Combined with current specifications and stress characteristics of concrete filled steel tubular （CFST） arch bridges, the determination principle of safe-middle-failure threestage mode is given. Accordingly, damage ...Combined with current specifications and stress characteristics of concrete filled steel tubular （CFST） arch bridges, the determination principle of safe-middle-failure threestage mode is given. Accordingly, damage probability and failure probability and the corresponding reliability indices are calculated; a direct relationship between reliability indices and three-stage working status is made. Based on the three-stage working mode, a combined FNM （finite element-neural network- Monte-Carlo simulation） method is put forward to estimate the reliability of existing bridges. According to time-dependent reliability theory, subsequent service time is divided into several stages; minimum samples required by the Monte-Carlo method are generated by random sampling; training samples are calculated by the finite element method, and the training samples are extended by the neural network; failure probability and damage probability are calculated by the Monte-Carlo method. Thus, time dependent reliability indices are obtained, and the working status is judged. A case study is investigated to estimate the reliability of an actual bridge by the FNM method. The bridge is a CFST arch bridge with an 83.6 m span and it has been in operation for 10 years. According to analysis results, in the tenth year, the example bridge is still in safe status. This conclusion is consistent with the facts, which proves the feasibility of the FNM method for estimating the reliability of existing bridges.展开更多
This paper reports on the current state of an ongoing research project which is aimed at implementing intelligent models for hardly predictable hazard scenarios identification in construction sites. As any programmati...This paper reports on the current state of an ongoing research project which is aimed at implementing intelligent models for hardly predictable hazard scenarios identification in construction sites. As any programmatic actions cannot deal with the unpredictable nature of many risk dynamics, an attempt to improve the current approach for safety management in the construction industry will be presented in this paper. To this aim, the features offered by Bayesian networks have been exploited. The present research has led to the definition of a probabilistic model using elicitation techniques from subjective knowledge. This model, which might be meant as a reliable knowledge map about accident dynamics, showed that a relevant part of occurrences fall in the ＂hardly predictable hazards＂ category, which cannot be warded off by programmatic safety measures. Hence, more effort turned out to be needed in order to manage those hardly predictable hazardous scenarios. Consequently, further developments of this research project will focus on a real time monitoring system for the identification of unpredictable hazardous events in construction.展开更多
New open manufacturing environments have been proposed aiming at realizing more flexible distributed manufacturing paradigms,which can deal with not only dynamic changes in volume and variety of products,but also chan...New open manufacturing environments have been proposed aiming at realizing more flexible distributed manufacturing paradigms,which can deal with not only dynamic changes in volume and variety of products,but also changes of machining equipments,dispersals of processing locations,and also with unscheduled disruptions.This research is to develop an integrated process planning and scheduling system,which is suited to this open,dynamic,distributed manufacturing environment.Multi-agent system(MAS)approaches are used for integration of manufacturing processing planning and scheduling in an open distributed manufacturing environment,in which process planning can be adjusted dynamically and manufacturing resources can increase/decrease according to the requirements.One kind of multi-level dynamic negotiated approaches to process planning and scheduling is presented for the integration of manufacturing process planning and scheduling.展开更多
基金The National Natural Science Foundation of China(No.10672060)
文摘Combined with current specifications and stress characteristics of concrete filled steel tubular （CFST） arch bridges, the determination principle of safe-middle-failure threestage mode is given. Accordingly, damage probability and failure probability and the corresponding reliability indices are calculated; a direct relationship between reliability indices and three-stage working status is made. Based on the three-stage working mode, a combined FNM （finite element-neural network- Monte-Carlo simulation） method is put forward to estimate the reliability of existing bridges. According to time-dependent reliability theory, subsequent service time is divided into several stages; minimum samples required by the Monte-Carlo method are generated by random sampling; training samples are calculated by the finite element method, and the training samples are extended by the neural network; failure probability and damage probability are calculated by the Monte-Carlo method. Thus, time dependent reliability indices are obtained, and the working status is judged. A case study is investigated to estimate the reliability of an actual bridge by the FNM method. The bridge is a CFST arch bridge with an 83.6 m span and it has been in operation for 10 years. According to analysis results, in the tenth year, the example bridge is still in safe status. This conclusion is consistent with the facts, which proves the feasibility of the FNM method for estimating the reliability of existing bridges.
文摘This paper reports on the current state of an ongoing research project which is aimed at implementing intelligent models for hardly predictable hazard scenarios identification in construction sites. As any programmatic actions cannot deal with the unpredictable nature of many risk dynamics, an attempt to improve the current approach for safety management in the construction industry will be presented in this paper. To this aim, the features offered by Bayesian networks have been exploited. The present research has led to the definition of a probabilistic model using elicitation techniques from subjective knowledge. This model, which might be meant as a reliable knowledge map about accident dynamics, showed that a relevant part of occurrences fall in the ＂hardly predictable hazards＂ category, which cannot be warded off by programmatic safety measures. Hence, more effort turned out to be needed in order to manage those hardly predictable hazardous scenarios. Consequently, further developments of this research project will focus on a real time monitoring system for the identification of unpredictable hazardous events in construction.
基金International Cooperative Research Project of China(No.2006DFA73180)
文摘New open manufacturing environments have been proposed aiming at realizing more flexible distributed manufacturing paradigms,which can deal with not only dynamic changes in volume and variety of products,but also changes of machining equipments,dispersals of processing locations,and also with unscheduled disruptions.This research is to develop an integrated process planning and scheduling system,which is suited to this open,dynamic,distributed manufacturing environment.Multi-agent system(MAS)approaches are used for integration of manufacturing processing planning and scheduling in an open distributed manufacturing environment,in which process planning can be adjusted dynamically and manufacturing resources can increase/decrease according to the requirements.One kind of multi-level dynamic negotiated approaches to process planning and scheduling is presented for the integration of manufacturing process planning and scheduling.
