15 results about "Macroscopic model" patented technology

The application relates to the technical field of energy storage safety, and discloses a multi-scale multi-physical-field energy storage emergency space twin modeling method, which comprises the following steps: presetting macro low-dimensional and micro high-dimensional models in an edge computing device, measuring residual computing power, setting a concurrent threshold, calculating space-time gradient characteristics by using a macro model based on annular buffer data to mark a candidate region, calculating a thermodynamic urgency index, sorting the candidate region, and screening out an activated region, calling historical data to drive a micro model to perform super-real-time operation, completing internal state initialization, establishing a heterogeneous model physical boundary bidirectional coupling by using flux impedance matching, outputting a fault evolution prediction result, and generating a fixed-point emergency control instruction. By means of thermodynamic urgency scheduling and boundary coupling technology, the application solves the high-fidelity simulation problem under the condition of limited computing power on the edge side, and improves the prediction accuracy and response speed of the multi-scale multi-physical-field energy storage emergency space twin modeling.

The application discloses a kind of coupling molecular dynamics first principle's gas cooled reactor cladding surface particle adsorption calculation method, steps are as follows: (1) based on computational fluid dynamics and particle discrete phase model establishes numerical simulation framework, including cladding, break, flow channel modeling, grid drawing, boundary condition setting;(2) according to the first principle of molecular dynamics, the binding surface energy of fission product molecules released into the gas gap and the cladding material molecular base is calculated;(3) establish the particle deposition model including particle's own attribute, effective modulus, relaxation time and surface energy;(4) the binding surface energy is implanted into the particle deposition model, and the particle deposition model is used as the wall boundary, and the gas-solid two-way coupling calculation of particle deposition is carried out.The method solves the problem that traditional macroscopic model depends on empirical parameters, realizes high-precision simulation based on physical mechanism, reveals the mechanism of micro-interface properties on macroscopic deposition behavior, and predicts complex deposition morphology.

This invention belongs to the field of metal smelting technology and relates to a method for predicting alloy element segregation in large-scale titanium alloy VAR ingots. The method includes: acquiring VAR furnace structure data; establishing a macroscopic FE model based on the VAR furnace structure data to calculate the ingot temperature field distribution; acquiring microscopic CA grids and state parameters; establishing a microscopic CA model using the CA grids and state parameters to calculate the microscopic solute concentration distribution; mapping the ingot temperature field distribution to the microscopic CA model for FE-CA cross-scale coupling to generate an FE-CA cross-scale coupled model for simulating the VAR process under different process parameter combinations, and generating an optimal process parameter combination with the objective that the maximum segregation degree of the target element should not be less than a preset threshold. This invention simulates the solidification process under different process conditions to predict the occurrence and development of compositional segregation in large-scale VAR titanium alloy ingots, thereby reducing segregation.

The invention discloses a novel buffer layer material evaluation method for solving the problem of buffer layer ablation, and belongs to the field of electrical engineering. The method comprises the following steps: acquiring a two-dimensional fault slice of a buffer layer material by adopting CT scanning, and reconstructing a microscopic model reflecting a real pore and fiber structure through a volume data method through AI artifact removal, filtering and ternary processing; discretizing the model into a finite element mesh, optimizing the finite element mesh, and embedding the finite element mesh into a cable macroscopic model to construct a macro-micro coupling three-dimensional finite element model; accelerating simulation by adopting local grid refinement, parallel calculation, model order reduction or a reasonable selection solution method, and calculating electric field and current distribution in an electricity-heat-force multi-physics field coupling environment; and by taking the polyester non-woven fiber water-blocking tape as a reference, comparing the ablation resistance of the novel buffer material, and judging whether the ablation resistance of the novel material reaches the standard or not. According to the method, quantitative evaluation from a real microstructure to system performance is realized, and the method has the advantages of high precision, good efficiency and high engineering applicability.

This invention discloses a layered design method for snow surface overlay on ice-structured load-bearing structures, relating to the field of ice and snow engineering technology. The method includes the following steps: S1, determining the design constraints and performance indicators of the snow surface overlay based on target working conditions and environmental data; S2, obtaining the microstructural parameters of the snow material to be laid, including initial porosity, ice crystal size distribution, coordination number, and contact geometry. This invention establishes a cross-scale mechanical performance evolution model to accurately capture the microscopic mechanisms of ice crystal sintering, particle creep, and fatigue damage of snow material under long-term load and temperature, solving the problem of performance prediction deviations caused by the inability of existing macroscopic models to reflect microscopic evolution. By constructing a quantitative mapping relationship between microstructural parameters and macroscopic mechanical properties, combined with thermo-coupling load history simulation, accurate performance evolution data of the overlay can be obtained.

