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The purpose of this paper devoted to the application of modal analysis to analyze the flow structure of trailing edge cutback film cooling and the effects of vortex structure on the film cooling effectiveness of the cutback surface.

Large eddy simulation (LES) is used to simulate the trailing edge cutback film cooling. The results of LES are analyzed by proper orthogonal decomposition (POD) method and dynamic mode decomposition (DMD) method. The POD method is used to determine the dominated vortex structure and the energy level of these structures. The DMD method is used to analyze the relationship between vortex structures and wall temperature.

The POD method shows that the flow field consists of three main vortices – streamwise vortex, lip vortex and coolant vortex. The DMD results show that the lip vortex mainly acts on the middle section of the cutback surface, while the streamwise vortex mainly acts on the back section of the cutback surface.

The modal analysis is only based on numerical simulation but the modal analysis of experimental results will be further studied in the future.

This paper presents the powerful ability of the modal analysis method to study complex flows in trailing edge cutback film cooling. Establishing the relationship between vortex and wall temperature by modal analysis method can provide a new idea for studying convective heat transfer problems.

The role of streamwise vortex in the flow of the trailing edge cutback cooling and its effect on the cooling effectiveness of the cutback surface is found.

The purpose of this study is to propose a fast method for predicting flow fields with periodic behavior with verification in the context of a radial turbine to meet the urgent requirement to effectively capture the unsteady flow characteristics in turbomachinery. Aiming at meeting the urgent requirement to effectively capture the unsteady flow characteristics in turbomachinery, a fast method for predicting flow fields with periodic behavior is proposed here, with verification in the context of a radial turbine (RT).

Sparsity-promoting dynamic mode decomposition is used to determine the dominant coherent structures of the unsteady flow for mode selection, and for flow-field prediction, the characteristic parameters including amplitude and frequency are predicted using one-dimensional Gaussian fitting with flow rate and two-dimensional triangulation-based cubic interpolation with both flow rate and rotation speed. The flow field can be rebuilt using the predicted characteristic parameters and the chosen model.

Under single flow-rate variation conditions, the turbine flow field can be recovered using the first seven modes and fitted amplitude modulus and frequency with less than 5% error in the pressure field and less than 9.7% error in the velocity field. For the operating conditions with concurrent flow-rate and rotation-speed fluctuations, the relative error in the anticipated pressure field is likewise within an acceptable range. Compared to traditional numerical simulations, the method requires a lot less time while maintaining the accuracy of the prediction.

It would be challenging and interesting work to extend the current method to nonlinear problems.

The method presented herein provides an effective solution for the fast prediction of unsteady flow fields in the design of turbomachinery.

A flow prediction method based on sparsity-promoting dynamic mode decomposition was proposed and applied into a RT to predict the flow field under various operating conditions (both rotation speed and flow rate change) with reasonable prediction accuracy. Compared with numerical calculations or experiments, the proposed method can greatly reduce time and resource consumption for flow field visualization at design stage. Most of the physics information of the unsteady flow was maintained by reconstructing the flow modes in the prediction method, which may contribute to a deeper understanding of physical mechanisms.

The study aims to display the bubbles' evolution in the shear layer and their relationship with the pressure fluctuations. Furthermore, the coherent structures of the first six modes are extracted, in order to provide insight into their temporal and spatial evolution and determine the relationship between cavitating bubbles and coherent structures.

In the present study, numerical simulations of submerged jet cavitating flow were carried out at a cavitation inception condition inside an axisymmetric cavity using the large eddy simulation (LES) turbulence model and the Schnerr–Sauer (S–S) cavitation model. Based on snapshots produced by the numerical simulation, dynamic mode decomposition (DMD) was performed to extract the three-dimensional coherent structures of the first six modes in the shear layer.

The cavitating bubbles in the shear layer are deformed to elongated ellipsoid shapes by shear forces. The significant pressure fluctuations are induced by the collapse of the biggest bubble in the group. The first mode illustrates the mean characteristics of the flow field. The flow in the peripheral region of the shear layer is mainly dominated by large-scale coherent structures revealed by the second and third modes, while different small-scale coherent structures are contained in the central region. The cavitating bubbles are associated with small size coherent structures as the sixth or higher modes.

This work demonstrates the feasibility of LES for high Reynolds number shear layer flow. The dynamic mode decomposition method is a novel method to extract coherent structures and obtain their dynamic information that will help us to optimize and control the flow.

(1) This paper first displays the three-dimensional coherent structures and their characteristics in the shear layer of confined jet flow. (2) The relationship of bubbles shape and pressure fluctuations is illustrated. (3) The visualization of coherent structures benefits the understanding of the mixing process and cavitation inception in jet shear layers.

