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Digital Twins for Automotive Structural Safety Engineering

30 Chapters
View Course Samples Online
01
Digital twin fundamentals for automotive structural safety
definitions, fidelity levels, and the safety engineering value chain.
automotivestructural
02
Vehicle body-in-white digital twin architecture
CAD/CAE integration, material models, and mesh strategy for crashworthiness.
body-in-whitearchitecture
03
Sensor and measurement systems for structural digital twins
strain gauges, accelerometers, and load cells in physical testing.
measurementstructural
04
Real-time data acquisition and telemetry pipelines for automotive structural health monitoring.
Real-time data acquisition and telemetry pipelines for automotive structural health monitoring.
Real-timeacquisition
05
Finite element model updating using test data
sensitivity analysis, optimization, and correlation metrics.
updatingsensitivity
06
Reduced-order modeling and surrogate models for fast structural response prediction in digital twins.
Reduced-order modeling and surrogate models for fast structural response prediction in digital twins.
Reduced-ordermodeling
07
Physics-based and data-driven hybrid modeling for crash and impact simulation.
Physics-based and data-driven hybrid modeling for crash and impact simulation.
Physics-baseddata-driven
08
Digital twin calibration and validation for frontal impact safety assessment.
Digital twin calibration and validation for frontal impact safety assessment.
calibrationvalidation
09
Side impact and pole crash digital twin development
modeling challenges and validation protocols.
developmentmodeling
10
Rear impact and roof crush digital twins
structural integrity and occupant protection.
structuralintegrity
11
Fatigue and durability digital twins for automotive structures under cyclic loading.
Fatigue and durability digital twins for automotive structures under cyclic loading.
durabilityautomotive
12
Corrosion and aging effects in structural digital twins
modeling degradation and remaining life.
Corrosionstructural
13
Digital twin for battery pack structural safety in electric vehicles
crash, vibration, and thermal runaway.
structuralelectric
14
Welded and bonded joint modeling in automotive digital twins
failure criteria and validation.
modelingautomotive
15
Composite and multi-material structural digital twins
delamination, fiber failure, and impact damage.
Compositemulti-material
16
Occupant restraint system interaction with structural digital twins
coupling and co-simulation.
Occupantrestraint
17
Pedestrian protection digital twins
hood, bumper, and energy absorber modeling.
Pedestrianprotection
18
Digital twin for rollover and roof strength
simulation and physical test correlation.
rolloverstrength
19
Structural health monitoring using digital twins
damage detection, localization, and quantification.
Structuralmonitoring
20
Model-based prognostics and remaining useful life estimation for automotive structures.
Model-based prognostics and remaining useful life estimation for automotive structures.
Model-basedprognostics
21
Uncertainty quantification and robust design in structural digital twins.
Uncertainty quantification and robust design in structural digital twins.
Uncertaintyquantification
22
Machine learning for real-time state estimation and anomaly detection in vehicle structures.
Machine learning for real-time state estimation and anomaly detection in vehicle structures.
real-timeestimation
23
Digital twin platforms and interoperability
FMI, SSP, and data standards for automotive safety.
platformsinteroperability
24
High-performance computing and cloud-based simulation for large-scale digital twins.
High-performance computing and cloud-based simulation for large-scale digital twins.
High-performancecomputing
25
Verification and validation (V&V) and accreditation for safety-critical digital twins.
Verification and validation (V&V) and accreditation for safety-critical digital twins.
Verificationvalidation
26
Regulatory and certification perspectives
FMVSS, Euro NCAP, and digital twin evidence.
Regulatorycertification
27
Digital twin for autonomous vehicle structural safety
sensor fusion and impact detection.
autonomousstructural
28
Case study
full-vehicle frontal crash digital twin from concept to validation.
full-vehiclevalidation
29
Case study
battery electric vehicle side impact digital twin for pack integrity.
electricintegrity
30
Future trends
AI-enhanced digital twins, edge computing, and lifelong learning for automotive structural safety.
AI-enhancedcomputing