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Comparison of Exact and Numerical Solutions with Special Attention to First Order Ordinary Differential Equations

机译:一阶常微分方程的精确解与数值解的比较

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In this paper I solved three first-order ordinary differential equations (ode) both analytically and numerically using 4 th order Runge-Kutta method (RK4). I selected differential equations which can also be solved analytically so as to compare the numerical solutions with the analytical solutions and see the accuracy of the 4 th order RungeKutta method in solving ordinary differential equations of type linear, separable and exact. Both solutions were obtained by employing a computer program written in FORTRAN 90/95. The absolute errors associated with different step sizes have been calculated and the efficient step size for the three types of odes under consideration has been identified. I found out that this numerical method is computationally more efficient and very accurate in solving first-order ordinary differential equations of the three types. This is verified from the relatively small (negligible) differences between the numerical and analytical values (absolute errors).To illustrate the efficiency of the method and for better visualization of its accuracy, the numerical and analytical solutions were plotted against the independent variable. For the differential equations under consideration, the efficient step size (the one with smallest average absolute error) is h = 0.100. When the step size decreases from 0.500 to 0.100, both the relative and absolute errors show a slight decline but they show a slight rise when the step size decreases further from 0.1 to 0.02. This is due to over accumulation of round off errors. Given step size h = 0.100, 4 th order Runge-Kutta method is found to be the most efficient for solving the linear ode. The possible reason for this is the relatively smallest degree (extent of nonlinearity) of the analytic solution associated with the linear ode. Further analysis should be made for detailed reasoning. Key words: Numerical solution, analytic solution, Runge-Kutta method, efficient step size.
机译:在本文中,我使用四阶Runge-Kutta方法(RK4)在解析和数值上求解了三个一阶常微分方程(ode)。我选择了也可以解析求解的微分方程,以便将数值解与解析解进行比较,并了解四阶RungeKutta方法在求解线性,可分离和精确类型的常微分方程中的准确性。两种解决方案都是通过使用FORTRAN 90/95编写的计算机程序获得的。已经计算了与不同步长相关的绝对误差,并且已经确定了所考虑的三种类型的信号的有效步长。我发现在求解这三种类型的一阶常微分方程时,该数值方法在计算上更有效且更准确。数值和分析值之间的相对较小(可忽略)差异(绝对误差)证明了这一点。为说明该方法的效率并更好地可视化其准确性,针对独立变量绘制了数值和分析解。对于所考虑的微分方程,有效步长(平均绝对误差最小的步长)为h = 0.100。当步长从0.500减小到0.100时,相对误差和绝对误差都显示出轻微的下降,但是当步长从0.1减小到0.02时,相对误差和绝对误差都出现轻微上升。这是由于舍入错误的累积所致。给定步长h = 0.100,发现四阶Runge-Kutta方法是求解线性ode的最有效方法。造成这种情况的可能原因是与线性极点相关的解析解的相对程度(非线性程度)。应该进行进一步分析以获得详细的推理。关键词:数值解,解析解,Runge-Kutta方法,有效步长。

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