continuum physics
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Related Articles from SNS
Exact Boundary Enforcement Along Implicit Geometries for Physics-Informed, Deep Learning Problems in Continuum Mechanics
arXiv:2606.07579v1 Announce Type: new Abstract: Solutions to well-posed problems in continuum mechanics are continuously dependent upon prescribed boundary conditions. Because of this, variations in the enforcement of boundary data can impact the reliability of inversion techniques that rely on efficient and accurate forward models. To this end, it is necessary to understand how specific boundary implementation techniques can affect the performance of a given forward model.
Mesh Field Theory: Port-Hamiltonian Formulation of Mesh-Based Physics
Announce Type: replace Abstract: We present Mesh Field Theory (MeshFT) and its neural realization, MeshFT-Net: a structure-preserving framework for mesh-based continuum physics that cleanly separates the physics' topological structure from its metric structure. Imposing minimal physical principles (locality, permutation equivariance, orientation covariance, and energy balance/dissipation inequality), we prove a reduction theorem for mesh-based physics. Under these conditions, the physical...
A novel large-strain kinematic framework for fiber-reinforced laminated composites and its application in the characterization of damage
arXiv:2512.22285v2 Announce Type: replace Abstract: In this paper, a novel kinematic framework for fiber-reinforced composite materials is presented. For this purpose, we use the multiple natural configurations in conjunction with the multi-continuum theory of Bedford and Stern~(1972). Keeping the underlying physics of the proposed kinematics consistent.
TransportBench: A Comprehensive Benchmark for Non-Equilibrium Flow Transport
Announce Type: new Abstract: Scientific machine learning models, as versatile tools for numerical simulation and analysis, are increasingly transforming the landscape of fluid mechanics research. However, existing datasets and benchmarks are primarily limited to continuum fluids and provide limited support for non-equilibrium transport phenomena. To address this gap, we present TransportBench, a high-fidelity dataset and standardized benchmark for non-equilibrium flow transport, designed to...
UniPixie: Unified and Probabilistic 3D Physics Learning via Flow Matching
arXiv:2606.05399v1 Announce Type: new Abstract: Existing feed-forward networks excel at predicting a single set of physical properties from visual appearance, but this point-estimate paradigm fundamentally fails to capture the real world's inherent physical ambiguity. We address this by reframing physics prediction as a task of learning a controllable, continuous distribution of material properties. We introduce UNIPIXIE, a framework trained to predict a continuous and parameterized path of...
Immiscible two-phase flow in porous media: a statistical mechanics approach
arXiv:2603.09658v2 Announce Type: replace Abstract: The central problem in the physics of immiscible two-phase flow in porous media is to find a proper description of the flow at scales large enough so that the medium may be regarded as a continuum: the scale-up problem. So far, the only workable approach to the multiphase flow scale-up problem has been a set of phenomenological equations that have obvious weaknesses. Attempts at going beyond this relative permeability theory have so far not...
Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence
arXiv:2606.01470v1 Announce Type: new Abstract: Whether physics foundation models can be usefully deployed on laboratory experiments remains an open question for scientific machine learning (ML). We test this question on the Rayleigh-Taylor instability (RTI), a ubiquitous and demanding fluid instability seen from tabletop flows to supernova explosions, in which small perturbations at a density interface grow into chaotic, multiscale mixing as a lighter fluid accelerates into a heavier one....
Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence
arXiv:2606.01470v1 Announce Type: cross Abstract: Whether physics foundation models can be usefully deployed on laboratory experiments remains an open question for scientific machine learning (ML). We test this question on the Rayleigh-Taylor instability (RTI), a ubiquitous and demanding fluid instability seen from tabletop flows to supernova explosions, in which small perturbations at a density interface grow into chaotic, multiscale mixing as a lighter fluid accelerates into a heavier one....
The Choreography of Augmented Reality Timelines: Studying the Relative Position, Chronology, & Situatedness of Event Sequences
Announce Type: new Abstract: Timelines are effective ways to tell historical and personal stories. However, most timeline visualization tools impose an inflexible model of time prioritizing chronological clarity. On the other hand, unconstrained representations can better capture the irregular and contextual nature of lived time, but often at the cost of interpretability.
Unstructured Mesh Tools for Fusion Energy System Design
new Abstract: The execution of accurate simulations of fusion energy systems requires the appropriate representation of critical component geometries as well as the coupling of complex fusion physics codes with one another and with engineering analysis tools. This paper examines the challenges of creating simulation workflows that fully leverage existing fusion research codes while integrating them with commercial computer-aided engineering (CAE) software. Key areas addressed include: (a)...