A high-resolution code for turbulent boundary layers

Simens, Mark P.; Jiménez, Javier; Hoyas, Sergio; Mizuno, Yoshinori

doi:10.1016/j.jcp.2009.02.031

Cited by 242 publications

(211 citation statements)

References 37 publications

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“…The numerical code uses a relatively classical fractional-step method (Kim & Moin 1985;Perot 1993) to solve the incompressible Navier-Stokes equations expressed in primitive variables. It is discussed in detail in Simens (2008) and Simens et al (2009), which also contain examples of applications to other problems. The simulation parameters are summarized in table 1.…”

Section: The Numerical Simulationmentioning

confidence: 99%

“…This was the source of several numerical difficulties, described in detail by Simens et al (2009). The result is that the initial 3OO<9 0 -4OO<9 0 « 355 99>0 -50á 99> o of the simulation domain have to be discarded.…”

Section: The Numerical Simulationmentioning

confidence: 99%

“…Of course, at least an initial washout time also has to be discarded from the boundary-layer simulation. Another necessary precaution is that the reference plane has to be located well beyond the end of the inflow region to avoid spurious feedbacks (Nikitin 2007;Simens et al 2009). In our case it is located at x re //6>o = 850 (Reg = U m 9/v = 1710).…”

Section: The Numerical Simulationmentioning

confidence: 99%

“…It is seen in figure 1(a) that the same is true for our results, which initially diverge widely from the experiments, but eventually settle into excellent agreement with them at about the same location at which the experimental scatter begins to decrease. Figure 1(a) also includes the limits of the useful region, which were determined in Simens et al (2009), in part by analogy with the tripping experiments, and in part from the arguments outlined in the previous section. The reader is referred to that work for details, but note that the tripping results suggest that the first half of that 'useful' range may retain some memory of the inflow.…”

Section: Basic Statisticsmentioning

confidence: 99%

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Turbulent boundary layers and channels at moderate Reynolds numbers

et al. 2010

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The behaviour of the velocity and pressure fluctuations in the outer layers of wall-bounded turbulent flows is analysed by comparing a new simulation of the zero-pressure-gradient boundary layer with older simulations of channels. The 99 % boundary-layer thickness is used as a reasonable analogue of the channel half-width, but the two flows are found to be too different for the analogy to be complete. In agreement with previous results, it is found that the fluctuations of the transverse velocities and of the pressure are stronger in the boundary layer, and this is traced to the pressure fluctuations induced in the outer intermittent layer by the differences between the potential and rotational flow regions. The same effect is also shown to be responsible for the stronger wake component of the mean velocity profile in external flows, whose increased energy production is the ultimate reason for the stronger fluctuations. Contrary to some previous results by our group, and by others, the streamwise velocity fluctuations are also found to be higher in boundary layers, although the effect is weaker. Within the limitations of the non-parallel nature of the boundary layer, the wall-parallel scales of all the fluctuations are similar in both the flows, suggesting that the scale-selection mechanism resides just below the intermittent region, y/S =0.3-0.5. This is also the location of the largest differences in the intensities, although the limited Reynolds number of the boundary-layer simulation (Reg «2000) prevents firm conclusions on the scaling of this location. The statistics of the new boundary layer are available from http://torroja.dmt.upm.es/ftp/blayers/.

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Section: The Numerical Simulationmentioning

confidence: 99%

Section: The Numerical Simulationmentioning

confidence: 99%

Section: The Numerical Simulationmentioning

confidence: 99%

Section: Basic Statisticsmentioning

confidence: 99%

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Turbulent boundary layers and channels at moderate Reynolds numbers

et al. 2010

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“…This restriction makes the numerical simulation of turbulent boundary layers at high Reynolds number (in the operational sense given above) extremely challenging. Recent examples of incompressible boundary layer simulations include the works of Schlatter andÖrlü 13 (up to Re τ ≈ 1200), Simens et al, 14 and Sillero et al 15 (up to Re τ ≈ 2000), which is comparable to the largest direct numerical simulation (DNS) of channel flow currently available. 16 In this paper we present novel data from turbulent boundary layer DNS, which extends the range of Reynolds number to Re τ ≈ 4000, thus meeting the constraints for the flow to be considered genuinely high-Reynolds.…”

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confidence: 94%

Probing high-Reynolds-number effects in numerical boundary layers

Pirozzoli

Bernardini

2013

Physics of Fluids

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We study the high-Reynolds-number behavior of a turbulent boundary layer in the low supersonic regime through very-large-scale direct numerical simulation (DNS). For the first time a Reynolds number is attained in DNS (Re-tau = delta/delta(v) approximate to 4000, where delta is the boundary layer thickness and delta(v) is the viscous length scale) at which theoretical predictions and experiments suggest the occurrence of phenomena pertaining to the asymptotic Reynolds number regime. From comparison with previous DNS data at lower Reynolds number we find evidence of a continuing trend toward a stronger imprint of the outer-layer structures onto the near-wall region. This effect is clearly manifested both in flow visualizations, and in energy spectra. More than a decade of nearly-logarithmic variation is observed in the mean velocity profiles, with log-law constants k approximate to 0.394, C approximate to 4.84, and a trend similar to experiments. We find some supporting evidence for the debated existence of a k(-1) region in the power spectrum of streamwise velocity fluctuations, which extends up to y(+) approximate to 150, and of a k(-5/3) spectral range in the outer layer. (C) 2013 American Institute of Physics. [http://dx.doi.org/10.1063/1.4792164

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Large‐eddy simulation of plume dispersion in a turbulent boundary layer flow generated by a dynamically controlled recycling method

Nakayama,

Takemi

2023

Atmospheric Science Letters

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When conducting large‐eddy simulations (LESs) of plume dispersion in the atmosphere, crucial issue is to prescribe time‐dependent turbulent inflow data. Therefore, several techniques for driving LESs have been proposed. For example, in the original recycling (OR) method developed by Kataoka and Mizuno (Wind and Structures, 2002, 5, 379–392), a mean wind profile is prescribed at the inlet boundary, the only fluctuating components extracted at the downstream position are recycled to the inlet boundary. Although the basic turbulence characteristics are reproduced with a short development section, it is difficult to generate target turbulent fluctuations consistent with realistic atmospheric turbulence. In this study, we proposed a dynamically controlled recycling (DCR) method that is a simple extension of the OR procedure. In this method, the magnitude of turbulent fluctuations is dynamically controlled to match with the target turbulent boundary layer (TBL) flow using a turbulence enhancement coefficient based on the ratio of the target turbulence statistics to the computed ones. When compared to the recommended data of Engineering Science Data Unit (ESDU) 85020, the turbulence characteristics generated by our proposed method were quantitatively reproduced well. Furthermore, the spanwise and vertical plume spreads were also simulated well. It is concluded that the DCR method successfully simulates plume dispersion in neutral TBL flows.

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A high-resolution code for turbulent boundary layers

Cited by 242 publications

References 37 publications

Turbulent boundary layers and channels at moderate Reynolds numbers

Turbulent boundary layers and channels at moderate Reynolds numbers

Probing high-Reynolds-number effects in numerical boundary layers

Large‐eddy simulation of plume dispersion in a turbulent boundary layer flow generated by a dynamically controlled recycling method

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