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Record W4319781863 · doi:10.2172/1923455

Reservoir Lining for Pumped Storage Hydropower: Scoping Study of Geomembrane Lining Systems

2023· report· en· W4319781863 on OpenAlexaff
Jason Hedien, Mustafa S. Altinakar, Scott DeNeale, Vladimir Koritarov

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsStantec (Canada)
FundersOak Ridge National LaboratoryWater Power Technologies OfficePacific Northwest National LaboratoryArgonne National LaboratoryUT-BattelleBattelleUniversity of ChicagoU.S. Department of CommerceU.S. Department of Energy
KeywordsEnergy storagePiston (optics)Compressed airVolume (thermodynamics)Head (geology)Petroleum engineeringEnvironmental sciencePumped-storage hydroelectricityEngineeringGas compressorRenewable energyMechanical engineeringGeologyElectrical engineeringPower (physics)Distributed generation

Abstract

fetched live from OpenAlex

review and approval of PSH developments including the United States Army Corps of Engineers (USACE), USBR, and state dam safety agencies.Given the lack of specific regulatory guidance for geomembrane lining systems used in PSH reservoirs, close coordination and interaction with FERC and other regulatory agencies is required.Several main takeaways have emerged from this study:• Geomembrane lining systems are one of several lining systems that can be considered for the impervious lining of PSH reservoirs.Others include DAC and concrete linings, and the selection of one lining system over another must consider a number of factors.• Given the variety of materials and factors that govern the design and construction of a geomembrane lining system, costs for the supply and installation of geomembrane lining systems should be expected to vary considerable from project to project and can be significant cost drivers for a given PSH project.The selection of a geomembrane lining system as the lining system for a PSH project is often based on factors other than costs, and in fact geomembrane systems may be more expensive than other options like DAC or concrete.• The geomembrane used as the primary water barrier is only one part of a comprehensive lining system carefully designed to control seepage from a reservoir.• There are a number of geomembrane materials available in the marketplace, and selection of a particular geomembrane material is subject to a variety of factors.There is not one material that can be considered superior in all respects.• Detailed design of a geomembrane lining system will require involvement of a geomembrane lining manufacturer, and the owner and engineer will need to decide whether to select the manufacturer during preparation of the overall project design or leave final design details and selection of the manufacturer to the contractor.• No PSH-specific design guidelines for geomembrane lining systems could be identified in the literature search conducted for this study.• No PSH-specific regulations on the use of geomembrane lining systems could be identified in the literature search conducted for this study.Topics for further study and investigation include the following:• Expand the assessment of PSH liners to all lining systems (e.g., DAC and concrete).• Perform a market assessment for potential liner applications.• Further engage FERC and other relevant agencies to better understand regulatory guidance for geomembrane lining systems.• Develop a cost model for pricing geomembrane lining system applications for PSH.• Develop a preliminary reference design and cost assessment.vi

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.104
GPT teacher head0.345
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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