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Additively manufactured structures often exhibit a correlation between their mechanical properties, such as stiffness, strength, and porosity, and their wall thickness. This correlation stems from the interplay between the manufacturing…

Optimization and Control · Mathematics 2024-03-26 Sukhminder Singh , Lukas Pflug , Fabian Wein , Michael Stingl

This paper presents a Material Mask Overlay topology optimization approach with the improved material assignment at the element level for achieving the desired discreteness of the optimized designs for pressure-loaded problems. Hexagonal…

Computational Engineering, Finance, and Science · Computer Science 2022-10-17 Prabhat Kumar , Anupam Saxena

Aiming at the promising superlensing for the medical ultrasonic and detection, the double-negative metamaterials which possess the negative mass density and elastic modulus simultaneously can be acted as the ideal superlens for breaking the…

Materials Science · Physics 2018-11-09 Hao-Wen Dong , Sheng-Dong Zhao , Yue-Sheng Wang , Chuanzeng Zhang

This work presents a computational method for the design of architected truss lattice materials where each strut can be made of one of a set of available materials. We design the lattices to extremize effective properties. As customary in…

Computational Engineering, Finance, and Science · Computer Science 2020-04-22 Hesaneh Kazemi , Ashkan Vaziri , Julian A. Norato

High quality mechanical resonators are critical for driving advances in quantum information technologies, precision sensing, and optomechanics. However, achieving compact resonator designs that maintain high performance is a key challenge.…

Quantum Physics · Physics 2025-12-01 Yincheng Shi , Fengwen Wang , Dennis Høj , Ole Sigmund , Ulrik Lund Andersen

The iterative nature of topology optimization, especially in combination with nonlinear state problems, often requires the solution of thousands of linear equation systems. Furthermore, due to the pixelated design representation, the use of…

Computational Engineering, Finance, and Science · Computer Science 2025-07-22 Gabriel Stankiewicz , Chaitanya Dev , Paul Steinmann

Hybrid-excited electrical machines aim to combine the advantages of permanent magnet machines (high efficiency and torque density) with those of separately excited machines (ease of flux-weakening at high speed). These machines are of…

Optimization and Control · Mathematics 2024-04-30 Théodore Cherrière

We present a new approach for adding Bernoulli beam reinforcements to Kirchhoff plates. The plate is discretised using a continuous/discontinuous finite element method based on standard continuous piecewise polynomial finite element spaces.…

Numerical Analysis · Mathematics 2017-06-06 Erik Burman , Peter Hansbo , Mats G. Larson

We study optimization problems for partially hinged rectangular plates, modeling bridge roadways, in the presence of real and artificial obstacles. Real obstacles represent structural constraints to avoid, while artificial ones are…

Optimization and Control · Mathematics 2025-11-07 Elvise Berchio , Filomena Feo , Antonio Giuseppe Grimaldi

In orthodontic treatment, the biological response of the tooth, periodontal ligament, and bone complex to orthodontic force is crucial in influencing treatment outcomes. The challenge lies in accurately measuring, estimating, and predicting…

Medical Physics · Physics 2025-04-01 Waheed Ahmad , Jing Xiong , Zeyang Xia

We propose a topology-constrained quantized nnUNet framework for efficient and anatomically accurate 3D tooth segmentation, addressing the challenges of spatial distortion introduced by quantization in deep learning models. The proposed…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Paarth Prasad , Ruchika Malhotra

A mesh improvement methodology is pre- sented which aims to improve the quality of the worst elements in 3D meshes with non-planar surfaces which cannot be improved using traditional methods. A nu- merical optimisation algorithm, which…

Optimization and Control · Mathematics 2013-07-15 Alan Kelly , Lukasz Kaczmarczyk , Chris Pearce

Efficient probabilistic inference by variable elimination in graphical models requires an optimal elimination order. However, finding an optimal order is a challenging combinatorial optimisation problem for models with a large number of…

Artificial Intelligence · Computer Science 2025-03-13 Sagad Hamid , Tanya Braun

The traditional element-based topology optimization based on material penalization typically aims at a 0/1 design. Our numerical experiments reveal that the compliance of a smooth design is overestimated when material properties of boundary…

Computational Engineering, Finance, and Science · Computer Science 2020-06-09 Xiaodong Huang

This paper presents a systematic topology optimization framework for designing a soft pneumatic gripper (SPG), explicitly considering the design-dependent nature of the actuating load. The load is modeled using Darcy's law with an added…

Robotics · Computer Science 2026-05-26 Prabhat Kumar , Chandra Prakash , Josh Pinskier , David Howard , Matthijs Langelaar

This paper aims to maximize optical force and torque on arbitrary micro- and nano-scale objects using numerically optimized structured illumination. By developing a numerical framework for computer-automated design of 3d vector-field…

Topological insulators (TIs) and topological crystalline insulators (TCIs) are materials with unconventional electronic properties, making their discovery highly valuable for practical applications. However, such materials, particularly…

Materials Science · Physics 2026-05-21 Haosheng Xu , Dongheng Qian , Zhixuan Liu , Yadong Jiang , Jing Wang

Recent developments in topological mechanics have demonstrated the ability of Maxwell lattices to effectively focus stress along domain walls between differently polarized domains. The focusing ability can be exploited to protect the…

Soft Condensed Matter · Physics 2025-02-04 Caleb Widstrand , Xiaoming Mao , Stefano Gonella

A major goal of materials design is to find material structures with desired properties and in a second step to find a processing path to reach one of these structures. In this paper, we propose and investigate a deep reinforcement learning…

Machine Learning · Computer Science 2021-07-09 Johannes Dornheim , Lukas Morand , Samuel Zeitvogel , Tarek Iraki , Norbert Link , Dirk Helm

The goal of this work is to serve as a foundation for deep studies of the topology of state, action, and policy spaces in reinforcement learning. By studying these spaces from a mathematical perspective, we expect to gain more insight into…

Machine Learning · Computer Science 2024-10-08 David Krame Kadurha
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