383 results about "Computational simulation" patented technology

The invention discloses a three-dimensional finite element simulation method for a complex slope excavation unloading process, which comprises the following steps of: 1) constructing a three-dimensional model of a complex slope, and establishing a finite element grid; 2) inputting boundary conditions of the model and material parameter information of each stratum; 3) calculating and simulating an initial stress field of the slope before excavation; (4) according to the initial stress field, the unloading load of the slope excavation part is calculated; (5) finite element calculation is conducted on stress deformation of the excavated slope; according to the method, the high-precision three-dimensional finite element model is established, various material parameters and actual boundary conditions are combined, the stress change and the unloading effect of the slope in the excavation process are simulated, the stress redistribution in the unloading process is accurately reproduced, the prediction precision of local instability and stress concentration areas is improved, and the prediction accuracy of the slope is improved. Therefore, a scientific basis is provided for safety assessment of slope excavation.

The invention relates to a pollutant concentration diffusion simulation method based on grid optimization and self-regulation. The method comprises the following steps: carrying out basic grid division on a simulation area to obtain a basic grid; calculating a pollutant concentration field of the simulation area according to the spatial position and the pollutant concentration value of the monitoring station; generating a concentration distribution matrix according to the pollutant concentration field of the simulation area, and then dynamically adjusting the grid density of the basic grid; calculating the calculation complexity of each grid region by using the grid density of the adjusted basic grid, carrying out pollutant concentration calculation task allocation according to a cloud platform and a weighted polling algorithm, and forming a pollutant concentration distribution prediction result of the simulation region by a pollutant concentration prediction result of each grid; and dynamically adjusting a pollutant concentration distribution prediction result according to the Kalman filtering and the obtained real-time environment data to obtain a final pollutant concentration prediction value. By adopting the method, the precision and the real-time performance of pollution diffusion simulation can be improved.

The invention discloses a simulation method and system based on multi-field coupling and dynamic grid processing, and belongs to the field of computational simulation, and the method comprises the steps: building and solving a coupling physical field model: carrying out finite element spatial discretization on a solving domain, building and solving a coupling partial differential equation set which at least comprises a temperature field, a displacement field and a stress field, and carrying out the finite element spatial discretization; obtaining numerical solutions of the physical fields in the current state; carrying out progressive unit removal based on a physical criterion; and finally, grid data structure updating and solver synchronization are executed. According to the method, the metal material can be gradually removed when the physical quantity reaches the critical condition, and the grid change is dynamically and robustly processed in the process.

The invention provides an evapotranspiration simulation method and system based on a PINN neural network, and belongs to the technical field of evapotranspiration calculation simulation. The method comprises the following steps: acquiring multi-source meteorological data and high-resolution remote sensing image data of a research area, and constructing an input data set; carrying out standardization processing on the input data set, and respectively generating a remote sensing image grid and a meteorological data grid; the grids are input into a trained PINN model, the PINN model performs feature extraction on the remote sensing image grids and the meteorological data grids by using multilayer convolution, and a feature map representing the evapotranspiration process is generated; embedding a surface energy balance equation into a loss function to realize physical constraint on the model; and combining the extracted features with a physical constraint result to generate a space-time distribution diagram of evapotranspiration. And performing visual display on the space-time distribution diagram based on a GIS technology to obtain an evapotranspiration intensity diagram and a change trend diagram of the research area. The problem that a traditional method lacks physical consistency is solved, and universality is enhanced.

The invention relates to a flood influence simulation analysis method and device, computer equipment and a storage medium. The method comprises the following steps: determining a target drainage basin, and determining sub-drainage basin units and sub-drainage basin nodes in regional data of the target drainage basin; constructing a plurality of hydrological models based on the relationship between the sub-basin units and the sub-basin nodes; determining a simulation analysis drainage basin in the target drainage basin, and determining at least one hydrological model in the simulation analysis drainage basin; calculating basin parameters in the simulation analysis basin based on the hydrological parameters in the simulation analysis basin and the at least one hydrological model; constructing a flood simulation model based on the topographic data of the simulation analysis drainage basin, performing flood simulation according to the flood simulation model and the drainage basin parameters, and performing analysis based on a flood simulation result to determine a flood influence; and the flood simulation model adopts a conservation form of a two-dimensional shallow water equation. The method can accurately reflect the spatio-temporal change of the confluence producing mechanism in the rainstorm flood process of the watershed.

