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Record W4409576485 · doi:10.61091/jcmcc127a-128

Applied Research on Rocky Slope Damage Mechanism and Prevention Based on Big Data and Discrete Element Simulation

2025· article· en· W4409576485 on OpenAlexvenueno aff
Yu Su, Lu Sun, Liangliang Chen

Bibliographic record

VenueJournal of Combinatorial Mathematics and Combinatorial Computing · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
Fundersnot available
KeywordsDiscrete element methodMechanism (biology)Element (criminal law)GeologyForensic engineeringEngineeringGeotechnical engineeringPhysicsMechanicsPolitical science

Abstract

fetched live from OpenAlex

The physical and mechanical properties of the rock body at the foot of the slope are prone to deterioration under water-rock action, which affects the stability of the slope body. Accurate understanding of the damage mechanism of anticlinal rocky slopes in reservoir area under the condition of deterioration of the rock body at the foot of the slope is the key to the reasonable evaluation of stability. In this paper, the main lithological characteristics of the anti-dipping rocky slopes in the reservoir area and the distribution characteristics of slope height, slope angle and inclination angle of the rock layer are investigated as the research object, and the deformation and damage characteristics and laws of the rock body are obtained. Numerical simulation of anticline slopes was carried out using GDEM mechanical analysis software based on the discrete element method of continuous medium mechanics. It is found that the upper and middle parts of the slope where the invert body is located in the studied engineering example have deep tensile cracks and shallow surface block tipping damage, while the middle and lower parts show deep bending deformation, and there is a gradual transition zone in the contact between the deformed rock layer and the bedrock. As the distance between the cave and the basement increases, the rock layers gradually tilt towards the Yellow River from the north-east to the north-west, with the rock layers at the base of the cave tilting between 340° and 350°. The inclination of the rock layer in the example slope is 76°, and the main rupture surface of the slope, i.e. the location of the largest bending moment of the rock layer, has a small inclination angle with the horizontal plane. The slope angle is 48°, and the sum of the angles of the slope angle and the inclination angle of the rock layer is obviously larger than 117°, and the slope will be deformed and damaged, which is consistent with the value of the conditions for the slope to be deformed and damaged.

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)0.003
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0000.001
Research integrity0.0000.001
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 head0.037
GPT teacher head0.321
Teacher spread0.284 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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