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Record W2806116417 · doi:10.1139/cgj-2017-0651

Kinematic energy balance approach to submarine landslide evolution

2018· article· en· W2806116417 on OpenAlexvenueno aff
Christian Buss, Balz Friedli, Alexander M. Puzrin

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsKinematicsSubmarineGeologyLandslideSlip (aerodynamics)Submarine landslideSlabEnergy balanceGeotechnical engineeringPlasticityDeformation (meteorology)MechanicsEngineeringClassical mechanicsGeophysicsPhysics

Abstract

fetched live from OpenAlex

The paper applies the energy balance kinematic method of plasticity theory to the large deformation problem of initiation and propagation of the spreading and ploughing failure outside a failed slab in submarine sediments. The models account for the phenomenon of the progressive propagation of a slope parallel slip surface, which is also quantified using the energy balance approach. In contrast to existing approximate analytical and numerical solutions, the proposed approach provides a theoretical basis for spreading and ploughing criteria as well as the comprehensive dynamic solution of the problem of post-failure landslide evolution. Incremental integration of the derived analytical expressions for kinetic energy in time allows for modelling recurrent initiation of new kinematic failure mechanisms with their subsequent large-scale deformation. Treating the failed slab as well as the spreading and ploughing mechanisms as one composite dynamically evolving mass movement allows for the final post-failure geomorphology of the failed slope to be predicted using basic mechanical principles.

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)0.001
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.193
Teacher spread0.187 · 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

Citations21
Published2018
Admission routes1
Has abstractyes

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