A Simulation Based Decision Tool for Transportation of Ready Mixed Concrete
Bibliographic record
Abstract
This paper presents a simulation tool which is applied to ready mixed concrete operations to analyze the utilization and assignment of production and transportation resources. In the developed simulation model, concrete pouring activities are classified into seven main types according to the type of pouring machine and the degree of diculty of poured structure element. Productivity-unit cost charts are generated to aid in decision making process by processing dierent generated outputs, including productivity rates, resources' utilization, unit cost of poured concrete, and system performance measurements. The productivity unit cost charts are used to determine production time, production cost, and resources combinations for a specified distance from a plant. Whereas, the unit cost contours' charts are used to determine the range of best alternative solutions to minimize production time and cost of the available plant resources, according to the transportation distance. A numerical example is presented to demonstrate the developed model and illustrate its essential features. The output results are compared against site orders and the sensitivity analysis tables.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".