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Methods for Estimating Pipe Pullback Loads for Horizontal Directional Drilling (HDD) Crossings

2002· article· en· W2161415091 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Infrastructure Systems · 2002
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsWestern University
Fundersnot available
KeywordsDirectional drillingPullbackPetroleum engineeringMarine engineeringGeologyEngineeringDrillingComputer scienceMathematical optimizationMathematicsMechanical engineeringGeometry

Abstract

fetched live from OpenAlex

This paper reviews and evaluates three current design practices for calculating tensile loading during the installation of steel and polyethylene pipe using horizontal directional drilling (HDD). A sensitivity analysis of the three models revealed that while the relative influence of the various parameters is a function of the length of pipe within the bore, the predicted pulling load is very sensitive to mud weight and mud drag. This observed sensitivity is not supported by recent published test data. The three design approaches were used to model two recent HDD installations—one a 400-m double crossing of the Grand River, Brantford, Ontario, and the second a 350-m double crossing of the North Saskatchewan River, Edmonton, Alberta. Poor agreement was observed between the model predictions and the field recorded data, both in terms of the trends of the installation loads and the maximum predicted pull head load. It is suggested that additional research is needed to develop a model that better captures the physical reality in the borehole during an HDD installation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.491
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.269
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it