Bibliographic record
Abstract
Steady state computations have traditionally been used for liquid pipeline hydraulic design. The hydraulic behavior of multiproduct pipelines is more complex than single-product lines because the throughput varies with time as the different batches move through the system. Designing a multiproduct pipeline involves hydraulic simulation to ensure that the system can meet a specified time-average throughput for the design batch line-up. To calculate the time-averaged throughput, the hydraulic simulation determines the total time it takes to ship the complete design batch cycle and the methodology must account for the time-varying throughput of the pipeline. Two basic methods available to accomplish this are: the fully-transient method, and the simpler succession-of-steady-state method. A fully-transient model would rigorously solve the time-dependent equations of energy, mass and momentum conservation to determine operating capacity. A succession-of-steady-state (SSS) model is one where batches are moved through the system in small volume increments, and the steady-state capacity is calculated at each step. Fully-transient type software models are powerful, but expensive, complex and usually require lengthy simulation run times. An SSS spreadsheet model would not be used to evaluate transient phenomena, but is adequate for determination of nominal pipeline capacities. This paper discusses the development of a trans-thermal, SSS spreadsheet based model that was created as a design tool to determine pipeline capacity and evaluate the impact of design alternatives or changes.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".