ObjectiveLimited room exists for lightweight optimization and energy absorption improvement of traditional energy-absorbing buffer structures including thin-walled structures, honeycombs and foams, accompanied by insufficient structural design flexibility and working condition adaptability. Relying on metal 3D printing additive manufacturing technology, a spider-web-inspired three-dimensional truss unit cell for buffering and energy absorption was designed to enhance the specific strength, specific stiffness and specific energy absorption of structures, and optimize structural design flexibility and working condition adaptability.MethodsFirstly, initial unit cell specimens were fabricated by metal 3D printing with AlSi10Mg powder, and quasi-static compression tests were conducted to obtain basic mechanical response data. Secondly, a finite element model of the initial unit cell was established, and simulation and test results were compared to verify model reliability. Then, the collapse mode and lightweight level of the unit cell were regulated through weak link design and redundant rod optimization. Finally, a variable-stiffness stacked periodic structure was constructed, and the regulation effect of the stacking strategy on overall energy absorption performance was analyzed.ResultsThe results show that the initial unit cell presents a lateral offset mode during collapse, and the compression process is divided into four stages with a simulation error of peak load of 2.71%. The energy absorption performance of the unit cell increases nonlinearly with the rise of volume fraction. The weak link induces a torsional collapse mode via the "tree felling" effect, and the specific energy absorption is increased by 26.93%. Removing redundant rods reduces the unit cell mass by 15.42% and raises the specific energy absorption by 1.47%. The variable-stiffness stacking strategy can increase the specific energy absorption of the periodic structure by 38.43%, which can provide references for the design of buffering and energy-absorbing structures.
ObjectiveExcessive computational cost is encountered in traditional Monte Carlo simulation (MCS) method for structural reliability analysis. Poor high-dimensional fitting performance and large memory occupation under low failure probability conditions are presented in Kriging surrogate model. An active learning structural reliability analysis method combining adaptive extreme learning machine (AELM) surrogate model with MCS method was proposed.MethodsFirstly, an AELM surrogate model was constructed, and the number of hidden layer nodes and activation function were optimized to improve the generalization ability of the model. Secondly, a Bayesian framework was introduced to model the uncertainty of hidden layer weights, and the posterior distribution was calculated to estimate the prediction variance. The problem that extreme learning machine cannot directly quantify prediction uncertainty was solved. Then, a active learning function was constructed to select the sample points with the maximum uncertainty for iterative model updating. Finally, the failure probability stability criterion was adopted as the convergence condition, and the structural failure probability was calculated in combination with the MCS method.ResultsThe results show that compared with the Kriging surrogate model algorithms, the number of limit state function calls of the proposed method is reduced by up to 71.64%, and the calculation error is as low as 0.10%. The method has both higher computational efficiency and accuracy in engineering problems with multiple failure domains, strong nonlinearity and low failure probability, and provides a reference for engineering structural reliability analysis.
ObjectiveLocal cracking occurs in compacted graphite cast iron exhaust pipes during service. The failure mechanism was revealed and a collaborative optimization scheme of structure and material was proposed.MethodsFirstly, a thermal-mechanical coupling finite element model of the exhaust pipe was established, and the distribution characteristics of its temperature field, stress field and strain field were analyzed to support the failure cause location and mechanism analysis. Secondly, structural improvement schemes of increasing the transition fillet radius and eliminating redundant stiffeners were proposed, and modal analysis was carried out to verify the dynamic characteristics of the optimized structure and eliminate the risk of resonance failure. Then, Taguchi test design method was adopted to quantitatively analyze the influence law of structural and material parameters such as wall thickness and elastic modulus on low-cycle fatigue life. Finally, a multi-objective evaluation system based on entropy weight-analytic hierarchy process was constructed to comprehensively balance high-temperature mechanical properties, process feasibility and economic indicators, and realize multi-dimensional optimization of material schemes.ResultsThe results show that increasing the transition fillet can reduce the stress in the crack area by 119 MPa, and removing the stiffeners can eliminate local stress concentration. The resonance margin ratio after structural optimization reaches 152%, which meets the requirements of ISO 10816-1 standard. The coefficient of thermal expansion has the most significant influence on fatigue life, with a response range of 680 cycles. After combined weighting optimization, compacted graphite cast iron with niobium addition mass fraction of 0.05%-0.07% is determined as the optimal material scheme, which provides reference for the optimal design of similar high-temperature pressure-bearing components.
