503 results about "Mesh node" patented technology

The invention relates to the technical field of equipment intelligent diagnosis, in particular to a generator digital twinning diagnosis method based on temperature field online simulation, which comprises the following steps: respectively constructing a three-dimensional virtual model, a temperature field simulation model and an intelligent agent diagnosis model; the digital twin is in data connection with the physical entity; data alignment is achieved through a unified space-time coordinate system, a mapping relation is established between a vertex of the three-dimensional virtual model and a grid node in the temperature field simulation model, and a fault probability matrix output by the intelligent agent diagnosis model is matched to a three-dimensional grid of the three-dimensional virtual model through spatial interpolation; according to a fault probability output by the intelligent agent diagnosis model, correcting a boundary condition of the temperature field simulation model, triggering local grid adaptive encryption of the temperature field simulation model, and marking a fault position in real time through a three-dimensional virtual model; and the simulation result of the temperature field simulation model verifies the fault probability output by the intelligent agent diagnosis model. Through the method, the fault identification accuracy can be effectively improved.

The invention discloses a rapid calculation method based on a non-coordination and reanalysis theory and a computer device. The invention relates to the technical field of structural design optimization, and solves the problem that it is difficult to realize efficient structural response analysis while ensuring the calculation precision in the prior art. The method comprises the following steps: selecting a structural member of a to-be-calculated structural response and discretizing the structural member; preprocessing the data, and determining a coarse and fine grid index set corresponding to interface fine grid nodes; solving a unit shape function, and embedding the shape function into a body stiffness matrix according to a degree-of-freedom position to serve as an interface constraint condition; calculating a variable element stiffness matrix, and completing the construction of a modified model stiffness matrix; carrying out iterative calculation to obtain a basis vector; and calculating and solving the structural response of the modified model. According to the method, the efficient response analysis of the non-coordinated variable structure is realized on the premise of ensuring the calculation precision.

The invention relates to the field of three-dimensional scene rendering, in particular to a three-dimensional scene data generation method, an analysis method, rendering equipment and a computer storage medium. According to the method, LOD (Level of Detail) grading processing is performed on three-dimensional scene data, foreground data in the three-dimensional scene data is divided into a plurality of LOD layers, each LOD layer is divided into a plurality of grid nodes, and each grid node is independently stored, so that the data can be loaded as required. Meanwhile, different compression modes are adopted for different data, the GPU can directly analyze and read the compressed data, decompression in a memory is not needed, occupation of the memory and video memory bandwidth is greatly reduced, and rendering efficiency is improved.

The invention relates to a valve health degree monitoring and maintaining method and system based on an electric actuator, and belongs to the technical field of mechanical control and automation. The method comprises the steps that valve maintenance data of the electric actuator are obtained, a position-pressure bimodal grid is constructed based on the valve maintenance data, pressure testing is conducted on a valve, torque-opening curves in the opening and closing processes are analyzed, and valve health degree data are obtained; an electric execution monitoring model is constructed, a valve torque curve is obtained, maintenance information labels are added to grid nodes according to the valve maintenance information through a labeling binding method, and a valve health maintenance scheme is generated; for the pressure test, identifying switching time delay, hysteresis and leakage data in a valve torque profile and an operation log through a curve feature extraction method to obtain a valve scheme optimization strategy; and executing the maintenance scheme optimized by the valve scheme optimization strategy, and automatically outputting the updated valve health maintenance scheme based on a recursive execution feedback method.

