1992 results about "Finite elemente analyse" patented technology

The present invention relates to the technical field of heat sink structure design, and in particular to a micro-channel heat sink structure design method based on a multi-objective function. The method comprises the following specific steps: S1, constructing a general mathematical description of a topology optimization problem; S2, acquiring input conditions for a specific design scenario, and dividing a topology optimization design domain; S3, establishing a governing equation for a topology optimization model; S4, on the basis of an adjoint method, performing sensitivity analysis of a multi-objective function with respect to design variables; S5, solving the topology optimization model by means of a method of moving asymptotes (MMA); S6, obtaining a two-dimensional flow channel configuration of a heat sink on the basis of contour reconstruction, carrying out finite element analysis of a two-dimensional flow channel structure, and narrowing down the selection range of constraint conditions; and S7, on the basis of a two-dimensional finite element analysis result, constructing a corresponding pseudo-three-dimensional model, carrying out finite element analysis, and determining optimal constraint conditions to obtain a final topology-optimized heat sink configuration. Compared with traditional methods, the present invention can more efficiently solve the problem in respect of heat sink structure optimization under different scenarios.

The invention provides a method for evaluating the grouting water control effect of an underground water-sealed cave depot project. The method comprises the steps that firstly, grouting and geological parameters and hydrological monitoring data of a project area are obtained; establishing a three-dimensional seepage-grouting coupling model, and simulating the dynamic state of a seepage field by using a finite element analysis algorithm; then calculating the equivalent permeability change rate of the grouting affected zone based on a simulation result; constructing an evaluation index system, and performing quantitative evaluation by using a fuzzy comprehensive evaluation algorithm; and finally, generating a grouting parameter dynamic adjustment scheme according to an evaluation result. According to the method, scientific and accurate evaluation and engineering optimization of the grouting water control effect can be achieved, and the safety and economical efficiency of engineering are improved.

The present invention relates to the technical field of mechanical property testing and characterization. Disclosed are a method and apparatus for calculating a crack propagation life of an engine structure in vibration fatigue, which method and apparatus aim to obtain reliable fracture mechanics parameters and a crack propagation rate curve and provide an accurately quantified crack propagation life, so as to provide methodological guidance for the life assessment of reusable engines. The calculation method comprises: acquiring a time-domain random stress spectrum of stress responses in an assessment section in a finite element model of an engine structure; on the basis of the time-domain random stress spectrum, performing finite element analysis processing on a crack model of the engine structure, so as to determine fracture mechanics parameters of a cracked structure; performing a vibration fatigue performance test on a crack propagation rate model, which is set up according to a preset crack propagation mode, and determining, by using parameter identification, a target parameter value corresponding to the crack propagation rate model; and in combination with the parameter value corresponding to the crack propagation rate model and a preset critical crack length value, performing crack propagation life calculation, so as to obtain a target crack propagation life.

The invention discloses a digital twinning-based major engineering construction safety active control method, system and equipment, and belongs to the technical field of construction active control. The problems of low safety risk identification efficiency and inaccurate risk control means in the major engineering construction process are solved, major engineering construction site environment and structural feature data are obtained through space-air-ground-water multi-way intelligent means and equipment, a digital twinborn model of a real-time mapping construction site is established, and the safety risk identification efficiency of the major engineering construction site is improved. Correcting the digital twinborn model by using real-time data; a digital twinborn model is used as a basic model of finite element analysis, mechanical properties of different construction stages are analyzed, dynamic early warning is performed on an analysis result in combination with real-time data, a safety risk derivation model is established to perform real-time analysis on key problems such as a risk point location, a risk influence range and risk derivation prediction in the digital twinborn model, and the safety risk derivation prediction result is obtained. Data support is provided for engineering safety active control, an active control strategy model is established, a control strategy is output to a servo control device according to risk information, strategy dynamic adjustment is performed according to a real-time effect, and high-precision cooperative control of major engineering safety monitoring is realized.

