Engineering › Civil and Structural Engineering

Topology Optimization in Engineering

Works Count: 28302

Wikipedia

Description

This cluster of papers focuses on the application of topology optimization in structural engineering, utilizing methods such as level set, sensitivity analysis, and morphology-based filters. It explores topics such as non-linear elastic structures, compliant mechanisms, additive manufacturing, and multi-material optimization using finite element methods and metaheuristic algorithms.

Keywords

Level Set Method; Sensitivity Analysis; Structural Boundary Design; Morphology-based Filters; Non-linear Elastic Structures; Compliant Mechanisms; Additive Manufacturing; Multi-material Optimization; Finite Element Method; Metaheuristic Algorithms

Introduction to shape optimization

1992-01-01

Jan Sokołowski , Jean-Paul Zolésio

Generalized shape optimization without homogenization

1992-09-01

G. I. N. Rozvany , Mingdong Zhou , T. Birker

Filters in topology optimization based on Helmholtz‐type differential equations

2010-12-28

Boyan S. Lazarov , Ole Sigmund

Abstract The aim of this paper is to apply a Helmholtz‐type partial differential equation as an alternative to standard density filtering in topology optimization problems. Previously, this approach has been … Abstract The aim of this paper is to apply a Helmholtz‐type partial differential equation as an alternative to standard density filtering in topology optimization problems. Previously, this approach has been successfully applied as a sensitivity filter. The usual filtering techniques in topology optimization require information about the neighbor cells, which is difficult to obtain for fine meshes or complex domains and geometries. The complexity of the problem increases further in parallel computing, when the design domain is decomposed into multiple non‐overlapping partitions. Obtaining information from the neighbor subdomains is an expensive operation. The proposed filter technique requires only mesh information necessary for the finite element discretization of the problem. The main idea is to define the filtered variable implicitly as a solution of a Helmholtz‐type differential equation with homogeneous Neumann boundary conditions. The properties of the filter are demonstrated for various 2D and 3D topology optimization problems in linear elasticity, solved on serial and parallel computers. Copyright © 2010 John Wiley & Sons, Ltd.

Topology optimization of non-linear elastic structures and compliant mechanisms

2001-03-01

T.E. Bruns , Daniel A. Tortorelli

A homogenization method for shape and topology optimization

1991-12-01

Katsuyuki Suzuki , Noboru Kikuchi

Rates of change of eigenvalues and eigenvectors.

1968-12-01

R. L. Fox , M. P. Kapoor

Exact expressions for rates of change of eigenvalues and eigenvector to facilitate computerized design of complex structures Exact expressions for rates of change of eigenvalues and eigenvector to facilitate computerized design of complex structures

On the Topological Derivative in Shape Optimization

1999-01-01

Jan Sokołowski , Antoni Żochowski

In this paper the topological derivative for an arbitrary shape functional is defined. Examples are provided for elliptic equations and the elasticity system in the plane. The topological derivative can … In this paper the topological derivative for an arbitrary shape functional is defined. Examples are provided for elliptic equations and the elasticity system in the plane. The topological derivative can be used for solving shape optimization problems in structural mechanics.

View PDF Chat

The COC algorithm, Part II: Topological, geometrical and generalized shape optimization

1991-08-01

Mingdong Zhou , G. I. N. Rozvany

Discrete Optimization of Structures Using Genetic Algorithms

1992-05-01

S. Rajeev , C.S. Krishnamoorthy

Optimizing most structural systems used in practice requires considering design variables as discrete quantities. The paper presents a simple genetic algorithm for optimizing structural systems with discrete design variables. As … Optimizing most structural systems used in practice requires considering design variables as discrete quantities. The paper presents a simple genetic algorithm for optimizing structural systems with discrete design variables. As genetic algorithms (GAs) are best suited for unconstrained optimization problems, it is necessary to transform the constrained problem into an unconstrained one. A penalty‐based transformation method is used in the present work. The penalty parameter depends on the degree of constraint violation, which is found to be wellsuited for a parallel search using genetic algorithms. The concept of optimization using the genetic algorithm is presented in detail using a three‐bar truss problem. All the computations for three successive generations are presented in the form of tables for easy understanding of the algorithm. Two standard problems from literature are solved and results compared. The application of the genetic algorithm to design optimization of a larger problem is illustrated using a 160‐bar transmission tower.

