Inorganic mineral casting stress analysis method and system based on virtual simulation system

Abstract

The invention relates to the technical field of mechanical property analysis, in particular to an inorganic mineral casting stress analysis method and system based on a virtual simulation system.The method comprises the following steps that grain voxel density difference is obtained, boundary points are screened, a boundary curve data set is generated, a defect appearance is formed through fitting, and a defect area grid model is constructed; and extracting a fatigue path node distribution diagram, screening thermal collaborative risk nodes, and drawing a concentrated stress area labeling result. According to the method, the density mutation feature is introduced as an identification basis when the grain structure boundary is obtained, boundary offset caused by traditional geometric approximation modeling is avoided, the closed curve network is established through boundary point space continuous connection, the refining degree of grain structure modeling is improved, and the modeling precision is improved. For a fatigue path calibration link, a continuous change relation of a node displacement trend is adopted to replace concentrated strain point acquisition, so that fatigue path identification is independent of single-point measurement, and the stress judgment integrity of a virtual simulation system under a multi-field condition is enhanced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mechanical property analysis, in particular to a stress analysis method and system for inorganic mineral castings based on a virtual simulation system. BACKGROUND

[0002] The technical field of mechanical property analysis is an engineering technical field for studying the stress-strain distribution law and deformation and failure mechanism of materials or components under stress state. The core matters include material mechanical property measurement, mechanical behavior prediction, stress structure modeling and mechanical response calculation, and rely on theoretical mechanics, material science and computer simulation technology to acquire and process information such as material parameters, load conditions and boundary constraints, establish a mechanical model that can be used for prediction and verification, and realize quantitative analysis and evaluation of the mechanical properties of materials or components under different working conditions. The traditional stress analysis method for inorganic mineral castings refers to using sample mechanical property test data and physical model test, combining manual calculation and two-dimensional statics analysis means to calculate and evaluate the stress state of the castings under service conditions, arranging strain gauges on the sample to measure strain, or using physical loading experiment to simulate external force, and referring to static equilibrium equation and material mechanics formula to complete stress calculation and distribution judgment.

[0003] The existing stress analysis method for inorganic mineral castings relies on sample measurement and geometric shape simplification when constructing grain structure boundaries, lacks three-dimensional continuity expression when processing internal defect boundaries, leading to local deviation in structure modeling, relies on strain gauge local response or sample performance of physical loading experiment in fatigue risk identification, cannot accurately lock the crack path under virtual working conditions, only relies on statics formula to calculate thermal stress response in high temperature gradient environment, lacks analysis basis for the coupling relationship between heat flow direction and load action direction, making it difficult to achieve positioning accuracy of failure area in thermal and mechanical structures, and when facing the demand for structure risk judgment under multiple working conditions, there are operation defects such as single response mode and limited prediction content. SUMMARY

[0004] In order to solve the technical problems existing in the prior art, the present application provides a stress analysis method for inorganic mineral castings based on a virtual simulation system, comprising the following steps:

[0005] In order to achieve the above purpose, the present application adopts the following technical scheme: a stress analysis method for inorganic mineral castings based on a virtual simulation system, comprising the following steps:

[0006] S1: Obtain the voxel density distribution data of the grain of the inorganic mineral casting in the three-dimensional scanning of the virtual simulation system, screen the voxel positions with a density difference exceeding material interface recognition, connect the adjacent boundary points into a closed boundary curve network to obtain a grain boundary curve data set;

[0007] S2: calling the grain boundary curve data set, performing three-dimensional surface fitting on the curve surrounding area, forming a closed defect shape, constructing a local independent area using the space difference between the defect shape and the overall grain structure, arranging nodes in the virtual simulation system grid at equal intervals, and constructing a defect area grid model;

[0008] S3: based on the defect area grid model, applying a preset cyclic load in the virtual simulation system, calling the three-dimensional displacement value of the grid node at the time step, calculating the displacement change of the adjacent time step, and generating a fatigue path node distribution map;

[0009] S4: calling the fatigue path node distribution map, obtaining the node temperature value and the adjacent node temperature value, calculating the temperature difference and forming a thermal gradient direction vector, comparing the thermal gradient direction vector with the equivalent stress direction vector of the node, and generating a thermal force synergy risk node set.

[0010] As a further scheme of the present application, the grain boundary curve data set includes boundary point coordinates, boundary curve topological relationship, and boundary curve closure, the defect area grid model includes grid cell size, grid node spatial distribution, and defect area volume shape, the fatigue path node distribution map includes node number sequence, node spatial path, and path change trend, and the thermal force synergy risk node set includes risk node coordinates, thermal gradient direction, and equivalent stress direction.

[0011] As a further scheme of the present application, the specific steps of S1 are:

[0012] S101: obtaining voxel density distribution data of inorganic mineral casting grains in a virtual simulation system three-dimensional scan, calling density values of six adjacent voxels in three-dimensional direction for voxel position, respectively performing subtraction operation on real-time voxel density value and six adjacent voxel density values, recording the obtained difference value, identifying the difference between the obtained difference value and the real-time voxel density value, and generating a density mutation voxel coordinate set;

[0013] S102: calling the density mutation voxel coordinate set, combining the spatial positions of voxels adjacent in the three-dimensional grid, connecting the voxel coordinates satisfying the spatial connection relationship in turn, and judging the continuity of adjacent positions in the three-dimensional coordinate axis direction, grouping and classifying the coordinate set of voxel points according to the continuity, and obtaining a boundary point coordinate combination sequence;

[0014] S103: based on the boundary point coordinate combination sequence, connecting the spatial positions between adjacent boundary points to construct a three-dimensional curve unit, and cyclically connecting the boundary points to form a spatial closed structure, eliminating non-closed point pairs with abnormal coordinate intervals, connecting the complete and continuous boundary line segment network, and obtaining a grain boundary curve data set.

[0015] As a further scheme of the present application, the specific steps of S2 are:

[0016] S201: Call the grain boundary curve dataset, select the spatial position coordinates of each group of three consecutive boundary points according to the arrangement order of the grain boundary curve in the three-dimensional coordinate system, construct an initial triangular patch in a three-point plane manner, generate a continuously distributed triangular mesh after circulating through the boundary point set, remove the mesh patches with abnormal vertex spacing, and generate a continuous three-dimensional fitting patch set;

[0017] S202: Based on the continuous three-dimensional fitting patch set, connect the edge positions of the fitting patch, detect whether the boundary line segment forms a closed path, interpolate to generate a missing patch for the non-closed part, and close the overall curved surface contour to form a defective three-dimensional shape boundary body;

[0018] S203: Call the defective three-dimensional shape boundary body and the original grain voxel density distribution data, compare the volume space coincidence of the corresponding positions in the three-dimensional coordinate system, extract the coordinate point set inside the defective boundary body but not covered by the original grain voxel, define the coordinate point set as a local difference space position, and mark the independent region number according to the three-dimensional boundary closure to obtain the grain internal difference space region;

[0019] S204: According to the grain internal difference space region, divide the grid nodes in the three-dimensional coordinate boundary at equal intervals, construct three-dimensional octahedral units after numbering the nodes in order, remove the boundary overlapping nodes and fill the non-homogeneous units, and construct a defect region grid model.

