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Related papers: Structure-Property Linkage in Shocked Multi-Materi…

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Quantitative structure-property relationships are crucial for the understanding and prediction of the physical properties of complex materials. For fluid flow in porous materials, characterizing the geometry of the pore microstructure…

Soft Condensed Matter · Physics 2020-09-21 Magnus Röding , Zheng Ma , Salvatore Torquato

Surface heterogeneity, particularly complex patterns of surface heating, significantly influences mesoscale atmospheric flows, yet observational constraints and modeling limitations have hindered comprehensive understanding and model…

Atmospheric and Oceanic Physics · Physics 2025-11-10 Tyler Waterman , Peter Germ , Marc Calaf , Eric Pardyjak , Nathaniel Chaney

The developed computational approach is capable of initiating and propagating cracks inside materials and along material interfaces of general multi-domain structures under quasi-static conditions. Special attention is paid to particular…

Computational Engineering, Finance, and Science · Computer Science 2023-08-23 Roman Vodička

Data-driven approaches to inferring the local structures responsible for plasticity in amorphous materials have made substantial contributions to our understanding of the failure, flow, and rearrangement dynamics of supercooled fluids. Some…

Soft Condensed Matter · Physics 2023-08-22 Tomilola M. Obadiya , Daniel M. Sussman

Topological Interlocking Structures (TIS) are assemblies of interlocking building blocks that hold together solely through contact and friction at the blocks' interfaces, and thus do not require any connective elements. This salient feature…

Soft Condensed Matter · Physics 2022-10-26 Shai Feldfogel , Konstantinos Karapiperis , Jose Andrade , David S. Kammer

Graph mining analyzes real-world graphs to find core substructures (connected subgraphs) in applications modeled as graphs. Substructure discovery is a process that involves identifying meaningful patterns, structures, or components within…

Social and Information Networks · Computer Science 2025-04-29 Arshdeep Singh , Abhishek Santra , Sharma Chakravarthy

Morphogenesis emerges from dynamic feedback among geometry, mechanics, and chemistry; however, disentangling these contributions in living systems remains challenging. Here, we focus on the interplay between geometry and mechanics by…

The interaction between a turbulent convective boundary layer (CBL) and the underlying land surface is an important research problem in the geosciences. In order to model this interaction adequately, it is necessary to develop tools which…

Data Analysis, Statistics and Probability · Physics 2019-06-10 José Licón-Saláiz , Cedrick Ansorge

In turbulent flows, energy production is associated with highly organized structures, known as coherent structures. Since these structures are three-dimensional, their detection remains challenging in the most common situation, when…

Fluid Dynamics · Physics 2023-09-12 Subharthi Chowdhuri , Tirtha Banerjee

We derive general depth-integrated model equations for overland flows featuring the evolution of suspended sediment that may be eroded from or deposited onto the underlying topography ('morphodynamics'). The resulting equations include…

Fluid Dynamics · Physics 2023-06-29 Jake Langham , Mark J. Woodhouse , Andrew J. Hogg , Luke T. Jenkins , Jeremy C. Phillips

The versatile physical properties of heterogeneous materials are intimately related to their complex microstructures, which can be statistically characterized and modelled using various spatial correlation functions containing key…

Materials Science · Physics 2019-10-01 Yang Jiao

This paper presents a general and robust method for the fluid-structure interaction of membranes and shells undergoing large displacement and large added-mass effects by coupling an immersed-boundary method with a shell finite-element…

Fluid Dynamics · Physics 2023-08-15 Marin Lauber , Gabriel D. Weymouth , Georges Limbert

We introduce a new measure of the structure of a liquid which is the softness of the mean-field potential developed by us earlier. We find that this softness is sensitive to small changes in the structure. We then study its correlation with…

Soft Condensed Matter · Physics 2021-05-26 Manoj Kumar Nandi , Sarika Maitra Bhattacharyya

A three-dimensional SPH computational framework is presented for modeling fluid-structure interactions with structural deformation and failure. We combine weakly compressible SPH with a pseudo-spring-based SPH solver to capture the fluid…

Computational Engineering, Finance, and Science · Computer Science 2025-07-16 Vishabjeet Singh , Chong Peng , Md Rushdie Ibne Islam

Soft particles such as microgels and core-shell particles can undergo significant and anisotropic deformations when adsorbed to a liquid interface. This, in turn, leads to a complex phase behavior upon compression. Here we develop a…

This work presents a rigorous mathematical formulation for topology optimization of a macrostructure undergoing ductile failure. The prediction of ductile solid materials which exhibit dominant plastic deformation is an intriguingly…

Numerical Analysis · Mathematics 2023-03-22 Nima Noii , Hassan Ali Jahangiry , Haim Waisman

Robotic manipulation tasks, such as object rearrangement, play a crucial role in enabling robots to interact with complex and arbitrary environments. Existing work focuses primarily on single-level rearrangement planning and, even if…

Robotics · Computer Science 2023-09-07 Manav Kulshrestha , Ahmed H. Qureshi

A spatiotemporal deep learning framework is proposed that is capable of 2D full-field prediction of fracture in concrete mesostructures. This framework not only predicts fractures but also captures the entire history of the fracture…

Computational Engineering, Finance, and Science · Computer Science 2024-07-25 Rasoul Najafi Koopas , Shahed Rezaei , Natalie Rauter , Richard Ostwald , Rolf Lammering

Dynamic heterogeneity as one of the most important properties in supercooled liquids has been found for several decades. However, its structural origin remains open for many systems. Here, we propose a new structural parameter to…

Disordered Systems and Neural Networks · Physics 2015-10-16 S. P. Pan , S. D. Feng , J. W. Qiao , W. M. Wang , J. Y. Qin

Establishing reliable and interpretable structure-property relationships in glasses is a longstanding challenge in condensed matter physics. While modern data-driven machine learning techniques have proven highly effective in establishing…

Disordered Systems and Neural Networks · Physics 2026-02-06 Chenyan Wang , Mouyang Cheng , Ji Chen
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