Improved Full Vehicle Finite Element Tire Road Noise Prediction

2017 ◽  
Author(s):  
Christian Glandier ◽  
Stefanie Grollius
Keyword(s):  
Finite Element ◽  
Noise Prediction ◽  
Road Noise ◽  
Full Vehicle

A Hybrid Full Vehicle Model for Structure Borne Road Noise Prediction

2005 ◽  
Author(s):  
Charles Gagliano ◽  
Andrea Martin ◽  
Jared Cox ◽  
Kimberly Clavin ◽  
François Gérard ◽  
...  
Keyword(s):  
Noise Prediction ◽  
Vehicle Model ◽  
Road Noise ◽  
Full Vehicle

Application of the Boundary Element Method and Modal Analysis to Tire Acoustics Problems

1993 ◽  
Vol 21 (2) ◽  
pp. 66-90 ◽  
Author(s):  
Y. Nakajima ◽  
Y. Inoue ◽  
H. Ogawa
Keyword(s):  
Finite Element ◽  
Boundary Element Method ◽  
Boundary Element ◽  
Acoustic Radiation ◽  
Traffic Noise ◽  
Noise Prediction ◽  
Prediction System ◽  
Tire Noise ◽  
Acoustic Contribution ◽  
Element Method

Abstract Road traffic noise needs to be reduced, because traffic volume is increasing every year. The noise generated from a tire is becoming one of the dominant sources in the total traffic noise because the engine noise is constantly being reduced by the vehicle manufacturers. Although the acoustic intensity measurement technology has been enhanced by the recent developments in digital measurement techniques, repetitive measurements are necessary to find effective ways for noise control. Hence, a simulation method to predict generated noise is required to replace the time-consuming experiments. The boundary element method (BEM) is applied to predict the acoustic radiation caused by the vibration of a tire sidewall and a tire noise prediction system is developed. The BEM requires the geometry and the modal characteristics of a tire which are provided by an experiment or the finite element method (FEM). Since the finite element procedure is applied to the prediction of modal characteristics in a tire noise prediction system, the acoustic pressure can be predicted without any measurements. Furthermore, the acoustic contribution analysis obtained from the post-processing of the predicted results is very helpful to know where and how the design change affects the acoustic radiation. The predictability of this system is verified by measurements and the acoustic contribution analysis is applied to tire noise control.

Modelling Tyre-Road Noise with Data Mining Techniques

2015 ◽  
Vol 40 (4) ◽  
pp. 547-560 ◽  
Author(s):  
Elisabete Freitas ◽  
Joaquim Tinoco ◽  
Francisco Soares ◽  
Jocilene Costa ◽  
Paulo Cortez ◽  
...  
Keyword(s):  
Data Mining ◽  
Predictive Model ◽  
Early Stage ◽  
Aggregate Size ◽  
Noise Prediction ◽  
Road Noise ◽  
Predictive Capacity ◽  
Data Mining Approach ◽  
Relevant Variables ◽  
Input Variables

Abstract The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and unevenness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V 4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.

Road Noise Prediction Assessment Using CAE Instead of Costly and Time Consuming Physical Tests

2020 ◽  
Author(s):  
Vishnu S ◽  
Prajith J ◽  
Muralidhara Holla ◽  
Patil Suhas ◽  
Indranil Bhattacharyya
Keyword(s):  
Noise Prediction ◽  
Road Noise ◽  
Physical Tests

A survey on road noise prediction for milled shoulder rumble strip designs

2018 ◽  
Vol 14 (3) ◽  
pp. 251
Author(s):  
Kira M. Glover Cutter ◽  
Yue Zhang ◽  
Christopher Parrish ◽  
David Hurwitz ◽  
Paris Kalathas
Keyword(s):  
Noise Prediction ◽  
Road Noise ◽  
Rumble Strip
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