ObjectiveCorrosive environments significantly degrade the load-bearing capacity of honeycomb structures and may even induce structural instability. Investigating this influence is of great importance for engineering applications.MethodsFirstly, quasi-static compression tests were conducted to compare and analyze the variation patterns of load-bearing capacity for regular hexagonal and square honeycomb structures before and after corrosion, aiming to clarify the differential effects of corrosion on the performance degradation of the two cellular configurations. Secondly, finite element models of both structures were established, and the accuracy of the numerical models was validated through comparison of load-displacement curves. Then, based on the validated numerical models, simulation calculations were performed on regular hexagonal honeycomb structures with different porosities to analyze the effect of porosity on structural strength. Finally, different corrosion degrees were simulated by varying local wall thicknesses, and the degradation patterns of the load-bearing capacity of honeycomb structures in corrosive environments were systematically investigated.ResultsThe results show that regular hexagonal honeycomb structures exhibit better stability than square ones. Corrosion has a relatively minor effect on the load-bearing capacity of hexagonal honeycombs, with reductions of 4.58% and 20.53% after 5 and 20 corrosion cycles, respectively, while the corresponding reductions for square honeycombs reach 13.29% and 25.88%. As porosity increases from 70% to 80%, the stress concentration at the structural bottom intensifies and the structural strength decreases.
ObjectiveThe bending strength of tooth roots of harmonic reducer flexsplines can be enhanced by fine particle peening. However, the influence laws of shot peening air pressure and coverage on flexspline surface properties have not been clarified due to the high cost of fine particle peening tests. Systematic investigations on parameter effects were conducted by combining numerical simulation and test methods.MethodsFirstly, a random multi-shot elastoplastic fine particle peening simulation model was constructed via the coupling of finite element method and discrete element method to reproduce the real working condition of continuous multi-shot impact. Secondly, a single-tooth model with local refined grids of the flexspline was established by SolidWorks software and Abaqus software to provide a high-precision calculation carrier for micron-scale peening simulation. Then, multiple groups of fine particle peening tests with controlled parameters were carried out, and residual stress and surface roughness were measured by a micro-area stress tester and a roughness profiler. Finally, simulation and test data were compared, and the influence laws of two types of process parameters on surface properties were quantitatively analyzed.ResultsThe results show that the simulation results are in good agreement with the test results, with a maximum error of 11.36%. The maximum residual compressive stress, its peak depth and the depth of residual compressive stress layer all increase with the rise of shot peening air pressure, and the compressive stress layer depth reaches 70 μm at 0.6 MPa air pressure. The surface residual compressive stress and maximum residual compressive stress increase with the improvement of shot peening coverage, while the stress layer depth shows no significant change. All roughness parameters increase obviously with the rise of air pressure, while the influence of coverage is weak with low growth amplitude of the arithmetic mean deviation of roughness profile. References for the optimization of flexspline peening processes can be provided.
ObjectiveAiming at the problems that the mobile charging vehicle frame has remarkable heavy-load characteristics and variable loads under multiple working conditions, and the traditional multi-objective genetic algorithm (MOGA) has insufficient global optimization ability and is prone to fall into local optimum, to solve the collaborative optimization problem of frame lightweight design and dynamic-static performance improvement, a multi-objective optimization method for vehicle frames based on an improved multi-objective genetic algorithm was proposed.MethodsFirstly, load information of key bearing parts of the frame was obtained through multi-condition real vehicle tests, and an implicit parametric finite element model of the frame was established to complete dynamic-static performance analysis and clarify structural response characteristics. Secondly, optimal Latin hypercube sampling was adopted to obtain sample points, and a high-precision proxy model was constructed to quantify the influence law of design variables on frame stress and mass. Then, an adaptive crossover strategy pool was introduced into the traditional multi-objective genetic algorithm to improve the global search ability of the algorithm, and a mathematical model for multi-objective optimization of the frame was established. Finally, the entropy-technique for order preference by similarity to ideal solution (TOPSIS) method was used to select the optimal scheme from the Pareto solution set, and the performance verification of the optimized scheme was completed.ResultsThe results show that the improved multi-objective genetic algorithm has significantly better convergence and global optimization ability; the mass of the optimized frame is reduced by 9.44%, the maximum stress and maximum displacement under four typical working conditions are decreased, and the first-order natural frequency is increased to 92.247 Hz. The dynamic and static performance of the frame is improved while lightweight is realized, which provides reference for the optimization design of similar bearing structures.
