Error analysis and simulations of complex phenomena
Error analysis and simulations of complex phenomena
复制标题
复杂现象的误差分析和模拟
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
Merri Wood
中科院分区：
文献类型：
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作者：
M. Christie;J. Glimm;J. Grove;D. Higdon;D. Sharp;Merri Wood
基于计算机的大规模模拟越来越多地用于预测复杂系统的行为。主要的例子包括天气，全球气候变化，核武器的性能，通过油藏的流动，以及先进飞机的性能。模拟总是涉及理论、实验数据和数值建模，所有这些都伴随着误差。因此，人们自然会问：“这些模拟可信吗？”“如何评估结果的准确性和可靠性？”本文列出了分析和组合可能发生的各种类型的错误的方法，然后给出了如何构建和使用错误模型的三个具体例子。在这两页的顶部是一个模拟的低粘度气体（紫色）取代高粘度石油（红色）在石油开采过程中。误差模型可用于改进该过程的石油产量预测。上图左侧是这种误差模型的一个组成部分，右侧是从简单经验模型结合全误差模型获得的特定油藏未来石油产量的预测。
Large-scale computer-based simulations are being used increasingly to predict the behavior of complex systems. Prime examples include the weather, global climate change, the performance of nuclear weapons, the flow through an oil reservoir, and the performance of advanced aircraft. Simulations invariably involve theory, experimental data, and numerical modeling, all with their attendant errors. It is thus natural to ask, “Are the simulations believable?” “How does one assess the accuracy and reliability of the results?” This article lays out methodologies for analyzing and combining the various types of errors that can occur and then gives three concrete examples of how error models are constructed and used. At the top of these two pages is a simulation of low-viscosity gas (purple) displacing higher-viscosity oil (red) in an oil recovery process. Error models can be used to improve predictions of oil production from this process. Above, at left, is a component of such an error model, and at right is a prediction of future oil production for a particular oil reservoir obtained from a simple empirical model in combination with the full error model.