[0020] As a further scheme of the present application, the specific steps of S3 are:

[0021] S301: Based on the defect region grid model, apply a set of cyclic load boundary conditions in a virtual simulation system according to a time axis, record the three-dimensional coordinate values of the grid nodes at multiple time steps, call the three-dimensional coordinate difference between the nodes at adjacent time steps, calculate the three-dimensional displacement change value of the nodes between adjacent time steps, and obtain time step displacement change data;

[0022] S302: Call the time step displacement change data, arrange the displacement change values of the nodes at the time steps in order according to the node number, construct the time sequence data corresponding to the nodes, count the numerical difference between the change values of adjacent time steps in the node sequence, and judge whether there is a continuously increasing change trend, mark the node number section that meets the continuously increasing characteristics, and obtain a continuously growing node number group;

[0023] S303: According to the continuously increasing node number group, the spatial position coordinates of the corresponding nodes in the defect area grid model are extracted, the adjacent nodes are sequentially connected according to the node number arrangement order, the path line segment indicating the change trend direction is constructed, and the path line segment set is outputted in the three-dimensional space according to the number identification, so that a fatigue path node distribution diagram is obtained.

[0024] As a further scheme of the present application, the specific steps of S4 are:

[0025] S401: The node number in the fatigue path node distribution diagram is called, the corresponding temperature value is extracted according to the node serial number, the temperature values of the six spatial adjacent nodes of the node are synchronously obtained, the temperature difference between the real-time node and the adjacent nodes is combined, the distribution direction of the temperature difference value in the three-dimensional coordinate system is identified, the direction vectors are integrated and vector superposition is performed, and a thermal gradient direction vector group is obtained.

[0026] S402: According to the thermal gradient direction vector group, the equivalent stress direction vector data recorded by the corresponding node in the fatigue path is extracted, the included angle value between each group of thermal gradient direction vectors and equivalent stress direction vectors is calculated one by one, and the node number corresponding to the included angle is recorded, so that a thermal stress included angle distribution list is obtained.

[0027] S403: The thermal stress included angle distribution list is called, the included angle value is sequentially compared with the set thermal force cooperation threshold value, the thermal force cooperation deviation value is calculated, the node number whose thermal force cooperation deviation value is lower than the threshold value is screened, and the spatial coordinates in the defect area grid model are extracted, so that a thermal force cooperation risk node set is obtained.

[0028] As a further scheme of the present application, the thermal force cooperation deviation value refers to the difference between the node and the average included angle and the thermal fluctuation of the node group.

[0029] As a further scheme of the present application, the method further comprises the step of S5:

[0030] S5: Using the thermal force cooperation risk node set, a risk area contour is drawn in a three-dimensional visualization interface of a virtual simulation system according to the node spatial coordinates, the direction consistency of the nodes in the same area is clustered and connected, a continuous stress concentration area is formed, the area position and range are marked, and a stress concentration area marking result is generated.

[0031] The stress concentration area marking result comprises an area spatial range, an area position identifier, and a node direction consistency clustering result.

[0032] As a further scheme of the present application, the specific steps of S5 are:

[0033] S501: calling the spatial coordinate values ​​of the nodes in the thermal coordination risk node set, sequentially connecting adjacent nodes according to the coordinate point distribution in the three-dimensional visualization interface of the virtual simulation system, extracting boundary points to form a continuous edge structure, gradually closing the boundary segments to form a polygonal area, and obtaining a three-dimensional risk area contour boundary layer;

[0034] S502: Based on the three-dimensional risk area contour boundary layer, extract the risk node numbers in the area, call the equivalent stress direction vectors corresponding to the risk nodes, calculate the angle between the direction vectors of any two nodes in the area, select node pairs whose angle values ​​are lower than the direction consistency limit angle, and connect them in ascending order to form cluster segments to construct a continuous concentrated stress cluster unit group;

[0035] S503: Extracting spatial node coordinates based on the continuous concentrated stress clustering unit group, calculating the center point position and three-axis projection size of each unit group in the three-dimensional space, marking the center point spatial position of the stress area and the coverage range in the three-axis direction, and obtaining the concentrated stress area marking result.

[0036] The inorganic mineral casting stress analysis system based on the virtual simulation system includes:

[0037] The grain boundary extraction module obtains the voxel density distribution data of inorganic mineral casting grains scanned in a virtual simulation system in three dimensions, subtracts the density value of the voxel from that of its six adjacent voxels, compares the difference with the material interface recognition threshold, and then selects the voxel positions where the difference exceeds the threshold to generate a grain boundary curve data set.

[0038] The defect region construction module performs three-dimensional surface fitting on the region enclosed by the curve based on the grain boundary curve dataset and forms a closed defect shape, calculates the spatial difference between the defect shape and the overall grain structure, and arranges grid nodes at equal intervals to construct a defect region grid model;

[0039] The fatigue path identification module calls the defect area mesh model, applies a preset cyclic load in the virtual simulation system, obtains the three-dimensional displacement value of each mesh node at each time step, calculates the displacement change between adjacent time steps, and generates a fatigue path node distribution map;

[0040] The thermal collaborative screening module extracts the node temperature value and the adjacent node temperature value according to the fatigue path node distribution diagram, calculates the temperature difference and forms a thermal gradient direction vector, calculates the angle between the vector and the node equivalent stress direction vector, and compares it with the thermal collaborative threshold to generate a thermal collaborative risk node set;

[0041] The centralized stress marking module calls the thermal force cooperative risk node set, draws a risk area contour according to node space coordinates in a three-dimensional visualization interface, and performs clustering calculation on the direction consistency of nodes in the same area to generate a centralized stress area marking result.

[0042] Compared with the prior art, the application has the advantages and positive effects that:

[0043] In the application, by introducing the density mutation feature as the recognition basis when acquiring the grain structure boundary, the boundary deviation caused by traditional geometric approximation modeling is avoided, a closed curve network is established through the spatial continuity connection of the boundary points, the refinement degree of the grain structure modeling is improved, the continuous change relationship of node displacement trend is used to replace the centralized strain point collection in the fatigue path calibration link, and the fatigue path recognition is screened in combination with the angle relationship between the node direction vector and the crack path, so that the fatigue path recognition is independent of single point measurement, the angle cooperativity recognition mode of the thermal gradient direction and the stress direction is used to establish the direction determination standard of the thermal driving failure area, the spatial marking and clustering positioning of the centralized stress area are completed in the simulation environment, the stress analysis is ensured to have the structure level recognition ability in the thermal force coupling scene, and the stress judgment integrity of the virtual simulation system in the multi-field condition is enhanced. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0045] Figure 1 The step flowchart of the present application is shown in the figure.

[0046] Figure 2 The S1 refinement schematic diagram of the present application is shown in the figure.

[0047] Figure 3 The S2 refinement schematic diagram of the present application is shown in the figure.

[0048] Figure 4 The S3 refinement schematic diagram of the present application is shown in the figure.

[0049] Figure 5 The S4 refinement schematic diagram of the present application is shown in the figure.

[0050] Figure 6 The S5 refinement schematic diagram of the present application is shown in the figure.

[0051] Figure 7 The system module diagram of the present application is shown in the figure. DETAILED DESCRIPTION

[0052] The technical solutions in the present application will be described below with reference to the drawings.

[0053] In the embodiments of the present application, the words such as "example", "for example" are used to represent an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0054] In the embodiments of the present application, "image" and "picture" can be used interchangeably at times, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized. "Of", "corresponding" and "corresponding" can be used interchangeably at times, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized.

[0055] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1, and the meanings expressed are consistent when the distinction is not emphasized.

[0056] In order to make the technical problems, technical solutions and advantages to be solved by the present application more clear, the following will be described in detail with reference to the drawings and specific embodiments.

[0057] Please refer to Figure 1 The embodiments of the present application provide a stress analysis method for inorganic mineral castings based on a virtual simulation system, comprising the following steps:

[0058] S1: Obtain the voxel density distribution data of the inorganic mineral casting grain in the three-dimensional scanning of the virtual simulation system, call the density values of the voxel and six adjacent voxels to perform subtraction operation, screen the voxel positions with density difference exceeding material interface recognition, take the voxel positions as structure boundary points, connect the adjacent boundary points into a closed boundary curve network to obtain the grain boundary curve data set;

[0059] S2: Call the grain boundary curve data set, perform three-dimensional surface fitting on the curve surrounding area to form a closed defect shape, utilize the space difference between the defect shape and the overall grain structure to construct a local independent area, arrange nodes in the virtual simulation system grid at equal intervals to construct a defect area grid model;

[0060] S3: Based on the defect area grid model, apply the preset cyclic load in the virtual simulation system, call the three-dimensional displacement value of the grid node at the time step, calculate the displacement change at the adjacent time step, and construct the displacement change sequence according to the node number, screen the node section with continuous increase of change value, and generate the fatigue path node distribution map;

[0061] S4: Call the node temperature value and the adjacent node temperature value in the fatigue path node distribution map, calculate the temperature difference and form the thermal gradient direction vector, compare the thermal gradient direction vector with the node equivalent stress direction vector, screen the risk nodes with the angle below the thermal force cooperation threshold, and generate the thermal force cooperation risk node set;

[0062] S5: Use the thermal force cooperation risk node set to draw the risk area contour according to the node spatial coordinates in the three-dimensional visualization interface of the virtual simulation system, cluster and connect the direction consistency of the nodes in the same area to form a continuous stress concentration area, and label the area position and range to generate the stress concentration area labeling result;

[0063] The grain boundary curve data set includes boundary point coordinates, boundary curve topology relationship, and boundary curve closure, the defect area grid model includes grid element size, grid node spatial distribution, and defect area volume shape, the fatigue path node distribution map includes node number sequence, node spatial path, and path change trend, the thermal force cooperation risk node set includes risk node coordinates, thermal gradient direction, and equivalent stress direction, and the stress concentration area labeling result includes area spatial range, area position identification, and node direction consistency clustering result.

[0064] Please refer to Figure 2 , the specific steps of S1 are:

[0065] S101: Obtain the voxel density distribution data of the inorganic mineral casting grain in the three-dimensional scanning of the virtual simulation system, call the density values of the six adjacent voxels in the three-dimensional direction for the voxel position, respectively perform subtraction operation on the real-time voxel density value and the six adjacent voxel density values, record the obtained difference value, identify the difference between the obtained difference value and the real-time voxel density value, and generate the density mutation voxel coordinate set;

[0066] The voxel resolution parameter setting needs to be completed in the scanning, and the voxel side length is set to 0.01 mm to ensure high-precision scanning data. After obtaining the three-dimensional scanning data, the voxel reconstruction is performed, the scanning point cloud data is mapped to the three-dimensional grid voxel unit through space mapping, for each voxel point V(x, y, z), the density values of the six adjacent voxel points in the positive and negative directions of the x, y and z axes are extracted in turn through the construction of the three-dimensional adjacent structure, and are denoted as The current voxel density value is recorded, and the subtraction operation is performed​ minus to The operation is recorded as , For any voxel point whose Δi value is greater than the set density change threshold τ, it is considered that there is a density mutation. The density change threshold τ can be set according to the actual material density variation range. For example, for inorganic mineral castings, if the average density is 3.5g / cm³ and the fluctuation range is ±0.2g / cm³, τ can be set to 0.3g / cm³. For example: The density is 3.6g / cm³, and the six adjacent voxels are 3.2, 3.4, 3.5, 3.6, 3.7, and 3.3g / cm³ respectively. Then the Δ values ​​are 0.4, 0.2, 0.1, 0, -0.1, and 0.3. According to τ=0.3, only and If the conditions are met, record the current voxel The coordinates are density mutation points, generating density mutation voxel coordinate sets.

[0067] S102: calling the density mutation voxel coordinate set, combining the spatial positions of adjacent voxels in the three-dimensional grid, sequentially connecting the voxel coordinates that satisfy the spatial connection relationship, and determining the continuity of adjacent positions in the three-dimensional coordinate axis direction. The coordinate sets of the voxel points are grouped and classified according to the continuity to obtain a boundary point coordinate combination sequence;

[0068] The position of each voxel point in the three-dimensional space is analyzed, and the eight-adjacency relationship in the three-dimensional space is established according to the coordinates of the voxel points. The adjacency matrix is ​​constructed by judging whether the change of the x, y, and z coordinate values ​​between adjacent voxels is ±1. The adjacent voxels are connected by the breadth-first traversal algorithm to form connected subsets. Each subset is a potential grain boundary area. For example, the voxel points V(10, 10, 10), V(10, 11, 10), and V(11, 11, 10) meet the adjacency conditions and are classified into the same subset. The distribution continuity of the voxel points in each connected subset in the direction of the three-dimensional coordinate axis is judged to determine Whether there is a discontinuity in a certain direction, that is, whether there is a hole between adjacent voxels. If there is no break, it is considered continuous, and the voxel points are classified according to continuity. For example, the voxel coordinate set in the connected area is {(10, 10, 10), (10, 11, 10), (10, 12, 10), (10, 14, 10)}. Since (10, 13, 10) is missing, it is regarded as two continuous areas and split into two boundary point sequences {(10, 10, 10), (10, 11, 10), (10, 12, 10)} and {(10, 14, 10)} to form a boundary point coordinate combination sequence.

[0069] S103: Based on the boundary point coordinate combination sequence, the spatial positions between adjacent boundary points are connected to construct a three-dimensional curve unit, and the spatial closed structure is formed by connecting the boundary points. The non-closed point pairs with abnormal coordinate intervals are removed, the complete and continuous boundary line segment network is connected, and the grain boundary curve data set is obtained;

[0070] The coordinates of each pair of adjacent points are sequentially taken out for Euclidean distance calculation, and connected to form a line segment. By using a three-dimensional space linear interpolation method, a three-dimensional curve unit connecting adjacent boundary points is constructed, such as connecting point A (10, 10, 10) and B (10, 11, 10), line segment L = =1, forming a basic boundary line segment. The line segments are connected in a loop to form a closed loop structure. If the distance between two boundary points exceeds a set threshold δ, the point pair is removed. The δ value needs to be set according to the actual grain size, for example, if the average diameter of the grain is 30 μm, δ = 2 μm. The distance between boundary points P (20, 20, 20) and Q (25, 20, 20) is 5 μm, which is determined as an abnormal point pair. After removal, only the points that meet the continuous connection condition are retained, the construction of the closed boundary curve is completed, and the network structure containing the complete and continuous boundary line segment is obtained, forming the grain boundary curve data set.

[0071] Please refer to Figure 3 , the specific steps of S2 are:

[0072] S201: Call the grain boundary curve data set, select the spatial position coordinates of each group of three consecutive boundary points according to the arrangement order of the grain boundary curve in the three-dimensional coordinate system, construct an initial triangular patch by three-point plane method, generate a continuously distributed triangular mesh after traversing the boundary point set, remove the mesh patches with abnormal vertex spacing, and generate a continuous three-dimensional fitting patch group;

[0073] According to the arrangement order of the curve in the three-dimensional coordinate system, the boundary points are sequentially arranged and combined. Three groups of adjacent boundary points are selected each time, and an initial triangular patch is generated by connecting three points. In the construction process, the system realizes continuous combination by using adjacent point index increment traversal. By using the plane rule defined by the boundary point coordinates in three-dimensional space, a group of patch units with spatial continuity are gradually connected and constructed. In the process of generating the patch, the system preliminarily judges the spatial distance relationship between each group of three points. If the distance between two points is much larger than the average distance between the remaining boundary points, it is considered to have an abnormal mutation. The distance difference value judgment method is used for screening. If the average distance between the boundary points is 5 μm, and the distance of one side of the three points exceeds 15 μm, it is considered that there is a coordinate outlier. The patch is removed and not included in the fitting range. The boundary point combinations that meet the conditions in the traversal process are all involved in the triangular mesh construction, and the adjacent three-point set is continuously updated to form a continuous curved surface structure. The three-point update is continuously performed until the boundary point set traversal is completed, and a continuous three-dimensional fitting patch group is generated.

[0074] S202: Based on the continuous three-dimensional fitting face piece group, the edge position of the fitting face piece is connected, it is detected whether the boundary line segment forms a closed path, interpolation is generated for the non-closed part to generate a missing face piece, and the whole surface profile is closed to form a defect three-dimensional shape boundary body;

[0075] The edge information of each face piece is extracted and integrated into a whole boundary line segment set, the three boundary coordinate points of each triangular face piece are recorded, and the boundary line segments are merged and processed, the spatial connection state between the end points of each line segment is judged, for the boundary line segments that cannot form a closed loop structure, the position interpolation method is used to construct the missing intermediate face piece, so that the spatial continuity with the connected face piece is formed, and the relative position, direction change, curvature trend and other parameters between the line segments are considered in the interpolation process. For the part with small distance between the line segments but not connected into a closed loop, reasonable interpolation points are generated according to the direction of the adjacent points to construct triangular face pieces to fill the gap. If the distance between two boundary segments in space is less than the set limit distance, a bridge edge will be automatically generated to form a new triangular face piece to close the area, and the non-closed boundary is gradually completed. The patch operation maintains the continuity of the adjacency and the natural transition of the curved surface, forms a defect three-dimensional shape boundary body structure with strict structure and closed boundary, and provides a reliable basic model for subsequent structure difference identification and spatial analysis to form a complete three-dimensional closed curved surface profile.

[0076] S203: The defect three-dimensional shape boundary body and the original grain voxel density distribution data are called, the volume space coincidence of the corresponding positions in the three-dimensional coordinate system is compared, the coordinate point set inside the defect boundary body but not covered by the original grain voxel is extracted, the coordinate point set is defined as the local difference space position, and the independent area number is marked according to the three-dimensional boundary closure to obtain the internal difference space area of the grain;

[0077] The defect three-dimensional shape boundary body and the original grain voxel density distribution data are mapped in space. Each voxel coordinate is taken as a detection unit. The system checks whether there is a matching item in the original grain density data voxel set for each space point in the defect shape boundary body. Through the comparison of the coordinate points in the boundary body and the original voxel set, if a coordinate is inside the defect boundary body but does not correspond to the original grain voxel, the point is identified as a difference space position. The system archives and records the difference point set, and performs grouping processing based on the spatial position continuity. The difference space structure is constructed using the spatial clustering method. Each difference segment is labeled according to its connection relationship with the adjacent difference points in the three-dimensional space. Through step-by-step traversal of the adjacent direction of the difference points, if the adjacent coordinate points also belong to the difference point set, they are classified into the same area. After the marking is completed, each spatial difference structure is assigned a unique number for subsequent identification, visualization and analysis to obtain the internal difference space area of the grain.

