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Record W7027961415

ENERGY BASED SEISMIC DESIGN OF A TIMBER CORE-WALL MULTI-STOREY HYBRID BUILDING

2017· article· en· W7027961415 on OpenAlexaboutno aff

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2017
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionWork (physics)LimitingField (mathematics)Frame (networking)
DOInot available

Abstract

fetched live from OpenAlex

Current earthquake design philosophy in North America recommends an equivalent static force procedure (ESFP). Much research lately has been in new performance based methodologies including direct displacement based design (DDBD) and energy-based design (EBD). Research in energy-based design has not had the attention of DDBD yet now is gaining in popularity because of the methods reliance on the velocity spectrum and duration of earthquake hazard. This paper discusses an energy based methodology in designing a novel multi-storey hybrid building consisting of a timber-steel core wall system. This hybrid system combines Cross Laminated Timber (CLT) panels with steel plates and connections to provide the required strength and ductility to core walled buildings. To improve the applicability of the hybrid system an EBD methodology is proposed to design the core-walled building. The methodology is proposed as it does not rely on empirical formulas and force modification factors to determine the final design of the structure. In order to assess the feasibility of the EBD method, it is implemented in the design of a 7-storey building based off an already built concrete benchmark building. The design is first carried out following the ESFP outlined by the National Building Code of Canada for Vancouver, BC. Nonlinear time history analysis is carried out on the ESFP design and the proposed EBD methodology using 10 ground motions selected at 2% in 50 years return period, to evaluate the suitability of the method and the results of the ESFP and EBD methodologies are discussed and compared.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.066
GPT teacher head0.296
Teacher spread0.230 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueIRIS Research product catalog (Sapienza University of Rome)Same topicSeismic Performance and AnalysisFrench-language works237,207