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Record W2598411247 · doi:10.1177/1077546317696362

Analytical transmissibility based transfer path analysis for multi-energy-domain systems using bond graphs

2017· article· en· W2598411247 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

VenueJournal of Vibration and Control · 2017
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBond graphTransmissibility (structural dynamics)Path (computing)VibrationComputer scienceBenchmark (surveying)Vibration isolationAlgorithmGraphEnergy (signal processing)Transfer functionDomain (mathematical analysis)Mathematical optimizationEngineeringTheoretical computer scienceMathematicsPhysicsAcoustics

Abstract

fetched live from OpenAlex

The increasing demand for vibration reduction in several high-tech industries has motivated many researchers to investigate novel vibration isolation techniques. Understanding the vibration transfer paths within a system is an essential part of designing an effective vibration isolation strategy. In this paper, an analytical transfer path analysis algorithm is proposed suitable for multi-energy-domain systems. The bond graph modeling technique, which is an effective approach to model multi-energy-domain systems, is used to extend the concept of transmissibility to such systems. In this paper, an electro-hydro-mechanical system is used as a benchmark example to elucidate the effectiveness of the proposed technique. An energy based path ranking algorithm based on the bond graph model of the system is also conducted.

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)0.001
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: none
Teacher disagreement score0.863
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.031
GPT teacher head0.271
Teacher spread0.240 · 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