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An additive manufacturing (AM) process often produces a {\it near-net} shape that closely conforms to the intended design to be manufactured. It sometimes contains additional support structure (also called scaffolding), which has to be…

Computational Geometry · Computer Science 2019-05-30 Saigopal Nelaturi , Morad Behandish , Amir M. Mirzendehdel , Johan de Kleer

Auxetic materials are characterized by a negative Poisson's ratio, $\mathrm{\nu}$. As the Poisson's ratio becomes negative and approaches the lower isotropic mechanical limit of $\mathrm{\nu = -1}$, materials show enhanced resistance to…

Soft Condensed Matter · Physics 2023-11-08 Daniel R. Reid , Nidhi Pashine , Alec S. Bowen , Sidney R. Nagel , Juan J. de Pablo

Movable antennas (MA) are a novel technology that allows for the flexible adjustment of antenna positions within a specified region, thereby enhancing the performance of wireless communication systems. In this paper, we explore the use of…

Signal Processing · Electrical Eng. & Systems 2025-11-25 Weijie Xiong , Kai Zhong , Zhiling Xiao , Jingran Lin , Qiang Li

Due to lack of data, overfitting ubiquitously exists in real-world applications of deep neural networks (DNNs). We propose advanced dropout, a model-free methodology, to mitigate overfitting and improve the performance of DNNs. The advanced…

Machine Learning · Computer Science 2021-08-11 Jiyang Xie , Zhanyu Ma , and Jianjun Lei , Guoqiang Zhang , Jing-Hao Xue , Zheng-Hua Tan , Jun Guo

Despite their outstanding mechanical properties, with many industrial applications, a rational and systematic design of new and controlled auxetic materials remains poorly developed. Here a unified framework is established to describe…

Soft Condensed Matter · Physics 2021-06-28 Daniel Acuna , Francisco Gutiérrez , Rodrigo Silva , Humberto Palza , Alvaro S. Nunez , Gustavo Düring

Bayesian optimization (BO) is a widely used algorithm for solving expensive black-box optimization problems. However, its performance decreases significantly on high-dimensional problems due to the inherent high-dimensionality of the…

Machine Learning · Computer Science 2025-04-16 Jundi Huang , Dawei Zhan

Optimizing expensive-to-evaluate black-box functions of discrete (and potentially continuous) design parameters is a ubiquitous problem in scientific and engineering applications. Bayesian optimization (BO) is a popular, sample-efficient…

Machine Learning · Computer Science 2022-10-20 Samuel Daulton , Xingchen Wan , David Eriksson , Maximilian Balandat , Michael A. Osborne , Eytan Bakshy

We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights.…

Applications · Statistics 2016-10-26 Federico Bassetti , Roberto Casarin , Francesco Ravazzolo

We propose an adaptive polygonal finite element formulation for collapse plastic analysis of solids. The article contributes into four crucial points: 1) Wachspress shape functions at vertex and bubble nodes handled at a primal-mesh level;…

Computational Engineering, Finance, and Science · Computer Science 2016-06-30 H. Nguyen-Xuan , Son H. Nguyen , Hyun-Gyu Kim , Klaus Hackl

We propose a simple and efficient scheme based on adaptive finite elements over conforming quadtree meshes for collapse plastic analysis of structures. Our main interest in kinematic limit analysis is concerned with both purely…

Computational Engineering, Finance, and Science · Computer Science 2019-03-11 H Nguyen-Xuan , Hien V Do , Khanh N Chau

Infinite-horizon optimal control of constrained piecewise affine (PWA) systems has been approximately addressed by hybrid model predictive control (MPC), which, however, has computational limitations, both in offline design and online…

Systems and Control · Electrical Eng. & Systems 2024-12-16 Kanghui He , Shengling Shi , Ton van den Boom , Bart De Schutter

An algorithm is devised for solving minimization problems with equality constraints. The algorithm uses first-order derivatives of both the objective function and the constraints. The step is computed as a sum between a steepest-descent…

Numerical Analysis · Mathematics 2017-11-15 Cristian Barbarosie , Sérgio Lopes , Anca-Maria Toader

Adhesive joints are increasingly used in industry for a wide variety of applications because of their favorable characteristics such as high strength-to-weight ratio, design flexibility, limited stress concentrations, planar force transfer,…

The rise of machine learning and additive manufacturing has enabled the design of architected materials with tailored properties that surpass those of natural materials. Inverse design offers a data-efficient alternative to trial-and-error…

Applied Physics · Physics 2026-04-30 Hirak Kansara , Leo Guo , Wei Tan

3D printing techniques such as Fused Deposition Modeling (FDM) have enabled the fabrication of complex geometry quickly and cheaply. High stiffness parts are produced by filling the 2D polygons of consecutive layers with contour-parallel…

Graphics · Computer Science 2020-04-29 Tim Kuipers , Eugeni L. Doubrovski , Jun Wu , Charlie C. L. Wang

Materials design can be cast as an optimization problem with the goal of achieving desired properties, by varying material composition, microstructure morphology, and processing conditions. Existence of both qualitative and quantitative…

Computational Physics · Physics 2019-07-08 Akshay Iyer , Yichi Zhang , Aditya Prasad , Siyu Tao , Yixing Wang , Linda Schadler , L Catherine Brinson , Wei Chen

In topology optimization of compliant mechanisms, the specific placement of boundary conditions strongly affects the resulting material distribution and performance of the design. At the same time, the most effective locations of the loads…

Computational Engineering, Finance, and Science · Computer Science 2025-02-05 Lee R. Alacoque , Anurag Bhattacharyya , Kai A. James

We present a physics-informed Bayesian optimization (PIBO) with a concise modification to its acquisition function to incorporate the physical prior knowledge. Specifically, this method multiplies the expected improvement (EI) by a weight…

Materials Science · Physics 2026-02-06 Yuki K. Wakabayashi , Takuma Otsuka , Yoshiharu Krockenberger , Yoshitaka Taniyasu

Adaptive network pruning approach has recently drawn significant attention due to its excellent capability to identify the importance and redundancy of layers and filters and customize a suitable pruning solution. However, it remains…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Liang Li , Pengfei Zhao

Topology optimization techniques have been applied in integrated optics and nanophotonics for the inverse design of devices with shapes that cannot be conceived by human intuition. At optical frequencies, these techniques have only been…

Optics · Physics 2022-04-15 Emadeldeen Hassan , Antonio Calà Lesina