An acquisition unit (15a) acquires real data. A calculation unit (15b) performs a simulation using a predetermined parameter and calculates a simulation result. A selection unit (15c) compares the simulation result with the real data corresponding to the simulation result, and selects a parameter such that the simulation result is assimilated with the real data, and the calculation unit (15b) performs the simulation using the selected parameter as the predetermined parameter.

The invention relates to the technical field of computational simulation, in particular to a fluid mechanics calculation method and system based on CFD simulation optimization. The method comprises the following steps: acquiring a flow field CFD original simulation model corresponding to fluid mechanics; generating a fluid mechanics flow field key grid area by setting the size of a flow field calculation domain grid and performing calculation domain grid division and flow field key area identification; the method comprises the following steps of: obtaining a grid length-width ratio and torsion resistance corresponding to each grid subunit in the grid, and carrying out grid constraint updating to generate a fluid mechanics flow field updating grid region; a corresponding Reynolds number and a turbulence scale are obtained through the fluid mechanics flow field updating grid area, turbulence model dynamic selection modeling is carried out, and a flow field grid area dynamic turbulence model is generated; and carrying out finite volume division and error simulation correction optimization on the dynamic turbulence model of the flow field grid region to obtain a corrected fluid mechanics flow field quantity calculation result. According to the method, collaborative improvement of fluid mechanics calculation precision and efficiency can be realized.

The invention relates to the field of temperature regulation and control, in particular to an intelligent regulation and control method and system for the temperature of a test box, and the method comprises the steps: calculating an optimal disturbance range in a simulated annealing algorithm, and obtaining the temperature in the test box in a next time period through the simulated annealing algorithm; the calculation method of the optimal disturbance range comprises the steps that a data set is obtained, the data set comprises multiple pieces of temperature data in the current time period, the dispersion degree of the data in the data set is calculated, the disturbance range optimization factor in the current time period is calculated, and the disturbance range optimization factor is in positive correlation with the dispersion degree. And taking a product of the disturbance range optimization factor and a preset disturbance range as an optimal disturbance range. The method has the effect of improving the calculation efficiency and the control precision of the simulated annealing algorithm.

The invention relates to the technical field of data processing, in particular to a parameter optimization method for a powder laser 3D printing forming process, which comprises the following steps: determining a solution space of a particle swarm algorithm, performing finite element analysis on each process parameter, determining an objective function of the particle swarm algorithm, and obtaining simulated particles and actually measured particles in the solution space, in the process of carrying out iterative training on a pre-constructed support vector machine by utilizing the actually measured particles, calculating the credibility of the simulated particles during any training, and when the product of the credibility and the normalized simulated fitness value is greater than a preset value and the actually measured fitness value of the simulated particles is greater than a conversion threshold value, judging that the simulated particles are not subjected to the training; and taking the simulated particles as actually measured particles in the subsequent training process, repeating the training process, and obtaining the target process parameters after the training is completed. According to the method, the accuracy of the determined target process parameters can be improved while the calculation amount and the time cost are reduced.

The invention relates to the technical field of PLC control, in particular to a B / S architecture-based digital twin virtual debugging system and method for a transmission line. The system comprises a three-layer B / S (Browser / Server) architecture consisting of a PLC (Programmable Logic Controller) simulation layer, a business logic layer and a three-dimensional visualization layer, the PLC simulation layer is used for operating a PLC program to obtain a feedback signal of the controlled equipment, simulating the control logic of the PLC to the controlled equipment based on the feedback signal, and sending a control signal to the service logic layer; the business logic layer is used for acquiring the control signal and carrying out business logic operation based on the control signal and the feedback signal so as to calculate and simulate the movement of the controlled equipment and obtain real-time position data; and the three-dimensional visualization layer is used for displaying the operation state of the controlled equipment based on a pre-constructed virtual model of the controlled equipment and the real-time position data so as to display the operation result of the PLC program, generating a feedback signal based on a virtual sensor on the virtual model of the controlled equipment, and sending the feedback signal to the business logic layer.

