Composite Material Model Research Articles

A hybrid model for accurate prediction of composite longitudinal elastic modulus

This research presents a novel hybrid model that integrates a physical-based empirical model with an Artificial Neural Network (ANN) to accurately predict the longitudinal modulus of elasticity for composites under compression. The study focuses on a composite material with a pore inclusion within an ABS plastic matrix, exploring various pore volumes, orientations, and shapes. As part of the proposed hybrid model, a regression-type neural network was trained in MATLAB® to predict and correct discrepancies between the Generalized Stiffness Formulation (GSF) homogenization-based modeling method and the collected compression experimental test results. Using MATLAB® neural network, random error datasets were used to train the feed-forward neural network, and the remaining error datasets were used for validating the performance of the proposed hybrid modeling scheme.The hybrid model demonstrated superior performance, achieving the lowest Mean Error (ME) of 0.1684864, Mean Absolute Error (MAE) of 1.051846, Mean Squared Error (MSE) of 3.500952, and highest R-squared of 0.998797. The proposed hybrid model outperformed both the Generalized Stiffness Formulation (GSF) and standalone ANN models. The significant improvement in prediction accuracy underscores the novelty and robustness of the hybrid approach in composite material modeling. Furthermore, this method can be used to refine any existing physical model by focusing on improving these established models to match experimental results and reducing the discrepancies, which offers a more efficient and attractive strategy for accurate predictions.

Crack monitoring and repair model of SMA composite material based on strain transfer

In the process of using composite materials, crack damage is unavoidable. These cracks may cause a decrease in the structural performance of the material and may even pose a threat to the safety of the entire structure. In this paper, the shape memory alloy (SMA) is embedded into the composite material, and the strain transfer effect of the interface layer is considered. The crack monitoring and repair model of SMA composite material based on strain transfer are established using SMA resistance-sensing characteristics and SMA constitutive model. Based on this monitoring and repair model, the crack monitoring behavior of SMA under different initial states and temperature conditions is discussed, and the crack repair behavior of SMA under specific initial states and temperature conditions is also discussed. The research results show that the change in SMA resistance and the strain of the composite material crack are linearly segmented, and as the temperature increases, the composite material crack is gradually repaired. This study can provide theoretical guidance for the further engineering application of SMA composite material crack monitoring and repair theory.

A fine-segmentation algorithm for XCT images of multiphase composite building materials based on deep learning

In response to the challenges presented by the variable internal structures and complex components of multiphase composite building materials, this study introduces a novel image segmentation network named UT-FusionNet. Building on the U-Net model, UT-FusionNet integrates Transformer module and tensor concatenation and fusion mechanism to overcome the limitations of convolutional networks in relation to the receptive field. UT-FusionNet is employed to segment CT images of conventional concrete, grout consolidation bodies, and fiber-reinforced concrete. The results demonstrate that UT-FusionNet achieves superior segmentation accuracy and robustness, with Accuracy (ACC), Intersection over Union (IoU) and Dice scores exceeding 90 % across all subtasks. The mean accuracy metrics are 99.44 %, 96.70 %, and 98.31 %, respectively. This innovative end-to-end network offers robust support for detailed structural analysis, damage detection, and digital modeling of multiphase composite building materials through deep learning.

Development and experimental verification of an advanced 3D elastoplastic progressive damage model for composite materials

This study develops a sophisticated three-dimensional elastoplastic progressive damage finite element analysis (FEA) model for stiffened composite materials under axial compression. The model integrates the Hashin and Ye criteria to capture the inception of damage within the composite and introduces a cohesive zone model (CZM) to simulate debonding between stiffeners and panels. Furthermore, damage evolution based on energy release rate and plastic flow rules grounded in Hill’s criteria are employed to thoroughly explore the progressive failure behavior of stiffened composite materials. Implemented within Abaqus/Explicit through user-defined ‘VUMAT’ subroutines, the model ensures computational accuracy and reliability. Comparative evaluations against standard linear elastic progressive damage models demonstrate a statistically significant improvement of at least 5% in predicting ultimate load capacities. Additionally, this model accurately captures different failure modes, providing a nuanced understanding of stiffened composite material failure under compressive loads.

