A FEASIBILITY STUDY ON UNDERGROUND INFRASTRUCTURE IMPLEMENTATION TO ENHANCE DHAKA’S ELECTRICAL GRID RELIABILITY
Bibliographic record
Abstract
This study systematically reviews the feasibility of implementing underground power infrastructure to enhance the reliability of Dhaka's electrical grid. Given the city's frequent power outages due to adverse weather and aging overhead power lines, this review synthesizes findings from peer-reviewed journal articles, technical reports, conference papers, and case studies published between 2010 and 2023. The review highlights the significant benefits of underground systems, including improved grid reliability and resilience, reduced outages, and enhanced urban aesthetics and safety. However, it also identifies substantial economic and technical challenges, such as high initial installation costs and complex maintenance requirements. Recent technological advancements, such as improved cable materials and installation techniques, have made underground power lines more feasible and cost-effective. Case studies from cities like Amsterdam, London, New York, and Toronto provide valuable insights into successful implementation strategies, emphasizing the importance of integrated urban planning and stakeholder collaboration. These findings offer a robust foundation for policymakers, utility companies, and urban planners to consider transitioning Dhaka's power infrastructure to an underground system, aiming to mitigate the impacts of severe weather and enhance overall grid reliability.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".