Applied Sciences (Jun 2024)

Evaluation of Noise-Reduction Techniques for Gas-Turbine Test Stands: A Preliminary Analysis

  • Laurentiu Cristea,
  • Marius Deaconu

DOI
https://doi.org/10.3390/app14135702
Journal volume & issue
Vol. 14, no. 13
p. 5702

Abstract

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Emphasizing the importance of acoustic attenuation in maintaining compliance with stringent noise regulations and enhancing workplace safety, this analysis covers theoretical and practical aspects of prediction methods used for the development of sound attenuators for gas-turbine testing stands. This paper presents a preliminary analysis and evaluation of the improvement of the Embleton method for projecting a noise attenuator for industrial applications, especially for gas-turbine test stands. While primarily focusing on the static acoustic behavior of the attenuator, certain considerations were also made regarding flow conditions, Mach number-dependent attenuation, pressure drop, and self-generated noise aspects to provide a comprehensive perspective on applying a suitable evaluation method. The study investigates different calculation methods for the assessment of noise reduction for linear and staggered baffles applied on a scaled reduced model of an attenuator. Thus, the critical parameters and development requirements necessary for effective noise reduction in high-performance gas-turbine testing environments will be evaluated in a downscaled model. Key factors examined include the selection of design parameters and configurations from various topological options (single, double, and triple parallel baffles vs. double and triple staggered baffles). Advanced computational methods, like analytic and finite-element analysis (FEM), are used to predict acoustic performance and evaluate the prediction method. Experimental validation is performed to corroborate the simulation results, ensuring the reliability and efficiency of the attenuator. The results indicate that an improved prediction method led to a better design for a sound-attenuator module, which can significantly reduce noise levels without compromising the operational performance of the gas turbine inside a test cell.

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