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Record W4413135898 · doi:10.1061/9780784486368.007

Mountain Home Air Force Base Water Resilience Project: Challenges Associated with Design of Pump Station and Pipeline with Tight Schedule

2025· article· en· W4413135898 on OpenAlexaff
Michael Georgalas, Timur Ayvaz, Erik Boschulte

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsPipeline (software)Resilience (materials science)ScheduleBase (topology)Computer scienceBase stationEnvironmental scienceMarine engineeringPipeline transportEngineeringTelecommunicationsEnvironmental engineeringOperating systemMaterials science

Abstract

fetched live from OpenAlex

The existing water supply for Mountain Home Air Force Base (MHAFB) consists of groundwater wells to meet the demands of the Air Force Base. However, the water level within the aquifer that the wells pump has been declining at a rate that is not sustainable, and some wells have been shut down due to nitrate contamination concerns. MHAFB is important to national security and contributes an estimated $1 billion to the Idaho economy. The Idaho Water Resource Board (IWRB) has been working for more than 10 years to develop a long-term, sustainable water supply for the base. The new water supply for MHAFB will come from the Snake River. Water will be pumped from the CJ Strike Reservoir through approximately 14.4 mi of 18″ to 22″ high-density polyethylene (HDPE) and 18″ steel pipeline to MHAFB. The steel pipeline was needed as the pipeline pressure exceeded 300 psi near the CJ Strike Reservoir. The pipeline has a design capacity of 3.64 million gallons per day (MGD). The Design-Build team of IMCO/Stantec was selected to design and construct the MHAFB Water Resilience Project. Construction began in May 2024 and is scheduled to be complete in July 2025. There were several challenges associated with the design and delivery of this project, stemming from its technical complexity, tight timelines, and fixed-price design-build delivery method. This paper explores how multidisciplinary teams can collaborate effectively to address these challenges by integrating advanced hydraulic modeling techniques, implementing strategic design schedule management practices, and conducting comprehensive project site evaluations and pipeline planning. By detailing the innovative approaches and coordinated efforts used to navigate the complexities of high-pressure pump station and pipeline design, this paper highlights key strategies for meeting aggressive deadlines, effective and early detailed evaluation of key design components, and achieving success in the alternative delivery and design-build market.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.796
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.198
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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