The Evaluation of Changes in Camber Position to Deflection of Arch Steel Bridge in Extreme Loads

Apriani, Widya; Lubis, Fadrizal; Suryanita, Reni; Firzal, Yohannes

doi:10.1007/978-3-030-32816-0_62

Cited by 2 publications

(2 citation statements)

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“…Deterioration of the bridge structure during service will cause damage and even collapse because of vehicle load overloading, fatigue on these structural elements, earthquake occurrences outside of planned predictions, and large wind loads [1]. In Riau province, several bridges have deteriorated.…”

Section: Introductionmentioning

confidence: 99%

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Damage Prediction of the Steel Arch Bridge Model Based on Artificial Neural Network Method

Apriani¹,

Suryanita²,

Firzal³

et al. 2021

GEOMATE

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Failure in the advance prediction of bridge structure collapse requires an enormous cost of rehabilitation. In most cases, the projection of decreases or damage to the structure due to difficulty in the testing condition. Therefore, this study analyses the damage and identification of the critical structural components' severity on the steel girder arch bridge. Using the Artificial Neural Networks (ANNs), this research has tested a parametric steel girder arch bridge. The numerical model of the 146 supported girder has analysed by epoch 500 values of ANNSs's parameter. The stiffness of 10th element is assumed to drop 10%, 20%, 30%, and 40% of whole the tested. The architecture model of ANNs was three neurons in the input layer, five neurons in the hidden layer and one neuron in the output layer. The simulation of the data set were 90:10, 80:20, 70:30, and 50:50. ANNs shows the damage' severity in this the stiffness reduction tested by applying the damage index methods. In this research, the ANNs' simulation has been reliable to predict 98% for identifying structural damage. Thus, the results confirm the feasibility of the technique and its application in predicting structural failure.

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Section: Introductionmentioning

confidence: 99%

“…But the negative camber (concave) looks. Deflection is an essential factor calculated to determine the bridge's level of use (serviceability) and predict [10]. A deflection is analyzing with a neural network system.…”

Section: Introductionmentioning

confidence: 99%