ObjectiveThe reliability problem of metal-to-metal sealing for plug valves under high-temperature and high-pressure conditions in deep oil and gas extraction remains to be solved. The influence laws of key geometric dimensions of arc segments and plugs on sealing performance were investigated, so as to provide reference for high-reliability design of plug valves.MethodsFirstly, a finite element simulation method based on pressure penetration mechanism was adopted, a pressure criterion related to surface roughness was established, and the penetration process of medium along the contact interface was dynamically simulated to realize analysis of sealing behavior under multi-factor coupling. Secondly, five sets of assembly models with different outer arc diameters were constructed, and contact characteristic calculations under multiple pressure levels were performed to clarify the influence of outer arc dimension on sealing band formation and contact pressure distribution. Then, with the optimal outer arc dimension fixed, five sets of models with different inner arc diameters were established, and the influence mechanism of inner arc dimension and assembly clearance on sealing performance was analyzed. Finally, multiple sets of dimension samples were fabricated and high-pressure sealing tests were conducted to verify the reliability of simulation conclusions.ResultsThe results show that when the outer arc diameter is 145.35 mm, a continuous and effective sealing band can be formed in the plug valve over the full pressure range of 5 000 psi-15 000 psi, with optimal comprehensive sealing performance and a distinct optimal size range. The inner arc diameter exhibits an approximately linear negative correlation with sealing performance. When the inner arc diameter is 126.01 mm, the assembly clearance reaches the minimum, the contact pressure distribution is more uniform, the sealing band width increases significantly, and the sealing reliability is effectively improved.
ObjectiveConventional force analysis methods for the horizontal arm of double flat-arm derricks fail to consider the influence of tensile elongation of tie rods on mechanical performance and neglect the additional bending moments induced by axial eccentric loads, resulting in insufficient calculation accuracy. To address these issues, an improved analytical method based on the three-moment equation with elastic supports was proposed.MethodsFirstly, the two-suspension-point horizontal arm of a double flat-arm derrick was taken as the research object, and the tensile elongation effect of tie rods was equivalently treated as elastic supports, from which the three-moment equation applicable to axially eccentric two-suspension-point structures was derived. Secondly, a mechanical model of the axially eccentric two-suspension-point horizontal arm was established, and the axial forces of the two tie rods under both elastic and rigid supports were calculated separately. Then, a finite element model was established using ANSYS software for simulation verification. Finally, the theoretically calculated results were compared with the finite element results.ResultsThe results show that the axial forces of tie rods calculated by the three-moment equation with elastic supports are in better agreement with finite element simulation data compared with those obtained using rigid supports, with the maximum relative error reduced from 89.52% under rigid supports to 8.05% under elastic supports. The correction effect of elastic supports becomes more significant with larger lifting loads and smaller tie rod cross-sectional areas, and the influence of tie rod elongation on axial force calculation results cannot be neglected. The proposed method can effectively improve the calculation accuracy and safety of horizontal arm design, and provides a reference for structural analysis of horizontal arms in similar lifting equipment.
