STATISTICAL ENERGY ANALYSIS OF COUPLED PLATE SYSTEMS WITH LOW MODAL DENSITY AND LOW MODAL OVERLAP

2002 ◽  
Vol 251 (2) ◽  
pp. 193-214 ◽  
Author(s):  
C. HOPKINS
2011 ◽  
Vol 189-193 ◽  
pp. 1914-1917
Author(s):  
Lin Ji

A key assumption of conventional Statistical Energy Analysis (SEA) theory is that, for two coupled subsystems, the transmitted power from one to another is proportional to the energy differences between the mode pairs of the two subsystems. Previous research has shown that such an assumption remains valid if each individual subsystem is of high modal density. This thus limits the successful applications of SEA theory mostly to the regime of high frequency vibration modeling. This paper argues that, under certain coupling conditions, conventional SEA can be extended to solve the mid-frequency vibration problems where systems may consist of both mode-dense and mode-spare subsystems, e.g. ribbed-plates.


1996 ◽  
Vol 39 (5) ◽  
pp. 38-45
Author(s):  
Leland Smith ◽  
Paul Bremner

Statistical energy analysis (SEA) was performed on models of International Space Station (ISS) truss segments. These segments are large truss structures built up from I-beam members. The purpose of this analytical program is to determine the random vibration environment for equipment mounted on these segments. The equipment is mounted to secondary structural built-up plates in most instances. In general, the secondary structure is more rigid than typical aerospace structures because of the large spans between the primary truss members. This presents a challenge to the SEA methodology because of the low modal density of both the primary and the secondary structure, and novel approaches to the problem were identified. The need to test verify these modeling approaches was apparent. On the previous Space Station Freedom program, a developmental vibroacoustic test of a space station-like truss segment was conducted. The development test specimen was modeled in a similar manner to the ISS segments and predicted responses were compared with test data. This paper discusses the modeling methods determined to be effective for these structures


2011 ◽  
Vol 130-134 ◽  
pp. 824-828
Author(s):  
Lin Ji ◽  
Zhen Yu Huang

A simple technique is introduced to estimate the inter-modal coupling relations of two Statistical Energy Analysis (SEA) subsystems connected via an arbitrary interface. Based on a subsystem modal approach, the dynamic stiffness matrix of a generic built-up system is derived analytically. The coupling stiffness terms between any pair of subsystem modes can then be determined in explicit expressions. Under the proper SEA conditions, e.g. each subsystem has a high modal density and the couplings between SEA subsystems are sufficiently weak, these inter-modal coupling stiffness expressions can be greatly simplified. The results can then be easily accommodated within the standard SEA modeling procedure to predict the SEA response of generic built-up systems in a simple manner. Theoretical applications are made to estimate the SEA coupling loss factors between two subsystems connected by two rigid points.


2017 ◽  
Vol 139 (5) ◽  
Author(s):  
Dean R. Culver ◽  
Earl H. Dowell

The root-mean-square (RMS) response of various points in a system comprised of two parallel plates coupled at a point undergoing high frequency, broadband transverse point excitation of one component is considered. Through this prototypical example, asymptotic modal analysis (AMA) is extended to two coupled continuous dynamical systems. It is shown that different points on the plates respond with different RMS magnitudes depending on their spatial relationship to the excitation or coupling points in the system. The ability of AMA to accurately compute the RMS response of these points (namely, the excitation point, the coupling points, and the hot lines through the excitation or coupling points) in the system is shown. The behavior of three representative prototypical configurations of the parallel plate system considered is: two similar plates (in both geometry and modal density), two plates with similar modal density but different geometry, and two plates with similar geometry but different modal density. After examining the error between reduced modal methods (such as AMA) to classical modal analysis (CMA), it is determined that these several methods are valid for each of these scenarios. The data from the various methods will also be useful in evaluating the accuracy of other methods including statistical energy analysis (SEA).


2019 ◽  
Vol 67 (6) ◽  
pp. 438-446
Author(s):  
M. Yoganandh ◽  
Jade Nagaraja ◽  
B. Venkatesham

In this article, statistical energy analysis (SEA) is used to predict insertion loss from a lagged rectangular HVAC duct. For a lagged duct, all duct walls are treated from outside with acoustic material. Although deterministic methods like the finite element method (FEM), boundary element method (BEM), and wave based methods can predict the breakout noise, these methods have limitations in handling systems with high modal density due to higher computational cost. In this study, a rectangular duct is divided into six subsystems, which are four duct walls (each wall considered as a subsystem), internal air cavity and external airspace. Power flow analysis is performed on all subsystems to calculate transverse transmission loss of an unlined duct and insertion loss for a lagged duct. Predicted transverse transmission loss values are validated with ASHRAE data and Insertion loss values with literature. The results obtained are in good agreement.


2012 ◽  
Vol 249-250 ◽  
pp. 307-313 ◽  
Author(s):  
Xiao Yan Yang ◽  
You Gang Xiao ◽  
Yu Shi

Statistical energy analysis(SEA) method has many advantages in analysis of high frequency, high modal density and complex dynamic systems. Dividing high-speed train cab into a series of sub-systems, the SEA model of high-speed train cab was established. The factors affecting the cab noise, such as modal density, damping loss factors, coupling loss factors, were gotten by theoretical analysis combined with experiments. Using large eddy simulation method, the fluctuation pressures from train head surface were calculated. Using fluctuation pressure as excitation source, wind noise spectra and power flow of sub-systems in cab were obtained, which provided the basis for the control of high-speed train cab noise.


2014 ◽  
Vol 638-640 ◽  
pp. 1619-1622
Author(s):  
Xian Feng Huang ◽  
Zhi Xiang Zhuang ◽  
Shang You Wei ◽  
Jun Xin Lan

Statistical energy analysis (SEA) method is an adequate tool to solve complex problems to building acoustics. This research on the application in variety of the building materials as the subsystem of SEA model is performed. For the purpose to explore the relationship between the building element and its mode, these commonly used building materials are selected to determine this relationship. It is indicated that the properties of building material have obvious effect on the modal density and modal overlap of building members. As the consequence, a useful technique to account for a building member to be appropriate for a SEA (statistical energy analysis) subsystem is presented.


2013 ◽  
Vol 423-426 ◽  
pp. 1563-1566
Author(s):  
Xiao Feng Zhang ◽  
You Gang Xiao ◽  
Yu Shi ◽  
Wu Yang Zeng

Dividing wheel-track system of subway into a series of sub-systems, the statistical energy analysis (SEA) model of wheel/track system is established. The factors affecting the wheel/track noise, such as modal density, damping loss factors, coupling loss factors, are gotten by theoretical analysis combined with experiments. The calculated results show that the track noise is about 4.5 dB(A) higher than the wheel noise at 160 km/h, and the wheel noise is reduced by 2.8 dB(A) at 160 km/h and by 2.3 dB(A) at 90 km/h by attaching damped layer plates to the wheels, but the total reduction is only 0.9 dB(A) at 160 km/h and 0.4 dB(A) at 90 km/h, so the attempts to reduce the total noise should exert noise control measures on the track, not on the wheel.


2017 ◽  
Vol 10 (6) ◽  
pp. 323
Author(s):  
Raffaella Di Sante ◽  
Marcello Vanali ◽  
Elisabetta Manconi ◽  
Alessandro Perazzolo

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