PEDESTRIAN PROTECTION EVALUATOR¶
Runs pedestrian protection (PedPro) LS-DYNA simulations by combining a vehicle baseline model (or pre-positioned inputs) with one or more impactor types (headform, lower leg, upper leg) at defined strike positions. Submits a batch of HPC jobs for each position and collects the resulting study and simulation records for downstream post-processing.
When to use¶
Tagged: pedestrian_impact, batch_simulation, headform, hpc, impactor, lower_leg, ls-dyna, pedestrian_protection.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Study Name | study_name | text | PedPro Simulations | ✓ | Human-readable label assigned to the PedPro simulation study; defaults to ‘PedPro Simulations’ and is used to group all submitted jobs. |
| Impactor Type | impactor_type | select | headform | Selects the pedestrian impactor type to use — ‘headform’, ‘lower_leg’, or ‘upper_leg’ — which determines the impactor FE model and applicable injury criteria extracted during post-processing. | |
| Vehicle Input Files | main_input_files | file | — | ✓ | Vehicle LS-DYNA input deck(s): upload multiple flat files or a single ZIP archive; if zipped, the main include file must contain the word ‘main’ in its filename. |
| Input file type | input_file_type | select | baseline | Specifies how impactor positions are encoded in the uploaded files: ‘baseline’ (single model with embedded positions), ‘positioned_folders’ (ZIP with one sub-folder per position), or ‘positioned_files’ (individual pre-positioned decks). | |
| Impactor Positions | impactor_positions | dataset | — | Optional dataset supplying impactor strike positions (translations, direction cosines, rotation centre, angle) when ‘baseline’ input_file_type is selected; leave empty if positions are baked into the file structure. | |
| Impactor Position Mapper | impactor_positions_col_map | mapper | — | Column mapper that aligns dataset fields from impactor_positions to the required position schema (X/Y/Z-Translation, X/Y/Z-Cosine, X/Y/Z-Rotation-Center, Angle); must be configured whenever impactor_positions is supplied. | |
| Part and Sensors Map for Post processing | part_and_sensors_map | keyvalue | (complex) | ✓ | Key-value map of LS-DYNA part IDs and sensor/load-cell IDs used during post-processing to extract contact, tracking-node, femur, and tibia responses; defaults cover a standard single-impactor model setup. |
| Impactor Node Set Id | impactor_node_set_id | text | 1 | Impactor node set id | |
| Impactor Transform Id | impactor_transform_id | text | 1 | Impactor transform id | |
| Template ID | template_id | remote_lookup | — | ||
| Project ID | project_id | remote_lookup | — | ||
| Study ID | study_id | remote_lookup | — | ||
| Saved HPC Config | saved_hpc_config | remote_lookup | — | ||
| Run Baseline Only | baseline_only | select | yes | ✓ | Option to run baseline or all positions |
| Impactor Position file pattern | position_file_pattern | text | PedShot | Impactor Position File Name pattern. This file will be replaced | |
| Main input file pattern | main_input_file_pattern | text | Main | Main input file pattern. This file will be used to replace the positioned files | |
| Termination Time | term_time | text | 0 | Optional termination time. Only supported for positioned files | |
| Include Files pattern | include_files_pattern | text | INCLUDE | Include file pattern. Only files matching this pattern will be included in the simulation basides the main and the pedshot file | |
| Update main input file name with Impactor filename | update_main_file | select | no | ✓ | Helps to distinguish when the filename is identical in all runs |
| Analysis | analysis | select | simulation | Simulation runs every point. Eigenvalue does a localized modal run per point. ML-Assisted simulates a chosen subset and predicts HIC for the rest. Select-only returns the picked-vs-skipped points for review, with no simulations. | |
| Saved ML model | saved_model | remote_lookup | — | ML-Assisted only. Supply a saved model to skip simulation and predict HIC for all points directly. | |
| Subset sizing | sizing_mode | select | fixed | ML-Assisted only. How the simulated subset is sized. | |
| Subset size (K or fraction) | num_subset_points | text | 0.2 | How many points to select: an integer count, or a fraction 0<f<1 of all points (0.2 = 20%). | |
| Include eigen features | include_eigen_features | select | no | ML-Assisted only. When Yes, run eigenvalue at all points to add eigen frequency/mass/stiffness as features. | |
| Accuracy target | accuracy_target | text | 0.9 | ML-Assisted only. Target prediction accuracy (R^2) for adaptive / fixed-plus-one sizing. | |
| Feature source | ml_feature_source | select | compute | Where features come from. Compute: measure per-point metrics from the model. Use supplied rows: take the input positions as-is (they already carry the metric columns, e.g. a clearance spreadsheet). | |
| Selection method | ml_selection_method | select | kmeans | How the simulated subset is chosen (all deterministic). K-means: uniform cluster representatives. Latin-hypercube: even coverage per feature. Farthest-point: the extremes. Combined: union of those three, trimmed to K by consensus (combined-all keeps every unique point). Zone lines: per line keep both ends, the center, and N interior points, along constant-Px (zone-x), constant-Py (zone-y), or both (zone-line). | |