The purpose of this paper is to investigate the characteristic flow structures behind a backward-facing step. With better understanding of unsteady features, effective control practice with harmonic actuation is illustrated.

The present study employs Improved Delayed Detached Eddy Simulation to resolve flow turbulence with a finite-volume approach on structured grid mesh. The coherent structure is displayed through temporal- and spatial-evolution of pressure fluctuations. Characteristic frequencies in different flow regions are extracted using fast Fourier transform. Dynamic mode decomposition method is applied to uncover the critical dynamic modes.

The time- and spanwise-averaged quantities agree well with experimental data. It is observed that two distinct modes exist: shear layer mode and shedding mode. The former is related to Kelvin-Helmholtz instability mechanism, vortex pairing and step mode with non-dimensional frequency, St_h,st at around 0.2. The latter is of multi-scale, with a typical coherent structure shedding frequency, St_h,st at 0.074. Step mode interacts with shedding mode in the reattachment region, resulting in the low-frequency characteristics.

An optimal excitation frequency to reduce recirculation bubble length is obtained at about St_h,st =0.2 with an explanation.

The purpose of this paper is to numerically investigate the mildly separated flow phenomena on a near-stall NACA0015 airfoil, by using Detached-Eddy Simulation (DES) type methods. It includes a comparison of different choices of underlying Reynolds-averaged Navier–Stokes model as well as subgrid-scale stress model in Large-Eddy simulation mode.

The unsteady flow phenomena are simulated by using delayed DES (DDES) and improved DDES (IDDES) methods, with an in-house computational fluid dynamics solver. Characteristic frequencies in different flow regions are extracted using fast Fourier transform. Dynamic mode decomposition (DMD) method is applied to uncover the critical dynamic modes.

Among all the DES type methods investigated in this paper, only the Spalart–Allmaras-based IDDES captures the separation point as measured in the experiments. The classical vortex-shedding and the shear-layer flapping modes for airfoil flows with shallow separation are also found from the IDDES results by using DMD.

The value of this paper lies in the assessment of five different DES-type models through the detailed investigation of the Reynolds stresses as well as the separation and reattachment.

This paper aims to present an efficient IMPES algorithm based on a global model order reduction method, proper orthogonal decomposition (POD), to achieve the fast solution and prediction of two-phase flows in porous media.

The key point of the proposed algorithm is to establish an accurate POD reduced-order model (ROM) for two-phase porous flows. To this end, two projection methods including projecting the original governing equations (Method I) and projecting the discrete form of original governing equations (Method II) are respectively applied to construct the POD-ROM, and their distinctions are compared and analyzed in detail. It is found the POD-ROM established by Method I is inapplicable to multiphase porous flows due to its failed introduction of fluid saturation and permeability that locate on the edge of grid cell, which would lead to unphysical results.

By using Method II, an efficient IMPES algorithm that can substantially speed up the simulation of two-phase porous flows is developed based on the POD-ROM. The computational efficiency and numerical accuracy of the proposed algorithm are validated through three numerical examples, and simulation results illustrate that the proposed algorithm displays satisfactory computational speed-up (one to two orders of magnitude) without sacrificing numerical accuracy obviously when comparing to the standard IMPES algorithm that without any acceleration technique. In addition, the determination of POD modes number, the relative errors of wetting phase pressure and saturation, and the influence of POD modes number on the overall performances of the proposed algorithm, are investigated.

1. Two projection methods are applied to establish the POD-ROM for two-phase porous flows and their distinctions are analyzed. The reason why POD-ROM is difficult to be applied to multiphase porous flows is clarified firstly in this study. 2. A highly efficient IMPES algorithm based on the POD-ROM is proposed to accelerate the simulation of two-phase porous flows. 3. Satisfactory computational speed-up (one to two orders of magnitude) and prediction accuracy of the proposed algorithm are observed under different conditions.

The purpose of this paper is to establish an intelligent framework to generate the data representatives in snapshot simulation in order to construct the online reduced-order model based on the generated data information. It could greatly reduce the computational time in snapshot simulation and accelerate the computational efficiency in the real-time computation of reduced-order modeling.

The snapshot simulation, which generates the data to construct reduced-order models (ROMs), usually is computationally demanding. In order to accelerate the snapshot generation, this paper presents a discrete element interpolaiton method (DEIM)-embedded hybrid simulation approach, in which the entire snapshot simulation is partitioned into multiple intervals of equal length. One of the three models: the full order model (FOM), local ROM, or local ROM-DEIM which represents a hierarchy of model approximations, fidelities and computational costs, will be adopted in each interval.

