611 results about "Grid partition" patented technology

The invention discloses a low-altitude airspace management method and system based on data analysis, and relates to the technical field of air traffic management and low-altitude airspace planning, and the method comprises the steps: 1, multi-scale dynamic grid division: adjusting the grid granularity in real time according to the aircraft density and environment complexity, generating a multi-scale grid by adopting an optimized quadtree data structure, and carrying out the multi-scale dynamic grid division; boundary smoothing processing is carried out on boundary areas of the grids with different scales; 2, intelligent airspace layering: dynamically adjusting the thickness of a height layer according to a risk score, and setting a buffer layer to enhance the flight safety; and 3, intelligent semantic annotation: giving dynamic semantic information such as risk levels and traffic priorities to the grid units, embedding airspace control regulations and flight rules, and realizing multi-source data fusion and real-time updating of semantic information. According to the method, the problems of static division limitation, boundary problem, insufficient real-time performance and the like in the prior art are solved, and the airspace resource utilization rate and the flight safety are improved.

The invention relates to the technical field of temperature equalization control, and discloses a temperature equalization control method and device for a liquid cooling over-charging system. The method comprises the following steps: carrying out grid division on the liquid cooling overcharge system, inputting thermophysical parameters, and obtaining a temperature field calculation matrix through finite difference time domain analysis; establishing a two-layer distributed control network of a station-level control layer and a pile-level control layer based on the temperature field calculation matrix; acquiring real-time temperature data of the two layers of distributed control networks, and performing temperature field mapping to obtain temperature field distribution data; performing linear prediction and nonlinear prediction calculation on the temperature field distribution data to obtain a temperature change trend and a temperature extreme point; the target temperature is calculated according to the temperature change trend and the temperature extreme point, the cascade PID controller is adopted to adjust the rotating speed of the cooling liquid pump, and the temperature balance control parameters are obtained, station-level and pile-level cooperative control is achieved, cooling resources among the multiple charging piles are reasonably distributed, and the overall cooling efficiency of the system is improved.

The invention discloses a grading, zoning and differentiating risk early warning method for mountain torrent disasters in medium and small watershed. Firstly, a drainage basin risk area is determined through mountain torrent disaster data analysis; the drainage basin delay time is calculated, the section water level and the drainage basin submerging range are simulated through the simplified hydrodynamic model, and quantitative analysis is conducted on the model; according to the method, a high-precision grid database is formed by combining unstructured grid division and risk source identification, and then clustering grading is performed on multi-dimensional characteristics of grids through a Gaussian mixture model (GMM) to obtain risk levels of the grids in a drainage basin. Finally, a differential early warning threshold value and a response strategy are formulated according to a grid partition grading result, and dynamic updating and linkage issuing are achieved on a GIS platform in combination with actual measurement data. According to the method, limited real conditions of small and medium-sized basin data and precision requirements of model simulation are taken into consideration, fine setting of the early warning threshold value is realized on the basis of grading and partitioning, and the accuracy of mountain torrent risk identification is also remarkably improved.

The invention provides an unmanned aerial vehicle autonomous flight path planning and image acquisition method and system, and relates to the technical field of unmanned aerial vehicle inspection. Firstly, through intelligent three-dimensional grid division and dynamic route planning, the coverage rate and efficiency of feature region monitoring are remarkably improved; secondly, due to the integration of real-time meteorological data and historical feature data, the pertinence and adaptability of acquisition are enhanced, and high-quality images can be obtained in a complex and changeable environment; through combination of real-time processing and ground deep learning analysis, the accuracy and efficiency of feature extraction are greatly improved; and on the basis of a self-adaptive supplementary sampling mechanism of the region of interest, quick response and accurate positioning of the suspected feature region are realized, and reliable data support is provided for subsequent detailed analysis and decision making. The method is not only suitable for identification tasks of various preset features, but also has good expansibility and flexibility, and can be adjusted and optimized according to different application requirements.

