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当工程师评估大坝的风险时,他们需要各种各样的信息,如仪器数据、事故的历史记录、之前的风险评估报告、施工记录、大坝几何形状、地理位置信息等。然而,这些信息大多记录在不同文件中,或者由机构、个人掌握。这种大坝相关历史数据的存储方式过于分散,无助于综合评估以及在存储数据中挖掘知识以及分析数据的有效可视化。如果没有综合的信息库,工程师很难有效地做出风险确定的决策。为改进风险确定决策制定过程,先进的信息建模、分析和可视化技术已成功应用在建筑和基础设施领域。笔者概述并评价了这些最佳实践应用在大坝风险评估中的适用性、优势和局限性。具体而言,笔者回顾了信息模型、数据标准、可视化系统和数据分析等领域的最佳实践,并探讨如何利用它们改进大坝风险评估。笔者提出的最佳实践可以使工程师在一个综合环境中审查和交换所有必要信息,有可能改进现有大坝风险管理过程。
When engineers assess the dam’s risks, they need a variety of information such as instrument data, accident history, previous risk assessment reports, construction records, dam geometry, geo-location information, and more. However, most of this information is recorded in different documents or by institutions and individuals. The storage of such dam-related historical data is too fragmented to contribute to comprehensive assessments and effective visualization of data mining and knowledge mining. Without a comprehensive repository of information, engineers find it difficult to make risk-determining decisions efficiently. Identifying decision-making processes to improve risk, advanced information modeling, analysis and visualization technologies have been successfully used in the fields of construction and infrastructure. The author summarizes and assesses the applicability, advantages and limitations of these best practices in dam risk assessment. Specifically, I review best practices in the areas of information modeling, data standards, visualization systems and data analysis, and discuss how to use them to improve dam risk assessment. The author’s best practices allow engineers to review and exchange all the necessary information in an integrated environment and make it possible to improve existing dam risk management processes.