1,252 research outputs found
Multiresolution Wavelet Based Adaptive Numerical Dissipation Control for High Order Methods
The recently developed essentially fourth-order or higher low dissipative shockcapturing scheme of Yee, Sandham, and Djomehri [25] aimed at minimizing numerical dissipations for high speed compressible viscous flows containing shocks, shears and turbulence. To detect non-smooth behavior and control the amount of numerical dissipation to be added, Yee et al. employed an artificial compression method (ACM) of Harten [4] but utilize it in an entirely different context than Harten originally intended. The ACM sensor consists of two tuning parameters and is highly physical problem dependent. To minimize the tuning of parameters and physical problem dependence, new sensors with improved detection properties are proposed. The new sensors are derived from utilizing appropriate non-orthogonal wavelet basis functions and they can be used to completely switch off the extra numerical dissipation outside shock layers. The non-dissipative spatial base scheme of arbitrarily high order of accuracy can be maintained without compromising its stability at all parts of the domain where the solution is smooth. Two types of redundant non-orthogonal wavelet basis functions are considered. One is the B-spline wavelet (Mallat and Zhong [14]) used by Gerritsen and Olsson [3] in an adaptive mesh refinement method, to determine regions where refinement should be done. The other is the modification of the multiresolution method of Harten [5] by converting it to a new, redundant, non-orthogonal wavelet. The wavelet sensor is then obtained by computing the estimated Lipschitz exponent of a chosen physical quantity (or vector) to be sensed on a chosen wavelet basis function. Both wavelet sensors can be viewed as dual purpose adaptive methods leading to dynamic numerical dissipation control and improved grid adaptation indicators. Consequently, they are useful not only for shock-turbulence computations but also for computational aeroacoustics and numerical combustion. In addition, these sensors are scheme independent and can be stand-alone options for numerical algorithms other than the Yee et al. scheme
APPLICATION OF DATA FUSION TO FLUID DYNAMIC DATA
In recent years, there have been improvements in the methods of obtaining fluid dynamic data, which has led to the generation of vast amounts of data. Extracting the useful information from large data sets can be a challenging task when investigating data from a single source. However, most experiments use data from multiple sources, such as particle image velocimetry (PIV), pressure sensors, acoustic measurements, and computational fluid dynamics (CFD), to name a few. Knowing the strengths and weaknesses of each measurement technique, one can fuse the data together to improve the understanding of the problem being studied. Concepts from the data fusion community are used to combine fluid dynamic data from the different data sources. The data is fused using techniques commonly used by the fluid dynamics community, such as proper orthogonal decomposition (POD), linear stochastic estimation (LSE), and wavelet analysis. This process can generate large quantities of data and a method of handling all of the data and the techniques in an efficient manner is required. To accomplish this, a framework was developed that is capable of tracking, storing, and, manipulating data.
With the framework and techniques, data fusion can be applied. Data fusion is first applied to a synthetic data set to determine the best methods of fusing data. Data fusion was then applied to airfoil data that was obtained from PIV, CFD, and pressure to test the ideas from the synthetic data. With the knowledge gained from applying fusion to the synthetic data and airfoil data, these techniques are ultimately applied to data for a Mach 0.6 jet obtained from large-window PIV (LWPIV), time-resolved PIV (TRPIV), and pressure.
Through the fusion of the different data sets, occlusion in the jet data were estimated within 6% error using a new POD based technique called Fused POD. In addition, a technique called Dynamic Gappy POD was created to fuse TRPIV and LWPIV to generate a large-window time-resolved data set. This technique had less error than other standard techniques for accomplishing this such as pressure-based stochastic estimation.
The work presented in this document lays the groundwork for future applications of data fusion to fluid dynamic data. With the success of the work in this document, one can begin to apply the ideas from data fusion to other types of fluid dynamic problems, such as bluff bodies, unsteady aerodynamics, and other. These ideas could be used to help improve understanding in the field of fluid dynamics due to the current limitations of obtaining data and the need to better understand flow phenomena
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Wavelet-based response spectrum compatible synthesis of accelerograms-Eurocode application (EC8)
An integrated approach for addressing the problem of synthesizing artificial seismic accelerograms compatible with a given displacement design/target spectrum is presented in conjunction with aseismic design applications. Initially, a stochastic dynamics solution is used to obtain a family of simulated non-stationary earthquake records whose response spectrum is on the average in good agreement with the target spectrum. The degree of the agreement depends significantly on the adoption of an appropriate parametric evolutionary power spectral form, which is related to the target spectrum in an approximate manner. The performance of two commonly used spectral forms along with a newly proposed one is assessed with respect to the elastic displacement design spectrum defined by the European code regulations (EC8). Subsequently, the computational versatility of the family of harmonic wavelets is employed to modify iteratively the simulated records to satisfy the compatibility criteria for artificial accelerograms prescribed by EC8. In the process, baseline correction steps, ordinarily taken to ensure that the obtained accelerograms are characterized by physically meaningful velocity and displacement traces, are elucidated. Obviously, the presented approach can be used not only in the case of the EC8, for which extensive numerical results/examples are included, but also for any code provisions mandated by regulatory agencies. In any case, the presented numerical results can be quite useful in any aseismic design process dominated by the EC8 specifications
Diagnosis of Arrhythmia Using Neural Networks
This dissertation presents an intelligent framework for classification of heart arrhythmias.
It is a framework of cascaded discrete wavelet transform and the Fourier transform as
preprocessing stages for the neural network. This work exploits the information about
heart activity contained in the ECG signal; the power of the wavelet and Fourier
transforms in characterizing the signal and the power learningpower of neural networks.
Firstly, the ECG signals are four-level discrete wavelet decomposed using a filter-bank
and mother wavelet 'db2'. Then all the detailed coefficients were discarded, while
retaining only the approximation coefficients at the fourth level. The retained
approximation coefficients are Fourier transformed using a 16-point FFT. The FFT is
symmetrical, therefore only the first 8-points are sufficient to characterize the spectrum.
The last 8-points resulting from theFFTare discarded during feature selection.
The 8-point feature vector is then used to train a feedforward neural network with one
hidden layer of 20-units and three outputs. The neural network is trained by using the
Scaled Conjugate Gradient Backpropagation algorithm (SCG). This was implemented in
a MATLAB environment using the MATLAB GUINeural networktoolbox..
This approach yields an accuracy of 94.66% over three arrhythmia classes, namely the
Ventricular Flutter (VFL), the Ventricular Tachycardia (VT) and the Supraventricular
Tachyarrhythmia (SVTA). We conclude that for the amount of information retained and
the number features used the performance is fairly competitive
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