Analytical and Numerical Simulations to Observe the Seawater Cooling Phenomena Through a Single Rectangular Plate-Fin
Bibliographic record
Abstract
This paper describes several simulations of the seawater cooling phenomenon using a theoretical approach based on analytical method, numerical method of Euler’s and Runge-Kutta of fourth-order (RK4). These research objectives, i.e. to get the energy balance equations, to use the solution equations, and to do the simulation processes. The methods used, i.e. (i) do the completion of mathematical equations to get the constants for energy balance based on the ordinary differential equations (ODEs), (ii) do the made of solving equations for simulation, and (iii) does the simulation processes assisted by a spreadsheet application and result in analysis. The results are in the form of (a) the constants for energy balance, i.e. b1 is 0.9134∙10-3 sec-1 and b2 is 0.31∙10-6 sec-1, (b) produced three solving equations for the simulation, and (c) obtained curves of the temperature changes. The results of the simulation processes based on a spreadsheet application have obtained the results, that the time span 1800 seconds (30 minutes) can cause changes in the temperature of the fluid from 25℃ to (i) 4.823770℃ with a rate of change of 0.092%, if used of the analytical method; (ii) 4.819088℃ with a rate of change of 0.092%, if used the numerical method of Euler’s; and (iii) 5.600404℃ with a rate of change of 0.083%, if used the numerical method of RK4’s. The conclusion in this paper, that all the curves of changes in the temperature of the fluid are the non-linear curves. Even though the final value of temperature is the highest, but the RK4 more thoroughly. Suggestions for future work, that the simulation of its phenomena must be begun with making the mathematical models with the analytical and/or numerical method and implemented them into the computer application.
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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 | 0.000 |
| 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) | 0.002 | 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".