Structural optimization using sensitivity analysis and a level-set method

2003-12-19

Grégoire Allaire , François Jouve , Anca-Maria Toader

View PDF Chat

Level-set methods for structural topology optimization: a review

2013-03-22

Nico P. van Dijk , Kurt Maute , Matthijs Langelaar +1 more

Topology Optimization in Aircraft and Aerospace Structures Design

2015-04-13

Jihong Zhu , Weihong Zhang , Liang Xia

A critical review of established methods of structural topology optimization

2008-02-20

G. I. N. Rozvany

On the Design of Compliant Mechanisms Using Topology Optimization*

1997-01-01

Ole Sigmund

ABSTRACT This paper presents a method for optimal design of compliant mechanism topologies. The method is based on continuum-type topology optimization techniques and finds the optimal compliant mechanism topology within … ABSTRACT This paper presents a method for optimal design of compliant mechanism topologies. The method is based on continuum-type topology optimization techniques and finds the optimal compliant mechanism topology within a given design domain and a given position and direction of input and output forces. By constraining the allowed displacement at the input port, it is possible to control the maximum stress level in the compliant mechanism. The ability of the design method to find a mechanism with complex output behavior is demonstrated by several examples. Some of the optimal mechanism topologies have been manufactured, both in macroscale (hand-size) made in Nylon, and in microscale (<.5mm)) made of micromachined glass. Notes *Communicated by P. Pedersen

Mixed variable structural optimization using Firefly Algorithm

2011-09-14

Amir H. Gandomi , Xin‐She Yang , Amir H. Alavi

An analysis of the finite element method

1980-09-01

Gilbert Strang , George J. Fix , D. S. Griffin

Convergent and mesh-independent solutions for the bi-directional evolutionary structural optimization method

2007-09-21

Xiaodong Huang , Yi Min Xie

On projection methods, convergence and robust formulations in topology optimization

2010-12-23

Fengwen Wang , Boyan S. Lazarov , Ole Sigmund

A simple evolutionary procedure for structural optimization

1993-12-01

Yi Min Xie , Grant P. Steven

An alternative interpolation scheme for minimum compliance topology optimization

2001-09-01

Mathias Stolpe , Krister Svanberg

Optimal shape design as a material distribution problem

1989-12-01

Martin P. Bendsøe

Topology optimization of continuum structures: A review*

2001-07-01

H. Eschenauer , Niels Olhoff

It is of great importance for the development of new products to find the best possible topology or layout for given design objectives and constraints at a very early stage … It is of great importance for the development of new products to find the best possible topology or layout for given design objectives and constraints at a very early stage of the design process (the conceptual and project definition phase). Thus, over the last decade, substantial efforts of fundamental research have been devoted to the development of efficient and reliable procedures for solution of such problems. During this period, the researchers have been mainly occupied with two different kinds of topology design processes; the Material or Microstructure Technique and the Geometrical or Macrostructure Technique. It is the objective of this review paper to present an overview of the developments within these two types of techniques with special emphasis on optimum topology and layout design of linearly elastic 2D and 3D continuum structures. Starting from the mathematical-physical concepts of topology and layout optimization, several methods are presented and the applicability is illustrated by a number of examples. New areas of application of topology optimization are discussed at the end of the article. This review article includes 425 references.

Filters in topology optimization

2001-02-14

Blaise Bourdin

Abstract In this article, a modified (‘filtered’) version of the minimum compliance topology optimization problem is studied. The direct dependence of the material properties on its pointwise density is replaced … Abstract In this article, a modified (‘filtered’) version of the minimum compliance topology optimization problem is studied. The direct dependence of the material properties on its pointwise density is replaced by a regularization of the density field by the mean of a convolution operator. In this setting it is possible to establish the existence of solutions. Moreover, convergence of an approximation by means of finite elements can be obtained. This is illustrated through some numerical experiments. The ‘filtering’ technique is also shown to cope with two important numerical problems in topology optimization, checkerboards and mesh dependent designs. Copyright © 2001 John Wiley & Sons, Ltd.

Achieving minimum length scale in topology optimization using nodal design variables and projection functions

2004-07-15

James K. Guest , Jean H. Prévost , Ted Belytschko

Abstract A methodology for imposing a minimum length scale on structural members in discretized topology optimization problems is described. Nodal variables are implemented as the design variables and are projected … Abstract A methodology for imposing a minimum length scale on structural members in discretized topology optimization problems is described. Nodal variables are implemented as the design variables and are projected onto element space to determine the element volume fractions that traditionally define topology. The projection is made via mesh independent functions that are based upon the minimum length scale. A simple linear projection scheme and a non‐linear scheme using a regularized Heaviside step function to achieve nearly 0–1 solutions are examined. The new approach is demonstrated on the minimum compliance problem and the popular SIMP method is used to penalize the stiffness of intermediate volume fraction elements. Solutions are shown to meet user‐defined length scale criterion without additional constraints, penalty functions or sensitivity filters. No instances of mesh dependence or checkerboard patterns have been observed. Copyright © 2004 John Wiley & Sons, Ltd.

