This work addresses optimality aspects related to composite laminates having layers with different orientations.RegressionNeuralNetworks can model the mechanical behavior of these laminates,specifically the stressstra...This work addresses optimality aspects related to composite laminates having layers with different orientations.RegressionNeuralNetworks can model the mechanical behavior of these laminates,specifically the stressstrain relationship.If this model has strong generalization ability,it can be coupled with a metaheuristic algorithm–the PSO algorithm used in this article–to address an optimization problem(OP)related to the orientations of composite laminates.To solve OPs,this paper proposes an optimization framework(OFW)that connects the two components,the optimal solution search mechanism and the RNN model.The OFW has two modules:the search mechanism(Adaptive Hybrid Topology PSO)and the Prediction and Computation Module(PCM).The PCM undertakes all the activities concerning the OP at hand:the stress-strain model,constraints checking,and computation of the objective function.Two case studies about the layers’orientations of laminated specimens are conducted to validate the proposed framework.The specimens belong to“Off-axis oriented specimens”and are subjects of two OPs.The algorithms for AHTPSO and for the two PCMs(one for each problem)are proposed and implemented by MATLAB scripts and functions.Simulations are carried out for different initial conditions.The solutions demonstrated that the OFW is effective and has a highly acceptable computational complexity.The limitation of using the OFWis the generalization ability of the RNN model or any other regression models.To harness the RNN model efficiently,it must have a very good generalization power.If this condition ismet,the OFWcan be integrated into any design process to make optimal choices of the layers’orientations.展开更多
This study investigates the uncertain dynamic characterization of hybrid composite plates by employing advanced machine-assisted finite element methodologies.Hybrid composites,widely used in aerospace,automotive,and s...This study investigates the uncertain dynamic characterization of hybrid composite plates by employing advanced machine-assisted finite element methodologies.Hybrid composites,widely used in aerospace,automotive,and structural applications,often face variability in material properties,geometric configurations,and manufacturing processes,leading to uncertainty in their dynamic response.To address this,three surrogate-based machine learning approaches like radial basis function(RBF),multivariate adaptive regression splines(MARS),and polynomial neural networks(PNN)are integrated with a finite element framework to efficiently capture the stochastic behavior of these plates.The research focuses on predicting the first three natural frequencies under material uncertainties,which are critical to ensuring structural reliability.Monte Carlo simulation(MCS)is used as a benchmark for generating probabilistic datasets,including mean values,standard deviations,and probability density functions.The surrogate models are then trained and validated against these datasets,enabling accurate representation of uncertainty with substantially fewer samples compared to conventionalMCS.Among the methods studied,the RBFmodel demonstrates superior performance,closely approximating MCS results with a reduced sample size,thereby achieving significant computational savings.The proposed framework not only reduces computational time and costs but also maintains high predictive accuracy,making it well-suited for complex engineering systems.Beyond free vibration analysis,the methodology can be extended to more sophisticated scenarios,such as forced vibration,damping effects,and nonlinear structural responses.Overall,this work presents a computationally efficient and robust approach for surrogate-based uncertainty quantification,advancing the analysis and design of hybrid composite structures under uncertainty.展开更多
Accelerated aging tests are widely used to rapidly evaluate the durability of materials,of which thermal-oxidative aging is the most common approach.To quantitatively predict the effects of multiple coupled factors,th...Accelerated aging tests are widely used to rapidly evaluate the durability of materials,of which thermal-oxidative aging is the most common approach.To quantitatively predict the effects of multiple coupled factors,this study takes polyamide66 reinforced with glass fiber(PA66-GF)as a model system and proposed a high-precision paradigm for coupled thermal-oxidative aging.By integrating Arrhenius-type reaction kinetics with oxygen diffusion,a predictive formula that holistically captures the nonlinear synergistic effects of multiple factors was developed,thereby overcoming the limitations of traditional single-variable models.A systematic evaluation of the stepwise improved formulas through nonlinear fitting showed that the coefficient of determination(R^(2))increased from 0.223 to 0.803,elucidating the fundamental reason why conventional approaches fail in quantitative prediction.These formulae were further embedded as physical constraints into a physics-informed neural network(PINN),which further enhanced the predictive performance,with the proposed formula achieving a peak R^(2)of 0.946.The results highlight that robust data fitting alone is insufficient;the decisive factor for the success of PINN lies in whether the embedded formula faithfully reflects the underlying physical mechanisms.When applied to polyamide 6 reinforced with glass fiber(PA6-GF),the Formula-constrained PINN maintained a high level of accuracy(R^(2)=0.916),demonstrating its strong cross-system generalizability.In summary,this work establishes a robust hybrid physics-machine learning framework that combines high accuracy with transferability for predicting the thermal-oxidative aging behavior of composite material systems.展开更多
Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade compone...Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade components.In this paper,a dynamic model of 3D 4-directional braided composite thin plates considering braiding directions is established.Based on Kirchhoff's plate assumptions,the displacement variables of the plate are expressed.By incorporating the braiding directions into the constitutive equation of the braided composites,the dynamic model of the plate considering braiding directions is obtained.The effects of the speeds,braiding directions,and braided angles on the responses of the plate with fixed-axis rotation and translational motion,respectively,are investigated.This paper presents a dynamic theory for calculating the deformation of 3D braided composite structures undergoing both translational and rotational motions.It also provides a simulation method for investigating the dynamic behavior of non-isotropic material plates in various applications.展开更多
