Parallel Systems and Structural Frames Realignment Planning and Actuation Strategy
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
Parallel structural systems and assemblies are challenging to erect, align and plumb on construction sites due to their complex geometries and current heuristic realignment strategies. Examples of parallel systems include complicated pipe modules and pipe racks in the industrial construction sector. This paper presents a generalized approach analogous to robotics and inverse kinematics for building parallel systems’ realignment planning, introduced using a series approach. In addition to the calculation of a realignment strategy, feasible applications of such a strategy are also investigated in this paper. The framework for realigning parallel systems has two primary steps: (1) as-built status identification by capturing the geometric state of construction assemblies using three-dimensional (3D) imaging theories, and (2) realignment calculation and actuation based on degrees of freedom (DOFs) defined during the development of the kinematics chains of assemblies. A Quasi-Newton-Raphson (QNR) method is employed for solving the kinematics equation of the inverse kinematics analogy. Experimental results show that the developed algorithms are sufficiently accurate to capture any incurred geometrical discrepancies in parallel construction assemblies and proactively calculate and plan for efficient realignment strategies. Generalization of realignment calculation for parallel systems and realignment actuation are the key contributions of this work.
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