The invention belongs to the field of data analysis, and discloses a data analysis method for engineering consultation digital intelligent management, which comprises the following steps: mapping multi-project heterogeneous data to a unified three-dimensional space-time grid through space-time grid division to form a grid mapping data set; detecting data format and attribute conflicts based on neighborhood correlation analysis, and distributing calibration data through dynamic weight; missing values and abnormal fluctuations are processed by using a time sequence autoregression model and a smoothing technology, and a complete data set with continuous time is constructed by combining linear interpolation and multi-dimensional data fusion; key indexes are extracted to construct a digital mirror image containing spatial positions, time sequences and attribute association, real-time data are synchronized, and outlier grid points are corrected; and multi-scene operation conditions are constructed based on the mirror image data, and a dynamic adjustment scheme is realized. According to the method, heterogeneous data are integrated through space-time grids, digital twinning and multi-scene simulation technologies are combined, and full-period management and risk intelligent decision-making of engineering data are achieved.

The embodiment of the invention provides a low-altitude flight target conflict identification method and device, and the method comprises the steps: obtaining a basic scale of a space grid according to the features of a target airspace and the performance features of an aircraft, carrying out the multi-level grid division of the target airspace according to the difference logic and the basic scale of the space grid, and constructing a distributed grid reference space; performing height reference conversion and time reference synchronization on the flight data in the reference space, and associating the flight data with the reference space to obtain a target airspace index space; performing high layering on target airspace index space, performing secondary fine-grained flight conflict detection on each index space layer according to a preset time period, judging whether a potential flight conflict risk exists or not, if yes, acquiring real-time state data of the flight targets, predicting the minimum distance between the flight targets, judging whether an actual flight conflict risk exists or not, and if not, determining whether the actual flight conflict risk exists or not; the method can support the real-time conflict recognition of large-scale aircrafts, and improves the flight efficiency and safety of low-altitude aircrafts.

The invention relates to a mold 3D analogue simulation analysis method, which comprises the following steps: acquiring a three-dimensional CAD model of a mold, carrying out preprocessing and grid division, encrypting grids in a key area, calculating a stress value by utilizing finite element analysis, optimizing the grids through iterative calculation until a convergence requirement is met, and obtaining a stress distribution condition. A support vector machine regression algorithm is adopted to establish a nonlinear prediction model of stress characteristics and fatigue life, mold structure optimization is carried out, an optimization scheme is converted into a CAD model, a machining program is generated, accurate prediction and automatic optimization design of the fatigue life of the mold are achieved, the service life of the mold is prolonged, and the reliability of the mold is improved. And important technical support is provided for 3D analogue simulation analysis of mold design and manufacturing.

The invention provides a KKS code generation method and system based on space grid and three-dimensional data fusion, and the method comprises the steps: obtaining an original three-dimensional space data set covering a target facility region and a basic attribute data set of a corresponding facility, and carrying out the grid division of the original three-dimensional space data set; generating a multi-level spatial grid unit set matched with the spatial range of the target facility region, and performing association mapping on the basic attribute data set and the multi-level spatial grid unit set to generate a fusion data set with a binding relationship between the spatial position and the attribute information, and calling a pre-constructed KKS coding rule model to carry out coding generation on the fusion data set, obtaining a KKS coding sequence corresponding to the facility space position and attribute information, carrying out uniqueness verification, generating a verification result set containing a code passing verification and a code not passing verification, and carrying out adjustment processing to generate an effective KKS code. According to the method, the quality and practicability of KKS coding are remarkably improved.

The invention discloses a method for predicting dynamic distribution of an indoor air flow field and a temperature field of a building. The method comprises the steps of performing grid division on a target space to obtain three-dimensional grid units, setting boundary attributes of the target space and initial values of air field parameters, and then obtaining vector velocities of the three-dimensional grid units according to an air transfer velocity between two three-dimensional grid units, then, according to the pressure intensity, the temperature and the air transfer speed of the three-dimensional grid units at the current moment, the pressure intensity, the temperature and the air transfer speed of the three-dimensional grid units at the next moment are obtained, and finally, the air flowing moment of the target space is continuously updated and iterated. And the distribution result of the air flow field and the temperature field in the target space in the air flowing process is obtained. The method is beneficial to improving the directivity of heating and ventilation design or air conditioning system adjustment, so that the efficiency of indoor environment quality optimization is improved, and effective assistance is provided for improving the comfort of a user and reducing energy consumption.

