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Record W4404672196 · doi:10.3390/acoustics6040056

A Design Methodology Incorporating a Sound Insulation Prediction Model, Life Cycle Assessment (LCA), and Thermal Insulation: A Comparative Study of Various Cross-Laminated Timber (CLT) and Ribbed CLT-Based Floor Assemblies

2024· article· en· W4404672196 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAcoustics · 2024
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsUniversité LavalUniversité du Québec à Chicoutimi
FundersNatural Resources CanadaAlberta InnovatesNatural Sciences and Engineering Research Council of CanadaMinistère des Ressources Naturelles et de la FauneFPInnovations
KeywordsCross laminated timberSoundproofingLife-cycle assessmentThermal insulationStructural engineeringEngineeringEnvironmental scienceMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Mass timber is increasingly being employed in constructing low- and mid-rise buildings. One of the primary reasons for using mass timber structures is their sustainability and ability to reduce environmental consequences in the building sector. One criticism of these structures is their lower subjective sound insulation quality. Therefore, acoustic treatments should be considered. However, acoustic solutions do not necessarily contribute to lower environmental impacts or improved thermal insulation performance. This paper discusses a design methodology that incorporates the development of a sound insulation prediction tool (using an artificial neural networks approach), life cycle assessment analysis, and thermal insulation study. A total of 112 sound insulation measurements (in one-third octave bands from 50 to 5000 Hz) are utilized to develop the network model and are also used for the LCA and thermal insulation study. They are lab-based measurements and are performed on 45 various CLT- and ribbed CLT-based assemblies. The acoustic model demonstrates satisfactory results with 1 dB differences in the prediction of airborne and impact sound indices (Rw and Ln,w). An acoustic sensitivity study and a statistical analysis are then conducted to validate the model’s results. Additionally, an LCA analysis is performed on the floor assemblies to calculate their environmental footprints. LCA categories are plotted against the acoustic performance of floors. No correlations are found, and the results emphasize that a wide range of sound insulation can be achieved with similar environmental impacts. Within each acoustic performance tier, the LCA results can be optimized for a floor assembly by selecting appropriate materials. The thermal insulation of floors is then calculated. Overall, a strong positive correlation is found between the total thermal resistance and heat loss against acoustic performance. Designers should be cognizant of the trade-offs between acoustic, thermal insulation, and environmental performance when choosing assemblies with favorable environmental impacts relative to acoustic and thermal insulation ratios.

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)0.001
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 score0.376
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.086
GPT teacher head0.334
Teacher spread0.249 · 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