Identification of environmental categories for Markovian deterioration models of bridge decks
Identification of environmental categories for Markovian deterioration models of bridge decks
复制标题
桥面马尔可夫劣化模型的环境类别识别
DOI：
10.1061/(asce)1084-0702(2003)8:6(353
复制
发表时间：
2003
影响因子：
3.6
通讯作者：
M. Mirza
中科院分区：
文献类型：
--
作者：
G. Morcous;Z. Lounis;M. Mirza
一般来说，最先进的桥梁管理系统采用马尔可夫链模型来预测未来的条件下的桥梁元件和网络在不同的环境中，当各种维护措施的实施。然而，用于描述桥梁元件的各种可能环境的类别既没有准确定义，也没有明确地与影响元件劣化的外部因素联系起来。在本文中，提出了一种新的方法，提供一个有效的决策支持工具，以确定类别，最好地定义特定于他们的桥梁结构的环境和运营条件的运输机构。这种方法是基于遗传算法，以确定最适合每个环境类别的恶化参数的组合。所提出的方法是适用于开发马尔可夫恶化模型的混凝土桥面使用从魁北克省运输部获得的实际数据。该应用程序说明了所提出的方法的能力，以相关的环境类别的定义参数，如公路等级，区域，平均每日交通量，卡车交通的百分比，在一个准确和有效的方式。
In general, state-of-the-art bridge management systems have adopted Markov-chain models to predict the future condition of bridge elements and networks in different environments when various maintenance actions are implemented. However, the categories used to describe the various possible environments for a bridge element are neither accurately defined nor explicitly linked to the external factors affecting the element deterioration. In this paper, a new approach is proposed to provide transportation agencies with an effective decision support tool to identify the categories that best define the environmental and operational conditions specific to their bridge structures. This approach is based on genetic algorithms to determine the combinations of deterioration parameters that best fit each environmental category. The proposed approach is applied to develop Markovian deterioration models for concrete bridge decks using actual data obtained from the Ministre des Transports du Qubec. This application illustrates the ability of the proposed approach to correlate the definition of environmental categories to parameters, such as highway class, region, average daily traffic, and percentage of truck traffic, in an accurate and efficient manner.