ObjectiveTo address the problems of insufficient consideration of uncertain factors and low design accuracy in the traditional design of gantry crane main girders, research on lightweight design and multi-objective reliability optimization of main girder webs was conducted to improve the rationality and safety of structural design for heavy lifting equipment.MethodsFirstly, a parametric finite element model of web thickness was established with SolidWorks software and Ansys software for a gantry crane main girder with a span of 10 m and a load capacity of 800 t, which provided numerical support for optimization analysis. Secondly, an implicit limit state function of the structure was constructed by combining the Latin hypercube sampling method and back propagation (BP) neural network technology, and the structural reliability index was calculated using the Monte Carlo simulation method. Thirdly, multi-objective reliability design optimization was carried out with the non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ), taking the minimum main girder mass, minimum maximum total deformation and maximum reliability index as optimization objectives. Finally, the simulation accuracy of the finite element model was verified through a scaled model lifting test and acoustic emission sensing detection.ResultsThe results show that 70 groups of Pareto optimal solution sets are obtained through multi-objective optimization. For the comprehensively selected optimal scheme, the mass of the main girder structure is reduced by 24.56% and the structural reliability is improved by 9.7% under the premise that deformation and stress meet safety requirements. An efficient reliability optimization system for main girders can be constructed with the proposed method, and reference can be provided for the structural safety design of heavy lifting equipment.
ObjectiveThe connection performance of shape memory alloy pipe joints and its key influencing factors were investigated, and the action mechanism of various parameters on connection strength was clarified.MethodsFirstly, shape memory alloy, an assembly mechanical model was established by combining the ideal elastoplastic model and the maximum shear stress yield criterion, and analytical solutions were derived to provide a benchmark for simulation verification. Secondly, the Boyd-Lagoudas constitutive model was introduced via the UMAT user subroutine of Abaqus software, and a full-scale finite element model was constructed to complete the mechanical simulation of the assembly process. Then, a pull-out analysis step was defined, and the axial pull-out force was adopted as the core index to quantify the connection performance. Finally, parametric analysis was performed to investigate the influence laws of geometric dimensions, operating temperature and critical transformation strain.ResultsThe results show that the errors between the simulated start and end phase transformation stresses during diameter expansion and the analytical solutions are 2.11% and 0.96% respectively, and the contact stress error ranges from 4.6% to 10.2%, indicating favorable simulation accuracy. The increase of wall thickness, interference fit and pipe length of the joint all improves the axial pull-out force, among which the pipe length enhances the pull-out performance by expanding the contact area. The larger the critical transformation strain, the greater the recoverable deformation and the better the connection performance. The influence of operating temperature on pull-out force is negligible within the range of 278 K to 318 K. The results provide reference for the engineering application of shape memory alloy pipe joints.
ObjectiveTo enhance the fatigue life of high-power fracturing pump hydraulic cylinders under ultra-high alternating pulse loads, a quantitative correlation analysis method between autofrettage residual stress and hydraulic cylinder fatigue life was established based on the thick-walled cylinder autofrettage mechanism.MethodsFirstly, six pressure levels of autofrettage process parameters were designed by taking the minimum allowable maximum autofrettage pressure, and a three-dimensional model of the 5 000 HP type fracturing pump hydraulic cylinder was established to provide a geometric basis for subsequent finite element simulation analysis. Secondly, a finite element model of the hydraulic cylinder was developed, and the distribution patterns of residual stress under different autofrettage pressures and the superposition effects of working loads were simulated by combining Ansys software and Miner’s linear cumulative damage rule, with the fatigue life safety factor calculated accordingly. Then, the residual stress and superimposed stress were measured using X-ray diffraction method and strain gauge method, respectively, to verify the effectiveness of the simulation results. Finally, the fatigue life of the hydraulic cylinder before and after autofrettage treatment was compared through field fracturing operation tests.ResultsThe results show that the optimal autofrettage performance is achieved at an autofrettage pressure of 430 MPa. The simulated residual compressive stress on the inner wall of the hydraulic cylinder reaches 723 MPa, the maximum combined stress on the inner wall under working conditions is reduced by 51%, and the fatigue life safety factor is increased to 2.05 times that before autofrettage. The optimal residual stress measured in the test is 732.1 MPa, and the optimal superimposed working stress is 335.5 MPa. The field operation tests verify that the fatigue life of the hydraulic cylinder after autofrettage treatment is extended by 2.4 times compared with that of the untreated one.