As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely...As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely used in aerospace, unmanned driving, and other fields. However, due to the temper-ature sensitivity of optical devices, the influence of environmen-tal temperature causes errors in FOG, thereby greatly limiting their output accuracy. This work researches on machine-learn-ing based temperature error compensation techniques for FOG. Specifically, it focuses on compensating for the bias errors gen-erated in the fiber ring due to the Shupe effect. This work pro-poses a composite model based on k-means clustering, sup-port vector regression, and particle swarm optimization algo-rithms. And it significantly reduced redundancy within the sam-ples by adopting the interval sequence sample. Moreover, met-rics such as root mean square error (RMSE), mean absolute error (MAE), bias stability, and Allan variance, are selected to evaluate the model’s performance and compensation effective-ness. This work effectively enhances the consistency between data and models across different temperature ranges and tem-perature gradients, improving the bias stability of the FOG from 0.022 °/h to 0.006 °/h. Compared to the existing methods utiliz-ing a single machine learning model, the proposed method increases the bias stability of the compensated FOG from 57.11% to 71.98%, and enhances the suppression of rate ramp noise coefficient from 2.29% to 14.83%. This work improves the accuracy of FOG after compensation, providing theoretical guid-ance and technical references for sensors error compensation work in other fields.展开更多
A partial-periodic model is proposed for predicting structural properties of composite laminate structures.The partial-periodic model contains periodic boundary conditions in one direction or two directions,and free b...A partial-periodic model is proposed for predicting structural properties of composite laminate structures.The partial-periodic model contains periodic boundary conditions in one direction or two directions,and free boundary condition in other directions.In the present study,partial-periodic model for composite laminate beam structures is particularly studied.Three-point bending experiments for laminate beam specimens with different laying parameters are firstly used to verify the present partial-periodic model.In addition,a detailed finite element method(FEM)model is also used to further quantitatively compare with the present partial-periodic model for composite laminate beams with different laying parameters.The results indicate that the proposed partial-periodic model is capable of providing accurate predictions in most cases.The computational time cost of the proposed partial-periodic model is much lower than that of the detailed FEM model as well.Convergence studies are also conducted for the present partial-periodic model with different model sizes and element sizes.It is suggested that the proposed partial-periodic model has the potential to be used as an accurate and time-saving tool for predicting the structural properties of composite laminate beam structures.展开更多
The prediction of the rolling force and thickness ratio plays an important role in the development and application of bimetallic composite plates.To analyze the rolling force of the bimetallic composite plate more acc...The prediction of the rolling force and thickness ratio plays an important role in the development and application of bimetallic composite plates.To analyze the rolling force of the bimetallic composite plate more accurately,a novel hypothesis based on Orowan's theory was proposed.The variation in the thickness of each differential element at different positions was considered to establish the analytical model.According to the characteristics of bimetallic composite plate rolling,the rolling deformation can be divided into forward and backward slip zones.The initial thickness ratio after rolling was predetermined by the thickness ratio before rolling;the rolling force balance of the upper and lower rollers was considered the convergence condition;and the final thickness ratio of the bimetallic composite plate was obtained by iterative calculation.The calculation results of the analytical model were compared with the measured and simulated data.The results showed that the errors in the calculation of the rolling force and thickness ratio were both less than 10%.The analytical model has high precision,meets engineering requirements,and has important reference significance for rolling process optimization and thickness ratio prediction.展开更多
Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring.However,there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fib...Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring.However,there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fibers,and the detailed mechanism of how embedded optical fibers affect the micromechanical behavior and damage failure processes within composite materials remains unclear.This paper presents a micromechanical simulation analysis of composite materials embedded with optical fibers.By constructing representative volume elements(RVEs)with randomly distributed reinforcing fibers,the optical fiber,the matrix,and the interface phase,the micromechanical behavior and damage evolution under transverse tensile and compressive loads are explored.The study finds that the presence of embedded optical fibers significantly influences the initiation and propagation of microscopic damage within the composites.Under transverse tension,the fiber-matrix interface cracks first,followed by plastic cracking in the matrix surrounding the fibers,forming micro-cracks.Eventually,these cracks connect with the debonded areas at the fiber-matrix interface to form a dominant crack that spans the entire model.Under transverse compression,plastic cracking first occurs in the resin surrounding the optical fibers,connecting with the interface debonding areas between the optical fibers and the matrix to form two parallel shear bands.Additionally,it is observed that the strength of the interface between the optical fiber and the matrix critically affects the simulation results.The simulated damage morphologies align closely with those observed using scanning electron microscopy(SEM).These findings offer theoretical insights that can inform the design and fabrication of smart composite materials with embedded optical fiber sensors for advanced structural health monitoring.展开更多
Carbon nanotubes(CNTs)have garnered great attention in recent years due to their outstanding electrical,thermal,and mechanical properties.The incorporation of small amounts of CNTs in polymers can substantially improv...Carbon nanotubes(CNTs)have garnered great attention in recent years due to their outstanding electrical,thermal,and mechanical properties.The incorporation of small amounts of CNTs in polymers can substantially improve the sensitivity of the polymer's electrical conductivity.This paper presents a modified Maxwell model to evaluate the electrical conductivity of CNTs-filled polymer composites by introducing a transition zone to account for the tunneling effect.In this modified Maxwell model,the CNTs-filled polymer composite is modeled as a three-phase composite,consisting of a matrix(polymer),inclusions(CNTs),and a transition zone(tunneling zone).The effective electrical conductivity(EEC)of the composite is calculated based on the volume fractions and electrical conductivities of the matrix,inclusions,and transition zone.The model's validity is confirmed through the use of available test data,which demonstrates its capability to accurately capture the nonlinear conductivity behavior observed in CNTs-polymer composites.This study offers valuable insights into the design of high-performance conductive polymer nanocomposites,and enhances the understanding of electrical conduction mechanisms in CNT-dispersed polymer composites.展开更多