The invention belongs to the field of machine tool geometric accuracy design, and particularly discloses a machine tool geometric accuracy analysis optimization method based on dynamic sensitivity, which comprises the following steps: constructing an error transfer model, and determining a target function; selecting an SOBOL method based on the global influence demand for quantifying each error term; selecting a Morris method based on the non-linear influence demand of the evaluation error term range change; dividing the travel of each movement shaft of the machine tool into grid nodes; selecting an error initial value for calculation based on parameter input and an error range, performing sensitivity calculation by using SOBOL, and taking a result as an optimization constraint condition; performing sensitivity calculation by using Morris, and taking a result as an optimization iteration basis; carrying out loop iteration and updating a sensitivity result to guide precision optimization, and carrying out multi-round iterative optimization until iterative convergence to obtain an optimized error term; and traversing grid nodes and carrying out sensitivity normalization in the transverse direction to obtain an optimized error curve in which error terms change along with coordinates. The geometric accuracy of machine tool machining can be improved.

The invention provides a safety coefficient prediction method based on slope three-dimensional finite element analysis and application, and relates to the field of hydraulic geotechnical engineering. Comprising the following steps: inputting a finite element grid, and calculating a geometric topological relation of the three-dimensional finite element grid; the method comprises the following steps: inputting position information and mechanical parameters of a bottom sliding surface and a side sliding surface of a possible sliding block, calculating to obtain a description equation of the possible sliding block, performing cutting calculation by utilizing a sliding surface equation and geometry of a finite element grid to obtain polygons of a boundary surface of the sliding block, decomposing each polygon into triangular grids, and analyzing a stress result based on a slope finite element to obtain a stress result of the boundary surface of the possible sliding block. Calculating stress values of triangular mesh nodes of the boundary surface through line interpolation; integration is carried out on the sliding force and the anti-sliding force of the boundary surface, and the safety coefficient of the possible sliding block body is calculated; according to the method, efficient intersection of the sliding surface and the finite element grid is achieved, geometric processing efficiency is improved, calculation efficiency and calculation accuracy are improved, and the method is suitable for three-dimensional irregular sliding block analysis in the fields of water conservancy, mines and the like.

The invention belongs to the technical field of engineering simulation data processing, and particularly discloses a finite element grid graph structure construction method and system, a terminal and a medium. Comprising the following steps: analyzing original full-amount grid data exported by finite element simulation, segmenting unstructured grid data into a grid vertex coordinate set and a grid unit mark number set, and constructing a graph edge topological structure corresponding to a grid based on a unit mark number relationship; on the basis, loading physical field data and adopting a tolerance-based coordinate matching algorithm to realize accurate mapping of physical field labels and material attributes with grid nodes; and generating standardized finite element grid graph data which can be directly used for graph neural network processing. By means of the method, high-consistency and high-physical-reliability conversion from the finite element simulation data to the graph structure data is achieved, and the physical field modeling and simulation acceleration capacity based on graph learning is improved.

The invention discloses a petroleum pipeline service life prediction system based on a 3D technology, and relates to the technical field of pipeline service life detection, and the system comprises a contour reconstruction module S11 which is used for obtaining the surface three-dimensional point cloud image data of a petroleum pipeline housing in an actual operation environment, and carrying out the surface contour reconstruction processing based on the three-dimensional point cloud image data, extracting space geometric structure data containing a local deformation defect area; the force-heat coupling analysis module S12 is used for constructing a finite element analysis grid according to the space geometric structure data and loading operation condition data into corresponding grid nodes to generate a force-heat coupling stress field, and the operation condition data comprises a periodic internal working pressure value, along-line temperature field data and an axial disturbance stress tensor; the feature extraction module S13 is used for calculating an equivalent stress distribution value of a defect area node based on a force-heat coupling stress field; according to the invention, accurate quantification of fatigue damage evolution of the defect area is realized.

The invention belongs to the technical field of control detection, and particularly relates to a laser cutting machine cutting control method and system.The laser cutting machine cutting control method comprises the following steps that S1, frequency sweeping excitation is applied to a plurality of preset grid node positions of a laser cutting machine workbench, and vibration response data of a cutting head is collected; a dominant pole and a zero point of a vibration transfer function of each grid node are identified and extracted, spatial distribution is fitted by using a non-uniform rational B-spline surface, and a spatial model of continuous mapping between a cutting head position and a vibration transfer function parameter is established; s2, decomposing a to-be-processed path into a plurality of path infinitesimal segments, and calculating a preliminary feed-forward compensation instruction of each path infinitesimal segment based on a space model and a zero-phase error tracking control algorithm; according to the invention, the contour error caused by structural vibration and non-linear factors is reduced, the processing precision and the cutting surface quality of the laser cutting machine in a full working range are improved, and the forming effect of a complex contour at a high speed is improved.

