All issues

The Fourier transformation is the basic tool for evaluating the spectral characteristics of a turbulent flow. The Fourier transform (usually discrete) of the first power of the longitudinal or transverse component of the velocity vector pulsations allows estimation of the energy spectral density (ESD) or power spectral density (PSD). To estimate the ESD and PSD of a turbulent signal obtained from numerical simulation, an array of signal values with discretization in the time or spatial domain is generated. The reference distribution of the ESD spectrum (scaling law) within the wave number domain of the inertial subrange is derived from two hypotheses proposed by A.N. Kolmogorov and is characterized by the $−\frac{5}{3}$ law. The $-\frac{5}{3}$ law is also used in most references to estimate the ESD distribution in the frequency domain. The distribution of the power spectrum PSD is derived from the distribution of the energy spectrum ESD by normalizing to the signal scanning time. An alternative energy spectral characteristic (ESS) of velocity fluctuations can be determined by the Fourier transform of the square of the velocity fluctuations. In the wave numbers domain, the dimension of ESS in the spatial domain coincides with the dimension of A.N. Kolmogorov's $−\frac{5}{3}$ law. When considering a signal sampled in the time domain, a scaling law of $−2$ for ESS was previously obtained in the frequency domain. An alternative estimate of the Power Signal Spectrum (PSS) is discussed in this paper based on the Fourier transform of the third-order velocity pulsations. Based on the hypotheses proposed by A.N.Kolmogorov, it can be inferred that in the frequency domain, the scaling law of the PSS spectrum is characterized by the power of $−\frac{5}{2}$. Unsteady incompressible flow around a 3D cylindrical surface section at the Reynolds number of 3900 is considered as an application. The numerical simulation is performed using ANSYS Fluent commercial code and based on the Navier – Stokes equations. The spatio-temporal characteristics of the turbulent flow velocity vector are analyzed using the Proper Orthogonal Decomposition (POD). The Fourier transform is used to estimate the ESS and PSS of a time-sampled signal.

Atherosclerotic diseases such as carotid artery diseases (CAD) and chronic kidney diseases (CKD) are the major causes of death worldwide. The onset of these atherosclerotic diseases in the arteries are governed by complex blood flow dynamics and hemodynamic parameters. Atherosclerosis in renal arteries leads to reduction in arterial efficiency, which ultimately leads to Reno-vascular hypertension. This work attempts to identify the localization of atherosclerotic plaque in human abdominal aorta — renal artery junction using Computational fluid dynamics (CFD).

The atherosclerosis prone regions in an idealized human abdominal aorta-renal artery junction are identified by calculating relevant hemodynamic indicators from computational simulations using the rheologically accurate shear-thinning Yeleswarapu model for human blood. Blood flow is numerically simulated in a 3-D model of the artery junction using ANSYS FLUENT v18.2.

Hemodynamic indicators calculated are average wall shear stress (AWSS), oscillatory shear index (OSI), and relative residence time (RRT). Simulations of pulsatile flow (f=1.25 Hz, Re = 1000) show that low AWSS, and high OSI manifest in the regions of renal artery downstream of the junction and on the infrarenal section of the abdominal aorta lateral to the junction. High RRT, which is a relative index and dependent on AWSS and OSI, is found to overlap with the low AWSS and high OSI at the cranial surface of renal artery proximal to the junction and on the surface of the abdominal aorta lateral to the bifurcation: this indicates that these regions of the junction are prone to atherosclerosis. The results match qualitatively with the findings reported in literature and serve as initial step to illustrate utility of CFD for the location of atherosclerotic plaque.

This paper is devoted to investigation of the swirl flows. Such flows are widely used in various industrial processes. Swirl flows can be accompanied by time-dependent effects, for example, precession of the vortex core. In turn, the large-scale fluctuations due to the precession of the vortex can cause damage of structures and reduce of equipment reliability. Thus, for engineering calculations approaches that sufficiently well described such flows are required. This paper presents the technique of swirl flows calculation, tested for CFD packages Fluent and SigmaFlow. A numerical simulation of several swirl flow test problems was carried out. Obtained results are compared with each other and with the experimental data.

The gas-dynamics approach to the calculation of the aerodynamic characteristics of modern aircraft makes it necessary to consider the complex and extensive set of tasks requiring the development of new methods for their solution. Drag coefficient for two bodies in subsonic and transonic flow regimes was calculated using ANSYS Fluent software. Numeric solution and results of the experiment are in good agreement; calculation error does not exceed 3 %.