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Quantitative CAE-Test Correlation and Model Parameter Calibration

30 Chapters
View Course Samples Online
01
Course overview
scope, concepts, and technical context of quantitative CAE-test correlation and model parameter calibration.
technicalquantitative
02
CAE-test correlation fundamentals
definitions, objectives, and the role of correlation in product development cycles.
CAE-testcorrelation
03
Test data acquisition for correlation
sensor selection, measurement uncertainty, and data quality assessment.
acquisitioncorrelation
04
CAE model setup for correlation
geometry simplification, mesh convergence, and boundary condition representation.
CAEcorrelation
05
Quantitative correlation metrics
scalar and vectorial error measures, correlation coefficients, and confidence intervals.
Quantitativecorrelation
06
Introduction to model parameter calibration
forward vs. inverse problems, identifiability, and ill-posedness.
parametercalibration
07
Design of experiments for calibration
sampling strategies, space-filling designs, and test matrix optimization.
experimentscalibration
08
Sensitivity analysis
local and global methods for identifying influential parameters in CAE models.
Sensitivityanalysis
09
Optimization-based calibration
gradient-based and derivative-free algorithms for parameter estimation.
Optimization-basedcalibration
10
Surrogate modeling for calibration
response surface, kriging, and polynomial chaos expansion.
Surrogatemodeling
11
Bayesian calibration
prior elicitation, likelihood construction, and posterior inference using MCMC.
Bayesiancalibration
12
Uncertainty quantification in calibrated models
propagation, confidence bounds, and prediction intervals.
Uncertaintyquantification
13
Model validation and validation metrics
separation of calibration and validation data, and acceptance criteria.
validationseparation
14
Case study
calibration of a structural dynamics model using modal test data.
calibrationstructural
15
Case study
calibration of a thermal model using temperature measurements from a thermal test.
calibrationtemperature
16
Case study
calibration of a crashworthiness model using full-scale impact test data.
calibrationcrashworthiness
17
Case study
calibration of a CFD model using wind tunnel or flow bench measurements.
calibrationCFD
18
Case study
calibration of a multibody dynamics model using motion and force measurements.
calibrationmultibody
19
Handling variability and noise in test data
filtering, outlier detection, and robust calibration.
Handlingvariability
20
Multi-response calibration
trade-offs, Pareto optimality, and weighted objective functions.
Multi-responsecalibration
21
Calibration under uncertainty
stochastic calibration, robust design, and reliability-based approaches.
Calibrationuncertainty
22
Model form uncertainty
discrepancy modeling, model bias correction, and Bayesian model averaging.
uncertaintydiscrepancy
23
Practical implementation
software tools, scripting workflows, and automation of calibration loops.
implementationsoftware
24
Verification and validation (V&V) framework
ASME V&V 10/20, NASA standards, and regulatory context.
Verificationvalidation
25
Reporting and documentation
correlation reports, calibration traceability, and audit readiness.
Reportingdocumentation
26
Industrial application
calibration in automotive NVH and durability engineering.
Industrialapplication
27
Industrial application
calibration in aerospace structural and thermal analysis.
Industrialapplication
28
Industrial application
calibration in energy systems and turbomachinery.
Industrialapplication
29
Emerging trends
machine learning-assisted calibration, digital twins, and real-time model updating.
Emerginglearning-assisted
30
Capstone project
end-to-end quantitative correlation and calibration study for a selected CAE model.
Capstoneend-to-end