165 results about "Parametric simulation" patented technology

The present invention relates to the technical field of building foundation reinforcement deviation correction, and provides a building reinforcement lifting method based on numerical simulation, comprising: establishing an initial building model representing a building experiencing subsidence, and acquiring an initial subsidence displacement of the building; on the basis of the initial building model, adjusting shallow foundation parameters under the building foundation, simulating reinforcement of the shallow foundation, and forming a reinforced shallow foundation model; on the basis of the reinforced shallow foundation model, adjusting deep foundation parameters under the building foundation, simulating reinforcement of the deep foundation, and forming a reinforced deep foundation model; and, on the basis of the reinforced deep foundation model, dividing an intermediate lifting layer located between the deep foundation and the shallow foundation into a plurality of lifting areas and, on the basis of the subsidence displacement of each area, performing corresponding simulated lifting to implement simulated lifting of the building. The present method uses a numerical simulation approach to perform simulated optimisation on actual grouting deviation correction engineering cases, achieving both engineering economy and safety.

The invention discloses a power transmission line lightning arrester fault defect analysis method and system, and relates to the technical field of intelligent operation and maintenance of power equipment, and the method comprises the following steps: obtaining a lightning arrester simulation model; simulating a preset defect working condition by adjusting parameters of the lightning arrester simulation model, executing simulation for a plurality of times, and constructing a defect state feature set; acquiring multi-dimensional time sequence monitoring data during a single discharge action period of the lightning arrester, acquiring equivalent strength data based on the deep learning model, and accumulating the equivalent strength data to obtain accumulated equivalent action strength; performing feature similarity matching on the defect state feature set and the action feature vector of the multi-dimensional time sequence monitoring data, and identifying the defect type of the lightning arrester; and carrying out proportion calculation on the accumulated equivalent action intensity and preset tolerable action intensity, and if a preset alarm condition is met, outputting alarm information. The method is used for solving the problems that a traditional lightning arrester monitoring pair lacks structural modeling, and accurate defect evaluation and dynamic early warning are difficult to achieve.

The invention provides an insulating material surface arc ablation resistance simulation method based on magnetohydrodynamics, and belongs to the field of insulating material performance detection. The method comprises the following steps: establishing an insulating material surface arc ablation resistance model; constructing a magnetohydrodynamic control equation set; setting boundary conditions of the model; and iteratively solving the magnetohydrodynamic control equation set through finite element simulation software to obtain a temperature distribution diagram of the insulating material under different arc ablation times, and comparing the temperature distribution diagram with a TGA curve of the insulating material to judge the arc ablation resistance of the insulating material. According to the invention, the power-frequency alternating-current high-voltage arc and the insulating material are used as simulation objects, engineering practice is better met, the surface arc ablation resistance process of any insulating material can be simulated by changing the physical characteristic parameters of the insulating material, and the TGA curve of the material is introduced to judge the arc ablation resistance of the insulating material. And technical support is provided for high-voltage switch equipment insulating material type selection.

The invention relates to the technical field of hemodialysis teaching systems, and discloses a hemodialysis teaching system based on AI intelligent pushing. The system comprises an operation feature extraction module, an instrument positioning analysis module, an operation step analysis module and a teaching strategy generation module. Operating a feature extraction module to obtain a hemodialysis teaching video stream, and extracting multi-modal features containing an instrument movement track sequence and physiological parameter simulation data; an instrument positioning analysis module calls a pre-training network for positioning and generates a coordinate data set containing instrument types and three-dimensional position coding mapping; the operation step analysis module analyzes the time sequence characteristics by means of an action segmentation model, and generates a result containing step integrity and an error operation mark; and the teaching strategy generation module inputs a result into the intelligent push model, plans a personalized teaching path, outputs a knowledge point sequence containing a student ability model and dynamic teaching elements of operation difficulty parameters, and assists the hemodialysis teaching to be precise and personalized.

