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Record W2907098065 · doi:10.4408/ijege.2013-06.b-58

Exploration of the kinematics of the 1963 vajont slide, Italy, using a numerical modelling toolbox

2013· article· en· W2907098065 on OpenAlexfundno aff
Andrea Wolter, Mohsen Havaej, Luca Zorzi, Doug Stead, John J. Clague, Monica Ghirotti, R. Genevois

Bibliographic record

VenueArchivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaRio TintoAngloGold Ashanti
KeywordsKinematicsToolboxComputer scienceGeologyGeodesyPhysicsProgramming language

Abstract

fetched live from OpenAlex

The Vajont Slide has been studied for half a century,
\nyet questions about its kinematics and dynamics
\nstill remain. Application of state-of-the-art numerical
\ntechniques aids in understanding the slide’s mechanical
\nbehaviour. In the current paper, we use four two- and
\nthree-dimensional finite element, distinct element, and
\nlattice-spring modelling codes in a toolbox approach
\nto conduct a forensic, exploratory investigation of the
\nkinematics of the slide. We examined the influence of
\nrock mass properties and friction along the failure surface
\nusing the 2D finite element code. Preliminary results
\nindicate that weaker units within the sliding mass
\ndeformed more than stronger units, and that a Prandtl
\nwedge zone of transition developed between the active
\nupper and passive lower blocks of the slide mass in the
\nwest. The difference between the biplanar western sliding
\nsurface and the more circular eastern surface proves
\nto be significant in terms of stability. Models suggest
\na critical friction angle of approximately 18°, above
\nwhich the slope is stable. The 2D distinct element modelling
\nresults indicate that both failure surface morphology
\nand block size are important. Planar and arc-shaped
\nfailure surfaces are most unstable, whereas rough undulating
\nsurfaces are stable. As block size increases, overall
\nslope stability increases and a lower friction angle
\nalong the failure surface is required to initiate sliding.
\nBlock kinematics were further investigated using a 3D
\ndistinct element code. This numerical code illustrated
\nthe controls of bounding structural features such as the Col Tramontin Fault and Erto Syncline, as well as block
\nsize, on the failure. Finally, preliminary simulations in
\na new 3D lattice-spring code show that crack clusters
\ndeveloped, and became concentrated in the transition
\nzone between the back and seat of the chair-shaped failure
\nsurface.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.021
GPT teacher head0.211
Teacher spread0.190 · 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 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

Citations11
Published2013
Admission routes1
Has abstractyes

Explore more

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