Slope Stability Analysis and Hazards Assessment of Swat Motorway, Khyber Pakhtunkhwa, Pakistan
Bibliographic record
Abstract
The 81-kilometer-long Swat motorway starts from the Karnal Sher Khan interchange connecting M1 motorway with Chakdara, Swat. Major part of the motorway runs through Peshawar basin, while crossing Malakand ranges at some locations. Geologically, this region belongs to weak meta morphosed rocks of Mesozoic age and consists of schist, phyllite and schistose marble. These rocks are excavated for the highway with a height ranges from a few meters to 80 meters, which requires significant stabilization measures.In this case study, slope stability of the benches along the highway have been analyzed by kinematic approach using DIPS (Rocscience software). By using the discontinuities data collected from scanline survey of the area, probability of different modes of failures are predicted and potential unstable zones are determined. Keeping in view the financial aspects, it is desired to have a hybrid stabilization technique in contrast to conventional techniques to make the slopes stable and ensure road safety. Different slope angles are analyzed and it is found that there is high chances of planar failure i.e. 43% (average)1:0.15 sloping grade, while the failure chances can be reduced to 23%, if the slope gradeis kept as 1:0.5 (63.430), which is safer enough.Moreover, the benches are highly unstable under any seismic activity.According to kinematic analysis, a data of 225 discontinuities are recorded which is divided into three sets, among them set 3 is recorded as the most critical set of discontinuities resulting in 68.7 % chances of planar failure. A hybrid stabilization system comprised of a ditch filled with sand or fine debris material and rock fall protection system is proposed, which is economical and easily constructible for slope stability at KM 37 of the Swat motorway. Keeping in view the significance and efficiency of the system, it is recommended to be adopted at other sections of the Swat motorway as well.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".