Article
Mechanics
Xingjun Gao, Weihua Chen, Yingxiong Li, Gongfa Chen
Summary: This paper proposes an efficient method for robust multimaterial topology optimization problems of continuum structures under load uncertainty. The method minimizes the weighted sum of the mean and standard deviation of structural compliance for each material phase, separates the Monte Carlo sampling from the topology optimization procedure, and establishes an efficient procedure for sensitivity analysis. By using an alternating active-phase algorithm of the Gauss-Seidel version, the multi-material topology optimization problem is split into a series of binary topology optimization sub-problems, leading to the demonstration of the effectiveness of the proposed method through several 2D examples.
COMPOSITE STRUCTURES
(2021)
Article
Computer Science, Interdisciplinary Applications
Ming Zhou, Ole Sigmund
Summary: The paper discusses Sigmund's 2001 educational paper with a self-contained 99-line MATLAB code, which has had a far-reaching impact on teaching and research of topology optimization. The goal of the paper is to provide clarity to the theoretical foundation and enable students to learn the complete iterative optimization solution with minimum additional effort.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Federico Ferrari, Ole Sigmund, James K. Guest
Summary: The Matlab code presented here is designed for topology optimization based on linearized buckling criteria, handling multiple objectives or constraints efficiently. By using aggregation functions, sequential approximation, and vectorized implementation, the code improves efficiency and reduces computational bottlenecks. This allows for solving buckling topology optimization problems of significant size on a laptop, demonstrating code flexibility and performance through structural design examples.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Chemistry, Multidisciplinary
Nam H. Kim, Ting Dong, David Weinberg, Jonas Dalidd
Summary: The study proposed a generalized optimality criteria method for topology optimization, capable of handling multiple inequality constraints with high computational efficiency.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Multidisciplinary
Weichun Fan, Zhongming Xu, Zhifei Zhang
Summary: A modified optimality criteria (OC) method using Proportional, Integral, Derivative (PID) control for determining the Lagrange multiplier is proposed in this study. The method improves the convergence of the OC method by considering the Lagrange multiplier as the controlled variable of the PID controller. The modified method achieves fast convergence with few iterations and short computational time in both single material and multi-material topology optimization.
OPTIMIZATION AND ENGINEERING
(2023)
Article
Engineering, Mechanical
Eduardo Lenz Cardoso, Andre Jacomel Torii
Summary: Optimality criteria methods are commonly used in structural optimization for their efficiency and simplicity. This manuscript discusses the limitation of extending common criteria used for minimum compliance problems to stress-based optimization problems. The sensitivity of compliance is shown to be a local quantity, while stress-based sensitivity is not, requiring global update rules. The Proportional Topology Optimization method's limitations for stress-based problems are also explained.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2023)
Article
Thermodynamics
Mine Kaya, Shima Hajimirza
Summary: This study introduces a framework based on topology optimization to discover new nanoparticle designs for improved scattering. By maximizing the scattering cross section of the particle domain, increased scattering cross-section at the nanoscale is achieved, leading to improved light trapping efficiency.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2021)
Article
Computer Science, Interdisciplinary Applications
Jesus Martinez-Frutos, Rogelio Ortigosa
Summary: This paper introduces a novel probabilistic approach for fail-safe robust topology optimization, which considers the probability of failure at specific locations and incorporates random failure sizes, pursuing a multi-objective problem to enhance structural robustness. The technique offers optimized solutions for different volume fractions and provides smooth and clearly defined structural boundaries, demonstrating the ability to enhance structural robustness compared to conventional deterministic designs.
COMPUTERS & STRUCTURES
(2021)
Article
Computer Science, Interdisciplinary Applications
Changkye Lee, Sundararajan Natarajan, Seong-Hoon Kee, Jurng-Jae Yee
Summary: This study employs three variants of strain smoothing techniques for structural topology optimization, highlighting their features of not requiring explicit shape functions and being less sensitive to mesh distortion. The optimum structural topology is estimated by minimizing the total strain energy, and a parametric study is conducted to find suitable control parameters. The relative performance of different strain smoothing techniques is also presented.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2021)
Article
Engineering, Civil
Mariano Victoria, Concepcion Diaz, Pascual Marti, Osvaldo M. Querin
Summary: This paper presents an extension to the Isolines Topology Design (ITD) algorithm for the topology design of 2D continuum structures under the influence of buckling. The alternative approach incorporates the buckling effect by transforming the buckling topology optimization problem into a stress-based topology design problem. The effectiveness of the new approach is demonstrated through three examples, showing good agreement with existing literature.
