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Calibrating and verifying crystal plasticity material models is a significant challenge, particularly for materials with a number of potential slip and twin systems. Here we use digital image correlation on coarse-grained $\alpha$-uranium…

Materials Science · Physics 2020-11-24 Nicolò Grilli , Philip Earp , Alan C. F. Cocks , James Marrow , Edmund Tarleton

This paper proposes a novel, more computationally efficient method for optimizing robot excitation trajectories for dynamic parameter identification, emphasizing self-collision avoidance. This addresses the system identification challenges…

Computer models are commonly used to represent a wide range of real systems, but they often involve some unknown parameters. Estimating the parameters by collecting physical data becomes essential in many scientific fields, ranging from…

Applications · Statistics 2020-05-27 Chih-Li Sung , Beau David Barber , Berkley J. Walker

This technical note considers the identification of nonlinear discrete-time systems with additive process noise but without measurement noise. In particular, we propose a method and its associated algorithm to identify the system nonlinear…

Optimization and Control · Mathematics 2015-04-27 Wei Pan , Ye Yuan , Jorge Gonçalves , Guy-Bart Stan

Stochastic, iterative search methods such as Evolutionary Algorithms (EAs) are proven to be efficient optimizers. However, they require evaluation of the candidate solutions which may be prohibitively expensive in many real world…

Neural and Evolutionary Computing · Computer Science 2013-03-12 Maumita Bhattacharya

In this study the common least-squares minimization approach is compared to the Bayesian updating procedure. In the content of material parameter identification the posterior parameter density function is obtained from its prior and the…

Data Analysis, Statistics and Probability · Physics 2024-08-12 Thomas Most

Contemporary material characterisation techniques that leverage deformation fields and the weak form of the equilibrium equations face challenges in the numerical solution procedure of the inverse characterisation problem. As material…

Designing topological materials with specific topological indices is a complex inverse problem, traditionally tackled through manual, intuition-driven methods that are neither scalable nor efficient for exploring the vast space of possible…

Mesoscale and Nanoscale Physics · Physics 2025-10-28 Samuel Bird , Chiara Devescovi , Pascal Engeler , Agnes Valenti , Doruk Efe Gökmen , Robin Worreby , Valerio Peri , Sebastian D. Huber

Hierarchically designed mechanical metamaterials involve nested levels of structural organization, mimicking natural structures (such as bones, wood, and bird feathers) to create advanced functional materials. Compositional hierarchy, a…

Soft Condensed Matter · Physics 2026-05-21 Shammo Dutta , Girish Krishnan , Sree Kalyan Patiballa

Concurrent multiscale finite element analysis (FE2) is a powerful approach for high-fidelity modeling of materials for which a suitable macroscopic constitutive model is not available. However, the extreme computational effort associated…

Numerical Analysis · Mathematics 2020-07-16 I. B. C. M. Rocha , P. Kerfriden , F. P. van der Meer

The increasing availability of full-field displacement data from imaging techniques in experimental mechanics is determining a gradual shift in the paradigm of material model calibration and discovery, from using several simple-geometry…

Computational Engineering, Finance, and Science · Computer Science 2025-07-01 Saeid Ghouli , Moritz Flaschel , Siddhant Kumar , Laura De Lorenzis

This paper deals with shape optimization for elastic materials under stochastic loads. It transfers the paradigm of stochastic dominance, which allows for flexible risk aversion via comparison with benchmark random variables, from…

Numerical Analysis · Mathematics 2016-07-01 Sergio Conti , Martin Rumpf , Rüdiger Schultz , Sascha Tölkes

The ability to engineer optimized protein variants has transformative potential for biotechnology and medicine. Prior sequence-based optimization methods struggle with the high-dimensional complexities due to the epistasis effect and the…

Artificial Intelligence · Computer Science 2026-01-19 Jiahao Wang , Shuangjia Zheng

This paper presents a reproducible and physically feasible dynamic parameter identification framework for CRANE-X7, a low-cost robot arm driven by modular smart actuators. To improve practical identifiability, products of inertia are…

Robotics · Computer Science 2026-05-18 Junji Oaki , Koki Yamane , Koki Inami , Sho Sakaino

In structural optimization, both parameters and shape are relevant for the model performance. Yet, conventional optimization techniques usually consider either parameters or the shape separately. This work addresses this problem by…

Optimization and Control · Mathematics 2025-03-18 Michael Wiesheu , Theodor Komann , Melina Merkel , Sebastian Schöps , Stefan Ulbrich , Idoia Cortes Garcia

Integrated Digital Image Correlation (IDIC) is nowadays a well established full-field experimental procedure for reliable and accurate identification of material parameters. It is based on the correlation of a series of images captured…

Data Analysis, Statistics and Probability · Physics 2018-10-22 O. Rokoš , J. P. M. Hoefnagels , R. H. J. Peerlings , M. G. D. Geers

The role of mechanics is known to be of primary order in many arterial diseases; however, determining mechanical properties of arteries remains a challenge. This paper discusses the identifiability of the passive mechanical properties of a…

Medical Physics · Physics 2012-04-09 Pierre Badel , Stéphane Avril , Susan Lessner , Michael A. Sutton

We develop mathematical models for shape design and topology optimization in structural contact problems involving friction between elastic and rigid bodies. The governing mechanical constraint is a nonlinear, non-smooth, and non-convex…

Optimization and Control · Mathematics 2025-12-17 Yixin Tan , Fang Feng , Shengfeng Zhu

Inverse problem for the identification of the parameters for large-scale systems of nonlinear ordinary differential equations (ODEs) arising in systems biology is analyzed. In a recent paper in \textit{Mathematical Biosciences, 305(2018),…

Quantitative Methods · Quantitative Biology 2020-12-07 Ugur G. Abdulla , Roby Poteau

We propose a method to accurately and efficiently identify the constitutive behavior of complex materials through full-field observations. We formulate the problem of inferring constitutive relations from experiments as an indirect inverse…

Materials Science · Physics 2024-12-05 Andrew Akerson , Aakila Rajan , Kaushik Bhattacharya
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