Multidomain Topology Optimization for Structural and Material Designs

2005 ◽  
Vol 73 (4) ◽  
pp. 565-573 ◽  
Author(s):  
Zheng-Dong Ma ◽  
Noboru Kikuchi ◽  
Christophe Pierre ◽  
Basavaraju Raju
Keyword(s):  
Topology Optimization ◽  
Engineering Design ◽  
Optimization Technique ◽  
Functionally Graded ◽  
Material Distribution ◽  
Design Problems ◽  
Linearization Methods ◽  
Engineering Design Problems ◽  
Wide Range ◽  
Multiple Materials

A multidomain topology optimization technique (MDTO) is developed, which extends the standard topology optimization method to the realm of more realistic engineering design problems. The new technique enables the effective design of a complex engineering structure by allowing the designer to control the material distribution among the subdomains during the optimal design process, to use multiple materials or composite materials in the various subdomains of the structure, and to follow a desired pattern or tendency for the material distribution. A new algorithm of Sequential Approximate Optimization (SAO) is proposed for the multidomain topology optimization, which is an enhancement and a generalization of previous SAO algorithms (including Optimality Criteria and Convex Linearization methods, etc.). An advanced substructuring method using quasi-static modes is also introduced to condense the nodal variables associated with the multidomain topology optimization problem, especially for the nondesign subdomains. The effectiveness of the new MDTO approach is demonstrated for various design problems, including one of “structure-fixture simultaneous design,” one of “functionally graded material design,” and one of “crush energy management.” These case studies demonstrate the potential significance of the new capability developed for a wide range of engineering design problems.

Improved hybrid Strength Pareto Evolutionary Algorithms for multi-objective optimization

2018 ◽  
Vol 11 (1) ◽  
pp. 20-46 ◽  
Author(s):  
K. Shankar ◽  
Akshay S. Baviskar
Keyword(s):  
Engineering Design ◽  
Nsga Ii ◽  
Design Problems ◽  
Content Type ◽  
Multi Objective ◽  
Decision Variables ◽  
Engineering Design Problems ◽  
Wide Range ◽  
Conflicting Objectives ◽  
Utopia Point

Purpose The purpose of this paper is to design an improved multi-objective algorithm with better spread and convergence than some current algorithms. The proposed application is for engineering design problems. Design/methodology/approach This study proposes two novel approaches which focus on faster convergence to the Pareto front (PF) while adopting the advantages of Strength Pareto Evolutionary Algorithm-2 (SPEA2) for better spread. In first method, decision variables corresponding to the optima of individual objective functions (Utopia Point) are strategically used to guide the search toward PF. In second method, boundary points of the PF are calculated and their decision variables are seeded to the initial population. Findings The proposed methods are tested with a wide range of constrained and unconstrained multi-objective test functions using standard performance metrics. Performance evaluation demonstrates the superiority of proposed algorithms over well-known existing algorithms (such as NSGA-II and SPEA2) and recent ones such as NSLS and E-NSGA-II in most of the benchmark functions. It is also tested on an engineering design problem and compared with a currently used algorithm. Practical implications The algorithms are intended to be used for practical engineering design problems which have many variables and conflicting objectives. A complex example of Welded Beam has been shown at the end of the paper. Social implications The algorithm would be useful for many design problems and social/industrial problems with conflicting objectives. Originality/value This paper presents two novel hybrid algorithms involving SPEA2 based on: local search; and Utopia point directed search principles. This concept has not been investigated before.

Multi-Domain Topology Optimization for Vehicle Substructure Design

2002 ◽  
Author(s):  
Zheng-Dong Ma ◽  
Noboru Kikuchi ◽  
Christophe Pierre ◽  
Basavaraju Raju
Keyword(s):  
Topology Optimization ◽  
Design Problem ◽  
Degrees Of Freedom ◽  
Optimization Technique ◽  
Synthesis Method ◽  
Material Design ◽  
Functionally Graded ◽  
Structural Domain ◽  
Management Problem ◽  
Design Problems

Topology optimization of a structure is generally considered as a problem of optimum material distribution (OMD) within a given structural domain, subject to a given amount of material and to boundary conditions and loading conditions applied to the structure. The effective design of a complex engineering structure, however, may require controllability over how the material should be distributed among the various subdomains of the structure, as well as even the use of different materials for the different subdomains. A multi-domain topology optimization technique is therefore proposed in this paper, which is based upon the homogenization method, and which employs a generalized Sequential Approximation Optimization (GSAO) algorithm. This algorithm enhances the capabilities of current topology optimization methods by using advanced updating rules and providing additional flexibility in the optimization process, thus resulting in improved convergence and higher computational efficiency. A Component Mode Synthesis method is also employed, which can significantly reduce the number of degrees of freedom associated with the subdomains whose designs are fixed at the current stage. Several example design problems are considered, including a “structure-fixture simultaneous design” problem, a “functionally graded material design” problem, a “crush energy management” problem, and a “truck frame design” problem that illustrates how the technique developed can be applied to real vehicle substructure design problems.

