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Record W3121842504 · doi:10.5552/crojfe.2021.722

Skyline Tensile Forces in Cable Logging

2021· article· en· W3121842504 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCroatian journal of forest engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsUniversity of British Columbia
FundersU.S. Forest ServiceMitacsUniversità degli Studi di PadovaU.S. Department of Agriculture
KeywordsSkylineUltimate tensile strengthFinite element methodStructural engineeringPayload (computing)Computer scienceMean squared errorLine (geometry)SimulationEngineeringMaterials scienceMathematicsStatisticsData miningComposite materialGeometry

Abstract

fetched live from OpenAlex

Skyline tensile forces have been shown to frequently exceed the recommended safety limits during ordinary cable logging operations. Several models for skyline engineering analyses have been proposed. Although skyline tensile forces assume a dynamic behaviour, practical solutions are based on a static approach without consideration of the dynamic nature of the cable systems.The aim of this study was to compare field data of skyline tensile forces with the static calculations derived by dedicated available software such as SkylineXL. To overcome the limitation of static calculation, this work also aimed to simulate the actual response of the tensile fluctuations measured in the real environment by mean of a finite element model (FEM).Field observations of skyline tensile forces included 103 work cycles, recorded over four different cable lines in standing skyline configuration. Payload estimations, carriages positions, and time study of the logging operations were also collected in the field. The ground profiles and the cable line geometries were analysed using digital elevation models. The field data were then used to simulate the work cycles in SkylineXL. The dynamic response of six fully-suspended loads in a single-span cable line was also simulated by a dedicated FEM built through ANSYS®. The observed data and the software calculations were then compared.SkylineXL resulted particularly reliable in the prediction of the actual tensile forces, with RMSE ranging between 7.5 and 13.5 KN, linked to an average CV(RMSE) of 7.24%. The reliability in predicting the peak tensile forces was lower, reporting CV(RMSE) of 10.12%, but still not likely resulting in a safety or performance problem. If properly set-up and used, thus, SkylineXL could be considered appropriate for operational and practical purposes. This work, however, showed that finite element models could be successfully used for detailed analysis and simulation of the skyline tensile forces, including the dynamic oscillations due to the motion of the carriage and payload along the cable line. Further developments of this technique could also lead to the physical simulation and analysis of the log-to-ground interaction and the investigation of the breakout force during lateral skidding.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.578

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 head0.007
GPT teacher head0.191
Teacher spread0.183 · 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