The invention discloses an oil reservoir balanced injection and production parameter determination method based on multi-algorithm analysis. The method comprises the steps that S1, a balanced injection and production influence parameter simulation model is established through oil reservoir numerical simulation software; s2, obtaining a prediction model result through numerical simulation operation, screening out balanced injection and production influence parameters, and summarizing various factor rules of different reservoir conditions; s3, correlation analysis is conducted on the oil reservoir data; and S4, determining balanced injection and production main control factors and weights thereof under different reservoir conditions. The invention further discloses a system. The method comprises the following steps: performing correlation analysis on oil reservoir data, and determining main control factors and weights of balanced injection and production under different reservoir conditions, thereby comprehensively analyzing numerous influence factors, considering the influence factors under different reservoir conditions, accurately screening out core parameters influencing balanced injection and production, and then determining the weights of the core parameters. A key basis is provided for formulating a scientific exploitation scheme, the oil reservoir exploitation process can be effectively optimized, the recovery efficiency is improved, energy waste is reduced, and therefore the economic benefits of oil reservoir exploitation are improved.

The invention provides a carbon dioxide injection well perforation parameter optimization method and device and electronic equipment, and the method comprises the steps: carrying out the standardization processing of geological and logging data, and constructing a multi-dimensional data set comprising lithology, porosity, permeability, crack parameters and a ground stress field; a three-dimensional digital twinborn model is constructed based on the data set, and reservoir heterogeneity and fracture network distribution are restored; on the basis of the digital twinborn model, performing multi-physics field coupling simulation including carbon dioxide migration simulation, shaft stress distribution simulation and long-term corrosion prediction; based on a multi-objective optimization algorithm, with the effective wave and volume of the carbon dioxide, the integrity coefficient of the shaft and the anti-channeling safety coefficient as objectives, an optimal perforation parameter combination is screened; and outputting a visual report including perforation parameters, simulation results and risk assessment. Digital twinning, multi-physics field simulation and multi-objective optimization are deeply fused, and a set of complete, accurate and efficient perforation parameter optimization solution from data to decision is formed.

The invention discloses an ice rink re-paving ice layer thickness prediction method, system and equipment based on digital twinning, and relates to the technical field of ice rink ice surface thickness. The method comprises the following steps: step 1, constructing a digital twinborn model of the re-paved ice surface of the ice pouring vehicle through COMSOL numerical simulation software, and mapping and fusing the digital twinborn model of the re-paved ice surface of the ice pouring vehicle and real-time environmental data to generate a dynamic digital twinborn body; 2, real-time operation parameters of the ice pouring vehicle are input into the dynamic digital twin body, operation is simulated, and the simulated icing thickness is output; and 3, inputting the simulated icing thickness, the real-time operation parameters of the ice pouring vehicle and the real-time environment data into the trained machine learning model to obtain the thickness of the re-laid ice layer. According to the method, the icing thickness of the re-paved ice surface of the ice pouring vehicle corresponds to the twin model through the digital twin technology, so that the re-paved ice layer thickness prediction is more accurate and comprehensive, the re-paved ice layer thickness prediction is realized, the risk of different ice layer thicknesses is reduced, the waste of water resources is avoided, and the energy consumption is saved.

The invention discloses a multilayer wave-absorbing material design method, system, medium and equipment, and the method comprises the steps: building a multilayer wave-absorbing material model through electromagnetic simulation software, taking a radar cross-sectional area RCS as an optimization target, and controlling FEKO to be within a specified target frequency band; sampling electromagnetic parameters in a value range by adopting a Latin hypercube sampling algorithm, performing parameterized simulation on the multilayer wave-absorbing material model, extracting radar cross-sectional area (RCS) values to form a parameter-RCS data set, generating an electromagnetic parameter-RCS data set, training a convolutional neural network, and obtaining a multi-layer wave-absorbing material model; establishing a nonlinear mapping model from the electromagnetic parameters to a radar cross-sectional area (RCS); embedding a proxy model obtained by training into a Bayesian optimization framework, applying an expected improved function to guide a search space, automatically optimizing an electromagnetic parameter combination, and performing FEKO full-wave simulation verification; if the RCS value of the optimization result is lower than the preset threshold value, iteration continues until the performance requirement is met, and the optimal electromagnetic parameter combination is output.

