116 results about "Computer-aided engineering" patented technology

The invention belongs to the technical field of geometric pretreatment in computer aided engineering (CAE), and particularly relates to a dirty geometry restoration method for a complex three-dimensional geometric model, which comprises a dirty geometry detection and restoration module based on heuristic rules and geometric topology analysis. By means of a multi-model collaborative alignment and bonding mechanism, high-precision assembly between parts is achieved through geometric feature matching and adjacent domain self-adaptive adsorption; acquiring material attributes provided by the simulation platform, and performing accurate cutting and boundary reconstruction on an intersection domain based on an intersection domain intelligent segmentation algorithm of the material attributes to ensure correct mapping of boundary conditions of a physical field; a geometric Boolean processing engine iterative learning mechanism of a general merging algorithm is integrated, and a high-quality model for simulating a grid is generated through multi-round iterative optimization. According to the method, double challenges of internal dirty geometry of a single model and derivative dirty geometry of intersection / adjacent areas among multiple bodies are solved, and key physical attributes and topological continuity of electromagnetic signal links are ensured and are completely reserved during repair.

The invention relates to the technical field of computer-aided engineering, in particular to a nonlinear efficient iterative solving method for thermal strain load, which is used for solving an obtained finite element equation by using a modified Newton-Raphson method and comprises the following steps of: firstly, establishing a geometric model to be analyzed and performing grid division; the method comprises the following steps: firstly, setting a model to be analyzed, then setting boundary conditions and temperature field change conditions of the model to be analyzed, finally, inputting the conditions into an algorithm solver, solving a nonlinear equation set, iteratively inputting a load continuously according to a modified Newton-Raphson method in the solving process, calculating node displacement until convergence, and solving stress-strain conditions in the welding process according to a material constitutive relation. In the solving process, by judging the size of the two norms of the displacement increment obtained in the adjacent increment step heuristic stage, the convergence of nonlinear solving of the structure is enhanced through the calculation mode, and the solving speed of the nonlinear problem in the thermal elastic-plastic constitutive structure is increased.

The invention discloses a three-dimensional physical field real-time prediction method and system based on geometric deep learning and physical constraint, and relates to the technical field of computer-aided engineering and artificial intelligence. The method comprises the following steps: directly extracting native boundary representation data (B-Rep) of a three-dimensional model from a computer aided design system; constructing a heterogeneous dual graph taking a parameterized curved surface as a graph node, skipping finite element grid division, and aggregating local and global topological features by using a graph neural network; in combination with a physical information driving mechanism, a partial differential equation (PDE) residual error is introduced as a loss function for constraint training, and generalization prediction of a novel geometric structure is realized; and finally, the physical field state quantity is predicted through direct regression and is rendered in real time. An incremental reasoning mechanism based on a local topology subgraph is adopted, millisecond-level physical field real-time feedback under design modification is achieved, and the method is suitable for scheme rapid screening and trend prediction in the initial stage of design.

The invention belongs to the technical field of underground engineering and computer-aided engineering analysis, and particularly relates to an anti-seismic safety collaborative analysis method for multi-modal data of proximity tunnel engineering. By integrating engineering geology, structural design, construction monitoring and multi-level seismic oscillation data, a three-dimensional numerical model fusing geology and structural information is constructed. Firstly, refined simulation of the whole construction process and the operation static load is carried out, and a reference mechanical state is obtained; carrying out multi-task condition earthquake dynamic time history analysis on the basis, dynamically capturing dynamic response of surrounding rock and a structure, carrying out collaborative interpretation on static and dynamic analysis results, emphatically analyzing spatio-temporal evolution and connectivity risks of a tunnel anchor and an adjacent highway tunnel surrounding rock plastic zone, and extracting a plurality of quantitative collaborative indexes; and an interactive analysis report integrating a three-dimensional visual scene, a multi-dimensional comparison chart and a rule base-based safety interpretation conclusion is automatically generated, and systematic decision support is provided for seismic design, construction control and safety evaluation of proximity projects.