The invention provides a pipe jacking construction digital twinning optimization system and method based on high-precision physical simulation, and relates to the technical field of underground pipe network pipe jacking construction. Construction data of multiple physical entities during pipe jacking construction are collected in real time through a physical simulation engine module and then transmitted to an established digital twin model, virtual mapping synchronously updated with the construction data of the physical entities is established, and an optimization and decision module optimizes construction parameters by adopting a joint simulation algorithm fusing finite element analysis (FEA) and computational fluid dynamics (CFD), so that the construction parameters are optimized. The construction feedback module realizes automatic parameter adjustment based on PLC control according to optimized construction parameters, the analysis report module analyzes time sequence data and generates a construction efficiency evaluation report, a stress concentration area is accurately simulated, the simulation precision is improved, high synchronization of a virtual model and physics is realized, and the precision and real-time performance of system execution are improved.

The invention relates to the field of construction engineering, in particular to a roadbed construction slope displacement monitoring system based on cloud computing. A sensor network is used for collecting roadbed construction data in a roadbed, wavelet transform is used for denoising the data, a dynamic time warping algorithm in a cloud computing unit is used for aligning time sequence data in the initial roadbed construction data, and the weight of each sensor data is dynamically distributed based on an entropy weight method. A hybrid prediction model is established based on an LSTM long short-term memory network and FEA finite element analysis, a slope stress field result simulated by FEA is used as a physical constraint layer of the LSTM, an attention layer is embedded in the physical constraint layer, hyper-parameters of the initial hybrid prediction model are optimized by using a Cs-Ant improved cuckoo-ant colony combinatorial algorithm, and a slope stress field is obtained. And inputting the feature roadbed construction data into the target Cs-FEA-LSTM hybrid prediction model for prediction. The manual analysis cost is effectively reduced, and the level of roadbed engineering full-period monitoring is improved.

The present application relates to the technical field of seismic performance evaluation for building structures, and in particular to a BIM-based system and method for evaluating the seismic performance of a building structure. The method comprises: acquiring BIM data of a target building structure, and extracting geometric features and material properties thereof; on the basis of the geometric features and the material properties, generating a finite element analysis model under multiple load cases; performing dynamic response simulation on the finite element analysis model to obtain key performance indicators under the load cases; and on the basis of the key performance indicators combined with preset evaluation criteria, outputting an evaluation result of the seismic performance of the building structure. The present application can improve the automation level, application scope and accuracy of seismic performance evaluation, and also realizes the comprehensive analysis of complex building structures.

The invention discloses a bridge structure optimization method based on BIM and a finite element method, and relates to the technical field of bridge structure optimization. According to the method, the finite element analysis model can be more accurately established, and the design precision is improved. Through finite element analysis and a digital simulation technology, structure response data is rapidly obtained, and design optimization is accelerated; the optimization of the final scheme is ensured by a multi-iteration optimization strategy, the extreme load response is predicted by introducing a machine learning algorithm, a high-risk area is identified in advance, and the overall performance is improved; based on a multi-scale analysis method, the durability and safety of the structure are comprehensively evaluated, weak links are identified, and long-term performance is guaranteed; meanwhile, the influence of environmental factors on material characteristics is considered, adjustment is performed according to climate data, the design scheme is closer to the actual environment, and durability is enhanced.

The invention provides an intelligent grabbing control method and system based on tactile perception, and the method comprises the steps: obtaining a tactile feedback signal through a sensor array of a humanoid robot, carrying out the frequency domain decomposition of the signal through a Fourier transform method, and carrying out the analysis of the pressure and deformation data of each contact point on the surface of a to-be-grabbed object, calculating to obtain frequency characteristic distribution of the tactile feedback signal; if the initial estimation value of the object rigidity gradient exceeds a threshold value, performing finite element analysis on the object rigidity gradient, and combining a time domain processing result of the tactile feedback signal to obtain object rigidity gradient distribution; carrying out probability modeling on the deformation field by adopting a Bayesian inference method according to the gradient distribution of the rigidity of the object, and carrying out iterative optimization on a modeling result to obtain dynamic update parameters mapped by the deformation field; and regenerating an action sequence of the end effector of the humanoid robot based on the optimized strategy according to a trigger condition of grabbing failure detection, and determining a final grabbing control parameter.

