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Record W2942344501

Performance of a district heating substation in low temperature district heating

2019· dissertation· en· W2942344501 on OpenAlexaboutno aff
Hilla Kinnunen

Bibliographic record

VenueLUTPub (LUT University) · 2019
Typedissertation
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceNuclear engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

The object of this study was to examine, what is the performance of the district heating substation in low temperature district heating. One of the Alfa Laval’s plate heat exchanger was studied with Anytime-program. Supply and return temperatures and flow rates were changed. The aim of the study was to examine, if it is possible to use a heat exchanger, that is sized based on today’s sizing parameters, in low temperature district heating and how to control the substation. \nThe outcome was, that it is not possible to only change the district heating supply temperature without changing the control methods of the substation. When the secondary side return temperature was decreased by lowering the flow rate and regulating the supply temperature according the control curve, it was possible to lower the district heating supply temperature by 10 °C, whit out too high return temperature in primary side. The secondary flow rate can be adjusted by lowering the pumps rotational speed. By lowering the secondary flow rate, it is possible to decrease the district heating supply temperature.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.003
GPT teacher head0.162
Teacher spread0.158 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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