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Real-world applications of computational fluid dynamics often involve the evaluation of quantities of interest for several distinct geometries that define the computational domain or are embedded inside it. For example, design optimization…

Numerical Analysis · Mathematics 2023-08-08 Guglielmo Padula , Francesco Romor , Giovanni Stabile , Gianluigi Rozza

Fluid-structure interactions are a widespread phenomenon in nature. Although their numerical modeling have come a long way, the application of numerical design tools to these multiphysics problems is still lagging behind. Gradient-based…

Numerical Analysis · Mathematics 2021-09-27 Mohamed Abdelhamid , Aleksander Czekanski

Despite being vastly ignored in the literature, coping with topological noise is an issue of increasing importance, especially as a consequence of the increasing number and diversity of 3D polygonal models that are captured by devices of…

Graphics · Computer Science 2017-05-16 Asli Genctav , Yusuf Sahillioglu , Sibel Tari

Designing heterogeneous, self-assembling systems is a central challenge in soft matter and biology. We present a framework that uses gradient-based optimization to invert an analytical yield calculation, tuning systems toward target…

Soft Condensed Matter · Physics 2025-10-21 Livia A. J. Guttieres , Ryan K. Krueger , Remi Drolet , Michael P. Brenner

The latest sheet stamping processes enable efficient manufacturing of complex shape structural components that have high stiffness to weight ratios, but these processes can introduce defects. To assist component design for stamping…

Machine Learning · Computer Science 2022-02-09 Hamid Reza Attar , Alistair Foster , Nan Li

The development of accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges arise both in considering the appropriate model assumptions…

Machine Learning · Computer Science 2023-02-22 Jan N. Fuhg , Craig M. Hamel , Kyle Johnson , Reese Jones , Nikolaos Bouklas

Topology optimization (TO) serves as a widely applied structural design approach to tackle various engineering problems. Nevertheless, sensitivity-based TO methods usually struggle with solving strongly nonlinear optimization problems. By…

Machine Learning · Computer Science 2025-06-16 Jun Yang , Shintaro Yamasaki

In recent years, significant advancements have been made in computational methods for analyzing masonry structures. Within the Finite Element Method, two primary approaches have gained traction: Micro and Macro Scale modeling, and their…

Computational Engineering, Finance, and Science · Computer Science 2024-09-02 Alejandro Cornejo , Philip Kalkbrenner , Riccardo Rossi , Luca Pelà

In affine formation control problems, the construction of the framework with universal rigidity and affine localizability is a critical prerequisite, but it has not yet been well addressed, especially when additional agents join the…

Systems and Control · Electrical Eng. & Systems 2025-06-05 Huiming Li , Hao Chen , Xiangke Wang , Zhongkui Li , Lincheng Shen

Topology design optimization offers tremendous opportunity in design and manufacturing freedoms by designing and producing a part from the ground-up without a meaningful initial design as required by conventional shape design optimization…

Machine Learning · Statistics 2019-01-10 Sharad Rawat , M. H. Herman Shen

Generative modeling is typically framed as learning mapping rules, but from an observer's perspective without access to these rules, the task becomes disentangling the geometric support from the probability distribution. We propose that…

Machine Learning · Statistics 2025-12-04 Rui Tong

Pixel- and voxel-based representations of microstructures obtained from tomographic imaging methods is an established standard in computational materials science. The corresponding highly resolved, uniform discretitization in numerical…

Numerical Analysis · Mathematics 2019-08-27 Andreas Fischer , Bernhard Eidel

Localized features such as singularities, sharp gradients, discontinuities, and moving sources require adaptive finite element discretizations. Conventional refinement strategies introduce significant computational overhead through…

Computational Engineering, Finance, and Science · Computer Science 2026-04-29 Jan Niklas Schmäke , Martin Ruess

Multi-cellular robot design aims to create robots comprised of numerous cells that can be efficiently controlled to perform diverse tasks. Previous research has demonstrated the ability to generate robots for various tasks, but these…

Artificial Intelligence · Computer Science 2023-12-04 Heng Dong , Junyu Zhang , Chongjie Zhang

We present a novel framework for PDE-constrained $r$-adaptivity of high-order meshes. The proposed method formulates mesh movement as an optimization problem, with an objective function defined as a convex combination of a mesh quality…

Numerical Analysis · Mathematics 2025-07-03 Tzanio Kolev , Boyan Lazarov , Ketan Mittal , Mathias Schmidt , Vladimir Tomov

Persistent Homology (PH) offers stable, multi-scale descriptors of intrinsic shape structure by capturing connected components, loops, and voids that persist across scales, providing invariants that complement purely geometric…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Prachi Kudeshia , Jiju Poovvancheri , Amr Ghoneim , Dong Chen

We propose an algorithm for the computational homogenization of locally periodic hyperelastic structures undergoing large deformations due to external quasi-static loading. The algorithm performs clustering of macroscopic deformations into…

Numerical Analysis · Mathematics 2026-02-26 Vladimír Lukeš , Eduard Rohan

We develop a new optimisation technique that combines multiresolution subdivision surfaces for boundary description with immersed finite elements for the discretisation of the primal and adjoint problems of optimisation. Similar to wavelets…

Numerical Analysis · Mathematics 2016-01-20 Kosala Bandara , Thomas Rüberg , Fehmi Cirak

For domains that involve numerical simulation, it can be computationally expensive to run an ensemble of simulations spanning a parameter space of interest to a user. To this end, an attractive surrogate for simulation is the generative…

Machine Learning · Computer Science 2025-05-13 Xiaohan Wang , Matthew Berger

Persistent homology is a powerful tool for characterizing the topology of a data set at various geometric scales. When applied to the description of molecular structures, persistent homology can capture the multiscale geometric features and…

Quantitative Methods · Quantitative Biology 2018-07-31 Zixuan Cang , Guo-Wei Wei
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