Synthesis of stream‐split heat exchanger networks using non‐structural model considering serial equipment in stream branches and submixing of substreams
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This paper proposes a non‐structural model with stream splits, for heat exchanger network (HEN) synthesis, that allows for submixing of substreams within splits and series connection of exchanger units in a substream. In a submix, one substream totally combines with another non‐isothermally, and by allowing this feature, the designer incurs only piping costs, which are significantly low compared to other HEN costs, and benefits from increased possibility of manipulating substream temperatures. An algorithm employing random walk principles and compulsive evolution is applied for HEN optimization. The method's randomness, which enhances its explorative searching power and efficiency, is an attractive property that matches the proposed model. Four case studies from the literature are solved and annual cost savings of $1800, $7769, and $4771/year are achieved for three of them in comparison with published best solutions, attesting to the effectiveness of the proposed model.
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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 it