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Record W4210768319 · doi:10.3390/en15031141

Investigating the Impact of Plumbing Configuration on Energy Savings for Falling-Film Drain Water Heat Recovery Systems

2022· article· en· W4210768319 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergies · 2022
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTRNSYSHeat exchangerWork (physics)Heat recovery ventilationEnergy recoveryElectricityTransient (computer programming)Environmental scienceEnergy (signal processing)Nuclear engineeringEngineeringProcess engineeringMechanical engineeringComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

Falling-film drain water heat recovery (DWHR) systems are heat exchangers utilized in residential buildings for recovering energy from greywater. A recent publication by the authors contained a validated model that can be used to predict the performance of DWHR heat exchangers under variable flowrates and temperatures, and this work shows the implementation of the model into Transient System Simulation Tool (TRNSYS) software to perform energy simulations. This work aims to show the different plumbing configurations in which DWHR heat exchangers could be installed, and to simulate their performance under various conditions. The results show that plumbing configuration has a significant impact on energy savings expected from DWHR heat exchangers, and maximum savings are achieved in equal-flow configuration. However, other plumbing configurations provide significant savings, and the mains temperature could dictate which configuration provides higher energy savings.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.032
GPT teacher head0.285
Teacher spread0.254 · 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