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Record W4387344389 · doi:10.3390/aerospace10100867

Experimental and Numerical Modal Analysis of a Composite Rocket Structure

2023· article· en· W4387344389 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

VenueAerospace · 2023
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFinite element methodRocket (weapon)Modal analysisNumerical analysisStiffnessStructural engineeringModalHammerComputer simulationExperimental dataComputer scienceEngineeringAerospace engineeringMathematicsMaterials scienceSimulation

Abstract

fetched live from OpenAlex

Finite Element Analysis (FEA) is a powerful tool that can aid in the engineering design process to reduce cost and time. However, it is best used in conjunction with experimental data, through which its numerical results can be verified. This paper presents the experimental and numerical modal analyses of an experimental rocket aerostructure to verify the accuracy of the numerical models. This aerostructure has been through flight loads and a recovery. The first numerical results for the rocket showed a 96% difference with the experimental ones. Subsequently, three mass refinements were made to create calibrated FEM models whose results differed from the experimental ones by 19% to 8%. Additionally, as expected, the FEM results tended to overestimate the stiffness of structures. The numerical simulations for all components were performed through ANSYS software, and the experiments were conducted using the hammer tap test with laser vibrometers as sensors.

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 score0.251
Threshold uncertainty score0.381

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 head0.004
GPT teacher head0.218
Teacher spread0.213 · 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