English
Related papers

Related papers: Cutting force prediction based on a curved uncut c…

200 papers

Carbon fiber-reinforced composites (CFRC) are pivotal in advanced engineering applications due to their exceptional mechanical properties. A deep understanding of CFRC behavior under mechanical loading is essential for optimizing…

Machine Learning · Computer Science 2025-04-22 Zeping Chen , Marwa Yacouti , Maryam Shakiba , Jian-Xun Wang , Tengfei Luo , Vikas Varshney

Crack-templated networks, metallic frameworks fabricated from crack patterns in sacrificial thin films, can exhibit high optical transmittance, high electric conductivity, and a host of other properties attractive for applications. Despite…

Applied Physics · Physics 2022-06-08 Jaeuk Kim , Thomas M. Truskett

Machine learning force fields possess unprecedented potential in achieving both accuracy and efficiency in molecular simulations. Nevertheless, their application in organic systems is often hindered by structural collapse during simulation…

Computational Physics · Physics 2026-02-03 Junbao Hu , Dingyu Hou , Jian Jiang

The force transmitted from the front tires and tie rods to the steering rack of a vehicle, called the rack force, significantly influences the torque experienced by a driver at the steering wheel. As a result, estimates of rack force are…

Systems and Control · Electrical Eng. & Systems 2021-04-29 Akshay Bhardwaj , Daniel Slavin , John Walsh , James Freudenberg , R. Brent Gillespie

In this contribution a method is introduced that allows for a linkage between the process-induced structural damage and the fracture behaviour. Based on an anisotropic elastic material model, different modelling approaches for initial…

Applied Physics · Physics 2020-06-30 Benjamin Schmidt , Michael Rose , Martina Zimmermann , Markus Kästner

The problem of finding what direction cracks should move is not completely solved. A commonly accepted way to predict crack directions is by computing the density of elastic potential energy stored well away from the crack tip, and finding…

Soft Condensed Matter · Physics 2009-11-10 Michael Marder

While crack nucleation and propagation in the brittle or quasi-brittle regime can be predicted via variational or material-force-based phase field fracture models, these models often assume that the underlying elastic response of the…

Computational Engineering, Finance, and Science · Computer Science 2020-08-13 Hyoung Suk Suh , WaiChing Sun , Devin O'Connor

Simulations involving the Lennard-Jones potential usually employ a cut-off at $r=2.5\sigma$. This paper investigates the possibility of reducing the cut-off. Two different cut-off implementations are compared, the standard shifted potential…

Soft Condensed Matter · Physics 2013-01-29 Søren Toxvaerd , Jeppe C. Dyre

The shape of a crack front propagating through a thin sample is studied using a phase field model. The model is shown to have a well defined sharp interface limit. The crack front is found to be an ellipse with large axis the width of the…

Materials Science · Physics 2010-12-07 Hervé Henry

This paper discusses a novel data-driven nonlinearity identification method for mechanical systems with nonlinear restoring forces such as polynomial, piecewise-linear, and general displacement-dependent nonlinearities. The proposed method…

Dynamical Systems · Mathematics 2026-03-18 Akira Saito , Hiromu Fujita

Model predictive control (MPC) is a promising technique for motion cueing in driving simulators, but its high computation time limits widespread real-time application. This paper proposes a hybrid algorithm that combines filter-based and…

Robotics · Computer Science 2023-09-06 Vishrut Jain , Andrea Lazcano , Riender Happee , Barys Shyrokau

Cell formation is a critical step in the design of cellular manufacturing systems. Recently, it was tackled using a cut-based-graph-partitioning model. This model meets real-life production systems requirements as it uses the actual amount…

Discrete Mathematics · Computer Science 2016-12-19 Boulif Menouar

A new predictor-corrector type incremental algorithm is proposed for the exact construction of weighted straight skeletons of 2D general planar polygons of arbitrary complexity based on the notion of deforming polygon. In the proposed…

Computational Geometry · Computer Science 2020-11-18 Baris Irhan

Predictive modelling represents an emerging field that combines existing and novel methodologies aimed to rapidly understand physical mechanisms and concurrently develop new materials, processes and structures. In the current study,…

Model compression is crucial for deployment of neural networks on devices with limited computational and memory resources. Many different methods show comparable accuracy of the compressed model and similar compression rates. However, the…

Machine Learning · Computer Science 2020-08-21 Ben Mussay , Daniel Feldman , Samson Zhou , Vladimir Braverman , Margarita Osadchy

Computational solid mechanics has become an indispensable approach in engineering, and numerical investigation of fracture in composites is essential as composites are widely used in structural applications. Crack evolution in composites is…

Materials Science · Physics 2023-09-26 Hao Xu , Wei Fan , Ambrose C. Taylor , Dongxiao Zhang , Lecheng Ruan , Rundong Shi

The present work introduces a novel numerical approach for the process modeling of fiber-reinforced thermoset polymers at the micro-scale level, that can be used to predict curing-induced residual stresses. The cure kinetics is described…

Applied Physics · Physics 2022-12-14 Manish H. Nagaraj , Marianna Maiaru

Estimating the forces acting between instruments and tissue is a challenging problem for robot-assisted minimally-invasive surgery. Recently, numerous vision-based methods have been proposed to replace electro-mechanical approaches.…

Computer Vision and Pattern Recognition · Computer Science 2020-08-07 Nils Gessert , Marcel Bengs , Matthias Schlüter , Alexander Schlaefer

Statistically correcting measured cross sections for detector effects is an important step across many applications. In particle physics, this inverse problem is known as unfolding. In cases with complex instruments, the distortions they…

In material science, models are derived to predict emergent material properties (e.g. elasticity, strength, conductivity) and their relations to processing conditions. A major drawback is the calibration of model parameters that depend on…

Neural and Evolutionary Computing · Computer Science 2021-11-22 Gabriel Kronberger , Evgeniya Kabliman , Johannes Kronsteiner , Michael Kommenda