Material interpolation schemes in topology optimization

1999-11-22

Martin P. Bendsøe , Ole Sigmund

Morphology-based black and white filters for topology optimization

2007-01-19

Ole Sigmund

View PDF Chat

A level set method for structural topology optimization

2002-12-27

Michael Yu Wang , Xiaoming Wang , Dongming Guo

A 99 line topology optimization code written in Matlab

2001-04-01

Ole Sigmund

Efficient topology optimization in MATLAB using 88 lines of code

2010-11-18

Erik Andreassen , Anders Clausen , Mattias Schevenels +2 more

View PDF Chat

Topology optimization of fluids in Stokes flow

2002-12-11

Thomas Borrvall , Joakim Petersson

Abstract We consider topology optimization of fluids in Stokes flow. The design objective is to minimize a power function, which for the absence of body fluid forces is the dissipated … Abstract We consider topology optimization of fluids in Stokes flow. The design objective is to minimize a power function, which for the absence of body fluid forces is the dissipated power in the fluid, subject to a fluid volume constraint. A generalized Stokes problem is derived that is used as a base for introducing the design parameterization. Mathematical proofs of existence of optimal solutions and convergence of discretized solutions are given and it is concluded that no regularization of the optimization problem is needed. The discretized state problem is a mixed finite element problem that is solved by a preconditioned conjugate gradient method and the design optimization problem is solved using sequential separable and convex programming. Several numerical examples are presented that illustrate this new methodology and the results are compared to results obtained in the context of shape optimization of fluids. Copyright © 2003 John Wiley & Sons, Ltd.

A survey of structural and multidisciplinary continuum topology optimization: post 2000

2013-07-03

Joshua D. Deaton , Ramana V. Grandhi

A review of homogenization and topology optimization I—homogenization theory for media with periodic structure

1998-12-01

Behrooz Hassani , E. Hinton

Numerical instabilities in topology optimization: A survey on procedures dealing with checkerboards, mesh-dependencies and local minima

1998-08-01

Ole Sigmund , Joakim Petersson

Approximation by finite element functions using local regularization

1975-01-01

Ph. Clément

avec les conditions générales d'utilisation (http://www.numdam.org/legal. avec les conditions générales d'utilisation (http://www.numdam.org/legal.

View PDF Chat

Topology optimization approaches

2013-08-20

Ole Sigmund , Kurt Maute

The Mathematical Theory of Elasticity.

1928-04-01

Carl A. Garabedian , A. E. H. Love

Stochastic Dynamics of Structures

2009-03-26

Jie Li , Jianbing Chen

View PDF Chat

Current and future trends in topology optimization for additive manufacturing

2018-05-03

Jikai Liu , Andrew T. Gaynor , Shikui Chen +7 more

View PDF Chat

Doing Topology Optimization Explicitly and Geometrically—A New Moving Morphable Components Based Framework

2014-05-07

Xu Guo , Weisheng Zhang , Wenliang Zhong

In the present work, we intend to demonstrate how to do topology optimization in an explicit and geometrical way. To this end, a new computational framework for structural topology optimization … In the present work, we intend to demonstrate how to do topology optimization in an explicit and geometrical way. To this end, a new computational framework for structural topology optimization based on the concept of moving morphable components is proposed. Compared with the traditional pixel or node point-based solution framework, the proposed solution paradigm can incorporate more geometry and mechanical information into topology optimization directly and therefore render the solution process more flexibility. It also has the great potential to reduce the computational burden associated with topology optimization substantially. Some representative examples are presented to illustrate the effectiveness of the proposed approach.

