Parameter identification of induction motor

Numerous recent techniques of induction motor parameters calculating are hard to be done and expensive. Accurate calculations of the parameters of these motors would allow savings in different prospective like energy and cost. The major problem in calculating induction motor parameters is that it\u27s hard to measure output power precisely and without harm during the operation of the machines. It will be better to find other way to find out the output power with certain amount of inputs like input voltage and current.;Particle swarm optimization (PSO) and genetic algorithms (GAs) are often used to estimate quantities from limited information. They belong to a class of weak search procedures, that is, they do not provide the best solution, but one close to it. It is a randomized process in which follows the principles of evolution.;In this thesis genetic algorithm and partial swarm optimization are used to identify induction motor parameters. The inputs used to estimate electrical and mechanical parameters are measured stator voltages and currents. The estimated parameters compare well with the actual parameters. Data Acquisition (DAQ) is used to obtain these variable with the help of LABVIEW software. The induction motor used is a 7.5-hp with a constant frequency and in free acceleration. IEEE standard test of 7.5-hp induction motor is used to compare with performance of the simulated and measured data obtained. According to the output results, method of optimizing induction machine can be used in different models of induction motor

Deflated BiCGStab for linear equations in QCD problems

The large systems of complex linear equations that are generated in QCD problems often have multiple right-hand sides (for multiple sources) and multiple shifts (for multiple masses). Deflated GMRES methods have previously been developed for solving multiple right-hand sides. Eigenvectors are generated during solution of the first right-hand side and used to speed up convergence for the other right-hand sides. Here we discuss deflating non-restarted methods such as BiCGStab. For effective deflation, both left and right eigenvectors are needed. Fortunately, with the Wilson matrix, left eigenvectors can be derived from the right eigenvectors. We demonstrate for difficult problems with kappa near kappa_c that deflating eigenvalues can significantly improve BiCGStab. We also will look at improving solution of twisted mass problems with multiple shifts. Projecting over previous solutions is an easy way to reduce the work needed.Comment: 7 pages, 4 figures, presented at the XXV International Symposium on Lattice Field Theory, 30 July - 4 August 2007, Regensburg, German

Algebraic Multi-Grid solver for lattice QCD on Exascale hardware: Intel Xeon Phi

In this white paper we describe work done on the development of an efficient iterative solver for lattice QCD based on the Algebraic Multi-Grid approach (AMG) within the tmLQCD software suite. This development is aimed at modern computer architectures that will be relevant for the Exa-scale regime, namely multicore processors together with the Intel Xeon Phi coprocessor. Because of the complexity of this solver, implementation turned out to take a considerable effort. Fine tuning and optimization will require more work and will be the subject of further investigation. However, the work presented here provides a necessary initial step in this direction

Discrete Models of Time-Fractional Diffusion in a Potential Well

Mathematics Subject Classification: 26A33, 45K05, 60J60, 60G50, 65N06, 80-99.By generalization of Ehrenfest’s urn model, we obtain discrete approximations to spatially one-dimensional time-fractional diffusion processes with drift towards the origin. These discrete approximations can be interpreted (a) as difference schemes for the relevant time-fractional partial differential equation, (b) as random walk models. The relevant convergence questions as well as the behaviour for time tending to infinity are discussed, and results of numerical case studies are displayed. See also, http://www.diss.fu-berlin.de/2004/168/index.htm

Vitamin C promotes pluripotency of human induced pluripotent stem cells via the histone demethylase JARID1A

Somatic cells can be reprogramed into induced pluripotent stem (iPS) cells by defined factors, which provide a powerful basis for personalized stem-cell based therapies. However, cellular reprograming is an inefficient and metabolically demanding process commonly associated with obstacles that hamper further use of this technology. Spontaneous differentiation of iPS cells cultures represents a significant hurdle that hinder obtaining high quality iPS cells for further downstream experimentation. In this study, we found that a natural compound, vitamin C, augmented pluripotency in iPS cells and reduced unwanted spontaneous differentiation during iPS cells maintenance. Gene expression analysis showed that vitamin C increased the expression of the histone demethylase JARID1A. Furthermore, through gain- and loss-of-function approaches, we show that JARID1A is a key effector in promoting pluripotency and reducing differentiation downstream of vitamin C. Our results therefore highlight a straightforward method for improving the pluripotency and quality of iPS cells; it also shows a possible role for H3K4me2/3 in cell fate determination and establishes a link between vitamin C and epigenetic regulation