Adjoint-based pressure determination from PIV data in compressible flows — Validation and assessment based on synthetic data

Lemke, Mathias; Sesterhenn, Jörn

doi:10.1016/j.euromechflu.2016.03.006

Cited by 23 publications

(11 citation statements)

References 17 publications

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“…Scarano and Moore's idea was later also generalized to volumes [11]. The demand of such an increase in temporal resolution has shown to be very important for the extraction of pressure gradients from PIV data where the acceleration must be known precisely [12][13][14][15] or as an input for simulations [16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Hybrid time series from PIV for characterization of turbulent flow fields: ASTRA -- Approach using Spatially and Temporally Resolved Advection

Wester¹,

Fuchs²,

Peinke³

et al. 2021

Preprint

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Particle Image Velocimetry (PIV) has become increasingly popular to study structures in turbulent flows. PIV allows direct extraction and investigation of spatial structures in the given flow field. Increasing temporal resolution of PIV systems allows a more accurate capture of the flow evolution. Despite the very good spatial resolution of PIV, current systems can only match the multiple kHz sampling rates of hot-wire or Laser Doppler Anemometer (LDA) measurements for a very short period in temporal analyses of flow. In this study, an advection-based approach is presented which uses Taylor's hypothesis of "frozen turbulence" for small scale turbulent patterns. Compared to the underlying raw data a major increase of the temporal resolution for extracted time series is shown. The quality of the presented approach is shown for two-point analyses, which would not be possible with presently known methods. To demonstrate this, different turbulent flow cases behind a fractal grid are studied. For the validation of the results corresponding hot-wire measurements at various positions along the centerline were used.

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Section: Introductionmentioning

confidence: 99%

Hybrid time series from PIV for characterization of turbulent flow fields: ASTRA -- Approach using Spatially and Temporally Resolved Advection

Wester¹,

Fuchs²,

Peinke³

et al. 2021

Preprint

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show abstract

“…Notable examples in this direction are represented by the work of Foures et al [17] and Symon et al [18], where a variational data assimilation framework for low Reynolds number mean flow reconstruction using a vectorial forcing term in the RANS equations as control parameter was developed. A similar control parameter was also adopted by Lemke and Sesterhen [19], who also assimilated the initial and non-reflecting boundary conditions of simple unsteady flows. Mons et al [20] developed a data assimilation framework for viscous flow at low Reynolds number which was able to tune the unsteady initial and inflow conditions.…”

Section: Introductionmentioning

confidence: 99%

Assessment of a Data Assimilation Technique for Wind Tunnel Wall Interference Corrections

Belligoli

Dwight

Eitelberg

2019

AIAA Scitech 2019 Forum

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“…It should be remarked that the problem of supersampling measurement data has also been approached with more complex methods that take further into account the non-linear dynamics in the temporal evolution of the velocity field. In this respect, several methods have been proposed that use a variational approach to assimilate data from measurements and numerical simulations (Suzuki et al 2009;Cuzol and Mémin 2009;Lemke and Sesterhenn 2016;Yegavian et al 2015;Gesemann et al 2016). Such variational approaches have proven to be successful in increasing the spatial resolution of three-dimensional time-resolved measurements Gesemann et al 2016;Schneiders et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Pressure spectra from single-snapshot tomographic PIV

et al. 2018

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The power spectral density and coherence of temporal pressure fluctuations are obtained from low-repetition-rate tomographic PIV measurements. This is achieved by extension of recent single-snapshot pressure evaluation techniques based upon the Taylor's hypothesis (TH) of frozen turbulence and vortex-in-cell (VIC) simulation. Finite time marching of the measured instantaneous velocity fields is performed using TH and VIC. Pressure is calculated from the resulting velocity time series. Because of the theoretical limitations, the finite time marching can be performed until the measured flow structures are convected out of the measurement volume. This provides a lower limit of resolvable frequency range. An upper limit is given by the spatial resolution of the measurements. Finite time-marching approaches are applied to low-repetition-rate tomographic PIV data of the flow past a straight trailing edge at 10 m/s. Reference results of the power spectral density and coherence are obtained from surface pressure transducers. In addition, the results are compared to state-of-the-art experimental data obtained from time-resolved tomographic PIV performed at 10 kHz. The time-resolved approach suffers from low spatial resolution and limited maximum acquisition frequency because of hardware limitations. Additionally, these approaches strongly depend upon the time kernel length chosen for pressure evaluation. On the other hand, the finite timemarching approaches make use of low-repetition-rate tomographic PIV measurements that offer higher spatial resolution. Consequently, increased accuracy of the power spectral density and coherence of pressure fluctuations are obtained in the high-frequency range, in comparison to the time-resolved measurements. The approaches based on TH and VIC are found to perform similarly in the high-frequency range. At lower frequencies, TH is found to underestimate coherence and intensity of the pressure fluctuations in comparison to time-resolved PIV and the microphone reference data. The VIC-based approach, on the other hand, returns results on the order of the reference.

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Adjoint-based pressure determination from PIV data in compressible flows — Validation and assessment based on synthetic data

Cited by 23 publications

References 17 publications

Hybrid time series from PIV for characterization of turbulent flow fields: ASTRA -- Approach using Spatially and Temporally Resolved Advection

Hybrid time series from PIV for characterization of turbulent flow fields: ASTRA -- Approach using Spatially and Temporally Resolved Advection

Assessment of a Data Assimilation Technique for Wind Tunnel Wall Interference Corrections

Pressure spectra from single-snapshot tomographic PIV

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