The invention relates to the technical field of power grid topology data updating, in particular to a power distribution network topology identification self-iteration updating method, which comprises the following steps of: acquiring a multi-layer topology structure of a power distribution network, adopting a random walk algorithm and considering the influence of edges and weight information of the edges on walk; performing multi-step migration on nodes in the same-layer power distribution network topological structure in the multi-layer topological structure of the power distribution network, calculating access probabilities among different nodes in a simulation process, and marking node pairs with the access probabilities exceeding a preset access probability threshold as potential associated nodes in the same layer; and analyzing relevance among nodes in the cross-layer power distribution network topological structure according to the same-layer potential relevance nodes, and generating same-layer and cross-layer potential relevance node information. According to the method, the problem that the incidence relation between the nodes in a complex network is difficult to accurately capture is solved by extracting the nodes, the paths and the weight information of the nodes in the multi-layer topological structure of the power distribution network and determining the potential correlation between the nodes in combination with a random walk algorithm.

The invention discloses a parallel computing simulation method for thermal exploitation of a buried pipe well group in a geothermal reservoir, which comprises the following steps of: dispersing a grid volume unit of a buried pipe by adopting a parallel finite element unit method, and simplifying the buried pipe and circulating fluid in the pipe into a one-dimensional linear finite element unit; constructing a plurality of pipeline flow models arranged in an array, and combining the in-pipe one-dimensional linear units and the out-pipe three-dimensional volume units to obtain a well group type pipeline flow geometric model; a parallel finite element unit method is adopted to be combined with a non-isothermal pipeline flow physical field, an underground water seepage physical field and a porous medium heat transfer physical field to conduct multi-physical-field coupling, and a well group type pipeline flow numerical model is obtained; fluid flow and convective heat transfer in the buried pipe and pipe wall heat conduction are solved in a combined mode; and performing factor sensitivity analysis by changing different thermophysical parameters of the rock-soil body and heat exchange characteristic factors of the buried pipe well group. The invention provides a new method for researching fluid flowing and heat transfer behaviors of the buried pipe well group, and provides a new idea for optimal design and efficient simulation of thermal exploitation of the buried pipe well group in a geothermal reservoir.

Embodiments of present disclosure provide methods and systems for increasing transaction approval rate. Method performed includes accessing transaction features and determining via fraud model and approval model, first and second set of rank-ordered transaction features. Method includes computing difference in ranks of transaction features and determining set of utilized and unutilized transaction features and generating simulated authorizing model and computing simulated transaction approval rate and simulated fraud transaction rate for simulated authorizing model. Method includes generating plurality of proxy authorization models. Method includes computing transaction approval rates and fraud transaction rates for each of plurality of proxy authorization models and computing an increase in transaction approval rate and change in fraud transaction rate for each of plurality of proxy transaction approval models. Method includes determining one or more recommended transaction features from set of unutilized transaction features and transmitting one or more recommended transaction features to authorizing entity.

The invention relates to the technical field of sensor fault detection, in particular to a brushless direct current motor sensor fault detection method and system based on a neural network. Comprising the following steps: setting a detection priority of each sensor, and carrying out fault detection in a preset time period; predicting the path range of the equipment at the next moment by combining the sensing information, the position information, the equipment control information and the neural network path prediction model at the previous moment, and obtaining the path deviation through the deviation between the actual path and the prediction range; simulating a motor parameter based on the control information, the path deviation and the motor attribute information, calculating the deviation degree of the simulation parameter and the real-time sensing information, and identifying a fault sensor; and dynamically adjusting the detection priority according to the deviation degree, and entering a fault-free sensor mode when a fault occurs. The problem of dynamic detection of the motor is solved, the detection efficiency and precision are improved, and the real-time performance and reliability of motor control are guaranteed.

