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Building Facade Failures due to Rainwater Entry in Turkey

2022· article· en· W4311171159 on OpenAlexaff
C Baş, A. N. Türkeri, M A Lacasse

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsRainwater harvestingFacadeCladding (metalworking)Forensic engineeringWater leakageEnvironmental scienceCivil engineeringEngineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Abstract Facade failures due to rainwater entry are common in Turkey although, few systematic studies have been completed to determine the types of defects and failures and their causes as would permit developing appropriate repair solutions. The intent of this study is to determine the types of defects and failures caused by rainwater ingress to building facades based on case studies of failure in Turkey. Thus, defects and failures can be characterized and classified, such that the most common types of failure can be revealed and adequate repair solutions proposed. A review of literature was conducted of studies undertaken in Turkey on rainwater entry and building defects. Additionally, field inspections were carried out for 16 public buildings in Istanbul and information regarding failures was gathered from local authorities. Based on data evaluated from previous research and field inspections, it was determined that majority of the buildings had cladding walls with stucco being the most common cladding material. Failures occurred in cladding facades with stucco included detachment of cladding, staining, and cracks; the most common failure was blistering and exfoliation. Air and rainwater leakage due to defects in sealants was the most common failure in buildings with panel and stick wall systems.

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 categoriesInsufficient payload (model declined to judge)
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 score0.824
Threshold uncertainty score0.996

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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