Test Correlation Skill Skill

Test Correlation Skill

Purpose

The Test Correlation skill provides capabilities for correlating test results with analytical predictions, enabling model validation, calibration, and uncertainty quantification for mechanical systems.

Capabilities

Test data processing and analysis
Prediction-to-test comparison
Model calibration techniques
Uncertainty quantification
Statistical analysis and regression
Correlation report generation
Model updating recommendations
Validation criteria assessment

Usage Guidelines

Correlation Methodology

Data Processing

Test Data Preparation

Data quality checks:
- Missing data handling
- Outlier detection
- Noise filtering
- Time synchronization
- Unit verification

Signal Processing | Operation | Purpose | Method | |-----------|---------|--------| | Low-pass filter | Remove noise | Butterworth | | Resampling | Match analysis | Interpolation | | Baseline correction | Remove offset | Linear/polynomial | | Windowing | FFT preparation | Hanning, Hamming |
Derived Quantities
- Integrate acceleration to velocity/displacement
- Differentiate displacement to velocity
- Calculate strain from displacement
- Compute stress from strain

Prediction Extraction

Analysis Results
- Match output locations to sensor positions
- Match load cases to test conditions
- Account for coordinate systems
- Include analysis uncertainty

Interpolation

For locations between nodes:
- Shape function interpolation
- Nearest node approximation
- Surface interpolation (for contours)

Comparison Methods

Point Comparison

Percent difference:
%diff = (Test - Analysis) / Test * 100

For near-zero values:
%diff = (Test - Analysis) / max(|Test|, |Analysis|) * 100

Absolute difference:
delta = Test - Analysis

Statistical Comparison

| Metric | Formula | Purpose | |--------|---------|---------| | Mean error | mean(Test - Analysis) | Bias detection | | RMS error | sqrt(mean((Test-Analysis)^2)) | Overall accuracy | | Correlation coefficient | r | Linear relationship | | R-squared | r^2 | Variance explained |

Modal Correlation

Frequency Comparison

Frequency error:
%error = (f_test - f_analysis) / f_test * 100

Typical acceptance: +/- 5-10%

Mode Shape Correlation

MAC (Modal Assurance Criterion):
MAC = |{phi_test}^T {phi_analysis}|^2 /
      ({phi_test}^T{phi_test})({phi_analysis}^T{phi_analysis})

MAC = 1: Perfect correlation
MAC > 0.9: Good correlation
MAC > 0.7: Acceptable correlation

Cross-Orthogonality

XOR = {phi_test}^T [M] {phi_analysis}

XOR_ii > 0.9: Good correlation
XOR_ij < 0.1: Mode independence

Model Calibration

Parameter Identification

Sensitivity Analysis
- Identify influential parameters
- Rank by sensitivity
- Define adjustment ranges
Optimization Methods | Method | Application | Pros/Cons | |--------|-------------|-----------| | Manual iteration | Simple cases | Intuitive, slow | | Gradient-based | Smooth response | Fast, local minimum | | Genetic algorithm | Complex response | Global, slow | | Response surface | Multiple cases | Efficient, approximation |

Common Calibration Parameters

| Parameter | Structural | Thermal | CFD | |-----------|-----------|---------|-----| | Stiffness | Young's modulus | Conductivity | - | | Boundary | Joint stiffness | HTC | Inlet profile | | Damping | Modal damping | - | Turbulence | | Mass | Density | Cp | Density | | Geometry | Thickness | Contact area | Mesh |

Validation Criteria

Acceptance Criteria

Typical validation targets:
- Displacement: +/- 10%
- Stress: +/- 15%
- Natural frequency: +/- 5%
- MAC: > 0.9
- Temperature: +/- 5 degrees
- Pressure: +/- 10%

Validation Levels

| Level | Evidence | Application | |-------|----------|-------------| | 1 | Qualitative trends match | Preliminary design | | 2 | Quantitative agreement | Detailed design | | 3 | Statistical validation | Certification | | 4 | Prediction capability | Production release |

Uncertainty Quantification

Sources of Uncertainty

Test Uncertainty
- Instrumentation accuracy
- Environmental variation
- Setup variability
- Measurement resolution
Model Uncertainty
- Material property variability
- Geometry simplifications
- Boundary condition approximations
- Discretization error

Combined Uncertainty

u_combined = sqrt(u_test^2 + u_model^2)

Overlap criteria:
If |Test - Analysis| < 2 * u_combined:
  Results are statistically consistent

Process Integration

ME-022: Prototype Testing and Correlation

Input Schema

{
  "test_data": {
    "file_path": "string",
    "format": "csv|mat|hdf5",
    "channels": "array of channel IDs"
  },
  "analysis_results": {
    "file_path": "string",
    "software": "ANSYS|NASTRAN|Abaqus|other",
    "output_locations": "array"
  },
  "comparison_type": "static|modal|transient|steady_state",
  "correlation_requirements": {
    "metrics": "array",
    "acceptance_criteria": "object"
  }
}

Output Schema

{
  "correlation_results": {
    "comparison_table": "array of point comparisons",
    "statistical_metrics": {
      "mean_error": "number",
      "rms_error": "number",
      "max_error": "number",
      "correlation_coefficient": "number"
    },
    "modal_metrics": {
      "frequency_errors": "array",
      "mac_matrix": "2D array"
    }
  },
  "validation_status": {
    "overall": "pass|fail|conditional",
    "by_criterion": "array"
  },
  "calibration_recommendations": [
    {
      "parameter": "string",
      "current_value": "number",
      "recommended_value": "number",
      "sensitivity": "number"
    }
  ],
  "uncertainty_analysis": {
    "test_uncertainty": "number",
    "model_uncertainty": "number",
    "combined": "number"
  }
}

Best Practices

Process test data before comparison
Match locations and coordinates carefully
Account for all sources of uncertainty
Document calibration changes
Validate across multiple load cases
Report both agreements and discrepancies

Integration Points

Connects with FEA Structural for model results
Feeds into Design Review for validation evidence
Supports Test Planning for requirements
Integrates with Requirements Flowdown for verification

Agent Skills: Test Correlation Skill

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