A simulator of an embodiment is an electrolysis device simulator configured to simulate, by computation, the performance of a first electrolysis cell stack including one or more electrolysis cells each including a cathode configured to perform a reduction reaction and an anode configured to perform an oxidation reaction. It includes an arithmetic unit configured to perform an arithmetic operation using a first variable group representing at least one of flooding and salt precipitation in the first electrolysis cell stack, in a computational algorithm implemented in the simulator of the embodiment.

The invention discloses a CFD (computational fluid dynamics) boundary processing acceleration method based on GPU (graphics processing unit) parallelism, and belongs to the technical field of fluid mechanics related calculation. The problem that in the prior art, a traditional CFD boundary processing acceleration method is low in calculation efficiency is solved. The method comprises the following steps: generating a computational grid required for simulating a flow field, and reading grid information and boundary condition information of computational simulation; initializing a flow field according to the calculation parameters, copying flow field data and flow field boundary information from a main memory to a video memory, establishing a boundary pointer array in the video memory, and instantiating a boundary pointed by each pointer; according to the boundary pointer array, the flow field data and the flow field boundary information, time step cycle calculation is carried out by utilizing a GPU, and physical quantity updating of a boundary virtual unit corresponding to the thread is realized; and after time step cycle calculation convergence, video memory flow field data are copied to a main memory, and flow field simulation calculation is completed. The method effectively improves the calculation efficiency, and can be applied to CFD boundary processing.

The invention discloses a laboratory intelligent agent construction method and system based on artificial intelligence, and relates to the technical field of intelligent laboratories. In order to solve the problems of scattered laboratory data information, low scientific and technological resource matching efficiency, lack of a unified AI driving platform and the like in the prior art, a core agent is constructed by introducing machine learning or an artificial intelligence architecture, and digital access and resource pooling are carried out on scientific research total factors such as infrastructures, software and hardware, human property and the like. The intelligent agent is based on semantic alignment and inference rules, dynamic intelligent configuration of resources such as field observation, experimental analysis and computational simulation is achieved, and finally a full-life-cycle intelligent management and scientific research environment integrating equipment perception, intelligent control and business application is formed. According to the method, resource islands are effectively broken, the resource utilization efficiency is improved, a novel scientific research normal form of'big data + AI + model 'is promoted, and systematic support is provided for refined and automatic management of laboratories.

The invention discloses a building heat emission model modeling method and device, a terminal and a medium, and the method comprises the steps: firstly collecting building structure data and heat emission environment data of a target area, calculating artificial emission heat emitted by an air conditioner outdoor unit assembled on a building through an enthalpy difference method, and superposing the artificial emission heat to obtain dynamic heat emission data; dividing a heat storage space by taking an air conditioner position as an original point, and establishing a temperature change calculation formula in combination with a wind speed condition to calculate air flux change caused by a hot-pressing effect; thirdly, layering the urban canopies according to the vertical height, calculating the hot pressure difference formed by the air density difference of each layer, and constructing an interlayer heat transfer relationship; finally, integration of the coupling relation between the temperature rise data of the heat storage space and the thermal layer is achieved, the heat emission distribution and the temperature rise trend of the building in the target area under different wind speed conditions are simulated, and the technical problem that an existing heat emission temperature rise calculation simulation method is large in calculation error is solved.

Disclosed is a neural network computing device. The neural network computing device includes a neural network accelerator including an analog MAC, a controller controlling the neural network accelerator in one of a first mode and a second mode, and a calibrator that calibrating a gain and a DC offset of the analog MAC. The calibrator includes a memory storing weight data, calibration weight data, and calibration input data, a gain and offset calculator reading the calibration weight data and the calibration input data from the memory, inputting the calibration weight data and the calibration input data to the analog MAC, receiving calibration output data from the analog MAC, and calculating the gain and the DC offset of the analog MAC, and an on-device quantizer reading the weight data, receiving the gain and the DC offset, generating quantized weight data, based on the gain and the DC offset.

