• Earthquakes and Structures
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• v.22 no.1
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• pp.95-107
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• 2022

This paper introduces a novel, rigorous, and efficient probabilistic methodology for the performance-based optimal design (PBOD) of semi-active tuned mass damper (SATMD) for seismically excited nonlinear structures. The proposed methodology is consistent with the modern performance-based earthquake engineering framework and aims to design reliable control systems. To this end, an optimization problem has been defined which considers the parameters of control systems as design variables and minimization of the probability of exceeding a targeted structural performance level during the lifetime as an objective function with a constraint on the failure probability of stroke length damage state associated with mass damper mechanism. The effectiveness of the proposed methodology is illustrated through a numerical example of performance analysis of an eight-story nonlinear shear building frame with hysteretic bilinear behavior. The SATMD with variable stiffness and damping have been designed separately with different mass ratios. Their performance has been compared with that of uncontrolled structure and the structure controlled with passive TMD in terms of probabilistic demand curves, response hazard curves, fragility curves, and exceedance probability of performance levels during the lifetime. Numerical results show the effectiveness, simplicity, and reliability of the proposed PBOD method in designing SATMD with variable stiffness and damping for the nonlinear frames where they have reduced the exceedance probability of the structure up to 49% and 44%, respectively.

• Journal of Power System Engineering
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• v.13 no.2
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• pp.63-70
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• 2009

This paper discusses the influence on long-tenn predictions of the ship response in ocean by using the Global Wave Statistics data, GWS, and wave information from the remote sensing satellites. GWS's standard scatter diagrams of significant wave height and zero-crossing wave period are suggested to be corrected to a round number of 0.01/1000 fitted with a statistical analytic model of the conditional lognormal distribution for zero-crossing wave period. The GEOSAT satellite data are utilized which presented by I. R. Young and G. J. Holland (1996, named as GEOSAT data). At first, qualities of this data are investigated, and statistical characteristic trends are studied by means of applying known probability distribution functions. The wave height data of GEOSAT are compared to the data observed onboard merchant ships, the data observed by measure instrument installed on the ocean-going container ship and so on. To execute a long-tenn prediction of ship response, joint probability functions between wave height and wave period are introduced, therefore long-term statistical predictions are executed by using the functions.

• Structural Engineering and Mechanics
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• v.34 no.4
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• pp.417-447
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• 2010

The uncertainty often observed in experimental strengths of masonry constituents makes critical the selection of the appropriate inputs in finite element analysis of complex masonry buildings, as well as requires modelling the building ultimate load as a random variable. On the other hand, the utilization of expensive Monte Carlo simulations to estimate collapse load probability distributions may become computationally impractical when a single analysis of a complex building requires hours of computer calculations. To reduce the computational cost of Monte Carlo simulations, direct computer calculations can be replaced with inexpensive Response Surface (RS) models. This work investigates the use of RS models in Monte Carlo analysis of complex masonry buildings with random input parameters. The accuracy of the estimated RS models, as well as the good estimations of the collapse load cumulative distributions obtained via polynomial RS models, show how the proposed approach could be a useful tool in problems of technical interest.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.167-182
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• 1999

This article is concerned with the selection of subsets of predictor variables to be included in building the binary response probit regression model. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting promising subsets. This procedure reformulates the probit regression setup in a hierarchical normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. The appropriate posterior probability of each subset of predictor variables is obtained through the Gibbs sampler, which samples indirectly from the multinomial posterior distribution on the set of possible subset choices. Thus, in this procedure, the most promising subset of predictors can be identified as the one with highest posterior probability. To highlight the merit of this procedure a couple of illustrative numerical examples are given.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.59-69
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• 2006

Pearson's correlation coefficient and Vector similarity are generally applied to The users' similarity weight of user based recommender system. This study is needed to find that the correlation coefficient of similarity weight is effected by the number of pair response and significance probability. From the classified correlation coefficient by the significance probability test on the correlation coefficient and pair of response, the change of MAE is studied by comparing the predicted precision of the two. The results are experimentally related with the change of MAE from the significant correlation coefficient and the number of pair response.

• Journal of the Society of Naval Architects of Korea
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• v.34 no.4
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• pp.91-98
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• 1997

Most dynamic systems have various random properties m excitation and system parameters. In this paper, a procedure for structural response and reliability analysis is proposed for the linear dynamic system with random properties in both excitation and system parameters. The system parameter and response with random properties are modeled by the perturbation technique, and then the response analysis is formulated by probabilistic and vibration theories. Probabilistic FEM is also used for the calculation of mean response which is difficult by the proposed response model. The first passage analysis by the integral equation method is used to analyze the probability of failure. The integral equation method results in the first passage probability in terms of crossing rates and first passage probability densities. In this study it is assumed that excitations, system parameters and responses are Gaussian. As an application example, the probabilities of failure at transient state are calculated for a sdof system with random mass and spring constant subjected to stationary white-noise excitation and the results are compared to those of numerical simulation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.1001-1011
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• 2006

It is a general agreement that exact statistical solutions can be found by a Monte Carlo technique. Due to difficulties, however, in the numerical generation of random fields, which satisfy not only the probabilistic distribution but the spectral characteristics as well, it is recognized as relatively difficult to find an exact response variability of a structural response. In this study, recognizing that the random field assumes a constant over the domain under consideration when the correlation distance tends to infinity, a semi-theoretical solution of response variability is proposed for general structures. In this procedure, the probability density function is directly used. It is particularly noteworthy that the proposed methodology provides response variability for virtually any type of probability density function, and has capability of considering correlations between multiple random variables.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.225-233
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• 2004

In this study, the seismic safety of containment building is assessed using response surface method. The structural analyses considering random variables such as load, resistance and analysis by ABAQUS are performed to obtain the structural response. The structural response is represented by polynomial of random variables, and the reliability analysis is performed by Level II method. Drucker-Prager failure criterion is applied as limit state function to take bi-axial stress states into account in the concrete. The lifetime probability of failure is evaluated by considering the lifetime of containment building, the annual occurrence rate of earthquake and the conditional probability of failure. Also the sensitivity analysis on the selection of sampling points is performed to obtain the steady results from response surface method.

• Journal of the Korean Geosynthetics Society
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• v.21 no.3
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• pp.1-10
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• 2022

In this paper, the spatial randomness and probability characteristics of material properties are inversely estimated by using a set of the stochastic fields for the material properties of geotechnical structures. By using the probability distribution and probability characteristics of these estimated material properties, topology optimization is performed on structure shape, and the results are compared with the existing deterministic topology optimization results. A set of stochastic fields for material properties is generated, and the spatial randomness of material properties in each field is simulated. The probability distribution and probability characteristics of actual material properties are estimated using the partial values of material properties in each stochastic field. The probability characteristics of the estimated actual material properties are compared with those of the stochastic field set. Also, response variability of the ground structure having a modulus of elasticity with randomness is compared with response variability of the ground structure having a modulus of elasticity without randomness. Therefore, the quantified stochastic topology optimization result can be obtained with considering the spatial randomness of actual material properties.

• Ocean Systems Engineering
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• v.1 no.3
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• pp.249-261
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• 2011

The stochastic nonlinear dynamic behavior and probability density function of ship rolling are studied using the nonlinear dynamical systems approach and probability theory. The probability density function of the rolling response is evaluated through solving the Fokker Planck Equation using the path integral method based on a Gauss-Legendre interpolation scheme. The time-dependent probability of ship rolling restricted to within the safe domain is provided and capsizing is investigated from the probability point of view. The random differential equation of ships' rolling motion is established considering the nonlinear damping, nonlinear restoring moment, white noise and colored noise wave excitation.