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Record W4283579108 · doi:10.3390/en15134677

Construction and Calibration of a Unique Hot Box Apparatus

2022· article· en· W4283579108 on OpenAlexaff
Abdalhadi Alhawari, Phalguni Mukhopadhyaya

Bibliographic record

VenueEnergies · 2022
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCalibrationWorkmanshipEnvelope (radar)Point (geometry)ThermalMechanical engineeringBuilding envelopeComputer scienceEnvironmental scienceEngineeringAerospace engineeringPhysicsMathematics

Abstract

fetched live from OpenAlex

A variety of mathematical models are available to estimate the thermal performance of buildings. Nevertheless, mathematical models predict the thermal performance of buildings that might differ from the actual performance. The hot box is a widely-used test apparatus to assess the actual thermal performance of various building envelope components (walls, roofs, windows) in the laboratory. This paper presents the process of designing, constructing, and calibrating a unique small-scale hot box apparatus. Despite its smaller metering area (1.0 m × 1.0 m), this apparatus met the key requirements (below ±0.25 °C fluctuations in chambers’ air temperature, and below 2.0% variation from the point-to-point temperature in reference to the temperature difference across the specimen) as prescribed in the ASTM C1363 and ISO 8990 standards. The walls of this apparatus are uniquely constructed using vacuum insulation panels or VIPs. The efficient and novel use of VIPs and workmanship during the construction of the apparatus are demonstrated through the temperature stability within the chambers. The achieved range of temperature steadiness below ±0.05 °C and point-to-point temperature variation below 1.0% of the temperature difference across the specimen allow for this apparatus to be considered unique among the calibrated hot box categories reported in the literature. In addition, having an affordable, simple-to-operate, and high-accuracy facility offers a great opportunity for researchers and practitioners to investigate new ideas and solutions. The apparatus was calibrated using two extruded polystyrene foam (XPS) specimens with thicknesses of 2″ and 4″. The calibration exercise indicates small differences between results obtained numerically, theoretically, and experimentally (below 3.0%). Ultimately, the apparatus was employed to measure the thermal properties of a specimen representing a lightweight steel framing (LSF) wall system, which is commonly used in cold climates. The results obtained experimentally were then compared to the ones estimated numerically using a 3D finite element modelling tool. The difference between the results obtained by both methods was below 9.0%.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.168

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 head0.005
GPT teacher head0.171
Teacher spread0.167 · 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 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

Citations15
Published2022
Admission routes1
Has abstractyes

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