25 papers · ranked by Valyu relevance
Josué D. Díaz-Avalos, Antoine Laurain
This article presents the toolbox FormOpt for two- and three-dimensional shape optimization with parallel computing capabilities, built on the FEniCSx software framework. We introduce fundamental concepts of shape sensitivity analysis and their numerical applications, mainly for educational purposes, while also…
Mathieu Dubied, Paolo Tiso, Robert K. Katzschmann
The efficient optimization of actuated soft structures, particularly under complex nonlinear forces, remains a critical challenge in advancing robotics. Simulations of nonlinear structures, such as soft-bodied robots modeled using the finite element method (FEM), often demand substantial computational resources…
Daiyu Zhang, Daxing Zeng, Heng Zhou, Chaoming Bao + 2 more
To address the challenges of high computational cost and lengthy design cycles in the high-precision optimization of ray-like underwater gliders, this study proposes a high-accuracy, low-cost parametric modeling and optimization method. The proposed framework begins by extracting the characteristic contours of the…
Wenhao Fan, Yuanwei Bin, Jianghan Gu, Wenfa Luo + 3 more
Engineering shape optimization faces challenges in both expert-dependent problem setup and surrogate-model reliability. In practical aerodynamic design, optimization settings such as editable regions, deformation ranges, and design-preservation constraints are typically specified manually by experienced engineers…
Steffen Tillmann, Felipe A. González, Stefanie Elgeti
Purpose: In fused deposition modeling (FDM), the nozzle plays a critical role in enabling high printing speeds while maintaining precision. Despite its importance, most applications still rely on standard nozzle designs. This work investigates the influence of nozzle geometry on pressure loss inside the nozzle, a key…
Authors not listed
This article presents an overview about the state of the art in the development of structured packings for distillation applications. The focus is on highlighting different approaches including heuristic development cycles, the development of new packing structures, 3D-printing as tool for manufacturing, and…
Xiao Xiao, Fehmi Cirak
Shape optimisation of thin-shell structures requires a flexible, differentiable geometric representation suitable for gradient-based optimisation. We propose a neural parametric representation (NRep) for the shell mid-surface based on a neural network with periodic activation functions. The NRep is defined using a…
Marc Dambrine, Helmut Harbrecht, Viacheslav Karnaev
We consider the numerical solution of shape optimization problems for thermoelasticity with temperature-dependent material parameters. We show the existence of the shape derivative and derive an expression for generic functionals of domain integral type. Numerical results are presented for two settings: minimization of…
Chunyang Xia, Kui Zeng, Jiawei Ning, Yaoyu Ding + 2 more
Laser-arc hybrid additive manufacturing (LAHAM) combines the benefits of arc-based deposition and laser precision but involves complex, nonlinear process interactions that challenge the prediction and control of bead geometry and energy consumption. This study develops a machine learning (ML) framework to predict bead…
Xin Tao, Li Bin, Dapeng Wei
To improve the continuous chordwise bending performance of morphing wings, this study proposes a rigid-flexible coupled wing rib structure and its control strategy. Initially, the optimal rigid-flexible hybrid configuration was optimized via the mean camber line parameterization and genetic algorithm. For the flexible…
Alexander Busch, Olaf Bruch, Dirk Reith, Yunfa Zhang
Reducing material usage in plastic products is a key lever for improving resource efficiency and minimizing environmental impact. In thin-walled structures subjected to mechanical loading, material efficiency must be achieved without compromising structural performance. In particular, resistance to buckling, a critical…
Min-Gi Kim, Jae-Chang Ryu, Chan-Joo Lee, Jin-Seok Jang + 2 more
The increasing use of vinyl-coated metal (VCM) sheets in home appliances requires robust forming processes to prevent defects such as delamination and wrinkling, especially under elevated temperatures and humidity. This study presents a deep neural network (DNN)-based multi-objective optimization framework to determine…
Tim Y.Y. Tian, Colin B. Macdonald, Eric N. Cytrynbaum
