MétaCan
Menu
Back to cohort
Record W2102850766 · doi:10.1061/40889(201)101

Tuned Liquid Dampers to Mitigate Wind-Induced Motions of Buildings

2006· article· en· W2102850766 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStructures Congress 2006 · 2006
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsMcMaster UniversityWestern University
Fundersnot available
KeywordsSlosh dynamicsRobustness (evolution)Tuned mass damperDamperNonlinear systemStructural engineeringThermoluminescent dosimeterComputer scienceAcousticsEngineeringPhysicsOptics

Abstract

fetched live from OpenAlex

Passive auxiliary dynamic vibration absorbers (DVA), in particular the tuned mass damper (TMD) and tuned liquid damper (TLD), have become accepted devices for reducing the resonant motions of lively tall structures. A TLD is comprised of a rigid tank partially filled with liquid (usually water) and fitted with energy dissipating mechanisms such as screens. Despite the simplicity of a TLD's physical components, its nonlinear dynamic characteristics complicate the prediction of its performance as a DVA. This paper focuses on the application side of tuned liquid dampers fitted with internal damping screens. Experimental data are presented from a research program conducted to provide insight into the performance of a TLD in terms of its efficiency and robustness. The efficiency of a TLD is measured by comparing the effectiveness of a particular TLD to that of an equivalent optimal linear TMD with the same mass ratio. The entire water mass often does not participate in the sloshing motion resulting in an efficiency level that is less than that of an equivalent optimal linear TMD. Robustness of a damper is the measure of insensitivity of its performance to changes in the parameters of the damper and the main structure from their proposed values. In this study, robustness is determined by examining the effectiveness of a TLD under various response amplitudes, the limiting of the sloshing motion by restricting the available freeboard, and varying the natural frequency of the structure itself. Two directional TLDs, which operate simultaneously in two orthogonal directions, are also briefly discussed.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
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 head0.006
GPT teacher head0.209
Teacher spread0.203 · 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