Computational and Experimental Assessment of Models for the First AIAA Sonic Boom Prediction Workshop

Cliff, Susan E.; Durston, Donald A.; Chan, William; Elmiligui, Alaa A.; Moini-Yekta, Shayan; Sozer, Emre; Jensen, James C.

doi:10.2514/6.2014-0560

Cited by 17 publications

(30 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Configurations were placed on a linear actuator within the tunnel and the model was translated either in the X-direction (into the flow) or in the Z-direction (away from the pressure rail) and measurements were taken during sweeps of the model. Further detail regarding the experimental testing is given by Cliff et al 2 The three geometries used in this study are shown in Figure 1. The SEEB-ALR model (left) is recognized by a flat-top signature, leaving flow-field variations easy to identify.…”

Section: A Experimental Setupmentioning

confidence: 99%

“…This particular feature of this dispersion model helps to improve the rounding of the signature peaks observed in the experimental measurement results. 2 In order to apply this dispersion approach, the order of the Fourier series must be determined. A spectral analysis, using a fast Fourier transform (FFT) of the nominal signature, can highlight those frequencies that carry the most energy in the signature.…”

Section: B Fourier Dispersionmentioning

confidence: 99%

See 1 more Smart Citation

Sonic Boom Pressure Signature Uncertainty Calculation and Propagation to Ground Noise (Invited)

West

Bretl

Walker

et al. 2015

53rd AIAA Aerospace Sciences Meeting

View full text Add to dashboard Cite

The objective of this study was to outline an approach for the quantification of uncertainty in sonic boom measurements and to investigate the effect of various near-field uncertainty representation approaches on ground noise predictions. These approaches included a symmetric versus asymmetric uncertainty band representation and a dispersion technique based on a partial sum Fourier series that allows for the inclusion of random error sources in the uncertainty. The near-field uncertainty was propagated to the ground level, along with additional uncertainty in the propagation modeling. Estimates of perceived loudness were obtained for the various types of uncertainty representation in the near-field. Analyses were performed on three configurations of interest to the sonic boom community: the SEEB-ALR, the 69 o Delta Wing, and the LM 1021-01. Results showed that representation of the near-field uncertainty plays a key role in ground noise predictions. Using a Fourier series based dispersion approach can double the amount of uncertainty in the ground noise compared to a pure bias representation. Compared to previous computational fluid dynamics results, uncertainty in ground noise predictions were greater when considering the near-field experimental uncertainty.Bias Limit g i = Dispersion Function U = Uncertainty Magnitude u − = Lower Uncertainty Bound u + = Upper Uncertainty Bound ∆u − = Lower Uncertainty Increment ∆u + = Upper Uncertainty Increment U = Uncertainty Magnitude P = Pressure = Uncertainty Factor N = Partial Fourier Series Order a k , b k , h k = Fourier Expansion Coefficients ∆x = Phase Uncertainty

show abstract

Section: A Experimental Setupmentioning

confidence: 99%

Section: B Fourier Dispersionmentioning

confidence: 99%

Sonic Boom Pressure Signature Uncertainty Calculation and Propagation to Ground Noise (Invited)

West

Bretl

Walker

et al. 2015

53rd AIAA Aerospace Sciences Meeting

View full text Add to dashboard Cite

show abstract

“…The geometry differences between the as-designed and as-built are summarized by Cliff et al 35 , Aftosmis and Nemec. 36 The model has a reference length of L= 17.68 in. This axisymmetric calibration model should theoretically produce a flat top pressure signature with an 8-inch region of constant pressure.…”

Section: B Seeb-alr Modelmentioning

confidence: 99%

“…The unit Reynolds number provided to the SBPW-1 workshop was 2.12E5 per inch, whereas the wind tunnel unit Reynolds number was 3.75E5 per inch, 13,36 the increase in Reynolds number resulted in improved measurement accuracy and productivity, so in present simulation we set the Reynolds number as 3.75E5.…”

Section: (A) Geometry Of Lm1021 Model (B) Computation Zone and Extracmentioning

confidence: 99%

Near Field Sonic Boom Analysis with HUNS3D Solver

Wang

Ren

et al. 2017

55th AIAA Aerospace Sciences Meeting

View full text Add to dashboard Cite

Accurate analysis of sonic boom pressure signature using Computational Fluid Dynamics (CFD) is still a challenging task. In this paper, four benchmark cases including two axisymmetric body, a simple delta wing body and a full configuration includes fuselage, wing, tail, flow-through nacelles, and blade wing were computed with a Reynold-averaged Navier-Stokes (RANS) based flow solver to predicted the near field sonic boom signature. The computed results from CFD agree well with the measured data in wind tunnel experiment. The effects of geometry equivalent radius, grid size, turbulence model and spatial discretization schemes are investigated and discussed. I.

show abstract

“…In order to compare the both aerodynamic characteristic and flow field between the basic configuration and optimized configuration, the numerical simulation was done. The computation domain was composed of two parts as shown in Figure 14: a cylinder domain at the inner part with non-aligned volume mesh and a mach cone domain around the cylinder with aligned anisotropic cells [14]. The Euler equation was solved for the basic configuration and optimized configuration.…”

Section: Numerical Simulation Of the Supersonic Business Jet Configurmentioning

confidence: 99%

The Research of Supersonic Aircraft Low Sonic Boom Configuration Design and Optimizations

Huang¹,

Cheng²

2016

J Aeronaut Aerospace Eng

View full text Add to dashboard Cite

High noise level of sonic boom is one of the most important reasons that the supersonic transport can't be applied to civil aviation broadly. Sonic boom is a complicated problem relating to aircraft configuration design, aerodynamics, acoustics and so on. The traditional sonic boom minimization theory is an inverse design method with single object, which makes it difficult to be applied in multi-objective optimization, effectively. For the low sonic boom configuration optimization, the sonic boom noise level prediction method based on supersonic linear theory was developed. The sonic boom level of a basic configuration of supersonic business jet was computed and the cause of formation of sonic boom was analyzed, based on which the fuse and wing plane wais optimized to decrease the noise level of sonic boom. Compared with the basic configuration, the sonic boom level of optimized configuration decreased distinctively, with the overpressure decreasing 41% and the A-weighted noise level decreasing 7.55 decibel. The aerodynamic characteristics of optimized configuration were computed. Compared with the basic configuration, the drag decreased obviously at the cruise condition without moment change.

show abstract

Computational and Experimental Assessment of Models for the First AIAA Sonic Boom Prediction Workshop

Cited by 17 publications

References 31 publications

Sonic Boom Pressure Signature Uncertainty Calculation and Propagation to Ground Noise (Invited)

Sonic Boom Pressure Signature Uncertainty Calculation and Propagation to Ground Noise (Invited)

Near Field Sonic Boom Analysis with HUNS3D Solver

The Research of Supersonic Aircraft Low Sonic Boom Configuration Design and Optimizations

Contact Info

Product

Resources

About