View PDF Chat

Minimization Methods for Non-Differentiable Functions

1985-01-01

N. Z. Shor

L. <i>On the calculation of the equilibrium and stiffness of frames</i>

1864-04-01

James Clerk Maxwell

Numerical Optimization

2006-01-01

Jorge Nocedal , Stephen J. Wright

Topology optimization of pneumatic soft actuators based on porohyperelasticity

2025-06-25

Sumit Mehta , Konstantinos Poulios | Computer Methods in Applied Mechanics and Engineering

Geometrically nonlinear isogeometric topology optimization via extended finite element method

2025-06-25

Jianli Liu , Haobo Zhang , Min Qiang +3 more | Computers & Structures

Buckling-constrained topology optimization of multi-phase materials via iso-geometric analysis

2025-06-25

Ning Gan , JoonHyun Kan , Bo Sun | International Journal of Mechanics and Materials in Design

Learning elastoplasticity with implicit layers

2025-06-24

Jérémy Bleyer | Computer Methods in Applied Mechanics and Engineering

Integrating large models with topology optimization for conceptual design realization

2025-06-24

Ze‐Long Liang , Ye Zhang , Yingjun Wang +1 more | Advanced Engineering Informatics

A CPU-parallel thermal topology optimization framework for arbitrary structures using flood fill algorithm and implicit identification model

2025-06-24

Jiawei Wu , Liang Gao , Lin Wang +2 more | Computer Methods in Applied Mechanics and Engineering

Literature Reviews of Topology Optimal Design Methods and Applications in Magnetic Devices

2025-06-24

Jiaqi Wu , Ziyan Ren , Dianhai Zhang | Energies

With the evolution of magnetic devices toward structural innovation and high reliability, the traditional design methods, such as size optimization and shape optimization, are limited by preset structural forms, making … With the evolution of magnetic devices toward structural innovation and high reliability, the traditional design methods, such as size optimization and shape optimization, are limited by preset structural forms, making it challenging to generate novel structures and topologies. Topology-optimized design methods can achieve an optimal distribution of constituent materials of magnetic devices by optimizing the objective performance subject to certain constraints, and can provide greater freedom for designers. Based on the above background, this paper firstly investigates the principles of deterministic topology optimization methods, and introduces the latest specific applications in magnetic devices. It also demonstrates the advantages of topology optimization technology in enhancing operating performance, fostering structural innovation, and improving material utilization in magnetic devices. To manage uncertainties in design and manufacturing processes of magnetic devices, this paper analyzes uncertainty topology optimization methods, respectively, reliability and robustness-based topology optimization algorithms. To facilitate manufacturing, this paper summarizes the filter strategy for the new structure obtained by topology optimization. Finally, the problems faced by the topology optimization method in the field of magnetic devices are discussed, and a future development direction is projected.

Term-sparse polynomial optimization for the design of frame structures

2025-06-24

Marouan Handa , Marek Tyburec , Michal Kočvara | Optimization and Engineering

AI-Driven Generative and Reinforcement Learning for Mechanical Optimization of Two-Dimensional Patterned Hollow Structures

2025-06-23

Yicheng Shan , Leitao Cao , Yu Wang +4 more | Materials Futures

Abstract Two-dimensional patterned hollow structures (2D-PHS) have emerged as advanced materials with exceptional mechanical properties and lightweight characteristics, making them ideal for high-performance applications in aerospace and automotive industries. However, … Abstract Two-dimensional patterned hollow structures (2D-PHS) have emerged as advanced materials with exceptional mechanical properties and lightweight characteristics, making them ideal for high-performance applications in aerospace and automotive industries. However, optimizing their structural design to achieve uniform stress distribution and minimize stress concentrations remains a significant challenge due to the complex interplay between geometric patterns and mechanical performance. In this study, we develop an integrated framework combining Conditional Generative Adversarial Networks (cGAN) and Deep Q-Network (DQN) to predict and optimize the stress fields of 2D-PHS. We generated a comprehensive dataset comprising 1,000 samples across five distinct density classes using a custom grid pattern generation algorithm, ensuring a wide range of structural variations. The cGAN accurately predicts stress distributions, achieving a high correlation with finite element analysis (FEA) results while reducing computational time from approximately 40 seconds (FEA) to just 1-2 seconds per prediction. Concurrently, the DQN optimizes design parameters through scaling and rotation operations, enhancing structural performance based on predicted stress metrics. Our approach resulted in a 4.3% improvement in average stress uniformity and a 23.1% reduction in maximum stress concentrations. These improvements were validated through FEA simulations and experimental tensile tests on 3D printed TPU samples. The tensile strength of optimized samples increased from an initial average of 5.9 MPa to 6.6 MPa under 100% strain, demonstrating enhanced mechanical resilience. This study demonstrates the efficacy of combining advanced AI techniques for rapid and precise material design optimization, providing a scalable and cost-effective solution for developing superior lightweight materials with tailored mechanical properties for critical engineering applications.

