Simulation of ground bearing pressure profile under hydraulic crane outrigger mats for the verification of 16-point combined loading
Bibliographic record
Abstract
The modular construction approach relies heavily on mobile cranes. With the increase in weight of modules, the ground bearing pressure (GBP) applied by the hydraulic crane also increases. To avoid ground failure, the primary technique is to determine the GBP by calculating the resulting force at each outrigger and assuming it is distributed uniformly over the surface area of the mat under the outrigger. Finite element analysis (FEA) indicates that the pressure profile beneath the crane mat is not uniform in nature, which means the traditional method of calculating the GBP is inaccurate. In this study, a new method is proposed to determine the GBP profile. The proposed methodology can determine the GBP at 16 points, the four corners of each of the four outriggers. For a theoretical case study, a hydraulic crane Grove GMK 7550 with three different payloads is examined and the results are verified by using FEA.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".