The invention relates to an existing building glass curtain wall operation and maintenance method and system based on a digital base. The method comprises the following steps that curtain wall vibration response data, visible light image data and three-dimensional point cloud data are obtained; based on the curtain wall vibration response data, comparing the current modal parameter with the historical modal parameter, and determining the dynamic characteristics of the curtain wall panel; identifying the curtain wall apparent damage type and the corresponding damage degree based on the visible light image data; based on the three-dimensional point cloud data, a curtain wall live-action three-dimensional point cloud model is constructed and mapped into a numerical model, a local stiffness reduction coefficient is calculated based on curtain wall panel dynamic characteristics, curtain wall apparent damage types and corresponding damage degrees, and a local stiffness matrix of a corresponding unit or node in the numerical model is corrected; and performing finite element analysis on the corrected numerical model to realize performance evaluation and deduction of the glass curtain wall. Compared with the prior art, the method has the advantages that the performance change of the glass curtain wall can be accurately and dynamically sensed and predicted, and the like.

The invention discloses a spiral anchor foundation bearing effect evaluation method and system, and relates to the technical field of finite element analysis, and the method comprises the steps: building a soil body and spiral anchor finite element model, setting boundary conditions, and obtaining finite element data; according to the finite element data, a local damage variable is introduced based on a stress-strain degradation function, local shear band development is simulated, first damage data are generated, and the first damage data comprise a first stress-strain curve and a first local damage variable; layering the soil body, and optimizing the first damage data based on intra-layer constraints to obtain second damage data; calculating full-field stress, displacement and bearing capacity for effect evaluation based on a finite element solver according to the second damage data; the problem of inaccurate evaluation of the screw anchor effect caused by the nonlinear behavior and the layered heterogeneous effect of the soil body is solved.

The invention discloses a mass concrete intelligent temperature control system, and relates to the technical field of concrete temperature control, the system comprises a sensor monitoring module, a data collector, a data transmission module, a central control module, an execution mechanism and a data recording and remote monitoring module; by integrating the sensor monitoring module, the data collector, the data transmission module and the central control module, real-time monitoring and accurate analysis of key parameters in the concrete and in the construction environment are achieved, and a temperature and humidity prediction unit in the central control module can predict the temperature and humidity of the concrete by means of a finite element analysis method and a CFMH dynamic prediction formula. According to the method, the temperature and humidity trends of the concrete in different time and areas can be accurately predicted, the concrete quality problem caused by temperature and humidity fluctuation is greatly reduced, the quality stability of concrete construction is improved, a scientific and reliable decision basis is provided for constructors, the construction process is optimized, and the construction cost is reduced.

The invention relates to the field of thin-wall structure displacement field monitoring, and discloses a coupled functional unilateral inverse finite element cylindrical thin-wall structure displacement field monitoring method, which comprises the following steps of: performing discretization by adopting a four-node inverse shell unit, and arranging a sensor at a geometric center position of each unit; based on the basic mathematical model of the inverse finite element, establishing an overall pseudo-stiffness matrix and an overall pseudo-force matrix; and calculating to obtain a displacement field of the structure by solving a linear equation set formed by the overall pseudo-stiffness matrix, the overall pseudo-force matrix and the global displacement vector. According to the method, the structural displacement field is calculated by using the strain information measured at one side, and the global deformation is accurately and reversely deduced under the condition that only the local strain data is obtained by combining the advantages of finite element analysis and inverse problem solution. By optimizing local strain data solution, high cost and low efficiency of global strain measurement in a traditional method are avoided, and the method has remarkable practical advantages.

