The physical behavior for the energy distribution function (EDF) of the reactant particles depending upon the gases (fuel) temperature are completely described by a physical model covering the global formulas controlling the EDF profile. Results about the energy distribution for the reactant system indicate a standard EDF, in which it’s arrive a steady state form shape and intern lead to fix the optimum selected temperature.

This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J

Gas coning is one of the most serious problems in oil wells. Gas will reach the perforations and be produced with oil. Anyhow there is a certain production rate called critical production rate. The daily production rate should not exceed the critical production rate. In this research ten oil wells have been tested for problem of gas coning for a period of time of eighteen months. The production rates of these Ten oil wells are tabulated in a table exist in this research.
These production rates are considered as critical production rate because no gas coning has been observed in these wells. The critical production rates of these wells don't concide with those obtained from (Meyer, Gardiner, Pirson) method and also they don’t concide

   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, a

This study aims at making formation evaluation for Mishrif Formation in three wells within Noor Oilfield which are: No-1, No-2 and No-5. The study includes calculations of shale volume and porosity, water saturation using Archie method, measuring the bulk volume of water (BVW) and using Buckle plot, as well as measuring the movable and residual hydrocarbons. These calculations were carried out using Interactive Petrophysics (IP) version 3.5 software as well as using Petrel 2009 software for structural map construction and correlation purposes. It was found that the Mishrif Formation in Noor Oilfield is not at irreducible water saturation, though it is of good reservoir characteristics and hydrocarbon production especially at the upper pa

In recent years, there is more interest in water sources availability, including groundwater due to an increase in demand for water because of the increasing population in the world, and the water recedes due to climate change also. Therefore, the study of groundwater has required more attention. The aim of the present study is to establish a MODFLOW model in the groundwater modeling system software to simulate the movement of groundwater in the Turssaq alluvial fan which is located in the Qazaniyah city, east of Diyala Governorate. The solid model was used to define the aquifer in the study area. Using the GIS software, mapping and preparing the data needed to create a conceptual model were carried out. The data of the

In the last few years, fiber-coupled diode lasers have shown massive applications in many fields of communication and scientific research. Particularly, the pumping of solid-state lasers is a key application for more powerful diode lasers enabling good solutions in various laser micro methods like metal cutting, sintering, structuring as well as drilling. In this work, a simple beam shaping method is demonstrated for coupling a high-power semiconductor laser diode into multi-mode fiber optic using optical lenses. The optical lenses as beam transformation components are utilized to reshape the asymmetrical irradiation of the diode laser bar and to circularize the laser beam. Using this simple method, compact, high-output-power, and high-b

Autonomous motion planning is important area of robotics research. This type of planning relieves human operator from tedious job of motion planning. This reduces the possibility of human error and increase efficiency of whole process.

This research presents a new algorithm to plan path for autonomous mobile robot based on image processing techniques by using wireless camera that provides the desired image for the unknown environment . The proposed algorithm is applied on this image to obtain a optimal path for the robot. It is based on the observation and analysis of the obstacles that lying in the straight path between the start and the goal point by detecting these obstacles, analyzing and studying their shapes, positions and

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg