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العنوان
Numerical solution to some random nonlinear ordinary differential equations /
المؤلف
El-Kott, Ibrahim Abd El-Monem Ali.
هيئة الاعداد
باحث / ابراهيم عبد المنعم على القط
مشرف / ابراهيم لطفى حسن القلا
مشرف / احمد محمد عبدالله السعيد
مشرف / رضا عبده عبد المنعم
الموضوع
Random nonlinear equations. Recovery technique.
تاريخ النشر
2020.
عدد الصفحات
online resource (87 pages) :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة
تاريخ الإجازة
1/1/2020
مكان الإجازة
جامعة المنصورة - كلية الهندسة - الرياضيات والفيزياء الهندسية
الفهرس
Only 14 pages are availabe for public view

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Abstract

In this work, a new technique using finite element method is introduced for solving random nonlinear differential equations. In this technique, we use the finite element method to solve the considered problem at some selected values for the random variables. This yields a system of nonlinear algebraic equations that is then solved using simple iteration method. Then by using fitting over the selected values of the random variables, and utilizing the basis functions of the finite element method, we obtain the approximate solution as a function in both space and random variable. This thesis is organized as follows:In chapter 1, firstly we introduce a brief review of some basic concepts that are used through this thesis. Concept of mathematical modeling, random variable, random differential equations, and finite element method are presented. Finally, the objective of this thesis is introduced.In chapter 2, we illustrate the proposed technique of using finite element method for solving second order nonlinear random ordinary differential equations. Then this technique is applied to some numerical examples with different types of nonlinearities. The results obtained illustrate the efficiency of the proposed scheme as the approximate calculation and their expectation and variance agree with those of the exact solution.In chapter 3, we employ the proposed technique presented in chapter 2 to solve dimensionless nonlinear convective radiative fin equation with two random parameters.In chapter 4, we used polynomial preserving recovery (PPR) to improve the discretization scheme of the proposed technique in chapter 2. Then, we introduce the conclusion and the suggested future work in chapter 5.