Connectivity constraints for eigenvalue reduction in level-set topology optimization

2025-06-23

Giacomo Bonaccorsi , Matteo Pozzi , Jaeyub Hyun +2 more | Computers & Structures

The Semi-Penalized Updated Properties Model and Its Algorithm to Impose the Volume Fraction

2025-06-23

Amin Alibakhshi , Luis Saucedo‐Mora | Materials

Intricate structures with minimal weight and maximum stiffness are demanded in many practical engineering applications. Topology optimization is a method for designing these structures, and the rise of additive manufacturing … Intricate structures with minimal weight and maximum stiffness are demanded in many practical engineering applications. Topology optimization is a method for designing these structures, and the rise of additive manufacturing technologies has opened the door to their production. In a recently published paper, a novel topology optimization algorithm, named the Updated Properties Model (UPM), was developed with the homogenization of strain level as an objective function and an updating Young modulus as the design variable. The UPM method optimizes mechanical structures without applying any constraints. However, including constraints such as volume, mass, and/or stress in topology optimization is prevalent. This paper uses the density-dependent Young modulus concept to incorporate the volume fraction in the UPM method. We address the critical problem of constraint-aware design without the complexity of constraint-handling formulations. We show the proposed methodology’s success and functionality by plotting the algorithm’s results in two- and three-dimensional benchmark structures. Key results present that adjusting algorithmic parameters can yield both binary (single-material) and graded-material solutions, offering flexibility for different applications. These findings suggest that the UPM can effectively replicate constraint-driven outcomes without explicitly enforcing constraints. The main novelty of this work lies in extending the constraint-free UPM framework to allow for controlled material distribution using a physically meaningful update rule. This extends the applicability of the UPM beyond previous efforts in the literature. We have also created a Julia package for our proposal.

A Course in Homogenization-based Techniques

2025-06-22

Adrian Muntean | Advanced textbooks in mathematics

Multiscale Topology Optimization of Functionally Graded Lattice Structure for Energy Absorption

2025-06-22

MITCHELL Michela Lee , Hyunjun Kim , Jae‐Wook Lee | Multiscale Science and Engineering

Integrated optimization framework for multi-domain assemblies: A novel polygon topology to non-matching meshes and materials

2025-06-21

Xinqing Li , Jianghong Yang , Mi Xiao +1 more | Engineering Analysis with Boundary Elements

Structural Topology Optimization With the Simultaneous Constraints to Maximum Contact Pressure and Fatigue Damage

2025-06-21

Jiajia Li , Tong Gao , Ziad Moumni +1 more | International Journal for Numerical Methods in Engineering

ABSTRACT In this work, we develop a topology optimization method for elastic contact problems involving fatigue constraints under proportional loads. The method is formulated by means of B‐spline parameterization of … ABSTRACT In this work, we develop a topology optimization method for elastic contact problems involving fatigue constraints under proportional loads. The method is formulated by means of B‐spline parameterization of the pseudo‐density field to describe the material layout. Both the contact pressure control on the contact surface and fatigue constraint to the whole structure domain are taken into account simultaneously. The accumulated fatigue damage related to the fatigue constraint is calculated based upon the rainflow‐counting scheme, Sines method, S – N curve and Palmgren–Miner's linear damage hypothesis. The Kreisselmeier–Steinhauser (KS) function is adopted as an aggregated measure for both the maximum contact pressure and the maximum fatigue damage. The design sensitivities are derived analytically using the adjoint method. Both frictionless and frictional contact problems are investigated. The influence of fatigue constraints on the optimization result is discussed in comparison with the standard compliance minimization. Frictional contact effects upon the optimized results and fatigue damage are highlighted. Results show that the maximum contact pressure and maximum fatigue damage can effectively be controlled to avoid fatigue failure and that the fatigue strength of the structure can be improved at the cost of structural stiffness.

Development and validation of an offline multiscale topology optimization framework using interpolated constraint functions

2025-06-20

Brent Bielefeldt , Richard Beblo , Kevin Lawson +2 more | Computer Methods in Applied Mechanics and Engineering

Plane Frame Structures: Optimization and Design Solutions Clustering

2025-06-20

Joana S. D. Gaspar , M.A.R. Loja , Joaquim Infante Barbosa | Algorithms

This work aims to constitute a framework dataflow based on the prediction, optimization, and characterization of optimal solutions. To this purpose, a metaheuristic optimization method is used to obtain the … This work aims to constitute a framework dataflow based on the prediction, optimization, and characterization of optimal solutions. To this purpose, a metaheuristic optimization method is used to obtain the optimal design solutions for discrete plane frame structures considering as objective function the minimization of their maximum resultant displacement, subjected to side and behavioral constraints. The design variables that lead to the optimal solutions are constituted into datasets which are subsequently submitted to a clustering analysis. The results obtained provide pertinent insights about the optimal solutions clusters’ ranges, giving effective support to a specific solution selection.

