Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm
The present study investigates the mechanical behaviors of hybrid fiber-reinforced polyester composites in developing a new strengthened material. The experiments were planned as per the design of experiments, the selected input parameters were fiber length (mm), NaOH treatment (%), and fiber weight...
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| Format: | Article |
| Language: | English |
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Semnan University
2025-04-01
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| Series: | Mechanics of Advanced Composite Structures |
| Subjects: | |
| Online Access: | https://macs.semnan.ac.ir/article_8928_a15bf9aff0a11ba1bb037f604c79de12.pdf |
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| author | Vinoth Viswanathan Sathiyamurthy Subbarayan Ananthi Narayanaswamy Devi Panneerselvam Prabhakaran Jayasankar |
| author_facet | Vinoth Viswanathan Sathiyamurthy Subbarayan Ananthi Narayanaswamy Devi Panneerselvam Prabhakaran Jayasankar |
| author_sort | Vinoth Viswanathan |
| collection | DOAJ |
| description | The present study investigates the mechanical behaviors of hybrid fiber-reinforced polyester composites in developing a new strengthened material. The experiments were planned as per the design of experiments, the selected input parameters were fiber length (mm), NaOH treatment (%), and fiber weight (%) and the output parameters were tensile, flexural, and impact strength conditions. A Non-Linear Regression Modelling (NLRM) and Fuzzy logic model have been designed to predict and analyze the mechanical properties in unknown test conditions. Every input factor was categorized into three linguistic descriptors, while each output factor was classified into three linguistic categories. A triangular membership function was employed to define all these variables. The effectiveness of the nonlinear regression analysis and fuzzy logic model was evaluated through confirmatory experiments. The model predicted the mechanical results with an error of 7.19%, 5.38%, and 2.33% respectively. The proposed approach can significantly simplify real-life multi-response optimization problems, thereby reducing fabrication costs and enhancing composite fabrication efficiency. |
| format | Article |
| id | doaj-art-4f299acbeead4ecbb3e37aa19fc1647a |
| institution | Kabale University |
| issn | 2423-4826 2423-7043 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Semnan University |
| record_format | Article |
| series | Mechanics of Advanced Composite Structures |
| spelling | doaj-art-4f299acbeead4ecbb3e37aa19fc1647a2025-01-20T11:30:30ZengSemnan UniversityMechanics of Advanced Composite Structures2423-48262423-70432025-04-0112119921010.22075/macs.2024.33822.16488928Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic AlgorithmVinoth Viswanathan0Sathiyamurthy Subbarayan1Ananthi Narayanaswamy2Devi Panneerselvam3Prabhakaran Jayasankar4Easwari Engineering College (Autonomous), Chennai, Tamilnadu, 600089, IndiaEaswari Engineering College (Autonomous), Chennai, Tamilnadu, 600089, IndiaEaswari Engineering College (Autonomous), Chennai, Tamilnadu, 600089, IndiaB.S.Abdur Rahman Crescent Institute of Science and Technology, Vandalur, Chennai, Tamilnadu, 600048, IndiaIndian Institute of Technology, Chennai, Tamilnadu, 600036, IndiaThe present study investigates the mechanical behaviors of hybrid fiber-reinforced polyester composites in developing a new strengthened material. The experiments were planned as per the design of experiments, the selected input parameters were fiber length (mm), NaOH treatment (%), and fiber weight (%) and the output parameters were tensile, flexural, and impact strength conditions. A Non-Linear Regression Modelling (NLRM) and Fuzzy logic model have been designed to predict and analyze the mechanical properties in unknown test conditions. Every input factor was categorized into three linguistic descriptors, while each output factor was classified into three linguistic categories. A triangular membership function was employed to define all these variables. The effectiveness of the nonlinear regression analysis and fuzzy logic model was evaluated through confirmatory experiments. The model predicted the mechanical results with an error of 7.19%, 5.38%, and 2.33% respectively. The proposed approach can significantly simplify real-life multi-response optimization problems, thereby reducing fabrication costs and enhancing composite fabrication efficiency.https://macs.semnan.ac.ir/article_8928_a15bf9aff0a11ba1bb037f604c79de12.pdfhybrid fiberpolyestermechanical propertiesregression analysisfuzzy rule |
| spellingShingle | Vinoth Viswanathan Sathiyamurthy Subbarayan Ananthi Narayanaswamy Devi Panneerselvam Prabhakaran Jayasankar Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm Mechanics of Advanced Composite Structures hybrid fiber polyester mechanical properties regression analysis fuzzy rule |
| title | Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm |
| title_full | Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm |
| title_fullStr | Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm |
| title_full_unstemmed | Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm |
| title_short | Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm |
| title_sort | modeling and numerical prediction on mechanical behaviors of hybrid fiber reinforced polymer bio composites using fuzzy logic algorithm |
| topic | hybrid fiber polyester mechanical properties regression analysis fuzzy rule |
| url | https://macs.semnan.ac.ir/article_8928_a15bf9aff0a11ba1bb037f604c79de12.pdf |
| work_keys_str_mv | AT vinothviswanathan modelingandnumericalpredictiononmechanicalbehaviorsofhybridfiberreinforcedpolymerbiocompositesusingfuzzylogicalgorithm AT sathiyamurthysubbarayan modelingandnumericalpredictiononmechanicalbehaviorsofhybridfiberreinforcedpolymerbiocompositesusingfuzzylogicalgorithm AT ananthinarayanaswamy modelingandnumericalpredictiononmechanicalbehaviorsofhybridfiberreinforcedpolymerbiocompositesusingfuzzylogicalgorithm AT devipanneerselvam modelingandnumericalpredictiononmechanicalbehaviorsofhybridfiberreinforcedpolymerbiocompositesusingfuzzylogicalgorithm AT prabhakaranjayasankar modelingandnumericalpredictiononmechanicalbehaviorsofhybridfiberreinforcedpolymerbiocompositesusingfuzzylogicalgorithm |