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arXiv 0910.3583math.APmath.DS
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带惯性项的Cahn-Hilliard方程的轨道吸引子和光滑吸引子

Trajectory and smooth attractors for Cahn-Hilliard equations with inertial term

Maurizio Grasselli, Giulio Schimperna, Sergey Zelik

摘要:

本文对一些物理学家提出的经典Cahn-Hilliard方程进行了修正。这种修改是通过添加二阶时间导数的顺序参数乘以惯性系数,这通常是小的相比,其他物理常数。这个方程的主要特点是,即使是一个全球有界的非线性是“超临界”的情况下,两个和三个空间维度。因此,用于研究半线性双曲型方程的标准方法在这种情况下不是很有效。然而,我们最近证明了强解的整体存在性和耗散性的二维情况下(与立方控制增长的非线性)和3D情况下的小惯性系数和任意增长率的非线性。本文研究了该方程的弱(能量)解的长时间行为,是对前人研究结果的自然补充。也就是说,我们证明了能量吸引子和强解吸引子在上述两种情况下是一致的。因此,能量解是渐近光滑的。此外,我们还证明了任意能量解的非光滑部分随时间指数衰减,并由此推论出前面构造的强解的(光滑)指数吸引子同时也是能量解的指数吸引子.

英文摘要:

The paper is devoted to a modification of the classical Cahn-Hilliard equation proposed by some physicists. This modification is obtained by adding the second time derivative of the order parameter multiplied by an inertial coefficient which is usually small in comparison to the other physical constants. The main feature of this equation is the fact that even a globally bounded nonlinearity is "supercritical" in the case of two and three space dimensions. Thus the standard methods used for studying semilinear hyperbolic equations are not very effective in the present case. Nevertheless, we have recently proven the global existence and dissipativity of strong solutions in the 2D case (with a cubic controlled growth nonlinearity) and for the 3D case with small inertial coefficient and arbitrary growth rate of the nonlinearity. The present contribution studies the long-time behavior of rather weak (energy) solutions of that equation and it is a natural complement of the results of our previous papers. Namely, we prove here that the attractors for energy and strong solutions coincide for both the cases mentioned above. Thus, the energy solutions are asymptotically smooth. In addition, we show that the non-smooth part of any energy solution decays exponentially in time and deduce that the (smooth) exponential attractor for the strong solutions constructed previously is simultaneously the exponential attractor for the energy solutions as well.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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