Reliability Assessment of the Serviceability Performance of Geotechnical Structures Using Neural Networks

使用神经网络对岩土结构的使用性能进行可靠性评估

• 批准号: 0300198
• 负责人: Charng Juang
• 金额: $ 29.73万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-01 至 2008-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0300198&HistoricalAwards=false
• 关键词: Reliability; Assessment; Serviceability; Performance; Geotechnical

In this research project the feasibility of integrating finite element method and neural network technologies in a reliability-based framework for assessing serviceability reliability of geotechnical structures such as braced excavation systems is explored. A deep braced excavation in an urban area is a complex construction operation that often causes unacceptable ground movement and damage to adjacent buildings. Reliability assessment of potential ground displacement and damage to adjacent buildings aids in the safe design and construction of such geotechnical structures. The framework and procedures for conducting reliability assessment are established based on the results of reliability analyses. Provisions for reliability updating using field monitoring/measurement data are also established. Intellectually, this research may lead to a significantly improved method for design and construction of deep braced excavations that is both sound and safe for the environment. The developed methodology, which integrates the finite element method, neural networks, and the observational method into a reliability-based framework, is considered innovative. This methodology, if successfully developed, represents a significant breakthrough in assessing reliability of complex geotechnical structures. The broader impacts of the proposed research are also significant. First, this research is likely to result in an improved method for design and construction of deep braced excavation that is both sound and safe for the environment. The results of the research may be adopted by the engineering community, and thus, contribute in a significant way to protecting the public and their properties. Second, the results of the research will be disseminated broadly through a number of ways. Technology transfer, which is emphasized in this project, is an important element in the overall objective of integrating research and education. Third, the proposed research will enhance the infrastructure for research at Clemson University through its strong national and international collaboration. Fourth, the proposed research will broaden participation of underrepresented groups in a significant way, by participation of a female engineering faculty from an undergraduate institution through a subcontract and a female postdoctoral research assistant at Clemson University, and by recruiting and mentoring graduate and undergraduate assistants from underrepresented groups. Fifth and lastly, but equally important, the proposed research will advance the state of knowledge while promoting teaching, training, and learning by incorporating various activities that contribute to the overall objective of research and education integration.

在本研究项目中，探讨了将有限元法和神经网络技术集成在基于可靠性的框架中用于评估岩土结构（如支撑开挖系统）的可用性可靠性的可行性。 在城市地区进行深支撑开挖是一项复杂的施工作业，通常会导致不可接受的地面移动和对邻近建筑物的损坏。 潜在的地面位移和损坏相邻建筑物的可靠性评估艾滋病的安全设计和施工等岩土工程结构。 根据可靠性分析的结果，建立了进行可靠性评估的框架和程序。 还制定了使用现场监测/测量数据进行可靠性更新的规定。 从智力上讲，这项研究可能会导致一个显着改善的方法，设计和施工的深支撑开挖，既健全和安全的环境。 所开发的方法，它集成了有限元法，神经网络和观测方法到一个基于可靠性的框架，被认为是创新的。这种方法，如果开发成功，代表了一个重大突破，在评估复杂的岩土结构的可靠性。 拟议研究的更广泛影响也很重要。 首先，这项研究可能会导致一个改进的方法，设计和施工的深支撑开挖，是既健全和安全的环境。 研究结果可能会被工程界采用，从而为保护公众及其财产做出重要贡献。 第二，将通过多种方式广泛传播研究成果。本项目所强调的技术转让是研究与教育相结合这一总体目标的一个重要因素。 第三，拟议的研究将通过其强大的国家和国际合作，加强克莱姆森大学的研究基础设施。第四，拟议的研究将扩大代表性不足的群体的参与，在一个显着的方式，通过一个女工程教师从本科院校的参与，通过一个女博士后研究助理在克莱姆森大学，并从代表性不足的群体招聘和指导研究生和本科生助理。 第五，也是最后一点，但同样重要的是，拟议的研究将通过纳入有助于实现研究和教育一体化总体目标的各种活动，在促进教学、培训和学习的同时，提高知识水平。