The invention provides an intelligent grid size field prediction method, which comprises the steps of inputting geometric data, material parameters and boundary conditions of a to-be-processed CAE model, automatically extracting an input feature set, inputting the input feature set into a trained hybrid model, and outputting an initial grid size field; and performing post-processing on the initial grid size field, including performing smoothing processing by adopting Gaussian filtering to ensure that the size difference of adjacent patches does not exceed 20%, executing constraint verification to ensure that the grid size is within a preset range, and performing multi-physical field adaptation to take the minimum value of the size required by each physical field. And generating a CAE (Computer Aided Engineering) grid based on a post-processing grid size field driving grid generation algorithm, feeding back the grid quality in real time in a grid generation process, and if the grid distortion rate exceeds 5%, predicting and adjusting the size again. According to the method, the grid generation efficiency is remarkably improved, the manual intervention cost is reduced, the simulation precision and stability are ensured, and the method is suitable for complex engineering analysis scenes in the industries of aerospace, automobiles and the like.

The invention relates to the technical field of computer-aided engineering, and discloses an intelligent water conservancy design simulation system based on digital twinning, which comprises a parameterized geometric feature extraction module, a reduced-order model database, a tangent space linear deduction module and a flow field reconstruction module. According to the method, nonlinear flow field solution is dimensionally reduced into deterministic matrix vector multiplication, traditional statistical regression and iterative solution are replaced, it is ensured that a reconstruction result evolves in the tangential direction of a physical gradient, non-physical guess of a statistical model in a sparse sample area is avoided, and the calculation accuracy is improved. And high-fidelity flow field reconstruction with real-time performance and physical evolution conservation is realized.

The invention discloses a vehicle body grid parameter dynamic optimization method and system based on model simulation, and belongs to the crossing field of computer-aided engineering and artificial intelligence technology. According to an existing vehicle body grid optimization scheme, deep mining and analysis of grid data cannot be achieved, and consequently the accuracy and reliability of a grid optimization result are not high. According to the vehicle body grid parameter dynamic optimization method based on model simulation, a vehicle body historical database module, a vehicle body grid optimization module and a domain knowledge base module are utilized to match vehicle body grid data to be optimized with vehicle body historical data to obtain the most similar vehicle body historical data; the information is used as experience information and verification basis of vehicle body grid parameter optimization; and then experience information and a verification basis are reused, the to-be-optimized grid data of the vehicle body are analyzed and processed, and optimization suggestion information is generated, so that historical data can be deeply mined and analyzed, and the accuracy and reliability of a grid optimization result can be effectively improved.

The invention discloses a firmness safety assessment method and system for a power transmission line iron tower based on computer assistance, and belongs to the technical field of computer-aided engineering, and the method comprises the steps: forming a multi-source data set through fusing sensor, environment and historical maintenance data, and generating preprocessing data after time sequence alignment and filtering processing; and adjusting finite element mechanical parameters based on the data, constructing a dynamic parameterized finite element structure, and performing simulation to obtain physical index data. A preliminary risk index is generated by combining a historical fault library and risk rule matching, then an environment severity degree index is introduced, a comprehensive state index is obtained through calculation, hierarchical feature extraction and multi-scale fusion analysis are carried out, and finally risk early warning information is output. According to the technical scheme, the dynamic parameterization finite element structure is constructed and checked, and comprehensive evaluation and prediction are carried out in combination with data-driven risk matching, so that comprehensive and prospective evaluation and early warning of the firmness safety state of the power transmission line iron tower can be realized.

The present application belongs to the field of computer aided engineering and electromagnetic simulation technology, and relates to a Step model automatic repairing and optimizing method and system for electromagnetic simulation, the method comprising: S1: analyzing the Step model and performing geometry feature extraction and defect detection based on the analysis result, and automatically identifying different electromagnetic features based on the extracted geometry features and a preset electromagnetic knowledge base; S2: according to the electromagnetic simulation requirement, different repairing strategies are adopted for intelligent repairing of different electromagnetic features to obtain a repaired model; S3: based on the simulation acceleration requirement, the repaired model is optimized to obtain an optimized model; S4: the parameters generated in the repairing and optimizing process and the optimized model are integrated and sent to electromagnetic simulation software for electromagnetic simulation. It can greatly improve the simulation preprocessing efficiency and simulation accuracy, significantly accelerate the simulation solving process, realize the standardization and knowledge sedimentation of simulation, and form a positive closed loop.

