In a recent editorial article published in the Open Access Journal materialsthe researchers discussed the mechanical analysis, damage assessment and prediction of multi-scale simulation of composite structures.
To learn: Multiscale simulation of composite structures: damage assessment, mechanical analysis and prediction. Photo credit: nevodka/Shutterstock.com
Composite structures are increasingly being used in a variety of engineering applications. Multiscale simulation is a technology that makes it possible to explore and understand complicated systems and phenomena that are usually too expensive, risky or even impossible to study directly through experiments. Due to their complex failure mechanisms and non-uniform deformations, the mechanical characterization of the textile composites is a difficult task.
Polymer, carbon and glass fibers are commonly used to create protective systems. However, in recent years it has been found that combining high-tenacity yarns in different directions results in flexible fabrics that are both lightweight and extremely strong. Therefore, aramid fibers are currently the most commonly used protective materials.
Concrete filled steel pipes (CFSTs) have useful uses in the construction industry. The use of such structures is a problem because complicated connections between the different parameters that make up CFST and the relevant qualities have to be defined. The advantages of the composite shear wall over traditional reinforced concrete walls are numerous. As a result, numerous experimental experiments investigating the seismic behavior of composite shear walls have been documented in the literature. However, not many numerical studies have been identified in previous research due to problems with the interaction of steel and concrete.
About the study
In this study, the authors discussed several publications that advanced the field of multiscale simulation of composite structures by using all common computational and/or analytical methods either alone or in combination with experimental techniques for damage assessment or mechanical analysis and prediction.
A study of the progressive failure behavior of a notched, single-ply, triaxially braided composite subjected to axial tension used a three-dimensional mesoscale finite element model. The progressive damage behavior of the fiber bundles was investigated by analyzing the damage and stress contours in different load stages.
The team discussed a study that estimated the extent of cracks based on the tiny deflection of a box girder and the stress applied to a structure using a semi-empirical model. Steel fiber reinforced concrete was used to build a set of tiny steel-concrete composite box girders. The collected data set was then used to create a condensed formula that provided the maximum crack width. In one study, a simplified numerical model was used to study the impact angle of a bullet during a low-velocity impact with Kevlar materials. In this work, a simplified model was constructed to provide the industry with valuable and rapid prediction tools.
Researchers examined a study that discussed the feasibility of predicting Pu using a feedforward neural network (FNN). To build a hybrid FNN-IWO model and increase its predictive performance, the FNN weights and biases were tuned and optimized using the Invasive Weed Optimization (IWO) evolutionary optimization algorithm. A study investigated and determined the best settings for particle swarm optimization (PSO) to improve the performance of adaptive neuro-fuzzy inference systems in calculating the buckling strength of circular-aperture steel beams.
Based on a combination of finite element method and molecular dynamics (MD), a study established a hybrid numerical formulation to characterize the thermomechanical behavior of nanocomposites (FEM). In a study, a computer procedure was created to investigate the vibrational behavior of the laminated composite structures.
One of the studies investigated how the addition of a recently proposed nanoparticle to a polymer matrix such as polyethylene affects its thermomechanical properties. The analysis was based on MD simulations of the tensile stress-strain response of the polymer nanocomposites at different temperatures. A study investigated the bending behavior of a concrete beam consisting of two C-sections connected and filled with recycled aggregate (CFST beam).
In one study, filled steel plates and concrete were used to create intelligent composite shear walls. The ANSYS software was used to carry out the study. The mechanical connections between web plate and concrete have been studied in detail. One study introduced three different model order reduction strategies along with a simple Matlab code to address topological optimization for the design of materials.
The results showed that at a load of more than 80 kN, cracks appeared in the area of the cutting moments. The center of the beam, where the most negative moment was present, was found to have the highest crack zone.
The numerical model had the advantage that it was calculated about 90% faster than a full 3D model. The natural frequency for each mode increased with the volume fraction of graphene in the matrix. With a 3.1% overestimate of the flexural strength, the numerical model was able to effectively verify the flexural behavior and failure mode of the corresponding specimen.
According to the results, when the distance between the steel plate and the concrete wall was increased from 0 to 40 mm, the stiffness was increased by 18% compared to the reference model. At ratios of 95% and 58%, respectively, stiffness and energy absorption were improved as the core steel plate thickness was increased to 12 mm.
The model was constrained and the lateral offset reduced when the concrete wall thickness was increased to 150mm, improving energy absorption and ductility in ratios of 32% and 52%, respectively. Ductility and energy absorption were improved by approximately 66% and 32%, respectively, when the spacing between head studs was increased from 20% to 25%.
In conclusion, this editorial discussed high quality studies that advanced the research field of multiscale simulation of composite structures by applying any modern analytical or computational methods alone or in combination with experimental approaches to assess their damage, mechanical behavior and various properties.
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Georgantzinos, SK, Multiscale Simulation of Composite Structures: Damage Assessment, Mechanical Analysis and Prediction. Materials, 15(18), 6494 (2022). https://www.mdpi.com/1996-1944/15/18/6494.