323 results about "Element modeling" patented technology

The invention belongs to the technical field of nerve regulation and control, and discloses a portable noninvasive brain deep electrical stimulation system based on time interference, and the system comprises an electroencephalogram signal collection unit which is used for obtaining an electroencephalogram signal in a high-quality resting state, and carrying out the signal preprocessing and feature extraction, thereby obtaining an optimal stimulation envelope frequency; the personalized finite element modeling unit is used for constructing a head personalized model and outputting optimal electrode configuration and stimulation parameters for a target brain region target spot; the electrode positioning and stimulation execution unit is used for realizing accurate positioning of an electrode position and implementing time interference electrical stimulation; the MCU unit is used for realizing data management, task scheduling and remote communication; the human-computer interaction unit is used for realizing visual treatment flow and parameter setting; and the power supply management unit provides stable working voltage for the system. According to the invention, the portable, intelligent and personalized modeling of the electrical stimulation treatment equipment is realized, and the precision and efficiency of nerve regulation and control are remarkably improved.

The invention provides a finite element-based method for estimating pulling-out ultimate bearing capacity of a grouting screw anchor in gravelly soil, and relates to the technical field of civil structure engineering.A three-dimensional finite element model containing the grouting screw anchor and surrounding gravelly soil is established, model parameters cover the structure and material characteristics of the grouting screw anchor, and the grouting screw anchor and the surrounding gravelly soil are subjected to finite element modeling; a coordinate axis is established with the center of the anchor bottom as an original point for grid division, a stress concentration area is analyzed, principal stress is calculated to serve as critical bearing stress, vertical pull-out loads are applied step by step through a grouting pull-out test, a pull-out stress influence area is determined, soil stress of the area is analyzed, and soil binding power and friction force are calculated. And a grouting coefficient and a rock crack coefficient are generated, soil parameters are corrected, and the ultimate pulling bearing capacity of the grouting screw anchor is comprehensively obtained. According to the method, the pulling ultimate bearing capacity of the grouting screw anchor is accurately evaluated by establishing the three-dimensional finite element model and the graded loading experiment.

The invention provides a non-intrusive diagnosis method for typical rotor faults of a synchronous phase modifier, and the method comprises the steps: carrying out finite element modeling and fault working condition setting, carrying out simulation to obtain magnetic field distribution data under each working condition, carrying out the extraction and feature analysis of stray magnetic field signals, extracting time domain and frequency domain signals of a stray magnetic field under healthy and various fault working conditions, and carrying out the diagnosis of the typical rotor faults of the synchronous phase modifier. Fundamental wave, odd-even harmonic components and signal change trends are compared and analyzed, stray magnetic field characteristics corresponding to faults are extracted and recognized, diagnosis criterion establishment and fault recognition are carried out, diagnosis criteria and threshold values of rotor turn-to-turn short circuit, dynamic eccentricity and shaft-diameter composite eccentricity faults are established according to the stray magnetic field characteristics, and the fault diagnosis accuracy is improved. And when the specific harmonic amplitude or change characteristic of the stray magnetic field signal exceeds the criterion threshold, determining the rotor fault of the corresponding type and degree. Equipment dismounting or structure reconstruction is not needed, the detection system is simple in structure, internal fault characteristics of the phase modifier can be reflected in real time, and high sensitivity and practicability are achieved.

The invention discloses a tire finite element modeling and multidirectional rigidity optimization method and system based on characteristic lines. The method comprises the following steps: extracting tire section characteristic lines from a three-dimensional digital model; introducing the tire section characteristic line into a finite element analysis environment, generating a three-dimensional tire geometric model by rotationally scanning the characteristic line, and performing grid division on the model; setting tire material attributes, performing zoning setting on the model according to a tire crown, a tire shoulder and a tire side wall, and setting tire thickness based on zoning; applying a constraint boundary condition at the center of the tire, and establishing a contact form of the tread and the ground; a progressive inflation pressure load is applied, the deformation state of the inflated tire is calculated, and longitudinal rigidity, radial rigidity and lateral rigidity calculation and analysis steps are set; the tire elasticity modulus and the cord fabric thickness are used as design variables, and an optimization algorithm is adopted to solve a multi-objective optimization function. The method has the advantages of being simple in modeling method and high in practical operability, the tire modeling threshold can be lowered, and the fund and time cost of refined modeling is reduced.

