Análisis Comparativo de Metodologías para la Predicción de Propiedades Mecánicas de Materiales Compuestos

Sergio Gómez

doi:10.62876/tekhne.v29i1.7607

Autores/as

Sergio Gómez Universidad Pontificia Bolivariana https://orcid.org/0000-0002-6425-7062

DOI:

https://doi.org/10.62876/tekhne.v29i1.7607

Palabras clave:

elementos finitos, inteligencia artificial, materiales compuestos, predicción, propiedades mecánicas

Resumen

La predicción precisa de las propiedades mecánicas de los materiales compuestos representa un desafío técnico significativo, debido a su compleja estructura interna y a la amplia variedad de combinaciones posibles entre matrices y refuerzos. Este trabajo tiene como objetivo analizar y comparar las principales metodologías empleadas para este propósito, agrupándolas según su enfoque. El estudio se basó en una revisión sistemática de la literatura, mediante la cual se identificaron y clasificaron las estrategias utilizadas en cuatro categorías: experimentales, analíticas, numéricas (particularmente el método de elementos finitos) y basadas en inteligencia artificial. Posteriormente, se realizó un análisis comparativo de sus beneficios y limitaciones, considerando criterios como precisión, costo, flexibilidad, requerimientos técnicos y capacidad predictiva. Los resultados muestran que, si bien los ensayos experimentales ofrecen alta fidelidad, presentan limitaciones en términos de costos y replicabilidad. Los modelos analíticos se destacan por su simplicidad y rapidez, aunque tienden a perder exactitud en sistemas más complejos. Las simulaciones numéricas permiten representar estructuras heterogéneas con gran detalle, pero demandan recursos computacionales significativos. Finalmente, los enfoques basados en inteligencia artificial demuestran un alto potencial para gestionar grandes volúmenes de datos y reconocer patrones complejos, aunque su eficacia depende en gran medida de la calidad y representatividad de los datos disponibles.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

V. S. Hiremath, D. M. Reddy, R. Reddy Mutra, A. Sanjeev, T. Dhilipkumar y N. J, "Thermal degradation and fire retardant behaviour of natural fibre reinforced polymeric composites- A comprehensive review", Journal of Materials Research and Technology, vol. 30, pp. 4053-4063, 2024. DOI: https://doi.org/10.1016/j.jmrt.2024.04.085

Y. Wang y Z. Huang, "A Review of Analytical Micromechanics Models on Composite Elastoplastic Behaviour", Procedia Engineering, vol. 173, pp. 1283-1290, 2017. DOI: https://doi.org/10.1016/j.proeng.2016.12.159

P.-H. Lai, E. D. Gomez, B. D. Vogt y W. F. Reinhart, "Predicting the Strength of Composites with Computer Vision Using Small Experimental Datasets", ACS Materials Letters, vol. 7, no. 4, pp. 1503-1511, 2025. DOI: https://doi.org/10.1021/acsmaterialslett.4c02424

B. Raju, S. R. Hiremath y D. Roy Mahapatra, "A review of micromechanics based models for effective elastic properties of reinforced polymer matrix composites", Composite Structures, vol. 204, pp. 607-619, 2018. DOI: https://doi.org/10.1016/j.compstruct.2018.07.125

V. Panwar, P. Gupta, A. K. Bagha y N. Chauhan, "A Review on studies of Finite Element Model Updating and Updating of Composite Materials", Materials Today: Proceedings, vol. 5, no. 14, pp. 27912-27918, 2018. DOI: https://doi.org/10.1016/j.matpr.2018.10.030

S. S. Sorour, C. A. Saleh y M. Shazly, "A review on machine learning implementation for predicting and optimizing the mechanical behaviour of laminated fiber-reinforced polymer composites", Heliyon, vol. 10, no. 13, p. e33681, 2024. DOI: https://doi.org/10.1016/j.heliyon.2024.e33681

C. Veres y M. Tănase, "A Bibliometric and Systematic Review of the Use of Recycled Composite Materials with an Emphasis on the Mechanical Performance of Structures", Materials, vol. 18, no. 3, p. 607, 2025. DOI: https://doi.org/10.3390/ma18030607

