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Power BI DAX for Injury Metrics and CAE Performance KPIs

30 Chapters

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Injury metrics and CAE performance KPIs

overview of HIC, NIC, chest deflection, femur force, and their role in crashworthiness and occupant safety assessment.

Power BI data model foundations for CAE results

star schema design with fact tables for simulation runs, load cases, and injury metrics, and dimension tables for occupants, vehicles, and test configurations.

DAX fundamentals for injury metrics

calculated columns vs. measures, row context vs. filter context, and their impact on aggregating CAE output data.

Importing and shaping CAE result data

using Power Query to load LS-DYNA, PAM-CRASH, or Abaqus output files, handling time-history curves, and preparing injury metric tables.

Time-based injury metric calculations

computing HIC15 and HIC36 using DAX with time-windowed aggregations and integration over acceleration pulses.

Time-basedcalculations

DAX patterns for peak and cumulative injury metrics

MAX, MAXX, SUMX, and window functions to extract peak values and cumulative damage measures from simulation time series.

Filter context and CALCULATE for CAE load case analysis

isolating specific impact scenarios, occupant positions, and restraint configurations using CALCULATE and filter modifiers.

Context transition in injury metric evaluation

using CALCULATE to transition row context to filter context when computing per-run injury metrics from detailed time-step data.

transitionevaluation

Time intelligence for CAE performance tracking

comparing injury metrics across design iterations, model years, and test campaigns using DATEADD, SAMEPERIODLASTYEAR, and custom date tables.

intelligenceCAE

Ranking and percentile analysis of CAE results

RANKX and PERCENTILEX.INC to identify worst-case load cases and benchmark injury metrics against fleet or regulatory thresholds.

percentileanalysis

DAX for regulatory compliance checks

implementing pass/fail logic for FMVSS 208, Euro NCAP, and IIHS criteria using SWITCH, IF, and conditional aggregation.

Dynamic segmentation of injury metrics

using SUMMARIZE, GROUPBY, and window functions to analyze injury outcomes by body region, occupant size, and impact direction.

segmentationSUMMARIZE

What-if parameters for design exploration

integrating Power BI what-if parameters with DAX to evaluate sensitivity of injury metrics to restraint parameters and structural stiffness.

parametersexploration

DAX measures for CAE model correlation

computing correlation coefficients, RMSE, and normalized error between simulation and physical test injury metrics using DAX statistical functions.

Handling missing and outlier CAE data

using ISBLANK, COALESCE, and robust aggregation to manage incomplete simulation runs and anomalous injury values.

Optimizing DAX performance for large CAE datasets

reducing cardinality, using variables, avoiding context transitions in iterators, and leveraging aggregation tables for time-history data.

Building a CAE KPI dashboard with DAX

designing measures for overall injury risk score, occupant safety index, and trend indicators using dynamic formatting and conditional logic.

DAX for multi-level injury metric aggregation

rolling up from component to subsystem to full vehicle using SUMX and AVERAGEX with hierarchical relationships.

Time-series smoothing and filtering of injury signals

applying moving averages and low-pass filters in DAX to preprocess acceleration and force signals before metric calculation.

Time-seriessmoothing

DAX for injury risk curves and probability of injury

implementing logistic regression and cumulative distribution functions to estimate injury probability from CAE metrics.

Comparative analysis of CAE solvers and configurations

using DAX to compare injury metrics across solver types, element formulations, and material models with statistical summaries.

Comparativeanalysis

DAX measures for occupant kinematics

deriving head excursion, chest compression velocity, and other kinematic metrics from displacement and velocity time histories.

Integrating physical test data with CAE results

blending sled test and simulation injury metrics in a unified model and computing delta and ratio measures using DAX.

Integratingphysical

DAX for design optimization trade-offs

computing weighted composite injury scores and Pareto fronts using DAX to balance multiple injury criteria.

DAXoptimization

Automating CAE report generation with DAX

creating dynamic narrative measures and conditional formatting rules to highlight critical injury metrics in Power BI reports.

DAX patterns for load case matrix analysis

using CROSSJOIN and GENERATE to build a matrix of impact scenarios and injury outcomes for comprehensive safety assessment.

DAX for injury metric normalization and scaling

applying min-max normalization and z-score standardization to compare injury metrics across different scales and units.

DAXnormalization

Advanced DAX for time-windowed injury criteria

implementing sliding window calculations for NIC, NIJ, and other duration-dependent metrics using window functions and variables.

DAX measures for CAE model validation metrics

computing area under curve, peak timing error, and pulse shape correlation for acceleration and force curves.

Capstone project

building an end-to-end Power BI solution for CAE injury metrics, from data ingestion and DAX measure design to interactive dashboards and automated compliance reporting.

Capstonebuilding