DESIGN OPTIMIZATION AND VALIDATION OF THIN-WALLED MULTICELL STRUCTURES WITH ALUMUNIUM-COMPOSITE HYBRID ON AXIAL LOADING

This research was conducted because there are still few studies on optimizing the multicell structure with hybrid materials under axial loading which aims to determine the optimal hybrid multicell configuration to absorb impact energy. This study discusses the optimization of thin-walled multicellul...

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Main Author: Diya Ulhaqi Dewantoro, Hafidh
Format: Theses
Language:Indonesia
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Online Access:https://digilib.itb.ac.id/gdl/view/57015
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:57015
spelling id-itb.:570152021-07-23T16:39:13ZDESIGN OPTIMIZATION AND VALIDATION OF THIN-WALLED MULTICELL STRUCTURES WITH ALUMUNIUM-COMPOSITE HYBRID ON AXIAL LOADING Diya Ulhaqi Dewantoro, Hafidh Teknik (Rekayasa, enjinering dan kegiatan berkaitan) Indonesia Theses multicell, aluminum-composite hybrid, axial loading, optimization, artificial neural network, non-dominant sequencing genetic algorithm INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/57015 This research was conducted because there are still few studies on optimizing the multicell structure with hybrid materials under axial loading which aims to determine the optimal hybrid multicell configuration to absorb impact energy. This study discusses the optimization of thin-walled multicellular structures with aluminum-composite hybrid materials under axial loading. This thin-walled structure will apply a multi-cell geometry cross-section with material hybrids which are two effective approaches to increase the strength of the structure. The materials used in this structure are Aluminum 6061 and Carbon Fiber Reinforcement Polymer (CFRP). CFRP composite material is used as a reinforcing structure because it is lightweight but has high structural strength so it is suitable for use in various applications. Several parameters were varied, such as cross-sectional geometry, thickness of aluminum, angular orientation of the composite layer, and the number of composite layers in view of the performance of the structure. This optimization process is carried out using the LS-DYNA software. The optimization process was also carried out in this study to obtain the most optimal structure performance and composite orientation in the absorption of impact energy. This optimization process uses artificial neural network (ANN) methods, non-dominated sorting genetic algorithm – II (NSGA – II), and multi-objective optimization based on ratio analysis (MOORA) using the Python programming language. In this study, the structural characteristics that will be used as optimization parameters are specific energy absorption, crushing force efficiency, mean crushing force, and peak force. These parameters are used as a reference by the structure in absorbing energy. At the end of the study, the optimal configuration of the structural model obtained was the cruciform cross-sectional geometry of aluminum with a width of 50 mm and a thickness of 3.4 mm and the number of composite layers of 20 layers with orientation direction [44°/76°/29°/11°/48°/1 °/9°/12°/2°/42°]s. From this configuration, it was found that the performance increase for each parameter, namely the SEA value of 29%, CFE of 19%, the value of MCF of 29%, and a decrease in the peak force value of 0.009% against the baseline model. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
topic Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
spellingShingle Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
Diya Ulhaqi Dewantoro, Hafidh
DESIGN OPTIMIZATION AND VALIDATION OF THIN-WALLED MULTICELL STRUCTURES WITH ALUMUNIUM-COMPOSITE HYBRID ON AXIAL LOADING
description This research was conducted because there are still few studies on optimizing the multicell structure with hybrid materials under axial loading which aims to determine the optimal hybrid multicell configuration to absorb impact energy. This study discusses the optimization of thin-walled multicellular structures with aluminum-composite hybrid materials under axial loading. This thin-walled structure will apply a multi-cell geometry cross-section with material hybrids which are two effective approaches to increase the strength of the structure. The materials used in this structure are Aluminum 6061 and Carbon Fiber Reinforcement Polymer (CFRP). CFRP composite material is used as a reinforcing structure because it is lightweight but has high structural strength so it is suitable for use in various applications. Several parameters were varied, such as cross-sectional geometry, thickness of aluminum, angular orientation of the composite layer, and the number of composite layers in view of the performance of the structure. This optimization process is carried out using the LS-DYNA software. The optimization process was also carried out in this study to obtain the most optimal structure performance and composite orientation in the absorption of impact energy. This optimization process uses artificial neural network (ANN) methods, non-dominated sorting genetic algorithm – II (NSGA – II), and multi-objective optimization based on ratio analysis (MOORA) using the Python programming language. In this study, the structural characteristics that will be used as optimization parameters are specific energy absorption, crushing force efficiency, mean crushing force, and peak force. These parameters are used as a reference by the structure in absorbing energy. At the end of the study, the optimal configuration of the structural model obtained was the cruciform cross-sectional geometry of aluminum with a width of 50 mm and a thickness of 3.4 mm and the number of composite layers of 20 layers with orientation direction [44°/76°/29°/11°/48°/1 °/9°/12°/2°/42°]s. From this configuration, it was found that the performance increase for each parameter, namely the SEA value of 29%, CFE of 19%, the value of MCF of 29%, and a decrease in the peak force value of 0.009% against the baseline model.
format Theses
author Diya Ulhaqi Dewantoro, Hafidh
author_facet Diya Ulhaqi Dewantoro, Hafidh
author_sort Diya Ulhaqi Dewantoro, Hafidh
title DESIGN OPTIMIZATION AND VALIDATION OF THIN-WALLED MULTICELL STRUCTURES WITH ALUMUNIUM-COMPOSITE HYBRID ON AXIAL LOADING
title_short DESIGN OPTIMIZATION AND VALIDATION OF THIN-WALLED MULTICELL STRUCTURES WITH ALUMUNIUM-COMPOSITE HYBRID ON AXIAL LOADING
title_full DESIGN OPTIMIZATION AND VALIDATION OF THIN-WALLED MULTICELL STRUCTURES WITH ALUMUNIUM-COMPOSITE HYBRID ON AXIAL LOADING
title_fullStr DESIGN OPTIMIZATION AND VALIDATION OF THIN-WALLED MULTICELL STRUCTURES WITH ALUMUNIUM-COMPOSITE HYBRID ON AXIAL LOADING
title_full_unstemmed DESIGN OPTIMIZATION AND VALIDATION OF THIN-WALLED MULTICELL STRUCTURES WITH ALUMUNIUM-COMPOSITE HYBRID ON AXIAL LOADING
title_sort design optimization and validation of thin-walled multicell structures with alumunium-composite hybrid on axial loading
url https://digilib.itb.ac.id/gdl/view/57015
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