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Record W2147016612 · doi:10.5539/mas.v6n7p17

Parameterization and Evaluation of Seismic Resistance within the Context of Architectural Design

2012· article· en· W2147016612 on OpenAlexvenueno aff
Tomaž Slak, Vojko Kilar

Bibliographic record

VenueModern Applied Science · 2012
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsEarthquake resistanceArchitectureContext (archaeology)Architectural designSeismic analysisEarthquake engineeringSeismic resistanceCivil engineeringArchitectural engineeringConstruction engineeringComputer scienceEngineeringGeologyStructural engineeringGeography

Abstract

fetched live from OpenAlex

This paper explores and discusses the possible relations between the architecture and seismic resistance of buildings. The first part of the paper stresses the practical importance of earthquake resistance in every building built in earthquake prone areas. Further on it is shown that the earthquake resistance in architectural expression can be dealt in hidden or concealed principles or on the other hand in revealed or emphasized ways. The paper hypothesize that the architectural design, which to a certain level reflects an earthquake threat, might provide a better designs with stronger architectural identity for buildings in earthquake-prone areas. In this context it summarizes the term “earthquake architecture”, which is defined as particular approach to design of buildings in architecture in a way which draws the inspiration from earthquake engineering. Such an approach might be one of the best responses of the architects (in cooperation with structural engineers and earthquake specialists) to the earthquake threats. In the second part of the paper the proposed method for recognition and evaluation of architecture in the context of earthquake resistance is presented. Using this evaluation method, it is possible to classify buildings at several different levels of “earthquake architecture”. Case study of three comparable competition projects is presented as example of using this method to evaluate the architectural design in the context of seismic resistance, and at the same time, to indicate the ways in which architecture can play its role part within earthquake resistant design.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.155

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 head0.026
GPT teacher head0.234
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations5
Published2012
Admission routes1
Has abstractyes

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