In chemical science,the vertical ionization potential(VIP)is a crucial metric for understanding the electronegativity,hardness and softness of chemical material systems as well as the electronic structure and stabilit...In chemical science,the vertical ionization potential(VIP)is a crucial metric for understanding the electronegativity,hardness and softness of chemical material systems as well as the electronic structure and stability of molecules.Ever since the last century,the model chemistry composite methods have witnessed tremendous developments in computing the thermodynamic properties as well as the barrier heights.However,their performance in realm of the vertical electron processes of molecular systems has been rarely explored.In this study,we for the first time benchmarked the model chemistry composite methods(e.g.,CBS-QB3,G4 and W1BD)in comparison with the commonly used Koopmans's theorem(KT),electron propagator theory(e.g.,OVGF,D2,P3 and P3+)and CCSD(T)methods in calculating the VIP for up to 613 molecular systems with available experimental measurements.The large-scale test calculations strongly showed that the CBS-QB3 model chemistry composite technique can be well recommended to calculate VIP from the perspectives of accuracy,economy and applicability.Notably,the VIP values of up to 7 molecules were identified to have the absolute errors of larger than 0.3 e V at all calculation levels,which have strong hints that their VIP experimental values should be re-investigated.展开更多
High-volume fraction silicon particle-reinforced aluminium matrix composites(Si/Al)are increasingly applied in aerospace,radar communications,and large-scale integrated circuits because of their superior thermal condu...High-volume fraction silicon particle-reinforced aluminium matrix composites(Si/Al)are increasingly applied in aerospace,radar communications,and large-scale integrated circuits because of their superior thermal conductivity,wear resistance,and low thermal expansion coefficient.However,the abrasive and adhesive wear caused by the hard silicon reinforcement and the ductile aluminium matrix leads to significant tool wear,decreased machining efficiency,and compromised surface quality.This study combines theoretical analysis and cutting experiments to investigate polycrystalline diamond(PCD)tool wear during milling of 70 vol%Si/Al composite.A key contribution of this work is the development of a tool wear model that incorporates reinforcement particle characteristics,treating them as ellipsoidal structures,which enhances the accuracy of predicting abrasive and adhesive wear mechanisms.The model is based on abrasive and adhesive wear mechanisms,and can analyze the interaction between silicon particles,aluminium matrix,and tool components,thus providing deeper insights into PCD tool wear processes.Experimental validation of the model shows a good agreement with the results,with a mean deviation of approximately 10%.The findings on the tool wear mechanism reveal that,as tool wear progresses,the proportion of abrasive wear increases from 40%in the running-in stage to 75%in the rapid wear stage,while adhesive wear decreases.The optimal machining parameters of 120 m·min^(–1) cutting speed(v_(c))and 0.04 mm·z^(–1) feed rate(f_(z)),result in tool life of 33 min and surface roughness(S_(a))of 2.2μm.The study uncovers the variation patterns of abrasive and adhesive wear during the tool wear process,and the proposed model offers a robust framework for predicting tool wear during the machining of high-volume fraction Si/Al composites.The research findings also offer key insights for optimizing tool selection and machining parameters,advancing both the theoretical understanding and practical application of PCD tool wear.展开更多
In this work,the microstructure evolution and mechanical behavior of extruded SiC/ZA63 Mg matrix composites are investigated via combined experimental study and three-dimensionalfinite element modelling(3D FEM)based on...In this work,the microstructure evolution and mechanical behavior of extruded SiC/ZA63 Mg matrix composites are investigated via combined experimental study and three-dimensionalfinite element modelling(3D FEM)based on the actual 3D microstructure achieved by synchrotron tomography.The results show that the average grain size of composite increases from 0.57μm of 8μm-SiC/ZA63 to 8.73μm of 50μm-SiC/ZA63.The type of texture transforms from the typicalfiber texture in 8μm-SiC/ZA63 to intense basal texture in 50μm-SiC/ZA63 composite and the intensity of texture increases sharply with increase of SiC particle size.The dynamic recrystallization(DRX)mechanism is also changed with increasing SiC particle size.Experimental and simulation results verify that the strength and elongation both decrease with increase of SiC particle size.The 8μm-SiC/ZA63 composite possesses the optimal mechanical property with yield strength(YS)of 383 MPa,ultimate tensile strength(UTS)of 424 MPa and elongation of 6.3%.The outstanding mechanical property is attributed to the ultrafine grain size,high-density precipitates and dislocation,good loading transfer effect and the interface bonding between SiC and matrix,as well as the weakened basal texture.The simulation results reveal that the micro-cracks tend to initiate at the interface between SiC and matrix,and then propagate along the interface between particle and Mg matrix or at the high strain and stress regions,and further connect with other micro-cracks.The main fracture mechanism in 8μm-SiC/ZA63 composite is ductile damage of matrix and interfacial debonding.With the increase of particle size,interface strength and particle strength decrease,and interface debonding and particle rupture become the main fracture mechanism in the 30μm-and 50μm-SiC/ZA63 composites.展开更多
To address the issue of post-rolling warpage caused by differences in material properties during the composite rolling process of steel/aluminum thin strips,stress analysis was conducted at the entrance,middle,and exi...To address the issue of post-rolling warpage caused by differences in material properties during the composite rolling process of steel/aluminum thin strips,stress analysis was conducted at the entrance,middle,and exit sides of the rolling deformation zone for both steel and aluminum units.The unequal characteristics of the upper and lower contact arc lengths and the micromoment phenomenon,generated by the transfer of force between adjacent units on the aluminum side,were analyzed to explain the mechanical mechanism of warpage in the composite rolling process.A formula for calculating the contact arc length in the upper and lower rolling deformation zones was derived using the relationships among the contact arc length,rolling force,roll parameters,and strip parameters.On the basis of the deformation characteristics of steel and aluminum in the rolling deformation zone,the concepts of the inlet half-rolling zone,relative sliding zone,rolling composite zone,and outlet half-rolling zone were proposed.A quantitative model for characterizing warpage during the composite rolling of steel/aluminum composite thin strips was established.These results indicate that adjusting the diameters of the upper and lower work rolls is an effective method for controlling warpage defects and that warpage plays a dominant role in steel/aluminum thin strip composite rolling.Furthermore,finite element simulations of steel/aluminum composites rolled with different upper and lower roll diameters verified the deformation mechanism and influence of roll diameter differences on warpage defects.展开更多
Heterogeneous composites have strong anisotropy and are prone to dynamic recrystallization during hot compression,making the me-chanical response highly nonlinear.Therefore,it is a very challenging task to intellectua...Heterogeneous composites have strong anisotropy and are prone to dynamic recrystallization during hot compression,making the me-chanical response highly nonlinear.Therefore,it is a very challenging task to intellectually judge the thermal deformation characteristics of magnesium matrix composites(MgMCs).In view of this,this paper introduces a method to accurately solve the thermoplastic deformation of composites.Firstly,a hot compression constitutive model of magnesium matrix composites based on stress softening correction was established.Secondly,the complex quasi-realistic micromechanics modeling of heterogeneous magnesium matrix composites was conducted.By introducing the recrystallization softening factor and strain parameter into the constitutive equation,the accurate prediction of the global rheological response of the composites was realized,and the accuracy of the new constitutive model was proved.Finally,the thermal pro-cessing map of magnesium matrix composites was established,and the suitable processing range was chosen.This paper has certain guiding values for the prediction of the thermodynamic response and thermal processing of magnesium matrix composites.展开更多