The invention provides a grid clustering method and device, equipment and a storage medium, and the method comprises the steps: carrying out the layer-by-layer grid division of a target region represented by a target image according to each resolution corresponding to the target image, and obtaining N target grids corresponding to the target region; counting the grid density corresponding to each target grid to obtain N grid densities; sorting the N target grids according to the sequence of the corresponding grid densities from high to low to form a grid sequence; and clustering the N target grids according to the sequence of the N target grids in the grid sequence and the grid density corresponding to each target grid to obtain M clusters. In the embodiment of the invention, the target area is subjected to grid division through the hexagonal grid, so that the deviation and error of the clustering result can be reduced; in this way, the curvature and the non-rectangular terrain of the target area are adapted through a hexagonal grid clustering method, and the accuracy of a clustering result is improved.

The invention discloses a low-altitude flight base map construction method for unmanned aerial vehicle path planning, and belongs to the technical field of low-altitude flight base map construction. Screening the building data in the target area, and calculating the actual occupied area of each building after screening; dividing the grid level to which each building belongs according to the actual floor area of each building; performing grid coding on the grid level to which each building belongs; constructing an initial grid; and step-by-step refining is carried out on the initial grid by adopting a method based on building space characteristics to obtain sub-grids, and the building space is represented by utilizing a sub-grid group. According to the method, the low-altitude flight base map of the unmanned aerial vehicle is constructed based on the Beidou grid code, and the method has remarkable advantages in the aspects of data storage and calculation efficiency; through regularized grid division and a refinement strategy, an efficient and lightweight low-altitude flight base map of the unmanned aerial vehicle is constructed, so that the data storage amount of the base map is reduced by more than 95%, and the storage overhead is greatly reduced.

The invention relates to the technical field of plate heat exchange, in particular to a calculation method of a plate heat exchanger, which comprises the following steps: S1, converting pressure and temperature data into pressure and enthalpy values, setting boundary conditions, determining a hot side and a cold side of the heat exchanger according to the boundary conditions, and setting non-boundary values by segmentally applying energy conservation to obtain geometric parameters and empirical constants; s2, obtaining physical property parameters of the fluid by using a two-dimensional grid linear interpolation method, and obtaining the physical property parameters of the fluid by taking the enthalpy value and the pressure as coordinates; and S3, determining the effective area required by each section, and obtaining a local heat transfer coefficient and a pressure drop when the volume requirement is met under the fluid physical property parameters and the channel flow velocity. According to the method, the problem that the calculation speed of a calculation program is low when the performance of the brazing sheet heat exchanger is evaluated under different working conditions is solved through unique grid division in the plate heat exchanger and rapid calling of fluid physical properties, the calculation error value is effectively reduced, an accurate check result is obtained within ten iteration steps, and the calculation cost is saved.

The invention relates to the technical field of urban planning, in particular to a charging facility planning method and device based on machine learning and a medium, and the method comprises the following steps: carrying out the grid division of a planning region, which comprises a plurality of charging service grids; carrying out vehicle ownership prediction and charging facility demand prediction to obtain a charging demand quantity; adopting a clustering algorithm to obtain a plurality of charging block areas with balanced charging demand quantity; and constructing an objective function by maximizing the station revenue of each charging block area, constructing constraint conditions by full coverage of charging demands, calling an aurora optimization algorithm to obtain an optimal planning scheme of the charging facilities, and completing the planning of the charging facilities by adopting the optimal planning scheme of the charging facilities. According to the method, the problems of incomplete analysis and unreasonable partition optimization in the prior art can be solved, and various influence factors of charging facility layout are comprehensively considered, so that efficient layout and resource allocation of a charging network are realized, and the overall quality of charging services and the user satisfaction are remarkably improved.

