Multiproduct Pipe Transport Conversion of Abandoned Single Product Pipelines
Bibliographic record
Abstract
Abstract This paper explores the potential of utilizing large diameter steel pipelines, that are no longer in use, to simultaneously transport small batches of different products. These pipelines were originally created in the United States to transport gas from the south to the north. As Canada emerged as a gas supplier to the northern states, these pipelines were no longer needed for their original purpose. Many of these pipelines were completely abandoned because an alternate usage was not identified for transporting large quantities of a single product. With these pipelines obsolete, building new smaller diameter pipelines was the only solution considered to accommodate the present need. To accomplish the necessity of economically transporting small batches of product, multiple pipes are inserted into these large diameter steel pipelines. Polyethylene (PE) was selected as the piping material for this application because of the flexibility and tensile strength required during the insertion process. A method was developed to insert 10-mile sections of the PE pipes into the steel pipeline. Once these PE pipes are installed, a method of controlling and monitoring the flow is required. The control system allows the outputs to be maximized without causing failures such as bursting or leaking. Furthermore, to assure economical feasibility, performance benchmarks were proposed by industrial partners. The model produced from this study analyzes steady state operation as well as transient effects such as opening/closing a valve or starting/stopping the pipeline. New formulas are derived to calculate frictional pressure drop for fluid flow in pipes containing internal pipes. National Instruments Lab-View, a graphical programming language, was used to transform the mathematical model into a real-time operational tool that can be directly connected to the pipeline system.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".