The invention belongs to the technical field of digital twinning, and discloses a hydraulic engineering-oriented digital twinning model dynamic construction and risk assessment method, which comprises the steps of dividing a hydraulic engineering into a static basic component area and a dynamic response area, accessing historical hydraulic engineering data, combining BIM and a finite element analysis technology, and carrying out dynamic construction and risk assessment on a digital twinning model. Constructing a structure model of the static basic component area and an agent model of the dynamic response area; combining the structured model with the proxy model to obtain the hydraulic digital twin; state data in the water conservancy digital twinborn body operation process are collected, and a twinborn state sequence is generated; constructing a water conservancy semantic map, and carrying out semantic binding on the water conservancy digital twin, the real-time water conservancy data and the control logic; dynamically updating a twinning state sequence when the node state of the water conservancy semantic map changes by adopting an event-driven strategy; and the response time efficiency and the emergency regulation and control capability of the water conservancy project are further improved.

The invention discloses a concrete structure crack image detection method and system based on deep learning. The method comprises the following steps: acquiring a multi-view image; performing spatial alignment according to the multi-view image to obtain a matched image sequence; performing image fusion according to the matched image sequence to obtain a fused image; performing semantic segmentation based on transfer learning according to the fused image and a preset neural network model to obtain a crack mask; according to the crack mask and the fusion image, skeleton extraction is carried out, and a preliminary crack network topology is obtained; optimizing the preliminary fracture network topology to obtain a fracture network topology; carrying out finite element analysis according to preset material attributes, a stress state and a concrete structure to obtain a stress distribution cloud picture; and according to the stress distribution cloud picture and the fracture network topology, carrying out space matching to obtain a stress fracture correlation model. The method can analyze the dynamic change of the concrete crack.

The invention relates to an intelligent building damage detection method based on machine vision. The method comprises the following steps: multi-modal data acquisition; preprocessing and feature enhancement: processing the visual data and the acoustic data; damage detection: designing a material constitutive driven GAN architecture, calculating and generating stress distribution of a crack by a generator through a differentiable finite element analysis layer, performing L2 loss constraint on the stress distribution and an ABAQUS simulation result, evaluating image authenticity and physical consistency by a discriminator by adopting a double-branch structure, and outputting damage parameters in cooperation with a lightweight YOLOv8-Nano detection head; acoustics-vision depth fusion detection: aligning a potential space through a double-flow cross-modal encoder in combination with cross-modal contrast learning, and preferentially processing hidden damage by using a gating fusion unit for dynamically calculating a fusion weight through material acoustic impedance; when the visual detection confidence coefficient is smaller than a set threshold value, triggering frequency domain mutation detection and spatial positioning of the acoustic mode; and edge-cloud cooperative processing.

The invention discloses an intelligent construction method, system, equipment and medium based on a digital twin tunnel, and aims to construct a high-precision physical entity model by fusing dynamic and static data in real time through multiple types of sensors so as to improve data acquisition comprehensiveness; based on tunnel-level, soil-level and ground building-level multi-level modeling and finite element analysis, fine mechanical stability simulation is realized; multi-dimensional data features are extracted by combining a convolutional neural network algorithm, security risks are evaluated, and a reinforcement scheme is optimized through dynamic iteration; a closed-loop regulation and control mechanism of data monitoring, numerical simulation and dynamic feedback is formed by utilizing a collaborative architecture of a sensing layer, a simulation layer and a display layer, so that environmental disturbance is effectively reduced, and construction safety is guaranteed; according to the method, digital twinning, BIM, finite element analysis and deep learning are fused, real-time monitoring and intelligent optimization of the whole construction process are achieved, efficiency and safety are remarkably improved, and influences on the surrounding environment are reduced.