The invention discloses a layout generation method for load effect compensation and a related device, which are applied to the technical field of photoetching and comprise the following steps: acquiring photomask data; carrying out grid division on the mask graph according to the photomask data, and determining layout density in each grid; comparing the layout density of each grid with a target density, and determining a density difference value corresponding to each grid; determining a virtual graph corresponding to each grid according to the density difference value; and adding a corresponding virtual graph in a layout area corresponding to the grid to form a compensated mask plate graph. By performing grid division on the mask plate graph, calculating the specific layout density in each grid and adding the corresponding virtual graph to the layout area corresponding to the grid according to the difference value between the layout density and the target density, the graph density of the layout area in each grid can be effectively compensated, so that the load effect of each area in the layout is balanced, and the performance of the mask plate is improved. And the etching uniformity is improved.

The invention discloses an efficient local grid encryption method and system based on OpenFOAM (Open Field Operating and Maintenance). Comprising the following steps: firstly, determining a region needing local grid division and defining a corresponding local grid set; and then, the defined local grid sets are combined into a single grid set, so that the requirement of independently dividing each local grid set for multiple times is avoided. In this way, a user can efficiently divide a plurality of local grid sets at a time, the grid division efficiency and speed are remarkably improved, and especially when the number of local grids needing to be divided is large, the grid division time can be greatly shortened. According to the method, local grid division which needs to be completed in multiple steps originally is simplified to be completed in one step, so that the calculation efficiency is remarkably improved. In addition, the method has good expansibility, more complex grid division requirements can be met conveniently, and efficient division of locally encrypted grids in a computational domain is achieved.

The invention provides a super-large-scale high-expandability grid generation method and device and a storage medium, and the method comprises the steps: obtaining a geometric model of a numerical simulation task, carrying out the surface grid division, obtaining a corresponding overall surface grid connected domain, carrying out the segmentation of the overall surface grid connected domain, obtaining a plurality of sub connected domains corresponding to the geometric model, and carrying out the segmentation of the sub connected domains; the method comprises the following steps: acquiring a plurality of sub-connected domains, distributing each sub-connected domain to each node, enabling each node to carry out volume mesh division on the sub-connected domains to obtain a mesh data file, searching other connecting surfaces corresponding to the connecting surfaces in the sub-connected domains, and finally updating mesh information in the mesh data file of each node according to a corresponding relationship among the connecting surfaces. And each node writes the updated grid information into the grid model file of the geometric model in parallel, so that the generation of the grid model for numerical simulation is realized, the memory occupation of each node during grid generation is reduced, the grid generation stability is ensured, and the file writing efficiency is greatly improved.

The invention discloses a fluid internal particle motion simulation method based on CFD-DEM coupling. Comprising the following steps: constructing a three-dimensional model, and exporting the three-dimensional model as a. Step file; grid division is carried out on the solid and the grid between the solid and the drainage basin, and a. Msh file is generated; a dynamic grid motion control file is generated, and a. Model file is reserved; the. Msh file is imported into DEM simulation software, and a. Case file with the initial time being 0 is exported; and performing fluid mechanics and discrete phase calculation on the. Model file in CFD simulation software, and exporting a particle motion track and a variable change curve. According to the method, control over the moving part is more accurate, the movement trend of particles in the three-dimensional model can be accurately simulated, and particle movement simulation animation and variable data of more real points are output; the obtained simulation coupling result not only can judge the movement condition of the abrasive particles, but also can improve the structure according to a fluid mechanics (CFD) calculation result, optimize work and design parameters, reduce power loss and improve transmission performance.