The invention discloses a bridge structure monitoring method based on multi-source data and digital twinning and a related device, and relates to the technical field of bridge engineering.The method comprises the steps that an initial finite element model of a target bridge is constructed based on a design drawing and structural parameters of the target bridge, and the initial finite element model of the target bridge is constructed based on the initial finite element model and preset load conditions; calculating to obtain simulation mechanical response data of each grid node of the target bridge; based on the simulation mechanical response data and the obtained actually measured mechanical response data of each grid node of the target bridge, obtaining a corrected finite element model; inputting the obtained traffic load data passing through the target bridge into a digital twinborn calculation model constructed based on the corrected influence line data for numerical calculation to obtain an overall structure response cloud picture and a structure response-time curve of the key monitoring point, and fusing the overall structure response cloud picture and the structure response-time curve with the obtained three-dimensional visualization model to obtain a three-dimensional visualization model; and obtaining the structural state of the target bridge. According to the invention, accurate monitoring and real-time state evaluation of the bridge structure are realized.

The invention discloses a curved surface porous structure modeling simulation method and system for finite element analysis, and belongs to the technical field of mechanical engineering simulation, and the method mainly comprises the steps: carrying out the initial grid division of a target curved surface part, and obtaining a grid node set covering a curved surface; according to a preset hole center coordinate, three closest grid nodes are automatically searched in the grid node set, a local reference plane is established, and the hole axis direction is determined; generating an offset sketch plane in the normal direction of the reference plane, projecting the hole center to the sketch plane, drawing a circular sketch, and executing a stretching and cutting command to form a hole; and circularly executing the operation to realize automatic generation of multiple holes on the curved surface. And finally, the porous structure is subjected to grid division again, so that subsequent operation is facilitated. According to the method, the modeling process is combined with parameterization analysis and an automatic process, the efficiency and stability of porous modeling of the complex curved surface structure are remarkably improved, and a basis is provided for finite element pretreatment of the complex curved surface structure.

The invention belongs to the technical field of aircraft strength design, and particularly relates to an aircraft structure strain field reconstruction method and device based on a deep learning neural network, and the method comprises the steps: S1, carrying out the dimension reduction mapping of irregularly distributed three-dimensional grid nodes of a finite element model, and obtaining regular two-dimensional grid nodes; s2, obtaining calculation results of each two-dimensional grid node under a plurality of working conditions based on finite element simulation, and constructing a training set; s3, training the U-NET deep convolutional network through the training set to obtain a strain field proxy model; and S4, based on the strain field agent model, processing an input image with a small number of measurement point position measurement results to obtain an output image containing an aircraft structure strain field. According to the invention, the strain field of the whole aircraft can be reconstructed through displacement data of a small number of points measured by the static test of the whole aircraft.

The invention relates to an ocean platform pipeline wiring method and system based on an ant colony optimization algorithm, and a medium, and belongs to the technical field of intelligent optimization algorithms. Comprising the following steps: S11, environment modeling: discretizing a three-dimensional space of an ocean platform into a grid model, marking an obstacle region and a feasible region, and calculating a grid node energy value; s12, parameter initialization: constructing a heuristic information matrix based on pipeline inlet and outlet coordinates and equipment parameters, and determining a node transition probability by the matrix through a direction probability allocation strategy and a distance sensitive function; s13, path optimization: generating candidate paths through dynamic smooth search, local pheromone adaptive adjustment and collaborative ecological niche search, and updating pheromones; and S14, constraint verification and result output: verifying whether the path meets the engineering constraint or not, and outputting the three-dimensional coordinate, length and bend number of the optimal pipeline path after iterative optimization. According to the method, efficient, safe and economical wiring of the offshore platform pipeline is achieved.

