Wakae Kozukue

The development of eigenmode sensitivity analysis methods for coupled acoustic-structural systems and their application to reduction of vehicle interior noise

Abstract Reducing the noise and vibration of a vehicle is an important issue from the standpoints of improving its sales potential as a product and of preventing noise pollution problems. So researchers have used finite element methods or boundary element methods to make predictions of noise and vibration. But what is required at the design stage is to find body structures which will reduce the predicted noise and vibration to the target values. The use of sensitivity analysis makes it easy to determine how the analytical model should be modified or the structure optimized for the purpose of reducing vibration and noise of the structural-acoustic systems. The present work focused on a structural-acoustic coupling problem. As the coefficient matrices of a coupled structural-acoustic system are not symmetrical, the conventional orthogonality conditions obtained in structural dynamics generally do not hold true for the coupled system. To overcome this problem, the orthogonality and normalization conditions of a coupled system were derived by us. In this paper, the new sensitivity analysis methods are applied to an interior noise problem of a cabin model. It will be shown how a sensitivity analysis process is performed, and how vibration and noise can be reduced.

Development of sound pressure level integral sensitivity and its application to vehicle interior noise reduction

One of the authors has already formulated the sensitivity analysis for a coupled structural‐acoustic system and applied the method in order to obtain modal sensitivities and modal frequency response sensitivities for the sound pressure level at peak frequency points. However, for the development of a vehicle, not only the reduction of peak frequency level but also that of integral of noise for a specified frequency range is desired. For investigating this it is considered effective to use sensitivities of integrated sound pressure level for a specified frequency range. Thus a “sound pressure level integral” has been developed, which is the integrated value of sound pressure level, and further “sensitivity of sound pressure level integral”. Shows how an integral analysis process is performed, and how vibration and noise can be reduced.

Input load identification using a holographic neural network

A machine generates and undergoes dynamic loads during its operation. These dynamic loads are the main source of vibration and noise. If the dynamic loads can be identified exactly, it will become possible to provide the data effective for the reduction of vibration and noise. However, by the method of identification of dynamic loads of the conventional multiple-input systems, noise has a large influence on accuracy. Thus, in this paper, an identification method based on a neural network is proposed for independent multiple-input loads, and the results of the simulation by using the conventional method and the neural network are shown and compared in detail.

Analysis for Vehicle Interior Noise Using Helmholtz Resonator

In this paper the reduction analysis of the so-called ‘booming noise’, which occurs due to the resonance of a vehicle cabin, is tried to carry out by using the finite element method. For the reduction method a Helmholtz resonator, which is well known in the field of acoustics, is attached to a vehicle cabin. The resonance frequency of a Helmholtz resonator can be varied by adjusting the length of its throat. The simply shaped Helmholtz resonator is set up to the back of the cabin according to the resonance frequency of the cabin and the frequency response of the sound pressure at a driver’s ear position is calculated by using the finite element method. It is confirmed that the acoustical characteristics of the cabin is changed largely by attaching the resonator and the sound quality is quite varied. The resonance frequency of the resonator can be considered to follow the acoustical characteristics of the cabin by using an Origami structure as a throat. So, in the future the analysis by using an Origami structure Helmholtz resonator should be performed.Copyright

Force Identification Using Neural Network

Due to various causes, a machine generates and undergoes dynamic loads during its operation. These dynamic loads are the main source of vibration and noise. If dynamic loads can be identified exactly, it will become possible to provide data effective for the reduction of vibration and noise. However, by the method of identification of dynamic loads of the conventional multiple input systems, noise has large influence on the accuracy. Thus, in this paper, the identification method based on neural network (NN) are proposed for independent multiple input loads, and the result of the simulation by using the conventional method and NN are shown and compared in detail.Copyright

Topology optimization analysis for reduction of interior noise using a homogenization method for a mean eigenvalue

Shape and topology optimization analysis using a homogenization method has received much attention because it can treat topological changes of a design domain. However, as far as dynamic problems are concerned, it has not been successfully applied until recently. Here, it is applied to the reduction of interior noise in the coupled structural–acoustic system for the first time. Attempts were made to reduce the mean eigenvalue formulated by Ma et al. and the sound‐pressure level integral formulated by Kozukue et al. by using a homogenization method, and the validity of these combined methods is demonstrated.

Development of an analysis method for acoustic–structural coupling systems using the BEM for the acoustic field: The validity of the method developed and comparison with the FEM acoustic field

A formulation is developed for the analysis of coupled acoustic–structural systems using the boundary element method (BEM) in order to apply the coupled method to the open field in addition to the closed field. In this formulation the most general mode superposition method by Ma‐Hagiwara, namely, the high‐ and low‐order truncatable mode superposition method, is used where the higher and the lower modes are truncated. The propriety of this formulation is verified by comparing it with a theoretical solution in a one‐dimensional problem and with the solution by a method in an interior noise problem, which was developed using the finite‐element method (FEM).