A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters

For the frequency response analysis of acoustic field with random and interval parameters, a nonintrusive uncertain analysis method named Polynomial Chaos Response Surface (PCRS) method is proposed. In the proposed method, the polynomial chaos expansion method is employed to deal with the random par...

Full description

Bibliographic Details
Main Authors: Mingjie Wang, Zhimin Wan, Qibai Huang
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2016/3693262
id doaj-31ab0799a686483a80db5c79846c5ea0
record_format Article
spelling doaj-31ab0799a686483a80db5c79846c5ea02020-11-24T21:05:58ZengHindawi LimitedShock and Vibration1070-96221875-92032016-01-01201610.1155/2016/36932623693262A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval ParametersMingjie Wang0Zhimin Wan1Qibai Huang2State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaCollege of Automobile and Transportation Engineering, Nantong Vocational University, Nantong 226000, ChinaState Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaFor the frequency response analysis of acoustic field with random and interval parameters, a nonintrusive uncertain analysis method named Polynomial Chaos Response Surface (PCRS) method is proposed. In the proposed method, the polynomial chaos expansion method is employed to deal with the random parameters, and the response surface method is used to handle the interval parameters. The PCRS method does not require efforts to modify model equations due to its nonintrusive characteristic. By means of the PCRS combined with the existing interval analysis method, the lower and upper bounds of expectation, variance, and probability density function of the frequency response can be efficiently evaluated. Two numerical examples are conducted to validate the accuracy and efficiency of the approach. The results show that the PCRS method is more efficient compared to the direct Monte Carlo simulation (MCS) method based on the original numerical model without causing significant loss of accuracy.http://dx.doi.org/10.1155/2016/3693262
collection DOAJ
language English
format Article
sources DOAJ
author Mingjie Wang
Zhimin Wan
Qibai Huang
spellingShingle Mingjie Wang
Zhimin Wan
Qibai Huang
A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters
Shock and Vibration
author_facet Mingjie Wang
Zhimin Wan
Qibai Huang
author_sort Mingjie Wang
title A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters
title_short A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters
title_full A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters
title_fullStr A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters
title_full_unstemmed A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters
title_sort new uncertain analysis method for the prediction of acoustic field with random and interval parameters
publisher Hindawi Limited
series Shock and Vibration
issn 1070-9622
1875-9203
publishDate 2016-01-01
description For the frequency response analysis of acoustic field with random and interval parameters, a nonintrusive uncertain analysis method named Polynomial Chaos Response Surface (PCRS) method is proposed. In the proposed method, the polynomial chaos expansion method is employed to deal with the random parameters, and the response surface method is used to handle the interval parameters. The PCRS method does not require efforts to modify model equations due to its nonintrusive characteristic. By means of the PCRS combined with the existing interval analysis method, the lower and upper bounds of expectation, variance, and probability density function of the frequency response can be efficiently evaluated. Two numerical examples are conducted to validate the accuracy and efficiency of the approach. The results show that the PCRS method is more efficient compared to the direct Monte Carlo simulation (MCS) method based on the original numerical model without causing significant loss of accuracy.
url http://dx.doi.org/10.1155/2016/3693262
work_keys_str_mv AT mingjiewang anewuncertainanalysismethodforthepredictionofacousticfieldwithrandomandintervalparameters
AT zhiminwan anewuncertainanalysismethodforthepredictionofacousticfieldwithrandomandintervalparameters
AT qibaihuang anewuncertainanalysismethodforthepredictionofacousticfieldwithrandomandintervalparameters
AT mingjiewang newuncertainanalysismethodforthepredictionofacousticfieldwithrandomandintervalparameters
AT zhiminwan newuncertainanalysismethodforthepredictionofacousticfieldwithrandomandintervalparameters
AT qibaihuang newuncertainanalysismethodforthepredictionofacousticfieldwithrandomandintervalparameters
_version_ 1716767212243517440