Improving Calibration, Sensitivity and Uncertainty Analysis of Data Based Models of the Environment

0229176 鞋匠 特定地点的污染传输模型是基于现场数据和无法直接测量的参数值的校准。这种现场数据和校准模型的结合是环境分析中的有力工具。然而，使用这种模型的困难之一是，校准过程可以是非常苛刻的计算，如果它是彻底完成。一个更严重的计算障碍是量化的不确定性与模型预测的污染translation.This建议开发了一个新的计算程序（缩写ROCUS），可以应用于一系列的污染传输问题。在拟议的研究中，ROCUS将应用于纽约的一个大流域，PI的研究模型结果目前正在用于制定监管政策。ROCUS还将用于氯代乙烯的厌氧生物修复，使用由美国国防部收集的现场数据和PI及其学生开发的18种反应传输模型。ROCUS程序涉及一组计算效率高的算法，用于校准，结合灵敏度和不确定性分析，通过使用响应面方法进行集成。该研究的假设之一是，通过将当前使用的方法替换为待研究的两种新优化算法中的一种或两种，可以显着减少找到模型校准的良好值的计算时间。这两种方法都涉及使用径向基函数响应面与新的优化算法相结合。先前发表的论文和PI的计算实验支持这一假设。在何种程度上这一假设是有效的，将在拟议的研究中进行评估的准确性和计算速度的两个响应面优化算法与现有的启发式方法的系统比较。这些测试将在两个环境应用和标准的全局优化测试问题上进行。所代表的应用是非常严重的污染问题，其结果将增加对环境保护的科学理解和方法。将研究成果融入PI教授的两门课程中，实现教学和研究目标。研究基础设施的贡献将遵循研究的跨学科性质。此外，PI长期以来一直致力于促进代表性不足的群体，特别是女工程师，本研究项目将继续这一努力。

0229176 Shoemaker Site-specific pollution transport models are based on field data and the calibration of the parameter values that cannot be directly measured. This combination of field data and calibrated model is a powerful tool in environmental analysis. However, one of the difficulties in using such models is that the calibration process can be computationally very demanding if it is done thoroughly. An even more serious computational obstacle is the quantification of the uncertainty associated with model forecasts of pollution transport.This proposal develops a new computational procedure (acronym ROCUS) that can be applied to a range of pollution transport problems. In the proposed research, ROCUS will be applied to a large watershed in New York, for which the PI's research model results are currently being used in formulating regulatory policy. ROCUS will also be used for anaerobic bioremediation of chlorinated ethenes using field data collected by DOD and an 18 species reactive transport model developed by the PI and her students.The ROCUS procedure involves a group of computationally efficient algorithms for calibration, combined sensitivity and uncertainty analysis that is integrated through the use of response surface methods. One of the hypothesis of the study is that computation time to find good values for model calibration can be significantly reduced by replacing methods currently in use with one or both of the two new optimization algorithms to be investigated. These two methods both involve the use of a Radial Basis Function response surface coupled with a new optimization algorithm. Previously published papers and the PI's computational experiments support this hypothesis. The extent to which this hypothesis is valid will be assessed in the proposed research by a systematic comparison of accuracy and computational speed of the two response surface optimization algorithms with two existing heuristic methods. These tests will be performed on the two environmental applications and on standard global optimization test problems.The applications represented are very serious pollution problems, and the results will add to scientific understanding and to methods for environmental protection. The teaching and research objectives will be obtained by incorporation of research results into two courses the PI teaches. Research infrastructure contributions will follow from the interdisciplinary nature of the research. In addition, the PI has a long history of working to promote underrepresented groups, especially women engineers, and this research project will continue that effort.