In this paper, two-oscillating grid turbulence with/without viscoelastic additives was performed experimentally by particle image velocimetry. Two classical drag-reducing additives-polymer (Polyacrylamide, PAM) and cationic surfactant (cetyltrimethyl ammonium chloride, CTAC) were chosen. The experiments were carried out under the classical concentration (25ppm) and three different grid oscillation frequencies. Two-dimensional wavelet transform was utilized to investigate multi-scale characteristics of vortex structures and intermittency based on wavelet coefficient. The results showed that at the same decomposition level, the existence of viscoelastic additives attenuates the high-frequency components of fluctuation velocity. The small-scale intermittency is remarkably inhibited by viscoelastic additives especially for scale parameter smaller than 2 4 . Besides, CTAC additives show different effect from PAM additives. Therefore, turbulent drag reduction with additives also happens in two-oscillating grid turbulence without wall effect.

When a material spreads in turbulent flow, areas with high concentration are formed by the local turbulence. These high concentration islands can lead to heavy damage. In this study, the high concentration areas are extracted as pulses by a conditional sampling technique, and statistical analysis were performed in order to investigate the difference between the pulses and concentration plume. Assuming homogeneous flow, a series of images by Planar Laser Induced Fluorescence and Particle Image Velocimetry techniques are acquired at several downstream positions. For PLIF images, a conditional sampling technique is used to extract the high concentration areas. For simultaneous PIV and PLIF images, wavelet analysis is performed to probe into the relationship between high concentration pulses and velocity fluctuation. Turbulent diffusion coefficient of the high concentration areas is found to increase with the downstream distance whereas that of the concentration plume is constant, which implies that the diffusion process of the pulses differs from that of the plume. Besides by wavelet analysis result, it is indicated that concentration fluctuation in the pulses is negatively correlated with streamwise velocity fluctuation. It is concluded that high concentration pulses and plume have different generative mechanisms.

Ship-motion forecasting can be useful for naval operations such as aircraft landing, cargo transfer, off-loading of small boats, and ship “mating” between a large transport ship and smaller ships. The forecasted ship motion is particularly useful in sea states above SS3 when unanticipated large motions can suddenly occur. A 5- to 10-second forecast of future ship motion provides the operator time to compensate for the motion to avoid serious collisions. Ship motion forecasting can enable autonomous landing during higher sea states and can also provide an alternative ship location estimate during emergency procedures such as loss of communication link. This paper summarizes the evaluation of four categories of forecasting methodologies: subspace algorithms, autoregressive algorithms, nonlinear autoregressive using a wavelet network, and perturbation error methods. Simulated Model 5415 ship motion was evaluated in 24 conditions including sea states 4–6, ship speeds of 5, 10, 20, and 30 kts, and wave headings 150 and 180 deg (bow and head seas). For each condition, the simulation motion data was divided into twenty 7.5-minute segments consisting of 0.5 to 5 minutes of training data and 2.5 minutes of testing data. Two types of forecasting accuracy metrics were developed. One metric was based on forecasting simulated ship motion and the other metric involved forecasting periods when the motion exceeds threshold limits within a 4-second window, representing a quiescent period. The results indicate that for simulation forecast accuracy, the correlation coefficient between forecasted and actual motion was greater than 80% for 5-sec forecast horizons, and greater than 60% for 10-sec forecast horizons. For motion threshold forecasting, the forecasting accuracy was greater than 90% for 5-sec horizons and greater than 60% for 10-sec horizons. A qualitative assessment of both simulation and threshold metrics indicated that 80% accuracy produces a good forecast and 60% accuracy produces an acceptable forecast. Threshold forecasting can forecast the presence and duration of near-future quiescent periods, enabling safer, more efficient operations and reduced cost of ship-based aviation operations such as launch, recovery, and movement of aircraft.

