Innovative 3D‐modelling for selecting and locating mobile cranes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper provides an overview of a recently developed system for selecting and locating mobile cranes on construction sites. The proposed system provides direct help on two fronts: cost and time savings, and improved safety arrangements. The system has a number of interesting features: a relational database designed to store the cranes' geometry‐related variables and to present them using powerful graphics; a selection module supported by an algorithm designed to satisfy geometrical requirements and necessary clearances, accounting for site constraints and lift configurations; and 3D animation to facilitate the planning of crane operations. The system provides a near‐optimum selection of crane lift configurations, considering available cranes. This paper focuses mainly on case examples to demonstrate and to illustrate the use and capabilities of the developed system. Two actual cases, featuring different site constraints and lift configurations, are presented. In these cases, cranes were selected and their operations planned using the developed system. The findings of the two cases are discussed and the benefits of the proposed methodology are highlighted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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