STUDY ON HYBRID METHOD OF COMBINING MATHEMATICAL PROGRAMMING METHOD AND EVOLUTIONARY METHOD FOR TOPOLOGY OPTIMIZATION OF FRAME STRUCTURES

2025-06-19

Yoshikatsu Hayashi , Shinya MATSUMOTO , Masatoshi MANABE +1 more | AIJ Journal of Technology and Design

Phase-field-based structural optimization of 3D cross-lattice structure to lightweight periodic lattice cells

2025-06-18

Leonie Wallat , Martin Reder , Marcus Seiler +3 more | Engineering Optimization

Two-scale concurrent topology optimization of multiple lattice materials with non-uniform thickness interfaces

2025-06-18

Chao Li , Qihan Wang , Minghui Zhang +2 more | Computer Methods in Applied Mechanics and Engineering

Robust topology optimization of multi-material structure with load uncertainty based on element-free Galerkin method

2025-06-18

Jianping Zhang , Tao Chen , Jiahong Chen +4 more | Engineering Structures

Automated elasto-plastic design of truss structures based on residual plastic deformations using a geometrical nonlinear optimization framework

2025-06-18

Péter Grubits , Majid Movahedi Rad | Computers & Structures

Application of topology optimisation in the strut-and-tie method: a review

2025-06-17

Sławomir Dudziak | Archives of Civil Engineering

The paper delivers an overview of the literature concerning the adaption of Topology Optimisation (TO) to the Strut-and-Tie Method (STM). In the beginning, the foundations and basics of STM are … The paper delivers an overview of the literature concerning the adaption of Topology Optimisation (TO) to the Strut-and-Tie Method (STM). In the beginning, the foundations and basics of STM are briefly summarised. STM is a practical implementation of the lower bound theory of plasticity for reinforced concrete (RC). It is generally used to design so-called D-regions (i.e. Discontinuity caused by irregular geometry or concentrated load) working under the complex stress state. These regions are modelled with the equivalent truss consisting of struts (representing the flow of compressive forces carried by concrete), ties (representing rebar) and nodes. The STM algorithm’s most demanding part is determining the layout of the truss, which correctly reflects force flow in a specific D-region. During this stage, TO methods can eliminate the designer’s arbitrary decisions. Analysed literature sources are divided into two groups differing in the adopted TO algorithms: the former uses layout optimisation procedures for trusses, whereas the latter uses TO methods for continuum domains. In the first approach, the equivalent truss is obtained explicitly as an outcome of the TO phase. In the second approach, the material continuum material layout is an inspiration for the ST model or is post-processed with image analysis methods and possibly shape optimisation methods to obtain bending-free bar structures. The advantages and limitations of both approaches are put forward in the conclusion section. Further development in this field is very likely, so future prospects are also anticipated.

Method of Heat Sinks Testing Based on Cooling Curves

2025-06-17

Lenka Dobšáková , Baptiste Zanolini , Vladimír Horák | Advances in science and technology

A heat sink is a cooling device that transfers the dissipated heat away from electronics to the surroundings. The testing method presented in the paper applies the nonequilibrium thermodynamic analysis … A heat sink is a cooling device that transfers the dissipated heat away from electronics to the surroundings. The testing method presented in the paper applies the nonequilibrium thermodynamic analysis of heat sink cooling curves. Here, the heat sink temperature time course is measured by using a thermal imager. The used thermal imager Flir T-640 takes single shots with recording of images. The proposed method validation test was performed on a selected heat sink. By analyzing the heat sink cooling curves, it is possible to obtain courses of the heat power and the heat sink surface to ambient thermal resistance. The presented testing method also enables a thermal analysis to distinguish between the convective and radiative components of heat transfer.

Periodic topology optimization of anisotropic heat conduction structure using the element-free Galerkin method

2025-06-17

Jianping Zhang , Jiahong Chen , Jiangpeng Peng +4 more | Engineering With Computers

Improving the Robustness of the Projected Gradient Descent Method for Nonlinear Constrained Optimization Problems in Topology Optimization

2025-06-16

Lucka Barbeau , Marc‐Étienne Lamarche‐Gagnon , F. Ilinca | International Journal for Numerical Methods in Engineering

