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In this paper, a topology optimization framework utilizing automatic differentiation is presented as an efficient way for solving 2D density-based topology optimization problem by calculating gradients through the fully differentiable…

Computational Engineering, Finance, and Science · Computer Science 2020-09-23 Liang Chen , Herman M. H. Shen

Transistor topology optimization is a critical step in standard cell design, directly dictating diffusion sharing efficiency and downstream routability. However, identifying optimal topologies remains a persistent bottleneck, as…

Machine Learning · Computer Science 2026-04-17 Zhan Song , Yu-Tung Liu , Chen Chen , Guoheng Sun , Jiaqi Yin , Chia-tung Ho , Ang Li , Haoxing Ren , Cunxi Yu

The design of porous infill structures presents significant challenges due to their complex geometric configurations, such as the accurate representation of geometric boundaries and the control of localized maximum stress. In current…

Optimization and Control · Mathematics 2025-10-14 Shuzhi Xu , Hiroki Kawabe , Kentaro Yaji

In this paper we present a novel two-scale framework to optimize the structure and the material distribution of an object given its functional specifications. Our approach utilizes multi-material microstructures as low-level building blocks…

Computational Engineering, Finance, and Science · Computer Science 2017-06-13 Bo Zhu , Mélina Skouras , Desai Chen , Wojciech Matusik

The simulation of heat flow through heterogeneous material is important for the design of structural and electronic components. Classical analytical solutions to the heat equation PDE are not known for many such domains, even those having…

Numerical Analysis · Mathematics 2019-05-21 Andrew Loeb , Christopher Earls

Engineers learn from every design they create, building intuition that helps them quickly identify promising solutions for new problems. Topology optimization (TO) - a well-established computational method for designing structures with…

Computational Engineering, Finance, and Science · Computer Science 2025-02-05 Igor Kuszczak , Gawel Kus , Federico Bosi , Miguel A. Bessa

In this paper we present a mixed projection- and density-based topology optimization approach. The aim is to combine the benefits of both parametrizations: the explicit geometric representation provides specific controls on certain design…

Computational Engineering, Finance, and Science · Computer Science 2019-10-09 Nicolò Pollini , Oded Amir

Topology Optimization (TO) holds the promise of designing next-generation compact and efficient photonic components. However, ensuring the optimized designs comply with fabrication constraints imposed by semiconductor foundries remains a…

Numerical Analysis · Mathematics 2024-07-02 Rahul Kumar Padhy , Aaditya Chandrasekhar

We present a new method for stochastic shape optimisation of engineering structures. The method generalises an existing deterministic scheme, in which the structure is represented and evolved by a level-set method coupled with mathematical…

Statistical Mechanics · Physics 2017-09-13 Lester O. Hedges , H. Alicia Kim , Robert L. Jack

This contribution focuses on the development of Model Order Reduction (MOR) for one-way coupled steady state linear thermomechanical problems in a finite element setting. We apply Proper Orthogonal Decomposition (POD) for the computation of…

We present a versatile high-level programming-language implementation of nonlinear topology optimization. Our implementation is based on the commercial software package Femlab, and it allows a wide range of optimization objectives to be…

Fluid Dynamics · Physics 2007-05-23 Laurits H. Olesen , Fridolin Okkels , Henrik Bruus

Complex non-local behavior makes designing high efficiency and multifunctional metasurfaces a significant challenge. While using libraries of meta-atoms provide a simple and fast implementation methodology, pillar to pillar interaction…

This paper proposes a level set-based method for optimizing shell structures with large design changes in shape and topology. Conventional shell optimization methods, whether parametric or nonparametric, often only allow limited design…

Computational Engineering, Finance, and Science · Computer Science 2024-08-29 Hiroki Kobayashi , Katsuya Nomura , Yuqing Zhou , Masato Tanaka , Atsushi Kawamoto , Tsuyoshi Nomura

Analog and mixed-signal circuit design remains challenging due to the shortage of high-quality data and the difficulty of embedding domain knowledge into automated flows. Traditional black-box optimization achieves sampling efficiency but…

Machine Learning · Computer Science 2025-09-18 Ziming Wei , Zichen Kong , Yuan Wang , David Z. Pan , Xiyuan Tang

Topology optimization methods for inverse design of nano-photonic systems have recently become extremely popular and are presented in various forms and under various names. Approaches comprise gradient and non-gradient based algorithms…

Optics · Physics 2021-02-25 Rasmus E. Christiansen , Ole Sigmund

In various applications, design problems involving structures and compliant mechanisms experience fluidic pressure loads. During topology optimization of such design problems, these loads adapt their direction and location with the…

Computational Engineering, Finance, and Science · Computer Science 2020-06-12 Prabhat Kumar , Jan S. Frouws , Matthijs Langelaar

Homogenization is a fundamental technique for estimating the macroscopic properties of materials with microscale heterogeneity. Among Homogenization methods, the FFT-based Homogenization algorithm has become widely used due to its…

Materials Science · Physics 2025-04-15 Sascha H. Hauck , Matthias Kabel , Mazen Ali , Nicolas R. Gauger

The adjoint method allows efficient calculation of the gradient with respect to the design variables of a topology optimization problem. This method is almost exclusively used in combination with traditional Finite-Element-Analysis, whereas…

Computational Engineering, Finance, and Science · Computer Science 2022-06-20 Indre Jödicke , Richard J. Leute , Till Junge , Lars Pastewka

Optimization, a key tool in machine learning and statistics, relies on regularization to reduce overfitting. Traditional regularization methods control a norm of the solution to ensure its smoothness. Recently, topological methods have…

Machine Learning · Computer Science 2020-11-11 Arnur Nigmetov , Aditi S. Krishnapriyan , Nicole Sanderson , Dmitriy Morozov

Inspired by natural cellular materials such as trabecular bone, lattice structures have been developed as a new type of lightweight material. In this paper we present a novel method to design lattice structures that conform with both the…

Computational Engineering, Finance, and Science · Computer Science 2019-09-06 Jun Wu , Weiming Wang , Xifeng Gao