[Objective]To address the insufficient bottom impact resistance of electric vehicle power battery boxes against road debris,a sandwich structure with negative Poisson ratio(NPR)was proposed to enhance the protective performance of the battery pack bottom while satisfying lightweight design requirements.[Methods]Firstly,a finite element model of the battery pack system under typical ground impact conditions was established using HyperMesh software and Ls-Dyna software,and the compression variation curves of battery cells were obtained to verify the reliability of the simulation model.Secondly,the concave arc NPR structure was adopted as the core layer of the sandwich panel.With the thicknesses of the bottom plate,top plate,and core plate,together with the cell length and concave arc radius,as design variables,and the specific energy absorption and battery axial compression as optimization objectives,multi-objective optimization was conducted based on the optimal Latin hypercube design,Kriging surrogate model,and non-dominated sorting genetic algorithm Ⅱ,so as to establish the mapping relationship between structural parameters and protective performance.Finally,the satisfaction function was employed to select the optimal combination of structural parameters from the Pareto optimal solution set,and the reliability of the optimization results was verified through simulation.[Results]The results show that,compared with the homogeneous aluminum alloy protective plate,the optimized NPR sandwich structure achieves an increase in specific energy absorption from 123.69 J/kg to 141.95 J/kg,representing an improvement of 14.76％;the mass of the protective structure is reduced by 13.38％;and the maximum axial compression of the battery decreases from 3.15 mm to 1.12 mm,with the protective effect parameter reaching 64.44％.The optimization scheme can effectively reduce the risk of thermal runaway of the battery box under impact,and can provide a reference for the impact-resistant structural design of power battery box bottoms.
ObjectiveMulti-scale parameter uncertainties are involved in the design of carbon fiber reinforced polymer (CFRP) control arms. Macro-scale layup optimization is mostly adopted in existing researches, which can hardly balance material micro-property fluctuation and macro structural reliability. To fully exploit the mechanical properties of CFRP, a reliability design scheme with synergistic macro and micro parameters was proposed for CFRP control arms.MethodsFirstly, the mechanical properties of unidirectional CFRP were predicted by Digimat software, and the prediction accuracy was verified through tensile tests to provide data support for cross-scale parameter transfer. Secondly, structural replacement of the CFRP control arm was completed based on the equal stiffness principle, and a finite element analysis model was constructed to provide a calculation carrier for reliability evaluation. Then, a double-weighted vector-projection response surface method was proposed, and reliability analysis of the control arm under multi-scale uncertain parameters was realized combined with a polynomial surrogate model to balance calculation accuracy and efficiency. Finally, a multi-scale reliability optimization framework was established and solved by integrating the surrogate model, improved response surface method and particle swarm optimization algorithm.ResultsThe results show that the reliability calculation error of the double-weighted vector-projection response surface method is less than 0.9% compared with the Monte Carlo method. The optimized CFRP control arm achieves a weight reduction of 41.29% compared with the original steel structure under the constraints of 90% reliability and performance requirements, which can provide references for lightweight reliability design of composite automotive structural parts.
ObjectiveTo address the numerical instability and insufficient optimization performance of the variable density method in continuum structural topology optimization, an improved strategy based on a modified interpolation model and a grayscale suppression operator was proposed to obtain ideal optimized structures with clear boundaries and fully discrete configurations.MethodsFirstly, an exponential improved interpolation model was constructed to overcome the limitations of the solid isotropic material with penalization model and the rational approximation material properties model in penalty efficiency and convergence speed, thereby enhancing the driving force for element densities to polarize toward 0 or 1 and providing support for subsequent optimization solving. Secondly, the Sigmund sensitivity filtering method was employed to eliminate checkerboard patterns and mesh dependency, ensuring the numerical stability of the optimized structures. Finally, a grayscale suppression operator was designed and integrated into the optimality criterion method to accelerate the transformation of grayscale elements toward solid or void states.ResultsThe results show that the proposed strategy achieves significant improvements in cantilever beam, double‑load cantilever beam, and L‑shaped beam examples under various load and constraint conditions. Compared with the control method, the iteration counts are reduced by 13, 5, and 82, respectively, while the structural compliances are decreased by 1.874, 2.943, and 16.948. Both the discreteness measure and the grayscale ratio are reduced to 0, yielding fully discrete, boundary‑clear optimized structures devoid of grayscale elements, which verifies the superiority of the proposed strategy in convergence speed and solution quality.