A sandwich-structured 1-3 type piezoelectric composite material for enhancing reliability

This study proposes a sandwich structure 1-3 piezoelectric composite, incorporating flexible silicone rubber to enhance the thickness vibration mode of piezoelectric ceramics. Rigid aluminum nitride (AlN) is employed to bolster the mechanical stability of the composite. Utilizing equivalent parameter theory, we establish a mathematical model for the sandwich structure composite material. The impact of the piezoelectric phase size and the volume fraction of AlN on several performance parameters of the material are analyzed, including the thickness electromechanical coupling coefficient, density, sound velocity, and characteristic impedance. The sandwich structure piezoelectric composite was fabricated using the "cutting and filling" technique. Experimental outcomes reveal that this material demonstrates concentrated thickness vibration modes, with a thickness electromechanical coupling coefficient reaching as high as 0.72, a 16.6 % increase compared to traditional 1-3 piezoelectric composites. Results from thermal shock tests and tensile tests suggest that the sandwich structure 1-3 piezoelectric composite has considerable potential for use in highly reliable low-frequency receiving transducers.

Study on the mechanical behavior of microcapsules during the mixing process of asphalt mixture

To enhance the survival rate of microcapsules during the mixing process of asphalt mixture, the mechanical behavior of microcapsules during this process was investigated through simulation. Initially, the asphalt mixture containing microcapsules was divided into mesoscopic and microscopic scales. Utilizing composite material models, the stepwise inclusion method and high-temperature tensile tests, the equivalent mechanical parameters for the microcapsules, asphalt mastic and asphalt mortar at mixing temperature were estimated. Following this, the mixing process of the asphalt mixture incorporating microcapsules was simulated employing the discrete element method (DEM) coupled with multi-body dynamics (MBD). This simulation was instrumental in identifying optimal mixing parameters and enabled the analysis of force chain transmission across the multi-scale model. Furthermore, the finite element method (FEM) was employed to develop a monomer model of the microcapsules, facilitating the assessment of their mechanical behavior under optimal mixing conditions. Finally, a detailed sensitivity analysis was performed to investigate the influence of various parameters on the mechanical behavior of microcapsules. The results indicated that, at the mixing temperature, the equivalent Young’s modulus and Poisson's ratio for urea-formaldehyde (UF) resin microcapsules, asphalt mastic, and asphalt mortar were determined to be 0.22 GPa and 0.478, 19.87 GPa and 0.4986, and 88.77 GPa and 0.468, respectively. The optimal mixing parameters for AC-16 asphalt mixture including mixing speed, filling rate and mixing duration were identified as 49 rpm, 50 % and 53 s, under which the most adverse load on the microcapsule is 80 mN. Under the most adverse load, microcapsules might rupture from the inside out, and their survival rate was not less than 68.9 %. Increasing the particle size of microcapsules and reducing the relative radius of the microcapsule core could potentially enhance the crack resistance of microcapsules during mixing.

Multiscale modeling and thermal conductivity evaluation of nano-reinforced composite materials with pore defect

The performance of resin-based composite materials often exhibits diversity due to the designability of various components. Thermal conductivity, an important thermal parameter of the composite, plays a significant role in thermal-chemical reactions, thermal stress analysis, temperature conduction, etc. However, it is relatively difficult to experimentally explore the thermal conduction mechanism of hybrid composite materials, mainly due to the relatively difficult control of various components. Therefore, this paper proposes a sequentially coupled cross-scale numerical method to characterize the thermal conductivity of nano-reinforced composite materials with pores by a multiscale periodic Representative Volume Element model generated by an improved Random Sequential Absorption algorithm. Firstly, periodic temperature boundary conditions are described, and the thermal conductivity performances of nano-reinforced matrix and composite with pores are investigated based on the finite element homogenization theory. Then, the proposed modes are validated and grid sensitivity analysis is conducted, indicating that the optimal grid sizes for the RVE models are 1.9 nm for the nano-reinforced matrix and 0.14 μm for the composite with pores based on a comprehensive comparison of four pore characterization methods, respectively. Furthermore, the study explored the effect of multiple parameters including nanoparticle content, pore content, and pore shape on thermal conductivity. Numerical findings reveal that the thermal conductivity of the nanocomposite matrix exhibits a linear increase with higher particle content. Specifically, compared to 0 % particle content, the thermal conductivity rises by 141.92 % at 12 % particle content. While the composite material's transverse thermal conductivity is sensitive to porosity content, it is less influenced by pore shape. The method proposed in this paper provides an effective approach for studying the thermal conduction of nano-reinforced composite materials with pores, and the research findings also offer theoretical guidance for process engineers.

Study on the Properties and Fatigue Characteristics of Glass Fiber Composites Due to Porosity

A study was conducted on the changes in mechanical properties and fatigue failure characteristics due to voids, one of the fabrication defects in composite materials. This study was primarily based on glass fiber fabrics applied to wind turbine blades and their material properties were predicted through micro and meso modeling of composite materials by simulating random defects including voids. As the wind turbine blades become larger, various defects develop. The fundamental changes in the materials’ properties due to voids were predicted through homogenization methods and Representative Volume Element (RVE), and the failure properties were obtained through progressive failure analysis by applying virtual coupons according to ASTM D3090 and ASTM D6641. The progressive failure was identified using the Matzenmiller–Lubliner–Taylor (MLT) failure condition, and the fatigue failure characteristics were assessed through the Tsai–Hill 3D load.

