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Record W2278122010 · doi:10.14288/1.0095774

Energy analysis of residential structure space conditioned by heat pump and furnace using computer simulation

2010· article· en· W2278122010 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldEngineering
TopicBuilding energy efficiency and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsHeat pumpEnergy (signal processing)Space (punctuation)Environmental scienceMechanical engineeringProcess engineeringEngineeringNuclear engineeringArchitectural engineeringWaste managementComputer scienceMathematicsHeat exchanger

Abstract

fetched live from OpenAlex

An energy simulation program, named RHECAP (Residential Home Energy Consumption Analysis Program), for residential structure space conditioned by a furnace and a heat pump has been developed. The program calculates the hourly cooling or heating load imposed on the furnace or heat pump and then the energy input to the furnace or heat pump to satisfy the load for every hour of every day of a condensed year. The condensed year consists of thirty-six days; a month is represented by three days. The hourly cooling load is determined by using a method designated as "Time-Averaging with Shift". This method has been developed from time-averaging principle and uses a different set of parameters, time-averaging period and shift amount, for different energy sources. Each hourly load of a day is obtained by summing the arithmetic average of the radiant heat gains of a number of preceding hours and the convective heat gain of the current hour. This gives the daily load profile which is then shifted to yield the final load profile. This method accounts for the building heat storage effect in converting instantaneous heat gain to the cooling load. A polynomial equation which expresses the furnace efficiency degradation with the drop of the furnace load has been developed. This equation and the furnace performance at steady state condition are used to represent furnace performance for the entire range of operating conditions. The same equation can be used for furnace units of all different capacities. Six linear equations that represent the non-dimensionalized heat pump performance, the output rating (heating and sensible cooling) and electricity use, have been developed. The equations are functions of the outdoor enthalpy. These equations only require the heat pump performance at the outdoor temperature of 35°C (tonnage of heat pump is quoted under this condition) to represent the heat pump performance for the entire range of outdoor operating conditions. The six equations can be used for heat pumps of different capacities from different manufacturers. A simple method of selecting a yearly condensed weather data has been developed. The condensed weather data consists of three days of actual weather information for each month. The weather information is used to determine the cooling and heating load contributions of weather dependent sources and heat pump performance. The program results are compared with the results of two existing programs using an existing and a fictitious residential structure in Vancouver to validate the program. The validation of the program seems to indicated that the program provides acceptable results and the simulation methods used are valid.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.959

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 head0.003
GPT teacher head0.166
Teacher spread0.163 · 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