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Record W3196011757 · doi:10.1007/s10518-021-01202-0

Shake-table response simulation of a URM building specimen using discrete micro-models with varying degrees of detail

2021· article· en· W3196011757 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.

Bibliographic record

VenueBulletin of Earthquake Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsMcGill University
FundersLaboratório Nacional de Engenharia CivilUniversità degli Studi di PaviaCentro Europeo di Formazione e Ricerca in Ingegneria Sismica
KeywordsEarthquake shaking tableUnreinforced masonry buildingMasonryScale (ratio)Computer scienceStructural engineeringShakeFunction (biology)EngineeringMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Abstract Recent technological advances have enabled earthquake engineering researchers to develop numerical models of increasing complexity, capable of duly reproducing even the smallest structural detail. In the case of unreinforced masonry (URM) structures, however, because of their discrete and heterogeneous nature, computational performance tends to decrease exponentially as a function of the adopted refinement level, thus confining the applicability of advanced micro-models, according to which each masonry unit is typically modelled separately, to reduced-scale problems. To enable their use at a building scale, and benefit from considering simultaneously out-of-plane failures, local wall-diaphragm interaction and collapses, researchers often need to decrease the level of detail of specific members or sub-structures. In the current literature, however, the influence of the abovementioned simplifications on the quality of micro-modelling predictions has been only marginally investigated so far, while code-based guidelines are missing. To start addressing such knowledge gap, the dynamic response of a shake-table-tested full-scale URM building specimen has been simulated in this work using a very detailed micro-model, and the results obtained were then compared with those of nominally identical models in which, however, the idealisation of some specific structural elements has been purposely simplified. Aimed at further extending the impact of this study, pushover analyses were also performed using the same models. Preliminary outcomes, which may serve as a reference to develop more informed, effective and targeted multi-scale micro-modelling strategies in the future, indicate that: (i) maximum base shear predictions tend to be less impacted by the introduction of modelling simplifications, (ii) despite requiring more labour, the explicit representation of the brickwork pattern generally led to better results in terms of predicted damage propagation, failure mechanisms and displacement capacity, (iii) using equivalent membranes, as opposed to modelling each component of timber diaphragms, provided acceptable results, making it a plausible alternative for practical applications of micro-modelling approaches.

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)0.000
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 score0.110
Threshold uncertainty score0.923

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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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