Numerical Evaluation of the Hydrothermal Process in a Water-Surrounded Heater of Natural Gas Pressure Reduction Plants
Bibliographic record
Abstract
The gas pressure in the main network of transmission lines is about 700 to 1000 psi (4826.33 to 6894.76 kPa), which is reduced to 250 psi (1723.69 kPa) at the entrance station of a city. This reduction process, which occurs in the regulator, causes a severe drop in gas temperature. The drop in the gas temperature produces hydrates and even causes the water vapor in the gas to freeze. As a result, there is a possibility that the passage of gas in the regulator is blocked and the gas flow is cut off. By employing heaters (indirect water heaters), the temperature of the gas entering the regulator can be preheated to eliminate the possibility of freezing in the regulator. This heater is fueled with natural gas and it operates for 24 hr a day, especially in the cold seasons. Therefore, one of the main challenges in using this type of heater is its high fuel consumption. Consequently, researchers are looking for a solution to reduce the fuel consumption (natural gas) of gas heaters. In this paper, the heat transfer and fluid flow in a heater of a natural gas pressure reduction plant, the Aliabad Power Plant (Iran), are numerically investigated using a commercial Computational Fluid Dynamics (CFD) code, ANSYS FLUENT 18.2. The considered heater consists of three parts, including (i) gas coils, (ii) a water bath (shell), and (iii) a fire tube. The indirect heat transfer process takes place between the hot liquid flow in the fire tube (combustion exhaust) and the cold liquid flow (natural gas) using the natural convection flows generated in the water bath. Numeric modeling is performed for four different gas mass flows, including 6 × 104, 8 × 104, 1 × 105, and 12 × 105 standard cubic meters per hour (or 16.67, 22.22, 27.78, and 33.33 m3/s). The results indicate that the natural gas outlet temperature achieved to a temperature higher than required. By installing a regulator on the burner, the gas consumption can be reduced, resulting in station cost savings, and also reducing the environmental impacts. The outcomes depict that the maximum possible reductions in monthly gas consumption and economic savings in the proposed system are 67,500 m3 and IRR 25 million at a gas mass flow rate of 60,000 SCMH.
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 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".