Numerical simulation and structure optimization of spiral wound heat exchanger with novel spacing bars
Bibliographic record
Abstract
Abstract Spiral wound heat exchangers are widely used in industrial production for their advantages, such as large heat transfer areas and compact structures. However, their compact design also poses significant difficulties for numerical simulation and experimental research. The spacing bar between tube bundles has an essential impact on the performance of wound tube heat exchangers. This paper presents a new type of spacing bar vertically installed on the core barrel of the spiral wound heat exchanger to enhance the comprehensive heat transfer performance. A numerical model of a new type of wrapped tube heat exchanger has been constructed, which agrees with experimental results. Under the same working conditions, the comprehensive heat transfer performance on the shell side of the spiral wound heat exchanger with new spacing bars is increased by 7.4%–10.5% compared with the traditional structure. On this basis, the influence of the new spacing bar's structural parameters on the heat exchanger's performance was studied, and the empirical correlation between the structural parameters and operating conditions of the new spacing bar and the performance of the heat exchanger was fitted. The research results have guiding significance for the design of spiral wound heat exchangers.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".