The outcome of the proposed snapshot simulation is an efficient ROM-DEIM applicable to various online simulations. Compared with the traditional FOM and the hybrid method without DEIM, the proposed method is able to accelerate the snapshot simulation by 54.4%–63.91% and 10.5%–27.85%, respectively. In the online simulation, ROM-DEIM only takes 4.81%–8.56% of the computational time of FOM, while preserving excellent accuracy (with relative error <1%).

1. A DEIM-embedded hybrid snapshot simulation methodology is proposed to accelerate snapshot data generation and reduced-order model (ROM)-DEIM development. 2. The simulation alternates among FOM, ROM and ROM-DEIM to adaptively generate snapshot data of salient subspace representation while minimizing computational load. 3. The DEIM-embedded hybrid snapshot approach demonstrates excellent accuracy (<1% error) and computational efficiency in both online snapshot simulation and online ROM-DEIM verification simulation.

The paper aims to develop an efficient data-driven modeling approach for the hydroelastic analysis of a semi-circular pipe conveying fluid with elastic end supports. Besides the structural displacement-dependent unsteady fluid force, the steady one related to structural initial configuration and the variable structural parameters (i.e. the variable support stiffness) are considered in the modeling.

The steady fluid force is treated as a pipe preload, and the elastically supported pipe-fluid model is dealt with as a prestressed hydroelastic system with variable parameters. To avoid repeated numerical simulations caused by parameter variation, structural and hydrodynamic reduced-order models (ROMs) instead of conventional computational structural dynamics (CSD) and computational fluid dynamics (CFD) solvers are utilized to produce data for the update of the structural, hydrodynamic and hydroelastic state-space equations. Radial basis function neural network (RBFNN), autoregressive with exogenous input (ARX) model as well as proper orthogonal decomposition (POD) algorithm are applied to modeling these two ROMs, and a hybrid framework is proposed to incorporate them.

The proposed approach is validated by comparing its predictions with theoretical solutions. When the steady fluid force is absent, the predictions agree well with the “inextensible theory”. The pipe always loses its stability via out-of-plane divergence first, regardless of the support stiffness. However, when steady fluid force is considered, the pipe remains stable throughout as flow speed increases, consistent with the “extensible theory”. These results not only verify the accuracy of the present modeling method but also indicate that the steady fluid force, rather than the extensibility of the pipe, is the leading factor for the differences between the in- and extensible theories.

The steady fluid force and the variable structural parameters are considered in the data-driven modeling of a hydroelastic system. Since there are no special restrictions on structural configuration, steady flow pattern and variable structural parameters, the proposed approach has strong portability and great potential application for other hydroelastic problems.

Biometric systems are widely used for face recognition. They have rapidly developed in recent years. Compared with other approaches, such as fingerprint recognition, handwriting verification and retinal and iris scanning, face recognition is more straightforward, user friendly and extensively used. The aforementioned approaches, including face recognition, are vulnerable to malicious attacks by impostors; in such cases, face liveness detection comes in handy to ensure both accuracy and robustness. Liveness is an important feature that reflects physiological signs and differentiates artificial from real biometric traits. This paper aims to provide a simple path for the future development of more robust and accurate liveness detection approaches.

This paper discusses about introduction to the face biometric system, liveness detection in face recognition system and comparisons between the different discussed works of existing measures.

This paper presents an overview, comparison and discussion of proposed face liveness detection methods to provide a reference for the future development of more robust and accurate liveness detection approaches.

The purpose of this paper is to present numerical investigations of the flow dynamic characteristics of a 47° Ahmed Body to identify wake flow control strategy leading to drag coefficient reduction, which could be tested later on sport utility vehicles.

This study begins with a mean flow topology description owing to dynamic and spectral analysis of the aerodynamic tensor. Then, the sparse promoting dynamic modal decomposition method is discussed and compared to other modal approaches. This method is then applied on the wall and wake pressure to determine frequencies of the highest energy pressure modes and their transfers to other frequency modes. This analysis is then used to design appropriated feedback flow control strategies.

This dynamic modal decomposition highlights a reduced number of modes at low frequency which drive the flow dynamics. The authors especially notice that the pressure mode at a Strouhal number of 0.22, based on the width between feet, induces aerodynamic losses close to the rear end. Strategy of the proposed control loop enables to dampen the energy of this mode, but it has been transferred to lower frequency mode outside of the selected region of interest.

This analysis and methodology of feedback control shows potential drag reduction with appropriated modal energy transfer management.