MétaCan
Menu
Back to cohort
Record W4389366763 · doi:10.1080/19236026.2023.2266351

CanmetMINING diesel and BEV field test series: MacLean Engineering diesel and battery electric cassette truck

2023· article· en· W4389366763 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCIM Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsDoug Bragg Enterprises (Canada)Natural Resources Canada
Fundersnot available
KeywordsTruckAutomotive engineeringDiesel fuelBattery (electricity)Fuel efficiencyEnvironmental scienceDriving cycleFossil fuelInternal combustion engineEngineeringRange (aeronautics)Electric vehicleWaste managementPower (physics)Aerospace engineering

Abstract

fetched live from OpenAlex

In light of Canada’s goal of achieving net-zero emissions by 2050 and conditions in increasingly deeper mines, the trend in Canadian mines is to move away from conventional internal combustion engine vehicles and toward battery electric vehicles (BEVs). However, the limited driving range and the longer time required to recharge a battery than refuel a tank could reduce BEV availability and negatively affect production targets. Understanding the differences between these two technologies is critical when designing a new mine or transforming an existing fossil fuel-based fleet into an electric fleet. Thus, the primary objective of this study was to compare diesel cassette trucks (DCTs) and electric cassette trucks (ECTs) in terms of net fuel and energy consumption, respectively. MacLean Engineering heavy-duty DCTs and ECTs were field-tested at Vale’s North Mine surface ramp at 5 and 15 km/h and loaded with the same weight. The controlled 2.5-km test route comprised 10 sections of 0, 5, 10, and 20% uphill and downhill inclination grades. This paper compares DCT and ECT performance in terms of ability to maintain the target speed under different operational conditions and fuel and energy consumption. The energy captured through regenerative braking and charging information was also evaluated for the ECT. An energy to fuel ratio (kWh/L) was calculated for various operating conditions. Furthermore, the data were used in a hypothetical duty cycle to estimate DCT and ECT availability within a work shift.

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.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.234
Teacher spread0.223 · 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