The invention discloses a network topology reconstruction-based adaptive sampling method for a CAE (Computer Aided Engineering) agent model of a numerical control machine tool, and relates to the research field of sampling methods for agent models in multi-dimensional complex scenes such as the numerical control machine tool. S12, a sample point preprocessing and validity checking stage; s2, a network topology construction stage; s23, a network topology validity verification and weight normalization stage; s3, a topology reconstruction stage; and S4, a dynamic optimization stage. According to the network topology reconstruction-based adaptive sampling method for the CAE agent model of the numerically-controlled machine tool, a sampling process is converted into a dynamic network reconstruction process, power-law distribution, small-world effect and scale invariance characteristics in a complex network theory are fused, system key information is captured by using a network topology structure, and global search capability of a simulated annealing algorithm is combined, so that the network topology reconstruction-based adaptive sampling method for the CAE agent model of the numerically-controlled machine tool is realized. The adaptive optimization distribution of sampling points is realized, the coverage rate and representativeness of samples to different working condition characteristics are improved, and high-quality training data are provided for a numerical control machine tool CAE agent model.

This invention relates to the field of finite element analysis technology, and provides a method for designing and constructing cast-in-place piles using a single-sided open-closed temporary casing based on finite element analysis. The method includes importing constitutive parameters of soft rheological silt into computer-aided engineering nonlinear finite element software to establish a spatial mesh model of the single-sided open-closed temporary casing with upper and lower reinforcing cylinder ends and a central standard cylinder; applying high-order friction penalty function contact constraints to the sliding pin, tension rod flange, and positive and negative labyrinth joints; sequentially loading three dynamic simulation conditions: pressing, holding, and large deformation during pull-out; outputting a solid manufacturing data table based on the simulation results of the three dynamic simulation conditions; constructing a closed-loop mud circulation system to maintain head balance; and achieving low-damage pull-out and demolding. This invention combines simulation-driven design, structural optimization, and refined construction control, significantly improving the reliability, efficiency, and pile quality of cast-in-place pile construction in soft rheological strata.

The invention relates to the technical field of computer-aided engineering and structure optimization, and discloses a wind power tower crane lightweight design method based on digital twinning and multi-objective optimization, comprising the following steps: S1, constructing a full-parameterized initial three-dimensional geometric model of a wind power tower crane, and establishing a corresponding initial finite element model in a finite element simulation platform; by defining a multi-objective optimization problem taking structural mass minimization and key part equivalent stress minimization as the core and adopting a non-dominated sorting mechanism for solving, a series of Pareto optimal design schemes capable of achieving the optimal balance between the lightweight degree and the structural strength can be automatically generated; the one-sidedness possibly caused by traditional single target optimization is avoided, and designers can make decisions in a more comprehensive tradeoff space, so that the structural weight is remarkably reduced, the stress level is effectively controlled, and the overall safety and reliability of the tower crane are guaranteed.

The invention relates to the technical field of model simulation and computer-aided engineering, in particular to a drive axle housing vibration noise numerical value determination system based on model simulation. A data set generation unit, an agent model training unit, a real-time prediction unit and a closed-loop correction unit are included; the system carries out adversarial training through the high-fidelity training data set to obtain an agent model; the core is that a prediction response field is generated in real time by using an agent model, and a bottleneck hot spot area is identified; when the hot spot area is identified, the system calculates the sensitivity gradient of the hot spot area to the design parameters, and solves and optimizes the design parameters; according to the method, the prediction period conversion from several days to the instantaneous prediction period is realized, and the design iteration efficiency is greatly improved.

The application relates to the field of computer-aided engineering design, and discloses a proxy-assisted particle swarm optimization method and system for expensive black-box optimization, which comprises the following steps: a database is constructed and a proxy model is trained by using a small amount of real evaluation samples to obtain a predicted target value and uncertainty of a candidate solution; a local candidate solution is generated for each particle, a local reference position is determined based on a self-adaptive lower confidence limit criterion, and each particle is allocated a dedicated inertia weight according to the correlation between the local reference position of each particle and a global reference position; Cauchy heavy tail disturbance is introduced in particle speed updating to enhance the non-local jump-out capability; and the self-adaptive lower confidence limit criterion is used again to screen elite candidate solutions from the candidate particles for real evaluation, and the database and the proxy model are updated. Under a limited real evaluation budget, the application can dynamically balance exploration and development, improve the effectiveness of the search direction, and is suitable for high-cost black-box optimization problems such as aerodynamic shape optimization.

The application discloses a computer simulation and optimization method for oriented rubber and meat close fitting, and belongs to the technical field of computer aided engineering and virtual simulation. A three-dimensional model of rubber and meat is constructed and material properties are defined, a virtual contact interface is constructed and is discretized into multiple contact units; a finite element analysis engine is used to simulate the rubber deformation process under different candidate pressure distribution modes, and corresponding deformation sequences are generated; the relative displacement between the rubber nodes and the meat nodes at each contact unit is extracted, and the overall fitting degree coefficient is calculated; the candidate pressure distribution mode is iteratively optimized until the optimized pressure distribution mode meeting the convergence condition is obtained, and is output as the target pressure application scheme. The application can automatically find the optimal pressure application scheme for the closest fitting of rubber and meat, effectively replace the traditional process debugging mode relying on experience and repeated experiments, significantly improve the fitting quality and efficiency, and provide accurate computer guidance for the formulation of actual production processes.

