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Computational fluid dynamics (CFD) is a valuable tool for personalised, non-invasive evaluation of hemodynamics in arteries, but its complexity and time-consuming nature prohibit large-scale use in practice. Recently, the use of deep…

Machine Learning · Computer Science 2022-01-21 Julian Suk , Pim de Haan , Phillip Lippe , Christoph Brune , Jelmer M. Wolterink

Fluid antenna systems (FAS) offer enhanced spatial diversity for next-generation wireless systems. However, acquiring accurate channel state information (CSI) remains challenging due to the large number of reconfigurable ports and the…

Information Theory · Computer Science 2025-05-09 Erqiang Tang , Wei Guo , Hengtao He , Shenghui Song , Jun Zhang , Khaled B. Letaief

A microfluidic approach to probing the first normal stress difference from single-point pressure measurements in transient shear flows is presented. Using an original experimental design, we examine the near-zero-mean pulsatile flow of…

Fluid Dynamics · Physics 2026-01-27 T. Rodrigues , F. J. Galindo-Rosales , L. Campo-Deaño

This study introduces a hybrid machine learning-based scale-bridging framework for predicting the permeability of fibrous textile structures. By addressing the computational challenges inherent to multiscale modeling, the proposed approach…

Machine Learning · Computer Science 2025-07-14 Denis Korolev , Tim Schmidt , Dinesh K. Natarajan , Stefano Cassola , David May , Miro Duhovic , Michael Hintermüller

We present a detailed comparison of the rheological behaviour of sheared sediment beds in a pressure-driven, straight channel configuration based on data that was generated by means of fully coupled, grain-resolved direct numerical…

Fluid Dynamics · Physics 2021-07-21 B. Vowinckel , E. Biegert , E. Meiburg , P. Aussillous , É. Guazzelli

Buoyant shear layers are encountered in many engineering and environmental applications and have been studied by researchers in the context of experiments and modeling for decades. Often, these flows have high Reynolds and Richardson…

Fluid Dynamics · Physics 2021-07-27 Naman Jain , Hieu T. Pham , Xinyi Huang , Sutanu Sarkar , Xiang Yang , Robert Kunz

Stress hotspots are regions of stress concentrations that form under deformation in polycrystalline materials. We use a machine learning approach to study the effect of preferred slip systems and microstructural features that reflect local…

Materials Science · Physics 2018-04-18 Ankita Mangal , Elizabeth A. Holm

The rapid advancement of machine learning techniques has led to their widespread application in various domains including water resources. However, snowmelt modeling remains an area that has not been extensively explored. In this study, we…

Machine Learning · Computer Science 2024-11-20 Ukesh Thapa , Bipun Man Pati , Samit Thapa , Dhiraj Pyakurel , Anup Shrestha

Stormwater infrastructures are decentralized urban water-management systems that face highly unsteady hydraulic and pollutant loadings from episodic rainfall-runoff events. Accurately evaluating their in-situ treatment performance is…

Computational Engineering, Finance, and Science · Computer Science 2025-07-08 Mohamed Shatarah , Kai Liu , Haochen Li

Material stress analysis is a critical aspect of material design and performance optimization. Under dynamic loading, the global stress evolution in materials exhibits complex spatiotemporal characteristics, especially in two-phase random…

Machine Learning · Computer Science 2025-05-06 Tengfei Xing , Xiaodan Ren , Jie Li

We introduce a novel approach to reveal ordering fluctuations in sheared dense suspensions, using line scanning in a combined rheometer and laser scanning confocal microscope. We validate the technique with a moderately dense suspension,…

Soft Condensed Matter · Physics 2022-11-04 Joia M. Miller , Daniel L. Blair , Jeffrey S. Urbach

This paper studies the effects of velocity gradients and secondary currents on the distribution of the shear force between the walls and bed of rectangular open channels. We show that neglecting the effect of secondary currents and assuming…

Fluid Dynamics · Physics 2017-09-22 Sasan Tavakkol , Amir Reza Zarrati

This work deals with the evaluation of the flow curve of colloidal systems that develop fluid phases with different mechanical properties, namely shear-banding fluids. The problem involved is that, as different fluid phases coexist in the…

Soft Condensed Matter · Physics 2007-05-23 Daniel Quemada , Claudio L. A. Berli

Simulating and predicting the water level/stage in river systems is essential for flood warnings, hydraulic operations, and flood mitigations. Physics-based detailed hydrological and hydraulic computational tools, such as HEC-RAS, MIKE, and…

An image-based deep learning framework is developed in this paper to predict damage and failure in microstructure-dependent composite materials. The work is motivated by the complexity and computational cost of high-fidelity simulations of…

Machine Learning · Computer Science 2022-06-07 Reza Sepasdar , Anuj Karpatne , Maryam Shakiba

Reliable river flow forecasting is an essential component of flood risk management and early warning systems. It enables improved emergency response coordination and is critical for protecting infrastructure, communities, and ecosystems…

Signal Processing · Electrical Eng. & Systems 2026-01-15 Gabriele Bertoli , Kai Schroeter , Rossella Arcucci , Enrica Caporali

An accurate sea clutter distribution is crucial for decision region determination when detecting sea-surface floating targets. However, traditional parametric models possibly have a considerable gap to the realistic distribution of sea…

Applications · Statistics 2018-09-10 Hongkuan Zhou , Yuzhou Li , Tao Jiang

Computational stress analysis is an important step in the design of material systems. Finite element method (FEM) is a standard approach of performing stress analysis of complex material systems. A way to accelerate stress analysis is to…

Materials Science · Physics 2023-01-02 Anindya Bhaduri , Ashwini Gupta , Lori Graham-Brady

Solving flow through porous media is a crucial step in the topology optimisation of cold plates, a key component in modern thermal management. Traditional computational fluid dynamics (CFD) methods, while accurate, are often prohibitively…

Fluid Dynamics · Physics 2026-03-10 Jinhong Wang , Matei C. Ignuta-Ciuncanu , Ricardo F. Martinez-Botas , Teng Cao

Granular materials show inhomogeneous flows characterized by strain localization. When strain is localized in a sheared granular material, rigid regions of a nearly undeformed state are separated by shear bands, where the material yields…

Soft Condensed Matter · Physics 2023-11-07 Aditya Pratap Singh , Vasileios Angelidakis , Thorsten Pöschel , Sudeshna Roy
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