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Record W4384695034 · doi:10.22215/etd/2023-15517

Building Integrated Sub-Slab Thermal Storage System for Coupling to a Heat Pump: Modelling, Optimization, and Thermal Performance

2023· dissertation· en· W4384695034 on OpenAlexaffabout
Luminita Dumitrascu

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsHeat pumpRetrofittingThermal energy storageHeat exchangerTRNSYSContext (archaeology)Renewable energyZero-energy buildingHeating systemEngineeringEnvironmental scienceEfficient energy useCivil engineeringThermalMechanical engineeringMeteorologyStructural engineering

Abstract

fetched live from OpenAlex

Canada, like most countries around the world, has adopted targets for reducing the greenhouse gas emissions associated with the built environment.In addition to reducing greenhouse gas emissions, goals for improving the resilience to climate change, and making buildings energy-wise, more comfortable, and more affordable, were adopted as well.In this context, low energy, and net zero energy buildings are becoming a target in the research field, through the incorporation of renewable energy systems and thermal energy storage among others.The greenhouse gas emissions associated with the energy use in buildings can be significantly reduced by taking an integrated approach for heating, cooling, ventilation, dehumidification, and domestic hot water heating when designing new buildings, or retrofitting existing ones.The research investigates the performance of a sub-slab ground heat exchanger, coupled to a heat pump system, and the ability of the system to provide space conditioning and domestic hot water heating for a low-rise multi-unit residential building.The thermal performance of the system was assessed through simulation for a multi-unit residential construction in Ottawa.Simulations using weather files for other five locations in different climate zones across Canada were conducted as well, to assess the suitability of the system to other climate conditions.Parametric analyses were conducted to optimize both the design of the building and of the ground heat exchanger.Appropriate control strategies were investigated also to optimize the energy consumption of the heat pump and the auxiliary equipment.According to the simulated results, the ground layer can store energy over the medium term, without reducing the long-term performance of the heat pump.The system is able also to fully meet the space conditioning and domestic hot water heating needs of the building.The annual electricity consumption of the heat pump was estimated to be 11.4 GJ per dwelling unit.Adding the energy use associated with lights and appliances, and all the auxiliary equipment, the total energy consumption of a dwelling unit was 29.8 GJ.Considering the average annual energy consumption of a dwelling unit in low-rise multi-unit residential building as 46.7 GJ, the investigated system can achieve approximately 40% reduction of the energy use.The last two chapters present some of the conclusions derived after conducting this work, and some recommendations for new directions that can be further explored.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.239
Teacher spread0.223 · 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 designSimulation or modeling
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
Published2023
Admission routes2
Has abstractyes

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