关于反复序列的外模型:斐波那契,帕多万和其他数列
1Observatoire de Paris, Université Paris-Saclay, Sorbonne Université, Laboratoire de Physique des Plasmas, CNRS, Ecole Polytechnique, F-91120 Palaiseau, France.
Physical review. E
|March 19, 2025
概括
使用像斐波纳契数列这样的反复波数的新外模型可以节省能量和螺旋性. 这些模型模仿标准的外模型,提供了对流间歇性和模拟中的潜在用途的见解.
科学领域:
- * 流体动力学 流体动力学
- * 计算物理 计算物理
背景情况:
- *标准外模型对于研究流是至关重要的.
- *这些模型通常依赖于自我相似的缩放,这可能是限制性的.
- *探索替代波数结构是推进流模型的关键.
研究的目的:
- * 提出和分析基于反复波数序列的新外模型.
- * 在这些新模型中研究能量和螺旋性的保存特性.
- * 将这些模型的性能与模拟流的标准外模型进行比较.
主要方法:
- * 在重复序列上定义外变量 (例如,斐波纳契,帕多万).
- * 在没有确切的自我相似性的情况下,对不变性保存的泛化相互作用系数.
- *分析功率定律光谱,光谱流和结构函数缩放.
- * 考虑局部和远程相互作用,包括螺旋模型.
主要成果:
- * 拟议的外模型保留了诸如能量和螺旋性之类的不确定的不变量.
- *这些模型具有与标准外模型相同的特征,包括功率定律光谱和光谱流.
- * 结构函数中自相似缩放的类似偏差表明可比的乱间歇性.
- * 一个具有远程相互作用的螺旋模型显示了一个反向级联.
结论:
- *反复波数外模型为标准模型提供了可行的替代方案.
- *这些模型可以作为诊断工具或子网模型用于直接的数值模拟.
- *该配方允许在正规网格上进行稀疏波数表示.
- *新型螺旋模型可以捕捉反向级联,扩大外模型应用的范围.
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