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HYBRID FINITE DIFFERENCE METHODS FOR SOLVING MODIFIED BURGERS AND BURGERS-HUXLEY EQUATIONS

机译:求解修正的BURGERS和BURGERS-HUXLEY方程的混合有限差分法。

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Most phenomena in the real world are described through non-linear equations. One of the most fascinating extensions of the Burgers: equation in the description of non-linear phenomena is the modified Burgers' equation and the Burgers-Huxley equation. Modified Burgers equation has varied applications in the field of Physics and particularly wherein dissipation is a significant aspect of wave propagation. On the other hand. Burgers-Huxley equation, under special choice of parameters, namely the Hodgkin-Huxley equation, describes how action potentials in neurons are initiated and propagated. This equation also shows the interplay between non-linear reaction and diffusive transport. Our objective in this paper is to devise and analyze robust numerical methods for numerically solving the modified Burgers' equation and the Burgers-Huxley equation. The methods are primarily based on monotone hybrid finite difference methods with piecewise uniform layer adaptive mesh. A rigorous analysis of the proposed methods for uniform convergence is given and the error estimates are derived. Several numerical experiments on benchmark problems are carried out and comparison of the numerical results made with the existing methods demonstrate the improvement and efficiency of the proposed methods.
机译:现实世界中的大多数现象都是通过非线性方程式描述的。 Burgers最吸引人的扩展之一:非线性现象描述中的方程是修正的Burgers方程和Burgers-Huxley方程。修正的Burgers方程在物理学领域有各种应用,特别是其中耗散是波传播的重要方面。另一方面。在特殊选择参数的情况下,Burgers-Huxley方程即Hodgkin-Huxley方程描述了如何启动和传播神经元中的动作电位。该方程还显示了非线性反应与扩散传输之间的相互作用。本文的目的是设计和分析鲁棒的数值方法,用于数值求解修正的Burgers方程和Burgers-Huxley方程。该方法主要基于具有分段均匀层自适应网格的单调混合有限差分方法。对所提出的均匀收敛方法进行了严格的分析,并得出了误差估计。进行了一些基准问题的数值实验,并与现有方法进行的数值结果比较证明了所提出方法的改进和效率。

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