The invention provides a steel bridge automatic finite element modeling method fusing three-dimensional point cloud and intelligent graph recognition, and the method comprises a bridge key construction external information automatic extraction method based on a point cloud model, and the method comprises the steps: carrying out the principal component analysis and transformation of a bridge point cloud principal axis; and secondly, carrying out secondary segmentation on the bridge structural member by using an adaptive threshold algorithm and a region growing RANSAC algorithm, and finally, realizing information extraction of a key carrier surface through a minimization loss function and parameterization expression, and accurately extracting external key parameters. On the other hand, a structure internal information extraction method based on deep learning and drawings is provided. According to the method, geometric dimension measurement and automatic finite element modeling can be automatically completed, reliable digital twin model support is provided for bridge safety assessment, and the method has high engineering application value.

The invention belongs to the field of laser processing and numerical simulation, and particularly relates to a finite element modeling and analysis method for a nanosecond pulse laser target material. The method comprises the following steps: establishing and loading a laser heat source model; establishing a target material finite element model and carrying out grid division; establishing and solving a transient heat conduction equation; carrying out multi-cycle iterative solution and post-processing; and performing model verification and parameter analysis. According to the method, the laser heat source model is established, the adaptive grid encryption strategy for temperature gradient optimization is adopted, and the transient solution algorithm is combined, so that compared with a traditional simplified analysis model or general commercial software simulation, the prediction precision of the target material temperature field spatio-temporal evolution law under the nanosecond pulse laser effect is remarkably improved. The method can accurately predict the temperature distribution and evolution law of the target material under the action of laser, has the advantages of high modeling precision, good calculation efficiency, wide application range and the like, and is suitable for engineering applications such as laser processing and damage evaluation of optical materials and composite materials.

The invention discloses a solid rocket engine bearing structure lightweight determination method based on a carbon fiber composite material, and relates to the technical field of composite material structure design, and the method comprises the steps: obtaining the structure size and geometric shape of a fixed body; replacing a titanium alloy material with a carbon fiber composite material, and determining a carbon fiber composite material structure response model based on a finite element modeling method; determining an optimal layering scheme based on structural response sensitivity analysis and a multi-objective optimization method; then determining a thickness optimization scheme based on the structural size and geometric shape of the fixed body and load distribution; determining a reinforcement optimization scheme based on a parametric modeling method; determining a metal reinforcement configuration by adopting a structural rigidity-quality collaborative evaluation method; and finally, determining a lightweight structure of the fixed body based on a composite material layering process design method. The mass of the fixing body structure can be reduced, the mechanical property of the fixing body structure is improved, and the high-performance design requirement of a solid rocket engine is met.

The invention discloses a method and device for predicting abrasive particle impact damage on the surface of a carbon fiber plate, relates to the field of aerospace material performance research, and can solve the problem that the evolution process of damage to the carbon fiber plate caused by micro-scale abrasive material impact cannot be directly observed and obtained in real time at the present stage, and the method comprises the steps that a gas-solid two-phase flow field model in a nozzle is established; setting a discrete phase injection source in CFD simulation software, and determining abrasive particle motion data according to the gas-solid two-phase flow field model in the nozzle after grid division; establishing a three-dimensional model of the abrasive particles in finite element modeling simulation software and carrying out grid division; a carbon fiber plate model is established in explicit dynamics simulation software, the abrasive particle three-dimensional model obtained after grid division is imported into the carbon fiber plate model, the initial impact speed of the abrasive particles on the carbon fiber plate model is set according to abrasive particle motion data obtained through calculation of CFD software, and the damage result of the carbon fiber plate is determined through impact simulation calculation of the abrasive particles on the carbon fiber plate. The method is used for simulating and predicting the damage caused by impact of the microscale abrasive on the carbon fiber plate.