Piezoelectric materials are capable of actuation and sensing and have been used in a wide variety of smart devices and structures.Active fiber composite and macro fiber composite are newly developed types of piezoelec...Piezoelectric materials are capable of actuation and sensing and have been used in a wide variety of smart devices and structures.Active fiber composite and macro fiber composite are newly developed types of piezoelectric composites,and show superior properties to monolithic piezoelectric wafer due to their distinctive structures.Numerous work has focused on the performance prediction of the composites by evaluation of structural parameters and properties of the constituent materials with analytical and numerical methods.Various applications have been explored for the piezoelectric fiber composites,including vibration and noise control,health monitoring,morphing of structures and energy harvesting,in which the composites play key role and demonstrate the necessity for further development.展开更多
TiC particles reinforced Ni-based alloy composite coatings were prepared on 7005 aluminum alloy by plasma spray. The effects of load, speed and temperature on the tribological behavior and mechanisms of the composite ...TiC particles reinforced Ni-based alloy composite coatings were prepared on 7005 aluminum alloy by plasma spray. The effects of load, speed and temperature on the tribological behavior and mechanisms of the composite coatings under dry friction were researched. The wear prediction model of the composite coatings was established based on the least square support vector machine (LS-SVM). The results show that the composite coatings exhibit smaller friction coefficients and wear losses than the Ni-based alloy coatings under different friction conditions. The predicting time of the LS-SVM model is only 12.93%of that of the BP-ANN model, and the predicting accuracies on friction coefficients and wear losses of the former are increased by 58.74%and 41.87%compared with the latter. The LS-SVM model can effectively predict the tribological behavior of the TiCP/Ni-base alloy composite coatings under dry friction.展开更多
By the constant stress tensile creep test method, creep tests were performed on aluminum silicate short fiber-reinforced AZ91D magnesium matrix composite with volume fraction of 30% and its matrix alloy AZ91D under di...By the constant stress tensile creep test method, creep tests were performed on aluminum silicate short fiber-reinforced AZ91D magnesium matrix composite with volume fraction of 30% and its matrix alloy AZ91D under different temperatures and stresses. The results indicate that the composite and the matrix have the same true stress exponent and true activation energy for creep, which are 3 and 144.63 kJ/mol, respectively. The creep of the composite is controlled by the creep of its matrix, which is mainly the controlling of viscous slip of dislocation, and the controlling of grain boundary slippage as a supplement. The creep constitutive model obtained from the experiment data can well describe the creep deformation pattern of the composite.展开更多
In order to establish the relationship between the measured dynamic response and the health status of long-span bridges, a double-layer model updating method for steel-concrete composite beam cable-stayed bridges is p...In order to establish the relationship between the measured dynamic response and the health status of long-span bridges, a double-layer model updating method for steel-concrete composite beam cable-stayed bridges is proposed. Measured frequencies are selected as the first-layer reference data, and the mass of the bridge deck, the grid density, the modulus of concrete and the ballast on the side span are modified by using a manual tuning technique. Measured global positioning system （GPS） data is selected as the second-layer reference data, and the degradation of the integral structure stiffness EI of the whole bridge is taken into account for the second-layer model updating by using the finite element iteration algorithm. The Nanpu Bridge in Shanghai is taken as a case to verify the applicability of the proposed model updating method. After the first-layer model updating, the standard deviation of modal frequencies is smaller than 7%. After the second-layer model updating, the error of the deflection of the mid-span is smaller than 10%. The integral structure stiffness of the whole bridge decreases about 20%. The research results show a good agreement between the calculated response and the measured response.展开更多
As an advanced composite material, the 3D braided composite has received more and more attention in foreign countries. However, it has received less attention in China. The geometric unit cell which can describe the b...As an advanced composite material, the 3D braided composite has received more and more attention in foreign countries. However, it has received less attention in China. The geometric unit cell which can describe the basic structure and the relationship between the braiding angle and geometric parameters of the fabric and fiber volume ratio are given in this paper based on two 3D braiding processes, namely, the four-step and the twostep ones. Several existing mechanical models to predict groperties of the 3D braided comPOsites are discussed and their shortcomings are pointed out herein. Then a new model called the inclined laminal combination model is proposed, which is based on the classical laminated plate theory and can predict the basic mechanical behavior of the two 3D braided composites with four-step or two-step braid. In the model, each yarn in the unit cell is regarded as an inclined laminate and then a 3D analysis is performed. It is found that the predicted mechanical properties of the 3D braided composites by the proposed model are compared well with the experimental data.展开更多
Theoretical and empirical models for predicting the thermal conductivity of polymer composites were summarized since the 1920s.The effects of particle shape,filler amount,dispersion state of fillers,and interfacial th...Theoretical and empirical models for predicting the thermal conductivity of polymer composites were summarized since the 1920s.The effects of particle shape,filler amount,dispersion state of fillers,and interfacial thermal barrier on the thermal conductivity of filled polymer composites were investigated,and the agreement of experimental data with theoretical models in literatures was discussed.Silica with high thermal conductivity was chosen to mix with polyvinyl-acetate （EVA） copolymer to prepare SiO2/EVA co-films.Experimental data of the co-films＇ thermal conductivity were compared with some classical theoretical and empirical models.The results show that Agari＇s model,the mixed model,and the percolation model can predict well the thermal conductivity of SiO2/EVA co-films.展开更多
基金supported by the Ministry of Research,Innovation and Digitization,CNCS/CCCDI–UEFISCDI(Romania),Nr.11/2024,within PNCDI IV.The APC received no external funding.