Wavelet-based methods have demonstrated great potential for solving partial differential equations of various types. The capabilities of the wavelet Galerkin method are explored by solving various heat transfer and fluid flow problems. A fictitious domain approach is used to simplify the discretization of the domain and a penalty method allows an efficient implementation of the boundary conditions. The resulting system of equation is solved iteratively via the Conjugate Gradient and Preconditioned Conjugate Gradient Methods. The fluid flow problems in the present study are formulated in such a manner that the solution of the continuity and momentum equations is obtained by solving a series of Poisson equations. This is achieved by using steepest descent method. The examples solved show that the method is amenable to solving large problems rapidly with modest computational resources.

An adaptive wavelet method is applied in order to enhance the computational efficiency of enhanced Multi-dimensional Limiting Process (e-MLP) without deterioration of the numerical accuracy of original Computational Fluid Dynamics (CFD) scheme. For this purpose, higher order of adaptive wavelet method is constructed including higher order of wavelet decomposition and modified thresholding. Besides, the locations of crucial features such as shock, vortex core, etc. are automatically and accurately searched in the CFD dataset through wavelet transformation. Only on these locations, high order spatial interpolation scheme with e-MLP are performed; in the other locations, interpolation method is utilized to compute residual values, which reduces the computational time of flux evaluation. This high order adaptive wavelet method was applied to unsteady Euler flow computations such as shock-vortex interaction problem. Throughout these processes, it was verified that computational efficiency was enhanced with preservation of numerical accuracy of CFD solver.

A system based on virtual instrument was set up to test and analyze the pressure pulsation and hydrodynamic noise in centrifugal pump. It has adjustable sampling time length and frequency which can avoid the disadvantages of data loss and redundancy caused by fixed sampling parameters. A signal preprocessing toolkit compiled by LabVIEW was set up, which can anti the aliasing of the signal by use of the low pass filter, decrease the noise in the concerned frequency by the wavelet de-noising and efficiently reduce the error caused by test system. Meanwhile, the data analysis toolkits in this system not only include signal power spectrum and octave for obtaining the frequency characteristic, but also include correlation analysis between the measured waveforms and wavelet analysis for detecting the signature of the signal. All of the toolkits could be used as an automatic real-time system. The feasibility of this system has already been evaluated in a centrifugal pump system, and it is testified that this system can realize and analyze the pressure pulsation and inner hydrodynamic noise automatically.

In order to safe design and optimize performance of some industrial systems, it’s often needed to categorize two-phase flow into different regimes. In each flow regime, flow conditions have similar geometric and hydrodynamic characteristics. Traditionally, flow regime identification was carried out by flow visualization or instrumental indicators. In this research3 kind of neural networks have been used to predict system characteristic and flow regime, and results of them were compared: radial basis function neural networks, self organized and Multilayer perceptrons (supervised) neural networks. The data bank contains experimental pressure signalfor a wide range of operational conditions in which upward two phase air/water flows pass to through a vertical pipe of 5cm diameter under adiabatic condition. Two methods of signal processing were applied to these pressure signals, one is FFT (Fast Fourier Transform) analysis and the other is PDF (Probability Density Function) joint with wavelet denoising. In this work, from signals of 15 fast response pressure transducers, 2 have been selected to be used as feed of neural networks. The results show that obtained flow regimes are in good agreement with experimental data and observation.

The cavitating behavior of a four blade inducer tested in the LML laboratory large test facility is considered in the present paper. Experimental investigations based on unsteady pressure measurements and records from a six components balance mounted on the inducer shaft are performed. Spectral analysis of the signals enables to detect several characteristic frequencies related to unbalanced two-phase flow patterns. The objective of the present paper is the understanding of the physical phenomena associated to these frequencies. Therefore, wavelet decomposition, flow visualizations, and direct analysis of the high-frequency force, moment, and pressure signals are applied. Results at nominal flow rate only are considered. Not only classical unbalanced cavitation patterns, but also unexpected flow organizations are discussed.

