CAREER: High-End Computing in Environmental Engineering With Application to Subsurface Characterization

准确的地下特征是发展可靠和有效的地下水管理实践的重要因素。准确可靠地估计水力传导率分布、污染物分布和/或污染源释放历史对于估算地下水产量、设计有效的清理策略以及确定污染事件中的责任方等问题是必要的。这需要解决一个逆问题，因为直接测量详细的地下性质是不可行的。逆问题求解困难，计算量大。这个多学科的CAREER提案将研究新的计算策略，以有效解决地下表征中的大规模逆问题。该职业建议的主要重点是通过开发灵活的原型测试环境，研究混合遗传算法-局部搜索（GA-LS）方法和并行计算在地下表征逆问题中的应用。提议的开发将针对并行超级计算机以及新兴的计算环境，如计算网格。本建议将探讨若干新想法，以提高该方法的效率和灵活性。计算方法将通过许多地下特征问题进行严格的测试和验证，包括案例研究、已公布的现场结果，并通过与北卡罗来纳州环境和自然资源部（NCDENR）合作，将其应用于北卡罗来纳州的现场问题。测试和验证活动将使人们更好地理解使用混合GA-LS算法来解决各种地下表征问题，并可能导致方法的进一步改进。目前，在将计算科学内容引入环境工程教育方面还没有一致的努力。教育活动的重点是通过将拟议研究的几个组成部分整合到现有和新的课程中，弥合环境工程和计算科学之间的差距。在逆建模、地下表征、GA-LS算法和并行计算方面的研究活动将被纳入研究生和本科课程。其中一门入门级研究生课程将面向NCSU远程教育项目。将开发互动式训练模组，向学生和实务人员介绍不同的逆建模方法。全国各地的教育工作者和从业人员都可以通过网络方便地访问该模块。通过与北卡罗来纳农工州立大学的合作，将计算科学教育引入少数民族环境工程专业的学生。这些教育活动将影响环境工程学生和实践者的计算科学教育。与NCDENR的合作将导致向北卡罗莱纳州的从业人员和决策者转移知识。预期这些活动将在提议期之后促进PI和国家减灾研究中心在研究和教育活动方面的长期关系。除了出版物和专业报告外，还将有意识地努力通过项目网页迅速传播教材、研究方法和结果以及软件。

0238623 Mahinthakumar Accurate characterization of the subsurface is an important element in the development of reliable and efficient groundwater management practices. Accurate and reliable estimation of hydraulic conductivity distribution, contaminant distribution, and/or contaminant source release history is necessary for problems such as estimating groundwater yields, design of efficient cleanup strategies, and identifying responsible parties in a contamination incident. This requires solution of an inverse problem because direct measurement of detailed subsurface properties is not feasible. Inverse problems are difficult to solve and are computationally demanding. This multidisciplinary CAREER proposal will investigate novel computational strategies for the efficient solution of large-scale inverse problems in subsurface characterization.A major focus of this career proposal is to investigate the use of hybrid genetic algorithm - local search (GA-LS) approaches and parallel computing for subsurface characterization inverse problems by developing a flexible prototype test environment.The proposed development will target parallel supercomputers as well as emerging computing environments such as the computational grid. Several new ideas will be explored in this proposal to improve the efficiency and flexibility of the approach. The computational approach will be rigorously tested and validated using a number of subsurface characterization problems including case studies, published field results, and application to field problems in North Carolina through collaboration with North CarolinaDepartment of Environment and Natural Resources (NCDENR). The testing and validation activities will lead to a greater understanding of using hybrid GA-LS algorithms for a wide range of subsurface characterization problems and may lead to further improvements of the approaches.Currently there are no concerted efforts in bringing computational science content into environmental engineering education. The educational activities will focus on bridging the gap between environmental engineering and computational science by integrating several components of the proposed research into existing and new courses. Research activities in inverse modeling, subsurface characterization, GA-LS algorithms, and parallel computing will be incorporated into graduate and undergraduate courses. One of these courses, an entry-level graduate course, will be targeted for the NCSU Distance Education Program. An interactive training module will be developed to introduce different inverse modeling approach to students and practitioners. Easy access to this module will be provided via the web for educators and practitioners throughout the nation. Introduction of computational science education to minority environmental engineering students will be pursued through collaboration with North Carolina A&T State University. These educational activities will impact computational science education among environmental engineering students and practitioners. The collaborations with NCDENR will result in the transfer of knowledge to practitioners and policy makers in North Carolina. These activities are expected to foster long-term relationships between the PI and NCDENR in research and educational activities beyond the proposal period. In addition to publications and professional presentations, a conscious effort will be made to quickly disseminate teaching materials, research methodologies and findings, and software through a project web page.