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Related papers: Data-driven Topology Optimization (DDTO) for Three…

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Topology optimization is widely used by engineers during the initial product development process to get a first possible geometry design. The state-of-the-art is the iterative calculation, which requires both time and computational power.…

Machine Learning · Computer Science 2021-09-30 Alex Halle , L. Flavio Campanile , Alexander Hasse

Electromagnetic interference (EMI) filters are used to reduce electromagnetic noise. It is well known that the performance of an EMI filter in reducing electromagnetic noise largely depends on its conductor layout. Therefore, if a conductor…

Optimization and Control · Mathematics 2025-05-05 Duanyutian Zhou , Nomura Katsuya , Shintaro Yamasaki

A density-based topology optimization framework is developed to manipulate characteristic modes of conducting surfaces. The adjoint sensitivity analysis provides an efficient computation of the material gradient utilized by the local…

Optimization and Control · Mathematics 2025-02-07 Jonas Tucek , Miloslav Capek , Lukas Jelinek

To effectively search for the optimal motion template in dynamic multidimensional space, this paper proposes a novel optimization algorithm, Dynamic Dimension Wrapping (DDW).The algorithm combines Dynamic Time Warping (DTW) and Euclidean…

Machine Learning · Computer Science 2024-11-18 Dongnan Jin , Yali Liu , Qiuzhi Song , Xunju Ma , Yue Liu , Dehao Wu

Data-driven methods have emerged as powerful tools for modeling the responses of complex nonlinear materials directly from experimental measurements. Among these methods, the data-driven constitutive models present advantages in physical…

Machine Learning · Computer Science 2025-05-05 Jihong Wang , Xiaochuan Tian , Zhongqiang Zhang , Stewart Silling , Siavash Jafarzadeh , Yue Yu

Finding an optimal parameter of a black-box function is important for searching stable material structures and finding optimal neural network structures, and Bayesian optimization algorithms are widely used for the purpose. However, most of…

Machine Learning · Computer Science 2019-02-27 Tatsuya Shiraishi , Tam Le , Hisashi Kashima , Makoto Yamada

Data-driven material models have many advantages over classical numerical approaches, such as the direct utilization of experimental data and the possibility to improve performance of predictions when additional data is available. One…

Computational Engineering, Finance, and Science · Computer Science 2020-06-11 Dengpeng Huang , Jan Niklas Fuhg , Christian Weißenfels , Peter Wriggers

We present a level-set based topology optimization algorithm for design optimization problems involving an arbitrary number of different materials, where the evolution of a design is solely guided by topological derivatives. Our method can…

Optimization and Control · Mathematics 2020-06-24 Peter Gangl

Topological data analysis (TDA) provides insight into data shape. The summaries obtained by these methods are principled global descriptions of multi-dimensional data whilst exhibiting stable properties such as robustness to deformation and…

Machine Learning · Computer Science 2024-03-18 Ali Zia , Abdelwahed Khamis , James Nichols , Zeeshan Hayder , Vivien Rolland , Lars Petersson

In this paper, we investigate an unmanned aerial vehicle (UAV)-assisted Internet-of-Things (IoT) system in a sophisticated three-dimensional (3D) environment, where the UAV's trajectory is optimized to efficiently collect data from multiple…

Information Theory · Computer Science 2022-01-20 Yang Wang , Zhen Gao , Jun Zhang , Xianbin Cao , Dezhi Zheng , Yue Gao , Derrick Wing Kwan Ng , Marco Di Renzo

Topology optimization (TO) is a popular and powerful computational approach for designing novel structures, materials, and devices. Two computational challenges have limited the applicability of TO to a variety of industrial applications.…

Computational Engineering, Finance, and Science · Computer Science 2020-12-01 Sirui Bi , Jiaxin Zhang , Guannan Zhang

This paper presents a novel data-driven stochastic MPC design for discrete-time nonlinear systems with additive disturbances by leveraging the Koopman operator and a distributionally robust optimization (DRO) framework. By lifting the…

Systems and Control · Electrical Eng. & Systems 2025-10-27 Zhengang Zhong , Ehecatl Antonio del Rio-Chanona , Panagiotis Petsagkourakis

Data-based optimization (DBO) offers a promising approach for efficiently optimizing shape for better aerodynamic performance by leveraging a pretrained surrogate model for offline evaluations during iterations. However, DBO heavily relies…

Machine Learning · Computer Science 2026-03-31 Yunjia Yang , Runze Li , Yufei Zhang , Haixin Chen

In this paper, gradient-based optimization methods are combined with finite-element modeling for improving electric devices. Geometric design parameters are considered by affine decomposition of the geometry or by the design element…

Topological methods can provide a way of proposing new metrics and methods of scrutinising data, that otherwise may be overlooked. In this work, a method of quantifying the shape of data, via a topic called topological data analysis will be…

Machine Learning · Statistics 2022-09-25 Tristan Gowdridge , Nikolaos Dervilis , Keith Worden

We consider the problem of optimizing the interconnection graphs of complex networks to promote synchronization. When traditional optimization methods are inapplicable, due to uncertain or unknown node dynamics, we propose a data-driven…

Systems and Control · Electrical Eng. & Systems 2023-09-29 Marco Coraggio , Mario di Bernardo

This work presents a rigorous mathematical formulation for topology optimization of a macrostructure undergoing ductile failure. The prediction of ductile solid materials which exhibit dominant plastic deformation is an intriguingly…

Numerical Analysis · Mathematics 2023-03-22 Nima Noii , Hassan Ali Jahangiry , Haim Waisman

Topology optimization is used to systematically design contact-aided thermo-mechanical regulators, i.e. components whose effective thermal conductivity is tunable by mechanical deformation and contact. The thermo-mechanical interactions are…

Computational Engineering, Finance, and Science · Computer Science 2024-06-04 Anna Dalklint , Joe Alexandersen , Andreas Henrik Frederiksen , Konstantinos Poulios , Ole Sigmund

Dynamic Threshold Optimization (DTO) adaptively "compresses" the decision space (DS) in a global search and optimization problem by bounding the objective function from below. This approach is different from "shrinking" DS by reducing…

Other Computer Science · Computer Science 2012-06-07 Richard A. Formato

For their excellent stiffness-to-weight characteristics, triply periodic minimal surfaces (TPMS) are widely adopted in architected materials. However, their geometric regularity often leads to elastic anisotropy, limiting their…

Computational Physics · Physics 2025-05-21 Minwoo Park , Junheui Jo , Seunghwa Ryu
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