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Record W1514447174 · doi:10.1002/pamm.201410092

Optimum Tuned Mass Dampers for Structures at Rock and Soil Sites

2014· article· en· W1514447174 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

VenuePAMM · 2014
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsTuned mass damperHarmony searchRock mass classificationGeotechnical engineeringGeologyEarthquake resistanceStructural engineeringSeismologyDamperEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract In optimum design of tuned mass dampers (TMD), several factors are effective. One of the most important factors is the characteristics of the excitation. Earthquake excitations recorded at soil and rock sites show different characteristics in period and damping. In this paper, optimum TMD properties are separately searched for seismic structures at soil sites and rock sites. For each optimization, six different earthquake records were used. A design methodology was used by employing harmony search (HS). The approach was applied to a ten story structure with one second critical period. Although more damping ratio for TMD is needed for soil sites than rock sites, TMD is more effective for rock sites than soil sites. (© 2014 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.272

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 head0.007
GPT teacher head0.198
Teacher spread0.191 · 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