Bibliographic record
Abstract
Many rivers and streams throughout the world in the past century were severely affected by human activities including water extraction, watershed land use changes, power generation, dam and levee construction. In highly urbanized cities, engineering practices advocate straightening, enlarging, and converting the natural rivers and streams into concrete channels to minimize flooding and erosion problems. These engineering design approaches destroy the natural equilibrium of the fluvial systems and eliminate the aquatic and riparian species in the watercourse. The objective of this research is to develop a general stream restoration design approach for flood control concrete channels in highly urbanized areas. The restoration goals are: 1) to create a natural and self-sustainable river system in order to re-establish the aquatic species on the flood control channel; 2) to provide appropriate in-stream covers, pools and riffles features for fish spawning and rearing; and 3) to maintain the flood control function after stream restoration. There are four phrases involved in the design methodology of flood channels restoration: 1) identification of restoration goals, 2) stream assessment on the existing condition; 3) modification and verification of the low-flow channel design based on stream assessment findings; and 4) confirmation of the original flood control function. Yuen Long Nullah in Hong Kong will be used as a pilot site study to demonstrate the design framework. Meanders and deflectors will be applied to the low-flow channel modification design. A physical model representing an actual 2-metre wide meander channel section of the low-flow channel was constructed and experimented at The Hong Kong Polytechnic University’s Hydraulics Laboratory. A numerical sediment transport model using the CCHE2D program was used to adjust the modification design and verify the flood control function. The pilot site has been tentatively demonstrated the restoration design approach developed in this research where deflectors are a major factor on pools creation. Moreover, a single deflector located along the inner curvature of the meander section with 1/3 contraction ratio is proved to be the best design using the physical model. The numerical model using the CCHE2D program showed that the 7-block system can be used to model a deflector with porosity of 40%. Numerical results also demonstrated that the bed material will not be totally flushed out after a severe thunder storm.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".