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Record W4416694451 · doi:10.1080/13632469.2025.2575273

Instantaneous Optimal Control Algorithm-Based Active Control of Reinforced Concrete Structures Subjected to Strong Ground Motions

2025· article· en· W4416694451 on OpenAlexaff
Maryam Shooshtari, Zaid A. Al-Sadoon, Murat Saatçioğlu, Ahed Habib

Bibliographic record

VenueJournal of Earthquake Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsReinforced concreteOptimal controlControl (management)Vibration controlBase isolationControl theory (sociology)

Abstract

fetched live from OpenAlex

Recent seismic events revealed the vulnerability of older structures. Retrofitting, especially with active force control, mitigates seismic risk by calculating real-time control forces to minimize deformations during earthquakes. However, current strategies often overlook nonlinear behavior. This study develops an active force control procedure for reinforced concrete frames, considering both elastic and inelastic deformations. It incorporates a time-varying stiffness matrix and rotational springs to simulate hysteretic response. Control forces are computed using an instantaneous optimal control algorithm. The procedure effectively reduces inelastic deformations and associated damage, despite challenges in hardware implementation and time delays.

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: none
Teacher disagreement score0.646
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.201
Teacher spread0.196 · 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
Published2025
Admission routes1
Has abstractyes

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