Predicting the modulus of elasticity of clayey soil composites reinforced with scrap tire rubber fibers using a composite material model

In this study, composite material models are used to predict the modulus of elasticity of a composite consisting of scrap tire rubber fibers and clayey soils. The calculated modulus of elasticity is compared with the reference modulus obtained from experimental testing. Predicting the effective mechanical properties of composites is crucial in situations where testing is impractical, challenging, or costly. The analysis involves various approaches within the elasticity framework, utilizing rheological models such as Voigt, Reuss, Hirsch-Dougill, Popovics, Halpin-Tsai, Hashin, and the Bache & Napper–Christensen estimation. These models aim to predict the effective Young's modulus of the composite system comprising soil and rubber fibers. The maximum discrepancies observed are 10.66%, 12.71%, and 12.98% for both soils. Voigt, Hashin, and Bache estimations provide highly accurate predictions of the effective Young's modulus, showing excellent agreement with experimental results across different fiber volume fractions ranging from 10% to 50%.

Modeling of ice-matrix composite fracture

This article discusses the results of a study that used the structural approach to conduct multiscale modeling of composite materials. These materials are composed of an ice matrix that has been enhanced with high-strength basalt fibers. The research involved numerical modeling to analyze the fracture process of composite materials made by freezing fresh water with added basalt fibers. The analysis included experimental data from samples of pure ice and composites with different amounts of filler. The effective modulus of elasticity of the composites was determined by considering the quantity of basalt fiber reinforcement. The discrepancy between the strength obtained by finite element complex ANSYS numerical calculation and the experimental data was revealed by a series of macroscopic test calculations of the composite material sample, according to which the effective modulus of elasticity of the composite was recalculated and corrections were introduced into the Voight and Reuss models, taking into account the non-uniform distribution of the fibers and the non-ideal adhesion between the fibers and water ice. A stochastic model of crack growth at the micro level was also used with the data on the diameter and length of basalt fibers and their random distribution in the layers of the composite material. Using the newly acquired effective elastic moduli and the SmartCrackGrowth algorithm, a satisfactory agreement of the crack growth rate with the obtained by stochastic calculation was achieved. The refined method of effective elastic moduli and multilevel model of stress-strain state calculation of composite materials are recommended for assessing the strength of ice cover and designing winter roads with high load-bearing capacity and long operational duration in the Arctic and Subarctic environments.

A dynamic response prediction of ultra-high strain rates of composite materials based on a surrogate model

Based on the propagation of laser-induced tensile waves in materials and the principle of material ply cracking, nondestructive testing technology for measuring the interfacial bonding force of composite materials can be developed. The study of the ultra-high strain rate dynamic response model of composite materials under the action of laser shock waves is crucial to this technique. Therefore, this paper proposes a method for constructing a dynamic response prediction model for composites based on data and a physical model driven by comprehensively considering the strain rate effect of materials. The constructed model can accurately predict the peak velocity and duration of the initial pulse of the velocity curve under the condition of ultra-high strain rate. The relative error between the predicted and simulated peak values is within 3%, and the relative error between the predicted and simulated initial pulse durations is within 5%. In addition, laser impact experiments were conducted on specimens of various thicknesses to validate the accuracy of the predicted data at ultra-high strain rates. The results show that the relative errors between the predicted and experimental peak values are all within 2%, and the relative errors of the initial pulse duration are within 9%.

Mesoscale Model for Composite Laminates: Verification and Validation on Scaled Un-Notched Laminates.

This paper presents a mesoscale damage model for composite materials and its validation at the coupon level by predicting scaling effects in un-notched carbon-fiber reinforced polymer (CFRP) laminates. The proposed material model presents a revised longitudinal damage law that accounts for the effect of complex 3D stress states in the prediction of onset and broadening of longitudinal compressive failure mechanisms. To predict transverse failure mechanisms of unidirectional CFRPs, this model was then combined with a 3D frictional smeared crack model. The complete mesoscale damage model was implemented in ABAQUS®/Explicit. Intralaminar damage onset and propagation were predicted using solid elements, and in-situ properties were included using different material cards according to the position and effective thickness of the plies. Delamination was captured using cohesive elements. To validate the implemented damage model, the analysis of size effects in quasi-isotropic un-notched coupons under tensile and compressive loading was compared with the test data available in the literature. Two types of scaling were addressed: sublaminate-level scaling, obtained by the repetition of the sublaminate stacking sequence, and ply-level scaling, realized by changing the effective thickness of each ply block. Validation was successfully completed as the obtained results were in agreement with the experimental findings, having an acceptable deviation from the mean experimental values.

