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

0238623马辛塔库马对地下水的准确描述是制定可靠和有效的地下水管理做法的一个重要因素。准确和可靠地估计水力传导性分布、污染物分布和/或污染源释放历史对于估计地下水产量、设计有效的清理策略以及确定污染事件中的责任方是必要的。这需要解决反问题，因为直接测量详细的地下属性是不可行的。反问题很难解决，而且需要大量的计算。这份多学科的职业建议书将探索有效解决大规模地下表征反问题的新计算策略。该职业建议书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反问题中的应用。所提出的开发将针对并行超级计算机和新兴的计算环境，如计算网格。这项提议将探讨几个新的想法，以提高方法的效率和灵活性。该计算方法将通过与北卡罗来纳州环境和自然资源部(NCDENR)的合作，使用一系列地下表征问题进行严格测试和验证，包括案例研究、已公布的现场结果和在北卡罗来纳州现场问题的应用。测试和验证活动将使人们更好地理解使用GA-LS混合算法来解决广泛的地下表征问题，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，没有达成一致的努力。教育活动的重点将是通过将拟议研究的几个组成部分纳入现有课程和新课程，弥合环境工程和计算科学之间的差距。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。其中一门课程是入门级研究生课程，将作为NCSU远程教育计划的目标。将开发一个互动培训模块，向学生和实践者介绍不同的逆向建模方法。全国各地的教育工作者和实践者将通过网络轻松访问本模块。将通过与北卡罗来纳A&T州立大学的合作，向少数族裔环境工程专业的学生介绍计算科学教育。这些教育活动将影响环境工程专业学生和从业者的计算科学教育。与NCDENR的合作将导致将知识转移给北卡罗来纳州的从业人员和政策制定者。这些活动预计将在建议期以外的研究和教育活动中促进PI和NCDENR之间的长期关系。除了出版物和专业介绍外，还将有意识地努力通过项目网页迅速传播教学材料、研究方法和成果以及软件。

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.