D. E. S. Rodrigues, J. Belinha, F. M. A. Pires, L. M. J. S. Dinis y R. M. N. Jorge, "Homogenization technique for heterogeneous composite materials using meshless methods", Engineering Analysis with Boundary Elements, vol. 92, pp. 73-89, 2018. DOI: https://doi.org/10.1016/j.enganabound.2017.12.012

A. Jasti, B. Akhil Chandra y S. Biswas, "Modified Halpin–Tsai model for predicting the mechanical properties of polymer composites reinforced with different cross-sectional fibers", Materials Today: Proceedings, vol. 91, pp. 14-18, 2023. DOI: https://doi.org/10.1016/j.matpr.2023.04.131

Y. Wang y Z. Huang, "Analytical Micromechanics Models for Elastoplastic Behavior of Long Fibrous Composites: A Critical Review and Comparative Study", Materials, vol. 11, no. 10, p. 1919, 2018. DOI: https://doi.org/10.3390/ma11101919

M. Kim y Y. Kim, "A Thermo-Mechanical Properties Evaluation of Multi-Directional Carbon/Carbon Composite Materials in Aerospace Applications", Aerospace, vol. 9, no. 8, p. 461, 2022. DOI: https://doi.org/10.3390/aerospace9080461

Y. Xie, G. Huang, H. Zhang, M. Xu, E. Sitnikova y S. Li, "Efficient characterization of mechanical nonlinearity in triaxially braided composites by a novel unit cell", Composite Structures, vol. 366, p. 119234, 2025. DOI: https://doi.org/10.1016/j.compstruct.2025.119234

F. Kibrete, T. Trzepieciński, H. S. Gebremedhen y D. E. Woldemichael, "Artificial Intelligence in Predicting Mechanical Properties of Composite Materials", Journal of Composites Science, vol. 7, no. 9, p. 364, 2023. DOI: https://doi.org/10.3390/jcs7090364

W. Jin, J. Pei, P. Xie, J. Chen y H. Zhao, "Machine Learning-Based Prediction of Mechanical Properties and Performance of Nickel–Graphene Nanocomposites Using Molecular Dynamics Simulation Data", ACS Applied Nano Materials, vol. 6, no. 13, pp. 12190-12199, 2023. DOI: https://doi.org/10.1021/acsanm.3c01919

M. Chairi, J. El Bahaoui, I. Hanafi, F. Mata Cabrera y G. Di Bella, "Composite Materials: A Review of Polymer and Metal Matrix Composites, Their Mechanical Characterization, and Mechanical Properties", en Next Generation Fiber-Reinforced Composites - New Insights, L. Li, A. B. Pereira y A. L. Pereira, Eds. IntechOpen, 2023. DOI: https://doi.org/10.5772/intechopen.106624

I. Wadgave, S. Kulkarni, S. Katekar y M. Kulkarni, "A comprehensive review on: Mechanical and acoustical characterization of natural fiber-reinforced composite", Materials Today: Proceedings, 2024. DOI: https://doi.org/10.1016/j.matpr.2024.05.002

J. Yun, S. Ryu, J. Kim, Y. Kim y D.-W. Kim, "Equivalent modeling for the prediction of mechanical behaviors of composite sandwich structures with thick cell walls", Composite Structures, vol. 364, p. 119162, 2025. DOI: https://doi.org/10.1016/j.compstruct.2025.119162

W. Mu, X. Chen, S. Li, Y. Sun, Q. Wang y J. Na, "Mechanical Performances Analysis and Prediction of Short Plant Fiber-Reinforced PLA Composites", Polymers, vol. 15, no. 15, p. 3222, 2023. DOI: https://doi.org/10.3390/polym15153222

D. K. Rathore, R. K. Prusty, S. C. Mohanty, B. P. Singh y B. C. Ray, "In-situ elevated temperature flexural and creep response of inter-ply glass/carbon hybrid FRP composites", Mechanics of Materials, vol. 105, pp. 99-111, 2017. DOI: https://doi.org/10.1016/j.mechmat.2016.11.013

H. Wu, J. Wang, L. Zhang, X. Sun, G. Zu, Y. Zhao y J. Sha, "Preparation of Bouligand biomimetic ceramic composites and the effect of different fiber orientations on mechanical properties", Journal of Manufacturing Processes, vol. 132, pp. 789-801, 2024. DOI: https://doi.org/10.1016/j.jmapro.2024.11.031