The invention discloses a turbine disc baffle structure optimization method and device, equipment, a medium and a product and relates to the field of turbine rotors, and the method comprises the steps that actual structure information of a turbine disc-baffle rotor system is obtained; performing finite element modeling on the actual structure information to obtain a finite element model; transient thermal analysis and transient stress analysis are sequentially carried out according to the finite element model, and the most dangerous time step where the maximum equivalent stress and the maximum contact stress are located is obtained; establishing a response surface model based on a Kriging model according to the most dangerous time step where the maximum equivalent stress and the maximum contact stress are located and actual structure information; according to the response surface model, a multi-target genetic algorithm is used for optimization, and optimized turbine disc baffle structure information is obtained. Stress concentration is effectively reduced, and the fatigue life is prolonged.

The invention relates to the field of oil and gas reservoir drilling, and provides a borehole wall stability analysis method for a deepwater shallow long horizontal well, which comprises the following steps: carrying out mechanical parameter test on a weakly cemented rock sample to obtain basic mechanical characteristic parameters; performing time-varying strength modeling on the weak cementation constitutive structure to obtain a damage evolution model; performing three-dimensional finite element modeling on the stratum around the borehole to obtain a numerical calculation model; establishing a control equation set, and discretely solving the control equation set through the numerical calculation model to obtain a field variable solving result; and well wall stability analysis is carried out based on the field variable solving result, and an analysis result is obtained. According to the method, the well wall stability prediction precision of the deep-water shallow-layer long horizontal well is improved, and the safety of well drilling is improved.

The invention relates to the technical field of electronic device assembly, and discloses a heat-conducting colloid evaluation method, device and equipment, a storage medium and a program product, and the method comprises the steps: carrying out the finite element modeling of a target heat-conducting colloid after the target heat-conducting colloid is determined, and obtaining an assembly model of the target heat-conducting colloid; performing finite element analysis on the assembly model based on a preset working condition to obtain an assembly response of the target heat-conducting colloid; and determining whether the target heat-conducting colloid meets a preset design requirement or not according to the assembly response. By performing finite element simulation analysis on the heat-conducting colloid, whether the uniformity design of the heat-conducting colloid is reasonable or not can be quickly, efficiently, accurately and reliably determined in the initial stage of design, and adjustment is performed in time when the uniformity design is unreasonable, so that the optimal scheme is selected during assembly, the quality problem of later test verification is avoided, and the production efficiency is improved. And the problems of over-high temperature and serious thermal failure caused by non-uniform distribution of the heat-conducting colloid due to deformation of the heat-conducting colloid are effectively solved.

This invention discloses a rapid modeling method for large-size composite structures with variable thickness solid meshes based on a yarn model, belonging to the field of finite element modeling of fiber-reinforced composite materials. Its core process includes: for a large-size component S to be analyzed, generating yarn models for each ply partition using composite material design software and batch-dividing triangular meshes; similarly, extracting smooth surface profiles from the three-dimensional geometry of the overall component S and generating a structured shell mesh as the base carrier; then, using a voxel hash-accelerated spatial Boolean intersection algorithm to automatically identify the element sets of each ply partition between each yarn mesh and the overall shell mesh, generating a stepped solid mesh through normal offset, ensuring interface compatibility through node merging, and finally assigning material properties and generating an analysis model that can be directly submitted for solution. This invention significantly reduces manual workload and error risk, providing an efficient and reliable preprocessing solution for the curing deformation and strength analysis of composite material structures.

