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Record W7030406621

Modelling of soil-tool interactions using the discrete element method (DEM)

2016· dissertation· en· W7030406621 on OpenAlexafffund

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typedissertation
Languageen
FieldEngineering
TopicSoil Mechanics and Vehicle Dynamics
Canadian institutionsUniversity of Manitoba
FundersMitacs
KeywordsApproximation errorDiscrete element methodFlow (mathematics)Variable (mathematics)Finite element methodParticle (ecology)HullObservational error
DOInot available

Abstract

fetched live from OpenAlex

Soil disturbance and cutting force are two of the most common performance indicators for soil-engaging tools. In this study the interaction of two soil-engaging tools (a disc opener for fertilizer banding and a hoe opener from an air drill) with soil were modeled using Particle Flow Code in Three Dimensions (PFC3D), a discrete element modeling software. When comparing the disc model to the experiment results, the relative error was 11% for the average soil throw, 1.9% for the average draft force, and 51% for the average vertical force. Results from the soil-hoe model showed a relative error of 15% between the simulated soil throw and the measured one. In conclusion, both the soil-disc and soil-hoe models could simulate the selected soil dynamic properties (except for the vertical forces of the disc opener) with a reasonably good accuracy, considering the highly variable nature of the soil.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.240
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueMspace (University of Manitoba)Same topicSoil Mechanics and Vehicle DynamicsFrench-language works237,207