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Record W2159678940 · doi:10.26077/3xaj-ad02

Powering Small Satellites with Advanced NiH2 Dependent Pressure Vessel (DPV) Batteries

2025· article· en· W2159678940 on OpenAlexaff
Dwight B. Caldwell, Chris L. Fox, Lee E. Miller

Bibliographic record

VenueDigital Commons - USU (Utah State University) · 2025
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsEaglePicher (Canada)
Fundersnot available
KeywordsBattery (electricity)SpacecraftAutomotive engineeringComputer scienceReliability engineeringElectrical engineeringEngineeringAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

The Dependent Pressure Vessel (DPV) nickel-hydrogen (NiH2) design is being developed by Eagle-Picher Industries, Inc. (EPI), as a spacecraft battery for both large and small, military and commercial satellites. The DPV cell design offers high specific energy, energy density and reduced cost, while retaining the established IPV technology flight heritage and database. This advanced design also offers a more efficient mechanical, electrical and thermal cell and battery configuration and a reduced parts count. The geometry of the DPV cell promotes compact, minimum volume packaging and battery weight efficiency. The DPV battery design offers significant cost and weight savings potential while providing minimal design risks. In this presentation, we will discuss design features and present test data from existing development cells and address issues relevant to design and production of a DPV battery suitable for a small satellite application which would retain the energy increases and weight and cost reductions proposed. With the DPV, EPI has combined the unique features and significant advantages of NiH2 electrochemistry with the simplicity and extensive design heritage of the NiCd battery system.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.169
Teacher spread0.163 · 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 designBench or experimental
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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Same venueDigital Commons - USU (Utah State University)Same topicSpacecraft and Cryogenic TechnologiesFrench-language works237,207