The invention provides a multi-scale finite element modeling and optimizing method for progressive compression sock design, belongs to the field of medical textile and finite element simulation, and is used for solving the problems of weak multi-scale coupling, one-sided data input, poor scene adaptation and difficulty in small sample modeling in related technologies. According to the method, a macroscopic-mesoscopic-microscopic multi-scale finite element model is constructed, dynamic mechanical and multi-modal data are collected and preprocessed, mechanical-blood flow-thermal-wet multi-physics field coupling simulation is carried out, key parameters are optimized in combination with reinforcement learning, group knowledge and closed-loop feedback, and finally compressed sock design parameters are output. Accurate design of compressed socks can be achieved, and scene adaptability and small sample adaptability are improved.

The invention discloses an anti-seismic property analysis method for a complex high-rise structure. The method comprises the following steps: determining a boundary range of a super high-rise building; the anti-seismic requirement of the over-limit high-rise building is determined, the height limit is determined based on different structural forms, and it is ensured that at least one aspect of the height, the height-width ratio and the body regularity of the house meets specifications and regulations; step 3, structural finite element modeling: based on the general situation of the constructional engineering, simplifying a finite element model to enable the finite element model to be consistent with an actual structure, and establishing the finite element model; 4, analyzing dynamic characteristics of the structure, wherein the inherent dynamic performance of the structure is reflected by the similar characteristics of the structure; and step 5, structural seismic response spectrum applying: applying the seismic response spectrum to the whole structure to research the maximum response of the structure under the seismic load effect of fortification intensity. According to the anti-seismic performance analysis method for the complex high-rise structure, multiple key aspects of super high-rise building boundary range determination, clear anti-seismic design requirements, structural finite element modeling, dynamic characteristic analysis, seismic response spectrum analysis and the like are comprehensively covered, and a set of systematic and complete analysis process is formed; and the anti-seismic performance of the complex high-rise structure can be deeply and carefully analyzed.

The invention discloses a structure feature extraction and model correction system fusing convolution and a self-attention mechanism, relates to the technical field of structure engineering information, and aims at solving the problem that the structure feature extraction and model correction of a cable net structure can be realized by introducing a convolution-self-attention fusion mechanism and a double-domain consistency constraint optimization model in the whole process of cable net structure modeling, feature extraction and parameter correction. And the precision dynamic correction from the finite element simulation data to the actual measurement response data is realized. The output of the finite element modeling subsystem is used as a multilayer objective function, after the principal component screening subsystem extracts a sensitivity principal component, the system extracts a local correlation feature by using a convolutional neural network in a feature extraction stage, and then captures a global dependency feature by a self-attention mechanism, so that the model can pay attention to the micro-scale response of a local structure and also can pay attention to the global dependency feature. And the overall dynamic mode can be identified. Compared with a traditional mode, the disturbance consistency constraint and adversarial training mechanism is introduced, so that the network can still keep stable output under input disturbance.

The invention relates to the technical field of man-machine collaboration, and discloses a man-machine co-fusion model construction method and system suitable for the power industry. The method comprises the following steps: segmenting an initial point cloud model to obtain a target point cloud model containing a plurality of scene minimum units; performing element modeling on the man-machine collaborative operation domain to obtain an operation scene model; modeling the man-machine cooperation task logic in the target scene to obtain a task representation model; performing decision calculation on the operation scene model and the task representation model to obtain a man-machine task division basis, and performing operation sequence generation on the man-machine task division basis to obtain a man-machine co-fusion collaborative operation sequence; and performing interaction rule fusion on the man-machine co-fusion collaborative operation sequence to obtain man-machine co-fusion interaction logic, and performing interaction function integration on the man-machine co-fusion interaction logic to obtain a man-machine co-fusion model. The man-machine co-fusion model constructed by the method can meet the requirement of efficient and safe operation in a complex environment in the power industry.

