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An Adaptive Shifted Power Method for Computing Generalized Tensor Eigenpairs
Several tensor eigenpair definitions have been put forth in the past decade, but these can all be unified under generalized tensor eigenpair framework, introduced by Chang, Pearson, and Zhang [J. Math. Anal. Appl. , 350 (2009), pp. 416--422]. Given mth-order, n-dimensional real-valued symmetric tensors ${\\mathscr{A}}$ and $\\boldsymbol{\\mathscr{B}}$, the goal is to find $\\lambda \\in \\mathbb{R}$ and $\\mathbf{x} \\in \\mathbb{R}n}, \\mathbf{x} \\neq 0$ such that ${\\mathscr{A}}\\mathbf{x}m-1} = \\lambda {\\mathscr{B}}\\mathbf{x}m-1}$. Different choices for ${\\mathscr{B}}$ yield different versions of the tensor eigenvalue problem. We present our generalized eigenproblem adaptive power (GEAP) method for solving the problem, which is an extension of the shifted symmetric higher-order power method (SS-HOPM) for finding Z-eigenpairs. A major drawback of SS-HOPM is that its performance depended on choosing an appropriate shift, but our GEAP method also includes an adaptive method for choosing the shift automatically.
Journal Article
Analysis of Transient Stability through a Novel Algorithm with Optimization under Contingency Conditions
Predicting the need for modeling and solutions is one of the largest difficulties in the electricity system. The static-constrained solution, which is not always powerful, is provided by the Gradient Method Power Flow (GMPF). Another benefit of using both dynamic and transient restrictions is that GMPF will increase transient stability against faults. The system is observed under contingency situations using the Dynamic Stability for Constrained Gradient Method Power Flow (DSCGMPF). The population optimization technique is the foundation of a recent algorithm called Training Learning Based Optimization (TLBO). The TLBO-based approach for obtaining DSCGMPF is implemented in this work. The total system losses and the cost of the individual generators have been optimized. Analysis of the stability limits under contingency conditions has been conducted as well. To illustrate the suggested approaches, a Standard 3 machine 5-bus system is simulated using the MATLAB 2022B platform.
Journal Article
ANTIOXIDANT ACTIVITY OF POMEGRANATE
Natural fruits antioxidants play a significant role in inhibiting reactive oxygen species and scavenging free radicals, thus avoiding chronic, degenerative diseases such as cardiovascular disease, aging, cholesterol rates and cancer. The study covered six categories of each three tastes of different pomegranate fruits obtained or purchased in Erbil/Kurdistan-Iraq, a total of 54 samples (6x3x3) were analyzed. Each type was tested for ferric reduction of antioxidant power assay, reduced power method, ascorbic acid content, total phenol and total flavonoid. Our results have shown that the Sour Smilan cultivar has the highest antioxidant properties, ferric antioxidant power reduction (536.89±14.65), ferric power reduction (0.965), ascorbic acid content (0.252±0.012), total phenol (139.66±3.49), total flavonoid (23.08±2.23), and short comparative studies have been conducted to analyze the amount of iron (11) in pomegranate in order to analyze their interferences to the antioxidant activity reported in the ferric reduction of antioxidant power assay.
Journal Article
Modeling and control of engines and drivelines
Control systems have come to play an important role in the performance of modern vehicles with regards to meeting goals on low emissions and low fuel consumption. To achieve these goals, modeling, simulation, and analysis have become standard tools for the development of control systems in the automotive industry.
eBook
Blind multichannel identification based on Kalman filter and eigenvalue decomposition
A noise-robust approach for blind multichannel identification is proposed on the basis of Kalman filter and eigenvalue decomposition. It is proved that the state vector composed of the multichannel impulse responses is nothing but the eigenvector corresponding to the maximum eigenvalue of the filtered state-error correlation matrix. This eigenvector can be computed iteratively with the so-called ‘power method’ to reduce the complexity of the algorithm. Furthermore, it is found that the computation of the inverse of the filtered state-error correlation matrix is much easier than itself, the wanted state vector can be computed from this inverse matrix with the so-called ‘inverse power method’. Therefore, two algorithms are proposed on the basis of the eigenvalue decomposition of the filtered state-error correlation matrix and its inverse matrix, respectively. In addition, for reducing the computing complexity of the proposed algorithms, matrix factorization such as QR-, LU- and Cholesky-factorizations are exploited to accelerate the computation of the algorithms. Simulations show that the proposed algorithms perform well over a wide range of the signal-to-noise ratio of the multichannel signals.
