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Record W4412754937 · doi:10.11159/iccste25.361

Influence of LRB Isolators on Accelerations and Shear Forces in an Eight-Story Building with Shear Walls in Comas, Lima, Peru

2025· article· en· W4412754937 on OpenAlexvenueno aff
Lenin Bendezú, Paul O. Awoyera

Bibliographic record

VenueProceedings of the International Conference on Civil, Structural and Transportation Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsShear (geology)GeologyStructural engineeringEngineeringPetrology

Abstract

fetched live from OpenAlex

Earthquakes are one of the leading causes of material losses and loss of human life worldwide.For this reason, ensuring the safety of buildings is of utmost importance.An effective solution to mitigate these risks is base isolation systems, a technology designed to reduce the impact of seismic movements on building structures.This study examines the influence of LRB (Lead Rubber Bearings) devices on the structural behavior in terms of accelerations and shear forces in an eight-story building, utilizing Etabs v22 software.The study compares structural performance through a nonlinear time-history analysis of a fixed base building against the same building equipped with a base isolation system.The results for the base isolated building demonstrate a reduction and a more uniform distribution of floor accelerations, which improves the stability of the building contents.Shear forces were significantly reduced by 72.76%, highlighting the effective flexibility of the implemented isolation system.Additionally, the energy dissipated by the LRB system achieved an efficiency of 76.5%.These findings confirm those reported in other studies and emphasize the importance of considering the implementation of these seismic protection systems in housing projects located in high seismic risk areas, such as the district of Comas, Lima, Peru.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.355

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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 designObservational
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

Explore more

Same venueProceedings of the International Conference on Civil, Structural and Transportation EngineeringSame topicSeismic Performance and AnalysisFrench-language works237,207