The invention belongs to the technical field of image processing and three-dimensional modeling, and particularly relates to an SLAM three-dimensional modeling method suitable for a complex dynamic scene. By constructing a multi-modal feature hierarchical processing architecture, the system realizes technical breakthrough in three dimensions: firstly, in combination with a pixel mask pattern and a multi-view geometric method, static feature points are reserved while dynamic feature points are removed as far as possible; secondly, according to the optimal flow field mapping relation of the grid nodes, static background restoration of the shielded area is achieved by establishing the geometric constraint relation of adjacent key frames; and finally, the depth perception data and the optimized feature set are fused to construct a tightly coupled three-dimensional reconstruction model, and a closed-loop optimization framework with motion robustness is formed.

The embodiment of the invention discloses a method and device for generating a dam surface settlement cloud picture based on a self-adaptive interpolation model. A specific embodiment of the method comprises the steps of performing feature extraction on multi-dimensional monitoring point data of a preset dam structure to generate a dam body scene portrait; according to the dam body scene portrait, generating an optimal interpolation algorithm; optimizing the optimal interpolation algorithm to generate an optimized interpolation algorithm; generating a non-oscillation cloud picture according to dam body physical attributes of a preset dam structure and an optimization interpolation algorithm; performing preset-size grid block division on the non-oscillation cloud picture to generate a cloud picture grid node set; performing parallel processing on each cloud picture grid node in the cloud picture grid node set to generate an accelerated interpolation result; and performing incremental updating on the accelerated interpolation result to generate an updated interpolation result. According to the implementation mode, the accuracy, efficiency and engineering applicability of dam settlement interpolation are improved.

The invention relates to the technical field of enterprise resource management, in particular to a mobile observation project full-process collaborative management method, which comprises the following steps: acquiring multi-dimensional observation data and an elevation model of a to-be-observed area, and accessing an inventory node to construct a digital instance library; constructing a collaborative constraint graph based on the data, calculating a grid node operation deployment resistance index and an accessibility factor, and generating an admission control matrix; traversing the instance library to obtain an efficiency portrait, and calling an element matching model to evaluate a matching index and generate a circulation work order; receiving a stress accumulation log in the logistics process, executing stress recovery evaluation to generate an inventory freezing time window, and dynamically updating a task scheduling time axis; and executing project compliance auditing and evaluating a business consistency index, generating a performance qualification voucher, and incorporating the nodes updated to be in the in-service state into a resource allocation scheduling queue. According to the invention, through dynamic cooperation of the multi-dimensional environment constraint and the equipment stress, the whole-process accurate management of assets is realized.

The invention discloses an induction heating path optimization method suitable for a heterogeneous noise elimination structure, and particularly relates to the field of induction heating path optimization of the heterogeneous noise elimination structure, and the method comprises the steps: building a grid coordinate in a target region, collecting the heat conductivity coefficient, the specific heat capacity, the thermal resistance value and the induction coil gap value of each grid node in the grid coordinate, generating a thermal response model; and performing heat conduction calculation on the thermal response model and a preset heating power curve, calculating a temperature rise value of each grid node in a fixed preset heating time, marking the grid nodes of which the temperature rise values reach or exceed a safe temperature threshold and the adjacent grid nodes as heat concentration areas, and generating risk area data after gathering the heat concentration areas. A risk assessment and dynamic reordering mechanism based on local thermal characteristic difference is introduced in a heating path planning process, so that advanced identification and real-time avoidance of a heat concentration area are realized.