The invention relates to the technical field of roller press main roller simulation, in particular to a parameterized simulation method and system for the radian of a roller press main roller and a storage medium. The method comprises the following steps that surface space scanning is conducted on a main roller of the roller press, and main roller space parameters are obtained; main roller radian distribution evaluation is conducted according to the main roller space parameters, and a main roller radian distribution diagram is obtained; carrying out regional division on the main roller radian distribution diagram, and importing mechanical analysis software to construct a roller press main roller initial state model; rolling material data are obtained; performing material-main roller stress parameterization simulation according to the rolled material data and the roller press main roller initial state model to obtain simulated main roller stress state data; and intelligent main roller bending compensation is carried out based on the simulated main roller stress state data, and main roller bending compensation parameters are obtained. Intelligent compensation of the radian state of the main roller of the roller press is achieved through main roller stress parameterization simulation, the product quality is effectively improved, energy consumption is reduced, and the service life of equipment is prolonged.

The invention relates to a simulation analysis method and device for bottle performance. The simulation analysis device comprises a bottle blank wall thickness obtaining module, a bottle blank heating simulation module, a blow molding simulation module and a structure simulation module, and the bottle blank wall thickness obtaining module, the bottle blank heating simulation module and the structure simulation module are all associated with the blow molding simulation module; a bottle blank wall thickness acquisition module acquires continuous and non-uniform bottle blank wall thickness data of the bottle blank three-dimensional solid model; the bottle blank heating simulation module receives the heating simulation parameters and simulates the heating process of the bottle blank before blow molding to obtain continuous and non-uniform bottle blank temperature distribution data; the blow molding simulation module simulates a bottle blank blow molding process according to the bottle blank wall thickness data, the bottle blank temperature distribution data and the received blow molding simulation parameters to obtain a bottle simulation model; and the structure simulation module performs bottle performance simulation analysis on the bottle simulation model to obtain performance simulation data of the bottle simulation model. And more real bottle body wall thickness distribution data and bottle blank temperature distribution data can be obtained, and the performance of the bottle can be predicted and evaluated more accurately.

The invention discloses a dynamic simulation method, a dynamic simulation device, dynamic simulation equipment, a dynamic simulation medium and a dynamic simulation product for a network construction type fuel cell power generation system, and relates to the field of physical object simulation dynamic modeling and performance analysis. The method comprises the following steps: firstly, determining the overall structure and configuration of the network-constructing type fuel cell power generation system, carrying out comprehensive modeling by utilizing a thermoelectric comparison method on the basis, and establishing an overall standard circuit model of the network-constructing type fuel cell power generation system; constructing a dynamic simulation model of the network-constructing type fuel cell power generation system based on the overall standard circuit model; by adjusting input parameters of the dynamic simulation model, simulating dynamic responses of the network-forming type fuel cell power generation system in different distributed power generation scenes; and performing cluster analysis on simulation results under different distributed power generation scenes, and formulating an intelligent control strategy of the distributed power generation system. According to the method, the dynamic response of the network-forming type fuel cell power generation system to the power grid in the distributed power generation system can be accurately simulated under the condition that large-scale on-site deployment is not needed.

The invention discloses a simulation charging pile test method, system and device based on a charging pile simulator, and relates to the technical field of simulation charging piles, and the method comprises the steps: obtaining parameters of a simulation charging pile and a platform server; tCP long connection is established between the simulation charging pile and the platform server; selecting different charging modes to test each charging flow to obtain charging process data; and obtaining fault data and log message data. According to the main technical scheme and effects, the charging pile simulator simulates data interaction of various business test scenes of a charging APP, an applet and a management platform, including charging pile charging and discharging, fault warning and the like, the test development process is separated from an actual charging pile and a new energy automobile, and the material preparation cost is greatly saved; according to the simulation charging pile, the multi-thread design is adopted, it is ensured that the process runs smoothly, the multiple charging pile simulators can be started to work at the same time, and the data interaction efficiency of the simulation charging pile and the platform server side is greatly improved.

