Analysis, design, and installation of vibration isolation for lightweight helipads
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".