2 resultados para Forcing terms

em Digital Commons - Michigan Tech


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From the customer satisfaction point of view, sound quality of any product has become one of the important factors these days. The primary objective of this research is to determine factors which affect the acceptability of impulse noise. Though the analysis is based on a sample impulse sound file of a Commercial printer, the results can be applied to other similar impulsive noise. It is assumed that impulsive noise can be tuned to meet the accepTable criteria. Thus it is necessary to find the most significant factors which can be controlled physically. This analysis is based on a single impulse. A sample impulsive sound file is tweaked for different amplitudes, background noise, attack time, release time and the spectral content. A two level factorial design of experiments (DOE) is applied to study the significant effects and interactions. For each impulse file modified as per the DOE, the magnitude of perceived annoyance is calculated from the objective metric developed recently at Michigan Technological University. This metric is based on psychoacoustic criteria such as loudness, sharpness, roughness and loudness based impulsiveness. Software called ‘Artemis V11.2’ developed by HEAD Acoustics is used to calculate these psychoacoustic terms. As a result of two level factorial analyses, a new objective model of perceived annoyance is developed in terms of above mentioned physical parameters such as amplitudes, background noise, impulse attack time, impulse release time and the spectral content. Also the effects of the significant individual factors as well as two level interactions are also studied. The results show that all the mentioned five factors affect annoyance level of an impulsive sound significantly. Thus annoyance level can be reduced under the criteria by optimizing the levels. Also, an additional analysis is done to study the effect of these five significant parameters on the individual psychoacoustic metrics.

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This study focuses on a specific engine, i.e., a dual-spool, separate-flow turbofan engine with an Interstage Turbine Burner (ITB). This conventional turbofan engine has been modified to include a secondary isobaric burner, i.e., ITB, in a transition duct between the high-pressure turbine and the low-pressure turbine. The preliminary design phase for this modified engine starts with the aerothermodynamics cycle analysis is consisting of parametric (i.e., on-design) and performance (i.e., off-design) cycle analyses. In parametric analysis, the modified engine performance parameters are evaluated and compared with baseline engine in terms of design limitation (maximum turbine inlet temperature), flight conditions (such as flight Mach condition, ambient temperature and pressure), and design choices (such as compressor pressure ratio, fan pressure ratio, fan bypass ratio etc.). A turbine cooling model is also included to account for the effect of cooling air on engine performance. The results from the on-design analysis confirmed the advantage of using ITB, i.e., higher specific thrust with small increases in thrust specific fuel consumption, less cooling air, and less NOx production, provided that the main burner exit temperature and ITB exit temperature are properly specified. It is also important to identify the critical ITB temperature, beyond which the ITB is turned off and has no advantage at all. With the encouraging results from parametric cycle analysis, a detailed performance cycle analysis of the identical engine is also conducted for steady-stateengine performance prediction. The results from off-design cycle analysis show that the ITB engine at full throttle setting has enhanced performance over baseline engine. Furthermore, ITB engine operating at partial throttle settings will exhibit higher thrust at lower specific fuel consumption and improved thermal efficiency over the baseline engine. A mission analysis is also presented to predict the fuel consumptions in certain mission phases. Excel macrocode, Visual Basic for Application, and Excel neuron cells are combined to facilitate Excel software to perform these cycle analyses. These user-friendly programs compute and plot the data sequentially without forcing users to open other types of post-processing programs.