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Record W2771730309 · doi:10.1520/gtj20160254

Design and Performance of an In-Flight Rainfall Simulator in a Geotechnical Centrifuge

2017· article· en· W2771730309 on OpenAlexaboutno aff
Dipankana Bhattacherjee, B. V. S. Viswanadham

Bibliographic record

VenueGeotechnical Testing Journal · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
Fundersnot available
KeywordsCentrifugeGeotechnical engineeringIntensity (physics)ReplicateEnvironmental scienceGeologyMathematics

Abstract

fetched live from OpenAlex

Abstract The objective of this paper is to present the design details and performance of an actuator for simulating in-flight rainfall at enhanced gravity levels in centrifuge. The developed simulator is capable of inducing in-flight rainfall of various intensities (varying from 10 mm/h to 80 mm/h in prototype dimensions) and durations (over a year continuously in prototype dimensions) on geotechnical structures using specially designed pneumatic nozzles. The intensity and duration of rainfall can be regulated at any point of time in the in-flight condition to replicate prototype natural hazards, ranging from long-term medium intensity rainfall to a short spell of very high intensity rainfall. The various components of the developed simulator are discussed, with special emphasis on measures adopted to nullify Coriolis effects on droplet trajectory. Furthermore, the simulator produces rainfall in the form of fine mist at high gravities, which neutralizes chances of erosion due to impact of raindrops. In the present paper, a total of six calibration tests at high gravities and four centrifuge model tests on a typical silty sand slope were carried out using a 4.5-m radius large beam geotechnical centrifuge facility available at IIT Bombay, India. The analysis and interpretation of calibration results indicated that uniform rainfall intensity could be achieved over entire model surface area, and they were further applied to implement the scaling laws involved in modelling of rainfall in a geotechnical centrifuge. The model tests on silty sand slope indicated a rise in phreatic surface with ingress of rainwater, accompanied by face deformations and surface settlements, which increased in magnitude with higher rainfall intensities. In addition, the phreatic surfaces induced during rainfall using the developed simulator and time corresponding to failure observed in centrifuge were compared with numerical results using Geostudio 2012 (Geo-Slope, Calgary, Canada) and were found to corroborate well.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.256
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2017
Admission routes1
Has abstractyes

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