The scalar auxiliary variable (SAV) method was introduced by Shen et al. and has been broadly used to solve thermodynamically consistent PDE problems. By utilizing scalar auxiliary variables, the original PDE problems are reformulated into equivalent PDE problems. The advantages of the SAV approach, such as linearity, unconditionally energy stability, and easy-to-implement, are prevalent. However, there is still an open issue unresolved, i.e., the numerical schemes resulted from the SAV method preserve a "modified" energy law according to the auxiliary variables instead of the original variables. Truncation errors are introduced during numerical calculations so that the numerical solutions of the auxiliary variables are no longer equivalent to their original continuous definitions. In other words, even though the SAV scheme satisfies a modified energy law, it does not necessarily satisfy the energy law of the original PDE models. This paper presents one essential relaxation technique to overcome this issue, which we named the relaxed-SAV (RSAV) method. Our RSAV method penalizes the numerical errors of the auxiliary variables by a relaxation technique. In general, the RSAV method keeps all the advantages of the baseline SAV method and improves its accuracy and consistency noticeably. Several examples have been presented to demonstrate the effectiveness of the RSAV approach.
翻译:Salar辅助变量(SAV)方法由Shen等人采用,并广泛用于解决热力一致的PDE问题。通过使用 scal 辅助变量,最初的PDE问题被重新改造成等效的PDE问题。SAV方法的优点很普遍,如线性、无条件的能源稳定性和易于执行等,但SAV方法的优点仍然很普遍。然而,还有一个尚未解决的问题,即SAV方法产生的数字办法根据辅助变量而不是原始变量来保留“修改”的能源法。在数字计算中引入了调校错误,使辅助变量的数值解决方案不再等同于原有的连续定义。换句话说,即使SAV方案符合经修订的能源法,但不一定满足原PDE模型的能源法。本文提出了克服这一问题的一种基本的放松技术,即我们称之为“放松-SAV(RSAV)”方法。我们RSAV方法用较宽松的技术来惩罚辅助变量的数字错误。一般来说,RSAV方法有好几种例子表明SAAV方法的准确性。