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Record W4400287362 · doi:10.1121/10.0027715

Analysis, design, and installation of vibration isolation for lightweight helipads

2024· article· en· W4400287362 on OpenAlexaff
Alfredo Rodrigues, Ashwin Dias, Freddy Saddik

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2024
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsVibration isolationIsolation (microbiology)VibrationStructural engineeringEngineeringComputer scienceAcousticsPhysicsBiology

Abstract

fetched live from OpenAlex

This case study discusses the design and manufacturing steps for the installation of a vibration isolation solution for two lightweight helidecks installed on the rooftop of an existing medical center building. The design stage involved the analysis of the relevant information, involving several specialties, such as Acoustics (for sources of vibration and acoustic performance requirements), Heliport Design[AR1] (for the type of aircraft, MTOW, number of supports, static and dynamic loads), and Structural (for the types of connections to the existing building structure). A collaborative effort between CDM Stravitec and the helideck supplier led the design through a progressive and iterative process where a final design that responded to the strong acoustical requirements and the complex nature of a fully functional and integrated lightweight helideck. Along the design, compromises where made ensure that requirements are met for both acoustic and structural performance. The solution delivered was a prefabricated box, which could easily be installed on site, comprised the necessary components, such as springs and uplift restraints to deal with the challenging aspects of the isolation of lightweight helidecks. The paper also discusses the challenges and best practices encountered during the production and installation of the system.

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: Methods · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.144

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.229
Teacher spread0.221 · 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
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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