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Record W4241669002 · doi:10.32920/ryerson.14655300.v1

Validation of wind-driven rain module for HAM-tools

2021· preprint· en· W4241669002 on OpenAlexaff
Sam Siassi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsASHRAE 90.1SoftwareComputer scienceField (mathematics)Process (computing)Environmental scienceMeteorologySimulationMathematics

Abstract

fetched live from OpenAlex

This study is a continuation of previous research carried out to improve the hygrothermal analysis capabilities of the readily available HAM-Tools building simulation software. Previous study intended to improve the program by adding a wind driven rain (WDR) module using the semi-empirical model from ASHRAE 160P. However, further verification of the model was needed. In this study, the WDR module’s verification process was corrected and compared to WUFI simulation. The module was then validated by comparing its results with field measurements. The results indicated that the newly designed HAM-Tools WDR module have good agreement with field measurements. HAM-Tools with added WDR module is then used to study the hygrothermal responses of wood-frame wall with WDR amount calculated using different averaging techniques of high resolution meteorological data. It was concluded that in climates with high rainfall, it is best to use high resolution data (at least 10 minutes) for hygrothermal simulations.

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.246
Teacher spread0.208 · 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
GenreMethods

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
Published2021
Admission routes1
Has abstractyes

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Same topicHygrothermal properties of building materialsFrench-language works237,207