文摘This work addresses optimality aspects related to composite laminates having layers with different orientations.RegressionNeuralNetworks can model the mechanical behavior of these laminates,specifically the stressstrain relationship.If this model has strong generalization ability,it can be coupled with a metaheuristic algorithm–the PSO algorithm used in this article–to address an optimization problem(OP)related to the orientations of composite laminates.To solve OPs,this paper proposes an optimization framework(OFW)that connects the two components,the optimal solution search mechanism and the RNN model.The OFW has two modules:the search mechanism(Adaptive Hybrid Topology PSO)and the Prediction and Computation Module(PCM).The PCM undertakes all the activities concerning the OP at hand:the stress-strain model,constraints checking,and computation of the objective function.Two case studies about the layers’orientations of laminated specimens are conducted to validate the proposed framework.The specimens belong to“Off-axis oriented specimens”and are subjects of two OPs.The algorithms for AHTPSO and for the two PCMs(one for each problem)are proposed and implemented by MATLAB scripts and functions.Simulations are carried out for different initial conditions.The solutions demonstrated that the OFW is effective and has a highly acceptable computational complexity.The limitation of using the OFWis the generalization ability of the RNN model or any other regression models.To harness the RNN model efficiently,it must have a very good generalization power.If this condition ismet,the OFWcan be integrated into any design process to make optimal choices of the layers’orientations.
文摘This study investigates the uncertain dynamic characterization of hybrid composite plates by employing advanced machine-assisted finite element methodologies.Hybrid composites,widely used in aerospace,automotive,and structural applications,often face variability in material properties,geometric configurations,and manufacturing processes,leading to uncertainty in their dynamic response.To address this,three surrogate-based machine learning approaches like radial basis function(RBF),multivariate adaptive regression splines(MARS),and polynomial neural networks(PNN)are integrated with a finite element framework to efficiently capture the stochastic behavior of these plates.The research focuses on predicting the first three natural frequencies under material uncertainties,which are critical to ensuring structural reliability.Monte Carlo simulation(MCS)is used as a benchmark for generating probabilistic datasets,including mean values,standard deviations,and probability density functions.The surrogate models are then trained and validated against these datasets,enabling accurate representation of uncertainty with substantially fewer samples compared to conventionalMCS.Among the methods studied,the RBFmodel demonstrates superior performance,closely approximating MCS results with a reduced sample size,thereby achieving significant computational savings.The proposed framework not only reduces computational time and costs but also maintains high predictive accuracy,making it well-suited for complex engineering systems.Beyond free vibration analysis,the methodology can be extended to more sophisticated scenarios,such as forced vibration,damping effects,and nonlinear structural responses.Overall,this work presents a computationally efficient and robust approach for surrogate-based uncertainty quantification,advancing the analysis and design of hybrid composite structures under uncertainty.
基金financially supported by the National Natural Science Foundation of China(No.22473032)。
文摘Accelerated aging tests are widely used to rapidly evaluate the durability of materials,of which thermal-oxidative aging is the most common approach.To quantitatively predict the effects of multiple coupled factors,this study takes polyamide66 reinforced with glass fiber(PA66-GF)as a model system and proposed a high-precision paradigm for coupled thermal-oxidative aging.By integrating Arrhenius-type reaction kinetics with oxygen diffusion,a predictive formula that holistically captures the nonlinear synergistic effects of multiple factors was developed,thereby overcoming the limitations of traditional single-variable models.A systematic evaluation of the stepwise improved formulas through nonlinear fitting showed that the coefficient of determination(R^(2))increased from 0.223 to 0.803,elucidating the fundamental reason why conventional approaches fail in quantitative prediction.These formulae were further embedded as physical constraints into a physics-informed neural network(PINN),which further enhanced the predictive performance,with the proposed formula achieving a peak R^(2)of 0.946.The results highlight that robust data fitting alone is insufficient;the decisive factor for the success of PINN lies in whether the embedded formula faithfully reflects the underlying physical mechanisms.When applied to polyamide 6 reinforced with glass fiber(PA6-GF),the Formula-constrained PINN maintained a high level of accuracy(R^(2)=0.916),demonstrating its strong cross-system generalizability.In summary,this work establishes a robust hybrid physics-machine learning framework that combines high accuracy with transferability for predicting the thermal-oxidative aging behavior of composite material systems.
基金Project supported by the National Natural Science Foundation of China(Nos.12372071 and 12372070)the Aeronautical Science Fund of China(No.2022Z055052001)the Foundation of China Scholarship Council(No.202306830079)。
文摘Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade components.In this paper,a dynamic model of 3D 4-directional braided composite thin plates considering braiding directions is established.Based on Kirchhoff's plate assumptions,the displacement variables of the plate are expressed.By incorporating the braiding directions into the constitutive equation of the braided composites,the dynamic model of the plate considering braiding directions is obtained.The effects of the speeds,braiding directions,and braided angles on the responses of the plate with fixed-axis rotation and translational motion,respectively,are investigated.This paper presents a dynamic theory for calculating the deformation of 3D braided composite structures undergoing both translational and rotational motions.It also provides a simulation method for investigating the dynamic behavior of non-isotropic material plates in various applications.
基金supported by the National Natural Science Foundation of China(62375013).
文摘As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely used in aerospace, unmanned driving, and other fields. However, due to the temper-ature sensitivity of optical devices, the influence of environmen-tal temperature causes errors in FOG, thereby greatly limiting their output accuracy. This work researches on machine-learn-ing based temperature error compensation techniques for FOG. Specifically, it focuses on compensating for the bias errors gen-erated in the fiber ring due to the Shupe effect. This work pro-poses a composite model based on k-means clustering, sup-port vector regression, and particle swarm optimization algo-rithms. And it significantly reduced redundancy within the sam-ples by adopting the interval sequence sample. Moreover, met-rics such as root mean square error (RMSE), mean absolute error (MAE), bias stability, and Allan variance, are selected to evaluate the model’s performance and compensation effective-ness. This work effectively enhances the consistency between data and models across different temperature ranges and tem-perature gradients, improving the bias stability of the FOG from 0.022 °/h to 0.006 °/h. Compared to the existing methods utiliz-ing a single machine learning model, the proposed method increases the bias stability of the compensated FOG from 57.11% to 71.98%, and enhances the suppression of rate ramp noise coefficient from 2.29% to 14.83%. This work improves the accuracy of FOG after compensation, providing theoretical guid-ance and technical references for sensors error compensation work in other fields.