Within plant cells, the self-organization of cortical microtubules (MTs) into ordered arrays is an important process for directional growth. There is growing evidence that cortical MTs respond to cell shape and/or mechanical stresses in the cell wall, requiring in silico models on complicated surfaces to provide a…
Oz Shaul, Tali Ilovitsh
Beam shaping of ultra-short pulses is essential for medical ultrasound, where single-cycle excitations are required to achieve high axial resolution and improve frame rate. Conventional methods, such as the Gerchberg–Saxton (GS) algorithm or more recent deep learning approaches, are generally effective for…
Zepeng Liu, Shaogang Liu, Bai Chen, Alexander Malkin
This research systematically investigates the shape memory properties of re-entrant hexagonal negative Poisson’s ratio (NPR) honeycomb structures fabricated via 4D printing, using polyethylene terephthalate glycol (PETG) and polylactic acid (PLA) as comparative materials. Periodic honeycomb models with varied wall…
Authors not listed
Designing efficient photoreactors remains challenging due to the complex interplay of light transport phenomena, shaped by reflection, scattering and absorption processes. Here, we introduce a workflow that integrates ray-tracing digital twins with multi-objective Bayesian optimization to autonomously design…
Yuzhe Wang, Zhonghuai Wu, Mario Iodice
Highlights What are the main findings?1. A thermo-mechanical physical field coupling mechanism was established, and a topology optimization method based on multi-physics field coupling was proposed. 2. By combining the advantages of topology optimization and parameter optimization, the optimized mirror exhibits better…
Maria Evangelia Vlachou, Elizabeth Thomas, Jean Blouin
In this paper, we address the problem of quantifying similarity between planar 2D shapes, which is relevant to studies of internal representations in cognitive, developmental, and neurological research. We designed a set of test shapes arranged along a visually defined perceptual similarity gradient and used them to…
Mercedes Quintana, Le Yang Loh, Ayush Parikh, Jonathan J. Suh + 4 more
Morphological measurements underpin a wide range of ecological and evolutionary research, yet the manual landmarking workflows on which most morphometric studies depend remain a persistent bottleneck that limits both the pace and scale of biological research. Machine learning offers compelling solutions, but most…
Authors not listed
TurtleMol is an open-source Python package that aims to help users generate large, complex molec- ular systems. In the current version, users can generate systems by filling volumes defined by basic geometric shapes (e.g. cube, sphere), or by shapes of arbitrary gemoetries defined meshes created in other software (such…
Changin Oh, Kathleen P. Wilkie
We present the Toroidal Search Algorithm (TSA), a novel population-based metaheuristic optimization method inspired by the topology of a torus. Conventional metaheuristics frequently suffer from boundary stagnation, a phenomenon that severely degrades performance in bounded and high-dimensional search spaces. TSA…
Authors not listed
Given the recent inclusion of sodium-ion batteries (SIBs) in the energy market, the optimization of their performance becomes a relevant research topic. At the electrode-level, the parameters selected during its manufacturing process influence its microstructure and, consequently, its electrochemical performance. Here…
Authors not listed
Inverse molecular design aims to generate novel chemical structures that satisfy multiple property constraints, yet reinforcement-learning (RL) fine-tuning can be sensitive to how objectives are converted into a scalar reward. Here, we systematically analyze how scalarization choices and stabilization mechanisms shape…
Authors not listed
Crystal structure prediction has developed into a valuable tool for anticipating the likely crystalline arrangement that a molecule will adopt, with applications in materials discovery and polymorph screening. Although powerful, crystal structure prediction is usually limited to locating the local minima of the crystal…
Madeline Gunawardena, Bao Chau, Hayden Nothacker, Rudra Pangeni + 3 more
Oral microemulsions are one drug delivery system often implemented to improve intestinal permeability and oral bioavailability of poorly-water soluble drugs. They also present several practical advantages including high patient compliance and simplified manufacturing methods which contribute to their promise as…