The goal of this research is to develop a numerical model that can be used to simulate the sedimentation process under two scenarios: first, the flocculation unit is on duty, and second, the flocculation unit is out of commission. The general equation of flow and sediment transport were solved using the finite difference method, then coded using Matlab software. The result of this study was: the difference in removal efficiency between the coded model and operational model for each particle size dataset was very close, with a difference value of +3.01%, indicating that the model can be used to predict the removal efficiency of a rectangular sedimentation basin. The study also revealed that the critical particle size was 0.01 mm, which means that most particles with diameters larger than 0.01 mm settled due to physical force, while most particles with diameters smaller than 0.01 mm settled due to flocculation process. At 10 m from the inlet zone, the removal efficiency was more than 60% of the total removal rate, indicating that increasing basin length is not a cost-effective way to improve removal efficiency. The influence of the flocculation process appears at particle sizes smaller than 0.01 mm, which is a small percentage (10%) of sieve analysis test. When the percentage reaches 20%, the difference in accumulative removal efficiency rises from +3.57% to 11.1% at the AL-Muthana sedimentation unit.
Due to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of appl
This paper deals with constructing mixed probability distribution from exponential with scale parameter (β) and also Gamma distribution with (2,β), and the mixed proportions are ( .first of all, the probability density function (p.d.f) and also cumulative distribution function (c.d.f) and also the reliability function are obtained. The parameters of mixed distribution, ( ,β) are estimated by three different methods, which are maximum likelihood, and Moments method,as well proposed method (Differential Least Square Method)(DLSM).The comparison is done using simulation procedure, and all the results are explained in tables.
The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the
... Show MoreBackground: Rehabilitation of the carious tooth to establish tooth structure integrity required cavity design that show a benign stress distribution. The aim of this study was to investigate the influence of the cavity position on the stress values in the reamining tooth structure restored with amalgam or resin composite. Materials and methods: Seven 2-D models of maxillary first premolar include class I cavity design was prepared, one sound tooth (A) 3 composite (B1, B2, and B3) and 3 amalgam (C1, C2, and C3). In design (BI and C1) the cavity position is in the mid distance between bacc-lingual cusp tip, design (B2 and C2) and (B3 and C3) shifted toward the buccal cusp and the lingual cusp for 0.5 mm respectively. One hundred N vertical
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