Object-oriented Simulation Model for Earthmoving Operations
Bibliographic record
Abstract
This paper presents a simulation engine, developed to model earthmoving operations. The engine has been designed utilizing object-oriented features, and it represents a main component in a newly developed automated system for selecting a near-optimum fleet configuration. It provides contractors with a vehicle for estimating the time and cost of this class of projects considering different practical scenarios. The system has been implemented in a Microsoft environment to facilitate integration among its components, which have been developed in the same environment. The paper focuses on the modeling aspects of the simulation process using discrete event simulation and object orientation. A numerical example of an actual case is analyzed to validate the developed simulation engine and demonstrate its capabilities. The results are compared to those generated using Caterpillar software (FPC). The engine and FPC recommended the same fleet and their estimated project durations were very close, with a difference less than 8%. Unlike FPC, the developed engine, however, can model and account for uncertainty during the execution of earthmoving operations in a reliable manner.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".