ABSTRACT The Projected Gradient Descent (PGD) algorithm is a widely used and efficient first‐order method for solving constrained optimization problems due to its simplicity and scalability in large design spaces. … ABSTRACT The Projected Gradient Descent (PGD) algorithm is a widely used and efficient first‐order method for solving constrained optimization problems due to its simplicity and scalability in large design spaces. Building on recent advancements in the PGD algorithm, where an inertial step component has been introduced to improve efficiency in solving constrained optimization problems, this study introduces two key enhancements to further improve the algorithm's performance and adaptability in large‐scale design spaces. First, univariate constraints (such as design variable bounds constraints) are directly incorporated into the projection step via the Schur complement and an improved active set algorithm with bulk constraints manipulation, avoiding issues with min–max clipping. Second, the update step is decomposed relative to the constraint vector space, enabling a post‐projection adjustment based on the state of the constraints and an approximation of the Lagrangian, significantly improving the algorithm's robustness for problems with nonlinear constraints. Applied to a topology optimization problem for heat sink design, the proposed PGD algorithm demonstrates performance comparable to or exceeding that of the Method of Moving Asymptotes (MMA), with minimal parameter tuning. These results position the enhanced PGD as a robust tool for complex optimization problems with large variable spaces, such as topology optimization problems.

Multiscale topology optimization of architected fiber reinforced composites considering manufacturability

2025-06-16

Arijit Pradhan , Narasimha Boddeti | Computer Methods in Applied Mechanics and Engineering

Evaluating the Efficiency of Nature-Inspired Algorithms for Finite Element Optimization in the ANSYS Environment

2025-06-16

Antonino Cirello , Tommaso Ingrassia , Antonio Mancuso +3 more | Applied Sciences

Nature-inspired metaheuristics have proven effective for addressing complex structural optimization challenges where traditional deterministic or gradient-based methods often fall short. This study investigates the feasibility and benefits of embedding three … Nature-inspired metaheuristics have proven effective for addressing complex structural optimization challenges where traditional deterministic or gradient-based methods often fall short. This study investigates the feasibility and benefits of embedding three prominent metaheuristic algorithms, the Genetic Algorithm (GA), the Firefly Algorithm (FA), and the Group Search Optimizer (GSO) embedded into the ANSYS Parametric Design Language (APDL). The performance of each optimizer was assessed in three case studies. The first two are spatial truss structures, one comprising 22 bars and the other 25 bars, commonly used in structural optimization research. The third is a planar 15-bar truss in which member sizing and internal topology were simultaneously refined using a Discrete Topology (DT) variable method. For both the FA and the GSO, enhanced ranger-movement strategies were implemented to improve exploration–exploitation balance. Comparative analyses were conducted to assess convergence behavior, solution quality, and computational efficiency across the different metaheuristics. The results underscore the practical advantages of a fully integrated APDL approach, highlighting improvements in execution speed, workflow automation, and overall robustness. This work not only provides a comprehensive performance comparison of GA, FA, and GSO in structural optimization tasks, but it can also be considered a novelty in employing native APDL routines for metaheuristic-based finite element analysis.

Stress‐Constrained Topology Optimization With the Augmented Lagrangian Method: A Comparative Study of Subproblem Solvers

2025-06-16

Gustavo Assis da Silva , Hélio Emmendoerfer | International Journal for Numerical Methods in Engineering

ABSTRACT Incorporating stress constraints in topology optimization is a challenging task due to the large number of constraints in the formulation. One effective strategy to address this challenge is the … ABSTRACT Incorporating stress constraints in topology optimization is a challenging task due to the large number of constraints in the formulation. One effective strategy to address this challenge is the augmented Lagrangian (AL) method, which transforms the original stress‐constrained problem into a sequence of subproblems with only bound constraints. The effectiveness of the AL method heavily depends on the optimization method used to solve these subproblems. This work performs a comparative study of six optimization solvers: The method of moving asymptotes (MMA), the steepest descent method with move limits (SDM), the spectral projected gradient (SPG), and the limited‐memory BFGS with bound constraints (L‐BFGS‐B), along with two proposed adaptations, steepest descent method with move limits—Barzilai–Borwein (SDMBB) and spectral projected gradient with move limits (SPGM). These methods are evaluated in the context of the volume minimization problem with local stress constraints. The solutions are compared in terms of performance, defined as the final volume fraction, and efficiency, measured by the number of state and adjoint analyses required. A mesh dependence study is conducted to assess the robustness of each method across different mesh sizes, including high‐resolution cases with approximately 1.8 million elements. SDMBB exhibits the highest efficiency, while SPGM achieves the best performance, followed by SDM. The MMA, SPG, and L‐BFGS‐B show limitations in high‐resolution problems or fail to meet specific stopping criteria. The results demonstrate that the choice of the optimization solver significantly affects the efficiency of the AL method, as well as the performance and mesh dependence of the solutions. Furthermore, this study identifies the most promising methods for solving large‐scale stress‐constrained problems.

