The present work presents a new experimental study of the enhancement of turbulent
convection heat transfer inside tubes for combined thermal and hydrodynamic entry length of one
popular “turbulator” (twisted tape with width slightly less than internal tube diameter) inserted for
fire tube boilers. Cylindrical combustion chamber was used to burn (1.6 to 7kg/h) fuel oil #2 to
deliver hot gases with ranges of Reynolds number (10500 to 21700), and (11400 to 24150) for both
empty and inserted tube respectively.A uniform wall temperature technique was used by keeping
approximately constant water temperature difference (25ºC) between inlet and exit cooling water in
parallel flow shell and tube heat exchanger. The test
Correlation equations for expressing the boiling temperature as direct function of liquid composition have been tested successfully and applied for predicting azeotropic behavior of multicomponent mixtures and the kind of azeotrope (minimum, maximum and saddle type) using modified correlation of Gibbs-Konovalov theorem. Also, the binary and ternary azeotropic point have been detected experimentally using graphical determination on the basis of experimental binary and ternary vapor-liquid equilibrium data.
In this study, isobaric vapor-liquid equilibrium for two ternary systems: “1-Propanol – Hexane – Benzene” and its binaries “1-Propanol –
... Show MoreIn this paper, we proposed a new class of Weighted Rayleigh Distribution based on two parameters, one is scale parameter and the other is shape parameter which introduced in Rayleigh distribution. The main properties of this class are derived and investigated in . The moment method and maximum likelihood method are used to obtain estimators of parameters, survival function and hazard function. Real data sets are collected to investigate two methods which depend it in this study. A comparison was made between two methods of estimation.
Fractional calculus has paid much attention in recent years, because it plays an essential role in many fields of science and engineering, where the study of stability theory of fractional differential equations emerges to be very important. In this paper, the stability of fractional order ordinary differential equations will be studied and introduced the backstepping method. The Lyapunov function is easily found by this method. This method also gives a guarantee of stable solutions for the fractional order differential equations. Furthermore it gives asymptotically stable.
Recently, new generalizations have been presented for the hyponormal operators, which are (N, k)-hyponormal operators and (h, M)-hyponormal operators. Some properties of these concepts have also been proved, one of these properties is that the product of two (N, k)-hyponormal operator is also (N, k)- hyponormal operator and the product of two (h, M)-hyponormal operators is (h, M)-hyponormal operator. In our research, we will reprove these properties by using the (l,m)-commuting operator equations, in addition to that we will solve the (l, m)-commuting operator equations for (N, k)-hyponormal operators and (h, M)-hyponormal operators.
This research represents a reflection seismic study (structural and stratigraphic) for a (852) km2 area located in the south of Iraq within the administrative border of the province of Al-Muthanna and Qadisiyah province ,by using 2-D seismic data from Oil Exploration company three main seismic reflectors are picked, these are (Zubair and Yamama) Formations which they deposited during the Cretaceous age , and (Gotnia) Formation which deposited during Jurassic age .Structural maps of Formations are prepared to obtain the location and direction of the sedimentary basin and shoreline ,time, velocity and depth maps are drawn depending on the structural interpretation of the picked reflectors and show several structural feature as nose structu
... Show MoreThis paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord
... Show MoreThe present study aims to get experimentally a deeper understanding of the efficiency of carbon fiber-reinforced polymer (CFRP) sheets applied to improve the torsional behavior of L-shaped reinforced concrete spandrel beams in which their ledges were loaded in two stages under monotonic loading. An experimental program was conducted on spandrel beams considering different key parameters including the cross-sectional aspect ratio (
This paper is interested in comparing the performance of the traditional methods to estimate parameter of exponential distribution (Maximum Likelihood Estimator, Uniformly Minimum Variance Unbiased Estimator) and the Bayes Estimator in the case of data to meet the requirement of exponential distribution and in the case away from the distribution due to the presence of outliers (contaminated values). Through the employment of simulation (Monte Carlo method) and the adoption of the mean square error (MSE) as criterion of statistical comparison between the performance of the three estimators for different sample sizes ranged between small, medium and large (n=5,10,25,50,100) and different cases (wit
... Show MoreSemantic segmentation is effective in numerous object classification tasks such as autonomous vehicles and scene understanding. With the advent in the deep learning domain, lots of efforts are seen in applying deep learning algorithms for semantic segmentation. Most of the algorithms gain the required accuracy while compromising on their storage and computational requirements. The work showcases the implementation of Convolutional Neural Network (CNN) using Discrete Cosine Transform (DCT), where DCT exhibit exceptional energy compaction properties. The proposed Adaptive Weight Wiener Filter (AWWF) rearranges the DCT coefficients by truncating the high frequency coefficients. AWWF-DCT model reinstate the convolutional l
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