The invention relates to the technical field of computer-aided engineering, in particular to an instant mode and retention mode mixed interface display interaction method and system, equipment and a medium, and the method mainly comprises the steps that a main interface is constructed, and an event bus and a data bus are constructed; all modules are initialized and loaded, each module comprises a basic control library, a layout engine and a resource management and memory management module, the basic control library comprises a retention mode and an instant mode, the retention mode is used as a main frame, the instant mode is integrated as a dynamic element, and the instant mode and retention mode mixed interface display interaction method and system are formed. The method can give full play to the advantages of the two, guarantees the stability and layout capability of the whole interface, achieves the high-performance refreshing of a local region, and achieves the efficient cooperation effect of the whole system.

The invention discloses a cloud computing-based post-processing method, device and system supporting a super-large scale model CAE simulation result, and belongs to the technical field of computer-aided engineering simulation and cloud computing. The method comprises the following steps that: a cloud end adopts a hybrid architecture to carry out self-adaptive partitioning and multi-level LOD modeling on a simulation result; the client calculates a visible area and a required LOD level according to user interaction and generates a request; the cloud side dispatches data according to needs and transmits the data in a streaming mode; and after receiving the data, the client uses a local GPU to render in real time and realize LOD dynamic smooth switching. The invention aims to solve the problems of hardware bottleneck, interaction delay and low resource utilization rate when a traditional method is used for processing super-large-scale CAE data.

The invention discloses an anti-slide pile cantilever section internal force and displacement calculation method, equipment and a medium, and relates to the technical field of engineering design, and the method comprises the following steps: solving a time-varying support reaction field parameter set and a cantilever section depth computational domain execution structural mechanics equation, and generating a predicted displacement curve and a predicted internal force curve; reconstructing the predicted displacement curve and the predicted internal force curve into a high-order tensor field, extracting local response correlation features through a depth separable convolution kernel, and generating a coupling response feature field; based on the coupling response characteristic field, reverse constraint correction is carried out on the time-varying support reaction field parameter set, combined solving is carried out in combination with a cantilever section depth calculation domain, and a correction displacement curve and a correction internal force curve are generated. According to the method, the space-time Gaussian process prior model is constructed, in computer-aided engineering, the internal force and displacement prediction precision is improved, and the reliability and applicability of cantilever section structure analysis under the complex stratum condition are achieved.

This invention discloses a lightweight design method for new energy vehicle body frames based on digital twins. The invention relates to the field of new energy vehicle body structure design and computer-aided engineering simulation technology, and includes the following steps: Step S1: Establishing a digital twin connected to the physical vehicle body sensing system; Step S2: A dynamic precision topology network module, used to dynamically divide the simulation precision region of the body frame according to the mechanical energy transfer path and real-time sensing data. This lightweight design method for new energy vehicle body frames based on digital twins achieves intelligent allocation of computing resources through a dynamic precision topology network. While ensuring accurate prediction of key structures, it effectively reduces the computational burden of multi-physics coupled simulation; it effectively resolves the sharp contradiction between model accuracy, real-time response, and optimization efficiency, enabling lightweight design to achieve effective closed-loop iteration under complex constraints.

This invention relates to the fields of computational mechanics and computer-aided engineering, specifically a mathematical model capable of predicting the forming shape of spherical bearings. The model takes the blank's geometric dimensions, mold parameters, and material elastic modulus as input. Based on the precise geometric relationships of the compression process, it establishes a system of equations, deriving the core relationship between the compression amount and the theoretical mean diameter, and solving for the theoretical shape without considering springback. By introducing the theory of compression-bending springback, it establishes springback geometric constraints and expressions for reverse stress. Based on the static equilibrium conditions under pure bending, it derives the explicit relationship between the radius after springback and the radius before springback, elastically correcting the theoretical shape to obtain a predicted shape closer to the actual forming result. The model's output can be compared and verified with finite element simulations and actual experimental data, exhibiting high prediction accuracy in the stable deformation stage with large compression amounts. This invention provides effective guidance for process parameter design and optimization, reducing the number of experiments and development cycles.