Node-based body-fitted topology optimization with a boundary-preserving sensitivity filter

2025-06-16

Yulin Xiong , Zicheng Zhuang , Yunzhen He +2 more | Engineering Structures

Time-averaged algorithm for solving the topology optimization problem for unsteady laminar, turbulent and anisothermal flows

2025-06-14

Delphine Ramalingom , Alain Bastide , Pierre-Henri Cocquet +2 more | Journal of Computational Physics

Novel parameter and topology combination optimization of switched reluctance motor for multi-objective performance improvement

2025-06-14

Tong Ben , Bo Yin , Long Chen +2 more | COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

Purpose This paper aims to propose a novel parameter and topology combination optimization method of switched reluctance motors with an amorphous alloy core (SRMA), which can take into account the … Purpose This paper aims to propose a novel parameter and topology combination optimization method of switched reluctance motors with an amorphous alloy core (SRMA), which can take into account the vibration and torque of SRMA and achieve multi-objective performance improvement. Design/methodology/approach First, the stator pressing structure is designed according to the force− magnetic coupling relationship, which is based on the inverse-magnetostrictive effect by parameter optimization, and the rotor structure is designed according to a solid isotropic with material penalization-based method by topology optimization. Second, a novel parameter and topology combination optimization model is established. Then, the optimal pressure value of stator teeth and the optimal rotor structure are obtained by the proposed method. Finally, the novel parameter and topology method is verified by simulations and experiments. Findings The results verify the efficacy of the proposed method and the accuracy of the proposed numerical analysis model. The magnetostriction effect and its inverse effect cannot be ignored in motor design. Compared with the motor before optimization, the average torque is increased by 11%, the maximum vibration displacement is reduced by 37% and the torque ripple is not increased. Originality/value The novel parameter and topology combination optimization method proposed in this paper takes into account the magnetostrictive effect and its inverse effect of motor core materials and establishes an electromagnetic-mechanical coupling numerical analysis model of SRMA, which improves the multi-objective performance of motor.

Optimal design methodology for negative stiffness structures considering lifespan and additive manufacturing uncertainty

2025-06-12

Hyung-Do Kim , Young-Jin Kang , Yoojeong Noh | Smart Materials and Structures

Abstract Negative stiffness honeycomb unit cells (NSH-UCs), which employ negative stiffness beams (NSBs), are capable of absorbing impact energy and are reusable, making them promising for energy-absorbing structural applications. However, … Abstract Negative stiffness honeycomb unit cells (NSH-UCs), which employ negative stiffness beams (NSBs), are capable of absorbing impact energy and are reusable, making them promising for energy-absorbing structural applications. However, limited research has addressed their operational lifespan and manufacturing variability, both of which are critical for practical implementation. This study aims to establish a design optimization framework for NSH-UCs that accounts for both performance metrics—such as energy absorption—and operational aspects like reusability and manufacturing-induced uncertainty. To this end, NSH-UC samples with varying dimensions were fabricated using fused filament fabrication (FFF) with PLA/PHA filaments, and their mechanical behavior was evaluated through quasi-static and cyclic compression tests. A surrogate-based optimization method was then applied to improve energy absorption and extend service life, while considering geometric and material uncertainties inherent to the additive manufacturing process. The proposed framework led to a significant improvement in energy absorption (EA) and end-of-life (EOL) performance compared to the initial design, despite only modest changes in specific energy absorption (SEA). These findings demonstrate the feasibility of incorporating performance, reliability, and manufacturing variability into early-stage design, highlighting the framework’s potential for structural health monitoring (SHM) and prognostic health management (PHM) applications.&#xD;

Topology optimization of cold plate for battery thermal management based on length scale control

2025-06-12

Na Deng , Qiuxiao Huang , Yang Li +5 more | International Journal of Heat and Mass Transfer

Improvement of adaptive optimization technique with low computational cost for size and topology optimization of truss structures under seismic excitation

2025-06-12

Hassan Moghaddam , Mohsen Zare Golmoghany | Structures

Comparing the Performance of Domain Transform-based Differential Evolution with Recent CEC Competition Winners on the CEC2025 Numerical Optimization

2025-06-08

Xin Rou Hu , Jun Luo , Sheng Xin Zhang | 2022 IEEE Congress on Evolutionary Computation (CEC)