ObjectiveLarge calculation scale and slow convergence speed exist in structural stress topology optimization. Considering the computational requirements of large-scale finite element analysis, the multigrid preconditioned conjugate gradient (MGCG) method was adopted to reduce the solution cost and improve the computational efficiency of stress-constrained topology optimization.MethodsFirstly, based on the framework of the solid isotropic material with penalization method, a topology optimization model with dual constraints of stress and compliance was constructed with structure volume minimization as the optimization objective. The P-mean function was used to relax local stress constraints into global stress constraints, providing mathematical support for the optimization solution. Secondly, starting from the adjoint sensitivity of the global stress measurement, the element-level sensitivity calculation formula was derived to improve the efficiency of sensitivity analysis. Then, the MGCG method was applied to accelerate the solution of finite element linear equations. The approximate inverse preconditioner of the stiffness matrix was constructed using the V-cycle strategy and damped Jacobi smoother to accelerate the convergence of the iterative solver. Finally, combined with density filtering and Heaviside projection to eliminate gray elements and checkerboard effect, the method of moving asymptotes was used to update design variables, forming a complete optimization process.ResultsThe results show that the MGCG method can significantly accelerate the iterative convergence process of topology optimization. On the premise that the optimized structure meets the constraints of stress and compliance, the total calculation time is reduced by 11.1%-18.2% compared with the traditional variable density method. When the penalty coefficient of the P-mean function is set to 50, the stress concentration can be effectively alleviated, and the stress concentration factor is reduced by 41.87%. Meanwhile, a 0-1 binary topology configuration with clear boundaries can be obtained, which provides reference for the efficient solution of similar stress topology optimization problems.
ObjectiveAt present, there is no targeted static stiffness calculation method for bushing-type rubber suspensions of tracked vehicles under combined deformation conditions. A static stiffness calculation method applicable to multiple bushing configurations was proposed to provide reference for the initial design and stiffness matching of rubber suspensions.MethodsFirstly, based on the linear elastic mechanical analysis method, the effects of radial, tilting and torsional deformations of axisymmetric rubber bushings on suspension travel were analyzed, and calculation formulas for the balance elbow rotation angle and road wheel vertical displacement were derived to support stiffness calculation. Secondly, combined with the cross-sectional characteristics of axisymmetric and non-axisymmetric rubber bushings, vertical deformation compensation and rotation angle correction coefficient were introduced, and calculation methods for the static vertical stiffness and static torsional stiffness of the suspension under combined deformation were established. Then, finite element models of the bushings were established using Ansys/Workbench software, and static mechanical simulation analysis was performed to verify the accuracy of deformation calculation. Finally, a loading test bench for rubber suspensions was constructed, and the engineering applicability of the stiffness calculation method was verified through quasi-static loading tests.ResultsThe results show that the force and deformation law of the rubber bushing is consistent with the simulation and test results. The errors between the calculated values and test values of the static vertical stiffness and static torsional stiffness are 9.43% and 5.71% respectively, both within the 10% allowable engineering error range, which can satisfy the engineering requirements of preliminary suspension design.
ObjectiveAiming at the problem that traditional dynamic Bayesian networks cannot intuitively characterize the event correlation between nodes via conditional probability tables, and the deficiency that existing studies mostly focus on component-level analysis and ignore the dynamic failure effect of system redundancy design, a dynamic reliability analysis method adapted to electric multipe unit (EMU) traction drive systems was proposed.MethodsFirstly, the improved continuous-time dynamic Bayesian network rules were constructed, and the calculation methods of reliability, posterior probability and importance based on the rule execution degree of node timing conditional probability table and impulse function were proposed to clarify the logical correlation of events between nodes. Secondly, based on the failure mechanism of the CRH3 EMU traction drive system, a dynamic Bayesian network model of the system was established to clarify the hierarchical failure logic. Then, the fuzzy set method and extension principle were adopted to process historical fault data, and the fuzzy interval of component failure rate was obtained to characterize data uncertainty. Finally, multi-dimensional reliability analysis was carried out to realize the identification of system weak links.ResultsThe results show that compared with the traditional dynamic Bayesian network method, the maximum improvement of the proposed method in reliability and accuracy reaches 0.031104. The system reliability decreases continuously with the increase of running time, and approaches 0 at about 2 000 h. Four types of core weak components are identified, which provides reference for structural optimization and fault diagnosis of traction drive systems.
