(An ISO 9001:2008 Certified Online Journal) ISSN:2455-9660


Volume 01 Issue 01 (March-2016) | IJERAS

Title: A Study on Solving the Boundary Value Problem of Three-Region Composite Modified Bessel Equation

Authors: Xiao-xu Dong, Zhi-bin Liu , Shun-chu Li

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This paper studies the boundary value problem (BVP) of three-region composite modified Bessel equation. Firstly, on the basis of similar structure of solution of BVP of differential equation, a new method for solving the class of BVPs is put forward and its steps are summed up. Secondly, the flow chart of algorithm of the new method is given and a program which corresponds with it is compiled. Finally, the new method is applied to solving a given BVP of three-region composite modified Bessel equation and the curve of solution of the boundary value problem is drawn by running the program on the computer. The new method is simple and direct to solve a class of boundary value problems.

Page 1-8


Title: Similar structure of solution for unsteady seepage flow model of shale gas reservoirs

Authors: Duo Zhang , Shunchu Li, Pengshe Zheng

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In view of the problem that the flow model of shale gas reservoir is generally more complex, a simple and convenient method – similar constructive method to solve the shale gas seepage model is proposed. According to the model of unsteady shale gas flow in the double medium, the bottom hole pseudo pressure with similar structure is constructed by introducing the leading solution functions and similar kernel functions. On this basis, draw the characteristic curves and carry on the sensitivity analysis with the drawing software. The study shows that the bottom hole pseudo pressure is different from the kernel function under different boundary conditions. So when using the similar structure theory to draw the characteristic curves of different boundary conditions, only need to change the kernel functions. It also provides a new way of thinking for the research and development of new well testing analysis software

Page 13-16


Title: An Overview on Application of Solar Thermal Power Generation

Authors: Vedant Vyas, Dilip Jani

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Due to worldwide population growth and industrialization, the need of energy is growing rapidly. The conventional energy resources like coal, gas, oil are depleting day by day and will finish soon. To accommodate this need of energy, renewable energy resources will play a crucial role. One of them most promising energy resource is solar energy. This paper reviews the different technologies of solar thermal power generation such as parabolic trough, Linear Fresnel, Central receiver and parabolic dish. From all the technologies of solar power generation, parabolic trough technology is found to be most suitable for solar thermal power generation. A review on energetic and exergetic efficiencies is also carried for different sub assemblies of solar thermal power plant

Page 17-21


Title: On the BP neural network and support vector machine in the role of oil production forecast

Authors: Li Xiaofeng, Gu Xinglong

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The accurate prediction of oil production, the oil companies to develop a reasonable production plan, avoid blind investment, important conditions for achieving sustainable development. In order to improve the accuracy of production forecasts, the paper proposes a BP neural network model, detailing its basic principles and algorithms and the concrete process of this model, and finally apply it to predict job in the oil industry. After the model of learning and training simulation to predict actual results of the comparison show that the model can well achieve the desired effect, it is important to the oil production forecasting. Oilfield proposed system modeling theory based SVM, and the original application-dual algorithm to solve SVM quadratic programming problems. SVM is used to predict the oil production wells, forecasting examples show that the maximum relative error of generalization 5.611%, very close to the predicted value of the actual output of oil wells; compared with other prediction methods, the prediction model has high prediction accuracy. Using BP neural network and support vector machine to predict the oil production and the advantages and disadvantages of the two methods[1].

Page 22-24


Title: Harmonics Reduction Using 5 Level Inverter

Authors: Nikhileshwar P Adhikari, Anurag Tiwari

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In this paper control the drive & reducing the Total Harmonic Distortion using the 5 Level 3 Lags Multilevel Inverter & to compare the THD using different filter. The proposed scheme for neutral point clamped multilevel inverter is Sinusoidal PWM control. The conventional two level inverter is not produce the high output voltage, but the high quality AC output voltage is obtained by the help of multi level inverter. The Multi level inverter consist series of power semiconductor switches, dc source & capacitor to get superior power. The simulation results shows that the proposed model increases the performance of drive by reducing the THD.

Page 9-12