[0078] S204: According to the spatial region difference inside the grain, the grid nodes are divided at equal intervals within the three-dimensional coordinate boundary, and the three-dimensional octahedral units are constructed after the nodes are sequentially numbered. The boundary overlapping nodes are removed and the heterogeneous units are filled to construct the grid model of the defect region;

[0079] The three-dimensional region grid division model is established within the coordinate range frame. During the division process, the grid nodes are generated by using equal interval interpolation method. The boundary range is evenly cut in X, Y and Z directions to form a regular three-dimensional grid point array. Each direction is equally divided into several segments. The generated nodes are sequentially numbered according to the coordinate order to facilitate the establishment of subsequent structural units. Each eight adjacent nodes form an octahedral unit. The position of the unit body is determined according to the spatial arrangement rule, and the grid surface is constructed by connecting the edges to avoid node repetition or unit overlap. If there are repeated nodes with the remaining units in the boundary area, the nodes are automatically removed or offset to form an independent node set without repetition. In the internal difference area, the material property inhomogeneity marker is set. Different label values are assigned to part of the units for subsequent multi-property simulation. For example, the unit number from 100 to 120 in a certain area is defined as a high-density difference area. The remaining area is set as a normal unit. The entire difference area grid model is constructed by node numbering and unit mapping method, so that the structure has complete topology, spatial uniformity and subsequent analysis executability. The grid model of the defect region is constructed.

[0080] Please refer to Figure 4 The specific steps of S3 are as follows:

[0081] S301: Based on the grid model of the defect region, a set of cyclic load boundary conditions is applied in the virtual simulation system according to the time axis. The three-dimensional coordinate values of the grid nodes at multiple time steps are recorded. The three-dimensional coordinate difference between adjacent time steps is called. The three-dimensional displacement change value of the node between adjacent time steps is calculated to obtain the time step displacement change data.

[0082] Load the time axis parameters in the virtual simulation system. Set the total loading time, time step interval and cyclic load characteristics. Set the load frequency, amplitude, direction, etc. and input the parameters into the system boundary condition module. The system applies the load according to the set cyclic boundary conditions. After the action of each time step is completed, the simulation module records the three-dimensional coordinate value change of the current grid node to form the sequence data of the node coordinate evolution with time. The coordinate difference value between time steps is calculated for each node number, i.e. the current time step coordinate and the previous time step coordinate are processed by vector difference to obtain the displacement change vector of the current time step. The displacement difference value of the node is stored as time step displacement change data. This data set covers the displacement change result between the simulation nodes and the time steps to form a multi-dimensional data set of the spatial position response of the node under load. The time step displacement change data is obtained.

[0083] S302: Call the time step displacement change data, arrange the displacement change value under the time step in turn according to the node number, construct the time sequence data corresponding to the node, count the numerical difference between the adjacent time step change values in the node sequence, and judge whether there is a continuous increasing change trend, mark the node number section that meets the continuous increasing characteristics, and obtain the continuous growth node number group;

[0084] The system sorts the time sequence displacement change value of each node according to the node number order, and forms a group of continuous sequence data from the displacement change in the time step. The system gradually calculates the numerical difference between each pair of adjacent time steps in the sequence, that is, the difference between the displacement values at the time points, obtains the continuous difference value sequence, and then judges whether there are three or more adjacent time steps whose displacement changes continuously increase, that is, the difference value is positive and increasing. The displacement sequence of a certain node is [0.02, 0.03, 0.05, 0.08], and its difference value sequence is [+0.01, +0.02, +0.03], which belongs to the continuous growth trend. The node number is identified and recorded, and the node numbers that meet the rule are grouped and sorted according to the number range to obtain the continuous growth node number group. And The system sorts the time sequence displacement change value of each node according to the node number order, and forms a group of continuous sequence data from the displacement change in the time step. The system gradually calculates the numerical difference between each pair of adjacent time steps in the sequence, that is, the difference between the displacement values at the time points, obtains the continuous difference value sequence, and then judges whether there are three or more adjacent time steps whose displacement changes continuously increase, that is, the difference value is positive and increasing. The displacement sequence of a certain node is [0.02, 0.03, 0.05, 0.08], and its difference value sequence is [+0.01, +0.02, +0.03], which belongs to the continuous growth trend. The node number is identified and recorded, and the node numbers that meet the rule are grouped and sorted according to the number range to obtain the continuous growth node number group.

[0085] S303: According to the continuous growth node number group, extract the spatial position coordinates of the corresponding node in the defect area grid model, connect the adjacent nodes in turn according to the node number arrangement order, construct the path line segment representing the change trend direction, and output the path line segment set in the three-dimensional space after being marked by the number, to obtain the fatigue path node distribution map;

[0086] The three-dimensional coordinates corresponding to the node number are extracted from the defect area grid model, the spatial positions of each node are read in turn according to the number order, and the line segment path is constructed according to the coordinate relationship between adjacent nodes. The continuous connection of the line segments represents the evolution direction of the displacement trend in the space. The path line segment set is marked as the main path of the fatigue response, and each path line segment is uniquely identified by the node number at its start and end points during output, and its position coordinates in the three-dimensional space are recorded. The path line segment set can be output to the visualization module in the form of three-dimensional graphics, and the paths are marked by different colors or numbers to distinguish the evolution degree between the path segments, complete the extraction and graphics construction of the fatigue path, realize the accurate expression of the node spatial response path, and obtain the fatigue path node distribution map.

[0087] Please refer to Figure 5 , the specific steps of S4 are:

[0088] S401: Call the node number in the fatigue path node distribution diagram, extract the corresponding temperature value according to the node sequence number, synchronously obtain the temperature value of the six spatial adjacent nodes of the node, combine the temperature difference between the real-time node and the adjacent node, identify the distribution direction of the temperature difference value in the three-dimensional coordinate system, integrate the direction vector and perform vector superposition to obtain the thermal gradient direction vector group;

[0089] According to the spatial position index of each node, the temperature record value of the node in the simulation process is sequentially extracted, and the node number of the adjacent node in six directions (±X, ±Y, ±Z) in the three-dimensional grid structure is called to obtain the temperature value corresponding to each adjacent node, forming a temperature data group containing the current node and six adjacent nodes. The temperature difference between each group of adjacent points is processed in direction, that is, the temperature difference value in each adjacent direction is converted into the temperature gradient component along the direction. The temperature of the current node is set to , the temperature of the adjacent point in the +X direction is , and the X direction gradient component is . The temperature gradient components in six directions are calculated respectively, the direction components are combined into gradient vectors according to the corresponding coordinate axes, the six gradient vectors are subjected to vector merging processing, and the total thermal gradient direction vector at the node is formed by weighted superposition or direct linear superposition. In this way, the nodes on the fatigue path are traversed to obtain the thermal gradient direction vector group.

[0090] S402: According to the thermal gradient direction vector group, the equivalent stress direction vector data recorded in the fatigue path corresponding to the node is extracted, the included angle value between each group of thermal gradient direction vectors and equivalent stress direction vectors is calculated one by one, and the node number corresponding to the included angle is recorded to obtain the thermal stress included angle distribution list.

