• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1B
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• pp.59-69
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• 2012

Probabilistic design is required to effectively consider the coastal environment of great uncertainty. However, designers who are familiar with the deterministic design method prefer a method which is similar to the existing method but is based on the probabilistic concept. Therefore, the partial safety factor method has been adopted as a new design method over the world. In Korea, Tetrapod is widely used for armoring rubble mound breakwaters. Even though the partial safety factor method developed in the United States and Europe covers Tetrapods, the limited wave and structure conditions in its development make the engineers hesitate about its use in practical breakwater design. In this study, partial safety factors for Tetrapod armor blocks have been developed by analyzing 116 breakwater cross-sections and wave conditions in 16 trade harbors and 15 coastal harbors with the FORM and optimal code calibration approach. Especially, partial safety factors have been proposed depending on the shape parameter of the Weibull extreme wave height distribution. For other types of extreme distributions, it is possible to apply the proposed partial safety factors using the relationship between skewness coefficient and shape parameter. Finally, the proposed partial safety factors have been applied to existing structures to show that they better satisfy the target reliability of the structures than previous partial safety factors.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.1
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• pp.109-117
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• 2011

It was calculated using empirical formulas for the weight of Tetrapod, which was a representative armor unit in the rubble mound breakwater in Korea. As the formulas were evaluated from a curve-fitting with the result of hydraulic test, the uncertainty of experimental error was included. Therefore, the neural network and M5' model tree were used to minimize the uncertainty and predicted the stability number of armor block. The index of agreement between the predicted and measured stability number was calculated to assess the degree of uncertainty for each model. While the neural network with the highest index of agreement have an excellent prediction capability, a significant disadvantage exists that general designers can not easily handle the method. However, although M5' model tree has a lower prediction capability than the neural network, the model tree is easily used by the designers because it has a good prediction capability compared with the existing empirical formula and can be used to propose the formulas like an empirical formula.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.827-837
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• 2018

The stabilities of sliding and overturning of caisson and bearing capacity of mound against eccentric and inclined loads, which possibly happen to a composite caisson breakwaters, have been analyzed by using the technique of multiple failure modes. In deterministic approach, mathematical functions have been first derived from the ultimate limit state equations. Using those functions, the minimum cross section of caisson can straightforwardly be evaluated. By taking a look into some various deterministic analyses, it has been found that the conflict between failure modes can be occurred, such that the stability of bearing capacity of mound decreased as the stability of sliding increased. Therefore, the multiple failure modes for the composite caisson breakwaters should be taken into account simultaneously even in the process of deterministically evaluating the design cross section of caisson. Meanwhile, the reliability analyses on multiple failure modes have been implemented to the cross section determined by the sliding failure mode. It has been shown that the system failure probabilities of the composite breakwater are very behaved differently according to the variation of incident waves. The failure probabilities of system tend also to increase as the crest freeboards of caisson are heightening. The similar behaviors are taken place in cases that the water depths above mound are deepening. Finally, the results of the first-order modal are quite coincided with those of the second-order modal in all conditions of numerical tests performed in this paper. However, the second-order modal have had higher accuracy than the first-order modal. This is mainly due to that some correlations between failure modes can be properly incorporated in the second-order modal. Nevertheless, the first-order modal can also be easily used only when one of failure probabilities among multiple failure modes is extremely larger than others.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.5
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• pp.277-283
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• 2016

Tetrapod is one of the most widely used concrete armor units for rubble mound breakwaters. The calculation of the stability number of Tetrapods is necessary to determine the optimal weight of Tetrapods. Many empirical formulas have been developed to calculate the stability number of Tetrapods, from the Hudson formula in 1950s to the recent one developed by Suh and Kang. They were developed by using the regression analysis to determine the coefficients of an assumed formula using the experimental data. Recently, software engineering (or machine learning) methods are introduced as a large amount of experimental data becomes available, e.g. artificial neural network (ANN) models for rock armors. However, these methods are seldom used probably because they did not significantly improve the accuracy compared with the empirical formula and/or the engineers are not familiar with them. In this study, we propose an explicit method to calculate the stability number of Tetrapods using the weights and biases of an ANN model. This method can be used by an engineer who has basic knowledge of matrix operation without requiring knowledge of ANN, and it is more accurate than previous empirical formulas.