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Python Occupant Injury Metrics Calculation and Reporting

30 Chapters
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01
Course overview
occupant injury metrics in crash safety, Python toolchain, and end-to-end calculation-to-reporting workflow.
occupanttoolchain
02
Injury metric fundamentals
HIC, HIC15, HIC36, a3ms, Nij, chest deflection, and their biomechanical basis.
HICHIC15
03
Data acquisition
importing accelerometer, load cell, and displacement time histories from ISO 6487 and SAE J211 channels.
acquisitionimporting
04
Signal conditioning
filtering per SAE J211 CFC 600, 1000, and 180, detrending, and offset correction in Python.
conditioningfiltering
05
Time-history alignment
synchronizing impact events, t0 detection, and cross-channel time base reconciliation.
Time-historyalignment
06
HIC computation
implementing HIC, HIC15, and HIC36 with vectorized NumPy and validating against reference values.
HICcomputation
07
Head injury criteria extensions
HIC15 vs HIC36 trade-offs, rotational metrics, and BRIC introduction.
criteriaextensions
08
Neck injury metrics
Nij, Nte, Ntf, Nce, Ncf, and Nkm calculation from upper neck load cell data.
calculation
09
Chest injury metrics
chest deflection, VC, and chest acceleration 3 ms clip computation.
deflectionacceleration
10
Lower extremity metrics
femur force, tibia index, and axial force moment evaluation.
extremityevaluation
11
Pelvis and abdomen metrics
pubic symphysis force, abdominal pressure, and deflection-based criteria.
symphysisabdominal
12
Occupant size scaling
mass scaling, Hybrid III vs THOR, and normalization to 50th percentile male.
OccupantIII
13
Sled test data processing
extracting channels, computing metrics, and comparing to FMVSS 208 and Euro NCAP limits.
processingextracting
14
Crash test data formats
reading ISO MME, DIAdem, and TDMS files with Python libraries.
ISOMME
15
Automated metric calculation pipeline
modular functions, configuration files, and batch processing of test runs.
Automatedcalculation
16
Quality checks
outlier detection, signal dropout handling, and metric plausibility validation.
detectionhandling
17
Visualization
time-history plots, HIC window overlays, and injury metric bar charts with Matplotlib and Plotly.
Visualizationtime-history
18
Reporting
generating HTML and PDF reports with Jinja2, WeasyPrint, and embedded interactive plots.
Reportinggenerating
19
Regulatory reporting
FMVSS 208, ECE R94, and Euro NCAP compliance tables and pass/fail logic.
Regulatoryreporting
20
Database integration
storing metrics in SQLite and PostgreSQL for fleet-wide analysis.
Databaseintegration
21
Statistical analysis
distribution fitting, percentile estimation, and injury risk curves from computed metrics.
Statisticalanalysis
22
Sensitivity analysis
effect of filter class, window length, and t0 selection on HIC and Nij.
Sensitivityanalysis
23
Case study
frontal ODB test — full pipeline from raw data to regulatory report.
ODBpipeline
24
Case study
side impact MDB test — handling multiple occupants and asymmetric loading.
MDBhandling
25
Case study
rear impact whiplash — NIC, Nkm, and seat belt load limiting evaluation.
whiplashNIC
26
Pedestrian protection
headform and legform impactor metric calculation and reporting.
Pedestrianprotection
27
Child occupant safety
Q-series and Hybrid III 3-year-old scaling and metric computation.
occupantQ-series
28
Automation with CI/CD
unit testing metric functions, regression testing, and containerized deployment.
AutomationCI/CD
29
Interactive dashboards
Streamlit and Dash apps for real-time metric exploration and reporting.
Interactivedashboards
30
Capstone project
end-to-end Python application for occupant injury metric calculation, validation, and automated report generation.
Capstoneend-to-end