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Record W4317677031 · doi:10.1139/tcsme-2022-0064

Design, modeling, and simulation of a novel transducer for vibration energy recovery system of speed bump

2023· article· en· W4317677031 on OpenAlexvenueno aff
Guo Yan, Xuhui Liao, Haodong Meng, Fulong Dong, Shang-Kuo Yang

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsnot available
Fundersnot available
KeywordsTransducerVibrationAccelerationAcousticsTime domainDecoupling (probability)Displacement (psychology)Coupling (piping)EngineeringMATLABControl theory (sociology)Computer sciencePhysicsControl engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Based on the designed vibration energy recovery system of speed bump, the structure and principle of a novel transducer are introduced in this paper, which is an important part of the system. AMEsim simulation software was used to study the characteristics of the transducer, and the feasibility of the transducer design was verified through modeling and analysis of the dual-cylinder transducer. The coupling model of vehicle speed bump and transducer was analyzed, the dynamic differential equation was listed, and the decoupling operation was carried out. On the basis of the above, Matlab/Simulink was used to establish the model simulation, and the time-domain responses of displacement, velocity, and acceleration of the vibration of the car body, wheel, and transducer in the coupling model system were analyzed. The control variable method was used to further explore the time-domain response of vehicle acceleration in the coupling system only when the vehicle speed changes or the transducer damping changes. Finally, the vibration energy recovery system of the speed bump was built, and the preliminary test proved that the transducer can realize its function.

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: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.385

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 head0.028
GPT teacher head0.213
Teacher spread0.184 · 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
GenreEmpirical

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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicHydraulic and Pneumatic SystemsFrench-language works237,207