基金financial support from the National Key Research and Development Plan(2022YFB3707700)the National Natural Science Foundation of China(11872138 and 12172074)+1 种基金the Liaoning Revitalization Talents Program(XLYC2001003)the Dalian Excellent Young Science and Technology Talent Program(2023RY025).
文摘A partial-periodic model is proposed for predicting structural properties of composite laminate structures.The partial-periodic model contains periodic boundary conditions in one direction or two directions,and free boundary condition in other directions.In the present study,partial-periodic model for composite laminate beam structures is particularly studied.Three-point bending experiments for laminate beam specimens with different laying parameters are firstly used to verify the present partial-periodic model.In addition,a detailed finite element method(FEM)model is also used to further quantitatively compare with the present partial-periodic model for composite laminate beams with different laying parameters.The results indicate that the proposed partial-periodic model is capable of providing accurate predictions in most cases.The computational time cost of the proposed partial-periodic model is much lower than that of the detailed FEM model as well.Convergence studies are also conducted for the present partial-periodic model with different model sizes and element sizes.It is suggested that the proposed partial-periodic model has the potential to be used as an accurate and time-saving tool for predicting the structural properties of composite laminate beam structures.
基金Supported by National Key Research and Development Program of China(Grant No.2018YFA0707300)Major Program of National Natural Science Foundation of China(Grant No.U22A20188)+1 种基金General Program of National Natural Science Foundation of China(Grant No.51974196)Postdoctoral Science Foundation of China(Grant No.201903D421047)。
文摘The prediction of the rolling force and thickness ratio plays an important role in the development and application of bimetallic composite plates.To analyze the rolling force of the bimetallic composite plate more accurately,a novel hypothesis based on Orowan's theory was proposed.The variation in the thickness of each differential element at different positions was considered to establish the analytical model.According to the characteristics of bimetallic composite plate rolling,the rolling deformation can be divided into forward and backward slip zones.The initial thickness ratio after rolling was predetermined by the thickness ratio before rolling;the rolling force balance of the upper and lower rollers was considered the convergence condition;and the final thickness ratio of the bimetallic composite plate was obtained by iterative calculation.The calculation results of the analytical model were compared with the measured and simulated data.The results showed that the errors in the calculation of the rolling force and thickness ratio were both less than 10%.The analytical model has high precision,meets engineering requirements,and has important reference significance for rolling process optimization and thickness ratio prediction.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFB3402500)the National Natural Science Foundation of China(Grant No.12372129).
文摘Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring.However,there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fibers,and the detailed mechanism of how embedded optical fibers affect the micromechanical behavior and damage failure processes within composite materials remains unclear.This paper presents a micromechanical simulation analysis of composite materials embedded with optical fibers.By constructing representative volume elements(RVEs)with randomly distributed reinforcing fibers,the optical fiber,the matrix,and the interface phase,the micromechanical behavior and damage evolution under transverse tensile and compressive loads are explored.The study finds that the presence of embedded optical fibers significantly influences the initiation and propagation of microscopic damage within the composites.Under transverse tension,the fiber-matrix interface cracks first,followed by plastic cracking in the matrix surrounding the fibers,forming micro-cracks.Eventually,these cracks connect with the debonded areas at the fiber-matrix interface to form a dominant crack that spans the entire model.Under transverse compression,plastic cracking first occurs in the resin surrounding the optical fibers,connecting with the interface debonding areas between the optical fibers and the matrix to form two parallel shear bands.Additionally,it is observed that the strength of the interface between the optical fiber and the matrix critically affects the simulation results.The simulated damage morphologies align closely with those observed using scanning electron microscopy(SEM).These findings offer theoretical insights that can inform the design and fabrication of smart composite materials with embedded optical fiber sensors for advanced structural health monitoring.
基金Project supported by the National Natural Science Foundation of China(Nos.11972203 and 11572162)the Science and Technology Innovation 2025 Major Project of Ningbo City of China(No.2022Z209)Ningbo Key Technology Breakthrough Plan Project of“Science and Technology Innovation Yongjiang 2035”(No.2024Z256)。
文摘Carbon nanotubes(CNTs)have garnered great attention in recent years due to their outstanding electrical,thermal,and mechanical properties.The incorporation of small amounts of CNTs in polymers can substantially improve the sensitivity of the polymer's electrical conductivity.This paper presents a modified Maxwell model to evaluate the electrical conductivity of CNTs-filled polymer composites by introducing a transition zone to account for the tunneling effect.In this modified Maxwell model,the CNTs-filled polymer composite is modeled as a three-phase composite,consisting of a matrix(polymer),inclusions(CNTs),and a transition zone(tunneling zone).The effective electrical conductivity(EEC)of the composite is calculated based on the volume fractions and electrical conductivities of the matrix,inclusions,and transition zone.The model's validity is confirmed through the use of available test data,which demonstrates its capability to accurately capture the nonlinear conductivity behavior observed in CNTs-polymer composites.This study offers valuable insights into the design of high-performance conductive polymer nanocomposites,and enhances the understanding of electrical conduction mechanisms in CNT-dispersed polymer composites.
基金funded by the National Natural Science Foundation of China(Nos.22073069,21773082)Science Research Project of Hebei Education Department(No.QN2024255)。
文摘In chemical science,the vertical ionization potential(VIP)is a crucial metric for understanding the electronegativity,hardness and softness of chemical material systems as well as the electronic structure and stability of molecules.Ever since the last century,the model chemistry composite methods have witnessed tremendous developments in computing the thermodynamic properties as well as the barrier heights.However,their performance in realm of the vertical electron processes of molecular systems has been rarely explored.In this study,we for the first time benchmarked the model chemistry composite methods(e.g.,CBS-QB3,G4 and W1BD)in comparison with the commonly used Koopmans's theorem(KT),electron propagator theory(e.g.,OVGF,D2,P3 and P3+)and CCSD(T)methods in calculating the VIP for up to 613 molecular systems with available experimental measurements.The large-scale test calculations strongly showed that the CBS-QB3 model chemistry composite technique can be well recommended to calculate VIP from the perspectives of accuracy,economy and applicability.Notably,the VIP values of up to 7 molecules were identified to have the absolute errors of larger than 0.3 e V at all calculation levels,which have strong hints that their VIP experimental values should be re-investigated.
