为了充分利用超高性能混凝土(ultra high performance concrete, UHPC)优越的力学性能,降低桥梁造价,采用粒子群算法对UHPC梁桥进行结构优化设计;针对传统粒子群算法容易陷入局部最优的不足,基于杂交的粒子群算法,在迭代过程中增加选择...为了充分利用超高性能混凝土(ultra high performance concrete, UHPC)优越的力学性能,降低桥梁造价,采用粒子群算法对UHPC梁桥进行结构优化设计;针对传统粒子群算法容易陷入局部最优的不足,基于杂交的粒子群算法,在迭代过程中增加选择杂交的操作,采用非线性自适应权重更新方法对粒子群优化算法进行改进。基于上述改进粒子群优化算法,对公路常用跨径的普通钢筋UHPC梁、预应力UHPC梁的优化设计方法进行了研究。结果表明:(1)相较于传统的粒子群算法,改进的粒子群算法具有更高的收敛速度和收敛精度;(2)普通钢筋UHPC梁的最优高跨比随着跨径的增加而减小,造价逐渐提高;预应力梁的最优高跨比随着跨径的增大先减小后增大,造价逐渐提高。(3)在经济梁高的基础上,减小梁高会大幅增加底板的宽度以满足结构刚度的需要,造价也将大幅增加。展开更多
Over the past several decades,a variety of technical ways have been developed in seismic retrofitting of existing reinforced concrete frames(RFs).Among them,pin-supported rocking walls(PWs)have received much attention...Over the past several decades,a variety of technical ways have been developed in seismic retrofitting of existing reinforced concrete frames(RFs).Among them,pin-supported rocking walls(PWs)have received much attentions to researchers recently.However,it is still a challenge that how to determine the stiffness demand of PWs and assign the value of the drift concentration factor(DCF)for entire systems rationally and efficiently.In this paper,a design method has been exploited for seismic retrofitting of existing RFs using PWs(RF-PWs)via a multi-objective evolutionary algorithm.Then,the method has been investigated and verified through a practical project.Finally,a parametric analysis was executed to exhibit the strengths and working mechanism of the multi-objective design method.To sum up,the findings of this investigation show that the method furnished in this paper is feasible,functional and can provide adequate information for determining the stiffness demand and the value of the DCFfor PWs.Furthermore,it can be applied for the preliminary design of these kinds of structures.展开更多
Preventative maintenance (PM) measures for bridges are proactive maintenance actions which aim to prevent or delay a deterioration process that may lead to failure. This type of maintenance can be justified on economi...Preventative maintenance (PM) measures for bridges are proactive maintenance actions which aim to prevent or delay a deterioration process that may lead to failure. This type of maintenance can be justified on economic grounds since it can extend the life of the bridge and avoid the need for unplanned essential/corrective maintenance. Due to the high importance of the effective integration of PM measures in the maintenance strategies of bridges, the authors have developed a two-stage evolutionary optimization methodology based on genetic algorithm (GA) principles which links the probabilistic effectiveness of various PM measures with their costs in order to develop optimum PM strategies. In this paper, the sensitivity of the methodology to various key input parameters of the optimization methodology is examined in order to quantify their effects and identify possible trends in the optimum PM intervention profiles. The results of the sensitivity studies highlight the combined use of both proactive and reactive PM measures in deriving optimum strategy solutions. The precise mix and sequence of PM measures is clearly a function of the relative effectiveness and cost of the different available PM options as well as the various key parameters such as discount rate, target probability of failure, initial probability of failure and service life period examined. While the results highlight the need for more reliable data they also demonstrate the robustness and usefulness of the methodology;in the case where data is limited it can be used as a comparative tool to improve understanding of the effects of various strategies and enhance the decision making process.展开更多
文摘为了充分利用超高性能混凝土(ultra high performance concrete, UHPC)优越的力学性能,降低桥梁造价,采用粒子群算法对UHPC梁桥进行结构优化设计;针对传统粒子群算法容易陷入局部最优的不足,基于杂交的粒子群算法,在迭代过程中增加选择杂交的操作,采用非线性自适应权重更新方法对粒子群优化算法进行改进。基于上述改进粒子群优化算法,对公路常用跨径的普通钢筋UHPC梁、预应力UHPC梁的优化设计方法进行了研究。结果表明:(1)相较于传统的粒子群算法,改进的粒子群算法具有更高的收敛速度和收敛精度;(2)普通钢筋UHPC梁的最优高跨比随着跨径的增加而减小,造价逐渐提高;预应力梁的最优高跨比随着跨径的增大先减小后增大,造价逐渐提高。(3)在经济梁高的基础上,减小梁高会大幅增加底板的宽度以满足结构刚度的需要,造价也将大幅增加。
基金The authors are grateful for the financial supports from the Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration(Nos.2019D12 and 2019D11)Open Foundation of State Key Laboratory of Disaster Reduction in Civil Engineering,Tongji University in China(No.SLDRCE19-01)+3 种基金Foundation of Public Welfare Technology Research Project of Zhejiang Province in China(No.LGF20E080013)Natural Science Foundation of Zhejiang Province,China(No.LY22E080003)Fundamental Research Fund for the Provincial Universities of Zhejiang(No.SJLZ2022003)Foundation of Public Welfare Technology Research Project of Ningbo in China,(Nos.2022S170,2022S179).
文摘Over the past several decades,a variety of technical ways have been developed in seismic retrofitting of existing reinforced concrete frames(RFs).Among them,pin-supported rocking walls(PWs)have received much attentions to researchers recently.However,it is still a challenge that how to determine the stiffness demand of PWs and assign the value of the drift concentration factor(DCF)for entire systems rationally and efficiently.In this paper,a design method has been exploited for seismic retrofitting of existing RFs using PWs(RF-PWs)via a multi-objective evolutionary algorithm.Then,the method has been investigated and verified through a practical project.Finally,a parametric analysis was executed to exhibit the strengths and working mechanism of the multi-objective design method.To sum up,the findings of this investigation show that the method furnished in this paper is feasible,functional and can provide adequate information for determining the stiffness demand and the value of the DCFfor PWs.Furthermore,it can be applied for the preliminary design of these kinds of structures.
文摘Preventative maintenance (PM) measures for bridges are proactive maintenance actions which aim to prevent or delay a deterioration process that may lead to failure. This type of maintenance can be justified on economic grounds since it can extend the life of the bridge and avoid the need for unplanned essential/corrective maintenance. Due to the high importance of the effective integration of PM measures in the maintenance strategies of bridges, the authors have developed a two-stage evolutionary optimization methodology based on genetic algorithm (GA) principles which links the probabilistic effectiveness of various PM measures with their costs in order to develop optimum PM strategies. In this paper, the sensitivity of the methodology to various key input parameters of the optimization methodology is examined in order to quantify their effects and identify possible trends in the optimum PM intervention profiles. The results of the sensitivity studies highlight the combined use of both proactive and reactive PM measures in deriving optimum strategy solutions. The precise mix and sequence of PM measures is clearly a function of the relative effectiveness and cost of the different available PM options as well as the various key parameters such as discount rate, target probability of failure, initial probability of failure and service life period examined. While the results highlight the need for more reliable data they also demonstrate the robustness and usefulness of the methodology;in the case where data is limited it can be used as a comparative tool to improve understanding of the effects of various strategies and enhance the decision making process.
