Publication2021
Numerical prediction of undrained cyclic triaxial experiments on saturated Kasai river sand using two constitutive models of liquefaction
- Industry, Innovation and Infrastructure
- Innovation, Science and Technology
The record
- Type
- Publication
- Date
- 1 November 2021
- Level
- National
- Journal
- Bulletin of Engineering Geology and the Environment
- Volume
- 80
- Issue
- 11
- Pages
- 8565-8582
- Published
- 1 November 2021
- DOI
- 10.1007/s10064-021-02449-2
- Scopus ID
- 85115706043
- ISSN
- 14359529
- Authors
- 4
- Open access
- No
- Citations
- 17
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Numerical simulation comparing Finn-Byrne and PM4 constitutive models for predicting soil liquefaction behavior in cyclic loading of saturated sand for geotechnical analysis.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-3 Innovation, Science and Technology
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 9 label. Numerical simulation comparing Finn-Byrne and PM4 constitutive models for predicting soil liquefaction behavior in cyclic loading of saturated sand for geotechnical analysis.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Numerical prediction of undrained cyclic triaxial experiments on saturated Kasai river sand using two constitutive models of liquefaction”. Kortex.