Structural Weight and Stiffness Optimization of a Midibus Using the Reinforcement and Response Surface Optimization (RSO) Method in Static Condition
Midibuses are medium-sized buses widely used for transportation purposes in Asia and Africa. However, most midibuses are locally built and indirectly regulated through inspecting the end product (finished bus) during licensing for the public transport business in Ethiopia. Due to lack of engineering...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Modelling and Simulation in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/6812744 |
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| author | Hailemichael Solomon Addisu Ermias Gebrekidan Koricho |
| author_facet | Hailemichael Solomon Addisu Ermias Gebrekidan Koricho |
| author_sort | Hailemichael Solomon Addisu |
| collection | DOAJ |
| description | Midibuses are medium-sized buses widely used for transportation purposes in Asia and Africa. However, most midibuses are locally built and indirectly regulated through inspecting the end product (finished bus) during licensing for the public transport business in Ethiopia. Due to lack of engineering analysis and testing, low stiffness and overweight of midibus were compromised. This research was aimed at analyzing and optimizing the midibus structure using the reinforcement and response surface optimization (RSO) method for pure bending and torsion loading cases. Results show that the maximum deformation occurred at the roof section of the original structure during both loading cases. Furthermore, the reinforcement design was found by replacing the cross section and layouts of structural members and adding reinforcements for the most suitable location of the original structure. Response surface optimization with the multiobjective genetic algorithm (MOGA) method in ANSYS DesignXplorer was performed on the reinforced structure to maximize the bending and torsional stiffness with reduced weight. The bending stiffness of the reinforced and optimized structure increased by 41.65% (1911.4 N/m) and 10.02% (651.7 N/m), respectively. In addition, the torsional rigidity or stiffness of the bus structure was improved by 12.56% (173.31 Nm/deg) via reinforcement design. Moreover, the torsional stiffness of the optimized (RSO) model was increased by 3.29% (51.07 Nm/deg). Reinforcement design was effectively reduced by 5.23% of the structure’s weight. Moreover, the RSO method has also decreased the weight of the reinforced structure by 2.64%. |
| format | Article |
| id | doaj-art-3f7a7f40d0f84615b7dcf0801f7a5f60 |
| institution | Kabale University |
| issn | 1687-5605 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Modelling and Simulation in Engineering |
| spelling | doaj-art-3f7a7f40d0f84615b7dcf0801f7a5f602025-02-03T06:06:49ZengWileyModelling and Simulation in Engineering1687-56052022-01-01202210.1155/2022/6812744Structural Weight and Stiffness Optimization of a Midibus Using the Reinforcement and Response Surface Optimization (RSO) Method in Static ConditionHailemichael Solomon Addisu0Ermias Gebrekidan Koricho1School of Mechanical and Industrial EngineeringDepartment of Mechanical EngineeringMidibuses are medium-sized buses widely used for transportation purposes in Asia and Africa. However, most midibuses are locally built and indirectly regulated through inspecting the end product (finished bus) during licensing for the public transport business in Ethiopia. Due to lack of engineering analysis and testing, low stiffness and overweight of midibus were compromised. This research was aimed at analyzing and optimizing the midibus structure using the reinforcement and response surface optimization (RSO) method for pure bending and torsion loading cases. Results show that the maximum deformation occurred at the roof section of the original structure during both loading cases. Furthermore, the reinforcement design was found by replacing the cross section and layouts of structural members and adding reinforcements for the most suitable location of the original structure. Response surface optimization with the multiobjective genetic algorithm (MOGA) method in ANSYS DesignXplorer was performed on the reinforced structure to maximize the bending and torsional stiffness with reduced weight. The bending stiffness of the reinforced and optimized structure increased by 41.65% (1911.4 N/m) and 10.02% (651.7 N/m), respectively. In addition, the torsional rigidity or stiffness of the bus structure was improved by 12.56% (173.31 Nm/deg) via reinforcement design. Moreover, the torsional stiffness of the optimized (RSO) model was increased by 3.29% (51.07 Nm/deg). Reinforcement design was effectively reduced by 5.23% of the structure’s weight. Moreover, the RSO method has also decreased the weight of the reinforced structure by 2.64%.http://dx.doi.org/10.1155/2022/6812744 |
| spellingShingle | Hailemichael Solomon Addisu Ermias Gebrekidan Koricho Structural Weight and Stiffness Optimization of a Midibus Using the Reinforcement and Response Surface Optimization (RSO) Method in Static Condition Modelling and Simulation in Engineering |
| title | Structural Weight and Stiffness Optimization of a Midibus Using the Reinforcement and Response Surface Optimization (RSO) Method in Static Condition |
| title_full | Structural Weight and Stiffness Optimization of a Midibus Using the Reinforcement and Response Surface Optimization (RSO) Method in Static Condition |
| title_fullStr | Structural Weight and Stiffness Optimization of a Midibus Using the Reinforcement and Response Surface Optimization (RSO) Method in Static Condition |
| title_full_unstemmed | Structural Weight and Stiffness Optimization of a Midibus Using the Reinforcement and Response Surface Optimization (RSO) Method in Static Condition |
| title_short | Structural Weight and Stiffness Optimization of a Midibus Using the Reinforcement and Response Surface Optimization (RSO) Method in Static Condition |
| title_sort | structural weight and stiffness optimization of a midibus using the reinforcement and response surface optimization rso method in static condition |
| url | http://dx.doi.org/10.1155/2022/6812744 |
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