The application relates to the technical field of logistics unmanned aerial vehicle part design and computer aided engineering, and provides a logistics unmanned aerial vehicle push rod mounting seat multi-working condition stress topology optimization method and system.The method comprises the following steps: constructing multi-working condition stress boundary conditions of a push rod mounting seat; establishing an initial structure topology optimization model of the push rod mounting seat according to the multi-working condition stress boundary conditions, wherein the initial structure topology optimization model comprises a U-shaped vertical plate, a rectangular bottom plate, three groups of equidistant mounting through holes, a push rod mounting through hole, a round corner transition structure at a connecting position of the vertical plate and the bottom plate, and a boss limiting structure at both ends of the bottom plate; a double-objective function of topology optimization is set in the initial structure topology optimization model; strength constraint conditions and fatigue life constraint conditions are set; an iteration calculation is performed by using a topology optimization solver to obtain an optimal structure parameter combination meeting all the constraint conditions; and the optimal structure parameter combination is output.The method avoids performance deviation and safety hazards caused by single-working condition design.

The invention relates to the technical field of computer-aided engineering and mechanical transmission digital design checking, in particular to a text-driven high-precision involute spline design checking method. The method comprises the steps that an input text and a configuration set are obtained, and a semantic verification result is generated through format standardization, term normalization, lexical analysis, semantic association and other processing; on the basis, rule matching and expansion, numerical solution, inspection size calculation and geometric parameter reverse calculation are carried out, and inspection and reverse geometric parameters are obtained; then carrying out model construction, grid division, load application, solving, bearing capacity checking and wear life evaluation to form a bearing capacity and life calculation checking result; and finally, outputting a standardized report archiving structure through report template rendering, paragraph splicing, annotation proofreading, data arrangement, warning summarization and version packaging. According to the method, the automation of the whole process from text input to design checking is realized, the design precision and efficiency are improved, and the data traceability and term consistency are ensured.

The invention relates to the technical field of computer-aided engineering and material science, and discloses a pavement construction material ratio intelligent calculation and scheme generation system, which comprises the following steps of: firstly, constructing a response manifold model under multi-scale constraint; accurately representing a nonlinear mapping relation among a material ratio parameter, a working condition disturbance parameter and a macroscopic performance index; an active learning and model iteration module is utilized to iteratively optimize the model in a mode of minimizing the number of physical tests; then, a ratio scheme reverse generation module reversely solves a robust reference ratio scheme which meets performance constraints and is insensitive to working condition disturbance based on the model; and finally, in the construction stage and the construction process, a self-adaptive correction module obtains field working condition disturbance data in real time, the model is used for calculating the proportion adjustment amount, and dynamic correction of the production process is achieved. According to the method, the efficiency and the quality of proportioning design are remarkably improved, the robustness of a proportioning scheme is ensured, and closed-loop control of a design stage and a production stage is realized.

The invention relates to the technical field of computer-aided engineering modeling, in particular to a prediction method and system for floor external corner cracks, and the method comprises the steps: collecting real-time temperature change data, concrete shrinkage deformation data, humidity information and sunlight intensity information of a floor external corner area; according to the method, a dynamic coupling model of temperature stress and concrete shrinkage is constructed, the influence coefficient of the temperature on the shrinkage rate and stress redistribution are calculated in real time in combination with a mechanical association algorithm, and the problem that dynamic interaction is not reflected due to independent calculation of the temperature stress and the concrete shrinkage in an existing method is solved; and then environment self-adaptive correction is performed on the model according to the humidity and the sunlight intensity, the sensitivity parameter and the temperature stress transmission attenuation coefficient are adjusted, and the defect that the real-time influence of environment factors is not included in an existing method is overcome.

The invention relates to the technical field of crossing of automobile engineering and computer-aided engineering, in particular to a vehicle misuse working condition simulation method and device and a vehicle. The method comprises the steps that tire size information is obtained, and a tire finite element model is established; establishing a tire parameter identification model based on the tire finite element model, setting identification parameters and an optimization target, firstly identifying tire radial rigidity parameters, then identifying tire three-dimensional rigidity parameters in combination with the parameters, and updating side wall material parameters of the tire finite element model into the three-dimensional rigidity parameters; the method comprises the following steps: obtaining vehicle structure data to establish a vehicle dynamics model, establishing a pavement model in combination with pavement material attributes and shapes, establishing a contact relationship between a tire finite element model and the pavement model, and carrying out misuse condition simulation on the vehicle dynamics model. Therefore, the problems that a multi-body dynamic model tire cannot simulate large deformation of the tire under the misuse working condition, and collision between a rim and a road surface cannot be accurately restored in the prior art are solved.

