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Record W4366506732 · doi:10.11159/icgre23.130

Performance Analysis of the Ituango Dam, Based On Geotechnical Instrumentation and Models

2023· article· en· W4366506732 on OpenAlexvenueno aff
Zorany S. Zapata, M.C. Sierra, Joshua D. Naranjo

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsInstrumentation (computer programming)Geotechnical engineeringGeologyCivil engineeringEngineeringEnvironmental scienceComputer science

Abstract

fetched live from OpenAlex

The performance of the Ituango Dam is analyzed in this document by comparing the results of geotechnical instrumentation with analytical and numerical models.Ituango Hydropower Plant Project has an Earth Core Rockfill Dam with modifications in its upper 50 meters.These modifications include a bentonite cement cutoff wall.The analyses focus on the behavior of pore pressures, settlements, and total stresses to identify the level of performance of the dam fills, the foundation, and important elements such as the cutoff wall indicated above.The field measurements (considering their range of statistical variation) are compared with the outcomes from analytical and finite element models in 2D and 3D.The geotechnical performance analysis of the dam corresponds to the current state, 3 years after its construction was completed.Through this research, it was found that the degree of correlation between field measurements and numerical calculations is high and, therefore, the measured variables are within what was expected.This information has also been of particular importance for the identification of anomalous behaviors, which complements the project's risk management plan.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.177
Teacher spread0.171 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicDam Engineering and SafetyFrench-language works237,207