The invention relates to the technical field of cave three-dimensional modeling, in particular to a cave three-dimensional modeling method and system based on multi-sensor fusion, and the method comprises the steps: recognizing a simulation feature network point set, calculating the simulation precision according to the simulation feature network point set and an actual verification network point set, carrying out the point drawing according to the area of a unit test grid and the simulation precision, and carrying out the calculation of the simulation precision. Performing regression analysis on the area precision point set to obtain an area precision regression line; constructing a triangular plane current grid according to a current to-be-measured cave region; performing inner wall secondary sensing sampling on the three-dimensional unit current grid according to predicted regression precision to obtain a secondary three-dimensional sampling point set; and performing three-dimensional correction on the current grid of the three-dimensional unit by using the secondary three-dimensional sampling point set to obtain an initial cave three-dimensional model, and fusing the cave sensing image and the initial cave three-dimensional model to obtain a target cave three-dimensional model. According to the invention, the laser sampling efficiency and the cave three-dimensional modeling precision can be improved.

The application relates to the technical field of calculation simulation of ship hull propulsion research, in particular to a simulation model convenient for hydrodynamic calculation of a full-rotation double-propeller ship, which comprises a plurality of groups of water pressure sensors arranged on the circular arc outer wall of a detection column and facing openings, a drainage long groove arranged on the circular arc outer wall of the detection column and located at the openings, a water inlet pipe of an external water pump assembly arranged in the detection column, and a lifting port arranged at one end of the water inlet pipe and capable of sliding along the drainage long groove to adjust the height, wherein the beneficial effects are that the water flow direction and flow rate in the pool model are accurately controlled through water pumping and high-pressure water inflow in the symmetrical direction, the data detection range of the test is improved, the simulation equipment provided with the water pressure sensors and the displacement sensors is arranged, so that the data in the test process can be conveniently collected, the position of the simulation small ship can be accurately collected through the coordinates established by the transparent grid plates, and the test accuracy is greatly improved.

The invention relates to the technical field of workpiece production data processing, in particular to a production data processing method and system based on a data medium table, and the method comprises the steps: installing r * c pressure sensors in a die to collect the pressure data of a plurality of positions in the die; performing first curve fitting on pressure data acquired by the pressure sensor in a local range to obtain a first curve, calculating simulated pressure data by adopting an interpolation method, and performing second curve fitting in the local range to obtain a second curve; calculating the original noise expression degree according to the pressure data collected by the same pressure sensor, and calculating the corrected noise expression degree according to the pressure data collected by the adjacent sensors at the same moment and the original noise expression degree; and according to the modified noise expression degree, screening to obtain the pressure data to be filtered and filtering the pressure data to be filtered. The technical problem that in the prior art, when a die is used for workpiece production, the data processing efficiency is low is solved.

A method can include receiving property data for a simulation model; analyzing the property data with respect to geometry of the simulation model to select a matrix preconditioner scheme using a machine model; and executing a computational simulator that implements parallel processing based on application of the matrix preconditioner scheme to a matrix representing the simulation model to generate simulation results based on the property data.

The invention discloses a Fe-Mn-C alloy interstitial atom potential function construction method based on a first principle and machine learning, and belongs to the technical field of material science and computational simulation. The construction method comprises the following steps: firstly, constructing a Fe-Mn-C alloy interstitial element atomic structure model, carrying out structure optimization on the interstitial element atomic structure model by utilizing a first principle, then carrying out first principle molecular dynamics (AIMD) multi-temperature sampling on the model after the structure optimization, and dividing a training set and a verification set; and finally, machine learning is conducted, and the Fe-Mn-C alloy gap potential function is output. According to the construction method, unification of high precision and high efficiency of the potential function is achieved, and the obtained Fe-Mn-C alloy gap potential function can be applied to research of a face-centered cubic (FCC) Fe-Mn-C alloy.

The Neuromorphic Emulation Constructor AI (NECA) is an artificial intelligence technology for building a Personal Neuromorphic Emulation (PNE), a detailed model of an individual's brain that is anatomically correct, capable of learning and plasticity, and able to emulate the person's brain electrical activity and behavior. The NECA accesses the neuroscience literature through automated search and acquisition technologies such as Google Scholar, and it assembles the knowledge of the brain's structure and function in ways that specify how to build and test the PNE.

