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CAE Sensitivity Analysis and Response Surface Modeling

30 Chapters
View Course Samples Online
01
Course introduction
role of sensitivity analysis and response surface modeling in CAE-driven design, key terminology, and workflow overview.
sensitivityanalysis
02
Design of experiments for CAE
screening designs, space-filling designs, and sample generation for sensitivity and response surface studies.
experimentsCAE
03
Local sensitivity methods
finite difference, complex-step, and adjoint formulations for gradient computation in CAE solvers.
sensitivitydifference
04
Global sensitivity analysis
variance-based methods (Sobol indices), elementary effects, and their interpretation for CAE outputs.
sensitivityanalysis
05
Sensitivity analysis with correlated inputs
handling dependencies, covariance-based measures, and practical implications for CAE models.
Sensitivityanalysis
06
Response surface methodology fundamentals
polynomial regression, least squares fitting, and model adequacy checking for CAE surrogate models.
Responsemethodology
07
Design and analysis of computer experiments
Gaussian process (Kriging) modeling, correlation functions, and trend selection for deterministic CAE data.
analysiscomputer
08
Radial basis function and support vector regression surrogates
formulation, parameter tuning, and application to CAE response surfaces.
functionregression
09
Model validation and error estimation
cross-validation, bootstrapping, and prediction error metrics for CAE surrogates.
validationestimation
10
Sensitivity analysis of response surface models
coefficient sensitivity, Sobol indices from polynomial chaos expansions, and variance decomposition.
Sensitivityanalysis
11
Polynomial chaos expansion for CAE
construction, coefficient estimation, and sensitivity analysis under uncertainty.
Polynomialexpansion
12
Multi-fidelity surrogate modeling
combining coarse and fine CAE simulations for efficient response surface construction.
Multi-fidelitysurrogate
13
Adaptive sampling strategies
infill criteria, expected improvement, and goal-oriented refinement for CAE response surfaces.
Adaptivesampling
14
Sensitivity analysis for optimization
gradient-based and derivative-free approaches using surrogates in CAE design loops.
Sensitivityanalysis
15
Response surface-based optimization
trust-region methods, sequential quadratic programming with surrogates, and convergence assessment.
Responsesurface-based
16
Robust design and reliability analysis
incorporating uncertainty, six-sigma design, and reliability-based optimization with CAE surrogates.
reliabilityanalysis
17
Sensitivity analysis for transient and dynamic CAE problems
time-dependent outputs, modal sensitivity, and transient response surfaces.
Sensitivityanalysis
18
Sensitivity analysis for nonlinear and contact problems
handling non-smooth responses, material nonlinearity, and contact status changes.
Sensitivityanalysis
19
Sensitivity analysis for multidisciplinary CAE systems
coupled physics, partitioned approaches, and cross-disciplinary sensitivity propagation.
Sensitivityanalysis
20
Response surface modeling for crashworthiness and impact
highly nonlinear responses, metamodeling challenges, and validation strategies.
Responsemodeling
21
Sensitivity analysis and response surfaces for CFD
turbulence model sensitivities, shape optimization, and flow response surfaces.
Sensitivityanalysis
22
Sensitivity analysis and response surfaces for thermal and structural problems
coupled thermo-mechanical effects and design trade-offs.
Sensitivityanalysis
23
Case study
sensitivity-driven design of a bracket under static loads using CAE and response surface models.
sensitivity-drivenCAE
24
Case study
crashworthiness optimization of a vehicle front rail using response surface surrogates and global sensitivity analysis.
crashworthinessoptimization
25
Case study
aerodynamic shape optimization of an airfoil using CFD-based response surfaces and adjoint sensitivities.
aerodynamicoptimization
26
Case study
reliability-based design of a turbine blade considering thermal and structural uncertainties.
reliability-basedconsidering
27
Software implementation
scripting sensitivity analysis and response surface workflows in commercial CAE environments (e.g., ANSYS, Abaqus, Nastran).
Softwareimplementation
28
Data management and automation
parametric CAD/CAE integration, job submission, and result extraction for large-scale sensitivity studies.
managementautomation
29
Verification and validation of sensitivity and surrogate models
code verification, solution verification, and validation experiments.
Verificationvalidation
30
Emerging trends and advanced topics
machine learning surrogates, active learning, digital twins, and integration with MBSE for CAE-driven design.
Emergingadvanced