Feasibility of using superelastic shape memory alloy in plastic hinge regions of steel bridge columns for seismic applications

AbstractThis paper contributes to the further development of seismic resilient infrastructure by introducing a novel prototype bridge which integrates tubular steel piers with superelastic shape memory alloy (SMA). The proposed bridge pier is composed of a circular steel tube which is bonded to a superelastic SMA tube in regions of high stress. The pier is distinguished by its ability to minimize residual drifts following inelastic deformations induced by cyclic loading. Three‐dimensional continuum finite element (FE) models are utilized to examine its lateral behavior. Experimental data is used to demonstrate the effectiveness of the continuum FE procedure in replicating the cyclic response and capturing both global and localized behaviors. A novel composite material model is proposed to represent the degradation of strength and accumulation of irreversible strains in the cyclic response of superelastic SMAs. An iterative procedure for the calibration of this material is presented. Investigations, employing the calibrated FE procedure, focus on the quasi‐static cyclic response of steel piers with superelastic SMA in the plastic hinge zone, aiming to identify the optimal length of the SMA tube for achieving a self‐centering response with reduced residual deformation. The study is then further expanded to examine the seismic response of a bridge structure incorporating such piers. Development of the FE model for the prototype bridge includes the modelling of the piers using continuum elements, while the superstructure, bearing units, abutment walls, and backfill material are modelled using discrete elements. Nonlinear time history analyses are undertaken to investigate the effects of column wall thickness and materials used in the plastic hinge zones of the piers. Dynamic FE study results indicate that bridges employing such piers are capable of returning to their original position, provided the SMA tube is of adequate length.

Модель накопления повреждений в ортотропном композиционном материале

The paper presents a theoretical and experimental study of the influence of damage accumulation in composite material on the elastic fourth-rank tensor and on the strength under quasi-static, cyclic and dynamic loads. Layered polymer composites (glass or carbon fiber-reinforced plastic) are considered. This work aims to develop a mathematical model that accounts for the impact of damage in the composite material on the fourth-rank tensor of elastic properties. The constitutive relations for an orthotropic composite material are proposed, taking into account the accumulation of damage during tensile or shear loading. A numerical simulation using the finite element method is done for a periodicity cell for composite variants (unidirectional, layered, etc.) to determine the effective elastic properties. Quasi-static loading experiments were conducted on composite samples (carbon plastic) to validate the model and the degradation of elastic properties was determined by measuring the longitudinal sound speed. The full-scale experiments confirmed that damage accumulation in carbon fiber-reinforced plastic leads to the degradation of its effective elastic properties. In this connection, a technique was developed to take into account irreversible damage in an orthotropic composite material through the components of the ductility tensor, which may be helpful for the design and analysis of composite structures. The findings of the study could help with the creation of new materials with enhanced mechanical characteristics, as well as with raising the quality of already-existing materials. The developed mathematical model of orthotropic composite material can be used to enhance the structural strength properties and boost the application safety in a variety of industry.

Comparative evaluation of mathematical models of polymer composite material with the implementation of a three-dimensional stress–strain state in the simulation of impact

Comparative evaluation of mathematical models of polymer composite material with the implementation of a three-dimensional stress–strain state in the simulation of impact

The effect of heat flux on enhancement heat transfer mechanism in copper metal foam composite paraffin wax during melting process: Experimental and simulation research

