Application of Proper Orthogonal Decomposition to Study Coherent Flow Structures in a Saccular Aneurysm

2021 ◽  
Vol 143 (6) ◽  
Author(s):  
Paulo Yu ◽  
Vibhav Durgesh ◽  
Tao Xing ◽  
Ralph Budwig
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Flow Structures ◽  
Complex Flow ◽  
Order Reconstruction ◽  
Proper Orthogonal ◽  
The Impact ◽  
Inflow Conditions ◽  
Aneurysm Model ◽  
Low Order

Abstract Aneurysms are localized expansions of weakened blood vessels that can be debilitating or fatal upon rupture. Previous studies have shown that flow in an aneurysm exhibits complex flow structures that are correlated with its inflow conditions. Therefore, the objective of this study was to demonstrate the application of proper orthogonal decomposition (POD) to study the impact of different inflow conditions on energetic flow structures and their temporal behavior in an aneurysm. To achieve this objective, experiments were performed on an idealized rigid sidewall aneurysm model. A piston pump system was used for precise inflow control, i.e., peak Reynolds number (Rep) and Womersley number (α) were varied from 50 to 270 and 2 to 5, respectively. The velocity flow field measurements at the midplane location of the idealized aneurysm model were performed using particle image velocimetry (PIV). The results demonstrate the efficacy of POD in decomposing complex data, and POD was able to capture the energetic flow structures unique to each studied inflow condition. Furthermore, the time-varying coefficient results highlighted the interplay between the coefficients and their corresponding POD modes, which in turn helped explain how POD modes impact certain flow features. The low-order reconstruction results were able to capture the flow evolution and provide information on complex flow in an aneurysm. The POD and low-order reconstruction results also indicated that vortex formation, evolution, and convection varied with an increase in α, while vortex strength and formation of secondary structures were correlated with an increase in Rep.

Modeling the Turbulent Wake Behind a Wall-Mounted Square Cylinder

2020 ◽  
Author(s):  
Christian Amor ◽  
José M Pérez ◽  
Philipp Schlatter ◽  
Ricardo Vinuesa ◽  
Soledad Le Clainche
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Turbulent Wake ◽  
Orthogonal Decomposition ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
Square Cylinder ◽  
Complex Flow ◽  
Reduced Order ◽  
Mode Decomposition ◽  
Proper Orthogonal

Abstract This article introduces some soft computing methods generally used for data analysis and flow pattern detection in fluid dynamics. These techniques decompose the original flow field as an expansion of modes, which can be either orthogonal in time (variants of dynamic mode decomposition), or in space (variants of proper orthogonal decomposition) or in time and space (spectral proper orthogonal decomposition), or they can simply be selected using some sophisticated statistical techniques (empirical mode decomposition). The performance of these methods is tested in the turbulent wake of a wall-mounted square cylinder. This highly complex flow is suitable to show the ability of the aforementioned methods to reduce the degrees of freedom of the original data by only retaining the large scales in the flow. The main result is a reduced-order model of the original flow case, based on a low number of modes. A deep discussion is carried out about how to choose the most computationally efficient method to obtain suitable reduced-order models of the flow. The techniques introduced in this article are data-driven methods that could be applied to model any type of non-linear dynamical system, including numerical and experimental databases.

Experimental Study of Large-Scale Flow Structures in an Aneurysm

2018 ◽  
Author(s):  
Paulo Yu ◽  
Vibhav Durgesh
Keyword(s):  
Large Scale ◽  
Flow Structures ◽  
Pump System ◽  
Vortical Structures ◽  
Abnormal Growth ◽  
Image Velocimetry ◽  
Large Scale Flow ◽  
The Impact ◽  
Inflow Conditions ◽  
Aneurysm Model

An aneurysm is an abnormal growth in the wall of a weakened blood vessel, and can often be fatal upon rupture. Studies have shown that aneurysm shape and hemodynamics, in conjunction with other parameters, play an important role in growth and rupture. The objective of this study was to investigate the impact of varying inflow conditions on flow structures in an aneurysm. An idealized rigid sidewall aneurysm model was prepared and the Womersley number (α) and Reynolds number (Re) values were varied from 2 to 5 and 50 to 250, respectively. A ViVitro Labs pump system was used for inflow control and Particle Image Velocimetry was used for conducting velocity measurements. The results showed that the primary vortex path varied with an increase in α, while an increase in Re was correlated to the vortex strength and formation of secondary vortical structures. The evolution and decay of vortical structures were also observed to be dependent on α and Re.

