Application of scalable sensor-assisted multi-scale computational methods in the simulation of micro mechanical behavior of composite materials

  • Pan Wang Science and Technology on Combustion, Internal Flow and Thermostructure Laboratory, Northwestern Polytechnical University, Xi’an 710072, China
  • Peijin Liu Science and Technology on Combustion, Internal Flow and Thermostructure Laboratory, Northwestern Polytechnical University, Xi’an 710072, China
  • Wen Ao Science and Technology on Combustion, Internal Flow and Thermostructure Laboratory, Northwestern Polytechnical University, Xi’an 710072, China
Keywords: scalable sensors; micromechanics; composite materials; carbon fiber reinforced polymers; multi-scale computational methods
Ariticle ID: 307

Abstract

Micro mechanics involves the examination of the mechanical behavior of heterogeneous materials, taking into account inhomogeneities such as voids, fractures, and inclusions, and building on mathematical models developed. Composites bring engineering design barriers despite their strengths. Composite manufacturing and processing need specialized equipment, strategies, and labor, ensuring they are challenging and expensive. Mechanical behavior deals with how a composite material performs if faced with mechanical effects and action. Scalable sensor-assisted multi-scale computational Methods (SS-MSCM) are used to investigate topics ranging from the molecular basis of soot production in combustion to how molecule-level flaws influence macroscopic mechanical qualities. Carbon fiber reinforced polymers (CFRP) are generated by mixing graphene fiber with a resin, like vinyl ester and epoxy, to render a composite material with superior performance to the component ingredients. Hence, SS-MSCM-CFRP has Improved mechanical qualities achieved by incorporating nano-reinforcements, including carbon nanofibers and graphene nanoplates, into the CFRP matrix: enhanced flexural and compressive strengths, energy absorption upon impact, toughness to fracture, and interlaminar bonding. Composite materials feature excellent mechanical qualities like high strength and stiffness, fatigue resistance, and durability. It is possible to insert scalable sensors throughout the manufacturing process, which enables real-time monitoring of structural health, strain, and other factors. Scalable sensor-assisted multi-scale computational methods offer enhanced accuracy, real-time monitoring, and cost-effectiveness by integrating sensor data with computational models, improving predictions and failure mechanism insights. However, they face limitations like sensor dependency, computational complexity, data integration challenges, and high implementation costs, leading to potential discrepancies between simulation and experimental results. Important qualities include corrosion resistance, thermal conductivity, and electrical conductivity. As the composite materials develop to satisfy the established mechanical stress and temperature conditions, they offer high durability and strength.

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Published
2024-09-24
How to Cite
Wang, P., Liu, P., & Ao, W. (2024). Application of scalable sensor-assisted multi-scale computational methods in the simulation of micro mechanical behavior of composite materials. Molecular & Cellular Biomechanics, 21(1), 307. https://doi.org/10.62617/mcb.v21i1.307
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Article