Author
Grant P. Steven
Other affiliations: Victoria University, Australia, Durham University, University of Western Sydney
Bio: Grant P. Steven is an academic researcher from University of Sydney. The author has contributed to research in topics: Finite element method & Topology optimization. The author has an hindex of 51, co-authored 197 publications receiving 10269 citations. Previous affiliations of Grant P. Steven include Victoria University, Australia & Durham University.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a simple evolutionary procedure is proposed for shape and layout optimization of structures, where low stressed material is progressively eliminated from the structure during the evolution process, and various examples are presented to illustrate the optimum structural shapes and layouts achieved by this procedure.
1,975 citations
TL;DR: In this paper, a model-dependent method with piezoelectric sensor and actuator incorporated into composite structures is proposed for on-line damage detection and health-monitoring on composite structures.
753 citations
Book•
08 Aug 1997
TL;DR: ESO as discussed by the authors is a computer program that performs structural optimization for multiple load cases and multiple support environments, including Pin-and Rigid-Jointed Frames and Structures with Stiffness or Desplacement Contraints.
Abstract: Contents: Preface.- Introduction.- Basic Evolutionary Structural Optimization.- ESO for Multiple Load Cases and Multiple Support Environments.- Structures with Stiffness or Desplacement Contraints.- Frequency Optimization.- Optimization Against Buckling.- ESO for Pin- and Rigid-Jointed Frames.- ESO for Shape Optimization and the Reduction of Stress Concentrations.- ESO Computer Program Evolve97.- Author Index.- Subject Index.
674 citations
TL;DR: In this article, the authors combine the basic ESO with the additive evolutionary structural optimisation (AESO) to produce bidirectional ESO whereby material can be added and can be removed.
Abstract: Describes development work to combine the basic ESO with the additive evolutionary structural optimisation (AESO) to produce bidirectional ESO whereby material can be added and can be removed. It will be shown that this provides the same results as the traditional ESO. This has two benefits, it validates the whole ESO concept and there is a significant time saving since the structure grows from a small initial one rather than contracting from a sometimes huge initial one where 90 per cent of the material gets removed over many hundreds of finite element analysis (FEA) evolutionary cycles. Presents a brief background to the current state of Structural Optimisation research. This is followed by a discussion of the strategies for the bidirectional ESO (BESO) algorithm and two examples are presented.
463 citations
TL;DR: In this article, the authors present an overview of the modelling that has been proposed by various workers in the field of smart or intelligent structures, and present the main objective of this article.
Abstract: The main objective of this article is to present an overview of the modelling that has been proposed by various workers in the field of smart or intelligent structures. Before the main discussion o...
309 citations
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TL;DR: A survey of current continuous nonlinear multi-objective optimization concepts and methods finds that no single approach is superior and depends on the type of information provided in the problem, the user's preferences, the solution requirements, and the availability of software.
Abstract: A survey of current continuous nonlinear multi-objective optimization (MOO) concepts and methods is presented. It consolidates and relates seemingly different terminology and methods. The methods are divided into three major categories: methods with a priori articulation of preferences, methods with a posteriori articulation of preferences, and methods with no articulation of preferences. Genetic algorithms are surveyed as well. Commentary is provided on three fronts, concerning the advantages and pitfalls of individual methods, the different classes of methods, and the field of MOO as a whole. The Characteristics of the most significant methods are summarized. Conclusions are drawn that reflect often-neglected ideas and applicability to engineering problems. It is found that no single approach is superior. Rather, the selection of a specific method depends on the type of information that is provided in the problem, the user’s preferences, the solution requirements, and the availability of software.
4,263 citations
TL;DR: A new approach to structural topology optimization that represents the structural boundary by a level set model that is embedded in a scalar function of a higher dimension that demonstrates outstanding flexibility of handling topological changes, fidelity of boundary representation and degree of automation.
2,404 citations
TL;DR: It is shown that only 49 Matlab input lines are required for solving a well-posed topology optimization problem and by adding three additional lines, the program can solve problems with multiple load cases.
Abstract: The paper presents a compact Matlab implementation of a topology optimization code for compliance minimization of statically loaded structures. The total number of Matlab input lines is 99 including optimizer and Finite Element subroutine. The 99 lines are divided into 36 lines for the main program, 12 lines for the Optimality Criteria based optimizer, 16 lines for a mesh-independency filter and 35 lines for the finite element code. In fact, excluding comment lines and lines associated with output and finite element analysis, it is shown that only 49 Matlab input lines are required for solving a well-posed topology optimization problem. By adding three additional lines, the program can solve problems with multiple load cases. The code is intended for educational purposes. The complete Matlab code is given in the Appendix and can be down-loaded from the web-site http://www.topopt.dtu.dk.
1,956 citations
TL;DR: An overview, comparison and critical review of the different approaches to topology optimization, their strengths, weaknesses, similarities and dissimilarities and suggests guidelines for future research.
Abstract: Topology optimization has undergone a tremendous development since its introduction in the seminal paper by Bendsoe and Kikuchi in 1988. By now, the concept is developing in many different directions, including “density”, “level set”, “topological derivative”, “phase field”, “evolutionary” and several others. The paper gives an overview, comparison and critical review of the different approaches, their strengths, weaknesses, similarities and dissimilarities and suggests guidelines for future research.
1,816 citations
TL;DR: The state-of-the-art of topological design and manufacturing processes of various types of porous metals, in particular for titanium alloys, biodegradable metals and shape memory alloys are reviewed.
1,393 citations