• Journal of Applied Reliability
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• v.9 no.1
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• pp.13-28
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• 2009

In this paper we propose a method for designing optimum degradation test based on nonlinear random-coefficients models. We use the approximated expression of the Fisher information matrix for nonlinear random-coefficients models. We apply the simplex algorithm to the inverse of the determinant of Fisher information matrix to satisfy the D-optimal criterion. By comparison of the results from PDP degradation data, we suggest a general guideline to obtain optimum experimental design for determining inspection intervals and number of samples in degradation testing.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.345-356
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• 1999

This paper deals with the problem of estimating regression coefficients in nonlinear regression model having random regressor. The sufficient conditions for consistency of the $L_1$-estimator with random regressor are given and discussed in this paper. An example is given to illustrate the application of the main results.

• Earthquakes and Structures
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• v.8 no.4
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.2
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• pp.106-121
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• 2020

In order to make harbor outskirt facilities robust using the reliability-based design, probabilistic models of wave heights at varying stage of shoaling process optimized for Korean sea waves are prerequisite. In this rationale, we numerically simulate the nonlinear shoaling process of random waves over the beach with a sandbar at its foreshore. In doing so, comprehensive numerical models made of spatially filtered Navier-Stokes Eq., LES [Large Eddy Simulation], dynamic Smagorinsky turbulence closure were used. Considering the characteristics of swells observed at the east coast of Korean Peninsula, random waves were simulated using JONSWAP wave spectrum of various peak enhancement coefficients and random phase method. The coefficients of probabilistic models proposed in this study are estimated from the results of frequency analysis of wave crests and its associated trough detected by Wave by Wave Analysis of the time series of numerically simulated free surface displacements based on the threshold crossing method. Numerical results show that Modified Glukhovskiy wave height distribution, the most referred probabilistic models at finite water depth in the literature, over-predicts the occurring probability of relatively large and small wave heights, and under predicts the occurrence rate of waves of moderate heights. On the other hand, probabilistic models developed in this study show vary encouraging agreements. In addition, the discrepancy of the Modified Glukhovskiy distribution from the measured one are most visible over the surf zone, and as a result, the Modified Glukhovskiy distribution should be applied with caution for the reliability-based design of harbor outskirt facilities deployed near the surf-zone.