The present invention discloses a heating intelligent decision-making system based on an artificial intelligence large model, including: a data layer for storing various types of data of the source-network-load-storage of the heating system; a knowledge base establishment and large model training layer for establishing a diversified task knowledge base for heating intelligent decision-making and establishing large models for each task; a human-machine enhanced optimization large model layer for putting forward improvement suggestions to the large model, optimizing the generated answers, evaluating multiple answers generated by the large model, and performing parameter optimization training on the large model; an intelligent agent decision-making layer for integrating the large models of each task into each intelligent agent for environmental perception, collaborative interaction, and autonomous adaptive decision-making; a simulation layer for providing a simulation operation environment, a user interaction interface, and dynamic parameter simulation of scenarios; an intelligent agent evaluation and optimization layer for constructing performance indicators for evaluating each intelligent agent, and evaluating and optimizing the behavior and decision-making of each intelligent agent.

The invention relates to an AMR task scene equipment parameter simulation generation method and device and a storage medium, and is applied to the technical field of digital twinning, and the method comprises the steps: determining equipment participating in a task scene through determining task processes of different AMR task scenes, and obtaining an interactive relationship between every two pieces of equipment (including AMR) participating in the task scene through obtaining the interactive relationship between every two pieces of equipment (including AMR) participating in the task scene; determining a coupling relationship between any two devices, screening N devices having strong coupling relationships with the AMR, and generating a sampling parameter combination of the AMR and the N devices according to historical operation data of the devices and the coupling relationships; a digital twinborn model of an AMR task scene is constructed through a digital twinborn technology, in the digital twinborn model, simulation operation of a task process is performed on different parameter combinations, and a reliability score corresponding to each parameter combination is obtained, so that an optimal parameter combination is screened out, and the reliability of the AMR task scene is improved. And updating the real AMR and the parameters of the equipment according to the optimal parameter combination.

The invention provides a deep foundation pit monitoring method based on BIM-physical model hybrid simulation. The method comprises the steps that real-time monitoring data and BIM model parameters of a deep foundation pit are collected; inputting a first model parameter in the BIM model parameters as an initial geometric condition into the initial physical model for simulation calculation to obtain first simulation data, and verifying the first simulation data based on the real-time monitoring data to obtain a verification result index; optimizing the soil mass mechanical parameters in the initial physical model based on the verification result index until the verification result index output in the optimization process meets a preset requirement, and obtaining an optimized physical model; simulating the construction process of the deep foundation pit on the basis of the optimized physical model in combination with a second model parameter in the BIM model parameters, and outputting second simulation data; and performing monitoring and early warning on the deep foundation pit based on the deep foundation pit knowledge graph in combination with the real-time monitoring data and the second simulation data to obtain a monitoring and early warning result. According to the invention, comprehensive monitoring of the deep foundation pit is realized.

The invention relates to the technical field of soil data processing, and discloses a soil data simulation method integrating machine learning and spatial analysis cooperation. The method comprises the following steps: acquiring multi-source soil data of a target area, determining spatial characteristic parameters of each soil data unit, calculating machine learning characteristic indexes and generating an analog input set; then, dynamic evolution parameters are determined by using a pre-trained machine learning model, and a collaborative simulation map is marked and generated in the spatial analysis model; and then performing data consistency detection, and simulating and generating soil data based on a detection result. And if the parameter conflict is detected, fusing the parameters according to the multi-source data priority. After the simulation result is generated, monitoring the attribute difference value of the soil data unit and the adjacent unit in real time, and dynamically correcting the parameter when the threshold value is exceeded. According to the method, multi-source data are integrated, machine learning and spatial analysis technologies are utilized, the precision and reliability of soil data simulation are improved, and powerful support is provided for soil research and related fields.

The invention relates to the technical field of vehicle brakes, in particular to a parameterized simulation design method for a vehicle brake structure. The method comprises the following steps: firstly, obtaining vehicle brake structure data and constructing a three-dimensional virtual model; then, multi-frequency rapid braking response simulation is carried out based on the model, the softening gradient of the brake disc is recognized, and displacement deformation of the brake disc caused by external force impact is analyzed; thirdly, defining the bearing boundary of the brake by combining the external force impact data and the structural data, and optimizing the structural performance; and finally, designing a parameterized simulation architecture based on the optimized data, and uploading the parameterized simulation architecture to a cloud platform to execute parameterized simulation of the brake. According to the method, the vehicle brake technology is optimized, so that the vehicle brake technology is more perfect.

