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CAE Injury Time-History Analysis and Curve Overlay 30 Cases

30 Chapters

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Import and Standardize Injury Time-History Data

Load head acceleration and chest deflection time histories from multiple CAE solvers (LS-DYNA, PAM-CRASH, Radioss) into a unified time base, resample to a common sampling rate, and verify channel alignment and units before overlay.

StandardizeTime-History

Build a Repeatable Curve Overlay Script for Multiple Impact Simulations

Create a parameterized Python script that reads a directory of simulation result files, extracts specified injury channels, and generates overlaid curves with consistent styling, legends, and axis limits for design comparison.

RepeatableMultiple

Compute HIC15 and HIC36 from Acceleration Time Histories

Implement the Head Injury Criterion calculation over sliding time windows, validate against reference values, and overlay HIC15 and HIC36 curves to compare severity across impact pulses.

Calculate 3 ms Chest Acceleration Clip and Overlay Limit Curves

Derive the 3 ms clip value from chest acceleration time histories, overlay the computed clip against regulatory limit lines, and annotate pass/fail status for multiple load cases.

CalculateAcceleration

Compute Chest Deflection Rate and Overlay with Injury Thresholds

Differentiate chest deflection time histories to obtain deflection rate, apply filtering, and overlay the rate curves with threshold lines to identify exceedance timing across simulations.

DeflectionThresholds

Filter and Smooth Injury Signals with CFC and SAE Filters

Apply CFC 180, CFC 600, and SAE J211 filters to acceleration and deflection channels, compare filtered versus raw overlays, and assess the effect of filter class on peak values and timing.

Align Curves by Impact Event Onset for Fair Overlay

Detect impact onset from acceleration signals using threshold and cross-correlation methods, shift time histories to a common zero, and overlay aligned curves to compare pulse shapes independent of initialization delays.

accelerationthreshold

Normalize and Overlay Injury Curves Across Scaled Tests

Normalize time and amplitude axes using scaling laws or reference values, overlay normalized curves from different impact severities, and evaluate curve collapse quality for severity scaling assessment.

Normalizeamplitude

Overlay Injury Curves from Multiple Occupant Positions

Extract and overlay head and chest injury time histories from driver, passenger, and rear-seat occupant simulations, highlighting position-dependent differences in peak timing and magnitude.

MultipleOccupant

Compare Injury Time Histories Across Restraint Configurations

Overlay acceleration and deflection curves from simulations with varying airbag pressure, seatbelt force limiter, and pretensioner settings, and quantify differences in injury metrics to support restraint tuning.

HistoriesRestraint

Generate Overlay Plots for Design of Experiments (DOE) Results

Read a DOE matrix of simulation outputs, group curves by factor levels, and produce overlaid subplots that reveal sensitivity of injury time histories to design parameters.

GenerateExperiments

Automate Batch Overlay of Injury Curves from a Parametric Study

Develop a batch processing pipeline that iterates over hundreds of simulation runs, extracts injury channels, generates overlay plots per parameter combination, and exports a summary report with peak values and times.

AutomateParametric

Overlay Injury Curves with Confidence Bands from Multiple Runs

Compute mean and percentile bands from a set of stochastic simulation runs, overlay individual curves with shaded confidence intervals, and identify time windows of high variability.

ConfidenceMultiple

Detect and Annotate Peak Values on Overlaid Curves

Implement automatic peak detection with prominence and distance constraints, annotate peak markers and values on overlaid injury curves, and export a table of peak magnitudes and times for all cases.

AnnotateOverlaid

Overlay Injury Curves and Compute Time-to-Peak Differences

Calculate time-to-peak for each curve in an overlay, compute pairwise differences relative to a baseline, and visualize the timing shifts as a bar chart alongside the overlaid curves.

Time-to-PeakDifferences

Integrate Acceleration to Velocity and Overlay with Displacement

Numerically integrate head acceleration to obtain velocity and displacement time histories, overlay these derived curves across simulations, and check consistency with initial conditions and boundary constraints.

IntegrateAcceleration

Compute Cross-Correlation and Phase Lag Between Injury Signals

Calculate cross-correlation functions between paired injury channels (e.g., head acceleration and chest deflection) from different simulations, determine phase lag at peak correlation, and overlay lagged curves for interpretation.

Cross-CorrelationCalculate

Overlay Curves in Frequency Domain Using FFT and PSD

Transform injury time histories to frequency domain via FFT, compute power spectral density, and overlay PSD curves to compare energy content and dominant frequencies across impact scenarios.

Assess Signal Quality and Artifacts in Injury Time Histories

Detect clipping, dropouts, and abnormal spikes in injury channels using statistical and spectral checks, flag suspect curves, and overlay flagged versus clean signals to illustrate artifact impact.

ArtifactsHistories

Overlay Curves from Physical Test and Simulation for Correlation

Load physical sled test data and corresponding CAE simulation output, align them by onset, overlay acceleration and deflection curves, and compute correlation metrics (e.g., ISO/TS 18571 or CORA) to quantify agreement.

PhysicalSimulation

Perform Sensitivity Analysis of Injury Metrics to Filter Cutoff Frequency

Vary CFC filter cutoff frequencies, recompute injury metrics (HIC, 3 ms clip), overlay resulting metric trends, and identify cutoff sensitivity to support filter selection in post-processing.

SensitivityAnalysis

Overlay Injury Curves from Different CAE Solver Versions

Run the same impact model in two solver versions, extract injury time histories, overlay curves to detect version-dependent differences, and quantify deviations in peak values and timing.

Create a Dashboard for Interactive Overlay Exploration

Build a simple interactive dashboard (e.g., using Plotly Dash or Streamlit) that allows users to select simulation cases, toggle channels, and dynamically overlay injury curves with zoom and hover details.

DashboardInteractive

Overlay Curves with Regulatory Limit Envelopes

Overlay computed injury time histories against regulatory limit curves (e.g., FMVSS 208, ECE R94), automatically check compliance at each time step, and highlight exceedance regions.

RegulatoryEnvelopes

Compute Injury Criteria from Overlaid Curves and Rank Configurations

Calculate a composite injury score from multiple metrics (HIC, chest clip, deflection rate) for each simulation, overlay normalized metric curves, and rank configurations using a weighted scoring scheme.

CriteriaOverlaid

Overlay Curves for Occupant Kinematics and Injury Correlation

Extract occupant kinematic time histories (head displacement, chest velocity) alongside injury channels, overlay them in synchronized subplots, and analyze correlation between kinematic events and injury peaks.

OccupantKinematics

Automate Overlay Report Generation with Embedded Curves

Develop a reporting script that generates a PDF or HTML report containing overlaid injury curves, peak tables, and pass/fail summaries for a set of simulations, with consistent formatting and metadata.

AutomateGeneration

Overlay Curves from Different Impact Directions

Extract injury time histories from frontal, side, and rear impact simulations, overlay them in a single figure with direction-specific styling, and compare injury metric magnitudes and timing across directions.

DifferentDirections

Validate Overlay Script Against Manual Plotting

Create a test suite that compares automated overlay outputs (pixel-level or data-level) against manually generated reference plots, ensuring correctness of data extraction, filtering, and plotting logic.

ValidatePlotting

Optimize Overlay Performance for Large Datasets

Profile and optimize a curve overlay script to handle thousands of time histories efficiently, using downsampling, vectorization, and lazy loading, and benchmark performance against a baseline implementation.

OptimizePerformance