Результаты поиска по 'embedding theorems':
Найдено статей: 2
  1. Nayshtut Yu.S.
    Neumann's method to solve boundary problems of elastic thin shells
    Computer Research and Modeling, 2015, v. 7, no. 6, pp. 1143-1153

    This paper studies possibilities to use Neumann's method to solve boundary problems of elastic thin shells. Variational statement of statical problems for shells allows examining the problems within the space of distributions. Convergence of the Neumann's method is proved for the shells with holes when the boundary of the domain is not completely fixed. Numerical implementation of the Neumann's method normally takes a lot of time before some reliable results can be achieved. This paper suggests a way to improve convergence of the process and allows for parallel computing and checkout procedure during calculations.

    Keywords: boundary problems, theory of thin elastic shells, Neumann's method, variational principles, Korn's inequality, distributions, embedding theorems, Green tensor.
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  2. Maglevanny I.I., Karyakina T.I.
    Numerical solution of Urysohn type nonlinear second kind integral equations by successive quadratures using embedded Dormand and Prince scheme 5(4)
    Computer Research and Modeling, 2020, v. 12, no. 2, pp. 275-300

    We present the iterative algorithm that solves numerically both Urysohn type Fredholm and Volterra nonlinear one-dimensional nonsingular integral equations of the second kind to a specified, modest user-defined accuracy. The algorithm is based on descending recursive sequence of quadratures. Convergence of numerical scheme is guaranteed by fixed-point theorems. Picard’s method of integrating successive approximations is of great importance for the existence theory of integral equations but surprisingly very little appears on numerical algorithms for its direct implementation in the literature. We show that successive approximations method can be readily employed in numerical solution of integral equations. By that the quadrature algorithm is thoroughly designed. It is based on the explicit form of fifth-order embedded Runge–Kutta rule with adaptive step-size self-control. Since local error estimates may be cheaply obtained, continuous monitoring of the quadrature makes it possible to create very accurate automatic numerical schemes and to reduce considerably the main drawback of Picard iterations namely the extremely large amount of computations with increasing recursion depth. Our algorithm is organized so that as compared to most approaches the nonlinearity of integral equations does not induce any additional computational difficulties, it is very simple to apply and to make a program realization. Our algorithm exhibits some features of universality. First, it should be stressed that the method is as easy to apply to nonlinear as to linear equations of both Fredholm and Volterra kind. Second, the algorithm is equipped by stopping rules by which the calculations may to considerable extent be controlled automatically. A compact C++-code of described algorithm is presented. Our program realization is self-consistent: it demands no preliminary calculations, no external libraries and no additional memory is needed. Numerical examples are provided to show applicability, efficiency, robustness and accuracy of our approach.

    Keywords: nonlinear Volterra–Fredholm integral equations, fixed point theorem, error analysis, iterative methods, fifth-order embedded Runge–Kutta rule, adaptive step-size control.

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