MétaCan
Menu
Back to cohort

Evaluating Water-Based Trombe Walls as a Source of Heated Water for Building Applications

2023· book-chapter· en· W4377995640 on OpenAlexaboutno aff
Harmeet Singh, Fatemeh Massah, Paul G. O’Brien

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicSolar Energy Systems and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsFlexibility (engineering)Thermal energy storageEnvironmental scienceThermalWater heaterWork (physics)Water heatingEngineeringMeteorologyWaste managementMechanical engineeringGeographyMathematics

Abstract

fetched live from OpenAlex

Abstract In this chapter the potential to use water-based Trombe walls to provide heated water for building applications during the summer months is investigated. Design Builder software is used to model a simple single-story building with a south-facing Trombe wall. The effects of using different thermal storage mediums within the Trombe wall on building heating loads during the winter and building cooling loads during the summer are modeled. The amount of thermal energy stored and temperature of water within the thermal storage medium during hot weather conditions were also simulated. On a sunny day on Toronto, Canada, the average temperature of the water in a Trombe wall integrated into a single-story building can reach ∼57°C, which is high enough to provide for the main hot water usages in buildings. Furthermore, the amount of water heated is three times greater than that required in an average household in Canada. The results from this work suggest that water-based Trombe walls have great potential to enhance the flexibility and utility of Trombe walls by providing heated water for building applications during summer months, without compromising performance during winter months.

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 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)0.000
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: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.659
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.045
GPT teacher head0.282
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicSolar Energy Systems and TechnologiesFrench-language works237,207