The invention relates to the technical field of civil engineering and computational mechanics, in particular to a load and environmental corrosion coupled reinforced concrete structure analysis method. The method comprises the following steps: carrying out structural finite element modeling; carrying out mechanical field solving; the diffusion characteristics of the crack-driven corrosive medium are updated; solving a corrosive medium diffusion field; the material performance is corrected; carrying out double-time-domain self-adaptive solution; by means of the mode, the coupling effect of complex loads and multiple environmental factors in the reinforced concrete structure can be comprehensively and accurately simulated within the engineering acceptable calculation cost, and reliable prediction of the full life cycle performance is achieved.

A system for selecting an intraocular lens for implantation into an eye includes a controller adapted to selectively execute a finite element model and a machine learning module. The controller is adapted to receive input data, including one or more biometric parameters of the eye. A plurality of capsule parameters are extracted based on the input data, via the machine learning module. The controller is adapted to determine an axial displacement factor based in part on the plurality of capsule parameters, via the finite element model. The axial displacement factor accounts for a predicted axial shift of the intraocular lens after implantation into the eye. The axial displacement factor may be incorporated into the final intraocular lens power when calculating a lens constant parameter utilizing the finite element model and machine learning modules.

The invention discloses a machine learning prediction method for mechanical properties of a metal dot matrix, and belongs to the technical field of metal materials. The method comprises the following steps: S1, finite element modeling and simulation testing; s2, data collection and preprocessing; s3, performing feature analysis; s4, training and evaluating a machine learning model; s5, carrying out interpretability analysis; and S6, performing performance prediction. According to the machine learning prediction method for the mechanical properties of the metal dot matrix, the research and development cost of the mechanical properties of the metal three-dimensional dot matrix is greatly reduced, the research and development efficiency is improved, the prediction precision is high, the blank of special configuration performance prediction is filled, the influence of parameters on the performance can be clarified, and a reliable basis is provided for structural optimization.

The invention discloses a self-adaptive exoskeleton control system and method based on model predictive control and finite element modeling. According to the system, exoskeleton movement data are collected through a sensor module, and signal conditioning and filtering processing are carried out through a data preprocessing module; the finite element FEM modeling module constructs an exoskeleton dynamic model based on the preprocessed data and outputs dynamic update parameters to the model prediction control MPC module, and the model prediction control MPC module generates a control instruction through a rolling optimization control sequence to drive the control execution module; the motion monitoring feedback unit feeds back execution data to the real-time correction module, and a closed loop is formed through error calculation and parameter estimation optimization model. Through modeling and control cooperation, the precision, stability and adaptability of the exoskeleton in a dynamic environment are improved.

The invention belongs to the technical field of a strength analysis method of a lattice structure, discloses an efficient finite element modeling and analysis integrated method for static analysis of the lattice structure, and establishes an efficient and high-precision finite element modeling and analysis integrated method for the lattice structure. Aiming at the limitations that in traditional finite element analysis, high-quality hexahedron mesh generation is difficult and units need to ensure welt processing, the method adopts structured meshes to quickly divide the meshes, improves a self-adaptive integral strategy in a traditional finite cell element method, and further improves simulation efficiency. Meanwhile, a penalty function method is adopted to weakly apply displacement boundary conditions. In addition, in post-processing, a result calculated by a finite cell method is mapped to a smoother visual model. Through example comparison, it is verified that the method can perform strength check domain analysis on the complex lattice structure in a stable and efficient mode, and a feasible scheme is provided for efficient analysis of a large-scale complex engineering structure.

The invention belongs to the field of artificial intelligence and industrial finite element analysis software, and particularly relates to an LLM agent-based Abaqus finite element modeling code generation method and device. According to the method, high-precision and high-reliability finite element analysis script generation is realized through construction of an instruction-code pair database, semantic retrieval and instruction reasoning, code generation and verification and lightweight model deployment. Comprising the following steps: constructing an instruction-code pair database; performing semantic retrieval and instruction reasoning; code generation and verification; and lightweight model deployment. By using the method, the accuracy and the reliability of finite element analysis script generation can be effectively improved, and the threshold and the cost of an engineering simulation task are remarkably reduced. The industrial finite element analysis software script generation method based on the large model agent can be widely applied to finite element analysis tasks in the fields of aerospace, machine manufacturing and the like.

