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Record W4409605293 · doi:10.1016/j.jobe.2025.112717

Mitigating higher mode effects in self-centering rocking frames by using a tuned mass damper

2025· article· en· W4409605293 on OpenAlexafffund
Esmaeil Mohammadi Dehcheshmeh, Saber Moradi, Aydin Hassanzadeh

Bibliographic record

VenueJournal of Building Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaWestern University
KeywordsTuned mass damperDamperMode (computer interface)Structural engineeringPhysicsMaterials scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

This paper proposes the application of tuned mass dampers (TMDs) for mitigating higher-mode effects in controlled rocking steel braced frames (CRBFs). The numerical study evaluates the effectiveness of using TMDs in rocking frames under different earthquake records. Furthermore, a connection detail is proposed to isolate the rocking frame from the diaphragm. The modified modal superposition (MMS) method is employed to design 12-, 16-, 20-, and 24-story CRBFs. Nonlinear response history analyses are performed to examine the influence of higher mode effects for the designed frames under twenty-two far-field ground motion records and fourteen near-field records without strong pulses (referred to as the FF and NF ground motion records, respectively). Furthermore, a particle swarm optimization algorithm is implemented to minimize higher mode effects in CRBFs with a TMD. Two optimization problems, Op1 and Op2, are considered for incorporating TMDs into the rocking frames. In Op1, the optimal TMD parameters, mass ratio, frequency, damping coefficient, and location are found. Subsequently, Op2 examines the specifications of the rocking joints, energy-dissipating fuse stiffness, fuse yield strength, number of cables, and the initial post-tensioning ratio of the PT cables, in addition to the TMD-related parameters and TMD placement. On average, the reductions in median story moments and shear demands in optimal designs are up to 18% and 24% under FF ground motion records and up to 22% and 29% under NF ground motion records, respectively. Finally, recommendations are presented for TMD and rocking joint parameters for the design of CRBFs equipped with TMD. • Proposed the use of a TMD in controlled rocking steel braced frames (CRBFs). • Evaluated the effectiveness of using TMDs in reducing higher mode effects. • Performed nonlinear response history analyses under far- and near-field records. • Proposed a connection detail to isolate the rocking frame from the diaphragm. • Performed optimization studies on rocking frames with a tuned mass damper (TMD).

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 categoriesMeta-epidemiology (narrow)
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 score0.484
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.003
GPT teacher head0.228
Teacher spread0.224 · 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.

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 routes2
Has abstractyes

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