Journal Article
Available Transfer Capability Enhancement by FACTS Devices Using Metaheuristic Evolutionary Particle Swarm Optimization (MEEPSO) Technique
Energy power flows are an important factor to be calculated and, thus, are needed to be enhanced in an electrical generation system. It is very necessary to optimally locate the Flexible Alternating Current Transmission Systems (FACTS) devices and improve the Available Transfer Capability (ATC) of the power transmission lines. It relieves the congestion of the system and increases the flow of power. This research study has been accomplished in two stages: optimization of location of FACTS device by the novel Sensitivity and Power loss-based Congestion Reduction (SPCR) method and the calculation of ATC using the proposed Metaheuristic Evolutionary Particle Swarm Optimization (MEEPSO) technique. The Thyristor Controlled Series Capacitor (TCSC) is used as a FACTS device to control the reactance of power transmission line. The effectiveness of the proposed methods is validated, utilizing the six bus as well as 30 bus system. The acquired outcomes are contrasted with conventional ACPTDF and DCPTDF procedures. These values are determined with the assistance of MATLAB version 2017 on the Intel Core i5 framework by taking two-sided exchanges and they are contrasted and values determined with the assistance of Power World Simulator (PWS) programming.
Journal Article
Solution of stochastic eigenvalue problem by improved stochastic inverse power method (I-SIPM)
Eigenvalue analysis is an important problem in a variety of fields. In structural mechanics in the field of naval architecture and ocean engineering, eigenvalue problems commonly appear in the context of, e.g. vibrations and buckling. In eigenvalue analysis, the physical characteristics are often considered as deterministic, such as mass, geometries, stiffness in the structures. However, in many practical cases, they are not deterministic. Such uncertainties may cause serious problems because the influence of the uncertainties is in general unknown. To solve the stochastic eigenvalue problem, in this article, we have proposed two methods. First, the improved stochastic inverse power method (I-SIPM) based on response surface methodology is proposed. The method is different with previous stochastic inverse power method. The minimum eigenvalue and eigenvector of stochastic eigenvalue problems can be evaluated using the proposed method. Second, the stochastic Wielandt deflation method (SWDM) is proposed to evaluate
i
th (
i
> 1) eigenvalues and eigenvectors of stochastic eigenvalue problems. This is very important for solving natural mode and buckling mode analysis problem. Next, two example problems are investigated to show the validity of two new methods compared with a Monte-Carlo simulation, i.e. the vibration problem of a discrete 2-DOF system and the buckling problem of a continuous beam. Finally, the uncertainty estimation for the dynamic damper problem is discussed using proposed method. The probability of the natural frequency falling into the range to be avoided is shown when the dynamic damper has a stochastic mass and stiffness.
Journal Article
Weibull parameters estimation using combined energy pattern and power density method for wind resource assessment
This work deals with the development of Combined Energy Pattern & Power Density Method (CEPPDM) to evaluate the two parameters needed to define Weibull distribution. Five years (2015–2019) wind data recorded each 60-minutes interval at eleven representative sites in Pakistan was used and efficiency of CEPPDM was compared with Energy Pattern Factor Method (EPFM) and Power Density Method (PDM) with the help of MAPE, MSE and R². Analysis showed that CEPPDM is the most efficient method while EPFM is the least efficient. Furthermore, it was found that RYK is the most lucrative site and Layyah is the weakest site regarding wind potential. Wind rose plots were drawn which showed that the wind mainly blows in the range of 200°–270°.
Journal Article
Evaluating wind energy potential in Gorgan–Iran using two methods of Weibull distribution function
In this study, wind energy characteristics of the, a city in northeast of Iran, measured at 10m height in 2014. The Gorgan airport one hour recorded data extrapolated to 50m height. The data have been statistically analyzed hourly, daily, monthly, seasonally and annually to determine the wind power potential. Weibull distribution function has been used to determine the wind power density and then the potential energy. Standard deviation method and power density method are the methods used to calculate the scaling and shaping parameters of the Weibull distribution function. The annual mean wind power calculated by the standard deviation method and the power density method is 38.98w/m2 and 41.32w/m2, respectively. By comparing the results concluded that the power density method is a better method than the standard deviation method. In addition, Gorgan wind energy potentiality categorized into class 1. So is unsuitable to utilize large wind energy turbine. Article History: Received November 21, 2015; Received in revised form January 15, 2016; Accepted February 10, 2016; Available onlineHow to Cite This Article: Babayani, D., Khaleghi, M., Tashakor, S., and Hashemi-Tilehnoee.,M. (2016) Evaluating wind energy potential in Gorgan–Iran using two methods of Weibull distribution function. Int. Journal of Renewable Energy Development, 5(1), 43-48.http://dx.doi.org/10.14710/ijred.5.1.43-48
Journal Article