H. Zhang, S. Zhang, D. Chen, Z. Wang, J. Xie y Y. Zhang, "Mechanical properties and failure mechanisms of three-dimensional stitched C/C-SiC ceramic matrix composites", Ceramics International, vol. 50, no. 24, pp. 55487-55497, 2024. DOI: https://doi.org/10.1016/j.ceramint.2024.10.409

X. Huang, S. Su, Z. Xu, Q. Miao, W. Li y L. Wang, "Advanced Composite Materials for Structure Strengthening and Resilience Improvement", Buildings, vol. 13, no. 10, p. 2406, 2023. DOI: https://doi.org/10.3390/buildings13102406

M. Chen, X. Zhang, K. Shen y G. Pan, "Uncertainty quantification and global sensitivity analysis for composite cylinder shell via data-driven polynomial chaos expansion", Journal of Physics: Conference Series, vol. 2174, no. 1, p. 012085, 2022. DOI: https://doi.org/10.1088/1742-6596/2174/1/012085

M. Xu, B. Zeng, Z. An, X. Xiong y X. Cheng, "Experimental and Numerical Investigation on Fatigue Properties of Carbon Fiber Cross-Ply Laminates in Hygrothermal Environments", Polymers, vol. 14, no. 9, p. 1857, 2022. DOI: https://doi.org/10.3390/polym14091857

M. Lezgy-Nazargah, S. A. Emamian, E. Aghasizadeh y M. Khani, "Predicting the mechanical properties of ordinary concrete and nano-silica concrete using micromechanical methods", Sādhanā, vol. 43, no. 12, p. 196, 2018. DOI: https://doi.org/10.1007/s12046-018-0965-0

M. Li, H. Hao, Y. Shi y Y. Hao, "Specimen shape and size effects on the concrete compressive strength under static and dynamic tests", Construction and Building Materials, vol. 161, pp. 84-93, 2018. DOI: https://doi.org/10.1016/j.conbuildmat.2017.11.069

G. Habbar, A. Maizia, A. Hocine, J. Ribeiro y M. H. Dhaou, "Micromechanical Analysis of a Bio-Sandwich Application for Cylinder under Pressure", Journal of Composites Science, vol. 6, no. 3, p. 69, 2022. DOI: https://doi.org/10.3390/jcs6030069

Y. Cao, W. Wang y Q. Wang, "Application of mechanical model for natural fibre reinforced polymer composites", Materials Research Innovations, vol. 18, no. sup2, pp. S2-354-S2-357, 2014. DOI: https://doi.org/10.1179/1432891714Z.000000000431

P. Ewart y J. Verbeek, "Using micro-mechanical modelling to predict short-fibre composite properties in computer-aided design of sporting equipment", Sports Engineering, vol. 13, no. 2, pp. 73-81, 2011. DOI: https://doi.org/10.1007/s12283-010-0057-9

J. M. Díaz-Mendoza, D. J. Valles-Rosales, Y. H. Park y R. C. Sabo, "Micromechanical Modeling for Tensile Properties of Wood Plastic Composites", Polymers, vol. 14, no. 3, p. 504, 2022. DOI: https://doi.org/10.3390/polym14030504

Y. C. Kim, H.-K. Jang, G. Joo y J. H. Kim, "A Comparative Study of Micromechanical Analysis Models for Determining the Effective Properties of Out-of-Autoclave Carbon Fiber–Epoxy Composites", 2024.

H. Yue, C. Lu, C. Wang y F. Yang, "Optimizing tensile strength and failure prediction in hemp fiber composites: Coupling effects of microfibril angle and fiber orientation under off-axis loading", Industrial Crops and Products, vol. 222, p. 119872, 2024. DOI: https://doi.org/10.1016/j.indcrop.2024.119872

S. Xu, H. Yang, T. Li y Y. Zhang, "Data-driven prediction of mechanical properties of 3D-printed dual-material composites based on deep transfer learning", Composites Part A: Applied Science and Manufacturing, vol. 198, p. 109083, 2025. DOI: https://doi.org/10.1016/j.compositesa.2025.109083