Article
Computer Science, Interdisciplinary Applications
Tej Kumar, Krishnan Suresh
Summary: This paper introduces a direct method for computing Lagrange multipliers in topology optimization. Through benchmark problems, it demonstrates advantages over the traditional bisection method including fewer and faster update iterations, smoother and more robust convergence, and insensitivity to material and force parameters. The method also provides drop-in replacements for popular Matlab-based topology optimization codes.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Song Bai, Zhan Kang
Summary: The paper presents a robust topology optimization method for structures with bounded loads and spatially correlated material uncertainties. The method combines random structural loads with bounded nature and random field discretization to model uncertainties, with a focus on minimizing mean value and standard deviation of structural compliance. Numerical examples show that the proposed method results in structurally robust designs against uncertainties.
COMPUTERS & STRUCTURES
(2021)
Article
Mathematics, Applied
X. Ou, Y. B. Lv, Y. C. Liou, T. Zhang, J. W. Chen
Summary: This paper investigates a multi-criteria optimization problem with uncertain data using its robust counterpart in the worst case. A robust constraint qualification is introduced, and necessary optimality conditions for weakly robust efficient solutions and properly robust efficient solutions are established. Furthermore, robust sufficient optimality conditions are derived under certain conditions.
JOURNAL OF NONLINEAR AND CONVEX ANALYSIS
(2021)
Article
Automation & Control Systems
Maksim Makarenko, Qizhou Wang, Arturo Burguete-Lopez, Fedor Getman, Andrea Fratalocchi
Summary: Flat-optics has emerged as a promising light manipulation technology, but designing flexible flat-optics in flexible structures poses challenges. Researchers have proposed an inverse design platform using large-scale optimizers and neural network predictors to achieve high-performance flexible flat-optics design.
ADVANCED INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Yanfa Wu, Wenke Qiu, Liang Xia, Wenbiao Li, Kai Feng
Summary: This work improves a previous stress-constrained topology optimization method and applies it to a typical aircraft engine bracket design problem. The improved method uses a more efficient and versatile self-adaptive scheme for determining the Lagrange multiplier, resulting in a bracket design that outperforms the original in terms of weight, stiffness, and strength.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Engineering, Multidisciplinary
Victor M. Ortiz-Martinez, Jesus Martinez-Frutos, Eloy Hontoria, Francisco J. Hernandez-Fernandez, Jose A. Egea
Summary: Wastewater treatment process design involves optimizing multiple conflicting objectives, and detecting different equivalent solutions is crucial for designers in efficiently switching to new optimal operation policies. This study focuses on the dynamic multi-objective optimization of a municipal wastewater treatment plant model, optimizing an economic cost term and an effluent quality index simultaneously. Simulating different realistic scenarios reveals that multiple solutions exist at least in some areas of the Pareto front.