基金supported by the National Natural Science Foundation of China(Grant No.52075255)the Jiangsu Provincial Science and Technology Plan(Grant No.BZ2023005).
文摘High-volume fraction silicon particle-reinforced aluminium matrix composites(Si/Al)are increasingly applied in aerospace,radar communications,and large-scale integrated circuits because of their superior thermal conductivity,wear resistance,and low thermal expansion coefficient.However,the abrasive and adhesive wear caused by the hard silicon reinforcement and the ductile aluminium matrix leads to significant tool wear,decreased machining efficiency,and compromised surface quality.This study combines theoretical analysis and cutting experiments to investigate polycrystalline diamond(PCD)tool wear during milling of 70 vol%Si/Al composite.A key contribution of this work is the development of a tool wear model that incorporates reinforcement particle characteristics,treating them as ellipsoidal structures,which enhances the accuracy of predicting abrasive and adhesive wear mechanisms.The model is based on abrasive and adhesive wear mechanisms,and can analyze the interaction between silicon particles,aluminium matrix,and tool components,thus providing deeper insights into PCD tool wear processes.Experimental validation of the model shows a good agreement with the results,with a mean deviation of approximately 10%.The findings on the tool wear mechanism reveal that,as tool wear progresses,the proportion of abrasive wear increases from 40%in the running-in stage to 75%in the rapid wear stage,while adhesive wear decreases.The optimal machining parameters of 120 m·min^(–1) cutting speed(v_(c))and 0.04 mm·z^(–1) feed rate(f_(z)),result in tool life of 33 min and surface roughness(S_(a))of 2.2μm.The study uncovers the variation patterns of abrasive and adhesive wear during the tool wear process,and the proposed model offers a robust framework for predicting tool wear during the machining of high-volume fraction Si/Al composites.The research findings also offer key insights for optimizing tool selection and machining parameters,advancing both the theoretical understanding and practical application of PCD tool wear.
基金supported by the National Natural Science Foundation of China[51974058,52371005,52022017,51927801]the Fundamental Research Funds for the Central Universities(DUT23YG104).
文摘In this work,the microstructure evolution and mechanical behavior of extruded SiC/ZA63 Mg matrix composites are investigated via combined experimental study and three-dimensionalfinite element modelling(3D FEM)based on the actual 3D microstructure achieved by synchrotron tomography.The results show that the average grain size of composite increases from 0.57μm of 8μm-SiC/ZA63 to 8.73μm of 50μm-SiC/ZA63.The type of texture transforms from the typicalfiber texture in 8μm-SiC/ZA63 to intense basal texture in 50μm-SiC/ZA63 composite and the intensity of texture increases sharply with increase of SiC particle size.The dynamic recrystallization(DRX)mechanism is also changed with increasing SiC particle size.Experimental and simulation results verify that the strength and elongation both decrease with increase of SiC particle size.The 8μm-SiC/ZA63 composite possesses the optimal mechanical property with yield strength(YS)of 383 MPa,ultimate tensile strength(UTS)of 424 MPa and elongation of 6.3%.The outstanding mechanical property is attributed to the ultrafine grain size,high-density precipitates and dislocation,good loading transfer effect and the interface bonding between SiC and matrix,as well as the weakened basal texture.The simulation results reveal that the micro-cracks tend to initiate at the interface between SiC and matrix,and then propagate along the interface between particle and Mg matrix or at the high strain and stress regions,and further connect with other micro-cracks.The main fracture mechanism in 8μm-SiC/ZA63 composite is ductile damage of matrix and interfacial debonding.With the increase of particle size,interface strength and particle strength decrease,and interface debonding and particle rupture become the main fracture mechanism in the 30μm-and 50μm-SiC/ZA63 composites.
基金funded by National Natural Science Foundation of China(No.52305406)Basic Research Program Project in Shanxi(No.202303021212046)+2 种基金Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(No.2024Q008)Open Research Fund from National Key Laboratory of Metal Forming Technology and Heavy Equipment(No.S2308100.W15)Major Science and Technology Projects in Hebei(No.23280101Z).
文摘To address the issue of post-rolling warpage caused by differences in material properties during the composite rolling process of steel/aluminum thin strips,stress analysis was conducted at the entrance,middle,and exit sides of the rolling deformation zone for both steel and aluminum units.The unequal characteristics of the upper and lower contact arc lengths and the micromoment phenomenon,generated by the transfer of force between adjacent units on the aluminum side,were analyzed to explain the mechanical mechanism of warpage in the composite rolling process.A formula for calculating the contact arc length in the upper and lower rolling deformation zones was derived using the relationships among the contact arc length,rolling force,roll parameters,and strip parameters.On the basis of the deformation characteristics of steel and aluminum in the rolling deformation zone,the concepts of the inlet half-rolling zone,relative sliding zone,rolling composite zone,and outlet half-rolling zone were proposed.A quantitative model for characterizing warpage during the composite rolling of steel/aluminum composite thin strips was established.These results indicate that adjusting the diameters of the upper and lower work rolls is an effective method for controlling warpage defects and that warpage plays a dominant role in steel/aluminum thin strip composite rolling.Furthermore,finite element simulations of steel/aluminum composites rolled with different upper and lower roll diameters verified the deformation mechanism and influence of roll diameter differences on warpage defects.
基金supported by the National Natural Science Foundation of China with the project of No.52305158Youth Innovation Team of Shaanxi Universities(2024),Shaanxi Province Qin Chuangyuan“Scientist+Engineer”Team construction of No.2024QCY-KXJ-112,Funding from Aero Engine Cooperation of China(No.ZZCX-2022-020)the industry-university-research cooperation of Eighth Research Institute of China Aerospace Science and Technology Corporation with the project of No.USCAST2021-1.
