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Record W2939869739 · doi:10.29173/mocs46

Addressing the Impact of Industrialized Components on the Cost of Temporary Heating in Cold-climate Regions

2018· article· en· W2939869739 on OpenAlexaffvenueabout
Regina Dias Barkokebas, Béda Barkokébas, Lana Secchi, Mustafa Gül, Yuxiang Chen, Mohamed Al‐Hussein

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2018
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFuel efficiencyScheduleContext (archaeology)Consumption (sociology)Cost estimateEnvironmental scienceBuilding envelopeEnvelope (radar)Environmental economicsEngineeringComputer scienceMeteorologyAutomotive engineeringEconomicsTelecommunicationsGeography

Abstract

fetched live from OpenAlex

In countries with cold climates such as Canada, the cost of providing space heating during the construction phase, also known as temporary heating, results in a significant additional construction cost, which causes budget deviations thus affecting the projectäó»s financial performance. In fact, the estimation of temporary heating is commonly overlooked due to the uncertainties such as weather forecast and the projectäó»s actual onsite schedule. The cost of temporary heating comprises two parts: (1) the cost of equipment rental, and (2) the fuel consumption required to heat a given area when the temperature falls below a certain threshold. The fuel consumption of the equipment is related to the temperature and exposure of the buildingäó»s envelope to the current weather conditions. Thus, the construction of the building envelope is critical to the reduction of fuel consumption and the consequent temporary heating cost of the project. In this context, the research presented in this paper aims to estimate the impacts of temporary heating for various constructive methods, such as the traditional stick-built practice and a few variations of panelized construction (in regard to the insulation used), by developing a simulation model to observe the variation of weather data, construction schedule, and fuel consumption for each scenario. To perform this analysis, a 4-story residential building located in the city of Edmonton, Alberta, Canada, is used as a case study in which the proposed scenarios are compared in order to address the advantages of industrialized components in reducing the cost of temporary heating.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score0.486

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 head0.065
GPT teacher head0.275
Teacher spread0.210 · 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
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
Published2018
Admission routes3
Has abstractyes

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