The invention discloses a thermal-mechanical coupling behavior numerical simulation system for a reinforced concrete structure, and particularly relates to the field of constructional engineering, and the system comprises a heat conduction analysis module, a mechanical behavior analysis module, a bond slip behavior analysis module and a simulation calibration module. The heat conduction analysis module simulates the temperature field change of the concrete in the fire disaster process by defining temperature related parameters of the concrete; the mechanical behavior analysis module is used for simulating nonlinear mechanical behaviors of concrete and analyzing strength degradation, crack propagation and plastic deformation of the concrete at high temperature in combination with a temperature-dependent material model; and the bond slip behavior analysis module is used for setting a non-linear contact behavior between the reinforcing steel bar and the concrete. According to the invention, comprehensive simulation of reinforced concrete under high-temperature conditions such as fire disasters and the like is realized, and the strength degradation and crack propagation of the concrete and the bond slip behavior of the reinforcing steel bars and the concrete can be accurately predicted in combination with a temperature field and a mechanical field.

The present invention relates to the field of data processing, and discloses a test method, device and storage medium for a body controller compatible with multiple models. The method includes: when a function test instruction is received, generating function requirement information according to the function test instruction; selecting a target test item set from a preset test item set according to the function requirement information; performing parameter simulation operations for multiple models according to the target test item set and a preset parameter simulation pattern to obtain a test parameter set; generating test cases according to the test parameter set; and controlling the body controller to perform a test operation according to the test cases to obtain a test result. In the embodiment of the present invention, compatible testing of body controllers of multiple models can be realized, and the compatibility of the body controller test method is improved.

The invention belongs to the technical field of microstructure simulation in the solidification process, and particularly relates to a nickel-based superalloy laser welding solidification structure evolution law prediction method and system.The method comprises the steps that simulation parameters are determined, a macroscopic temperature field is simulated to obtain molten pool temperature field data, a cellular automaton model is constructed, and grids are divided; initializing state variables such as component concentration and solid-phase fraction; coupling temperature field data, solving an optimized solute diffusion and redistribution equation to obtain a concentration field, updating a solid phase fraction according to local supercooling drive, and marking grain growth; counting a solid-phase fraction, and updating a solid-phase position; and judging whether the temperature of the cladding layer is lower than the solidus temperature and the solid fraction reaches a complete solidification threshold value or not, and if yes, outputting weld microstructure and target element concentration data. According to the method, the evolution law of the welding macroscopic temperature field and the structure and solute concentration field can be effectively predicted, experiments are replaced with numerical simulation, the cost is reduced, the technical blank is filled up, and reliable support is provided for precise regulation and control of the nickel-based high-temperature alloy laser welding process.

The invention discloses an oil and gas development favorable area prediction method based on Winsored particle size mean curve simulation, and the method comprises the following steps: based on laser particle size experiment data, employing a Winsored algorithm to process rock particle size data, removing abnormal interference values, and simulating a well hole particle size mean longitudinal curve through inputting logging response parameters by means of an XLSTM-Transform hybrid neural network model; selecting a shear modulus density and a longitudinal and transverse wave velocity ratio as sensitive attribute parameters of a granularity mean value in combination with seismic data, and forming two sets of three-dimensional attribute data volumes in combination with waveform structure inversion; according to the method, model training is carried out on the nonlinear relation between the particle size mean value and the seismic sensitive attribute parameters based on a machine learning method, and finally a Winsored particle size mean value inversion body is formed, so that the spatial distribution rule of a relatively large particle size reservoir can be defined, and effective prediction of a development favorable area is realized.

