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Crash Simulation Quality Assurance and Model Governance

30 Chapters
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01
Crash simulation in product development
role, regulatory drivers, and the need for quality assurance and model governance.
simulationdevelopment
02
Simulation model lifecycle
from requirements and model planning to verification, validation, deployment, and retirement.
Simulationlifecycle
03
Quality assurance fundamentals for crash simulation
accuracy, robustness, repeatability, and reproducibility metrics.
assurancesimulation
04
Model governance framework
roles, responsibilities, policies, and decision rights across CAE, test, and program teams.
governanceframework
05
Requirements engineering for crash models
translating safety and performance targets into simulation acceptance criteria.
Requirementstranslating
06
Mesh quality assurance
element quality metrics, convergence studies, and mesh independence for crashworthiness models.
assuranceconvergence
07
Material model calibration and validation
coupon tests, inverse methods, and uncertainty quantification for crash simulations.
Materialcalibration
08
Boundary conditions and loading
sled tests, barrier impacts, and occupant restraint inputs for model fidelity.
Boundaryconditions
09
Contact and impact modeling
penalty and kinematic methods, friction, and energy balance checks.
modelingkinematic
10
Solver verification
time step, hourglass control, mass scaling, and numerical stability in explicit crash codes.
verificationhourglass
11
Verification and validation (V&V) planning
V&V plan, validation hierarchy, and credibility assessment per ASME V&V 10 and 20.
Verificationvalidation
12
Validation metrics for crash simulation
corridor methods, objective rating, and statistical validation against physical tests.
Validationsimulation
13
Uncertainty quantification in crash models
aleatory and epistemic uncertainties, sensitivity analysis, and propagation.
Uncertaintyquantification
14
Model version control and configuration management
baselines, branching, and traceability for CAE models.
configurationmanagement
15
Data management for crash simulation
metadata, run records, and audit trails for regulatory compliance.
managementsimulation
16
Quality control in simulation workflows
checklists, peer reviews, and automated model checks.
simulationworkflows
17
Regression testing and model health monitoring
detecting drift, degradation, and unintended changes.
Regressionmonitoring
18
High-performance computing and solver quality
scalability, repeatability, and resource governance.
High-performancecomputing
19
Occupant safety models
dummy positioning, restraint system modeling, and validation for injury criteria.
Occupantpositioning
20
Pedestrian protection and structural crash models
subsystem validation and full-vehicle correlation.
Pedestrianprotection
21
Battery electric vehicle crash simulation
unique governance challenges for battery pack and thermal runaway modeling.
electricsimulation
22
Model governance for autonomous and ADAS-equipped vehicles
sensor placement, structural integrity, and scenario coverage.
governanceautonomous
23
Machine learning and surrogate models in crash simulation
governance, interpretability, and validation requirements.
surrogatesimulation
24
Digital twin and real-time crash simulation
governance for operational use and continuous updating.
real-timesimulation
25
Regulatory and standards landscape
FMVSS, Euro NCAP, ISO 26262, and ASME V&V requirements for simulation credibility.
Regulatorystandards
26
Audit and compliance
preparing simulation evidence for regulatory submissions and internal audits.
compliancepreparing
27
Risk management for simulation models
FMEA, model risk tiers, and mitigation strategies.
managementsimulation
28
Training and competency development for CAE engineers and model owners.
Training and competency development for CAE engineers and model owners.
Trainingcompetency
29
Case study
implementing a model governance program for a full-vehicle crash simulation portfolio.
implementinggovernance
30
Future trends and continuous improvement
AI-assisted V&V, cloud-based governance, and industry best practices.
continuousimprovement