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The quality of the part fabricated from the Additive Manufacturing (AM) process depends upon the process parameters used, and therefore, optimization is required for apt quality. A methodology is proposed to set these parameters…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Sunita Khod , Akshay Dvivedi , Mayank Goswami

This work presents a scalable computational framework for optimal design under uncertainty with application to multi-material insulation components of building envelopes. The forward model consists of a multi-phase thermo-mechanical model…

Optimization and Control · Mathematics 2023-04-20 Jingye Tan , Danial Faghihi

Accelerated proximal gradient methods have recently been developed for solving quasi-static incremental problems of elastoplastic analysis with some different yield criteria. It has been demonstrated through numerical experiments that these…

Optimization and Control · Mathematics 2020-11-13 Yoshihiro Kanno

Polymers, integral to advancements in high-tech fields, necessitate the study of their thermal conductivity (TC) to enhance material attributes and energy efficiency. The TC of polymers obtained by molecular dynamics (MD) calculations and…

Applied Physics · Physics 2024-04-02 Chunbo Lin , Han Zheng

The paper focuses on the stiffness modeling of heavy industrial robots with gravity compensators. The main attention is paid to the identification of geometrical and elastostatic parameters and calibration accuracy. To reduce impact of the…

Robotics · Computer Science 2013-11-28 Alexandr Klimchik , Yier Wu , Claire Dumas , Stéphane Caro , Benoît Furet , Anatol Pashkevich

A three-dimensional multi-scale computational homogenisation framework is developed for the prediction of nonlinear micro/meso-mechanical response of the fibre-reinforced polymer (FRP) composites. Two dominant damage mechanisms, i.e. matrix…

Computational Engineering, Finance, and Science · Computer Science 2016-10-18 Zahur Ullah , Lukasz Kaczmarczyk , Chris J. Pearce

Manipulating elasto-plastic objects remains a significant challenge due to severe self-occlusion, difficulties of representation, and complicated dynamics. This work proposes a novel framework for elasto-plastic object manipulation with a…

Robotics · Computer Science 2025-05-26 Zhen Zhang , Xiangyu Chu , Yunxi Tang , Lulu Zhao , Jing Huang , Zhongliang Jiang , K. W. Samuel Au

The aim of this work is to efficiently and robustly solve the statistical inverse problem related to the identification of the elastic properties at both macroscopic and mesoscopic scales of heterogeneous anisotropic materials with a…

Classical Physics · Physics 2020-06-29 Tianyu Zhang , Florent Pled , Christophe Desceliers

Constitutive modeling lies at the core of mechanics, allowing us to map strains onto stresses for a material in a given mechanical setting. Historically, researchers relied on phenomenological modeling where simple mathematical…

Computational Engineering, Finance, and Science · Computer Science 2024-08-28 Asghar A. Jadoon , Knut A. Meyer , Jan N. Fuhg

This work aims to model the hypersurface of the effective elastic modulus, \( E_{z, \text{eff}} \), and thickness, \( th_{\text{eff}} \), in corrugated boards. A Latin Hypercube Sampling (LHS) is followed by Gaussian Process Regression…

Applied Physics · Physics 2025-07-04 Ricardo Fitas

Plasticity is inherent to many engineering materials such as metals. While it can degrade the load-carrying capacity of structures via material yielding, it can also protect structures through plastic energy dissipation. To fully harness…

Computational Engineering, Finance, and Science · Computer Science 2025-02-05 Yingqi Jia , Xiaojia Shelly Zhang

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications,…

Materials Science · Physics 2016-08-29 Logan Ward , Ankit Agrawal , Alok Choudhary , Christopher Wolverton

Evaluating the mechanical response of fiber-reinforced composites can be extremely time consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input-output pairs and…

Materials Science · Physics 2024-10-03 Yixuan Sun , Imad Hanhan , Michael D. Sangid , Guang Lin

Woven fabrics play an essential role in everyday textiles for clothing/sportswear, water filtration, and retaining walls, to reinforcements in stiff composites for lightweight structures like aerospace, sporting, automotive, and marine…

Applied Physics · Physics 2023-11-27 Haotian Feng , Sabarinathan P Subramaniyan , Hridyesh Tewani , Pavana Prabhakar

Accurately estimating friction coefficients between arbitrary material pairs is critical for robotics, digital fabrication, and physics-based simulation, but exhaustive pairwise testing scales quadratically with the number of materials. We…

Robotics · Computer Science 2026-04-28 Zhendong Wang , Huamin Wang

The study is devoted to the geometrically nonlinear simulation of fiber-reinforced composite structures. The applicability of the multiplicative approach to the simulation of viscoelastic properties of a composite material is assessed,…

Applied Physics · Physics 2021-03-15 I. I. Tagiltsev , P. P. Laktionov , A. V. Shutov

Mesoscale simulations of woven composites using parameterized analytical geometries offer a way to connect constituent material properties and their geometric arrangement to effective composite properties and performance. However, the…

Materials Science · Physics 2023-02-21 Collin W. Foster , Lincoln N. Collins , Francesco Panerai , Scott A. Roberts

Fiber-reinforced soft biological tissues are typically modeled as hyperelastic, anisotropic, and nearly incompressible materials. To enforce incompressibility a multiplicative split of the deformation gradient into a volumetric and an…

Numerical Analysis · Mathematics 2022-04-13 Elias Karabelas , Matthias A. F. Gsell , Gundolf Haase , Gernot Plank , Christoph M. Augustin

Additive Manufacturing (AM) is a promising solution for handling the complexity of fabricating soft robots. However, the AM of hyperelastic materials is still challenging with a limited material range. Within this work, pellet-based 3D…

Robotics · Computer Science 2025-09-01 Nick Willemstein , Mohammad Ebrahim Imanian , Herman van der Kooij , Ali Sadeghi

In this article, a novel explicit approach for designing complex thin-walled structures based on the Moving Morphable Component (MMC) method is proposed, which provides a unified framework to systematically address various design issues,…

Graphics · Computer Science 2023-10-24 Wendong Huo , Chang Liu , Yunpu Liu , Zongliang Du , Weisheng Zhang , Xu Guo