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Record W4411351025 · doi:10.1139/cjce-2024-0478

Optimal design and performance of inter-story isolation system with inerter damper considering soil–structure interaction under near-fault pulse-like ground motions

2025· article· en· W4411351025 on OpenAlexvenueno aff
Yang Liu, Dewen Liu, H.T. Hu

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsAccelerationDamperDisplacement (psychology)EngineeringControl theory (sociology)White noiseStructural engineeringOptimal designTuned mass damperComputer scienceControl (management)

Abstract

fetched live from OpenAlex

The study investigates the optimal seismic performance of inter-story isolation system (IIS) with tuned inerter damper (TID) and tuned mass damper inerter (TMDI), considering soil–structure interaction. Simplified 6-degree-of-freedom models for two control systems are developed to analyze the seismic response variations of the systems under stationary white noise excitation. Frequency and damping parameters are optimized based on objective functions related to displacement and acceleration. The analysis also explores the effects of model parameters on optimum design. A comparison is made between the seismic responses of IIS with and without TID/TMDI under 34 near-fault pulse-like ground motions (NPGMs) through time history analysis. The results demonstrate that TID and TMDI effectively control acceleration and displacement responses of the systems. Notably, NPGM characteristics significantly influence control effectiveness, which should be carefully considered in design. It is highlighted that this optimal design strategy is applicable across various soil 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 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)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.177
Teacher spread0.170 · 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
Published2025
Admission routes1
Has abstractyes

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