E. A. W. de Menezes, L. Friedrich, A. Colpo y S. C. Amico, "Micromechanics of Short-Fiber and Particulate Composites", en Unsaturated Polyester Resins, S. Thomas, M. Hosur y C. J. Chirayil, Eds. Elsevier, 2019, pp. 125-152. DOI: https://doi.org/10.1016/B978-0-12-816129-6.00005-3

S. David Müzel, E. P. Bonhin, N. M. Guimarães y E. S. Guidi, "Application of the Finite Element Method in the Analysis of Composite Materials: A Review", Polymers, vol. 12, no. 4, p. 818, 2020. DOI: https://doi.org/10.3390/polym12040818

N. Shetty, S. M. Shahabaz, S. S. Sharma y S. Divakara Shetty, "A review on finite element method for machining of composite materials", Composite Structures, vol. 176, pp. 790-802, 2017. DOI: https://doi.org/10.1016/j.compstruct.2017.06.012

W. Hou, X. Xu, H. Wang y L. Tong, "Bending behavior of single hat-shaped composite T-joints under out-of-plane loading for lightweight automobile structures", Journal of Reinforced Plastics and Composites, vol. 37, no. 12, pp. 808-823, 2018. DOI: https://doi.org/10.1177/0731684418764608

A. Alade y A. Ibrahim, "Application of Finite Element Method for Mechanical Characterization of Wood and Reconstituted Lignocellulosic-Based Composites – A Review", Recent Progress in Materials, vol. 5, no. 1, pp. 1-37, 2023. DOI: https://doi.org/10.21926/rpm.2301003

M.-K. Hsu, H. Wu, J. Geng, Y. Xiao y Z. Zhai, "A deep learning empowered smart representative volume element method for long fiber woven composites", Frontiers in Materials, vol. 10, p. 1179710, 2023. DOI: https://doi.org/10.3389/fmats.2023.1179710

A. Wendling, J. L. Daniel, G. Hivet, E. Vidal-Sallé y P. Boisse, "Meshing Preprocessor for the Mesoscopic 3D Finite Element Simulation of 2D and Interlock Fabric Deformation", Applied Composite Materials, vol. 22, no. 6, pp. 869-886, 2015. DOI: https://doi.org/10.1007/s10443-015-9441-8

M. Rehan, T. He, D. Tahir, A. K. Khalil, W. S. Yip y S. S. To, "3D Finite element modeling and experimental investigation of micro milling of laser powder bed fusion fabricated Ti6Al4V", Results in Engineering, vol. 26, p. 104635, 2025. DOI: https://doi.org/10.1016/j.rineng.2025.104635

M. Mudabbirudin, J. Takacs, A. Mosavi, F. Imre y N. Nabipour, "Deep Learning and Machine Learning for Materials Design", en 2024 IEEE 6th International Symposium on Logistics and Industrial Informatics (LINDI), 2024, pp. 73-82. DOI: https://doi.org/10.1109/LINDI63813.2024.10820388

H. Hu, Z. Hu, J. Ji, S. Meng, Y. Chen y Y. Zhang, "Experimental and Numerical Investigation Integrated with Machine Learning (ML) for the Prediction Strategy of DP590/CFRP Composite Laminates", Polymers, vol. 16, no. 11, p. 1589, 2024. DOI: https://doi.org/10.3390/polym16111589

W. Gao, Z. Yang, Y. Li, Y. Zhang, Q. Wang y J. Zhou, "Accurately Predicting Multiple Performance of 3D Printing Photopolymers Using Ensemble Learning", ACS Applied Polymer Materials, vol. 6, no. 8, pp. 4501-4508, 2024. DOI: https://doi.org/10.1021/acsapm.3c03102

P. Guo, W. Meng, M. Xu, V. C. Li y Y. Bao, "Predicting Mechanical Properties of High-Performance Fiber-Reinforced Cementitious Composites by Integrating Micromechanics and Machine Learning", Materials, vol. 14, no. 12, p. 3143, 2021. DOI: https://doi.org/10.3390/ma14123143

S.-J. Huang, Y. Adityawardhana y J. Sanjaya, "Predicting Mechanical Properties of Magnesium Matrix Composites with Regression Models by Machine Learning", Journal of Composites Science, vol. 7, no. 9, p. 347, 2023. DOI: https://doi.org/10.3390/jcs7090347