Data · dataset · 2026
Supplemental Materials for "Smart-Green Hybrid Digital Twin Framework for Vetiver NbS Scour Countermeasures"
Listed in Teesside University Research Data Repository
This dataset contains supplemental materials supporting a peer-reviewed journal manuscript.
Description
Tables S1-S8 provide: S1) HEC-RAS 2D mesh sensitivity analysis at the abutment; S2) Manning’s n calibration for vetiver channels from literature and field tests; S3) Digital twin alert thresholds for velocity, shear stress, and scour depth; S4) Sources of 140 laboratory cases used for Random Forest model training; S5) RF hyperparameter ranges and optimal values from 5-fold cross-validation; S6) UAV image dataset summary for vetiver health classification; S7) Bill of quantities comparing vetiver NbS vs. riprap, using NHA CSR 2023 rates; S8) Embodied carbon calculations using Ecoinvent 3.9 and ICE v3.0 factors.
Figures S1-S4 include: S1) HEC-RAS 2D mesh layouts showing 4m, 2m, and 1m refinements; S2) Sample UAV training images from DJI Mavic 3E showing classes for healthy vetiver, stressed vetiver, bare soil, and water; S3) Field photographs of vetiver growth stages at Kala Khatai site, Mar-Jun 2026; S4) Lifecycle cost comparison charts for vetiver NbS vs. conventional riprap. All data were generated using HEC-RAS 6.4.1, Python 3.11.5 with scikit-learn 1.3.2, Agisoft Metashape 2.0, and publicly available sources.
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Raw code and processing scripts are included where applicable. The main article is complete without this supplemental data.
Links
Where it is published
- DOI doi.org/10.17632/jxsf6fn7hr.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
- Computer Science & AI · Earth & Environmental Science · Engineering
- Inferred from text
- Image 75%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/jxsf6fn7hr.1 | 14 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| 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[modality].local:modality:image | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| 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 |