In this paper, the problem of developing turbulent flow in rectangular duct is investigated by obtaining numerical results of the velocity profiles in duct by using large eddy simulation model in two dimensions with different Reynolds numbers, filter equations and mesh sizes. Reynolds numbers range from (11,000) to (110,000) for velocities (1 m/sec) to (50 m/sec) with (56×56), (76×76) and (96×96) mesh sizes with different filter equations. The numerical results of the large eddy simulation model are compared with k-ε model and analytic velocity distribution and validated with experimental data of other researcher. The large eddy simulation model has a good agreement with experimental data for high Reynolds number with the first, second and third mesh sizes and the agreement increase near the wall of the duct. The percentage error for the large eddy simulation model with experimental data of the (56×56) mesh size is less than 18 % and for the (76×76) mesh size is also less than 17% and for the (96×96) mesh size is less than 16 %. The large eddy simulation model show high stability and do not need extra differential equation like the k-ε model and a great saving in time and computer memory was achieved.
The ground state density distributions and electron scattering Coulomb form factors of Helium (4,6,8He) and Phosphorate (27,31P) isotopes are investigated in the framework of nuclear shell model. For stable (4He) and (31P) nuclei, the core and valence parts are studied through Harmonic-oscillator (HO) and Hulthen potentials. Correspondingly, for exotic (6,8He) and (27P) nuclei, the HO potential is applied to the core parts only, while the Hulthen potential is applied to valence parts. The parameters for HO and Hulthen are chosen to reproduce the available experimental size radii for all nuclei under study. Finally, the CO component of electron scattering charge fo
... Show MoreAbstract
This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per
... Show MoreThe nuclear size radii, density distributions and elastic electron scattering charge form factors for Fluorine isotopes (17,19,20,24,26F) were studied using the radial wave functions (WF) of harmonic-oscillator (HO) potential and free mean field described by spherical Hankel functions (SHF) for the core and the valence parts, respectively for all aforementioned isotopes. The parameters for HO potential (size parameter ) and SHF were chosen to regenerate the available experimental size radii. It was found that using spherical Hankel functions in our work improved the calculated results quantities in comparison with empirical data.
هناك عوامل عديدة تؤثر في البنية الشكلية للم ا ركز الحضرية التي تشهد تحولات وبصورة مستمرة ومع
توسع المدينة ونموها تفقد هذه الم ا ركز لمقومات بنيتها الحضرية المتكاملة بسبب تلك التحولات الحاصلة
ضمنه وبصورة ديناميكية من اضافات وتغيرات في النمط الحضري الذي يتشكل من عدة نماذج معمارية
جديدة مؤثرة ولأجل ذلك جاء البحث لايضاح اثر هذه العلاقة بين النمط الحضري والنموذج المعماري
وتحولاته في تكاملية البنية ا
The ground state densities of unstable proton-rich 9C, 12N and 23Al exotic nuclei are studied via the framework of the two-frequency shell model (TFSM) and the binary cluster model (BCM). In TFSM, the single particle harmonic oscillator wave functions are used with two different oscillator size parameters βc and βv, where the former is for the core (inner) orbits and the latter is for the valence (halo) orbits. In BCM, the internal densities of the clusters are described by single particle Gaussian wave functions. The long tail performance is clearly noticed in the calculated proton and matter density distributions of these nuclei. The structure of the valence proton in 9C and 12N is a pure (1p1/2) configuration while that for 23Al is
... Show MoreThis paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward
... Show MoreOver the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame
In this study, the stress-strength model R = P(Y < X < Z) is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used to estimate the parameters namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.
Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.