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Record W3203543550 · doi:10.4081/jae.2021.1185

Energy efficiency of a hybrid cable yarding system: A case study in the North-Eastern Italian Alps under real working conditions

2021· article· en· W3203543550 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.

Bibliographic record

VenueJournal of Agricultural Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAutomotive engineeringEnergy consumptionEngineeringWinchFuel efficiencyGreenhouse gasEnvironmental sciencePropulsionEfficient energy useWork (physics)Electrical engineeringMarine engineeringMechanical engineeringEcology

Abstract

fetched live from OpenAlex

In order to reduce greenhouse gas emissions, low emission or zero-emission technologies have been applied to light and heavyduty vehicles by adopting electric propulsion systems and battery energy storage. Hybrid cable yarders and electrical slack-pulling carriages could represent an opportunity to increase the energy efficiency of forestry operations leading to lower impact timber harvesting and economic savings thanks to reduced fuel consumption. However, given the limited experience with hybrid-electric systems applied to cable yarding operations, these assumptions remain uncertain. This study assessed an uphill cable yarding operation using a hybrid cable yarder and an active slack-pulling electric power carriage over thirty working days. A total of 915 work cycles on four different cable lines were analysed. Longterm monitoring using Can-BUS data and direct field observations were used to evaluate the total energy efficiency, total energy efficiency (%), and fuel consumption per unit of timber extracted (L/m3). The use of the electric-hybrid system with a 700 V supercapacitor to store the recovered energy made it possible to reduce the running time of the engine by about 38% of the total working time. However, only 35% to 41% of the Diesel-based mechanical energy was consumed by the mainline and haulback winches. Indeed, the remaining energy was consumed by the other winches of the cable line system (skyline, strawline winches and carriage recharging or breaking during outhaul) or dissipated by the system (e.g., by the haulback blocks). With reference to all work cycles, the highest net energy consumption occurred during the inhaulunload work element with a maximum of 1.15 kWh, consuming 70% of total net energy consumption to complete a work cycle. In contrast, lower energy consumption was recorded for lateral skid and outhaul, recording a maximum of 23% and 32% of the total net energy consumption, respectively. The estimated recovered energy, on average between the four cable lines, was 2.56 kWh. Therefore, the reduced fuel need was assessed to be approximately 730 L of fuel in the 212.5 PMH15 of observation, for a total emissions reduction of 1907 kg CO2 eq, 2.08 kg CO2 eq for each work cycle.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.203
Teacher spread0.191 · 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