The application discloses a metal sealing structure leakage prediction method and system, first, a macroscopic service finite element model is constructed according to the structure and service parameters of the sealing structure, the service deformation behavior is simulated, the model is based on the rotation symmetry characteristic of the sealing structure, the axisymmetric shell model is adopted in the finite element software, the cross section is simplified, the grid is divided and the flange movement is set. Then, a microscopic crystal plastic model with a rough surface is constructed based on the surface roughness, the model construction and grid processing are carried out by considering the material microstructure and characteristics. The deformation amount of the contact position is extracted from the macroscopic model as the boundary condition of the microscopic model to simulate the microscopic deformation. Finally, the distance between the rough surface mean line and the flange surface distance is determined from the microscopic model as the gap height, and the internal and external pressure difference in the service of the sealing structure is combined to calculate the leakage amount of the sealing structure. In this way, the simulation result is more close to the actual situation by combining the macroscopic and microscopic models, and the leakage prediction precision and efficiency of the sealing structure are improved.

This invention provides a method for generating training simulation scenarios based on road driving tests, relating to the field of human-computer interaction technology. The method includes: extracting desensitized visual trajectory sequences to obtain first data representing the spatiotemporal uncertainty of the local visual field; obtaining second data representing the graph topological impedance of the global road network; performing cross-covariance fusion calculation, converting the first spatiotemporal uncertainty data into pressure source terms and substituting them into a macroscopic model for solution, generating a spatiotemporal covariance tensor; generating a first rendering instruction based on the diagonal high-frequency components of the tensor orthogonal decomposition, triggering the dynamic instantiation of a 3D interactive object; and generating a second inference instruction based on the off-diagonal low-frequency components to update the global traffic flow density and perform closed-loop iteration. This method overcomes the technical limitations of the separation between microscopic visual interaction and macroscopic traffic inference, constructing a highly robust, cross-scale spatiotemporal coupling computation mechanism to achieve an ecological closed-loop evolution of high-fidelity simulation scenarios triggered by vision.

This invention provides a method and system for analyzing the mechanism of roadway floor heave, belonging to the technical field of roadway floor heave mechanism analysis. The invention first deploys multiple monitoring points within the roadway to collect real-time monitoring data, including pressure, vibration, temperature, and humidity data. Based on the monitoring data, the discrete element method and the finite element method are applied to construct microscopic and macroscopic models of the roadway. A state assessment is performed on historical monitoring data and corresponding contact forces and total stresses using an expert scoring method, constructing a risk prediction model based on the random forest algorithm. The model predicts the current state of each monitoring point to identify those with anomalies. The floor heave risk index at the abnormal monitoring points is analyzed to determine whether an early warning should be issued. This method effectively integrates multi-source data and model analysis, providing a scientific basis for roadway safety. Through this method, early warning of roadway floor heave risk can be achieved, helping to reduce safety hazards.

This invention discloses a multi-scale wear analysis method based on fractal principles and molecular dynamics. The method establishes a rough surface model for the required surface roughness using fractal principles, performs contact simulation to obtain the contact pressure distribution, and calculates the microscopic wear force load based on the contact pressure distribution. It then performs molecular dynamics wear simulation under the corresponding load to analyze the microscopic wear mechanism and calculate the microscopic tangential force. Based on the microscopic shear stress, it calculates the shear work and the actual interfacial shear strength of the material, and calculates the macroscopic wear volume based on the shear work of all contact nodes under the macroscopic slip distance. This invention establishes a macroscopic model based on fractal principles, solving the problem that wear analysis does not consider the actual morphology under different surface roughnesses. Furthermore, this invention can realize multi-scale wear calculation and analysis from macroscopic contact to microscopic wear and back to macroscopic wear, solving the problem that wear analysis is mostly performed at the same scale and does not reflect multi-scale characteristics.