A vibration-based fault diagnosis method of pump units based on wavelet packet transform (WPT) is proposed in this paper. Compared with Fourier transform (FT) and wavelet transform (WT), WPT can subdivide the whole time-frequency domain. It can perform signals with good time resolution at high frequency and vice versa. WPT is considered as a good tool to signal denoising, accounting for its perfect ability in decomposing and reconstructing signal and its characteristic of no redundancy and divulges after denoising. In addition, WPT modulus maximal coefficient provides a simple but accurate method in calculating the Lipschitz exponents, which is the measurement of signal singularity. According to the singularity analysis results of vibration signal, we can recognize the fault pattern of pump units. This paper makes a detail research on signal denoising and singularity analysis based on WPT. Taking the main shaft and thrust bearing vibration signal for example, the experimental results show that WPT is effectively in the fault diagnosis system of pump unit.

Initial condition effects in a self-preserving plane wake were investigated for two wake generators, i.e. a triangular cylinder and a screen of 50% solidity. Two orthogonal arrays of sixteen X-wires, eight in the ( x , y )-plane, i.e. the plane of mean shear, and eight in the ( x , z )-plane, which is parallel to both the cylinder axis and the streamwise direction, are used to simultaneously obtain velocity data in the experimental investigation. Measurements were made at x / h ( x is the streamwise distance downstream of the cylinder and h is the height of the wake generator) = 330 for the triangular cylinder and 220 for the screen. A two-dimensional orthogonal wavelet transform is used to analyze the measured hot-wire data. This technique enables the turbulence structures of various scales to be separated and characterized. Discernible differences are observed between the two wake generators in the turbulence structures of large- down to intermediate-scales. The differences are quantified in terms of the Reynolds shear stress, kinetic energy and root mean square vorticity values.

The flow feature of the jet issuing from the circular pipe with the rotating inclined section has been investigated by the method of the flow visualization and the image processing. It has been found that the jet diffusion is affected by the inclined angle and the rotating speed. The coherent structure of the jet has been also studied by using the wavelet multi-resolution analysis. The multi-scale turbulent structures were visualized and the core and edge of the vortex were identified at different broad scales.

We present a new wavelet-based adaptive multiresolution representation (WAMR) algorithm for the numerical solution of multiscale evolution problems. Key features of the algorithm are fast procedures for grid rearrangement, computation of derivatives, as well as the ability to minimize the degrees of freedom for a prescribed solution accuracy. To demonstrate the efficiency and accuracy of the algorithm, we use it to solve the two-dimensional benchmark problem of incompressible fluid-flow in a lid-driven cavity at large Reynolds numbers. The numerical experiments demonstrate the great ability of the algorithm to adapt to different scales at different locations and at different times so as to produce accurate solutions at low computational cost. Specifically, we show that solutions of comparable accuracy as the benchmarks are obtained with more than an order of magnitude reduction in degrees of freedom.

The extraction of dominant particle density fluctuation in various time-space frequency levels on a pipeline cross section was performed using capacitance-computed tomography and three-dimensional discrete wavelets transform. As a result, particle density fluctuation downstream of a bent pipe is decomposed into the time-space levels in a non-choking state and a pseudo-choking state. The proposed method enables realization of the time and position at which particle density fluctuations with respect to dominant time-space levels pass through the pipeline.

Haar-wavelet-based preconditioning technique for conjugate gradient Poisson solvers is described. The proposed method is suitable for parallel processing because of data locality. The method also has a superior property of preventing the computing time from increasing markedly with the increase in the number of grid points. These kinds of combined approaches of software and hardware are superior in large scale problems and will play more important roles in future computational science.

Single-precision floating point data from a simulation of barotropic turbulence is compressed with a wavelet-based method. The quantity being compressed is vorticity. The compression error is evaluated both in terms of error in the vorticity and the error in various quantities derived from the vorticity. Numerical error is evaluated in all quantities and visualizations of the vorticity and correlation of the error with the uncompressed data are evaluated. It is found that depending on the quantities of interest and the evaluation criteria, compression ratios of 4:1 to 256:1 are achievable. Under a conservative definition of acceptable error, it is possible to recover quantities of interest from data compressed 4:1 (8bpp), the data rate that in existing practice is used for visualization.