This invention provides a method and system for monitoring surrounding rock deformation in underground coal mines based on three-dimensional point clouds, relating to the field of coal mine safety monitoring. The invention includes the following steps: installing a reference target in the monitoring area and collecting point cloud data; preprocessing the point cloud data, performing coarse registration using the reference target and fine registration using the iterative nearest point algorithm, and generating a triangular mesh model using the Poisson surface reconstruction algorithm; parameterizing the triangular mesh model of the monitoring area into a two-dimensional analysis mesh, calculating the three-dimensional displacement vector of each node, and establishing a displacement field matrix; calculating the displacement gradient tensor based on the displacement vector, deriving the Green-Lagrange strain tensor, and obtaining the full-field strain distribution; recording the strain value of each mesh node, and determining whether an instability warning is triggered based on the relationship between the strain value and the warning threshold; this method can achieve high-precision monitoring of surrounding rock deformation in underground coal mines.

The invention discloses an intelligent well site comprehensive management system based on digital twinning and AI analysis, and belongs to the technical field of digital twinning. Uniformly representing the multi-physical field data as a tensor data structure including a space dimension, a time dimension and a physical quantity dimension; performing data fusion on the tensor data structure and the three-dimensional geometric model of the well site, and establishing a spatial association relationship of multi-physical field data at grid nodes; establishing physical field control equations based on the fused data, and correlating the equations through a coupling operator to form a multi-physical field coupling equation; solving the coupling equation to obtain a numerical solution of each physical field distribution; generating a control instruction sequence for adjusting the operation parameters of the well site equipment according to the numerical solution; according to the invention, accurate sensing and intelligent regulation and control of the operation state of the well site equipment are realized, and the intelligent level of well site management is obviously improved.

The invention discloses a surface material point embedding method for a multi-body contact problem, and belongs to the technical field of computational mechanics and numerical simulation. The method comprises the following steps: 1, performing discretization and parameter setting on a physical model of a multi-body contact system; 2, calculating a contact force; 3, transmitting the physical quantity of the material points of the contact body to background grid nodes to obtain node mass, momentum and force; 4, updating the grids; 5, updating the speed, the displacement, the stress and the density of the material point; 6, resetting the physical quantity of the background grid; seventhly, repeating the first step, the fourth step, the fifth step and the sixth step, sequentially updating the physical quantities of the material points of other contact bodies and the positions and the speeds of the slave nodes, and distributing background grid node memories of the areas where the corresponding contact bodies are located; and 8, after all contact bodies are updated, updating the current time to obtain a dynamic simulation result. According to the method, the boundary of the object can be accurately represented, complicated problems such as impact and multi-body contact can be effectively simulated, and meanwhile, the method has good stability and relatively low memory consumption.

This invention relates to the field of intelligent reconstruction technology for 3D models, specifically a method and system for intelligent reconstruction of 3D building models based on deep learning. The method includes acquiring multi-source data of the target ancient building; generating a dense point cloud through motion reconstruction and multi-view stereo matching; identifying structural and non-structural components through semantic segmentation and reconstructing an initial mesh model with semantically labeled information; using a graph neural network to analyze the spatial topological relationships of structural components, and combining this with a historical construction knowledge base to generate hierarchical combination methods and connection constraint rules; adaptively adjusting the pose of mesh nodes according to the connection constraint rules to drive the precise assembly of parameterized components, and fusing them to obtain a structured 3D model of the target ancient building. This invention can restore the structural component connection relationships in hidden areas of ancient buildings under non-contact acquisition conditions, significantly improving the structural rationality and geometric accuracy of the 3D model.

