二嵌段共聚物模型的改进跨跃时间推进法数值逼近

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Computation Pub Date : 2023-11-02 DOI:10.3390/computation11110215
Lizhen Chen, Ying Ma, Bo Ren, Guohui Zhang
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引用次数: 0

摘要

本文研究了二嵌段共聚物模型的一种有效的改进跨越式时间推进方案。提议的方案有三个主要优点。首先,它在时间上是线性的,每一步只需要求解一个线性代数系统。与其他方法相比,这可以显著降低计算成本。其次,该方案确保了无条件的能量稳定性,允许在不影响解稳定性的情况下使用大的时间步长。第三,严格证明了各时间步数值解的存在唯一性,保证了方法的可靠性和准确性。最后通过数值算例对该算法进行了验证,表明了该算法在实际应用中的准确性和有效性。
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Numerical Approximations of Diblock Copolymer Model Using a Modified Leapfrog Time-Marching Scheme
An efficient modified leapfrog time-marching scheme for the diblock copolymer model is investigated in this paper. The proposed scheme offers three main advantages. Firstly, it is linear in time, requiring only a linear algebra system to be solved at each time-marching step. This leads to a significant reduction in computational cost compared to other methods. Secondly, the scheme ensures unconditional energy stability, allowing for a large time step to be used without compromising solution stability. Thirdly, the existence and uniqueness of the numerical solution at each time step is rigorously proven, ensuring the reliability and accuracy of the method. A numerical example is also included to demonstrate and validate the proposed algorithm, showing its accuracy and efficiency in practical applications.
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来源期刊
Computation
Computation Mathematics-Applied Mathematics
CiteScore
3.50
自引率
4.50%
发文量
201
审稿时长
8 weeks
期刊介绍: Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to: bioinformatics mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions mathematical modeling of pathways and genetic interactions neuroscience computation including neural modeling, brain theory and neural networks computational chemistry, including, but not limited to: new theories and methodology including their applications in molecular dynamics computation of electronic structure density functional theory designing and characterization of materials with computation method computation in engineering, including, but not limited to: new theories, methodology and the application of computational fluid dynamics (CFD) optimisation techniques and/or application of optimisation to multidisciplinary systems system identification and reduced order modelling of engineering systems parallel algorithms and high performance computing in engineering.
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