文摘Heterogeneous composites have strong anisotropy and are prone to dynamic recrystallization during hot compression,making the me-chanical response highly nonlinear.Therefore,it is a very challenging task to intellectually judge the thermal deformation characteristics of magnesium matrix composites(MgMCs).In view of this,this paper introduces a method to accurately solve the thermoplastic deformation of composites.Firstly,a hot compression constitutive model of magnesium matrix composites based on stress softening correction was established.Secondly,the complex quasi-realistic micromechanics modeling of heterogeneous magnesium matrix composites was conducted.By introducing the recrystallization softening factor and strain parameter into the constitutive equation,the accurate prediction of the global rheological response of the composites was realized,and the accuracy of the new constitutive model was proved.Finally,the thermal pro-cessing map of magnesium matrix composites was established,and the suitable processing range was chosen.This paper has certain guiding values for the prediction of the thermodynamic response and thermal processing of magnesium matrix composites.
基金Project(51072235) supported by the National Natural Science Foundation of ChinaProject(11JJ1008) supported by the Natural Science Foundation of Hunan Province,China+2 种基金Project(20110162110044) supported by the PhD Program Foundation of Ministry of Education of ChinaProject(7433001207) supported by Hunan Provincial Innovation Foundation for Postgraduate,ChinaProject(2001JF3215) supported by Hunan Provincial Science and Technology Plan,China
文摘Piezoelectric materials are capable of actuation and sensing and have been used in a wide variety of smart devices and structures.Active fiber composite and macro fiber composite are newly developed types of piezoelectric composites,and show superior properties to monolithic piezoelectric wafer due to their distinctive structures.Numerous work has focused on the performance prediction of the composites by evaluation of structural parameters and properties of the constituent materials with analytical and numerical methods.Various applications have been explored for the piezoelectric fiber composites,including vibration and noise control,health monitoring,morphing of structures and energy harvesting,in which the composites play key role and demonstrate the necessity for further development.
文摘TiC particles reinforced Ni-based alloy composite coatings were prepared on 7005 aluminum alloy by plasma spray. The effects of load, speed and temperature on the tribological behavior and mechanisms of the composite coatings under dry friction were researched. The wear prediction model of the composite coatings was established based on the least square support vector machine (LS-SVM). The results show that the composite coatings exhibit smaller friction coefficients and wear losses than the Ni-based alloy coatings under different friction conditions. The predicting time of the LS-SVM model is only 12.93%of that of the BP-ANN model, and the predicting accuracies on friction coefficients and wear losses of the former are increased by 58.74%and 41.87%compared with the latter. The LS-SVM model can effectively predict the tribological behavior of the TiCP/Ni-base alloy composite coatings under dry friction.
基金Project(10151170003000002)supported by the National Science Foundation of Guangdong Province,China
文摘By the constant stress tensile creep test method, creep tests were performed on aluminum silicate short fiber-reinforced AZ91D magnesium matrix composite with volume fraction of 30% and its matrix alloy AZ91D under different temperatures and stresses. The results indicate that the composite and the matrix have the same true stress exponent and true activation energy for creep, which are 3 and 144.63 kJ/mol, respectively. The creep of the composite is controlled by the creep of its matrix, which is mainly the controlling of viscous slip of dislocation, and the controlling of grain boundary slippage as a supplement. The creep constitutive model obtained from the experiment data can well describe the creep deformation pattern of the composite.
基金The Special Project of the Ministry of Construction ofChina (No.20060909).
文摘In order to establish the relationship between the measured dynamic response and the health status of long-span bridges, a double-layer model updating method for steel-concrete composite beam cable-stayed bridges is proposed. Measured frequencies are selected as the first-layer reference data, and the mass of the bridge deck, the grid density, the modulus of concrete and the ballast on the side span are modified by using a manual tuning technique. Measured global positioning system （GPS） data is selected as the second-layer reference data, and the degradation of the integral structure stiffness EI of the whole bridge is taken into account for the second-layer model updating by using the finite element iteration algorithm. The Nanpu Bridge in Shanghai is taken as a case to verify the applicability of the proposed model updating method. After the first-layer model updating, the standard deviation of modal frequencies is smaller than 7%. After the second-layer model updating, the error of the deflection of the mid-span is smaller than 10%. The integral structure stiffness of the whole bridge decreases about 20%. The research results show a good agreement between the calculated response and the measured response.
文摘As an advanced composite material, the 3D braided composite has received more and more attention in foreign countries. However, it has received less attention in China. The geometric unit cell which can describe the basic structure and the relationship between the braiding angle and geometric parameters of the fabric and fiber volume ratio are given in this paper based on two 3D braiding processes, namely, the four-step and the twostep ones. Several existing mechanical models to predict groperties of the 3D braided comPOsites are discussed and their shortcomings are pointed out herein. Then a new model called the inclined laminal combination model is proposed, which is based on the classical laminated plate theory and can predict the basic mechanical behavior of the two 3D braided composites with four-step or two-step braid. In the model, each yarn in the unit cell is regarded as an inclined laminate and then a 3D analysis is performed. It is found that the predicted mechanical properties of the 3D braided composites by the proposed model are compared well with the experimental data.
基金supported by the High-Tech Research and Development Program of China (863 Program) (No.2006AA050203)
文摘Theoretical and empirical models for predicting the thermal conductivity of polymer composites were summarized since the 1920s.The effects of particle shape,filler amount,dispersion state of fillers,and interfacial thermal barrier on the thermal conductivity of filled polymer composites were investigated,and the agreement of experimental data with theoretical models in literatures was discussed.Silica with high thermal conductivity was chosen to mix with polyvinyl-acetate （EVA） copolymer to prepare SiO2/EVA co-films.Experimental data of the co-films＇ thermal conductivity were compared with some classical theoretical and empirical models.The results show that Agari＇s model,the mixed model,and the percolation model can predict well the thermal conductivity of SiO2/EVA co-films.
