Procedure Design for Experiments Towards Modeling of the Cutting Force in Excavation of Bulk Media
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Bibliographic record
Abstract
Procedure Design for Experiments Towards Modeling of the Cutting Force in Excavation of Bulk Media A. Hemami, F. Hassani Pages 111-117 (2003 Proceedings of the 20th ISARC, Eindhoven, Holland, ISBN 978-90-6814-574-8, ISSN 2413-5844) Abstract: The work discussed in this paper concerns automation of excavation or automation of loading particulate media by an excavating machine. Based on the analysis of the process, knowledge of the force of cutting/digging is required for feedback purposes. The lack of a reliable and well established model for the force in question dictates the primary work of the development of such a model. This interaction force is a function of a large number of parameters. Up to 32 parameters have been proposed. In addition to the large number of the parameters an analytical formulation of such a model is less likely possible, as can be seen from the past work. The complexity of the matter, therefore, calls for an empirical formulation, based on the results of experiments that must be carried out. This calls for a huge number of tests. It is important to reduce, as much as possible, the number of experiments to be performed. Also, if the material is categorized in a logical manner, various media can be prepared by mixtures of only a finite number of materials. The objective of the present paper is to define a generic function for the mathematical model and a plan for the tests that must be performed on soil type material. This leads to increased efficiency and helps to reduce duplications and unnecessary work before spending time on experiments. Based on this systematic approach the experiments can be arranged in a logical order, and the results can be later plugged in at their proper places. Keywords: Cutting/digging force, bulk media, model formulation, experiment DOI: https://doi.org/10.22260/ISARC2003/0011 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it