PICK CALIBRATION CURVES FROM DATASET

Selects one representative stress-strain curve per (state, strain_rate) bucket from a dataset of physical-test curves using Pareto-front scoring with a non-crossing constraint between adjacent strain rates within each state. Use this worker to reduce a raw coupon-test dataset down to the calibration-ready curve set for material card authoring.

When to use

Classification: process.

Tagged: bucket_selection, calibration, coupon, curve_selection, material, non_crossing, outlier_removal, pareto.

Inputs

Label ID Type Default Required Description
Dataset Of Test Curves dataset dataset Input dataset of physical test curves; each row must contain at minimum a state label, a strain-rate value, and a stress-strain curve cell.
State Column state_column scalar state   Name of the dataset column that identifies the deformation state (e.g. tension, compression, shear); defaults to ‘state’.
Strain Rate Column strain_rate_column scalar strain_rate   Name of the numeric dataset column that holds the strain-rate value for each test record; defaults to ‘strain_rate’.
Curve Column curve_column scalar eng_stress_strain   Name of the dataset column whose cells contain the engineering stress-strain curve objects to be evaluated; defaults to ‘eng_stress_strain’.
Pareto Selection Criteria pareto_criteria dataset (complex)   Table defining which curve features (slope, xmax, ymax, xatymax, integral, …) participate in Pareto-front scoring and whether each should be minimised or maximised; leave at default (slope/xmax/ymax all minimised) for standard conservative curve selection.
Type Of Data To Use data_type scalar median   Controls whether Pareto feature scores are measured relative to the per-bucket median (‘median’, default) or to raw feature values (‘raw’); use ‘raw’ when bucket populations are very small.
Remove Outliers remove_outliers scalar ymax   Pre-pass outlier removal strategy applied before Pareto scoring: ‘none’, ‘xmax’ (filter by failure strain), ‘ymax’ (filter by peak stress, default), or ‘both’.
Outlier Tolerance outlier_tolerance scalar 0.5   Fractional deviation threshold used by the outlier-removal pre-pass; 0.5 means a curve is flagged if its feature deviates more than 50 % from the bucket median (default 0.5).
Non-crossing Check: Minimum X non_crossing_check_min_x scalar auto   Lowest x at which to start checking for crossings. ‘auto’ = max(curve_a.xmin, curve_b.xmin)
When A (state, rate) Bucket Has No Surviving Candidate on_empty_bucket scalar omit   Behaviour when a (state, strain_rate) bucket contains no valid curves after outlier removal: ‘omit’ (default) skips the bucket silently, other values may raise a warning or error.
Cross-rate Envelope (Spread) pick_envelope scalar upper   Cross-rate spread objective. Default ‘upper’ targets the upper envelope of the candidate cloud at every rate so picks demonstrate strain-rate sensitivity instead of clustering (verified against Ashutosh’s manual selection on the ABS PBUV cloud, JIRA DW-2900). ‘lower’ flips to ymax=min everywhere. ‘auto_by_rate’ currently behaves like ‘upper’; reserved for future per-rate auto-detection. ‘none’ is legacy v1 — apply user criteria uniformly. Only the ymax criterion direction is rewritten; slope and xmax rows pass through unchanged.
Final Remove-Intersections Pass final_remove_intersections scalar yes   After per-bucket selection and the non-crossing walk, lift residual crossings between adjacent strain-rate picks via CurvesTransformer::remove_intersections. Default ‘yes’ (matches the post-processing path used downstream of typical material-card calibration). Mirrors the toggle used by extrapolate / sync_last_slope / interpolate_curves_*.
Final Removal Method final_removal_method scalar offset   Removal-method passthrough to CurvesTransformer::remove_intersections; only consulted when ‘Final Remove-Intersections Pass’ is not ‘no’. Default ‘offset’.

Outputs

Label ID Type Description
Picked Curves picked_curves dataset Dataset containing exactly one selected stress-strain curve per (state, strain_rate) bucket, with all original metadata columns preserved alongside the chosen curve cell.
Scatter Statistics scatter_stats dataset Dataset of per-bucket descriptive statistics (e.g. feature means, medians, scatter metrics) computed during Pareto scoring, useful for auditing selection quality and documenting test scatter.

Disciplines

  • data.curve.pair
  • data.dataset.transform
  • engineering.material.calibration
  • engineering.material.characterization
  • engineering.material.specimen

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