The invention belongs to the technical field of metal smelting, and relates to an alloy element segregation prediction method for a large-specification titanium alloy VAR ingot, which comprises the following steps: acquiring VAR furnace structure data, and establishing a macroscopic FE model based on the VAR furnace structure data for calculating ingot blank temperature field distribution; a microscopic CA grid and state parameters are obtained, and a microscopic CA model is established through the CA grid and the state parameters and used for calculating microscopic solute concentration distribution; and the ingot blank temperature field distribution is mapped to the microscopic CA model for FE-CA cross-scale coupling, an FE-CA cross-scale coupling model is generated and used for simulating the VAR process under different technological parameter combinations, and the optimal technological parameter combination is generated with the target that the maximum segregation degree of a target element needs to be not smaller than a preset threshold value. According to the method, the solidification process under different process condition parameters is simulated, and the generation and development of component segregation of the large-specification VAR titanium alloy cast ingot are predicted, so that the generation of segregation is reduced.

The invention discloses an agricultural film residual pollution monitoring method based on satellite-ground remote sensing data, and relates to the technical field of remote sensing monitoring and image processing, in particular to an agricultural film residual pollution monitoring method. The objective of the invention is to solve the problem that the existing satellite and unmanned aerial vehicle monitoring system cannot evolve automatically during operation and is always difficult to find an optimal balance point between the coverage range and the monitoring precision, so that the monitoring accuracy of agricultural film residue pollution is low. The method comprises the following steps: 1, collecting ground feature samples to construct a spectrum library, and determining a characteristic wave band for distinguishing agricultural film residues; 2, fusing satellite images and regional statistical data, and carrying out macroscopic inversion to delimit a high-risk key monitoring region; 3, planning a route according to the key area, and controlling the unmanned aerial vehicle to obtain hyperspectral image data; 4, analyzing the hyperspectral data by taking a laboratory spectrum library as a benchmark, and calculating the residual abundance of the agricultural film; and 5, performing scale conversion on the microcosmic data to serve as a true value, and feeding back and correcting satellite macroscopic model parameters so as to realize dynamic optimization.

This invention relates to a reactor temperature control system, comprising a macroscopic model prediction and control unit, a local temperature field analysis and dynamic compensation unit, a multi-source data fusion sensing unit, an adaptive safety decision-making unit, and a control command fusion execution unit. This invention enables simultaneous and precise tracking of the overall reactor temperature and high spatial homogenization of the internal temperature field, while embedding active safety protection throughout the entire process, thereby significantly improving the product quality, consistency, and operational safety of complex chemical reactions.

This invention relates to the field of situational awareness technology, and in particular to a multi-scale digital twin early warning system. The system collects target early warning data through a data acquisition module, performs hierarchical denoising and feature extraction through a data processing module, dynamically feeds micro-evolutionary information to a macro-model through a multi-scale modeling module, constructs a quantitative risk index through a risk assessment module, and integrates and dynamically visualizes multi-source data through a situational awareness module. This transforms complex equipment status information into intuitive situational awareness and presents risk levels in real time, significantly improving the efficiency of early warning.

This invention discloses a method and system for stability analysis of tunnel excavation faces in goaf areas, belonging to the fields of geotechnical engineering and tunnel construction safety. The method first generates a macroscopic stratigraphic model of the goaf area containing microscopic features based on geological survey data, and extracts representative microscopic units from it. Then, numerical limit analysis is performed on the representative microscopic units to obtain equivalent macroscopic strength parameters and their statistical characteristics. Next, a random field is generated based on the statistical characteristics and discretized to a macroscopic grid to construct a heterogeneous macroscopic model. Finally, macroscopic limit analysis is performed on the heterogeneous macroscopic model to obtain the stability evaluation results of the excavation face. This invention realizes the cross-scale transfer of mechanical parameters from microscopic to macroscopic levels, fully considers the spatial random variability of rock mass parameters, and can efficiently and reliably quantify the stability state of the tunnel excavation face, providing a scientific basis for the safe construction of tunnels traversing goaf areas.

The application relates to the technical field of intelligent transportation, and particularly discloses a traffic flow prediction system based on travel chain dynamic evolution. The system comprises travel chain real-time sensing and reconstruction modules, travel decision behavior dynamic deduction modules, group travel demand evolution calculation modules and macroscopic traffic flow dynamic prediction modules which are connected in sequence. Individual travel chains are sensed and reconstructed in real time, individual behaviors are dynamically deduced, group demands are aggregated based on agent simulation, and a macroscopic model is driven to perform prediction. The system builds a complete technical closed loop from real-time sensing of micro individual behaviors to dynamic prediction of macro road network flow. Through cooperation of the travel decision behavior dynamic deduction modules and the group travel demand evolution calculation modules, the system realizes fine simulation of group travel behavior emergent effect under a sudden situation.