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Python CAE Results Dashboards and Engineering Reporting

30 Chapters
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01
CAE results data landscape
common formats (ODB, XDB, H3D, VTK, CSV, HDF5), metadata, and engineering reporting requirements.
CAElandscape
02
Python ecosystem for CAE post-processing
NumPy, pandas, meshio, pyvista, vtk, and visualization libraries for engineering data.
ecosystemCAE
03
Extracting results from CAE solvers
scripting Abaqus, ANSYS, or Nastran output files and converting to Python-friendly structures.
ExtractingCAE
04
Data cleaning and transformation for CAE results
handling missing values, unit consistency, and time-step alignment.
cleaningtransformation
05
Building a reusable CAE results data model
classes for models, load cases, and result fields.
Buildingreusable
06
Static contour plots and field visualizations
matplotlib, pyvista, and plotly for stress, displacement, and temperature.
visualizationsmatplotlib
07
Interactive 3D visualization of CAE results
pyvista, vtk, and panel integration for mesh and scalar fields.
Interactivevisualization
08
Dashboard fundamentals with Dash
layout, callbacks, and component design for engineering metrics.
Dashboardcallbacks
09
Dashboard fundamentals with Streamlit
rapid prototyping of CAE result viewers and parameter studies.
DashboardStreamlit
10
Dashboard fundamentals with Panel
linking widgets, plots, and tables for CAE data exploration.
DashboardCAE
11
Time-series and transient result dashboards
animation, sliders, and playback controls for dynamic CAE output.
Time-seriestransient
12
Comparative and parametric study dashboards
side-by-side plots, difference maps, and sensitivity charts.
Comparativeparametric
13
Integrating CAE results with engineering KPIs
safety factors, mass, frequency, and performance metrics.
IntegratingCAE
14
Automated report generation with Python
Jinja2, ReportLab, and docx for engineering report templates.
Automatedgeneration
15
Embedding interactive plots in reports
HTML export, static image fallbacks, and PDF generation.
Embeddinginteractive
16
Batch processing and reporting for multiple load cases
loops, parallelization, and result aggregation.
processingreporting
17
Dashboard deployment for engineering teams
local servers, Docker, and cloud options.
Dashboarddeployment
18
User authentication and access control for CAE dashboards
basic auth, OAuth, and role-based views.
authenticationCAE
19
Performance optimization for large CAE datasets
downsampling, caching, and lazy loading.
Performanceoptimization
20
Case study
fatigue results dashboard for a welded structure.
dashboardstructure
21
Case study
thermal management dashboard for electronics cooling.
managementdashboard
22
Case study
crash simulation results dashboard with injury criteria.
simulationdashboard
23
Case study
modal analysis dashboard for NVH engineering.
analysisdashboard
24
Case study
CFD results dashboard for aerodynamic performance.
CFDdashboard
25
Case study
composite layup results dashboard with ply-based visualization.
compositedashboard
26
Case study
optimization results dashboard linking design variables to responses.
optimizationdashboard
27
Case study
real-time monitoring dashboard for structural health.
real-timemonitoring
28
Case study
multi-physics results dashboard for electromechanical systems.
multi-physicsdashboard
29
Best practices for CAE reporting
reproducibility, versioning, and validation.
practicesCAE
30
Capstone project
end-to-end CAE results dashboard and automated report for a realistic engineering scenario.
Capstoneend-to-end