MODELING FIELD GEOMETRY OF MICRO-IRRIGATION SYSTEMS
Bibliographic record
Abstract
The purpose of planning an irrigation network is to achieve suitable water distribution and to satisfy the hydraulics and economic rules. A model was developed to design, plan and manage an irrigation system subject to a number of constraints according to field geometry, soil properties, plant characteristics and irrigation system parameters. As a result, management criteria may be achieved by selecting a layout pattern and the appropriate number of shifts. The Microsoft Excel Solver tool was used to solve the partitioning part. The model divides the field into subunits. The decision variables are: 1) pipe lengths and diameters (lateral, riser, manifold, auxiliary, submain and main). 2) The total number of subunits, number of sets (subunit parallel to the main line). 3) Number of submain lines perpendicular to the main line. 4) Possible numbers of shifts and shift time. 5) List of system equipment. 6) Pump total dynamic head, system capacity and pump power. 7) Cost analysis of the system and total capital cost. The model was successfully solved the problem of partitioning the field and specifies the dimension of different parts of the micro irrigation system network. The planning of the irrigation field layout accomplished among five patterns (A through E). The validity of the model was extended to select the economic pipe sizes and estimate the system total costs in case of one shift operation policy or at a higher number of shifts to reduce the cost. Throughout a case study to plan design and management of 20 fed. (300 m length and 280 m width) to irrigate trees 5mx5m spacing, results indicated that pattern E was the most economic option either in operating the system in one shift (the cost is 7348 LE.fed) or to reduce further cost to be 3861 L.E./fed.) in case of operate the system in four shifts. Investigating the effect of system area ranged between 5 to 50 feddan on system total cost indicated that the cost increased linearly proportional to the increasing of the system area. The effect of number of shifts on total cost was also studied. The results showed that the relationship is power function where the total cost is inversely proportional to increasing the number of shifts.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".