The vortex structures in a separated region are generated by the motion of the separated shear layer caused by the introduction of periodic fluctuation. The main cause of the motion of the separated shear layer is the external fluctuation with the characteristic frequency. In order to investigate the principal motion of the velocity field, phase averaging was conducted to the velocity signals obtained by single hot-wire measurement. In phase averaging, wavelet analysis was applied to obtain the dominant frequency and the characteristic phase in the fluctuation. The profiles and the contours of the phase-averaged velocity could be found and discussed. The profiles vary dynamically at each phase and show the periodic motion of the shear layer. The separated shear layer flutters with the external fluctuation in the mean flow. If the suitable frequency is selected in the external fluctuation, the separated region disappears in almost all each phases owing to the depression of the shear layer near the wall.

Measurements of the fluctuating wall pressure field across the transition region of a flat plate zero pressure gradient boundary layer have been performed with a 64-element linear array of sub-miniature hearing-aid microphones. The measurements provide a unique description of the formation, convection, and growth of turbulent spots in the transition zone and insight into a potential source of low-wavenumber energy. A model for the nonhomogeneous wavenumber-frequency spectrum has been formulated based on the observed spatio-temporal properties of the field. Measured array-averaged wavenumber-frequency spectral levels for the transitional boundary layer collapse with fully turbulent spectra in the vicinity of the convective ridge when scaled by intermittency, similar to previous findings for single point spectra. The transition zone convective ridge is broader, however, consistent with the notion of rapidly evolving (versus equilibrium) structures. Insight into the low-wavenumber portions of the spectra requires an improved array phase calibration. Wavelet based transform methods are being pursued to understand the evolution of spectral components during spot formation and to resolve the space-varying wavenumber content of the field.

Physics based low dimensional approaches are playing an increasingly important role in our understanding of turbulent flows. They provide an avenue for us to understand the connection between coherent structures and the overall dynamics of the flow field. As such these approaches are fundamental to the implementation of physics based active control methodologies. In this paper we review applications of various low dimensional approaches (including Proper Orthogonal Decomposition (POD), Linear Stochastic Estimation (LSE), Conditional Averages and Wavelets) to turbulent shear layers and connect the results to simulation tools. The applications of all these methods to the 2D shear layer suggest a kind of universal behavior of both the large scale structure extracted and the background turbulence, irrespective of the technique (filtering method) used. A review of the application of POD and LSE to the axisymmetric jet at Reynolds numbers between 100,000 and 800,000 and Mach numbers ranging from very low to 0.6 suggest a universal behavior where the dynamics can be described with relatively low dimensional information (1 POD mode and 5 or 6 Fourier azimuthal modes) over the Reynolds/Mach number range studied. These results provide physical justification for simulation tools such as VLES, LES and SDM since such computational methods involve different levels of low-dimensional modeling.

The three-dimensional flow topology of square prism intermediate wake flow based on multi-point hot-wire measurements is investigated using wavelet analysis. A number of continuous wavelet techniques combining time and scale analysis are applied systematically to detect the primary and the secondary flow structures and to validate previously proposed topological models. Our results suggest that a preferred alternate rib spanwise arrangement similar to the one proposed by Meiburg and Lasheras [1] is plausible for the vortex topology of high Reynolds number square prism intermediate wakes. Moreover, it seems that the wake topology has a preferred spanwise wavelength of approximately 2 b = 2.4 d , which gives a relative spanwise/ streamwise wavelength ( 2 b / λ ) of 2/5.

Instability of the compressor operation is manifested in two forms: by mild or deep surge. Both of them should be avoided as they lead to reduced performance or serious damage to the machine and its driving system. One of the pre-surge symptoms is rotating stall that appears mainly in the impeller and transfers to other parts of the compressor. This phenomenon can be described as a rotating pressure wave arising and decaying intermittently. Such an irregularly changing object needs an analyzing tool that allows for a spectrum fluctuation study. The authors used the signal time-frequency representation with progressive wavelets to analyze the static pressure signals acquired during a few deep surge cycles. The rotating stall was identified with the cross-correlation of the continuous wavelet transform. The same method allowed for calculation of the time lag between oscillatory pressure signals coming from the diffuser and the inlet of the compressor, which estimates the reverse flow velocity.