Low Frequency In-Cab Booming Noise Reduction in the Passenger Car

Author(s):  
Pradeep Jawale ◽  
Nagesh Voderahobli Karanth ◽  
Atul Annasaheb Gaikwad ◽  
Keshav Mutalik
1967 ◽  
Vol 42 (5) ◽  
pp. 1202-1203
Author(s):  
J. Ronald Bailey ◽  
Franklin D. Hart

2015 ◽  
Vol 63 (1) ◽  
pp. 20-35 ◽  
Author(s):  
Dong Guan ◽  
Jiu Hui Wu ◽  
Li Jing ◽  
Nansha Gao ◽  
Mingming Hou

2021 ◽  
Vol 263 (6) ◽  
pp. 152-163
Author(s):  
Remi Roncen ◽  
Pierre Vuillemin ◽  
Patricia Klotz ◽  
Frank Simon ◽  
Fabien Méry ◽  
...  

In the context of noise reduction in diverse applications where a shear grazing flow is present (i.e., engine nacelle, jet pump, landing gear), improved acoustic liner solutions are being sought. This is particularly true in the low-frequency regime, where space constraints currently limit the efficiency of classic liner technology. To perform the required multi-objective optimization of complex meta-surface liner candidates, a software platform called OPAL was developed. Its first goal is to allow the user to assemble a large panel of parallel/serial assembly of unit acoustic elements, including the recent concept of LEONAR materials. Then, the physical properties of this liner can be optimized, relatively to given weighted objectives (noise reduction, total size of the sample, weight), for a given configuration. Alternatively, properties such as the different impedances of liner unit surfaces can be optimized. To accelerate the process, different nested levels of optimization are considered, from 0D analytical coarse designs in order to reduce the parameter space, up to 2D plan or axisymmetric high-order Discontinuous Galerkin resolution of the Linearized Euler Equations. The presentation will focus on the different aspects of liner design considered in OPAL, and present an application on different samples made for a small scale aeroacoustic bench.


Author(s):  
Qiao Zhang ◽  
Jinhua Sheng ◽  
Bin Chen

Background: X-ray computed tomography is the first imaging technology that supports accurate nondestructive interior image reconstruction of an object from sufficient projection data. Low-dose computed tomography (LDCT) has been considered to relieve the harm to patients caused by X-ray radiation. However, LDCT images can be degraded by quantum noise and streak artifacts. Methods: The objective of the authors’ study is to evaluate the optimal level of the hybrid iterative reconstruction (HIR) that generates images with the best diagnostic quality on different dose and noise levels. HIR with optimizations is proposed to reduce image noise and provide better performance at a low dose. The Catphan R 504 phantom is employed to assess various image qualities (IQ). Results: For any given scanning protocols, there is linear noise reduction and linear increase of contrast-to- noise ratio (CNR) using optimal HIR. The evidence from various module tests demonstrates that the shape of the noise power spectrum is continuously shifted to low frequency with increasing HIR levels compared with that of filtered-back-projection (FBP). This may describe the difference between the human observer performance and features of the ideal low-contrast objects. Conclusion: Optimal HIR is clearly demonstrated to be a superior method for reducing image noise and improving CNR compared to FBP. Optimal HIR also inhibits texture change or spectrum shift compared with the pure IR method. Even though there are continuous noise reduction and CNR increase with HIR at increasing levels, the human observer performance does not seem to improve simultaneously due to coarser noise (low-frequency noise). HIR level 3 to 5 is optimal for their study. It is possible for the optimal HIR to offer equivalent diagnostic IQ at a lower dose compared with FBP at a routine dose.


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