Authors
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Maxim Bobrov
"Institute of Thermophysics SB RAS, Russian Federation; Novosibirsk State University, Russian Federation"
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Mikhail Hrebtov
"Institute of Thermophysics SB RAS, Russian Federation; Novosibirsk State University, Russian Federation"
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Vladislav Ivashchenko
Institute of Thermophysics SB RAS, Russian Federation
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Rustam Mullyadzhanov
"Institute of Thermophysics SB RAS, Russian Federation; Novosibirsk State University, Russian Federation"
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Alexander Seredkin
"Institute of Thermophysics SB RAS, Russian Federation; Novosibirsk State University, Russian Federation"
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Mikhail Tokarev
"Institute of Thermophysics SB RAS, Russian Federation; Novosibirsk State University, Russian Federation"
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Dinar Zaripov
"Institute of Thermophysics SB RAS, Russian Federation; School of Mechanical Science and Engineering, Huazhong University of Science and Technology, China"
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Vladimir Dulin
"Institute of Thermophysics SB RAS, Russian Federation; Novosibirsk State University, Russian Federation"
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Dmitriy Markovich
"Institute of Thermophysics SB RAS, Russian Federation; Novosibirsk State University, Russian Federation"
Abstract
Lagrangian particle tracking Shake-the-box (STB) method (Schanz et al., 2016) acquires the 3D positions of tracer particles from the temporal sequences of their 2D projection images even for rather high seeding densities. Approximation of tracks by analytical functions (Gesemann, 2015) provides an accurate evaluation of tracers’ local velocity and acceleration. This data, which is obtained on non-regular grid, can be used to estimate local pressure fluctuations based on the Navier–Stokes equation. The present paper describes a grid-free least-squares method for the gradients and pressure evaluation based on irregularly scattered LPT data with random noise minimization.
Section
Pressure and Force
License
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