OPTIMIZATION AND ENGINEERING
(2021)
Article
Automation & Control Systems
Rogelio Ortigosa, Jesus Martinez-Frutos, Carlos Mora-Corral, Pablo Pedregal, Francisco Periago
Summary: This paper discusses the optimal control of hyperelastic materials using polyconvex stored energy functionals, introducing new tracking-type cost functionals and utilizing the Hausdorff metric for the first time in this context. The existence of a solution for a regularized version of the optimal control problem is proven, with a gradient-based method proposed for numerical resolution. Numerical examples demonstrate the viability and applicability of the Hausdorff metric in this new context.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2021)
Article
Engineering, Multidisciplinary
F. Marin, J. Martinez-Frutos, R. Ortigosa, A. J. Gil
Summary: This paper introduces a novel computational framework for analyzing complex deformation patterns, using Convex Multi-Variable energy density functionals to describe the physics of microscopic constituents. The nonlinearity of the electro-mechanical problem is resolved using a monolithic multi-scale Newton-Raphson scheme, and the potential loss of ellipticity in the homogenised constitutive model is monitored through the minors of the homogenised acoustic tensor. Numerical examples demonstrate the impact of various factors on the response of composites under different conditions.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
M. Franke, R. Ortigosa, J. Martinez-Frutos, A. J. Gil, P. Betsch
Summary: This paper aims to design a new Energy-Momentum (EM) preserving time integration scheme for thermo-electro-elastic processes undergoing large deformations. By utilizing polyconvexity and a new tensor cross product algebra, the scheme is able to derive comparatively simple formulas for discrete derivatives, overcoming the complex derivatives in classical EM schemes. The newly proposed scheme inherits the advantages of previous EM schemes while extending to the more generic case of nonlinear thermo-electro-mechanics, with a focus on robustness and numerical stability properties.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
F. Marin, R. Ortigosa, J. Martinez-Frutos, A. J. Gil
Summary: This paper investigates the viscoelastic up-scaling effects in electro-active polymers with a micro-structure architecture. By combining rank-n homogenisation principles and thermodynamical consistency, using Convex Multi-Variable (CMV) energy density functionals enriched with nonlinear continuum viscoelastic description, the study tackles the highly nonlinear visco-electro-mechanical problem.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
R. Ortigosa, J. Martinez-Frutos, C. Mora-Corral, P. Pedregal, F. Periago
Summary: This paper presents a novel in-silico framework for simultaneous optimal control and design of complex magnetic responsive polymer composite materials, introducing key novelties such as an optimization-driven method and establishing the well-posedness character of the optimization problem. The proposed gradient-based optimization algorithm provides explicit expressions of continuous gradients, demonstrating the capability of the proposal as an alternative to intuition or experimentally-based approaches.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Computer Science, Interdisciplinary Applications
David Herrero-Perez, Sebastian Gines Pico-Vicente, Humberto Martinez-Barbera
Summary: This work presents an efficient parallel implementation of density-based topology optimization using the Adaptive Mesh Refinement (AMR) scheme to reduce computational burden. The proposed method achieves equivalent designs at lower computational cost compared to uniformly fine mesh. By evaluating the objective function on a coarse mesh and employing the algebraic multigrid (AMG) method, the method demonstrates computational advantages. The numerical results show significant improvement in computing performance by combining dynamic coarsening, adaptive mesh refinement, and distributed memory computing architectures.
COMPUTERS & STRUCTURES
(2022)
Article
Engineering, Multidisciplinary
Dominik K. Klein, Rogelio Ortigosa, Jesus Martinez-Frutos, Oliver Weeger
Summary: In this work, a machine learning based constitutive model for electro-mechanically coupled material behavior at finite deformations is proposed. The model formulates an internal energy density as a convex neural network using different sets of invariants as inputs. It demonstrates applicability and versatility through calibration on different materials data and effective modeling of composite materials.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
R. Ortigosa, J. Martinez-Frutos, A. J. Gil
Summary: This paper presents a novel theoretical framework for designing flexoelectric energy harvesters under finite strain conditions. The framework combines a micromorphic continuum approach, a novel energy interpolation scheme, and an improved efficiency measure to accurately model and optimize the flexoelectric effects in highly deformable materials. The proposed framework overcomes the limitations of existing methods and offers new insights into the development of efficient and practical energy harvesters.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Chemistry, Multidisciplinary
David Herrero-Perez, Humberto Martinez-Barbera
Summary: This study presents the design and fabrication of an underwater soft gripper, utilizing soft robotics technology to address the limitations in versatility and robustness in underwater manipulation. The soft gripper is cost-effective, easily deployable, and capable of adapting to uncertain environmental conditions, with the ability to be rapidly redesigned for different applications. The feasibility and performance of the soft gripper are validated in a challenging underwater scenario using a subaquatic vehicle.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Multidisciplinary
Rogelio Ortigosa, Jesus Martinez-Frutos, Antonio J. Gil
Summary: This paper presents a novel engineering strategy for the design of Dielectric Elastomer (DE) based actuators, capable of attaining complex electrically induced shape morphing configurations. The strategy involves the use of a multilayered DE prototype with different materials and the development of a computational approach for designing new prototypes with predefined configurations. The proposed methodology shows promise in efficiently determining optimal designs for complex electrically induced configurations.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Computer Science, Interdisciplinary Applications
David Herrero-Perez, Sebastian Gines Pico-Vicente, Humberto Martinez-Barbera
Summary: This work presents an efficient parallel implementation of density-based robust topology optimization using adaptive mesh refinement schemes. We use sparse grid stochastic collocation methods to transform the problem into a deterministic problem at the collocation points. We combine distributed-memory parallel computing and AMR techniques to address the problem efficiently, resulting in significant performance improvements.
