IMPROVEMENT OF THE MAIN WATER NETWORK FOR MIDDLE CITY
Bibliographic record
Abstract
In systems of centralized water supply, the givining-distribution complex (GDC) has the highest cost, including pumping stations, water pipes and water supply networks: main, street, intra-quarter. The economic efficiency of the operation of this complex directly depends on the technical condition of the facilities and equipment. But over time, the technical characteristics of both pumping units and pipelines deteriorate due to wear. Therefore, it is necessary to periodically check their technical characteristics, as well as evaluate the topological characteristics of the water network in the process of its development. This requires regulatory documents and research by specialists in this field of technical sciences. This paper presents an example of such an approach for the givining-distribution complex of the water supply system the medium-sized city Borispol (65 thousand inhabitants) of the Kiev region. To set the throughput of the main water network, hydraulic calculations were performed on a computer using the HIDRO program. It has been established that the main water network has sufficient capacity, as evidenced by the constructed piezometric maps. It has been established that the topological structure of the water network is imperfect. To improve the structure, it is proposed to loop the network by introducing an additional section. This section is introduced in parallel to two existing dead-ends. This improvement made it possible to reduce the pressure at pumping stations by 2.4 m and obtain an annual energy saving of 19.57 thousand kWh. Due to the commissioning of an additional section, a new network ring was formed and the reliability of water supply to a number water consumers increased more than 5.6 times. The indicated increase in the reliability of water supply is due to the fact that this section is introduced in parallel with 2 existing dead-end sections.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".