Dynamic Simulation for Optimal Facility Sizing As Part of the Eastern New Mexico Rural Water Supply Project
Bibliographic record
Abstract
Ute Reservoir, located in northeastern New Mexico on the Canadian River, is the source of up to 16,450 acre-feet per year (ac-ft/yr) of water intended for use by New Mexico communities located in the Eastern New Mexico Rural Water Authority (ENMRWA) area. As `owner' of the water, the New Mexico Interstate Stream Commission has worked with U.S. Bureau of Reclamation (USBR) to develop a project to use the allocation to relieve the critical municipal water shortage situation in eastern New Mexico. The shortage is caused by the steady declines in water levels in the Ogallala (or High Plains) aquifer, which is currently the sole source of supply for much of eastern New Mexico for both municipal and agricultural water. The Eastern New Mexico Rural Water Supply Project was established to provide a surface water supply to Ute Reservoir water for ENMRWA members. The majority of the supply will be used to meet demands in the population centers of Clovis and Portales, but supplies will be conveyed through approximately 150 miles of pipelines as far as 120 miles south of the reservoir to the Town of Elida. Because significant pipelines are required to convey this surface supply, small changes in pipeline design can result in significant changes in capital and O&M costs. CH2M HILL developed and employed a dynamic simulation optimization model of the pipeline, pumps, and system storage to aid in developing an efficient (e.g. least cost) design. The primary objective of the evaluation was to test the hydraulic simulation-optimization approach, evaluate trade offs between pipe sizing, storage requirements, pump capacity, control valving, and overall costs as measured by estimated capital and operating costs. The model was developed using CH2M HILL's ReplicaTM Model resulting in nearly a 6 percent overall cost savings at more than $18 Million from the conceptual design report (CDR). This paper will discuss an overview of the project and project status, the design basis established for system demands, model components, model configuration, results, and project cost savings. This paper will benefit the professional community by showing how optimization models can potentially reduce costs for large transmission pipeline projects.
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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".