The invention discloses a digital twin system architecture of a vertical shaft and a structural performance monitoring method. The method comprises the following steps: constructing a five-dimensional digital twin system framework suitable for a vertical shaft based on a shaft operation mechanism and performance monitoring requirements; establishing a shaft digital twinborn model with dynamic characteristics; a finite element proxy model is constructed through a virtual-real mapping technology in combination with a grid dimensionality reduction finite element analysis method, and rapid generation of the digital twinborn body is realized. According to the system, a three-dimensional operation platform is constructed based on a Unity 3D virtual engine, and efficient mapping and bidirectional interaction between twin and finite element simulation data are realized by adopting a radial basis function (RBF) proxy model. And real-time acquisition and online prediction are carried out on structural performance parameters in the shaft operation process. And dynamically updating the twinborn model according to a prediction result, and constructing a high-precision and light-weight digital twinborn evolution model, thereby realizing real-time observation of the stress change of the shaft and intelligent monitoring of the structural performance. The method can be widely applied to the fields of shaft safety assessment, maintenance decision making, intelligent mine construction and the like.

The invention relates to the technical field of material simulation models, and particularly discloses a finite element analysis and thermal expansion mismatch effect-based comprehensive simulation model construction method, which comprises the following steps of performing geometric model construction on a target material; constructing a geometric model: adopting modeling software to create the geometric model of the target material, and obtaining a thermal mismatch target area interface; parameter data of a target material are obtained for assignment, and then a target material grid is preprocessed; performing boundary condition constraint on the geometric model of the target material, and applying a temperature load; establishing a thermal stress corresponding mechanism for the geometric model of the target material, calculating to obtain thermal stress values of the unit grids, and converting the thermal stress value on each unit grid into a cloud picture in a color manner based on the thermal stress values of the unit grids to obtain a thermal expansion mismatch effect comprehensive simulation model; the quantitative analysis capability of the thermal stress difference of multiple materials is realized; potential stress concentration areas caused by thermal expansion mismatch can be identified.

The invention discloses a method and a system for predicting and monitoring frame fatigue based on twinning of the Internet of Vehicles. The method comprises the following steps: analyzing a vehicle use scene and a working condition ratio based on historical data of the Internet of Vehicles; carrying out a frame real vehicle load test, and converting a strain-time history into a load-time history in combination with static loading calibration; performing weighted combination on each load history according to a working condition ratio to obtain a weighted composite load-time history; reconstructing a stress-time history of each measuring point based on finite element analysis, and constructing a stress cyclic spectrum by adopting a rain flow counting method; calculating the fatigue life of the frame by combining a stress-life method and a Miner linear damage criterion; and constructing a frame twinborn model corresponding to the real vehicle at the cloud, accessing vehicle operation data in real time, dynamically updating a stress process and fatigue damage, calculating the residual fatigue life, and triggering early warning when the life is lower than a threshold value. The method can achieve the precise evaluation and online monitoring of the fatigue life of the vehicle frame, and is suitable for the durability design and structural health management of new energy commercial vehicles.

The invention discloses a multi-axial fatigue and reliability analysis method for a semi-submersible wind turbine supporting structure, which comprises the following steps of: firstly, determining an input load power spectral density function of each part of an offshore semi-submersible wind turbine by combining a motion theory, a wind speed spectrum theory and a wave spectrum theory of the offshore semi-submersible wind turbine; carrying out finite element analysis on the offshore wind turbine in a frequency domain according to the load power spectral density function, determining a dangerous point through a frequency domain method, calculating damage by using a W-B critical plane method, predicting the fatigue life of the dangerous point in a time domain, verifying that wind-induced damage is far greater than wave-induced damage, and finally solving a failure probability curve of the wind turbine support structure. And multi-axial fatigue and reliability analysis of the semi-submersible wind turbine supporting structure is completed. According to the method, the randomness of the marine environment and the calculation interval of the wind turbine load can be well unified, the accuracy of predicting the fatigue life of the wind turbine supporting structure is improved, and the method has universality for any type of wind turbine supporting structures and is easy and convenient to operate and wide in application range.