The invention provides a dam safety monitoring data analysis method and device based on space-time gradient. Constructing a space-time fusion coordinate system, discretizing a three-dimensional space coordinate of the dam into finite element grid nodes, and mapping each node to a normalized parameter space through cubic spline interpolation to form a space parameter; the method comprises the following steps: dynamically expanding monitoring data on a time axis, generating time-frequency joint representation by adopting a sliding time window and wavelet transform, and forming a high-dimensional space-time curved surface with a time-space double-continuous axis; a first-order space-time gradient field and a second-order curvature tensor are calculated based on the space-time curved surface, a finite element balance equation is combined as a regularization item, and mathematical modeling and dynamic recognition of an abnormal propagation path are achieved; and according to the characteristics of the gradient field and the curvature tensor, constructing a space-time attention mechanism, automatically focusing a high-risk area and generating a graded early warning signal. According to the invention, the abnormity identification precision and early warning timeliness can be effectively improved, the false alarm rate is reduced, and the system expansibility is enhanced.

The invention discloses a flow field pressure gradient prediction method based on a graph attention network guided by a physical operator, and aims to rapidly and accurately predict the gradient distribution of a flow field. According to the method, a grid computational domain of computational fluid dynamics (CFD) is expressed as a graph structure, a graph neural network is adopted to carry out feature learning on grid nodes and adjacency relations, and a physical operator (such as a fluid control equation difference operator) is introduced in a model training process to carry out guide constraint on the network. Through the above technical scheme, the method can greatly improve the efficiency of flow field gradient prediction on the premise of ensuring the prediction precision and physical consistency, has the advantages of fast model calculation speed, strong adaptability to complex boundary conditions, and the prediction result meets the law of conservation of fluid mechanics, and is suitable for popularization and application. The method can be used for rapidly predicting the flow field gradient in the fields of aerospace fluid simulation, wind engineering and the like.

The application discloses a greenhouse environment control method based on adaptive control vector parameterization, comprising the following steps: constructing a nonlinear optimal control problem of a type of greenhouse environment dynamic constraint optimization based on constraint conditions in a greenhouse environment, and converting the problem into a nonlinear programming NLP problem of a type of limited dimension parameters; based on a control vector parameterization method, solving the NLP problem by fusing engineering constraint rules and a penalty function method aiming at different constraint conditions on fixed time grid nodes of a "coarse grid"; adaptively subdividing the fixed time nodes of the "coarse grid", and constructing new "refined" time grid nodes; based on the new "refined" time grid nodes, re-solving the NLP problem until a termination condition is met to stop the solving, so that the best solution result of the NLP problem is obtained. The application solves the problem of low calculation efficiency in the solving process of the control vector parameterization method for the dynamic optimal control problem in the prior art.

The invention relates to the technical field of water monitoring and detection, in particular to a simulation system and an early warning method for multi-point dam break flood. The simulation system comprises a data collection module, a data processing module, a model construction module and a simulation calculation module, and the simulation calculation module is used for completing calculation of multi-point dam break flood in the flood dynamic coupling model and outputting a simulation result. Different reference data are unified to the same projection coordinate system through a coordinate conversion algorithm, and terrain splicing dislocation is avoided; the model construction module firstly generates an unstructured grid based on accurate topographic data, and grid nodes are overlapped with actual topographic feature points through a grid boundary optimization algorithm; extracting a grid where a potential overflow point is located, and writing the grid into a parameter file as a dynamic boundary condition; finally integrating geometry, boundaries, parameters and source files to construct a coupling model; the problem that an existing simulation system cannot truly reflect nonlinear phenomena such as turbulence and vortex in the flood routing process is solved.

The invention discloses a drainage inspection well pipe network detection system and method based on low-frequency high-energy ultrasound. The system comprises a main controller, a main control module, a Mesh main router and a plurality of detection terminals. The detection terminal comprises a slave control module, a Mesh node route and an ultrasonic transducer; the main controller is electrically connected with the main control module and the Mesh main route respectively; the slave control module is electrically connected with the ultrasonic transducer and the Mesh node route respectively; the Mesh main route and each Mesh node route form a wireless Mesh network for networking communication; the master control module is in wireless networking communication with each slave control module to realize time synchronization; the ultrasonic sensing module is used for entering the drainage pipe from the inspection well in a suspended mode to send or receive ultrasonic signals. According to the drainage inspection well pipe network detection system and method, the communication state of the pipelines between the inspection wells can be rapidly and accurately recognized, and the system and method have important practical significance on timely finding and processing pipeline blockage and guaranteeing normal operation of an urban drainage system.

