Data · dataset · 2026
Data and code for: SHAP-Based Interpretability of Machine Learning Models for the Shear Capacity of Corrugated-Web Steel Girders
Listed in Teesside University Research Data Repository
Dataset, EN 1993-1-5 Annex D implementation, trained CatBoost model, SHAP attributions and analysis scripts supporting the article "SHAP-Based Interpretability of Machine Learning Models for the Shear Capacity of Corrugated-Web Steel Girders: Insights for Design-Code Calibration".
Description
The data comprise 181 experimentally tested steel girders with trapezoidal corrugated webs, a secondary compilation derived from the 206-specimen database of Shrif et al. (2024, Heliyon 10, e35778) by removing 25 specimens whose corrugation geometry falls outside the trapezoidal idealisation of EN 1993-1-5 Annex D. The deposit reproduces every numerical result, table and figure in the article, including the grouped SHAP attribution, the subgroup analysis of code-unconservative specimens, and the cross-validated trial recalibration of Annex D. The included EN 1993-1-5:2006 Annex D implementation has been verified expression by expression against the published standard, equations (D.4) to (D.10).
The same 181 specimens underlie a companion study on tri-code comparison, deposited separately at doi.org/10.17632/nsm2gxj88n.1. See README.md for full provenance, a file manifest, and reproduction instructions.
Links
Where it is published
- DOI doi.org/10.17632/p3vjt7w9v7.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Civil engineering · Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Machine learning · Social Science · Structural engineering
- Inferred from text
- Tabular 65%
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/p3vjt7w9v7.1 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:400510 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Structural Engineering'] |
| concepts[field].anzsrc:group:4005 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Civil Engineering'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:tabular | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |