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The spatial control of material placement afforded by metal additive manufacturing (AM) has enabled significant progress in the development and implementation of compositionally graded alloys (CGAs) for spatial property variation in…

Materials Science · Physics 2024-12-06 Marshall D. Allen , Vahid Attari , Brent Vela , James Hanagan , Richard Malak , Raymundo Arróyave

In this paper, we present a topology optimization (TO) framework to enable automated design of mechanical components while ensuring the result can be manufactured using multi-axis machining. Although TO improves the part's performance, the…

Computational Engineering, Finance, and Science · Computer Science 2020-02-19 Amir M. Mirzendehdel , Morad Behandish , Saigopal Nelaturi

Gel-elastomer composites, comprising an active swellable hydrogel and a passive elastomer, are a compelling class of programmable material systems (PMS) capable of shape morphing under multiphysics actuation. The precise design of the…

Computational Engineering, Finance, and Science · Computer Science 2026-05-20 Aaditya Chandrasekhar , Dex Doksoo Lee , Hyunwoo Kwon , Wei Chen

Topology optimization (TO) provides a principled mathematical approach for optimizing the performance of a structure by designing its material spatial distribution in a pre-defined domain and subject to a set of constraints. The majority of…

Machine Learning · Computer Science 2024-08-08 Amin Yousefpour , Shirin Hosseinmardi , Carlos Mora , Ramin Bostanabad

In this paper, we propose PATO-a producibility-aware topology optimization (TO) framework to help efficiently explore the design space of components fabricated using metal additive manufacturing (AM), while ensuring manufacturability with…

Computational Engineering, Finance, and Science · Computer Science 2021-12-10 Naresh S. Iyer , Amir M. Mirzendehdel , Sathyanarayanan Raghavan , Yang Jiao , Erva Ulu , Morad Behandish , Saigopal Nelaturi , Dean M. Robinson

This paper presents a machine learning-based framework for topology optimization of self-supporting structures, specifically tailored for additive manufacturing (AM). By employing a graph neural network (GNN) that acts as a neural field…

Computational Engineering, Finance, and Science · Computer Science 2025-08-27 Alireza Tabarraei , Saquib Ahmad Bhuiyan

Multiscale topology optimization (M-TO) entails generating an optimal global topology, and an optimal set of microstructures at a smaller scale, for a physics-constrained problem. With the advent of additive manufacturing, M-TO has gained…

Computational Engineering, Finance, and Science · Computer Science 2022-04-15 Aaditya Chandrasekhar , Saketh Sridhara , Krishnan Suresh

In topology optimization using deep learning, load and boundary conditions represented as vectors or sparse matrices often miss the opportunity to encode a rich view of the design problem, leading to less than ideal generalization results.…

Computational Engineering, Finance, and Science · Computer Science 2020-03-12 Zhenguo Nie , Tong Lin , Haoliang Jiang , Levent Burak Kara

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

Topology optimization (TO) is a family of computational methods that derive near-optimal geometries from formal problem descriptions. Despite their success, established TO methods are limited to generating single solutions, restricting the…

Machine Learning · Computer Science 2025-06-18 Andreas Radler , Eric Volkmann , Johannes Brandstetter , Arturs Berzins

In this paper, we present a topology optimization (TO) framework to simultaneously optimize the matrix topology and fiber distribution of functionally graded continuous fiber-reinforced composites (FRC). Current approaches in density-based…

Computational Engineering, Finance, and Science · Computer Science 2022-05-16 Aaditya Chandrasekhar , Amir Mirzendehdel , Morad Behandish , Krishnan Suresh

Neural network compression methods have enabled deploying large models on emerging edge devices with little cost, by adapting already-trained models to the constraints of these devices. The rapid development of AI-capable edge devices with…

Machine Learning · Computer Science 2019-12-20 Soroosh Khoram , Jing Li

Metal additive manufacturing (AM) processes often fabricate a near-net shape that includes the as-designed part as well as the sacrificial support structures that need to be machined away by subtractive manufacturing (SM), for instance…

Computational Engineering, Finance, and Science · Computer Science 2021-08-09 Amir M. Mirzendehdel , Morad Behandish , Saigopal Nelaturi

This paper presents a density-based topology optimization approach considering additive manufacturing limitations. The presented method considers the minimum size of parts, the minimum size of cavities, the inability of printing overhanging…

Computational Engineering, Finance, and Science · Computer Science 2022-04-18 Prabhat Kumar , Eduardo Fernández

For natural frequency optimization of engineering structures, cellular composites have been shown to possess an edge over solid. However, existing multiscale design methods for cellular composites are either computationally exhaustive or…

Computational Engineering, Finance, and Science · Computer Science 2021-06-14 Liwei Wang , Anton van Beek , Daicong Da , Yu-Chin Chan , Ping Zhu , Wei Chen

Topology optimization produces designs with intricate geometries and complex topologies that require advanced manufacturing techniques such as additive manufacturing (AM). However, insufficient consideration of manufacturability during the…

Computational Engineering, Finance, and Science · Computer Science 2025-02-28 Seungheon Shin , Byeonghyeon Goh , Youngtaek Oh , Hayoung Chung

Topology optimization facilitates the automated design of high-performance structures across various engineering fields but, if unconstrained, often produces designs that are complex and difficult to manufacture. A key attribute of the…

Applied Physics · Physics 2025-04-25 Vanessa Cool , Niels Aage , Ole Sigmund

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

We introduce a computational framework for the topology optimization of cellular structures with spatially varying architecture, which is applied to functionally graded truss lattices under quasistatic loading. We make use of a first-order…

Other Condensed Matter · Physics 2022-05-31 Bastian Telgen , Ole Sigmund , Dennis M. Kochmann

Topology Optimization (TO), which maximizes structural robustness under material weight constraints, is becoming an essential step for the automatic design of mechanical parts. However, existing TO algorithms use the Finite Element Analysis…

Robotics · Computer Science 2022-04-14 Zherong Pan , Xifeng Gao , Kui Wu
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