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Uncertainty Budgets for Virtual Crash Assessment Claims

30 Chapters
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01
Framing virtual crash assessment claims
regulatory context, credibility requirements, and the role of uncertainty budgets in evidence-based decision-making.
assessmentregulatory
02
Anatomy of an uncertainty budget
sources, propagation paths, and the mapping from simulation inputs to assessment claim confidence.
uncertaintypropagation
03
Key terminology and standards
GUM, ASME V&V, ISO 26262, and how uncertainty quantification aligns with crashworthiness validation frameworks.
terminologystandards
04
Identifying uncertainty sources in virtual crash models
geometry variability, material scatter, boundary conditions, and solver approximations.
Identifyinguncertainty
05
Characterizing input uncertainty
probabilistic material models, thickness tolerances, and loading condition distributions from physical tests.
Characterizinguncertainty
06
Sensitivity analysis methods for crash simulations
screening designs, variance-based methods, and their practical implementation in LS-DYNA and Radioss.
Sensitivityanalysis
07
Model form uncertainty
discretization error, contact algorithm assumptions, and validation metrics for finite element crash models.
uncertaintydiscretization
08
Propagating uncertainty through nonlinear explicit dynamics
Monte Carlo, polynomial chaos expansion, and surrogate modeling strategies.
Propagatinguncertainty
09
Building a first uncertainty budget for a frontal impact simulation
step-by-step source inventory and preliminary quantification.
Buildinguncertainty
10
Quantifying uncertainty in occupant injury criteria
HIC, chest deflection, and femur load predictions with confidence intervals.
Quantifyinguncertainty
11
Case study
uncertainty budget for a side pole impact assessment using physical test correlations and simulation scatter.
uncertaintyassessment
12
Handling correlated and dependent uncertainties
copula models, Gaussian processes, and their impact on budget aggregation.
Handlingcorrelated
13
Verification and validation uncertainty
numerical error estimation, grid convergence, and the role of validation experiments in budget refinement.
Verificationvalidation
14
Aggregating uncertainty sources
root-sum-square, Monte Carlo aggregation, and interval analysis for conservative claim bounds.
Aggregatinguncertainty
15
Decision-making with uncertainty budgets
pass/fail criteria, margin allocation, and risk-informed acceptance for virtual crash claims.
Decision-makinguncertainty
16
Practical workshop
constructing an uncertainty budget for a rear impact sled test simulation using provided material and geometry data.
workshopconstructing
17
Uncertainty in pedestrian protection simulations
head impact time, legform response, and budget implications for Euro NCAP claims.
Uncertaintypedestrian
18
Bayesian calibration of crash models
updating uncertainty budgets with test data and quantifying posterior predictive uncertainty.
Bayesiancalibration
19
Surrogate modeling for efficient uncertainty quantification
kriging, neural networks, and active learning in crashworthiness.
Surrogatemodeling
20
Case study
uncertainty budget for a battery electric vehicle crashworthiness claim including battery deformation and thermal runaway risk.
uncertaintyelectric
21
Software tools and workflows
Dakota, UQLab, and Python-based pipelines for automating uncertainty budgets in crash simulation.
Softwareworkflows
22
Reporting and communicating uncertainty budgets
visualization, documentation standards, and audit trails for regulatory submission.
Reportingcommunicating
23
Uncertainty budget for a full vehicle frontal offset crash
integrating subsystem and full-scale test data.
Uncertaintyintegrating
24
Handling model discrepancy
bias correction, model form uncertainty, and its treatment in virtual crash assessment claims.
Handlingdiscrepancy
25
Global sensitivity analysis for high-dimensional crash models
Sobol indices, Shapley effects, and computational strategies.
sensitivityanalysis
26
Uncertainty in material failure modeling
fracture strain scatter, strain-rate sensitivity, and their propagation to crash outcomes.
Uncertaintymaterial
27
Case study
uncertainty budget for a roof crush simulation and its role in FMVSS 216a compliance claims.
uncertaintysimulation
28
Validation metrics and uncertainty budgets
comparing simulation and test corridors, and updating budgets based on validation results.
Validationuncertainty
29
Practical workshop
reviewing and critiquing an existing uncertainty budget for a virtual crash assessment, identifying gaps and improvements.
workshopreviewing
30
Capstone project
develop a complete uncertainty budget for a virtual crash assessment claim of your choice, including source identification, quantification, aggregation, and decision recommendation.
Capstonecomplete