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Record W2928032573 · doi:10.11159/icsect19.151

Assessment of Hyper-Viscoelastic Seismic Isolator Behaviour Using Finite Element

2019· article· en· W2928032573 on OpenAlexvenueno aff
Emran Alotaibi, Nadia Nassif, Rami Alsodi, Sara Ayman, Ibrahim Haj Fattouh

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicElasticity and Material Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsViscoelasticityFinite element methodIsolatorStructural engineeringGeotechnical engineeringGeologyMaterials scienceEngineeringComposite materialElectronic engineering

Abstract

fetched live from OpenAlex

Base isolation concept is a new technology on seismic control of structures. There are various types of seismic isolators that are used nowadays including elastomeric bearings isolators and sliding isolators. This paper describes the behaviour of a Hyper-Viscoelastic rubber bearing isolator based on finite element (FE) software ANSYS. A 2D model consists of upper and lowers steel plates with a series of alternating layers of rubber and steel shim plates. Hysteresis graphs of the model was obtained from the software. This graph indicated the main characteristics of the isolator. Different stiffness coefficients were determined as well as the effective dumping. A detailed discussion was conducted at the end of this paper where the behaviour of the rubber bearing isolator was compared with the behaviour of a lead rubber isolator. Moreover, it has been proved that using Hyper-Viscoelastic Rubber would decrease the shear deformation amplitude (E), decrease of failure load and increase maximum deformation in the isolators.

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 score0.288
Threshold uncertainty score0.868

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 head0.005
GPT teacher head0.192
Teacher spread0.187 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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