The invention relates to the technical field of hydraulic engineering safety monitoring and numerical analysis, and discloses a multi-dimensional cloud agent model assisted high-performance adaptive probability inversion system, which comprises a finite element modeling module, a sample generation module, a cloud agent model construction module, an adaptive inversion module and a dynamic updating module. The system constructs a multi-dimensional coupling cloud agent model for replacing finite element calculation by calculating cloud digital characteristics such as expectation, entropy and hyper entropy of input variables and generating a multi-layer virtual cloud droplet; performing parameter inversion by using a variable step Markov chain Monte Carlo algorithm based on local and global uncertainty indexes; and processing time sequence monitoring data by combining a state space model and a Bayesian recursion strategy to realize continuous correction of parameter posterior distribution. According to the method, the problems of long time consumption, low convergence efficiency and difficulty in processing time-varying characteristics of traditional inversion calculation are effectively solved, and efficient dynamic inversion and safety state accurate evaluation of dam full life cycle parameters are realized.

The invention provides an anti-seismic performance prediction optimization method and system for a concrete-filled steel tube structure, and relates to the technical field of building materials, and the method comprises the steps: interactively obtaining building concrete-filled steel tube design and building anti-seismic performance requirements; performing finite element modeling to obtain an initial structure finite element model; carrying out an earthquake working condition structure response test, and positioning distributed anti-seismic risk nodes; transversely segmenting the initial structure finite element model into W layers of independent risk analysis sub-models according to the distributed anti-seismic risk nodes; according to the node building structure characteristics, hierarchical progressive anti-seismic structure optimization is carried out, and a multivariate anti-seismic optimization scheme set is output and comprises a tie bar structure subset, a reinforcement constraint structure subset and an interface bonding reinforcement subset. The technical problem that in the prior art, due to the fact that response differences of different areas and different components in a building in an earthquake cannot be accurately recognized through aseismic design, weak links of a local area are ignored, and the overall aseismic performance is reduced is solved.

The invention discloses a composite material crack propagation method, device and equipment and a storage medium. Comprising the following steps: constructing a finite element model of a composite material test piece, positioning a crack tip node in the finite element model, establishing a local coordinate system according to the crack tip node, and calculating a crack jump length and a unit vector; node force and opening displacement under the global coordinate system are extracted based on a finite element model, and the node force and the opening displacement are converted into local coordinate system components based on unit vectors; and calculating each energy release rate component according to the local coordinate system component and the crack jump length, and substituting each energy release rate component into a preset fracture criterion formula to generate a crack propagation result of the composite material test piece. Through finite element modeling, the structure and crack position of the composite material can be accurately represented, a basic model is provided for subsequent expansion analysis, the accuracy of energy release rate calculation is improved, the fracture criterion application condition is optimized in combination with the crack jump characteristic, and the crack expansion simulation result is closer to the actual working condition.

The invention discloses a fan lattice tower optimization design system and method based on an improved genetic algorithm, and the system comprises a parameter input module which is used for receiving and preprocessing tower design parameters; the population initialization module is used for randomly generating a population and adapting to the change of the overall structure layer number of the tower by adopting a variable-length coding strategy; the finite element modeling and analysis module is used for constructing a parameterized finite element model for individuals of each population based on a finite element platform and performing finite element analysis; the algorithm optimization module is used for calculating the total cost and penalty term of each individual, and then taking the total cost of the tower as an optimization target, and using an improved genetic algorithm to complete optimization iteration; and the result output module is used for outputting an optimal individual parameter and a total cost optimal value when optimization iteration reaches the maximum evolutionary algebra or meets a convergence condition. The manufacturing cost of the tower can be remarkably reduced on the premise that constraint conditions such as strength, stability and frequency are met.

