Monte Carlo Filtering (MCF) is one of the methods of Experimental Statistical Energy Analysis (E-SEA), which allows the correction of negative LFs (Loss Factors). In this article, a modification of the MCF method, called DESA (Diagonal Expansion of the Search Area), is proposed. The technique applies a non-uniform extension of the search area when generating a population of normalized energy matrices. The degree of expansion of the search area is controlled by the Diagonal Penalty Factor (DPF). The authors demonstrated the method’s effectiveness on a system that could not be identified in several frequency bands by the classical MCF method. After applying DESA, it was possible to fill in the problematic bands that were missing CLF (coupling loss factor) and DLF (damping loss factor) values. The paper also proposes a way to minimize the errors introduced by using overly high DPF values.
Monte Carlo Filtering (MCF) is one of the methods of Experimental Statistical Energy Analysis (E-SEA), which allows the correction of a negative LF (Loss Factor). In this article, a modification of the MCF method, called DESA (Diagonal Extension of the Search Area), is proposed. The technique applies a non-uniform extension of the search area when generating a population of normalized energy matrices. The degree of expansion of the search area is controlled by the Diagonal Penalty Factor (DPF). The authors demonstrated the method's effectiveness on a system that could not be identified in several frequency bands by the classical MCF method. After applying DESA, it was possible to fill in the problematic bands that were missing CLF and DLF values. The paper also proposes a way to minimize the errors introduced by using overly high DPF values.
Dissipative splitter silencers are widely used in industry for the reduction of propagated sound waves in ducts. Even though these systems are effective from the acoustics point of view when they are properly designed, they also introduce a pressure loss in the system, due to the modification of the properties of the flow circulating inside the duct. This effect is not desired in some industrial applications, so it is necessary to be able to predict the pressure loss as precisely as possible to design silencers according to the needs. Nevertheless, the prediction made by standards are usually limited to given geometries or flow speed. In this work, we present a comparative study on the results obtained for the pressure loss by means of the standards ISO 14163 and VDI 1801-1, numerical simulations with the finite element method, and experimental measurements. Additionally, two different profile shapes and four input face velocities are tested in order to know the influence of these parameters in the variations of the flow and the accuracy of the prediction of the different methods.
Baffle silencers are a well-known solution for noise mitigation in industrial applications. One of the issues concerning these devices is the flow-inducted noise produced when a non-laminar flow of the medium in the duct occurs. These situations occur, for example, in dedusting installations or exhaust systems with the high-speed flow (large Reynolds number of the turbulence and small Mach number). This kind of installation has a complex shape that causes a turbulent flow in the medium. Installing a baffle silencer in these conditions causes additional noise. This noise cannot be predicted by using a standard approach with equations for laminar flow conditions. This paper presents the first step of the research in this field. The first step is to find a relation between CFD simulations' results and self-noise of the baffle silencer. In this work, we use the formulation proposed by Proudman in 1952 to calculate the sound power generated by the flow. The formulation is based on the turbulent kinetic energy k and dissipation rate ε of the flow, which is calculated by CFD simulations. The resulting sound power level needs to be calibrated. The calibration method is developed and presented. The aim of this research is to design an experimental setup.
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