Abstract

The Center for Reference on Gas Turbines (CRTG), at the Technological Institute of Aeronautics, carries out research in relevant areas of gas turbines, to provide the support for teaching and the ability to design high performance gas turbines. Noise prediction, by means of theoretical and empirical methods, is among such areas. Emphasis is given to the prediction of noise from new engines, to anticipate problems at very early design stage and to take the necessary actions to guarantee that the engine noise is below the recommended limits. Noise prediction is part of a high fidelity gas turbine performance prediction computer program, which provides the designer, at any time during the design phases, with information on the noise levels generated by each component and by the engine. This paper presents results obtained with such methodology incorporated to the high fidelity engine performance prediction computer code, and in the format usually used in the literature. The SPL — far-field one-third octave band sound pressure level — and the OASPL — overall sound pressure level — for single-stream jet were calculated for several engine rotational speeds and observer positions. Two methods have been for the single-stream jet noise prediction, namely: ESDU item 98019 and SAE ARP 876D. Nozzle details were taken from a 5 kN turbojet engine, designed at the CRTG, and which is being installed in the test rig for the preliminary evaluation. In this paper the influence of the observer position on the calculated SPL is presented, and the corresponding OASPL for steady engine operation, combined with the effect of the engine rotational speeds on exhaust jet noise. It is shown that they are in agreement with the noise of similar operating conditions. Ground reflection and atmospheric attenuation were not considered in this work. The results indicate that the noise prediction is adequate for use during the design phase and that the model derived in the SAE ARP 876D paper provides better single-stream jet noise prediction than ones predicted using the ESDU Item 98019.

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