This research was aimed to determine the petrophysical properties (porosity, permeability and fluid saturation) of a reservoir. Petrophysical properties of the Shuiaba Formation at Y field are determined from the interpretation of open hole log data of six wells. Depending on these properties, it is possible to divide the Shuiaba Formation which has thickness of a proximately 180-195m, into three lithological units: A is upper unit (thickness about 8 to 15 m) involving of moderately dolomitized limestones; B is a middle unit (thickness about 52 to 56 m) which is composed of dolomitic limestone, and C is lower unit ( >110 m thick) which consists of shale-rich and dolomitic limestones. The results showed that the average formation water

BOOK REVIEW

The aesthetic contents of data visualization is one of the contemporary areas through which data scientists and designers have been able to link data to humans, and even after reaching successful attempts to model data visualization, it wasn't clear how that reveals how it contributed to choosing the aesthetic content as an input to humanize these models, so the goal of the current research is to use The analytical descriptive approach aims to identify the aesthetic contents in data visualization, which the researchers interpreted through pragmatic philosophy and Kantian philosophy, and analyze a sample of data visualization models to reveal the aesthetic entrances in them to explain how to humanize them. The two researchers reached seve

APDBN Rashid, International Journal of Humanities and Social Sciences/ RIMAK, 2023

Littoral and benthic invertebrates from Roundwood Reservoir System were sampled. Oligochaetes and molluscs were the dominant organisms in the littoral and benthic areas Trichopterans and chironomids were the most abundant insect groups. Scuba diving samples reinforced that view. Other groups of macroinvertebrates were poorly represented. Vertical and horizontal hauls of zooplankton revealed that there were twelve species of zooplankton present. Daphnia hyalina Leydig and Bosmina coregoni Baird were the two dominant species.

An assembled pulsed Nd:YAG laser-robot system for spot welding similar and dissimilar metals is presented in this paper. The study evaluates the performance of this system through investigating the possibility and accuracy of executing laser spot welding of 0.2 mm in thickness stainless steel grade AISI302 to 0.5 mm in thickness low carbon steel grade AISI1008. The influence of laser beam parameters (peak power, pulse energy, pulse duration, repetition rate, and focal plane position on the final gained best results are evaluated. Enhancement of the experimental results was carried by a computational simulation using ANSYS FLUENT 6.3 package code.

Abstract

Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance.  This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H₂/H_∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS).  Simulatio

         In this study miconazole nitrate was formulated as topically applied emulgel; different formulas were prepared using sodium carboxymethylcellulose (SCMC) and carboxypolymethylene (carbomer 941) as gelling agents. The influence of type of gelling agent and concentration of both oil phase and emulsifying agent on drug release was studied and compared with commercially available miconazole nitrate cream (Mecozalen^®). The results of in vitro release showed that SCMC emulgel bases gave better release than carbomer 941 bases and the release of drug increase from both bases as a function of increasing the concentration of emulisifying agent. The oil phase had retardation effect when

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur