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Record W2895863370 · doi:10.18280/mmep.050307

Energy performance of cross-laminated timber panel (X-Lam) buildings: A case study

2018· article· en· W2895863370 on OpenAlexvenueno aff
Francesco Nocera, Antonio Gagliano, Maurizio Detommaso

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2018
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsCross laminated timberStructural engineeringEnergy (signal processing)Architectural engineeringEngineeringMathematicsStatistics

Abstract

fetched live from OpenAlex

To mitigate the impact of climate change, building designers have to mature novel approaches that enable occupants to remain comfortable in the predictable more warming climate, as well as reduce the environmental footprint and emissions intensity of the building fabric.According to Energy Performance of Buildings Directive (EPBD), energy-efficient buildings represents one of the most accredited ways of reducing energy consumptions in the urbanized area as it requires both high-performance components and technical systems.In the last decades, Cross Laminated Timber Panel (X-Lam) buildings become very popular among the designers of passive and nZEB buildings for their earthquake resistance, excellent air tightness and thermal insulation, which allow achieving remarkable energy savings.In this paper the thermal performance and the indoor comfort of a Cross Laminated Timber Panel (CLT) building, have been evaluated.This simulation study was carried out adopting two approaches, steady state and dynamic regime, both in Catania and Bolzano two cities that, even belong in the Mediterranean area, are characterized by different climates.Dynamic numerical simulations were performed on a yearly basis through the software Design Builder, both in free-floating conditions and with an air-conditioning (AC) system.Furthermore, the effect of natural ventilation (N.V.) on the thermal behavior of the CLT building was investigated.The two approaches have provided almost the same energy needs in winter but a significant difference was revealed in summer in both sites.CLT building can lead to indoor overheating of the building in the hottest days of the summer period not only in Catania.Indeed, dynamic simulations in free-floating conditions have highlighted that the X-Lam building fabric suffers even in Bolzano where the operative temperature ranges from 27.2 ° C to 31.8 ° C.Moreover, the adoption of N.V. strategies can improve the indoor thermal conditions reducing maximum value of operative temperature around 1.0 ° C.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.220
Teacher spread0.195 · 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 designObservational
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

Citations7
Published2018
Admission routes1
Has abstractyes

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