ObjectiveA hierarchical optimization design method for impact resistance of isosceles triangular honeycomb structures was established to provide a reference for lightweight design of spacecraft impact buffering devices.MethodsFirstly, a numerical simulation model was built using Abaqus software, and the mechanical properties including relative density and plateau stress of isosceles triangular honeycomb structures under in-plane impact were analyzed, with the model reliability verified by comparison with literature results. Secondly, based on the Isight software platform, a multi-objective genetic algorithm was adopted to optimize macroscopic size parameters including cell base length, cell height, and wall thicknesses in different regions, with the objectives of minimizing structural mass and peak load. Then, for the optimal configuration obtained from macroscopic optimization, a symmetric cross-section was selected to establish a plane-strain model, and detailed optimization of the fillet radius at cell junctions was further carried out. Finally, the effectiveness of the hierarchical optimization strategy was evaluated by comparing the reaction force-time histories and deformation modes of honeycomb structures before and after optimization.ResultsThe results show that after macroscopic optimization, the structural mass is reduced by 73% (at 5 m/s) and 83% (at 35 m/s) under different impact velocities; after detailed fillet optimization, the peak reaction force is reduced by 31%.
ObjectiveThe contact stress and frictional heat generation between the cycloidal gear and pin teeth critically influence the transmission performance and service life. Current research on profile modification optimization mostly focuses on a single objective, lacking comprehensive consideration of thermo-mechanical coupling effects. To address this issue, a multi-objective optimization method for cycloidal gear tooth profile modification was proposed considering frictional heat conditions, aiming to simultaneously reduce the maximum contact stress and frictional heat flux density on the tooth surface, and to improve the temperature distribution.MethodsFirstly, a theoretical load contact analysis model was established according to the meshing characteristics of cycloidal planetary transmission, providing a mechanical calculation foundation for subsequent optimization. Secondly, the tooth surface was discretized and the frictional heat flux density calculation was introduced, and an optimization function was constructed with the objectives of minimizing the maximum contact stress and the sum of heat flux density. Then, a genetic algorithm program was coded using Matlab software, the range of modification parameters and constraint conditions were set, and a multi-objective optimization model for tooth profile modification was established, with feasibility judgment and penalty mechanisms added to address iteration non-convergence and abnormal results. Finally, the temperature fields of the tooth surface before and after optimization were compared through finite element simulation, and the optimization effect was evaluated in combination with theoretical calculation of meshing efficiency.ResultsThe results show that after multi-objective optimization, the maximum contact stress on the tooth surface is slightly reduced, and the total heat flux density on the tooth surface is significantly decreased. The simulation results show that the maximum tooth surface temperature is reduced by 5.346 ℃ and the area of temperature concentration is notably diminished. Meanwhile, the meshing power loss is decreased, and the meshing efficiency is improved by 1.5 percentage points.
ObjectiveTo accurately describe the nonlinear damage evolution behavior of epoxy resin under various loading conditions, an improved Lemaitre damage model incorporating the influence of elastoplastic strain energy on damage was used,, aiming to enhance the prediction accuracy of mechanical responses of epoxy resin structures under long-term service environments.MethodsFirstly, uniaxial tensile, compressive, and shear tests, along with corresponding loading-unloading cyclic tests, were conducted on YH69 epoxy resin specimens, and the damage parameters of the model were determined based on the elastic modulus variation method. Secondly, a UMAT user-defined material subroutine based on the improved Lemaitre constitutive model was developed on the Abaqus software platform. Then, numerical simulations of damage evolution in epoxy resin were performed under different loading conditions. Finally, the predicted results of the improved model were compared with those of the traditional Lemaitre model and the experimental data.ResultsThe results indicate that the improved Lemaitre damage model can effectively characterize the entire damage evolution process of epoxy resin under tensile, compressive, and shear loads, and its predicted stress-strain curves and force-displacement curves show higher fitting accuracy and better agreement with experimental data compared with the traditional Lemaitre model. The critical damage values for tension, compression, and shear are determined as 0.28, 0.25, and 0.27, respectively, with corresponding critical damage strain energy release rates of 3.4, 6.7, and 3.1.