Analysis of Unsteady Flow Structures in a Radial Turbomachine by Using Proper Orthogonal Decomposition

2018 ◽  
Author(s):  
Matthias Witte ◽  
Benjamin Torner ◽  
Frank-Hendrik Wurm
Keyword(s):  
Flow Field ◽  
Unsteady Flow ◽  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Mode Shapes ◽  
Flow Structures ◽  
Periodic Flow ◽  
Noise Emission ◽  
Turbulent Flow Field ◽  
Proper Orthogonal

Tonalities in hydro and airborne noise emission are a known problem of turbomachines, wherein the tonalities in the noise spectrum are associated with the different orders of the blade passing frequency (BPF). The proper orthogonal decomposition (POD) method was utilized to find the relationship between the fluctuations in the pressure field at the BPF orders which are the origin of the noise emission and the correlated fluctuations in the turbulent velocity field in terms of coherent, periodic flow structures. In order the provide the input data for the POD analysis, a URANS k-ω-SST scale adaptive simulation (SAS) of the turbulent flow field in a single stage radial pump under part load conditions was performed. Compared to traditional two equation turbulence models this approach is less dissipative and allows the development of small scale turbulence structures and is therefore an appropriate method for this study. In order to compute the POD correlation matrix Sirovich’s “Methods of Snapshots” was applied to the unsteady pressure and velocity fields from the CFD simulation. The discrimination of coherent, periodic flow structures and the incoherent, chaotic turbulence was carried out by analyzing the POD eigenvalue distributions, the POD mode shapes and the spectral properties of the POD time coefficients. Five coupled POD mode pairs were identified in total, which were strictly correlated with the 1st, 2nd, 3rd, 4th and 5th order of the BPF and therefore responsible for the noise emission at these discrete frequencies. The coherent structures were explored on the basis of the spatial POD velocity und pressure mode shapes and in terms of vortical structures after an additional phase averaging. The scope of this study is to introduce an enhanced collection of post processing techniques which are capable of analyzing highly unsteady flow fields from numerical simulations in a better way than is possible by just using traditional techniques like the evaluation of integral or time averaged quantities. The identified coherent flow structures and their associated pressure fluctuations are key elements for a proper comprehension of the internal dynamics of the turbulent flow field in a turbomachine and therefore essential for the understanding of the noise generation processes and the optimization of such machines.

Patterns and Reduced-order Reconstruction of Impinging Wiping Jet Pressure Profile Fluctuation Using Proper Orthogonal Decomposition

2021 ◽  
Author(s):  
Le Quang Phan ◽  
Andrew Johnstone ◽  
P. Buyung Kosasih ◽  
Wayne Renshaw
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Jet Impingement ◽  
Pressure Profile ◽  
Orthogonal Decomposition ◽  
Maximum Pressure ◽  
Frequency Spectra ◽  
Reduced Order ◽  
Order Reconstruction ◽  
Pressure Profiles ◽  
Proper Orthogonal

