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Record W4414062695 · doi:10.3390/geohazards6030053

Seismic Assessment of Concrete Gravity Dam via Finite Element Modelling

2025· article· en· W4414062695 on OpenAlex
Sanket Ingle, Lan Lin, S. Samuel Li

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeoHazards · 2025
Typearticle
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGravity damFinite element methodDam failureSeismic riskFoundation (evidence)Seismic analysisSeismic hazardInduced seismicity

Abstract

fetched live from OpenAlex

The failure of large gravity dams during an earthquake could lead to calamitous flooding, severe infrastructural damage, and massive environmental destruction. This paper aims to demonstrate reliable methods for evaluating dam performance after a seismic event. The work included a seismic hazard analysis and nonlinear finite element modelling of concrete cracking for two large dams (D1 and D2, of 35 and 90 m in height, respectively) in Eastern Canada. Dam D1 is located in Montreal, and Dam D2 is located in La Malbaie, Quebec. The modelling approach was validated using the Koyna Dam, which was subjected to the 1967 Mw 6.5 earthquake. This paper reports tensile cracks of D1 and D2 under combined hydrostatic and seismic loading. The latter was generated from ground motion records from 11 sites during the 1988 Mw 5.9 Saguenay earthquake. These records were each scaled to two times the design level. It is shown that D1 remained stable, with minor localised cracking, whereas D2 experienced widespread tensile damage, particularly at the crest and base under high-energy and transverse inputs. These findings highlight the influence of dam geometry and frequency characteristics on seismic performance. The analysis and modelling procedures reported can be adopted for seismic risk classification and safety compliance verification of other dams and for recommendations such as monitoring and upgrading.

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.

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: none
Teacher disagreement score0.890
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.237
Teacher spread0.230 · 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