The temperature distributions of a prestressed concrete box girder bridge under the effect of cold wave processes were analyzed. The distributions were found different from those under the effect of solar radiation or...The temperature distributions of a prestressed concrete box girder bridge under the effect of cold wave processes were analyzed. The distributions were found different from those under the effect of solar radiation or nighttime radiation cooling and should not be simplified as one dimensional. A temperature predicting model that can accurately predict temperatures over the cross section of the concrete box girder was developed. On the basis of the analytical model, a two-dimensional temperature gradient model was proposed and a parametric study that considered meteorological factors was performed. The results of sensitivity analysis show that the cold wave with shorter duration and more severe temperature drop may cause more unfavorable influences on the concrete box girder bridge. Finally, the unrestrained linear curvatures, self-equilibrating stresses and bending stresses when considering the frame action of the cross section, were derived from the proposed temperature gradient model and current code provisions, respectively. Then, a comparison was made between the value calculated against proposed model and several current specifications. The results show that the cold wave may cause more unfavorable effect on the concrete box girder bridge, especially on the large concrete box girder bridge. Therefore, it is necessary to consider the thermal effect caused by cold wave during the design stage.展开更多
The Stackelberg prediction game(SPG)is a bilevel optimization frame-work for modeling strategic interactions between a learner and a follower.Existing meth-ods for solving this problem with general loss functions are ...The Stackelberg prediction game(SPG)is a bilevel optimization frame-work for modeling strategic interactions between a learner and a follower.Existing meth-ods for solving this problem with general loss functions are computationally expensive and scarce.We propose a novel hyper-gradient type method with a warm-start strategy to address this challenge.Particularly,we first use a Taylor expansion-based approach to obtain a good initial point.Then we apply a hyper-gradient descent method with an ex-plicit approximate hyper-gradient.We establish the convergence results of our algorithm theoretically.Furthermore,when the follower employs the least squares loss function,our method is shown to reach an e-stationary point by solving quadratic subproblems.Numerical experiments show our algorithms are empirically orders of magnitude faster than the state-of-the-art.展开更多
基金Project(08Y60) supported by the Traffic Science’s Research Planning of Jiangsu Province,China
文摘The temperature distributions of a prestressed concrete box girder bridge under the effect of cold wave processes were analyzed. The distributions were found different from those under the effect of solar radiation or nighttime radiation cooling and should not be simplified as one dimensional. A temperature predicting model that can accurately predict temperatures over the cross section of the concrete box girder was developed. On the basis of the analytical model, a two-dimensional temperature gradient model was proposed and a parametric study that considered meteorological factors was performed. The results of sensitivity analysis show that the cold wave with shorter duration and more severe temperature drop may cause more unfavorable influences on the concrete box girder bridge. Finally, the unrestrained linear curvatures, self-equilibrating stresses and bending stresses when considering the frame action of the cross section, were derived from the proposed temperature gradient model and current code provisions, respectively. Then, a comparison was made between the value calculated against proposed model and several current specifications. The results show that the cold wave may cause more unfavorable effect on the concrete box girder bridge, especially on the large concrete box girder bridge. Therefore, it is necessary to consider the thermal effect caused by cold wave during the design stage.
文摘The Stackelberg prediction game(SPG)is a bilevel optimization frame-work for modeling strategic interactions between a learner and a follower.Existing meth-ods for solving this problem with general loss functions are computationally expensive and scarce.We propose a novel hyper-gradient type method with a warm-start strategy to address this challenge.Particularly,we first use a Taylor expansion-based approach to obtain a good initial point.Then we apply a hyper-gradient descent method with an ex-plicit approximate hyper-gradient.We establish the convergence results of our algorithm theoretically.Furthermore,when the follower employs the least squares loss function,our method is shown to reach an e-stationary point by solving quadratic subproblems.Numerical experiments show our algorithms are empirically orders of magnitude faster than the state-of-the-art.
