VIP20
本课程属于：003-Python Automation for Automotive CAE Engineering English Technical Courses · 共 20 门相关课程，组合学习更完整。
查看所属VIP全部课程 →
← 返回所属目录 咨询 / 购买

Python CAE Geometry and Model Preparation Automation

30 Chapters
View Course Samples Online
01
CAE geometry and model preparation automation
scope, role in simulation workflows, and key challenges in industrial practice.
CAEgeometry
02
Python ecosystem for CAE automation
NumPy, SciPy, pandas, and their integration with geometry and mesh data structures.
ecosystemCAE
03
Geometry kernel APIs and Python bindings
OpenCASCADE (pythonocc), ACIS, and Parasolid access patterns for automated model preparation.
GeometryAPIs
04
CAD file formats and interoperability
STEP, IGES, JT, and native formats; reading, writing, and healing geometry with Python.
CADinteroperability
05
Mesh generation libraries in Python
Gmsh, pyMesh, and MeshPy; scripting automated surface and volume meshing.
generationlibraries
06
Geometry cleanup and repair automation
removing slivers, closing gaps, fixing overlaps, and ensuring watertight solids.
Geometryautomation
07
Feature recognition and simplification
identifying holes, fillets, chamfers, and small features for defeaturing before meshing.
recognitionsimplification
08
Parametric model manipulation
driving CAD parameters via Python for design of experiments and optimization loops.
Parametricmanipulation
09
Automated midsurface extraction and shell mesh preparation for thin-walled structures.
Automated midsurface extraction and shell mesh preparation for thin-walled structures.
Automatedmidsurface
10
Domain decomposition and partitioning
splitting complex assemblies into meshable regions using Python scripts.
decompositionpartitioning
11
Boundary condition and load application automation
mapping named selections, sets, and groups from CAD to solver input decks.
Boundarycondition
12
Material assignment and property mapping
automating material libraries and region-based property definitions.
Materialassignment
13
Mesh quality assessment and improvement
Python scripts for checking aspect ratio, skewness, Jacobian, and auto-refinement.
assessmentimprovement
14
Solver input deck generation
automating NASTRAN, Abaqus, ANSYS, and CalculiX input files from prepared models.
generationautomating
15
Workflow orchestration with Python
scheduling geometry preparation, meshing, and solver runs using subprocess and job queues.
Workfloworchestration
16
Integration with CAE platforms
scripting ANSYS Workbench, Abaqus/CAE, and Simcenter through Python APIs.
IntegrationCAE
17
Automated model verification and validation
checking geometry integrity, mesh convergence, and setup consistency.
Automatedverification
18
Batch processing and parametric studies
looping over design variants and managing large sets of CAE models.
processingparametric
19
Data management for CAE automation
organizing geometry, mesh, and result files with Python and metadata schemas.
managementCAE
20
Case study
automating the preparation of a complex automotive chassis assembly for crash simulation.
automatingpreparation
21
Case study
Python-driven geometry cleanup and meshing for an aerospace turbine blade cooling channel.
Python-drivengeometry
22
Case study
automated midsurfacing and shell meshing of a consumer electronics enclosure for drop test simulation.
automatedmidsurfacing
23
Case study
parametric optimization of a heat sink using Python-scripted geometry and thermal FEA.
parametricoptimization
24
Case study
batch meshing and model setup for a large wind turbine blade under varying load cases.
25
Error handling and robustness in CAE automation
logging, exception management, and recovery strategies.
handlingrobustness
26
Performance optimization
parallel processing, memory management, and efficient geometry operations in Python.
Performanceoptimization
27
User interfaces and reporting
generating HTML reports, dashboards, and interactive plots for automated CAE workflows.
interfacesreporting
28
Deployment and reproducibility
containerization, environment management, and version control for CAE automation scripts.
Deploymentreproducibility
29
Emerging trends
machine learning for geometry simplification, generative design, and cloud-based CAE automation.
Emerginggeometry
30
Capstone project
end-to-end Python automation of geometry preparation, meshing, and solver setup for a real-world assembly.
Capstoneend-to-end