Optimization of a Seamless Inlet Liner Using an Empirically Validated Prediction Method

Schuster, Bill; Lieber, Lysbeth; Vavalle, Armando

doi:10.2514/6.2010-3824

Cited by 8 publications

(7 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, for the BPF case considered, the m = 22 circumferential mode should receive increased weighting (since, again, the fan has 22 blades). This is further illustrated in the work by Schuster,10 in which source modal decomposition shows the m = 21 through m = 24 circumferential modes to be dominant. The presence of the additional circumferential modes may be a result of Tyler-Sofrin type interactions a between the m = 22 mode and the single probe mounted in the nacelle (as seen in the figure 2).…”

Section: Resultsmentioning

confidence: 93%

“…The Mach number profiles were the result of iterative calculations in which the source plane Mach number was adjusted to approximate Mach number values used in the aforementioned seamless liner optimization effort. 10 As presented in figure 4, this translated to source plane Mach number values of M = 0.38 and M = 0.60 for 54% and 87% N1C, respectively. It should be noted that these Mach number profile approximations affect source and in-duct acoustic content and are a source of uncertainty in the prediction inputs.…”

Section: Prediction Code Descriptionmentioning

confidence: 98%

“…Slightly differing values for the acoustic liner impedance are found in the EVNERT report 6 and optimization study of Schuster. 10 However, the latter included plots of acoustic resistance and reactance at both engine speed settings of interest. From these plots, normalized acoustic impedance values of ζ 54% = (1, −1) and ζ 87% = (2, 0) were assumed for the 54% and 87% engine speed settings, respectively.…”

Section: Prediction Code Descriptionmentioning

confidence: 99%

“…in a previous seamless liner optimization effort for the same TECH977 engine. 10 As mentioned previously, predictions were performed for all hardwall and lined configurations to exercise the three-dimensional capability of CDUCT-LaRC. For this example calculation, and subsequent results presented, the internal computational domain consisted of (65x181x97) points in the radial, circumferential, and axial directions, respectively.…”

Section: Prediction Code Descriptionmentioning

confidence: 99%

See 3 more Smart Citations

Assessment of Radiated Fan Noise Prediction Capabilities using Static Engine Test Data

Nark

2011

17th AIAA/CEAS Aeroacoustics Conference (32nd AIAA Aeroacoustics Conference)

View full text Add to dashboard Cite

This paper describes further assessment of the CDUCT-LaRC code via comparison with static engine test data. In an effort to improve confidence in the use of CDUCT-LaRC for liner optimization studies addressing realistic three-dimensional geometries, inlet radiated fan noise predictions were performed at 54% and 87% engine speed settings. Predictions were then compared with far-field measurements to assess the approach and implementation. The particular configurations were chosen to exercise the three-dimensional capability of CDUCT-LaRC and it's applicability to realistic configurations and conditions. At the 54% engine speed setting, the predictions capture the general directivity and acoustic treatment effects quite well. Comparisons of the predicted and measured directivity at the 87% power setting were more problematic. This was likely due in part to the difficulties in source specification and possibly the nonlinear nature of buzz-saw tones at this engine operating condition. Overall, the approach captured the basic trends and provided a conservative estimate of liner effects from which relative performance metrics could be inferred.

show abstract

Section: Resultsmentioning

confidence: 93%

Section: Prediction Code Descriptionmentioning

confidence: 98%

Section: Prediction Code Descriptionmentioning

confidence: 99%

Section: Prediction Code Descriptionmentioning

confidence: 99%

See 2 more Smart Citations

Assessment of Radiated Fan Noise Prediction Capabilities using Static Engine Test Data

Nark

2011

17th AIAA/CEAS Aeroacoustics Conference (32nd AIAA Aeroacoustics Conference)

View full text Add to dashboard Cite

show abstract

“…In conjunction with this trend, a number of fan noise prediction assessments have provided valuable insights into improved fan noise propagation/radiation prediction with limited fan source information. 1,2,3 Advanced manufacturing techniques have also opened new possibilities for the practical implementation of broadband liner concepts. 4 With these observations in mind, a broadband acoustic liner optimization study for a benchmark scale model fan is pursued.…”

Section: Introductionmentioning

confidence: 99%

Broadband Liner Optimization for the Source Diagnostic Test Fan

Nark

Jones

2012

18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference)

View full text Add to dashboard Cite

The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more appealing. This paper describes a broadband acoustic liner optimization study for the scale model Source Diagnostic Test fan. Specifically, in-duct attenuation predictions with a statistical fan source model are used to obtain optimum impedance spectra over a number of flow conditions for three liner locations in the bypass duct. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Typical tonal liner designs targeting single frequencies at one operating condition are first produced to provide baseline performance information. These are followed by multiple broadband design approaches culminating in a broadband liner targeting the full range of frequencies and operating conditions. The broadband liner is found to satisfy the optimum impedance objectives much better than the tonal liner designs. In addition, the broadband liner is found to provide better attenuation than the tonal designs over the full range of frequencies and operating conditions considered. Thus, the current study successfully establishes a process for the initial design and evaluation of novel broadband liner concepts for complex engine configurations.

show abstract

Algorithms and analyses for stochastic optimization for turbofan noise reduction using parallel reduced-order modeling

Yang

Gunzburger

2017

Computer Methods in Applied Mechanics and Engineering

View full text Add to dashboard Cite

Simulation-based optimization of acoustic liner design in a turbofan engine nacelle for noise reduction purposes can dramatically reduce the cost and time needed for experimental designs. Because uncertainties are inevitable in the design process, a stochastic optimization algorithm is posed based on the conditional value-at-risk measure so that an ideal acoustic liner impedance is determined that is robust in the presence of uncertainties. A parallel reduced-order modeling framework is developed that dramatically improves the computational efficiency of the stochastic optimization solver for a realistic nacelle geometry. The reduced stochastic optimization solver takes less than 500 seconds to execute. In addition, well-posedness and finite element error analyses of the state system and optimization problem are provided.

show abstract

Optimization of a Seamless Inlet Liner Using an Empirically Validated Prediction Method

Cited by 8 publications

References 3 publications

Assessment of Radiated Fan Noise Prediction Capabilities using Static Engine Test Data

Assessment of Radiated Fan Noise Prediction Capabilities using Static Engine Test Data

Broadband Liner Optimization for the Source Diagnostic Test Fan

Algorithms and analyses for stochastic optimization for turbofan noise reduction using parallel reduced-order modeling

Contact Info

Product

Resources

About