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Record W1974368542 · doi:10.1139/l2012-016

A new performance based design approach for moment resisting frames

2012· article· en· W1974368542 on OpenAlexvenueno aff
Mark Grigorian, Carl E. Grigorian

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsStructural engineeringHingeStaticsMoment (physics)StiffnessMorphingStatically indeterminateStructural systemComputer scienceEngineering

Abstract

fetched live from OpenAlex

This paper proposes a simple, relatively new elastic–plastic design method for earthquake resisting frames that enables the engineer to directly control the essential aspects of the future behavior of certain structural forms, through basic statics and imposition of predetermined modes of behavior. The method is particularly applicable to the preliminary design of low to mid-rise buildings where the fundamental period of vibrations dominates the response of the system to seismic loading. The focus of this paper is directed towards simplified but accurate manual design rather than sophisticated structural analysis. The premise of the proposed solution is that the constituent elements of the system can be selected in such a way as to cause both the elastic as well as the plastic drift functions to follow linearly varying straight line profiles during all phases of loading. Frameworks designed by this method act not only as structures of uniform response (UR), i.e., uniform strength and stiffness, where the demand/capacity ratios of its members remain the same, both before and after formation of plastic hinges, but they also result in unique solutions, satisfying the prescribed yield criteria, the boundary support, as well as the of static equilibrium conditions.

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)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.624

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 head0.017
GPT teacher head0.184
Teacher spread0.167 · 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
GenreMethods

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

Citations14
Published2012
Admission routes1
Has abstractyes

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