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北京石油化工学院2026年研究生招生接收调剂公告
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tianlangxingaa

铁杆木虫 (著名写手)

[交流] 【分享】【分享】多尺度模拟 Multiscale modeling

In engineering, physics, meteorology and computer science, multiscale modeling is the field of solving physical problems which have important features at multiple scales, particularly multiple spatial and(or) temporal scales. Important problems include scale linking (Baeurle 2009, Baeurle 2006, Knizhnik 2002, Adamson 2007).
Multiscale modeling in physics is aimed to calculation of material properties or system behaviour on one level using information or models from different levels. On each level particular approaches are used for description of a system. Following levels are usually distinguished: level of quantum mechanical models (information about electrons is included), level of molecular dynamics models (information about individual atoms is included), mesoscale or nano level (information about groups of atoms and molecules is included), level of continuum models, level of device models. Each level addresses a phenomenon over a specific window of length and time. Multiscale modeling is particularly important in integrated computational materials engineering since it allows to predict material properties or system behaviour based on knowledge of the atomistic structure and properties of elementary processes.
In Operations Research, multiscale modeling addresses challenges for decision makers which come from multiscale phenomena across organizational, temporal and spatial scales. This theory fuses decision theory and multiscale mathematics and is referred to as Multiscale decision making. The Multiscale decision making approach draws upon the analogies between physical systems and complex man-made systems.
In Meteorology, multiscale modeling is the modeling of interaction between weather systems of different spatial and temporal scales that produces the weather that we experience finally. The most challenging task is to model the way through which the weather systems interact as models cannot see beyond the limit of the model grid size. In other words, to run an atmospheric model that is having a grid size (very small ~ 500 m) which can see each possible cloud structure for the whole globe is computationally very expensive. On the other hand, a computationally feasible Global climate model (GCM, with grid size ~ 100km, cannot see the smaller cloud systems. So we need to come to a balance point so that the model becomes computationally feasible and at the same we do not loose much information, with the help of making some rational guesses, a process called Parameterization.


see details:  http://en.wikipedia.org/wiki/Multiscale_modeling
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zhgj1979

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lei0736(金币+2):谢谢 2010-02-08 09:25
多尺度模拟确实最近比较热门,但偶觉得这个其实没有太多的新东西,只是新瓶子装老酒。(虽然它是说将几个尺度贯通起来,说明体系或物质的性质等等)
2楼2010-02-08 09:19:18
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lei0736

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小木虫(金币+0.5):给个红包,谢谢回帖交流
没搞过多尺度 呵呵 羡慕
楼上说的也是实话 确实是将几个尺度的连接起来 但是可以扩展时间 空间尺度 从工程和实际应用来说大有好处
关键难题应该是怎么实现各个尺度的“无缝连接” 边界条件如何衔接才能保证各个尺度的模拟精度合适 计算量合适 其实最难的就是条件自洽的实现 如算法和编程
3楼2010-02-08 09:28:45
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tianlangxingaa

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lei0736(金币+2):3x 2010-02-13 10:56
引用回帖:
Originally posted by lei0736 at 2010-02-08 09:28:45:
没搞过多尺度 呵呵 羡慕
楼上说的也是实话 确实是将几个尺度的连接起来 但是可以扩展时间 空间尺度 从工程和实际应用来说大有好处
关键难题应该是怎么实现各个尺度的“无缝连接” 边界条件如何衔接才能保证各个 ...

是的,各个尺度连接起来的方案也各不相同,Kremer组,Vatulanni组,Doi组等等都曾经做过系列工作,都是从potential着手,希望这是个很好的课题。
4楼2010-02-09 20:23:38
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zhgj1979

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小木虫(金币+0.5):给个红包,谢谢回帖交流
请问楼上的是应化所的同仁么?
5楼2010-02-10 20:53:55
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