The invention relates to the technical field of section design, and discloses a shipyard steel bent frame column and beam section design simulation method and system. The method comprises the following steps: classifying and storing the historical data of the shipyard steel bent, establishing an experience library and extracting initial section parameters; inputting a parametric modeling system to generate a geometric model and a load condition; obtaining an internal force envelope value based on finite element analysis; obtaining a stress ratio and a displacement ratio according to standard combination and checking calculation; using an NSGA-II algorithm to optimize section parameters; and modeling and marking based on an optimization result, and generating a structure optimization scheme and a design drawing. The problems that in the prior art, preliminary section type selection of a steel bent frame structure lacks system optimization, a large amount of manual adjustment is needed in the design process, the overall design efficiency is low, and the material utilization rate is low are effectively solved, and automatic, refined and multi-target comprehensive optimization of steel bent frame column and beam section design is achieved.

The invention discloses a side slope stability intelligent monitoring and supporting optimization method based on digital twinning, which comprises the following steps: extracting gradient, curvature and geological layering characteristics from a holographic terrain model, calculating a preliminary change trend of stress distribution of a rock-soil body in combination with a finite element analysis method, and determining spatial position distribution of a potential sliding surface of a side slope; according to the space coordinate set of the real-time monitoring point position, the data acquisition frequency of the sensor is adjusted through a time sequence analysis method, and a high-frequency monitoring data set reflecting dynamic changes of stress and underground water is obtained; extracting stress peak values and underground water level fluctuation characteristics from the high-frequency monitoring data set, and generating a multi-dimensional information matrix containing terrain, stress and water dynamics by combining spatial characteristics of the holographic terrain model and adopting a data fusion algorithm; according to the state parameters of the digital twinborn body, if it is judged that the stress distribution exceeds a preset threshold value, the stress distribution of the supporting structure is recalculated through finite element analysis, and an adjusted slope supporting design scheme is obtained.

The present application relates to the technical field of mold structure design. Disclosed are a mold structure design optimization method and apparatus. The method comprises: performing parametric modeling on a three-dimensional model of a laser cutting die to obtain an adjustable parameter set; performing cutting die geometric feature extraction and feature classification to obtain a feature classification result; performing adaptive multi-scale mesh division to obtain a multi-scale finite element analysis model; performing multi-physics coupling analysis to obtain stress distribution data, deformation data and temperature field distribution data; performing variance analysis to obtain target impact parameters, and, on the basis of the target impact parameters, constructing a multi-objective optimization model; by means of a non-dominated sorting genetic algorithm, solving the multi-objective optimization model to obtain a Pareto optimal solution set; and determining, from the Pareto optimal solution set, target optimization structural parameters of the laser cutting die, thereby improving the optimization efficiency while ensuring the calculation accuracy, and achieving the overall performance improvement of the laser cutting die.

The invention discloses a stamping die health state assessment method and system based on digital twinning, and relates to the technical field of die health state assessment, and the method comprises the following steps: a physical sensor network deployed on a stamping die collects die stamping process data in real time; constructing a finite element analysis simulation FEA model to simulate the working condition of the stamping die based on the geometric structure, the material attribute and the stamping process parameters of the die; according to the invention, the data of the die stamping process are collected in real time through the physical sensor network, and real-time calculation is carried out in combination with the finite element analysis simulation model, so that transient stress field, strain field and temperature field data of the die can be output in a short time, and real-time monitoring of the health state of the die is realized; by considering the degradation of the mold material performance along with the use time and the dynamic process of quantitative damage accumulation, the damage accumulation value is accurately calculated through the dynamic material performance database and the continuous damage mechanical model, and the accuracy of the evaluation result is improved.

The invention relates to the technical field of material processing control, and discloses a method for efficiently cutting a vacuum brazing soldering lug. The method comprises the following steps: firstly, receiving material parameters and target geometrical shape data of a to-be-cut soldering lug, and generating and optimizing an initial cutting track based on a preset algorithm; in combination with real-time temperature field monitoring data, thermal stress distribution is calculated through a finite element analysis method, and the cutting speed and laser power parameters are dynamically adjusted; and then the cutting precision and the equipment energy consumption are synchronously optimized through a multi-objective optimization algorithm, and final cutting parameters are output to a vacuum brazing control system. In addition, signals are collected in real time during cutting to recognize abnormity, and algorithm weights are calibrated by comparing geometric parameters after cutting. The cutting precision and efficiency can be effectively improved, equipment energy consumption is reduced, cutting abnormity is treated in time, self-optimization of the cutting process is achieved, and the method is suitable for the production field with the high requirement for vacuum brazing piece cutting.

