Risk-based maintenance and rehabilitation decisions for transportation infrastructure networks

A method for determining optimal risk-based maintenance and rehabilitation (M&R) policies for transportation infrastructure is presented. The proposed policies guarantee a certain performance level across the network under a predefined level of risk. The long-term model is formulated in the Markov Decision Process framework with risk-averse actions and transitional probabilities describing the uncertainty in the deterioration process. The well known Conditional Value at Risk (CVaR) is used as the measure of risk. The steady-state risk-averse M&R policies are modeled assuming no budget restriction. To address the short-term resource allocation problem, two linear programming models are presented to generate network-level polices with different objectives. While the proposed methodology is general and can be used with any performance indicator, pavement roughness is used for numerical studies and an analytical expression for computing CVaR is derived.     

保护环境,汽车人共同的使命

2009年12月召开的哥本哈根气候变化会议不仅让"低碳"成为流行的新名词,更成为全球汽车产业发展的新方向。作为碳排放"大户",汽车行业面临的形势紧迫,肩负的责任重大。在哥本哈根大会上,传出了汽车行业"保护环境"的承诺。本栏目选登了三篇文章,以飨读者。     

Thermodynamic Analysis of a Condensate Heating Systemfrom a Marine Steam Propulsion Plant with Steam Reheating

The thermodynamic (energy and exergy) analysis of a condensate heating system, its segments, and components from a marine steam propulsion plant with steam rehe...