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In nature, limbless locomotion is adopted by a wide range of organisms at various length scales. Interestingly, undulatory, crawling and inching/looping gait constitutes a fundamental class of limbless locomotion and is often observed in…

Optimization and Control · Mathematics 2023-07-28 Ashutosh Bijalwan , Jose J Munoz

Prandtl-Tomlinson (PT) model has been very successful in explaining nanoscale friction in a variety of situations. However, the simplistic PT model, on account of having a point mass being dragged across a sinusoidal force field, cannot be…

Statistical Mechanics · Physics 2020-04-22 Avirup Sircar , Puneet Kumar Patra

The accurate characterization of tire dynamics is critical for advancing control strategies in autonomous road vehicles, as tire behavior significantly influences handling and stability through the generation of forces and moments at the…

Systems and Control · Electrical Eng. & Systems 2026-02-12 Luigi Romano , Ole Morten Aamo , Jan Åslund , Erik Frisk

We discover a qualitatively new behavior for systems where the load transfer has limiting stress amplification as in real fiber composites. We find that the disorder is a relevant field leading to tri--criticality, separating a first-order…

Condensed Matter · Physics 2009-10-28 J. V. Andersen , D. Sornette , K. -T. Leung

Disorder and long-range interactions are two of the key components that make material failure an interesting playfield for the application of statistical mechanics. The cornerstone in this respect has been lattice models of the fracture in…

Statistical Mechanics · Physics 2009-11-11 Mikko J. Alava , Phani K. V. V. Nukala , Stefano Zapperi

Soft polymers are ubiquitous materials in nature and as engineering materials with properties varying from rate-independent to rate-dependent. Current fracture toughness measures are non-unique for rate-dependent soft materials for varying…

Soft Condensed Matter · Physics 2026-03-17 Aditya Konale , Vikas Srivastava

We study three different experiments that involve dry friction and periodic driving, and which employ both single and many-particle systems. These experimental set-ups, besides providing a playground for investigation of frictional effects,…

Statistical Mechanics · Physics 2022-04-29 Soumen Das , Shankar Ghosh , Shamik Gupta

Monitoring the atmospheric dispersion of pollutants is increasingly critical for environmental impact assessments. High-fidelity computational models are often employed to simulate plume dynamics, guiding decision-making and prioritizing…

Fluid Dynamics · Physics 2026-01-14 Ike Griss Salas , Megan R. Ebers , Jake Stevens-Haas , J. Nathan Kutz

We propose and analyze a linear and partitioned finite element method for fluid-shell interactions under the arbitrary Lagrangian-Eulerian (ALE) framework. We adopt the P1-bubble/P1/P1 elements for the fluid velocity, pressure, and…

Numerical Analysis · Mathematics 2026-01-07 Bangwei She , Tian Tian , Karel Tuma

We introduce a data-driven method for learning the equations of motion of mechanical systems directly from position measurements, without requiring access to velocity data. This is particularly relevant in system identification tasks where…

Systems and Control · Electrical Eng. & Systems 2025-05-28 Martine Dyring Hansen , Elena Celledoni , Benjamin Kwanen Tapley

Dynamic logit models are popular tools in economics to measure state dependence. This paper introduces a new method to derive moment restrictions in a large class of such models with strictly exogenous regressors and fixed effects. We…

Econometrics · Economics 2023-12-05 Kevin Dano

The interaction of crack fronts with asperities is central to the criteria of fracture in heterogeneous materials and for predicting fracture surface formation. It is known how dynamic crack fronts respond to small, 1st-order,…

Soft Condensed Matter · Physics 2025-09-17 Itamar Kolvin , Mokhtar Adda-Bedia

Fractional differential equations (FDEs) are an extension of the theory of fractional calculus. However, due to the difficulty in finding analytical solutions, there have not been extensive applications of FDEs until recent decades. With…

Numerical Analysis · Mathematics 2020-07-20 Nirupama Bhattacharya , Gabriel A. Silva

This paper exposes a novel exploratory formalism, which end goal is the numerical simulation of the dynamics of a cloud of particles weakly or strongly coupled with a turbulent fluid. Giventhe large panel of expertise of the list of…

Analysis of PDEs · Mathematics 2019-10-21 Ludovic Goudenège , Adam Larat , Julie Llobell , Marc Massot , David Mercier , Olivier Thomine , Aymeric Vié

Reduced-order models of flame dynamics can be used to predict and mitigate the emergence of thermoacoustic oscillations in the design of gas turbine and rocket engines. This process is hindered by the fact that these models, although often…

Fluid Dynamics · Physics 2020-07-07 Hans Yu , Matthew P. Juniper , Luca Magri

With the maturation of differentiable physics, its role in various downstream applications: such as model predictive control, robotic design optimization, and neural PDE solvers, has become increasingly important. However, the derivative…

Robotics · Computer Science 2025-09-26 Xiaohan Ye , Kui Wu , Zherong Pan , Taku Komura

The complexity of the frictional dynamics at the microscopic scale makes difficult to identify all of its controlling parameters. Indeed, experiments on sheared elastic bodies have shown that the static friction coefficient depends on…

The fragmentation of small, brittle, flexible, inextensible fibers is investigated in a fully-developed, homogeneous, isotropic turbulent flow. Such small fibers spend most of their time fully stretched and their dynamics follows that of…

Soft Condensed Matter · Physics 2019-12-17 Sofía Allende , Christophe Henry , Jérémie Bec

Understanding how stick-slip dynamics manifests in diverse physical conditions is a crucial topic in tribology. Although it has been extensively studied in simple frictional configurations, the characterization of stick-slip behavior in…

Soft Condensed Matter · Physics 2026-02-17 A. Plati , F. Restagno , C. Poulard

Diffusion models provide expressive priors for forecasting trajectories of dynamical systems, but are typically unreliable in the sparse data regime. Physics-informed machine learning (PIML) improves reliability in such settings; however,…

Machine Learning · Computer Science 2026-01-30 Kaiyuan Tan , Kendra Givens , Peilun Li , Thomas Beckers