Topology and shape optimization methods using evolutionary algorithms: a review

2015 ◽  
Vol 52 (3) ◽  
pp. 613-631 ◽  
Author(s):  
David J. Munk ◽  
Gareth A. Vio ◽  
Grant P. Steven
2015 ◽  
Vol 789-790 ◽  
pp. 306-310
Author(s):  
Jin Woo Lee

This work presents the framework to optimally design a cantilever for torsion mode frequency maximization. A cantilever design problem is formulated by topology and shape optimization methods. The torsion mode frequency is selected as an objective function, and the volume of the cantilever and the first bending mode frequency are constrained. Two optimization problems are defined and sequentially solved for the specific values. A new idea in this work is using a final topology obtained in the topology optimization problem as an initial shape in the shape optimization problem. The torsional mode frequency of the optimized cantilever is well improved in comparison with a nominal cantilever.


2021 ◽  
Vol 64 (4) ◽  
pp. 2687-2707
Author(s):  
Gabriel Stankiewicz ◽  
Chaitanya Dev ◽  
Paul Steinmann

AbstractDensity-based topology optimization and node-based shape optimization are often used sequentially to generate production-ready designs. In this work, we address the challenge to couple density-based topology optimization and node-based shape optimization into a single optimization problem by using an embedding domain discretization technique. In our approach, a variable shape is explicitly represented by the boundary of an embedded body. Furthermore, the embedding domain in form of a structured mesh allows us to introduce a variable, pseudo-density field. In this way, we attempt to bring the advantages of both topology and shape optimization methods together and to provide an efficient way to design fine-tuned structures without predefined topological features.


Author(s):  
D Spath ◽  
W Neithardt ◽  
C Bangert

International competition forces companies to use computer methods in order to accelerate the time-consuming development processes and further to improve the product quality. The use of numeric optimization methods can be very helpful to obtain ‘systematic and proper’ solution variants. Solutions that have been generated automatically provide the designer with new, previously unknown suggestions for problem solution. These structural optimization tools have not yet been sufficiently integrated into the design process. Within a research project, software companies, research institutes and users are working on the integration of topology and shape optimization. This article presents an example of this process and describes the potential of the structure optimization tools based on the example of a machine tool.


2021 ◽  
Author(s):  
Jafar Zamani ◽  
Ali Sadr ◽  
Amir-Homayoun Javadi

AbstractsIdentifying individuals with early mild cognitive impairment (EMCI) can be an effective strategy for early diagnosis and delay the progression of Alzheimer’s disease (AD). Many approaches have been devised to discriminate those with EMCI from healthy control (HC) individuals. Selection of the most effective parameters has been one of the challenging aspects of these approaches. In this study we suggest an optimization method based on five evolutionary algorithms that can be used in optimization of neuroimaging data with a large number of parameters. Resting-state functional magnetic resonance imaging (rs-fMRI) measures, which measure functional connectivity, have been shown to be useful in prediction of cognitive decline. Analysis of functional connectivity data using graph measures is a common practice that results in a great number of parameters. Using graph measures we calculated 1155 parameters from the functional connectivity data of HC (n=36) and EMCI (n=34) extracted from the publicly available database of the Alzheimer’s disease neuroimaging initiative database (ADNI). These parameters were fed into the evolutionary algorithms to select a subset of parameters for classification of the data into two categories of EMCI and HC using a two-layer artificial neural network. All algorithms achieved classification accuracy of 94.55%, which is extremely high considering single-modality input and low number of data participants. These results highlight potential application of rs-fMRI and efficiency of such optimization methods in classification of images into HC and EMCI. This is of particular importance considering that MRI images of EMCI individuals cannot be easily identified by experts.