ENGINEERING WITH COMPUTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
David Herrero-Perez, Sebastian Gines Pico-Vicente
Summary: This work presents an efficient parallel geometric multigrid (GMG) implementation for preconditioning Krylov subspace methods solving differential equations using non-conforming meshes for discretization. The approach calculates the restriction and interpolation operators for grid transferring between the non-conforming hierarchical meshes. Using non-Cartesian grids in topology optimization, it reduces the mesh size by discretizing only the design domain. The performance of the proposed method is evaluated using topology optimization problems, showing its computational advantages.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Computer Science, Interdisciplinary Applications
D. Herrero-Perez, S. G. Pico-Vicente
Summary: This work presents an efficient, flexible, and scalable strategy for implementing density-based topology optimization formulation in fail-safe structural design. The use of non-overlapping domain decomposition, adaptive mesh refinement, and computing buffers allows for successful evaluation of fault cases.
COMPUTERS & STRUCTURES
(2024)
Proceedings Paper
Automation & Control Systems
Antonio J. Gil, Rogelio Ortigosa, Jesus Martinez-Frutos, Nathan Ellmer
Summary: This paper presents the latest computational developments in using Electro-Active Polymers (EAPs) for the fabrication of miniaturised soft robotic actuators. The challenges faced by the research group include resolving massive strains, capturing complex material properties, and optimizing electrode structures. The paper demonstrates the capabilities and flexibility of the in-silico design tools through numerical examples. The authors plan to integrate a 3D Direct-Ink-Writer (DIW) printer for in-house device design, simulation, fabrication, and testing.
TOWARDS AUTONOMOUS ROBOTIC SYSTEMS, TAROS 2022
(2022)
Article
Computer Science, Interdisciplinary Applications
Jose Pedro G. Carvalho, Denis E. C. Vargas, Breno P. Jacob, Beatriz S. L. P. Lima, Patricia H. Hallak, Afonso C. C. Lemonge
Summary: This paper formulates a multi-objective structural optimization problem and utilizes multiple evolutionary algorithms to solve it. By optimizing the grouping of structural members, the best truss structure can be found. After analyzing various benchmark problems, the study reveals the existence of competitive structural member configurations beyond symmetry-based groupings.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Se-Hyeon Kang, Hyun-Seok Kim, Seonho Cho
Summary: This paper investigates shape identification using peridynamic theory and gradient-based optimization. The particle-based and non-local characteristics of peridynamics allow for direct interface modeling, avoiding remeshing difficulties. The boundary of scatterers is parameterized using B-spline surfaces, and design sensitivity is obtained using an efficient adjoint variable method. The accuracy and efficiency of the proposed method are verified through numerical examples.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Laura Rio-Martin, A. Prieto
Summary: Any numerical procedure in mechanics requires selecting an appropriate constitutive model for the material. The common assumptions for linear wave propagation in viscoelastic materials include the standard linear solid, Maxwell, Kelvin-Voigt, and fractional derivative models. Typically, the intrinsic parameters of the mathematical model are estimated based on available experimental data to fit the mechanical response of the chosen constitutive law. However, this approach may suffer from the uncertainty of inadequate model selection. In this work, the mathematical modeling and selection of frequency-dependent constitutive laws for linear viscoelastic materials are solely performed based on experimental measurements without imposing any functional frequency dependence. This data-driven methodology involves solving an inverse problem for each frequency.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Pramod Kumar Gupta, Chandrabhan Singh
Summary: In this paper, a novel algorithm is developed to generate the geometrical model of coarse aggregate, and it is further applied in the generation of a finite element model for concrete. Through numerical simulation and comparison with existing literature, the effectiveness of the meso-model is verified.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Xiao Wang, Qingrui Yue, Xiaogang Liu
Summary: This study proposes a graph neural networks-based method to recover the missing connection information in crack meshes, and comparative analysis shows that the trained GraphSAGE outperforms other GNNs on triangular meshing task, revealing the potential of GNNs in restoring missing information.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Dhiraj S. Bombarde, Manish Agrawal, Sachin S. Gautam, Arup Nandy
