氡测度空间中的结构化混凝破碎方程:统一离散和连续模型

IF 1.9 3区 数学 Q2 Mathematics
Azmy S. Ackleh, Rainey Lyons, N. Saintier
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引用次数: 5

摘要

我们提出了一个结构化的凝固破碎模型来描述海洋浮游植物的种群动态。该模型建立在Radon测度空间上,具有有界Lipschitz范数,统一了离散型和连续型混凝破碎模型的研究。我们证明了该模型是适定的,并表明它可以简化为经典的离散和连续混凝破碎模型。为了了解凝固和破碎等物理过程与生长、繁殖和死亡等生物过程之间的相互作用,我们建立了溶液的正则性结果,并利用它来表明在模型参数的某些条件下,固定溶液是绝对连续的。给出了一种质量守恒的半离散逼近格式,并证明了其收敛于唯一弱解。然后,我们使用该方案对模型进行数值模拟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structured coagulation-fragmentation equation in the space of radon measures: Unifying discrete and continuous models
We present a structured coagulation-fragmentation model which describes the population dynamics of oceanic phytoplankton. This model is formulated on the space of Radon measures equipped with the bounded Lipschitz norm and unifies the study of the discrete and continuous coagulation-fragmentation models. We prove that the model is well-posed and show it can reduce down to the classic discrete and continuous coagulation-fragmentation models. To understand the interplay between the physical processes of coagulation and fragmentation and the biological processes of growth, reproduction, and death, we establish a regularity result for the solutions and use it to show that stationary solutions are absolutely continuous under some conditions on model parameters. We develop a semi-discrete approximation scheme which conserves mass and prove its convergence to the unique weak solution. We then use the scheme to perform numerical simulations for the model.
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来源期刊
CiteScore
2.70
自引率
5.30%
发文量
27
审稿时长
6-12 weeks
期刊介绍: M2AN publishes original research papers of high scientific quality in two areas: Mathematical Modelling, and Numerical Analysis. Mathematical Modelling comprises the development and study of a mathematical formulation of a problem. Numerical Analysis comprises the formulation and study of a numerical approximation or solution approach to a mathematically formulated problem. Papers should be of interest to researchers and practitioners that value both rigorous theoretical analysis and solid evidence of computational relevance.
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