Author(s):  
G.B. Kryzhevich ◽  
A.R. Filatov

Объектом исследования является крышка люкового закрытия сухогрузного судна, служащая для обеспечения непроницаемости грузовых помещений и перевозки на ней грузов и обеспечивающая безопасность сухогрузных судов и осуществляемой на них морской перевозки грузов. Большая материалоемкость крышек снижает экономическую эффективность судна, ведет к необходимости использования мощных и массогабаритных средств подъема крышек (для съемных люковых закрытий), либо поворота и передвижения крышек (для шарнирно-откидных закрытий). Целью статьи является существенное снижение материалоемкости крышек люкового закрытия за счет рационального выбора их материала и конструктивного оформления при одновременном обеспечении требуемого уровня их надежности. Параметрическая оптимизация традиционной стальной крышки люкового закрытия сухогрузного судна проекта RSD59 может привести к снижению ее массы не более чем на 15-17. Поэтому для достижения цели работы решается задача оптимизации конструкции алюминиевой крышки на основе комплексного подхода, состоящего в последовательном использовании топологических и параметрических оптимизационных методов и выполнении на последней стадии работы снижения уровня концентрации напряжений путем оптимизации формы узлов крышки. При этом на стадии выбора конструктивно-силовой схемы крышки применяются приёмы топологической оптимизации, на стадии выбора толщин и параметров силовых элементов способы параметрической оптимизации, а на стадии конструктивно-технологического оформления узлов методы оптимизации формы. Выполненные расчетные исследования привели к следующим основным результатам: к выявлению прогрессивных конструктивно-силовых схем и конструктивно-технологических решений, обеспечивающих значительное снижению массы крышек люковых закрытий при умеренных затратах на их изготовление к высоким оценкам эффективности использования современных алюминиевых сплавов для изготовления люковых закрытий, способствующим существенному снижению их материалоемкости (примерно двукратному и более по сравнению с использованием стали), улучшению условий их функционирования и проведения погрузочно-разгрузочных работ на сухогрузных судах к выводу об эффективности использования разработанных конструкторских решений для крышек люковых закрытий при создании перспективных сухогрузных судов.A bulk carrier hatch cover, which provides cargo compartments impermeability and cargo transportation on the cover, as well as safety of bulk carriers and sea cargo transportation in them, is studied. Cover high material consumption decreases vessel profitability, causes the necessity to use either powerful and mass-dimensional cover lifting devices (for removable hatch covers) or covers rotation and movement (for hinged covers). The purpose of this paper consists in considerable decrease of hatch cover material consumption through rational selection of covers material and design at provision of the required covers reliability level. Parametric optimization of a conventional steel cover of RSD59 project bulk carrier could result in cover mass decrease by more than 15 to 17. Therefore, to achieve the work purpose, a problem of aluminum cover structural optimization was solved based on a comprehensive approach that consisted in successive use of topologic and parametric optimization methods and decrease of the stress concentration level at the last step via cover assemblies shape optimization. At that topological optimization methods were applied at the stage of selecting cover structural arrangement parametric optimization methods were applied at the stage of selecting load-carrying elements thickness and parameters, and shape optimization methods were used at the stage of structural and technology design of assemblies. The performed calculation studies resulted in the following: revealing the advanced structural arrangements and design and technology solutions that provide considerable hatch covers mass decrease at reasonable costs for their manufacture high assessment of using advanced aluminum alloys for manufacturing hatch covers that promote considerable decrease of their material consumption (approximately up to twofold or greater in comparison with steel), improving conditions of cover functioning and handling operation in bulk carriers conclusion on effectiveness of using developed design solutions for hatch covers when creating prospective bulk carriers.


2013 ◽  
pp. 105-129 ◽  
Author(s):  
Cedric Gondro ◽  
Paul Kwan

Evolutionary Computation (EC) is a branch of Artificial Intelligence which encompasses heuristic optimization methods loosely based on biological evolutionary processes. These methods are efficient in finding optimal or near-optimal solutions in large, complex non-linear search spaces. While evolutionary algorithms (EAs) are comparatively slow in comparison to deterministic or sampling approaches, they are also inherently parallelizable. As technology shifts towards multicore and cloud computing, this overhead becomes less relevant, provided a parallel framework is used. In this chapter the authors discuss how to implement and run parallel evolutionary algorithms in the popular statistical programming language R. R has become the de facto language for statistical programming and it is widely used in biostatistics and bioinformatics due to the availability of thousands of packages to manipulate and analyze data. It is also extremely easy to parallelize routines within R, which makes it a perfect environment for evolutionary algorithms. EC is a large field of research, and many different algorithms have been proposed. While there is no single silver bullet that can handle all classes of problems, an algorithm that is extremely simple, efficient, and with good generalization properties is Differential Evolution (DE). Herein the authors discuss step-by-step how to implement DE in R and how to parallelize it. They then illustrate with a toy genome-wide association study (GWAS) how to identify candidate regions associated with a quantitative trait of interest.


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