Critical lifting simulation of heavy industrial construction in gaming environment
Why this work is in the frame
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Bibliographic record
Abstract
Purpose Heavy industrial construction often relies on large mobile cranes to erect equipment and pre-assembled modules. Engineering calculations are required for the lifting analysis where lifting capacity is analyzed to ensure the feasibility of the lifting scenarios. Such engineering calculations are often presented in static formats, e.g. two-dimensional or three-dimensional models. However, it is difficult to help practitioners (e.g. lifting engineers, site crews and operators) understand the complexity of the lifting process and thus operational decisions are often made intuitively. Therefore, this paper aims to introduce a game-based simulation system to allow for interactive analysis of the lifting process to improve lifting efficiency and safety. Design/methodology/approach The proposed method treats the mobile crane as a robot with degree-of-freedoms, and the movements are simulated in the Unity game environment. The lifting capacity is calculated dynamically based on the lifting object weight, rigging weight and lifting radius. Findings Compared with the four-dimensional visualization, this development has added a dimension of real-time interactive simulation; this allows the users to understand the complexity and feasibility of the lifting process. Originality/value The developed prototype has been tested and validated using a real case study from a heavy industrial project with the possibility of generalizing crane lifting configurations.
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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 | 0.000 |
| 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 it