The invention relates to the technical field of electric digital data processing, in particular to a finite element modeling method and system for a trampoline net surface, and the method comprises the steps: carrying out the dynamic and static pressure testing of a target drop point of the trampoline net surface through the balance weight of each specification, and obtaining the stress load of the target drop point; determining the load direction of the target drop point by using the unit vector and the static tension value of the deflection spring and the pressure gradient of the target drop point; dividing the trampoline net surface into a plurality of load areas by utilizing the stress load and the load direction of the target drop point, and obtaining a load area sequence by utilizing the average value of the stress load of the load areas; and determining the unit size corresponding to each load area by using the number of the drop points of each load area in the load area sequence to obtain a finite element model of the trampoline net surface. According to the technical scheme, the simulation analysis precision of the finite element model on complex working conditions such as asymmetric impact and multi-point stress is improved, and the reliability of trampoline net surface deformation analysis and safety evaluation is enhanced.

The invention relates to the technical field of ship equipment, in particular to a method for calculating the impact resistance of a diesel engine turbocharger. Comprising the following steps that finite element modeling is conducted on a rotating part, a gas compressor part, a turbine part and an intermediate bearing part of the turbocharger, and overall model modeling is conducted; modal calculation is conducted on a fixed part, a rotating part and the whole of the turbocharger, and whether the modal of the turbocharger meets the requirement within the rotating frequency or not is analyzed; determining an impact load spectrum of the turbocharger, and converting the impact load spectrum into a time domain impact load; calculating and analyzing that the base bolt only bears the pre-tightening force; calculating and analyzing the overall impact response of the supercharger, including calculating and analyzing the structural strength, the acceleration response and the displacement response; evaluating the structural strength of the supercharger assembly and the impact resistance of the gap between the shell and the blade; through the mode, the shock resistance of the diesel engine turbocharger is accurately and effectively calculated, and the performance of the diesel engine turbocharger in a complex impact environment can be comprehensively evaluated.

The invention discloses a modeling and analysis method for a metal matrix composite crystal plasticity finite element, and particularly relates to the field of metal matrix composites for spaceflight. Comprising the following steps: acquiring EBSD data of a to-be-detected metal-based composite material; identifying a metal matrix phase and a reinforced fiber phase according to the EBSD data; carrying out texture analysis on the to-be-detected metal matrix composite material, and determining grain orientation data; according to the grain orientation data, establishing a finite element model of the to-be-tested metal matrix composite material, and generating a geometric grid; identifying a metal matrix phase and a reinforced fiber phase in the finite element model, and endowing each phase with parameters; according to the crystal plasticity constitutive model, determining the strain of the to-be-measured metal-based composite material; and original crystal plasticity parameters are corrected according to the actually-measured strain and strain, and the metal-based composite material model is obtained. The metal matrix composite model can obtain the grain plastic strain in the plastic deformation process.

This invention discloses a method and hoisting fixture suitable for the overall hoisting of large fiberglass towers. The method includes: determining the structure, dimensions, and preset hoisting position of the hoisting fixture based on the external dimensions, overall weight, and local components of the fiberglass tower; determining the binding method between the fiberglass tower and the hoisting fixture based on the details of the connection between the hoisting fixture and the fiberglass tower; performing finite element modeling analysis on the hoisting fixture to calculate the feasibility of its structure and dimensions, and adjusting the structure and dimensions of the hoisting fixture based on the calculation results; performing finite element modeling analysis on the fiberglass tower, and hoisting the fiberglass tower using the hoisting fixture when the stress and deformation of the fiberglass tower are within a set range. This achieves the goal of hoisting large fiberglass towers as a whole, avoiding segmented hoisting, reducing on-site docking workload and labor costs, and demonstrating strong practicality and operability.