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Record W3010810860 · doi:10.18280/ijsse.100115

A Shape Memory Alloy-Pendulum Damping System for Small Wild Goose Pagoda in Xi’an, China

2020· article· en· W3010810860 on OpenAlexvenueno aff
Yang Tao, Deming Liu, Yang Liu, Sheliang Wang, Binbin Li

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsnot available
FundersEducation Department of Shaanxi Province
KeywordsPagodaGooseChinaPendulumControl theory (sociology)EngineeringGeographyComputer scienceEcologyBiologyMechanical engineeringArchaeology

Abstract

fetched live from OpenAlex

This paper aims to develop a system to control the vibrations of ancient pagodas without damaging their original appearance. Taking the Small Wild Goose (SWG) Pagoda (Xi'an, Shaanxi Province) as the target structure, the authors designed a shape memory alloypendulum damping system (SMA-PDS) based on the theory of pendulum damping and the super elasticity of the SMA. To verify the effect of the SMA-PDS, a 1:10 scale model was created for the SWG Pagoda, and subjected to shaking table tests with and without the SMA-PDS. The test results indicate that: the small and flexible system can be installed easily inside the pagoda to dampen seismic vibrations; the SMA-PDS greatly reduced the acceleration response at the top of the SWG Pagoda model; the reduction is particularly prominent (32.5%), when the SMA wires had a pre-strain of 3%; the SMA-PDS worked better in medium and large earthquakes than in small earthquakes. To sum up, this paper provides a novel damping system for seismic vibration in ancient pagodas, shedding new light on the energy dissipation, vibration control and reinforcement of similar ancient pagodas.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.663

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 head0.199
Teacher spread0.190 · 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
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
Published2020
Admission routes1
Has abstractyes

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