Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology Optimization
This paper explores implementation of self-weight and inertial loading in topology optimization (TO) employing the Simulated Annealing (SA) algorithm as a non-gradient-based technique. This method can be applied to find optimum design of structures with no need for gradient information. To enhance t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/12/1/25 |
| _version_ | 1797343160629723136 |
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| author | Hossein Rostami Najafabadi Thiago C. Martins Marcos S. G. Tsuzuki Ahmad Barari |
| author_facet | Hossein Rostami Najafabadi Thiago C. Martins Marcos S. G. Tsuzuki Ahmad Barari |
| author_sort | Hossein Rostami Najafabadi |
| collection | DOAJ |
| description | This paper explores implementation of self-weight and inertial loading in topology optimization (TO) employing the Simulated Annealing (SA) algorithm as a non-gradient-based technique. This method can be applied to find optimum design of structures with no need for gradient information. To enhance the convergence of the SA algorithm, a novel approach incorporating the crystallization factor is introduced. The method is applied in a benchmark problem of a cantilever beam. The study systematically examines multiple scenarios, including cases with and without self-weight effects, as well as varying point loads. Compliance values are calculated and compared to those reported in existing literature to validate the accuracy of the optimization results. The findings highlight the versatility and effectiveness of the SA-based TO methodology in addressing complex design challenges with considerable self-weight or inertial effect. This work can contribute to structural design of systems where only the objective value is available with no gradient information to use sensitivity-based algorithms. |
| first_indexed | 2024-03-08T10:43:44Z |
| format | Article |
| id | doaj.art-d22a5426da484528b8d3a67461157685 |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-08T10:43:44Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-d22a5426da484528b8d3a674611576852024-01-26T17:23:48ZengMDPI AGMachines2075-17022023-12-011212510.3390/machines12010025Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology OptimizationHossein Rostami Najafabadi0Thiago C. Martins1Marcos S. G. Tsuzuki2Ahmad Barari3Advanced Digital Design, Manufacturing and Metrology Labs (AD2MLabs), Department of Mechanical and Manufacturing Engineering, University of Ontario Institute of Technology (Ontario Tech), Oshawa, ON L1G 0C5, CanadaEscola Politécnica, Universidade de São Paulo, São Paulo 05508-030, BrazilEscola Politécnica, Universidade de São Paulo, São Paulo 05508-030, BrazilAdvanced Digital Design, Manufacturing and Metrology Labs (AD2MLabs), Department of Mechanical and Manufacturing Engineering, University of Ontario Institute of Technology (Ontario Tech), Oshawa, ON L1G 0C5, CanadaThis paper explores implementation of self-weight and inertial loading in topology optimization (TO) employing the Simulated Annealing (SA) algorithm as a non-gradient-based technique. This method can be applied to find optimum design of structures with no need for gradient information. To enhance the convergence of the SA algorithm, a novel approach incorporating the crystallization factor is introduced. The method is applied in a benchmark problem of a cantilever beam. The study systematically examines multiple scenarios, including cases with and without self-weight effects, as well as varying point loads. Compliance values are calculated and compared to those reported in existing literature to validate the accuracy of the optimization results. The findings highlight the versatility and effectiveness of the SA-based TO methodology in addressing complex design challenges with considerable self-weight or inertial effect. This work can contribute to structural design of systems where only the objective value is available with no gradient information to use sensitivity-based algorithms.https://www.mdpi.com/2075-1702/12/1/25topology optimization (TO)simulated annealing (SA)self-weightinertial loadstructural design |
| spellingShingle | Hossein Rostami Najafabadi Thiago C. Martins Marcos S. G. Tsuzuki Ahmad Barari Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology Optimization Machines topology optimization (TO) simulated annealing (SA) self-weight inertial load structural design |
| title | Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology Optimization |
| title_full | Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology Optimization |
| title_fullStr | Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology Optimization |
| title_full_unstemmed | Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology Optimization |
| title_short | Structural Design with Self-Weight and Inertial Loading Using Simulated Annealing for Non-Gradient Topology Optimization |
| title_sort | structural design with self weight and inertial loading using simulated annealing for non gradient topology optimization |
| topic | topology optimization (TO) simulated annealing (SA) self-weight inertial load structural design |
| url | https://www.mdpi.com/2075-1702/12/1/25 |
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