[0091] According to the recorded equivalent stress direction vector data in the fatigue path node, the node number is matched one by one to ensure that each group of direction vector data corresponds to the same spatial position. The system calculates the included angle value between each group of thermal gradient vectors and stress direction vectors by using the three-dimensional vector included angle formula. The formula obtains the included angle cosθ through the vector dot product and the length ratio, and inversely calculates the included angle θ degrees. The included angle calculation is performed once for each node, and the obtained included angle value and the corresponding node number are recorded at the same time. Each row contains node number, thermal gradient vector, stress vector and included angle value, which supports sorting, filtering and graphical output processing of the list. The formation of the included angle value reflects the spatial coupling direction between the heat flow and the mechanical stress, and provides a directly quantifiable direction deviation index basis for subsequent node risk identification. The thermal stress included angle distribution list is obtained.

[0092] S403: Call the thermal stress angle distribution list, in turn, the angle value and the set of thermal force synergy threshold value comparison, calculate the thermal force synergy deviation value, screening thermal force synergy deviation value below the threshold of node number, and extract the spatial coordinates in the defect area grid model, get the thermal force synergy risk node set;

[0093] Thermal force synergy deviation value, using the formula:

[0094] ;

[0095] Wherein, is the thermal force synergy deviation value of the first node, represents the thermal stress angle value of the first node, represents the thermal stress angle value of the first node, represents the average value of the node angle value, indicates the set threshold value, indicates the sample variance of the angle set ;

[0096] The calculation logic of the formula: absolute value item represents the deviation of the current node angle and the average thermal stress angle, which is used to measure the individual difference; square root item is the square root of the mean square deviation of the node angle, that is, the overall dispersion trend of the set, which reflects the global risk volatility; the sum of the two constitutes the numerical basis of the deviation; divide the result by the thermal threshold , for normalization processing, standardize the difference degree; multiply the correction factor , the variance ratio measures the relative weight of thermal stress fluctuation and overall mean, which is used to adjust the response strength of the previous calculation value to the risk;

[0097] Thermal force synergy deviation value is a quantitative index to measure the deviation between the thermal stress angle of a node and the average state of the overall thermal field, considering the difference between the node and the average angle and the thermal fluctuation of the entire node group. The larger the value, the higher the risk of cooperative instability or damage of the node under the action of thermal force;

[0098] Parameter meaning and calculation process:

[0099] : The angle value of the first node in thermal stress simulation, unit: degree (°);

[0100] : The arithmetic mean value of the node angle value, the formula is , which is calculated from the set of all simulation node angles;

[0101] : Variance term of angle set, used to represent global fluctuation, N is the total number of nodes;

[0102] : Thermal synergy threshold, reference material mechanics safety margin set to 25°, which is based on the empirical value of thermal load failure critical angle;

[0103] : Angle set Sample variance of angle set, calculated as Shared data source with the previous item but used for internal factor calculation;

[0104] To verify the availability of the formula, the simulation angle results of 6 key thermal nodes in a certain local area are as follows:

[0105] Table 1: Thermal stress angle monitoring data table

[0106]

[0107] As shown in Table 1, set the current node as node 1, its angle value is , according to which the parameter calculation is carried out:

[0108] Calculate the average value :

[0109] ;

[0110] Calculate the variance term :

[0111] ;

[0112] ;

[0113] Calculate the square root of the square difference term :

[0114] ;

[0115] Calculate the absolute value difference term :

[0116] ;

[0117] Combine to construct the deviation degree calculation:

[0118] ;

[0119] First calculate the score term:

[0120] ;

[0121] ;

[0122] Substitute into the formula for calculation:

[0123] ;

[0124] The results show that the thermal synergy deviation of node 1 is 0.1884, which is relatively low compared to the benchmark interval (the low risk standard is empirically set to ), indicating that the current node is in a low-risk range. Nodes with higher risk can be retained or prioritized for analysis later.

[0125] The benefit of the formula is that by combining and superimposing the individual angle deviation term with the global mean square error term and introducing a correction based on the ratio of the angle variance to the square of the mean, it takes into account both single-point abnormal fluctuations and overall trend deviations. In the collaborative risk detection of the thermal field, isolated anomalies and disturbances can be identified simultaneously, thereby improving the sensitivity and accuracy of node screening.

[0126] See also Figure 6 , the specific steps of S5 are:

[0127] S501: Calling the spatial coordinate values ​​of nodes in the thermal coordination risk node set, sequentially connecting adjacent nodes according to the coordinate point distribution in the three-dimensional visualization interface of the virtual simulation system, extracting boundary points to form a continuous edge structure, gradually closing the boundary segments to form a polygonal area, and obtaining a three-dimensional risk area contour boundary layer;

[0128] The nodes are loaded one by one in the three-dimensional visualization environment of the virtual simulation system according to the node number, and the adjacent nodes are connected according to the spatial proximity relationship between the coordinate points to form an initial line segment network. It is judged whether the connection between the nodes meets the spatial adjacency condition, that is, whether the Euclidean distance between the nodes is lower than the set connection threshold. If the condition is met, the node pair is constructed as a line segment, and multiple boundary point closed-loop structures are constructed through continuous connection. The coordinates of the boundary points that form the line segments are identified, and the boundary points are connected into continuous polygonal boundary lines in spatial order. During the processing, the distance between the first and last points is verified. If the distance between the two points is lower than the set end tolerance, the boundary is determined to be closed. If not closed, interpolation connection is performed to ensure that the boundary line is closed to form a closed polygon area. The closed polygon outline is combined through three-dimensional coordinate mapping to obtain a three-dimensional risk area outline boundary layer.

[0129] S502: Based on the three-dimensional risk area contour boundary layer, the risk node number in the area is extracted, the equivalent stress direction vector corresponding to the risk node is called, the included angle value between the direction vectors of any two nodes in the area is calculated, the node pairs with the included angle value lower than the direction consistency limited angle are screened, and the clustering line segments are connected in ascending order to form a continuous concentrated stress clustering unit group;

[0130] The risk node number contained in the space region surrounded by the layer is screened, and the equivalent stress direction vector corresponding to the node is called. The direction vector data formed by the nodes in the region are combined and arranged. The included angle value between the direction vectors of each group of nodes is calculated. After the included angle value of the two vectors is calculated through the vector included angle formula, it is compared with the set direction consistency limited angle. If the included angle is less than the limited angle (such as 15°), it is considered that the stress direction of the node pair is highly consistent, and the node pair number is recorded. The node pairs meeting the condition are sorted in ascending order according to the number. The clustering line segments are constructed one by one. The node pairs with consistent directions and close positions are connected to form continuous line segments. If the line segments have continuity and node number sequence consistency, they are integrated into the same clustering unit. According to the connection continuity between the nodes in the layer, a plurality of continuous concentrated stress clustering unit groups are automatically divided. Each group contains a plurality of nodes and a set of direction consistency line segments formed by the nodes. It is used for subsequent space center analysis and size extraction processing to construct a continuous concentrated stress clustering unit group.