A digital twin assisted electroacoustic device simulation system includes a computing device and a simulation program that, when run by the computing device, causes the computing device to perform operations including the following steps: receiving various data of a physical system to establish an acoustic computer-aided engineering model; importing the operation data of the physical system into the acoustic computer-aided engineering model, and generating a digital twin virtual three-dimensional model; running physical simulation through the digital twin virtual three-dimensional model; and modifying or replacing simulation conditions of the digital twin virtual three-dimensional model to obtain simulation results under different conditions.

The present application relates to a kind of socket connection pipeline parameterized modeling system and modeling method, belong to computer aided engineering field.The present application is driven finite element software by Python script, realizes the automatic generation from standard drawing size to complete solution input file.The core steps include: parameter is collected by graphic interface;Based on analytical geometry algorithm, the control point coordinates of complex profile of socket, spigot and T type rubber ring are accurately solved;Automatic model is built and material attribute is given;According to geometric feature, surface domain is automatically cut and anti-lock gradient grid is generated;"shrinkage-expansion-insertion" multi-step analysis sequence based on virtual temperature field is created to solve large interference contact problem;Finally, standard INP file is exported by one key.The present application solves the defects of low efficiency, easy to make mistakes and difficult to standardize of traditional manual modeling, provides full-process automatic solution for large-scale, high-precision simulation of pipe interface.

The invention discloses a simulation prediction method based on reduced-order model machine learning, and relates to the technical field of crossing of computer-aided engineering simulation and machine learning, in particular to a simulation prediction method based on reduced-order model machine learning, which comprises the following steps: firstly, performing finite element simulation on automobile parts (such as an anti-collision beam) to obtain simulation data; secondly, selecting sample points by adopting a Latin hypercube sampling method, and verifying that a data set meets an order reduction requirement; then, carrying out dimension reduction processing on the data by applying an order reduction model (such as intrinsic orthogonal decomposition (POD) or singular value decomposition (SVD)); and finally, predicting the data after order reduction by using a Kriging method machine learning model, and evaluating the prediction precision by using a decision coefficient R2 and a root mean square error RMSE. According to the method, through combination of the reduced-order model and machine learning, the simulation calculation efficiency is effectively improved, meanwhile, the accuracy of a prediction result is ensured, and the method is suitable for rapid simulation optimization in automobile design.

The invention relates to the technical field of computer-aided engineering, in particular to an aviation force-bearing component performance detection and analysis system which comprises a component geometric feature recognition module used for detecting and extracting the minimum curvature radius, the maximum suspension angle and the minimum wall thickness value of an aviation force-bearing component according to an input three-dimensional CAD model of the aviation force-bearing component, and determining the minimum curvature radius, the maximum suspension angle and the minimum wall thickness value of the aviation force-bearing component according to the minimum curvature radius, the maximum suspension angle and the minimum wall thickness value of the aviation force-bearing component; and obtaining a key morphological characteristic parameter set. According to the method, geometric analysis is carried out on the three-dimensional CAD model of the aviation force-bearing component, key morphological characteristics such as the minimum curvature radius, the maximum suspension angle and the minimum wall thickness are detected, and a machining reachability spatial distribution diagram is constructed in combination with multidirectional detection line projection, so that quantitative evaluation of the component manufacturing difficulty is realized; the abstract geometrical morphology is directly associated with the specific manufacturing process capacity, and the process weak area generated due to milling tool limitation or additive manufacturing supporting requirements can be recognized.

The invention relates to the technical field of computer-aided engineering, and discloses a CAE elastic simulation architecture based on containerization orchestration, which packages each micro-service of CAE software and an operating environment thereof into an independent Docker container mirror image through a containerization method, realizes decoupling of the CAE software and the operating environment, is convenient to realize rapid deployment and dynamic adjustment of each micro-service of the CAE, and improves the simulation efficiency of the CAE software. And the portability and the deployment efficiency of the CAE software micro-service are improved. Meanwhile, the operation and maintenance management module can dynamically increase Worker nodes according to the load condition of the current computing cluster and a preset elastic strategy and match the Worker nodes for the to-be-executed tasks, resources can be accurately allocated to the to-be-executed tasks, unbalanced resource allocation is avoided, the waiting time of the to-be-executed tasks can be shortened, and the overall simulation efficiency can be improved.