• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.2
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• pp.109-120
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• 2017

A discounted cost model for preventive maintenance of armor units of rubble-mound breakwaters is mathematically derived by combining the deterioration model based on a discrete-time stochastic process of shock occurrence with the cost model of renewal process together. The discounted cost model of condition-based maintenance proposed in this paper can take into account the nonlinearity of cumulative damage process as well as the discounting effect of cost. By comparing the present results with the previous other results, the verification is carried out satisfactorily. In addition, it is known from the sensitivity analysis on variables related to the model that the more often preventive maintenance should be implemented, the more crucial the level of importance of system is. However, the tendency is shown in reverse as the interest rate is increased. Meanwhile, the present model has been applied to the armor units of rubble-mound breakwaters. The parameters of damage intensity function have been estimated through the time-dependent prediction of the expected cumulative damage level obtained from the sample path method. In particular, it is confirmed that the shock occurrences can be considered to be a discrete-time stochastic process by investigating the effects of uncertainty of the shock occurrences on the expected cumulative damage level with homogeneous Poisson process and doubly stochastic Poisson process that are the continuous-time stochastic processes. It can be also seen that the stochastic process of cumulative damage would depend directly on the design conditions, thus the preventive maintenance would be varied due to those. Finally, the optimal periods and scale for the preventive maintenance of armor units of rubble-mound breakwaters can be quantitatively determined with the failure limits, the levels of importance of structure, and the interest rates.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.63-72
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• 2016

An expected-discounted cost model based on RRP(Renewal Reward Process), referred to as a stochastic decision model, has been developed to estimate the optimal period of in-depth inspection which is one of critical issues in the life-cycle maintenance management of harbor structures such as rubble-mound breakwaters. A mathematical model, which is a function of the probability distribution of the service-life, has been formulated by simultaneously adopting PIM(Periodic Inspection and Maintenance) and CBIM(Condition-Based Inspection and Maintenance) policies so as to resolve limitations of other models, also all the costs in the model associated with monitoring and repair have been discounted with time. From both an analytical solution derived in this paper under the condition in which a failure rate function is a constant and the sensitivity analyses for the variety of different distribution functions and conditions, it has been confirmed that the present solution is more versatile than the existing solution suggested in a very simplified setting. Additionally, even in that case which the probability distribution of the service-life is estimated through the stochastic process, the present model is of course also well suited to interpret the nonlinearity of deterioration process. In particular, a MCS(Monte-Carlo Simulation)-based sample path method has been used to evaluate the parameters of a damage intensity function in stochastic process. Finally, the present stochastic decision model can satisfactorily be applied to armor units of rubble mound breakwaters. The optimal periods of in-depth inspection of rubble-mound breakwaters can be determined by minimizing the expected total cost rate with respect to the behavioral feature of damage process, the level of serviceability limit, and the consequence of that structure.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.3
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• pp.147-160
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• 2020

A stochastic probabilistic model for harbor structures such as rubble-mound breakwater has been formulated by using the generalized Wiener process considering the nonlinearity of damage drift and its nonlinear uncertainty, by which the damage path with real-time can be tracked, the residual useful lifetime at some age can also be analyzed properly. The formulated stochastic model can easily calculate the probability of failure with the passage of time through the probability density function of cumulative damage. In particular, the probability density functions of residual useful lifetime of the existing harbor structures can be derived, which can take into account the current age, its present damage state and the future damage process to be occurred. By using the maximum likelihood method and the least square method together, the involved parameters in the stochastic model can be estimated. In the calibration of the stochastic model presented in this paper, the present results are very well similar with the results of MCS about tracking of the damage paths as well as evaluating of the density functions of the cumulative damage and the residual useful lifetime. MTTF and MRL are also evaluated exactly. Meanwhile, the stochastic probabilistic model has been applied to the rubble-mound breakwater. The related parameters can be estimated by using the experimental data of the cumulative damages of armor units measured as a function of time. The theoretical results about the probability density function of cumulative damage and the probability of failure are very well agreed with MCS results such that the density functions of the cumulative damage tend to move to rightward and the amounts of its uncertainty are increased as the elapsed time goes on. Thus, the probabilities of failure with the elapsed time are also increased sharply. Finally, the behaviors of residual useful lifetime have been investigated with the elapsed age. It is concluded for rubble-mound breakwaters that the probability density functions of residual useful lifetime tends to have a longer tail in the right side rather than the left side because of the gradual increases of cumulative damage of armor units. Therefore, its MRLs are sharply decreased after some age. In this paper, the special attentions are paid to the relationship of MTTF and MRL and the elapsed age of the existing structure. In spite of that the sum of the elapsed age and MRL must be equal to MTTF deterministically, the large difference has been shown as the elapsed age is increased which is due to the uncertainty of cumulative damage to be occurred in the future.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.5
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• pp.345-356
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• 2009

Tetrapod has been used as the armor blocks of most rubble mound breakwaters constructed in Korea. The Hudson formula has been widely used in the design of breakwater armor blocks in Korea. In the present study, we calculate the load and resistance partial safety factors of the Hudson formula for Tetrapod armors. The partial safety factors were calculated for the typical breakwater cross-sections of 12 trade harbors and 8 coastal harbors in Korea. The mean and standard deviation of them were also calculated. The mean values were compared with the partial safety factors of US Army (2006). The load and resistance factors are slightly smaller and larger, respectively, than the US Army values. However, the overall safety factors obtained by multiplying the load and resistance factors are close to the US Army values. The result of the present study could be used as the basic data to propose authorized partial safety factors in the future.

• 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.