The invention belongs to the technical field of geographic information science, and particularly relates to a Markov-FLUS model-based feedback land utilization change simulation method and system, and the method comprises the steps: firstly predicting an initial area target vector based on historical data and a Markov chain, and inputting the initial area target vector into a FLUS model to carry out the first space distribution simulation; by calculating the achievement degree of the simulation result and the area target, the space conflict type which cannot be achieved due to the space constraint is identified, the area target vector is dynamically corrected according to the space conflict type, and the corrected target is fed back to the FLUS model for iterative simulation until the result is converged. According to the method, the technical problem of disjunction of area prediction and spatial layout in a traditional coupling model is effectively solved, and the scientificity and accuracy of land utilization change simulation are remarkably improved.

A simulation method for a coating installation including:a) specification of geometric data of the component to be coated,b) specification of general coating parameters,c) specification of starting values of coating parameters to be adjusted, including a coating path and current spray patterns for the individual path points of the coating path, whereby the current spray patterns represent the coating thickness distribution on the component,d) program-controlled execution of a simulation loop, including:calculation of a simulated coating result by computational superimposition of the current spray patterns provided for the individual path points of the coating path, taking into account the degree of wetness,testing the simulated coating result, taking into account the degree of wetness,adjusting the coating parameters to be optimized and repeat the simulation loop if the simulated coating result is not satisfactory,.terminating the simulation loop if the simulated coating result is satisfactory.

The invention relates to the technical field of power transmission line verification, and discloses a point cloud-based power transmission line windage yaw double-parabola verification method, system and device and a medium, and the method comprises the steps: obtaining three-dimensional point cloud data of a power transmission line corridor, and extracting key ground feature parameters; according to the input target simulation working condition parameters, applying a wire state equation to iteratively solve the dynamic horizontal tension of the wire under the corresponding working condition, and combining a double-parabola mechanical model to calculate a three-dimensional space curve of the power transmission line under the windage yaw state; inputting a three-dimensional space curve and key ground feature parameters, and calculating a three-dimensional space minimum clearance distance between the power transmission line and a key ground feature in a simulated windage yaw state; and after comparison, a verification result is output. According to the method, the wind deflection and sag forms are accurately reconstructed by applying a double-parabola mechanical model, and dynamic simulation of different working conditions is realized in combination with a wire state equation. By combining high-precision mechanical analysis with an automatic verification process, the stability and safety of power grid operation can be improved.

The invention discloses an actual cost accounting system and method for simulation measurement and calculation, the system comprises a simulation product cost accumulation module, a simulation cost allocation module, a simulation actual cost calculation module and a simulation cost analysis module, and the method comprises the following steps: S1, carrying out data check before calculation; s2, processing non-direct product consumption difference; s3, apportioning the cost of the cost center; and S4, calculating the actual cost of the simulated product. According to the invention, the cost information about to occur is predicted according to the purpose of measurement and analysis, the product cost is automatically calculated according to a built-in measurement algorithm, the method is accurate and efficient, and a cost analysis report is timely issued based on an accounting result; the method supports multi-version business data acquisition, including data acquisition of actual business and pre-estimated business, calculates multi-version simulation cost on the premise of different businesses, the simulation cost covers manufacturing cost, sales cost and inventory cost, forms a real and accurate pre-estimated cost analysis report at any time, and supports real-time operation analysis.

The invention belongs to the technical field of power system power distribution network relay protection, and provides an overhead line tree touch fault simulation method, which comprises the following steps of: 1, establishing a circuit model based on physical characteristics of a current path when an overhead line is in contact with a tree; 2, dividing a physical process according to a tree medium state change rule in a tree touch fault development process, and establishing a resistivity dynamic model of each stage; 3, respectively calculating the correlation of the analog signals by using a Pearson's correlation coefficient method; step 4, constructing a criterion based on the average correlation coefficient # imgabs0 # in the step 3; according to the method, through full-stage dynamic modeling and refined simulation, the time-varying characteristic of state change of a tree medium is fully considered, and the physical authenticity of simulation and the continuity of stage transition are remarkably improved; meanwhile, multi-stage correlation verification and reliability criteria are introduced, and the simulation precision is quantified by using a Pearson's correlation coefficient method, so that the credibility and engineering applicability of a touch tree fault simulation result are enhanced.