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Record W2802901881 · doi:10.1139/tcsme-2016-0036

A NEW TEST METHOD FOR SHIPPING PALLETS OF SOLAR PRODUCTS

2016· article· en· W2802901881 on OpenAlexvenueno aff
Shu-Tsung Hsu, Yean‐San Long, Teng‐Chun Wu

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2016
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPalletTruckPhotovoltaic systemAutomotive engineeringReliability (semiconductor)Product (mathematics)Reliability engineeringRenewable energyTest (biology)Computer scienceEngineeringEnvironmental scienceMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

The photovoltaic (PV) industry is expanding rapidly to meet the growing renewable-energy demands globally. The failure-rate analysis indicated that a large portion of the accelerated PV module qualification failures were related to the failure of PV cell itself, which was leading to the yield loss of PV products during shipping or transportation. Therefore, the damaged cell (or module) caused by shipping is always one of the serious problems to impact the long-term reliability of PV product. This paper aims to propose a new test method of reliability evaluation for shipping pallet of solar product. The first scenario is the test pallet shipped in fab (e.g., fork-lift truck or hand-pallet truck). The second scenario is the test pallet transported from fab to fab by different vehicle (e.g., truck, train, aircraft, and shipboard). Consequently, detailed results were applied to SEMI Doc. 5431 and released as SEMI PV56-1214 by voting in December 2014. The solar cell/module/system makers and buyers, or any other party interested like package design, can thus have a common document to refer to when desired.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.348
Threshold uncertainty score0.990

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 head0.015
GPT teacher head0.230
Teacher spread0.215 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicPhotovoltaic System Optimization TechniquesFrench-language works237,207