Summary: The study introduces a novel twenty-seven node quadratic EAS element, addressing the underutilization of quadratic elements in existing 3D EAS elements. Additionally, a six-node wedge and an eighteen-node wedge EAS element are presented in the manuscript.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Hau T. Mai, Seunghye Lee, Joowon Kang, Jaehong Lee
Summary: In this work, an effective Damage-Informed Neural Network (DINN) is developed for pinpointing the position and extent of structural damage. By using a deep neural network and Bayesian optimization algorithm, the proposed method outperforms other algorithms in terms of accuracy and efficiency.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Qingsong Xiong, Qingzhao Kong, Haibei Xiong, Lijia Liao, Cheng Yuan
Summary: This study proposes a novel physics-informed deep 1D convolutional neural network (SSM-CNN) for enhanced seismic response modeling. By construing the differential nexus of state variables derived from the state-space representation of initial structural response, an innovative parameter-free physics-constrained mechanism is designed and embedded for performance enhancement. Experimental validations confirmed the effectiveness and superiority of physics-informed SSM-CNN in seismic response prediction.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
D. Herrero-Perez, S. G. Pico-Vicente
Summary: This work presents an efficient, flexible, and scalable strategy for implementing density-based topology optimization formulation in fail-safe structural design. The use of non-overlapping domain decomposition, adaptive mesh refinement, and computing buffers allows for successful evaluation of fault cases.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Xiangyang Cui, Gongcheng Peng, Qi Ran, Huan Zhang, She Li
Summary: A novel degenerated shell element called MITC4+R is developed, which eliminates various locking problems common to shell elements and significantly improves the computational efficiency. It is based on assumed natural strain method and introduces a physical stabilization term.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Shouyan Jiang, Wangtao Deng, Ean Tat Ooi, Liguo Sun, Chengbin Du
Summary: This study presents an innovative data-driven algorithm that combines the scaled boundary finite element method and a deep learning framework for identifying crack-like defects in large-scale structures. The proposed algorithm accurately determines the number, location, and depth of cracks and is robust to noise. It provides valuable insight into the detection and diagnosis of structural defects.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Shiqiang Qin, Jiacheng Feng, Jian Tang, Xuejin Huo, Yunlai Zhou, Fei Yang, Magd Abdel Wahab
Summary: This study assesses the condition of a CFST arch bridge using in-situ vibration measurements, finite element model updating, and an improved artificial fish swarm algorithm. The results indicate that the bridge has good dynamic performance, but track conditions need improvement before operation.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Md. Imrul Reza Shishir, Alireza Tabarraei
Summary: In this paper, a density-based topology optimization method using neural networks is proposed for designing multi-material domains under combined thermo-mechanical loading. The method achieves automatic sensitivity analysis and removes the need for other optimization algorithms. Experimental results show that the method can handle high-resolution re-sampling, resulting in more refined and smooth optimal topologies.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
Bartosz Sobczyk, Lukasz Pyrzowski, Mikolaj Miskiewicz
Summary: This paper describes the problems encountered during the analysis of the structural response of historic masonry railroad arch bridges. It focuses on the stiffness of the masonry arches, their strengths, and the estimation of railroad load intensity. The paper presents computational models created to efficiently describe the responses of the bridges under typical loading conditions and discusses the outcomes of nonlinear static analyses. The possible causes of the deterioration of the bridges' condition were identified through these analyses.
COMPUTERS & STRUCTURES
(2024)
Article
Computer Science, Interdisciplinary Applications
T. Koudelka, T. Krejci, J. Kruis
Summary: This paper presents a numerical model for the coupled hydro-mechanical behaviour of partially saturated soils, and demonstrates its effective application through a numerical example.
COMPUTERS & STRUCTURES
(2024)