[0131] S503: According to the continuous concentrated stress clustering unit group, the space node coordinates are extracted, the center point position and three-axis projection size of each unit in the three-dimensional space are calculated, and the center point space position and three-axis direction coverage range interval of the stress area are marked respectively to obtain the concentrated stress area marking result;

[0132] The space coordinate values of the nodes contained in each unit group are extracted, and a geometric distribution model of the point set in the three-dimensional space is constructed based on the space coordinate values. The geometric center point of each point set is calculated. The center point coordinates are the average values of the space coordinates of the nodes in the clustering unit. The three-dimensional center position of each concentrated stress area is obtained. The maximum and minimum coordinate values of each clustering unit in X, Y and Z directions are counted to determine the coverage range interval of the unit group in three-axis direction, that is, the X-axis direction interval is [minX, maxX], the Y-axis direction interval is [minY, maxY], and the Z-axis direction interval is [minZ, maxZ]. The three-axis size projection forms the bounding box representation of the clustering unit in the three-dimensional space. The center position of each clustering area is marked, and the three-axis coverage interval is identified to form a complete concentrated stress area marking result.

[0133] Please refer to Figure 7 , the inorganic mineral casting stress analysis system based on virtual simulation system, comprising:

[0134] The grain boundary extraction module obtains voxel density distribution data of the inorganic mineral casting grain in the virtual simulation system three-dimensional scanning, calls the density values of the voxel and six adjacent voxels to perform subtraction operation, compares the difference value with the material interface recognition threshold, screens the voxel position whose difference value exceeds the threshold, and generates grain boundary curve data set;

[0135] The defect area construction module performs three-dimensional surface fitting on the curve surrounding area based on the grain boundary curve data set, forms a closed defect shape, calculates the space difference between the defect shape and the overall grain structure, arranges grid nodes at equal intervals, and constructs a defect area grid model;

[0136] The fatigue path recognition module calls the defect area grid model, applies a preset cyclic load in the virtual simulation system, obtains three-dimensional displacement values of each grid node at each time step, calculates displacement changes between adjacent time steps, and generates a fatigue path node distribution map;

[0137] The thermal force synergistic screening module extracts node temperature values and adjacent node temperature values to calculate temperature difference and form a thermal gradient direction vector, calculates the included angle between the vector and the equivalent stress direction vector of the node, compares it with the thermal force synergistic threshold, and generates a thermal force synergistic risk node set;

[0138] The concentrated stress labeling module calls the thermal force synergistic risk node set, draws the risk area contour in the three-dimensional visualization interface according to the node space coordinates, and performs clustering calculation on the direction consistency of the nodes in the same area to generate a concentrated stress area labeling result.

[0139] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any skilled person in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. The stress analysis method of inorganic mineral castings based on virtual simulation system is characterized by: The following steps are involved: S1: Obtain voxel density distribution data of inorganic mineral casting grains in a 3D scan of a virtual simulation system, select voxel positions where the density difference exceeds the material interface recognition, connect adjacent boundary points into a closed boundary curve network, and obtain a grain boundary curve dataset; S2: calling the grain boundary curve dataset, performing three-dimensional surface fitting on the area enclosed by the curve to form a closed defect shape, using the spatial difference between the defect shape and the overall grain structure to construct a local independent area, arranging nodes at equal intervals in the virtual simulation system grid, and constructing a defect area grid model; S3: Based on the defect area mesh model, a preset cyclic load is applied in the virtual simulation system, the three-dimensional displacement value of the mesh node in the time step is called, the displacement change amount of the adjacent time step is calculated, and the fatigue path node distribution diagram is generated; S4: Call the fatigue path node distribution diagram, obtain the node temperature value and the adjacent node temperature value, calculate the temperature difference and form a thermal gradient direction vector, compare the angle between the thermal gradient direction vector and the node equivalent stress direction vector, and generate a thermal synergy risk node set.

2. The method for stress analysis of inorganic mineral castings based on a virtual simulation system according to claim 1, characterized in that: The grain boundary curve dataset includes boundary point coordinates, boundary curve topological relationship, and boundary curve closure; the defect area grid model includes grid unit size, grid node spatial distribution, and defect area volume morphology; the fatigue path node distribution diagram includes node number sequence, node spatial path, and path change trend; the thermal synergy risk node set includes risk node coordinates, thermal gradient direction, and equivalent stress direction.

3. The inorganic mineral casting stress analysis method based on a virtual simulation system according to claim 1, characterized in that: The specific steps of S1 are: S101: obtaining voxel density distribution data of inorganic mineral casting grains scanned in a virtual simulation system in three dimensions, calling the density values ​​of six adjacent voxels in the three-dimensional direction for each voxel position, performing subtraction operations on the real-time voxel density value and the six adjacent voxel density values, recording the obtained differences, identifying the difference between the obtained differences and the real-time voxel density value, and generating a density mutation voxel coordinate set; S102: calling the density mutation voxel coordinate set, combining the spatial positions of adjacent voxels in the three-dimensional grid, sequentially connecting the voxel coordinates that satisfy the spatial connection relationship, and determining the continuity of adjacent positions in the three-dimensional coordinate axis direction. Grouping and classifying the voxel coordinate sets according to the continuity, and obtaining a boundary point coordinate combination sequence; S103: Based on the boundary point coordinate combination sequence, the spatial positions between adjacent boundary points are connected to construct a three-dimensional curve unit, and the boundary points are cyclically connected to form a spatial closed structure, and non-closed point pairs with abnormal coordinate intervals are eliminated. The complete and continuous boundary line segment network is connected to obtain a grain boundary curve dataset.