The invention discloses an assembly type composite floor slab cast-in-place section span beam joint design method based on digital twinning, and relates to the technical field of intelligent construction, the method comprises the following steps: adopting a least square optimization algorithm to obtain a material performance correction parameter and a geometric compensation parameter; based on the historical material performance correction parameters and the geometric compensation parameters, training the structure model through a genetic algorithm to generate a digital twin reference model; inputting the material performance correction parameters and the geometric compensation parameters into the digital twin reference model, performing multi-scale finite element analysis, and outputting a multi-scale node performance evaluation report; identifying a multi-scale node performance influence factor and a sensitive area by adopting a response surface method, outputting a design parameter sensitivity analysis result, and converting the multi-scale node performance influence factor into a preliminary node design scheme through a design parameter conversion algorithm; according to the method, the real-time accuracy of node design is remarkably improved through least square dynamic parameter correction.

The invention relates to the technical field of semiconductor photoelectronics, and discloses a multi-physics field coupling silicon-based optical interconnection chip degradation model construction method and application, and the method comprises the steps: firstly constructing a multi-physics field coupling analysis model, and quantitatively representing the coupling relation of thermodynamics, optics, electricity and material aging through an inter-field coupling equation and a material aging dynamic model; simulating field distribution of a chip key area under multi-environment stress through finite element analysis, and extracting data; then historical degradation data is collected by combining an accelerated aging test and long-term operation monitoring, and a degradation parameter prediction model is established after data processing based on machine learning; and finally, inputting a finite element result and a prediction result into a material aging dynamic model, and finally forming a multi-physics field coupling degradation model. The problems that the prior art depends on a single physical field, degradation mechanism analysis is incomplete, and service life evaluation is inaccurate are solved, and support can be provided for reliability evaluation, structure optimization and service life prediction of the silicon-based optical interconnection chip.

The invention provides a subjective optometry prediction method combining wavefront aberration and optical signals. According to the method, eyeball wavefront aberration data are measured through a wavefront sensor, cornea, crystal and retina biological parameters are obtained by combining multi-view-field scanning of a galvanometer system, and after high-credibility data points are screened, a gradient refractive index eyeball three-dimensional model is constructed by adopting an NURBS algorithm; using finite element analysis to optimize cornea stress distribution, iteratively correcting the model through a deformation energy function, and dynamically compensating eyeball motion errors based on eye movement tracking data; and generating a multi-field-angle visual chart image through ray tracing simulation, and predicting a subjective optometry result in combination with an image quality evaluation algorithm. According to the method, high-precision modeling, dynamic error suppression and intelligent simulation technologies are fused, the optometry prediction accuracy, the personalized adaptation degree and the dynamic scene adaptability are remarkably improved, and an efficient and reliable solution is provided for refraction correction.

The invention relates to the technical field of ball valve design and simulation, in particular to a three-dimensional simulation design method and system for a ball valve. The method comprises the following steps: performing reference geometric construction based on a ball valve design specification, and performing geometric parameterization to obtain an initial geometric configuration; importing the initial geometric configuration into a finite element analysis platform, and endowing material attributes to obtain a finite element mesh model; performing ball valve working stress analysis on the finite element mesh model to obtain a stress-strain field; performing model fluid domain grid division according to the initial geometric configuration and the stress-strain field to obtain a fluid domain grid; valve opening change setting is conducted on the fluid domain grids, and a CFD calculation model is obtained; internal flow field transient simulation of the ball valve under different opening degrees is conducted on the CFD calculation model, and fluid dynamic parameters are obtained. The dynamic characteristics of the valve under the complex working conditions are accurately captured, and the working performance of the valve under different working conditions is improved.