The invention discloses a seepage field adaptive analysis method and device based on a flexible polygon unit, and the method comprises the steps: dividing the polygon unit into a plurality of sub-regions, and constructing an internal water head field of each sub-region; recognizing a free water surface according to water head features extracted from the internal water head field of each sub-region; if the free water surface is recognized for the first time at present, or the error of the positions of the free water surfaces recognized by two adjacent rounds of iteration does not meet a preset condition, quadtree decomposition is carried out on the free water surface to obtain new sub-regions; returning to the step of extracting the water head features according to the internal water head field of each sub-region until the error of the positions of the free water surfaces identified by two adjacent rounds of iteration meets a preset condition, and obtaining a grid division result of the polygon unit; and performing seepage field analysis on the polygon units based on a grid division result to obtain a seepage field analysis result. According to the method, the complex seepage field is accurately simulated, and the optimal balance between high-precision discretization near the free water surface and the overall calculation efficiency is realized.

The invention relates to a numerical simulation method for multiphase fluid stratum seepage, which belongs to the technical field of numerical simulation and comprises the following steps: S1, generating an unstructured grid by adopting a mode of combining a leading edge propulsion method and Delaunay triangulation; s2, performing dynamic adjustment through an adaptive grid encryption technology according to the change of the seepage physical quantity; s3, establishing a dynamic phase change model, and obtaining a function of representing the phase change rate as temperature, pressure and concentration of each phase; s4, the mass and energy change of each phase in the phase change process is calculated in real time through a kinetic equation; s5, processing dynamic evolution of a phase interface by adopting a phase field method, and describing distribution conditions of different phases through phase field variables; and S6, coupling the grid system obtained by dividing the multi-scale unstructured grid with the dynamic phase change model through a numerical solution algorithm. According to the method, the complex geometrical shape of the stratum can be better fitted through multi-scale unstructured grid division, and then the change of the phase change process along with time and space can be tracked in real time through the dynamic phase change model.

The invention relates to the technical field of city updating simulation, and discloses a city updating multi-scene simulation evaluation system based on digital twinning. The system comprises a multi-source data acquisition module, a space grid division module, a scene simulation engine and a dynamic evaluation module. The multi-source data acquisition module acquires real-time monitoring data and historical city update project data of a city physical space, and the real-time monitoring data covers environmental parameters, infrastructure operation data and people flow dynamic data, so that a digital twinborn body is constructed. The space grid division module divides the digital twin into space grid units according to the urban functional area type and the updating target and gives attribute tags to the space grid units. And the scene simulation engine generates a simulation parameter combination based on the attribute tag, and drives the digital twin to carry out multi-scene dynamic simulation. And the dynamic evaluation module outputs a state evaluation value of each space grid unit according to a simulation result, the state evaluation value comprises an infrastructure load state and a people flow distribution state, and orderly promotion of city updating work is assisted.

The invention provides an electromagnetic environment test stationing optimization method, device and equipment and a medium, and relates to the technical field of electromagnetic monitoring, and the method comprises the steps: obtaining building structure information and machine room arrangement information of a target machine room; a plurality of grid division schemes are obtained; determining test sampling points in each grid based on the machine room arrangement information; obtaining a plurality of test point distribution schemes based on the test sampling points of each grid in the grid division scheme; respectively calculating an evaluation index of each test point distribution scheme; and determining an optimal test point distribution scheme. According to the method, the building structure information and the arrangement information of the target machine room are acquired, and equipment arrangement analysis and sampling point selection are performed based on a plurality of grid division schemes, so that efficient test point distribution for the electromagnetic environment of the machine room can be realized; by evaluating the evaluation index value of the test point distribution scheme corresponding to each grid division scheme, the optimal test point distribution scheme is determined, so that uniform distribution and comprehensive coverage of test points are ensured, and the test accuracy and efficiency are improved.

The invention discloses a reservoir dam leakage intelligent detection device, and the device comprises a soil hardness detection module which is used for determining a detection point according to the axis of a dam and the type of a dam body filling material; the grid division module is used for dividing the corresponding region into grid structures with associated sizes through the soil hardness mean value of the same region; the detection strategy matching module is used for determining a leakage detection strategy corresponding to the grid structure according to the soil hardness; the leakage detection module is used for detecting the leakage flow velocity of each grid in the grid structure according to the determined leakage detection strategy and determining the leakage state of each grid according to the leakage flow velocity; and the prediction module is used for predicting the leakage state of the grid according to the historical leakage data to obtain the duration required for deterioration of the leakage state of the corresponding region. According to the method, grids are reasonably divided according to the hardness of soil, so that detection is more detailed and comprehensive, potential leakage points can be accurately found, and the precision and reliability of leakage detection are improved.

