chain (CTMC) having a particular…

Systems and Control · Electrical Eng. & Systems 2019-10-29 Michalis Michaelides , Jane Hillston , Guido Sanguinetti

Granular flows govern many natural and industrial processes, yet their interior kinematics and mechanics remain largely unobservable, as experiments access only boundaries or free surfaces. Conventional numerical simulations are…

Computational Engineering, Finance, and Science · Computer Science 2026-05-26 Xuyang Li , Rui Li , Teng Man , Yimin Lu

This study develops a polygonal cell-based smoothed finite element method (CSFEM) for two-dimensional seepage analyses in porous media, covering steady-state, transient, and free-surface problems. Wachspress interpolation on convex…

Numerical Analysis · Mathematics 2026-02-19 Yang Yang , Mingjiao Yan , Zongliang Zhang , Yinpeng Yin , Qiang Liu , You liang Li

Continuous normalizing flows (CNFs) are an attractive generative modeling technique, but they have been held back by limitations in their simulation-based maximum likelihood training. We introduce the generalized conditional flow matching…

Membrane ultrafiltration (UF) is a pressure driven process allowing for the separation and enrichment of protein solutions and dispersions of nanosized microgel particles. The permeate flux and the near-membrane concentration-polarization…

Soft Condensed Matter · Physics 2015-05-19 Rafael Roa , Emiliy K. Zholkovskiy , Gerhard Nägele

For consensus on measurement-based distributed filtering (CMDF), through infinite consensus fusion operations during each sampling interval, each node in the sensor network can achieve optimal filtering performance with centralized…

Systems and Control · Electrical Eng. & Systems 2022-05-24 Jiachen Qian , Peihu Duan , Zhisheng Duan , Guanrong Chen , Ling Shi

We adapt and extend a formulation for soluble surfactant transport in multiphase flows recently presented by Muradoglu & Tryggvason (JCP 274 (2014) 737-757) to the context of the Level Contour Reconstruction Method (Shin et al. IJNMF 60…

Computational Engineering, Finance, and Science · Computer Science 2018-03-14 Seungwon Shin , Jalel Chergui , Damir Juric , Lyes Kahouadji , Omar K. Matar , Richard V. Craster
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