Real-Time Monitoring for Quality Delivery of Directional Drilling Installations
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 presents an overview of quality management theory and its application in the area of trenchless technology in general, and horizontal directional drilling (HDD) in particular. Current practices that support quality management in the HDD industry are described and are classified using the relevant clauses of ISO 9000. The development of load cell technology aimed at enhancing the quality control/quality assurance (QC/QA) of HDD is then described. Based on load cell data collected during 20 commercial installations, electronic records of installation loads are demonstrated to be a powerful tool for implementing QC/QA programs. The records provide installation rates, the average pull load per unit length of pipe, the maximum load exerted on the pipe, as well as the entire load history of the installation. Radio transmitting capability provides real-time load cell data that can be used to adjust drilling practices to match the level of installation effort to the parameters of the given installation, thereby maximizing productivity. Load cell data are expected to benefit owners, contractors, and consulting engineers.
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