Multidomain Topology Optimization for Crashworthiness Based on Hybrid Cellular Automata

2011 ◽  
Vol 486 ◽  
pp. 250-253 ◽  
Author(s):  
Lian Shui Guo ◽  
Jun Huang ◽  
Andres Tavor ◽  
John E. Renaud
Keyword(s):  
Topology Optimization ◽  
Element Analysis ◽  
Design Problems ◽  
Practical Applications ◽  
Control Rules ◽  
Engineering Design Problems ◽  
Wide Range ◽  
Result Show ◽  
Update Rules ◽  
Structure Result

This research introduces a multidomain topology optimization algorithm for crashworthy structure undergoing large deformations. This technique makes use of the hybrid cellular automaton framework, which combines transient, non-linear finite-element analysis and local control rules acting on cells. The set of all cells defines the multidomains. Each subdomain has been defined by different material update rules according to specify constraint, and optimization iteration of each subdomain has been converged respectively during the optimal design process. The effectiveness of this technique is demonstrated through the design of a bumper-like structure. Result show that the new algorithm is suitable for practical applications. The case study presented demonstrates the potential significance of this work for a wide range of engineering design problems.

scholarly journals Improved Efficient Projection Density Function Based on Topology Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Nouman Saeed ◽  
Kai Long ◽  
Jamshed Ahmed Ansari ◽  
Nasif Raza Jaffri ◽  
Usama Abrar
Keyword(s):  
Topology Optimization ◽  
Optimization Technique ◽  
Minimum Length ◽  
Design Problems ◽  
Manufacturing Costs ◽  
Minimum Compliance ◽  
Engineering Design Problems ◽  
Optimization Formulation ◽  
Solid Phases ◽  
Minimum Length Scale

Topology optimization is a powerful tool having capability of generating new solution to engineering design problems, while these designs enhance manufacturability and reduce manufacturing costs in a computational setting. Mesh-independent convergence and other techniques have been widely used as topology optimization technique, but they produce gray transition regions which is not a favorable condition for any material. In this article, a modified topology optimization formulation using a new function has been proposed. The suggested scheme makes use of the Heaviside Projection Method (HPM) to continuum topology optimization. Such technique is helpful to obtain the minimum length scale influence on void and solid phases. Application of this proposed approach is implemented to obtain the minimum compliance for macrostructures. Numerical remarkable examples illustrate the noteworthy value of the proposed approach.

Standards, Codes of Practice and Expert Systems

1988 ◽  
Vol 21 (1) ◽  
pp. 5-9 ◽  
Author(s):  
E G McCluskey ◽  
S Thompson ◽  
D M G McSherry
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Engineering Design ◽  
Performance Criteria ◽  
Design Problems ◽  
Codes Of Practice ◽  
Engineering Design Problems ◽  
And Performance

Many engineering design problems require reference to standards or codes of practice to ensure that acceptable safety and performance criteria are met. Extracting relevant data from such documents can, however, be a problem for the unfamiliar user. The use of expert systems to guide the retrieval of information from standards and codes of practice is proposed as a means of alleviating this problem. Following a brief introduction to expert system techniques, a tool developed by the authors for building expert system guides to standards and codes of practice is described. The steps involved in encoding the knowledge contained in an arbitrarily chosen standard are illustrated. Finally, a typical consultation illustrates the use of the expert system guide to the standard.

Biologically Inspired Design: A Macrocognitive Account

2010 ◽  
Author(s):  
Swaroop S. Vattam ◽  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Biological Sciences ◽  
Information Processing ◽  
Engineering Design ◽  
Design Patterns ◽  
Information Processing Model ◽  
Biologically Inspired ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Other Information ◽  
Biologically Inspired Design

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.

scholarly journals Lévy-Flight Moth-Flame Algorithm for Function Optimization and Engineering Design Problems

2016 ◽  
Vol 2016 ◽  
pp. 1-22 ◽  
Author(s):  
Zhiming Li ◽  
Yongquan Zhou ◽  
Sen Zhang ◽  
Junmin Song
Keyword(s):  
Engineering Design ◽  
Function Optimization ◽  
Superior Performance ◽  
Local Optimum ◽  
Lévy Flight ◽  
Design Problems ◽  
Levy Flight ◽  
Spiral Path ◽  
Straight Line ◽  
Engineering Design Problems

The moth-flame optimization (MFO) algorithm is a novel nature-inspired heuristic paradigm. The main inspiration of this algorithm is the navigation method of moths in nature called transverse orientation. Moths fly in night by maintaining a fixed angle with respect to the moon, a very effective mechanism for travelling in a straight line for long distances. However, these fancy insects are trapped in a spiral path around artificial lights. Aiming at the phenomenon that MFO algorithm has slow convergence and low precision, an improved version of MFO algorithm based on Lévy-flight strategy, which is named as LMFO, is proposed. Lévy-flight can increase the diversity of the population against premature convergence and make the algorithm jump out of local optimum more effectively. This approach is helpful to obtain a better trade-off between exploration and exploitation ability of MFO, thus, which can make LMFO faster and more robust than MFO. And a comparison with ABC, BA, GGSA, DA, PSOGSA, and MFO on 19 unconstrained benchmark functions and 2 constrained engineering design problems is tested. These results demonstrate the superior performance of LMFO.

Sign in / Sign up

Export Citation Format

Share Document