| Feature columns | ml_feature_columns | select | (complex) | Metric columns the selection spreads over (not used by zone lines). Empty = use all numeric metrics present, including any new ones (HIC/id auto-excluded). Or pick a subset, or type custom names for dataset features (e.g. MIN, CON1). | |
| Zone-line interior points (N) | zone_line_interior_points | text | 3 | Zone lines only. Interior points kept per line, plus its two ends and center. | |
| Zone-line grouping tolerance | zone_line_px_tolerance | text | 10 | Zone lines only. Points farther apart than this (along the grouping axis) start a new line. Raise if one line is split, lower if lines merge. | |
| Analysis scope | analysis_scope | select | entire_vehicle | Entire vehicle: analyse the model as supplied. Hood parts only: extract a self-contained submodel of the hood part ids and their connections and analyse that (requires Hood part ids). Eigenvalue only. | |
| Keep connections | keep_connections | select | yes | Hood parts only. Keep the submodel’s connections (spotwelds, rivets, tied contacts, BCs) among included parts. Eigenvalue only. | |
| Connection levels | attachment_levels | text | 0 | Hood parts only. Connection levels beyond the hood to include: 0 = hood + its internal connections, 1 = also directly-connected parts, 2 = one level further, etc. Eigenvalue only. | |
| Submodel delivery | submodel_delivery | select | copy | Copy: place the model/submodel in every simulation. Store once: stage it in one host simulation and point the rest at it via *INCLUDE_PATH (needs a shared file system). Eigenvalue only. | |
| Constraint type | constraint_type | select | free_free | SPC for the localized run. Free-free: none (full modal). All-outside: fix all nodes outside the impact box. Boundary: fix only the box-edge ring. All-outside-except-connected: as all-outside but leave spotweld/rivet/tied nodes free. Box shell: fix only the shell between an outer box and the impact box (fast; for hood-only submodels). Eigenvalue only. | |
| Headform radius (mm) | headform_radius | text | 82.5 | Pedestrian headform radius (165 mm dia = 82.5 mm). In-plane box half-extent is 1.5x this (82.5 -> 123.75 mm), with a tall z. Eigenvalue only. | |
| Impact-box half-extent override (mm) | head_impactor_diameter | text | — | Optional in-plane box half-extent override. Blank = size from the headform radius (1.5x). Eigenvalue only. | |
| Box half-extents override (mm) | box_half_extents | text | — | Optional explicit dx,dy,dz half-extents that override the head-impactor-diameter box. Leave blank to size the box from the head impactor diameter. Eigenvalue analysis only. | |
| Number of eigen modes | num_eigen_modes | text | 50 | Number of modes to compute (neig). Eigenvalue analysis only. | |
| ID offset for generated cards | id_offset | text | 9990000 | Eigenvalue analysis only. Added to the generated box and node-set ids so they do not clash with the baseline (e.g. offset 9990000 gives id 9990001). Increase if your baseline already uses ids in this range. | |
| Deck mode | deck_mode | select | per_point | Per-point creates one simulation for each impact point; single_case creates one simulation with a case per point. Eigenvalue analysis only. | |
| Remove previous study simulations | remove_previous_study_sims | select | no | When a study id is provided, delete that study’s prior simulations before creating new ones. | |
| Fetch results after jobs finish | fetch_results | select | no | When jobs are finished, aggregate eigout (eigenvalue) or HIC/responses (simulation) into a result dataset. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| Study Id | study_id | integer | Integer identifier of the d3VIEW study created to group all submitted pedestrian-protection simulations. |
| Simulations | simulations | dataset | Dataset listing each individual simulation record (one row per impactor position) with metadata linking position parameters to their respective jobs. |
| Hpcjobs | hpcjobs | dataset | Dataset of HPC job records corresponding to each submitted simulation, carrying queue status and job IDs for monitoring and downstream result extraction. |
| Results | results | dataset | After jobs finish (Fetch results = Yes), a dataset of results: for Eigenvalue analysis, one row per mode per simulation (eigenvalue, radians, frequency in Hz, period); for Simulation analysis, the extracted responses. |
| Metrics | metrics | dataset | ML-Assisted only. The per-point feature rows the point selection ran over (computed metrics, or the supplied dataset features). |
| Selected Points | selected_points | dataset | ML-Assisted (select points only). Every candidate point tagged selected (yes/no) along with its metric columns, so the picked-vs-skipped sweep can be reviewed before simulating. |
| Selected Count | selected_count | scalar | ML-Assisted (select points only). Number of points the sweep selected. |
Disciplines¶
- cae.preprocessing.scenario
- cae.solver
- engineering.crash.dynamics
- engineering.crash.occupant_safety
- platform.job_submission
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