To investigate the effect of heat flux on the enhanced heat transfer in phase change materials (PCMs) composed of copper metal foam (CMF) and paraffin wax (PX), a semi-cylindrical visualized heat storage device with a varied heat flux of 7.3 kW/m2, 8.5 kW/m2, 9.7 kW/m2, and 10.9 kW/m2 was established in this paper. Moreover, a 3-D mathematical model of composite phase change materials (CPCMs) was established using hybrid grid to study the temperature distribution, imbalance effect, flow, heat transfer mechanisms, and heat storage performance during the melting process. The results showed that the melting time of the CPCMs decreased as the heat flux increased. Compared with a heat flux of 7.3 kW/m2, the melting time was shortened by 10.05 %, 20.71 %, and 27.21 %, respectively. In addition, the Rayleigh number (Ra) increased with the increase in heat flux, and the amplitudes of Ra were 1.45×108,1.54×108,1.61×108, and 1.74×108, respectively, which indicated that the higher the heat flux, the larger the amplitudes. Moreover, the heat transfer mechanism during the melting process was dominated by conduction; however, with the increase in heat flux, the maximum flow velocity of the liquid paraffin increased, which caused the proportion of natural convection to increase from 27.80 % to 31.30 %. Hence, the integrated heat transfer coefficient of CPCMs increased from 5.69 W/(m·K) to 5.81 W/(m·K). However, the temperature imbalance effect of the CPCMs was exacerbated, as evidenced by the increased maximum temperature difference in the vertical direction of the center of the CPCMs from 24.7 K to 35.6 K. Besides, the heat storage performance was enhanced. Compared with a heat flux of 7.3 kW/m2, the heat storage capacities of the CPCMs increased by 4.21%, 9.46%, and 12.66 % with increasing heat flux, and the heat storage rates of the CPCMs increased by 15.3 %, 34.9 %, and 52.3 %, respectively. Furthermore, the relative error of the overall melting time was 3.4 %, indicating that the model provided reasonable predictions.

Configuration Design and Verification of Shear Compliant Border in Space Membrane Structure.

To solve the non-uniformity of stress in space membrane structure and the lack of shear compliant border configuration design method, shear compliant borders are designed, optimized, and verified in terms of configuration. Firstly, an orthotropic model of the borders is built by combining Hill and Christensen-Lo composite material models. Secondly, a finite element form-finding method is put forward by establishing rectangular and cylindrical coordinates in different areas. The configuration of borders is obtained and the influence of the borders on the edge of the membrane is 0.23%, which means that the borders are compatible with the existing tensegrity systems, especially the tensioning components and the cable sleeves. Thirdly, simulation verifies that borders can cut the spread of shear stress and improve the stress uniformity in membrane structure. The maximum stress in the membrane effective area is decreased by 35.6% and the stress uniformity is improved by 30.5%. Finally, a membrane extension experiment is committed to compare the flatness of membrane surface under shear stress with and without shear compliant borders. The borders decrease the increment speed of flatness by 58.1%, which verifies the amelioration of stress uniformity. The shear compliant border configuration design method provides a reference for space membrane structure stress-uniform design.

Computational Modelling and Mechanical Characteristics of Polymeric Hybrid Composite Materials: An Extensive Review

Computational Modelling and Mechanical Characteristics of Polymeric Hybrid Composite Materials: An Extensive Review

Modeling of Dual-Phase Composite Magnetic Material and Its Application in Transformers

Dual-phase composite magnetic materials have magnetic and permanent magnetic properties. They can realize the dual-phase conversion of soft magnetic and permanent magnetic composites with a small amount of excitation energy. They have the advantages of good control and conversion characteristics and save energy, and they have a wide range of application scenarios in regard to power equipment. In this paper, the magnetization modeling of dual-phase composite magnetic materials is carried out based on micromagnetic theory, and a specific mathematical expression is given. Secondly, the preparation process of the dual-phase composite magnetic material is studied, the dual-phase composite magnetic material is prepared, and the demagnetization curve of the dual-phase composite magnetic material is measured. Finally, the application of dual-phase composite magnetic materials in power equipment is carried out. Using the soft magnetic and permanent magnetic characteristics of dual-phase composite magnetic materials, their impact on DC bias suppression in transformers is assessed. Magnetic circuit reluctance theory is used to develop the structure and electromagnetic design of a transformer. A transformer prototype with DC bias suppression ability based on dual-phase composite magnetic materials is manufactured, and simulation and experimental research are carried out. The simulation and experimental results verify the correctness of the proposed scheme. Although this scheme requires a more complex core structure, the energy-saving effect is remarkable without changing the transformer’s neutral grounding. The indicators meet the actual requirements of the project.

Calculation model for bearing capacity of steel-CFRP composite pipeline under internal pressure

The Carbon Fiber Reinforced Polymer (CFRP)-wrapped steel pipeline system is emerging as an alternative for the repair and long-distance transportation of oil and gas. This system is recognized as a composite material. Under internal pressure, the pipe predominantly undergoes circumferential stretching. This study derives the tensile constitutive model of the steel-CFRP composite material using uniaxial tensile tests and the rule of mixtures. Subsequently, utilizing this newly calibrated constitutive model, a computational model to assess the internal pressure capacity of the steel-carbon fiber composite pipe was established. Finally, a comparison between the theoretical outcomes of the computational model and the actual internal pressure test results revealed a high degree of correlation. This holds substantial significance for the design and practical implementation of this novel composite pipeline system.