FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3198488410> ?p ?o ?g. }

• W3198488410 endingPage "8029" @default.
• W3198488410 startingPage "8029" @default.
• W3198488410 abstract "Vehicle interior noise is an important factor affecting ride comfort. To reduce the noise inside the vehicle at the vehicle body design stage, a finite element model of the vehicle body must be established. While taking the first-order global modal of the body-in-white, the maximum sound pressure level of the target point in the vehicle, the body mass, and the side impact conditions into account, the thickness of the body panel as determined via sensitivity analysis is treated as the input variable, and the sample is determined by following the Hamersley experimental design. Specifically, the Elman neural network predicts the noise value in the vehicle, and a vehicle body structure optimization method that comprehensively considers NVH performance and side impact safety is established. The prediction errors of the Elman neural network algorithm were within 3%, which meets the prediction accuracy requirements. To achieve satisfactory restraint performance, the maximum sound pressure level of the target point in the vehicle is reduced by 5.92 dB, and the maximum intrusions of the two points on the B-pillar inner panel are reduced by 31.1 mm and 33.71 mm, respectively. The side impact performance is improved while the noise inside the vehicle is reduced. This study provides a reference method for multidisciplinary research aiming to optimize the design of vehicle body structures." @default.
• W3198488410 created "2021-09-13" @default.
• W3198488410 creator A5004658590 @default.
• W3198488410 creator A5026526428 @default.
• W3198488410 creator A5030352267 @default.
• W3198488410 creator A5032129283 @default.
• W3198488410 creator A5043667434 @default.
• W3198488410 creator A5045408700 @default.
• W3198488410 creator A5058499562 @default.
• W3198488410 creator A5081110905 @default.
• W3198488410 date "2021-08-30" @default.
• W3198488410 modified "2023-10-16" @default.
• W3198488410 title "Vehicle Interior Noise Prediction Based on Elman Neural Network" @default.
• W3198488410 cites W1251058109 @default.
• W3198488410 cites W1982116442 @default.
• W3198488410 cites W2055102926 @default.
• W3198488410 cites W2073004501 @default.
• W3198488410 cites W2087673946 @default.
• W3198488410 cites W2089949001 @default.
• W3198488410 cites W2102010126 @default.
• W3198488410 cites W2462726398 @default.
• W3198488410 cites W2472783893 @default.
• W3198488410 cites W2554584531 @default.
• W3198488410 cites W2561657077 @default.
• W3198488410 cites W2563353868 @default.
• W3198488410 cites W2594492967 @default.
• W3198488410 cites W2600404434 @default.
• W3198488410 cites W2601233790 @default.
• W3198488410 cites W2608509367 @default.
• W3198488410 cites W2621113646 @default.
• W3198488410 cites W2769316532 @default.
• W3198488410 cites W2789810486 @default.
• W3198488410 cites W2790715602 @default.
• W3198488410 cites W2803015115 @default.
• W3198488410 cites W2803504791 @default.
• W3198488410 cites W2807215053 @default.
• W3198488410 cites W2866946904 @default.
• W3198488410 cites W2890889174 @default.
• W3198488410 cites W2892008852 @default.
• W3198488410 cites W2905552285 @default.
• W3198488410 cites W2915637418 @default.
• W3198488410 cites W2940842719 @default.
• W3198488410 cites W2970389211 @default.
• W3198488410 cites W2971069568 @default.
• W3198488410 cites W3000855622 @default.
• W3198488410 cites W3008633314 @default.
• W3198488410 cites W3037911826 @default.
• W3198488410 cites W3048516488 @default.
• W3198488410 cites W3082224727 @default.
• W3198488410 cites W3091580135 @default.
• W3198488410 cites W3125010078 @default.
• W3198488410 cites W3143184994 @default.
• W3198488410 cites W3153541578 @default.
• W3198488410 cites W3157172939 @default.
• W3198488410 cites W3171188586 @default.
• W3198488410 doi "https://doi.org/10.3390/app11178029" @default.
• W3198488410 hasPublicationYear "2021" @default.
• W3198488410 type Work @default.
• W3198488410 sameAs 3198488410 @default.
• W3198488410 citedByCount "9" @default.
• W3198488410 countsByYear W31984884102022 @default.
• W3198488410 countsByYear W31984884102023 @default.
• W3198488410 crossrefType "journal-article" @default.
• W3198488410 hasAuthorship W3198488410A5004658590 @default.
• W3198488410 hasAuthorship W3198488410A5026526428 @default.
• W3198488410 hasAuthorship W3198488410A5030352267 @default.
• W3198488410 hasAuthorship W3198488410A5032129283 @default.
• W3198488410 hasAuthorship W3198488410A5043667434 @default.
• W3198488410 hasAuthorship W3198488410A5045408700 @default.
• W3198488410 hasAuthorship W3198488410A5058499562 @default.
• W3198488410 hasAuthorship W3198488410A5081110905 @default.
• W3198488410 hasBestOaLocation W31984884101 @default.
• W3198488410 hasConcept C109400559 @default.
• W3198488410 hasConcept C115961682 @default.
• W3198488410 hasConcept C121332964 @default.
• W3198488410 hasConcept C127413603 @default.
• W3198488410 hasConcept C154945302 @default.
• W3198488410 hasConcept C171146098 @default.
• W3198488410 hasConcept C185592680 @default.
• W3198488410 hasConcept C188027245 @default.
• W3198488410 hasConcept C198394728 @default.
• W3198488410 hasConcept C21200559 @default.
• W3198488410 hasConcept C24326235 @default.
• W3198488410 hasConcept C24890656 @default.
• W3198488410 hasConcept C41008148 @default.
• W3198488410 hasConcept C44154836 @default.
• W3198488410 hasConcept C50644808 @default.
• W3198488410 hasConcept C68115822 @default.
• W3198488410 hasConcept C71139939 @default.
• W3198488410 hasConcept C76155785 @default.
• W3198488410 hasConcept C99498987 @default.
• W3198488410 hasConceptScore W3198488410C109400559 @default.
• W3198488410 hasConceptScore W3198488410C115961682 @default.
• W3198488410 hasConceptScore W3198488410C121332964 @default.
• W3198488410 hasConceptScore W3198488410C127413603 @default.
• W3198488410 hasConceptScore W3198488410C154945302 @default.
• W3198488410 hasConceptScore W3198488410C171146098 @default.
• W3198488410 hasConceptScore W3198488410C185592680 @default.

• next