Stability Analysis of Surface and Subsurface Geological Hazards Using Numerical Approach in Hydropower Project of India- a Case Study
Bibliographic record
Abstract
The paper reviews major geological problems encountered during construction of a mega hydropower project in the Lesser Himalayan region of Himachal Pradesh, India.Major hindrances encountered during construction of the project were backslope failure during construction of surface powerhouse in metavolcanics with slumped rockmass and rock bursting during tunnelling in hard and brittle quartzite.Two different modes of failures occurred during excavation of 180m long backslope of surface Powehousecircular failure along highly weathered slumped rockmass and planar failure along crushed rock filled valley dipping joints.Stability assessment of powerhouse backslope was carried out through Finite element based software and Limit equilibrium based software for analysis of planar failure in jointed rockmass and determine critical slip circle of failure and Factor of Safety of the slope through strength reduction technique.Optimum support analysis for stabilization of cutslope was carried out through numerical simulation.Deformation meshes, accumulated principal strain and total displacement are the other parameters obtained from the results computed and analysed using FEM.The paper also back analyzes magnitude of in-situ stresses in rock bursting zones encountered during tunnelling using finite element based software to determine role of depth of overburden and field stress ratio in causing rock bursting.The result indicates that magnitude of principal stresses and yielding zones increase with depth of overburden and decrease in field stress ratios.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".