The invention discloses a parameterized power transmission line distraction field site arrangement simulation method and equipment, structural characterization is carried out on extracted nodes by combining an interpolation method and a shape finding analysis method, parameterized modeling is carried out according to a characterization structure, a distraction field site model is further obtained, the distraction field site model accurately feeds back the shape of a distraction field, and the distraction field site arrangement simulation method and equipment have the advantages that the distraction field site arrangement simulation efficiency is improved. Meanwhile, the interaction relation between each machine and each structure is accurately fed back, and an accurate and stable distraction field model consistent with a construction field is provided for subsequent distraction field simulation; the arrangement simulation parameters subjected to construction verification are input into the distraction field migration model again to be circularly processed until the optimal arrangement simulation parameters are generated, the optimal arrangement simulation parameters serve as the optimal distraction field construction parameters, construction is conducted, and the problem that local engineering calculation is conducted on the parameters manually is solved; the calculation result is not standard, and meanwhile, the position of a dangerous point in the layout of the distraction field cannot be accurately estimated.

The invention discloses a cost optimization method and system for a buried pipe system, and relates to the technical field of buried pipe systems.The cost optimization method comprises the following steps that an optimization problem is solved, and a well track of a directional well group is obtained; a well group arrangement diagram is generated through the well track, and a buried pipe system numerical model is constructed based on the well group arrangement diagram; performing operation simulation on the numerical model of the buried pipe system, and determining the annual operation cost of the buried pipe system, the system operation cost of the whole life cycle and the average energy cost according to a simulation result; and correcting the initial investment cost, the annual operation cost, the system operation cost of the whole life cycle and the average energy cost according to the actual project condition. According to the method, efficient space utilization of the well group is achieved, and meanwhile the economical efficiency and the long-term stability of the system are improved by combining initial investment measurement and calculation, long-term operation parameter simulation and dynamic optimization of actual operation data.

The invention provides a power grid modeling simulation system and method, and relates to the technical field of power systems. The system comprises a power grid topological structure modeling unit used for constructing a topological structure model of a power grid according to parameter information of power grid components in the power grid; the topological structure model is used for indicating a connection relationship and layout information between power grid components in the power grid; the dynamic behavior simulation unit is used for simulating the dynamic behavior of the power grid based on the topological structure model and the operation influence parameters to obtain simulation information; the state evaluation unit is used for monitoring and evaluating the state of the power grid according to the topological structure model and the simulation information to obtain state evaluation information; and the decision support unit is used for generating optimization decision information of the power grid based on the simulation information and the state evaluation information. According to the invention, high-precision simulation and optimal scheduling of the complex operation condition of the power grid are realized, and the safety and stability of the power grid are improved.

The invention discloses a method and a system for determining deformation and warping parameters of an injection molding plate. The method comprises the following steps: acquiring simulation deformation data reflecting the deformation and warping degree of the injection molding plate; judging whether the change trend of the simulation deformation data relative to the standard deformation data is the same and meets a measurement index or not; if the change trends are the same and meet the measurement index, storing the first deformation warping parameter; if the change trends are the same but do not meet the measurement index, modifying a first deformation warping parameter corresponding to the simulation deformation data; if the change trends are different, the simulation deformation data are obtained again after the simulation mode for obtaining the simulation deformation data is switched, and the simulation deformation data are compared with the standard deformation data again. According to the method provided by the invention, the deformation warping of the injection molding plate can be simulated based on the preset deformation warping parameters, the obtained simulation deformation data reflecting the deformation warping degree of the injection molding plate is compared with the standard deformation data, and the corresponding deformation warping parameters are stored when the change trend and the measurement index are met.

The application discloses a mine roadway on-demand support structure optimization method based on artificial intelligence, relates to the technical field of mine roadway support, and collects roadway measurement data of a roadway measurement point; captures and extracts the roadway measurement data to obtain fissure geological parameters, classifies and summarizes the fissure geological parameters to obtain a rock mass quality grade; constructs a roadway section model, collects parameters, obtains original rock mass mechanical parameters, simulates and constructs the roadway section model to obtain a same-grade simulation parameter library; compares and simulates the same-grade simulation parameter library to obtain a parameter simulation result, enhances defects of the roadway measurement point according to the parameter simulation result, and obtains an optimal support scheme; the support scheme design efficiency and accuracy are improved, the roadway stability and safety are improved, excessive support or insufficient support is avoided, and support economy is optimized.

