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A reverse engineering approach to optimal design of site investigation schemes and monitoring networks

现场调查方案和监测网络优化设计的逆向工程方法

基本信息

批准号：
187824825
负责人：
Professor Dr.-Ing. Wolfgang Nowak
金额：
--
依托单位：
Lehrstuhl für Hydromechanik und Hydrosystemmodellierung
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2010
资助国家：
德国
起止时间：
2009-12-31 至 2013-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/187824825?language=en
关键词：
reverse engineering approach optimal design

项目摘要

The goal of experimental design is to investigate a system such that maximum information is achieved from a given, limited budget for investigation. Looking at groundwater as a drinking water resource, its quality and safety is hard to assess and predict mainly because subsurface materials are heterogeneous, and there are too few data to resolve this heterogeneity and extract the necessary key properties of the system. Experimental design can help to optimize subsurface exploration, maximizing the desired prediction confidence of groundwater quality and safety in spite of limited exploration budgets. However, experimental design is currently heavily limited by its computer demands, especially in complex large-scale problems such as stochastic groundwater quality models. The current project will re-formulate optimal design theory within a new information-theoretic perspective. Instead of traditionally and tediously searching through all possible measurement locations to find the most informative ones, the direction of analysis will be reverted to directly identify the most informative ones in a single step. This will dramatically reduce the computational load, allowing to apply optimal design for larger, more complex and hence more realistic problems. At the same time, this avoids simplifications or linearizations that compromise the information content of data sets in the analysis. Instead of giving in to computational restrictions, the new method will allow tackling current, goal-oriented and application- driven research tasks. At first developed and applied within the groundwater perspective, the new method will then be exported as a valuable tool for many scientific disciplines that face similar uncertainties in heterogeneous or complex dynamic systems.

实验设计的目标是研究一个系统，以便从给定的有限的研究预算中获得最大的信息。地下水作为一种饮用水资源，其质量和安全性很难评估和预测，主要是因为地下物质是异质的，而且数据太少，无法解决这种异质性并提取系统的必要关键属性。实验设计可以帮助优化地下勘探，最大限度地提高所需的预测信心的地下水质量和安全，尽管有限的勘探预算。然而，实验设计目前严重限制其计算机的要求，特别是在复杂的大规模问题，如随机地下水水质模型。目前的项目将在一个新的信息理论的角度重新制定最优设计理论。与传统上繁琐地搜索所有可能的测量位置以找到信息量最大的位置不同，分析的方向将恢复到在单个步骤中直接识别信息量最大的位置。这将大大减少计算负荷，允许应用更大，更复杂，因此更现实的问题的优化设计。与此同时，这避免了简化或线性化，这些简化或线性化会损害分析中数据集的信息内容。新方法将允许处理当前的、面向目标的和应用驱动的研究任务，而不是屈服于计算限制。在第一次开发和应用的地下水的角度来看，新的方法，然后将出口作为一个有价值的工具，许多科学学科面临类似的不确定性，在异构或复杂的动态系统。