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Record W7162421431 · doi:10.65521/ijasret.v9i6.1565

Multistoried and Multi Bay Steel Building Frame by Using Seismic Design

2025· article· W7162421431 on OpenAlexaff
Pramod Vishvkarma, Sumit Pahwa

Bibliographic record

VenueInternational Journal of Advance Scientific Research and Engineering Trends · 2025
Typearticle
Language
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsPrairie Improvement Network
Fundersnot available
KeywordsSeismic analysisFrame (networking)Moment (physics)Displacement (psychology)Steel frameShear (geology)Base (topology)Shear force

Abstract

fetched live from OpenAlex

The aim of the present work is to analyze a multistory and multi bay (G+5) moment resisting building frame for earthquake forces following IS 1893 and then design it as per IS 800:2007 .The frame consists of six story‟s and has three bays in horizontal direction and five bays in lateral direction. The selection of arbitrary sections have been done following a standard procedure. The two methods that have been used for analysis are Equivalent static load method and Response Spectrum method .A comparative study of the results obtained from both these methods have been made in terms of story displacement ,inter story drift and base shear . The frame has also been further checked for P- analysis and required correction in moments have been done following IBC code .Then the steel moment resisting frame has been designed following IS-800:2007 based on these methods of analysis. In the process of design the section has undergone numerous iterations till all the criteria mentioned in the IS 800 have been satisfied. The designed frame was again analyzed and results were compared in terms of sections used. The cost efficiency of both the methods have been 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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.481
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.039
GPT teacher head0.352
Teacher spread0.313 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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