A three-dimensional adaptive cellular automaton corrosion evolution and performance degradation simulation method, belonging to the field of corrosion evolution simulation, comprises the following steps: S1: determining corrosion environment parameters and corrosion evolution parameter patterns; S2: generating m sets of corrosion environment parameters based on the corrosion environment; S3: performing n-fold cellular automaton simulations of the current time step using each set of corrosion environment parameters based on the results of the previous time step, and calculating the accuracy of the corrosion evolution parameter simulation under each set of parameters; S4: extracting a%m groups with high accuracy from the m sets of corrosion environment parameters, exchanging adjacent array subparameters with a probability of b%, and varying subparameters with a probability of c%, generating (1-a%)m groups of parameters, and incorporating the extracted a%m groups into the newly generated m sets of parameters; S5: repeating steps S3-S4 until the target accuracy is reached; S6: if the target accuracy is still not reached after k repetitions, each cell undergoes three-way binary fission and S2-S5 are re-executed. This method can adaptively optimize corrosion parameters to improve accuracy.

The utility model relates to the technical field of traceability of electric vehicle power battery detection equipment, and specifically provides a parameter simulation-based traceability device for electric vehicle power battery detection equipment. The traceability device comprises traceability equipment and a charging female seat, the traceability equipment comprises a standard voltage source and a control switch, the standard voltage source is electrically connected with the charging female seat through the control switch, the charging female seat is electrically connected with detection equipment, and the detection equipment refers to electric vehicle power battery detection equipment; the standard voltage source is used for simulating the ideal voltage of the power battery of the electric vehicle in the traceability configuration stage; and the detection equipment is used for acquiring the ideal voltage of the power battery of the electric vehicle and performing traceability configuration based on the ideal voltage of the power battery of the electric vehicle and the traceability equipment. According to the utility model, the ideal voltage of the power battery of the electric vehicle is simulated through the standard voltage source, so that the matched connection of the detection equipment and the traceability equipment is realized, and the technical problem that the traceability device cannot simulate the relevant parameters of the power battery of the electric vehicle is solved.

The invention relates to a tunneling machine duct piece design technology, discloses a three-dimensional parameterization simulation calculation method for a tunneling machine duct piece structure, and solves the problems of complex manual modeling, low efficiency, time-consuming calculation and the like in an existing tunneling machine duct piece modeling and simulation scheme based on a simplified three-dimensional model. The method comprises the following steps: calling a model initialization command set to initialize a modeling environment, and calling a basic parameter command set to establish a basic parameter system; the load analysis command set is called to calculate and process the formation pressure borne by the duct piece, and the load borne by the duct piece is obtained; calling the structure modeling command set to construct and obtain a heading machine three-dimensional segment calculation model comprising nodes, beam units and spring units; calling a calculation analysis command set to carry out automatic simulation solving processing on the three-dimensional segment calculation model, and automatically outputting a calculation result; and obtaining a calculation result, calling a reinforcement analysis module and a structure calculation report module, and automatically obtaining recommended segment reinforcement information and a structure calculation report.

The present invention discloses an intestinal flow field modeling method and device based on bidirectional fluid-solid coupling. The method comprises: S1, collecting intestinal multimodal data; wherein the multimodal data includes geometric parameters, motion characteristics, content statistics and wall stress and strain data of the intestine; S2, reconstructing a three-dimensional geometric model of the human intestine; S3, preprocessing the established intestinal geometric model by format conversion and simplification and modification; S4, dividing the preprocessed model into a fluid domain and a solid domain, and establishing a bidirectional fluid-solid coupling model architecture; S5, performing fluid domain simulation settings: simulating multiphase flow contents and setting a fluid simulation model; S6, performing solid domain simulation settings: setting intestinal wall material parameters and simulating intestinal movement; S7, achieving bidirectional fluid-solid coupling and simulating the intestinal flow field. The method takes into account the bidirectional interaction between the intestinal wall solid domain and the intestinal content fluid domain, achieving more accurate intestinal flow field simulation.