The invention discloses a regional grid safety evaluation method and device based on smart gas and a medium, belongs to the technical field of gas safety supervision, and aims to solve the technical problem of how to overcome the defects of insufficient matching between grid division and gas facility characteristics and lagging leakage risk prediction in the prior art. In order to realize full-process intelligence from risk identification to closed-loop management and improve supervision efficiency and early warning precision, the technical scheme adopted by the invention is as follows: dividing a pressure sensitive grid: performing optimization division on a regional grid based on a gas pipeline pressure grade and facility distribution characteristics, and realizing accurate division of the regional grid where a pipe network is located by combining a GIS and an improved DBSCAN algorithm; acquiring three-level Internet of Things data: integrating sensor data of an unmanned aerial vehicle, a pipe network pressure device and a leakage monitoring device, and covering a full-link data system of a terminal sensing layer, an edge computing layer and a cloud storage layer; constructing a double-engine evaluation model; carrying out digital twinborn visualization; and scheduling the capability matrix.

The invention provides a transformer substation flood control optimization design modeling method and system based on grid division, and relates to the technical field of transformer substation flood control optimizing.The method comprises the steps that grid division is conducted on a transformer substation area according to multiple sets of schemes, and the optimal grid scheme is determined with the purpose of minimizing the area of a non-grid area; analyzing the stability of each grid foundation based on the foundation parameters, and dividing N stability grades; classifying the equipment in the station according to an electrical rule, determining the priority, and determining a storable grid according to the lowest stability requirement of the equipment; then, calculating dynamic stability indexes of all feasible storage schemes of each device according to a priority sequence, and selecting an optimal scheme for device arrangement; and finally, traversing all the devices to complete flood control optimization layout, and constructing a layout model of the devices according to the final scheme. According to the method, the foundation stability, the influence of adjacent grids and the priority of the equipment are comprehensively considered, and the flood control scientific layout of the substation equipment is realized through gridding partition and an intelligent optimization algorithm.

The invention relates to the technical field of refrigeration house energy-saving control, and provides a refrigeration house energy-saving control method based on deep reinforcement learning, which comprises the following steps: dividing a refrigeration house according to a multi-scale grid, collecting data in real time, weighting and aggregating according to spatial characteristics, calculating spatial semantic codes and confidence indexes of each grid, and obtaining a standardized and traceable state vector; real-time energy consumption, grid temperature space gradient, long-term exposure economic loss, event condition triggering and weighted summation form a reward function, and a deep strategy network is adopted to train parameters in an accumulated reward mode; constructing a grey box and residual dynamic prediction model, shrinking the original temperature and humidity constraint, solving the prediction model through scenario under the shrinkage constraint, and carrying out weighted fusion on the depth strategy obtained by training and the solution of the prediction model according to confidence; and calculating a statistical value in the sliding window, constructing confidence distribution of strategy return, triggering a hierarchical response according to a detection result, and inputting all triggers into an audit log for threshold self-calibration.

The invention discloses a clock tree comprehensive optimization method and system based on layered region division and buffer insertion, and the method carries out the clock tree comprehensive optimization through a layered buffer insertion mode, and comprises the steps: firstly, taking all registers as basic units, carrying out the rectangular region cutting of a circuit, and inserting a bottom buffer at a geometric center point; then taking the upper layer buffer as a basic unit, dividing a circuit area by using a rhombus grid division method, inserting a middle layer buffer at a geometric center point, and finally inserting a top layer buffer according to an H-tree structure; after the buffers are inserted, the positions of the buffers are dynamically adjusted, so that delay minimization and deflection control of the global clock tree are achieved, meanwhile, the number of the buffers is effectively reduced, power consumption is reduced, and design efficiency is improved.

