In-situ testing and model updating of a long-span cable-stayed railway bridge with hybrid girders subjected to a running train

<p>The weight and design speed of the railway vehicles increases in time. As a result, the values of design loads grow up. In old Bulgarian standard [1] the equivalent nosing force is prescribed as 60kN. In the present EN1991-2 [2] this value is 100kN. Meanwhile, a significant part of the very old bridges is not designed for nosing forces. In cases of long span between cross girders of the “open type” deck and lack of nosing braces, the load bearing capacity of longitudinal girders, concerning out of plane bending moments due to nosing forces, is insufficient. To investigate the value of equivalent nosing force are provided “in situ” measurements on the longitudinal girders of “open type” deck of a steel riveted railway bridge in exploitation in the Republic of Bulgaria. The strains and horizontal linear deformations are measured in the midspan of the longitudinal beams for real trains. The equivalent nosing force is calculated using developed procedures.</p>

Download Full-text

In-Situ Testing of Operation Stability in Hydraulic Turbine Generator Unit

Earth & Space 2008 ◽

10.1061/40988(323)67 ◽

2008 ◽

Cited By ~ 1

Author(s):

Shanshan Wang ◽

Pizhong Qiao

Keyword(s):

Hydraulic Turbine ◽

In Situ Testing ◽

Turbine Generator ◽

Operation Stability ◽

Generator Unit

Download Full-text

Urban Railway Bridge Fast Evaluation Based on Cloud Computing

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.71-78.4501 ◽

2011 ◽

Vol 71-78 ◽

pp. 4501-4505

Author(s):

Ming Chen ◽

Wan Zhou

Keyword(s):

Neural Networks ◽

Cloud Computing ◽

Model Updating ◽

Condition Assessment ◽

Fe Model ◽

Railway Bridge ◽

Fast Evaluation ◽

Railway Bridges ◽

Computing Model ◽

Bridge Condition Assessment

Although modern bridge are carefully designed and well constructed, damage may occur in them due to unexpected causes. Currently, many different techniques have been proposed and investigated in bridge condition assessment. However, evaluation efficiency of condition assessment has not been paid much attention by the researchers. A fast evaluation of the urban railway bridge condition based on the cloud computing is presented. In this paper dynamic FE model and Artificial neural networks technique is applied to model updating. The cloud computing model provides the basis for fast analyses. It was found that when applied to the actually railway bridges, the proposed method provided results similar to those obtained by experts, but can improve efficiency of bridge

Download Full-text