The invention relates to the technical field of building structure safety monitoring, in particular to a stress deformation monitoring method and system for a rib truss floor support plate. The method comprises the following steps: establishing a digital twinborn model, mapping sensor data to grid nodes on a plate surface, calculating a local curvature, and ensuring data reliability through temperature compensation and confidence interval verification; an abnormal sensitivity index ASI is constructed based on multi-modal data, strain, displacement, frequency and curvature deviation are fused and dynamically weighted, and an abnormal area is positioned in combination with spatial clustering; the ASI evolution trend is analyzed through sliding window regression, slope and intercept parameters are extracted, and a health evolution index HEI is generated to achieve four-level health grading early warning; and establishing an abnormal dynamic model to simulate a local abnormal propagation path, predicting the residual life and the health risk index, and guiding a maintenance decision. According to the invention, monitoring-early warning-decision closed-loop management is realized.

The invention provides a mine geological disaster early warning method and system based on digital twinning and electronic equipment, and relates to the technical field of geological disaster monitoring and early warning. The method comprises the following steps: constructing a digital twinborn model corresponding to a target mine based on multi-dimensional geological data and rock physical and mechanical parameters; collecting multi-source heterogeneous monitoring data of the target mine in real time, and mapping the multi-source heterogeneous monitoring data to corresponding grid nodes of the digital twinborn body based on the spatial coordinate relationship so as to update state attributes of the digital twinborn model in real time; according to the rock mass physical and mechanical parameters of the grid nodes and the updated state attributes, a slope stability coefficient is calculated through a rock and soil mechanical model; calculating a displacement predicted value based on historical time sequence characteristics of the multi-source heterogeneous monitoring data by using a data driving model; and carrying out fusion calculation on the slope stability coefficient and the displacement prediction value to obtain a comprehensive early warning index, and when the comprehensive early warning index meets a preset geological disaster alarm condition, rendering a risk area in the digital twinborn body.

The invention discloses a hierarchical collaborative anchoring prevention and control method for a hidden down-dip rock slope, and relates to the technical field of hierarchical collaborative anchoring prevention and control for the hidden down-dip rock slope, and the method comprises the following steps: obtaining geological survey data of a target slope, and generating a slope digital model composed of a plurality of grid nodes; and performing strength reduction on the slope digital model, simulating a process of evolving the target slope from a steady state to an unsteady state, obtaining data of each grid node in the simulation process, calculating a shear strain value of each grid node, and generating initial slope stress field data. According to the method, the dynamic evolution path of the shear band is accurately tracked through strength reduction simulation and space-time sequence reconstruction, and shear evolution characteristics can be accurately identified, so that dislocation of a reinforcement position and an actual disaster-causing region is effectively avoided, reinforcement failure caused by shear failure of a side slope is effectively avoided, and the prevention and control effect is effectively improved.

The invention belongs to the related technical field of subtractive manufacturing, and discloses a material removal simulation and workpiece deformation prediction method based on an extended finite element simulation model and application. The method comprises the following steps: carrying out finite element mesh division on a three-dimensional model of a blank, and carrying out mesh encryption treatment on the periphery of a preset virtual crack surface, so as to obtain a plurality of mesh units; loading residual stress in the three-dimensional model of the blank, and calculating a total load vector; calculating a global stiffness matrix; solving an overall displacement free vector; and obtaining a displacement free vector of each unit according to the total displacement free vector, and applying the displacement free vector of each unit to a grid node of each unit so as to obtain coordinates of the node after deformation, thereby realizing deformation prediction. According to the invention, the problems of low calculation efficiency and poor calculation precision in deformation simulation prediction are solved.