Abstract Wiping jet impingement pressure is important in controlling the coating mass (thickness) and influencing the smoothness of the thin metallic coating produced in continuous galvanizing lines (CGLs). However, the fluctuation of the impingement pressure profile that directly impacts the coating smoothness has not been adequately understood. To study key features of the impingement pressure fluctuation, the instantaneous impingement pressure profiles obtained from Large Eddy Simulations were analyzed using Proper Orthogonal Decomposition (POD). Dominant fluctuation modes of pressure profiles can be differentiated from the energy contents of the modes corresponding to different jet types namely mixing, non-mixing, and transitional mixing jet. The dominant modes of mixing jets in the wiping region contain comparable strength of all modes (flapping, pulsing, and out-of-phase multi pulsing). Non-mixing jets do not show discernable fluctuation modes and transitional mixing jets show pulsing and flapping modes only. Additionally, instantaneous maximum pressure gradient and their location were determined from the reduced-order reconstruction of the pressure profiles. From the analysis, frequency spectra of the magnitude and location fluctuations of the maximum pressure gradients associated with each of the jet types can be clearly distinguished. This is a knowledge that may be helpful for CGL operators in the operation of wiping jets.

Temporal evolution analysis of in-cylinder flow by means of proper orthogonal decomposition

2020 ◽  
pp. 146808742091724
Author(s):  
Li Shen ◽  
Kwee-Yan Teh ◽  
Penghui Ge ◽  
Fengnian Zhao ◽  
David LS Hung
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Internal Combustion Engines ◽  
Temporal Evolution ◽  
Flow Fields ◽  
Orthogonal Decomposition ◽  
Temporal Behavior ◽  
Decomposition Approach ◽  
Cylinder Flow ◽  
Proper Orthogonal ◽  
Low Order

In-cylinder flow fields and their temporal evolution have strong effect on the combustion dynamics of internal combustion engines. Proper orthogonal decomposition is a statistical tool to analyze these flow fields by decomposing them into flow patterns (known as proper orthogonal decomposition modes) and corresponding coefficients with their contribution to the ensemble flow kinetic energy successively maximized. However, neither of the two prevailing proper orthogonal decomposition approaches satisfactorily describes the temporal behavior of the flow fields. The phase-dependent proper orthogonal decomposition approach is limited to analyzing spatial flow structures at a certain engine phase. The phase-invariant proper orthogonal decomposition approach attempts to account for both spatial and temporal variations, but at the expense of diminished statistical and physical significance. In this article, we seek to understand the temporal behavior of tumble flow fields by analyzing the evolution of low-order phase-dependent proper orthogonal decomposition modes over multiple crank angles. The concept of relevance index is first generalized to enable comparison between two vectorial fields of different sizes. This metric is then used to quantify the directional similarities between the two lowest proper orthogonal decomposition modes obtained at sequential crank angles. The mode shapes are observed to evolve gradually and naturally over most crank angles, but change significantly at certain crank angles during intake. The results indicate that each of the low-order modes features strong velocity fluctuations in different regions of the tumble plane, and different numbers of modes are needed to represent the dominant features of tumble flow at different engine phases. Based on this understanding, we propose to use the partial sum of those proper orthogonal decomposition modes and their coefficients to form a low-order approximation model of the in-cylinder tumble flow, in order to reduce flow field complexity and noise while retaining its major spatial and temporal features.

scholarly journals A Proper-Orthogonal Decomposition Variational Multiscale Approximation Method for a Generalized Oseen Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
John Paul Roop
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Incompressible Flows ◽  
Reduced Order Modeling ◽  
Orthogonal Decomposition ◽  
Qualitative Properties ◽  
Complex Flow ◽  
Reduced Order ◽  
Variational Multiscale ◽  
Oseen Problem ◽  
Proper Orthogonal

We introduce the variational multiscale (VMS) stabilization for the reduced-order modeling of incompressible flows. It is well known that the proper orthogonal decomposition (POD) technique in reduced-order modeling experiences numerical instability when applied to complex flow problems. In this case a POD discretization naturally separates out structures which corresponding to the energy cascade on large and small scales, in order, a VMS approach is natural. In this paper, we provide the mathematical background necessary for implementing VMS to a POD-Galerkin model of a generalized Oseen problem. We provide theoretical evidence which indicates the consistency of utilizing a VMS approach in the stabilization of reduced order flows. In addition we provide numerical experiments indicating that VMS improves fidelity in reproducing the qualitative properties of the flow.

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