4. The method for stress analysis of inorganic mineral castings based on a virtual simulation system according to claim 3, characterized in that: The specific steps of S2 are: S201: calling the grain boundary curve dataset, selecting the spatial position coordinates of each group of three consecutive boundary points according to the arrangement order of the grain boundary curves in the three-dimensional coordinate system, constructing an initial triangular facet in a three-point faceting method, looping through the boundary point set to generate a continuously distributed triangular mesh, removing mesh faces with abnormal vertex spacing, and generating a continuous three-dimensional fitting facet group; S202: Based on the continuous three-dimensional fitting patch group, the edge positions of the fitting patches are connected, and whether the boundary segments form a closed path is detected. The missing patches are generated by interpolation for the non-closed parts, and the overall surface contour is closed to form a defective three-dimensional shape boundary body; S203: Recalling the three-dimensional boundary volume of the defect and the density distribution data of the original grain voxels, comparing the volumetric spatial overlap of the corresponding positions of the two in the three-dimensional coordinate system, extracting a set of coordinate points within the defect boundary volume but not covered by the original grain voxels, defining the set of coordinate points as a local difference spatial position, and marking independent region numbers according to the three-dimensional boundary closure to obtain the difference spatial region inside the grain; S204: Divide the grid nodes at equal intervals within the three-dimensional coordinate boundary according to the spatial difference region inside the grain, construct three-dimensional octahedral units after numbering the nodes in sequence, remove the boundary overlapping nodes and fill the heterogeneous units to construct a grid model of the defect area.

5. The method for stress analysis of inorganic mineral castings based on a virtual simulation system according to claim 4, characterized in that: The specific steps of S3 are: S301: Based on the defect area mesh model, applying a set cyclic load boundary condition along the time axis in the virtual simulation system, recording the three-dimensional coordinate values ​​of the mesh nodes in multiple time steps, calling the three-dimensional coordinate differences of the nodes between adjacent time steps, calculating the three-dimensional displacement change values ​​of the nodes between adjacent time steps, and obtaining time step displacement change data; S302: calling the displacement change data of the time step, arranging the displacement change values ​​under the time step in sequence according to the node number, constructing the time series data corresponding to the node, counting the numerical differences between the change values ​​of adjacent time steps in the node sequence, and determining whether there is a continuous increasing trend, marking the node number segments that meet the continuous increasing feature, and obtaining a continuously increasing node number group; S303: Based on the continuously growing node number group, the spatial position coordinates of the corresponding nodes in the defect area grid model are extracted, and the adjacent nodes are connected in sequence according to the node number arrangement order to construct path segments representing the direction of the change trend. The path segments are grouped in three-dimensional space and labeled by number and then output to obtain a fatigue path node distribution map.

6. The method for stress analysis of inorganic mineral castings based on a virtual simulation system according to claim 5, characterized in that: The specific steps of S4 are: S401: Calling the node number in the fatigue path node distribution map, extracting the corresponding temperature value according to the node sequence number, synchronously obtaining the temperature values ​​of the six spatially adjacent nodes of the node, combining the temperature difference between the real-time node and the adjacent nodes, identifying the distribution direction of the temperature difference in the three-dimensional coordinate system, integrating the direction vectors and performing vector superposition to obtain a thermal gradient direction vector group; S402: Extracting equivalent stress direction vector data recorded in the fatigue path of the corresponding node based on the thermal gradient direction vector group, calculating the angle between each group of thermal gradient direction vectors and the equivalent stress direction vector one by one, and recording the node number corresponding to the angle to obtain a thermal stress angle distribution list; S403: Call the thermal stress angle distribution list, compare the angle values ​​with the set thermal synergy threshold in turn, calculate the thermal synergy deviation value, filter the node numbers whose thermal synergy deviation values ​​are lower than the threshold, and extract the spatial coordinates in the defect area grid model to obtain the thermal synergy risk node set.

7. The method for stress analysis of inorganic mineral castings based on a virtual simulation system according to claim 6, characterized in that: The thermal synergy deviation value refers to the difference between the node and the average angle and the thermal fluctuation of the node group.

8. The method for stress analysis of inorganic mineral castings based on a virtual simulation system according to claim 1, characterized in that: The method further comprises step S5: S5: Using the thermal synergy risk node set, draw the outline of the risk area according to the node space coordinates in the three-dimensional visualization interface of the virtual simulation system, cluster and connect the nodes in the same area based on their directional consistency to form a continuous concentrated stress area, and mark the area position and range to generate a concentrated stress area marking result; The concentrated stress area marking result includes the area space range, area location identifier, and node direction consistency clustering result.

9. The method for stress analysis of inorganic mineral castings based on a virtual simulation system according to claim 8, characterized in that: The specific steps of S5 are: S501: calling the spatial coordinate values ​​of the nodes in the thermal coordination risk node set, sequentially connecting adjacent nodes according to the coordinate point distribution in the three-dimensional visualization interface of the virtual simulation system, extracting boundary points to form a continuous edge structure, gradually closing the boundary segments to form a polygonal area, and obtaining a three-dimensional risk area contour boundary layer; S502: Based on the three-dimensional risk area contour boundary layer, extract the risk node numbers in the area, call the equivalent stress direction vectors corresponding to the risk nodes, calculate the angle between the direction vectors of any two nodes in the area, select node pairs whose angle values ​​are lower than the direction consistency limit angle, and connect them in ascending order to form cluster segments to construct a continuous concentrated stress cluster unit group; S503: Extracting spatial node coordinates based on the continuous concentrated stress clustering unit group, calculating the center point position and three-axis projection size of each unit group in the three-dimensional space, marking the center point spatial position of the stress area and the coverage range in the three-axis direction, and obtaining the concentrated stress area marking result.

10. The inorganic mineral casting stress analysis system based on virtual simulation system is characterized by: The system is used to implement the inorganic mineral casting stress analysis method based on a virtual simulation system according to any one of claims 1 to 9, and the system includes: The grain boundary extraction module obtains the voxel density distribution data of inorganic mineral casting grains scanned in a virtual simulation system in three dimensions, subtracts the density value of the voxel from that of its six adjacent voxels, compares the difference with the material interface recognition threshold, and then selects the voxel positions where the difference exceeds the threshold to generate a grain boundary curve data set. The defect region construction module performs three-dimensional surface fitting on the region enclosed by the curve based on the grain boundary curve dataset and forms a closed defect shape, calculates the spatial difference between the defect shape and the overall grain structure, and arranges grid nodes at equal intervals to construct a defect region grid model; The fatigue path identification module calls the defect area mesh model, applies a preset cyclic load in the virtual simulation system, obtains the three-dimensional displacement value of each mesh node at each time step, calculates the displacement change between adjacent time steps, and generates a fatigue path node distribution map; The thermal collaborative screening module extracts the node temperature value and the adjacent node temperature value according to the fatigue path node distribution diagram, calculates the temperature difference and forms a thermal gradient direction vector, calculates the angle between the vector and the node equivalent stress direction vector, and compares it with the thermal collaborative threshold to generate a thermal collaborative risk node set; The concentrated stress marking module calls the thermal synergy risk node set, draws the risk area outline according to the node space coordinates in the three-dimensional visualization interface, and performs cluster calculation on the consistency of node directions in the same area to generate concentrated stress area marking results.

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