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RESEARCH PAPER · Journal of Composite Materials · 2020

Tailoring composite materials for nonlinear viscoelastic properties using artificial neural networks

Xianbo Xu, Mariam Elgamal, Mrityunjay R. Doddamani, Nïkhil Gupta

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Tailoring composite materials for nonlinear viscoelastic properties using artificial neural networksOriginalArtificial Neural Networks Framework for Detection of Defects in 3D-Printed Fiber Reinforcement Composites30Experimental and artificial neural network approach for prediction of the thermal degradation behavior of sugarcane-based vulcanization additives in natural rubber compounds7Deep Learning from Physicochemical Information of Concrete with an Artificial Language for Property Prediction and Reaction Discovery28Image Processing and Machine Learning Methods Applied to Additive Manufactured Composites for Defect Detection and Toolpath Reconstruction4The Role of Artificial Neural Networks in Prediction of Mechanical and Tribological Properties of Composites—A Comprehensive Review90The intersection of damage evaluation of fiber-reinforced composite materials with machine learning: A review59Adaptive neuro-fuzzy inference system approach to predict dynamic thermo-mechanical responses of poly (vinylidene fluoride) blend-based nanocomposites2Effective Elastic Properties of Multifunctional Syntactic Foams1Experimental investigation and machine learning prediction of mechanical properties of graphene nanoplatelets based triaxial braided composites13Advances in machine learning-aided design of reinforced polymer composite and hybrid material systems112Estimation of Critical Buckling Loads of Hybrid Composites in Different Environments using Artificial Neural Networks0Modeling the cure shrinkage–induced warpage of epoxy molding compound28Failure criterion model of carbon/phenolic composites based on artificial neural network with small sample space under high temperature and complex load conditions0Research progress in data-driven constitutive modeling of composite solid propellants6AI assisted mechanical and performance testing of lightweight composites0Machine leaning aided accelerated characterization of temperature and strain rate-dependent dynamic properties of close-cell polymer foams0Machine Learning-Based Predictive Framework for Tribological Performance Assessment of Aluminum Matrix Composites0

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  1. Artificial Neural Networks Framework for Detection of Defects in 3D-Printed Fiber Reinforcement Composites

    JOM · 2021-05-14

    Guan Lin Chen, Kaushik Yanamandra, Nïkhil Gupta

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  2. Experimental and artificial neural network approach for prediction of the thermal degradation behavior of sugarcane-based vulcanization additives in natural rubber compounds

    Cleaner Engineering and Technology · 2021-10-22

    Aline Zanchet, Francisco Maciel Monticeli, Fabiula Danielli Bastos de Sousa, Heitor Luiz Ornaghi

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  3. Deep Learning from Physicochemical Information of Concrete with an Artificial Language for Property Prediction and Reaction Discovery

    Resources Conservation and Recycling · 2022-01-01

    Soroush Mahjoubi, Rojyar Barhemat, Weina Meng, Yi Bao

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  4. Image Processing and Machine Learning Methods Applied to Additive Manufactured Composites for Defect Detection and Toolpath Reconstruction

    Composites science and technology · 2022-01-01

    Guan Lin Chen, Nïkhil Gupta

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  5. The Role of Artificial Neural Networks in Prediction of Mechanical and Tribological Properties of Composites—A Comprehensive Review

    Archives of Computational Methods in Engineering · 2022-01-29

    Uma Maheshwera Reddy Paturi, Suryapavan Cheruku, N.S. Reddy

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  6. The intersection of damage evaluation of fiber-reinforced composite materials with machine learning: A review

    Journal of Composite Materials · 2022-02-18

    Christopher Nelon, Oliver Myers, Asha J. Hall

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  7. Adaptive neuro-fuzzy inference system approach to predict dynamic thermo-mechanical responses of poly (vinylidene fluoride) blend-based nanocomposites

    Polymer Bulletin · 2022-07-31

    Mahboube Mohamadi, Mortaza Aliasghary

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  8. Effective Elastic Properties of Multifunctional Syntactic Foams

    SSRN Electronic Journal · 2023-01-01

    Siavash Sarrafan, Guoqiang Li

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  9. Experimental investigation and machine learning prediction of mechanical properties of graphene nanoplatelets based triaxial braided composites

    Materials Today Communications · 2023-01-13

    Gayatri Vineela Marrivada, Phaneendra Kiran Chaganti, Ravindran Sujith

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  10. Advances in machine learning-aided design of reinforced polymer composite and hybrid material systems

    Hybrid Advances · 2023-02-04

    Christian Emeka Okafor, Sunday Iweriolor, Okwuchukwu Innocent Ani, Shahnawaz Ahmad, Shabana Mehfuz, Godspower Onyekachukwu Ekwueme, Okechukwu Emmanuel Chukwumuanya, Sylvester Emeka Abonyi, Ignatius Echezona Ekengwu, Peter Okechukwu Chikelu

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  11. Estimation of Critical Buckling Loads of Hybrid Composites in Different Environments using Artificial Neural Networks

    Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi · 2023-12-25

    Ayla Tekin, Ayşe Öndürücü, Hüseyin Fırat KAYIRAN

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  12. Modeling the cure shrinkage–induced warpage of epoxy molding compound

    International Journal of Mechanical Sciences · 2024-01-20

    Chang‐Chun Lee, Hao-Zhou Lin

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  13. Failure criterion model of carbon/phenolic composites based on artificial neural network with small sample space under high temperature and complex load conditions

    SSRN Electronic Journal · 2025-01-01

    Xiaochu Lin, Shiao Sun, Enling Tang, Chenghai Xu, Fajun Yi, Weihua Xie

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  14. Research progress in data-driven constitutive modeling of composite solid propellants

    AIP Advances · 2025-05-01

    Bin Yuan, Hongfu Qiang, Chunguo Yue

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  15. AI assisted mechanical and performance testing of lightweight composites

    Elsevier eBooks · 2025-11-21

    Nïkhil Gupta, Guan-Lin Chen

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  16. Machine leaning aided accelerated characterization of temperature and strain rate-dependent dynamic properties of close-cell polymer foams

    Journal of Cellular Plastics · 2025-11-26

    Guan-Lin Chen, Nïkhil Gupta, Abhishek M. Shetty

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  17. Machine Learning-Based Predictive Framework for Tribological Performance Assessment of Aluminum Matrix Composites

    Journal of The Institution of Engineers (India) Series D · 2026-07-16

    Mitali Mhatre, Akhilanand Maurya, Sagarkumar J. Aswar, Priya Dongare Jadhav, Nallam Krishnaiah, Jivan Ingle, G T Danappa, Nilesh Khandare

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