The invention relates to a reinforcement learning-based intelligent grid division method from GIS data to GEOSOT, and relates to the technical field of reinforcement learning, and the method comprises the steps: obtaining a plurality of grid division samples which comprise sample GIS data and a sample optimal grid scale; determining a plurality of grid division influence factors based on the plurality of grid division samples; establishing an intelligent grid division model based on a reinforcement learning algorithm, and training the intelligent grid division model based on the plurality of grid division samples; obtaining to-be-divided GIS data; determining feature data of the to-be-divided GIS data based on the plurality of grid division influence factors; determining an optimal grid scale based on the feature data of the to-be-divided GIS data through the intelligent grid division model; according to the optimal grid scale, the GIS data to be divided are converted into the GeoSOT format, and the method has the advantages that the precision and efficiency of the GIS data in the gridding process are improved, and data redundancy is reduced.

The invention discloses a multi-scalar multiplication acceleration method based on resource estimation and a pre-calculation strategy, and provides a systematic solution for the problems of insufficient resource estimation, pre-calculation factor stiffness and low sorting efficiency of a Pippenger algorithm in zero-knowledge proof. A multi-resolution point multiplication table is dynamically generated through a hierarchical displacement pre-calculation strategy, and global memory access delay is remarkably reduced by combining memory layout optimization and asynchronous flow task scheduling of window inner barrel continuous storage. A dynamic resource adaptation mechanism is designed, thread block topology, grid division and sorting algorithm selection are adjusted in real time based on GPU hardware features, and load balancing and cache utilization rate maximization are achieved. Iterative reduction and double temporary bucket strategies are introduced, and data scale is compressed and boundary processing is optimized through multi-round reduction. In the large-scale MSM operation in the block chain and privacy computing field, the computing efficiency and the resource utilization rate can be remarkably improved, and the method is suitable for an elliptic curve cryptography acceleration task.

The invention discloses a method for quantitatively designing the rigidity of a wing tooling flag, which comprises the following steps of: 1, establishing a three-dimensional geometric model of the tooling flag, and simplifying the three-dimensional geometric model to obtain a simplified model of the wing tooling flag; 2, mechanical boundary conditions are set for the simplified model of the wing tooling flag; step 3, establishing a constraint equation according to the simplified model of the wing tooling flag and the position of a load action point in the model; 4, applying a concentrated load to a load acting point based on the tool flag simplification model, and solving a displacement field result of the wing tool flag simplification model under the concentrated load; 5, carrying out grid division on the tool flag simplified model and carrying out data post-processing on grid units, namely obtaining a displacement matrix and total mass of the wing tool flag simplified model by adopting the displacement field result obtained in the step 4 and the grid units divided by the wing tool flag simplified model; and step 6, calculating an optimal tooling flag design scheme meeting the rigidity index requirement by combining structural parameters in the simplified model of the wing tooling flag and adopting the calculation mode in the step 5. According to the technical scheme, the optimal parameter scheme is selected in the design according to the calculation result, the weight of the tool flag is reduced on the premise that the rigidity of the tool flag is guaranteed, structural deformation caused by insufficient rigidity of the tool flag is avoided, the proposed rigidity quantitative design method can provide a theoretical basis for optimization design, and the method is suitable for popularization and application. The method is a rapid and effective design method.

The invention discloses a photovoltaic cluster dynamic grid division method and device based on spatial-temporal characteristics, and the method comprises the steps: obtaining the historical characteristic data of a photovoltaic cluster, and constructing a spatial-temporal characteristic matrix and a data incidence matrix; wherein the historical feature data at least comprises historical meteorological data and historical output power, and the data incidence matrix is an incidence matrix of the historical meteorological data and the historical output power; performing similarity analysis on the spatial-temporal characteristic matrix, and dividing a photovoltaic cluster to obtain an initial grid; giving a reference output mode matched with the current day of the photovoltaic cluster based on the data incidence matrix, and dividing the initial grid to obtain a secondary grid; and carrying out dynamic optimization on the secondary grid, and giving a final grid division result. According to the invention, accurate clustering and dynamic division of photovoltaic sites can be realized.