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Record W7026489604

Aerial Lift Platform Design for Engine Testing Service

2013· report· en· W7026489604 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2013
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsLift (data mining)Work (physics)CounterweightContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

The ALPS (Aerial Lift Platform Specialists) were tasked with designing an aerial lift platform for the GLACIER facility in Thompson, Manitoba. This project consisted of three major phases: project definition, concept design, and final design. The first major project phase required identifying the problem statement and project objectives, and outlining the target specifications. We identified the constraints and limitations associated with designing an aerial lift platform (ALP) for use at the GLACIER facility, and outlined a project schedule. The second project phase was concept focused, and involved a great deal of research. We investigated all aspects of the required design, and identified current market solutions for the specific areas of design associated with our concepts, such as platform design, lifting mechanisms, and steering geometries. Employing the use of concept screening and scoring matrices, our team filtered a preliminary list of 62 concepts, spanning the eight functional categories of design, down to 23 suitable designs. Moving into the final project phase, we began final concept design, focusing on each of the eight functional design categories individually, and combining these optimized groups into one coherent final design. The GLACIER facility is in need of an ALP capable of meeting their size requirements. In order to meet facility requirements, a suitable lift must have a working surface area large enough to allow for access to all components of the engine while performing maintenance, troubleshooting, and sensor connection. The approximate size required for such a lift is 20’x20’. These restrictions result in increased costs associated with engine testing, longer turn-­?time, and reduced efficiency. The aerial lift platform we developed resembles that of a traditional scissor lift platform. Four wheels situated at the corners of the base platform consist of 28-­16-­22 MH20 solid rubber tires mounted on custom 22” diameter steel rims, with one set of wheels pivoting freely to give provision for steering of the platform. Wheels spindles re mounted high to allow for larger diameter wheels, while the base frame is built low to the ground in order to minimize the retracted height of the platform. Four sets of scissors are mounted […]

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.005

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 head0.107
GPT teacher head0.242
Teacher spread0.135 · 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
Published2013
Admission routes1
Has abstractyes

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