Geotechnical and geophysical characterisations of construction waste-infilled quarry for housing and commercial developments: Case study of Tehran, Iran
Bibliographic record
Abstract
The fast population growth in the metropolitan areas of the province of Tehran has led to the scarcity of land and inevitable expansion of urban construction to non-engineered fills and construction/demolition waste disposal sites. An abandoned aggregate quarry, infilled with construction wastes over 16 years, has been recently selected for a new development project consisting of several multi-storey commercial and residential complexes (up to 7 storeys). This study was aimed at delineation of the waste materials, geophysical and field and laboratory geotechnical characterisations prior to foundation design, and the design of the excavation programme. Geo-electric resistivity test was used to delineate the waste materials from natural ground materials. Surface and downhole P- and S-wave velocity measurements were used for the estimation of dynamic elastic properties of the wastes. In total, 12 boreholes (15-30 m deep) along with 10 test pits (4-8.5 m deep) provided the opportunity for visual observations of the waste materials, necessary sampling for compositional analyses, laboratory shear strength tests and determination of waste deposit thickness in different regions of the site. Manual standard penetration test (SPT) was also used to evaluate in situ stiffness of the fine materials of the waste. Six field plate load tests were performed on the waste materials at their natural water content conditions and at saturated (flooded) ground conditions to determine their compressibility and the ground reaction modulus. Based on the results from extensive characterisation programme, it was concluded that the waste materials are in a metastable state and exhibit heterogeneity across the site. The findings of current case study can provide new insight into construction/demolition waste behaviour, using available geophysical and geotechnical tools and testing procedures for characterisation, and eventually helping in reliable design of foundations for new development projects.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".