• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1996.10a
• /
• pp.62-69
• /
• 1996

Most dynamic systems have various random properties in excitation and system parameters. In this paper, a procedure fur response 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 perturbation technique, aand then response analysis is formulated by probabilistic and vibration theories. And probabilistic FEM is also used for the calculation of mean response which is difficult by the proposed response model. As an application example, the transient response is 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.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10b
• /
• pp.451-455
• /
• 1993

Interaction between system and disturbance results in system with time-dependent parameter. Parameter variation due to interaction has random characteristics. Most of the randomly varying parameters in control problem is regarded as white noise random process which is not a realistic model. In real situation those random variation is colored noise random process. Modified F-P-K equation is proposed to get the response of the random parametric system using some correction factor. Proposed technique is employed to obtain the colored noise parametric system response and confirmed via Monte-Carlo Simulation.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.857-864
• /
• 2006

Due to the difficulties in numerical generation of random fields that satisfy not only the probabilistic distribution but the spectral characteristics as well. it is relatively hard to find an exact response variability of a structural response with a specific random field which has its features in the spatial and spectral domains. In this study. focusing on the fact 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 in-plane and plate bending structures. In this procedure, the probability density function is used directly resulting in a semi-exact solution for the random field in the state of random variable. It is particularly noteworthy that the proposed methodology provides response variability for virtually any type of probability density functions.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.18 no.2
• /
• pp.187-193
• /
• 2009

Dynamic response of an elastic pendulum system under random excitations was studied by using the Lagrangian equations of motion which uses the kinetic and potential energy of a target system. The responses of random excitations were calculated by using Monte Carl simulation which uses the series of random numbers. The procedure of Monte Carlo simulation is generation of random numbers, system model, system output, and statistical management of output. When the levels of random excitations were changed, the expected responses of the pendulum system showed various responses.

• Computational Structural Engineering
• /
• v.10 no.3
• /
• pp.125-131
• /
• 1997

Most dynamic systems have are known to various random properties in excitation and system parameters. In this paper, a procedure for response analysis is proposed for the linear dynamic system with random properties in both excitation and system parameters. The system parameters and responses with random properties are modeled by perturbation technique, and then response analysis is formulated by probabilistic and vibration theories. And probabilistic FEM is also used for the calculation of mean response which is difficult by the proposed response model. As an applicative example, the transient response is considered for systems of single degree of freedom with random mass and spring constant subjected to stationary white-noise excitation and the results are compared to those of numerical simulation.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.4 no.1
• /
• pp.234-245
• /
• 2001

This paper considers the Maximum Pesponse Spectrum for the random vibration, sinusoidal vibration, linear sweep vibration. The random vibration quality levels and the sinusoidal vibration quality level are compared using MRS. And the severity between the vibration test specification and real environments using Maximum Response Spectrum are also compared using it.

• Structural Engineering and Mechanics
• /
• v.3 no.3
• /
• pp.273-287
• /
• 1995

Stochastic response of systems to random excitation can be estimated by direct integration methods in the time domain such as the stochastic central difference method (SCDM). In this paper, the SCDM is applied to compute the variance and covariance in response of linear and nonlinear structures subjected to random excitation. The accuracy of the SCDM is assessed using two-DOF systems with both deterministic and random material properties excited by white noise. For the former case, closed-form solutions can be obtained. Numerical results also are presented for a simply supported geometrically nonlinear beam. The stiffness of this beam is modeled as a random field, and the beam is idealized by the stochastic finite element method. A perturbation technique is applied to formulate the equations of motion of the system, and the dynamic structural response statistics are obtained in a time domain analysis. The effect of variations in structural parameters and the numerical stability of the SCDM also are examined.

• The Korean Journal of Applied Statistics
• /
• v.35 no.4
• /
• pp.485-499
• /
• 2022

Controlling the total survey error including sampling error and non-sampling error is very important in sampling design. Non-sampling error caused by non-response accounts for a large proportion of the total survey error. Many studies have been conducted to handle non-response properly. Recently, a lot of non-response imputation methods using machine learning technique and traditional statistical methods have been studied and practically used. Most imputation methods assume MCAR(missing completely at random) or MAR(missing at random) and few studies have been conducted focusing on MNAR (missing not at random) or NN(non-ignorable non-response) which cause bias and reduce the accuracy of imputation. In this study, we propose a non-response imputation method that can be applied to non-ignorable non-response. That is, we propose an imputation method to improve the accuracy of estimation by removing the bias caused by NN. In addition, the superiority of the proposed method is confirmed through small simulation studies.

• Structural Engineering and Mechanics
• /
• v.39 no.1
• /
• pp.47-75
• /
• 2011

An accurate substructural synthesis method including random responses synthesis, frequency-response functions synthesis and mid-order modes synthesis is developed based on rigorous substructure description, dynamic condensation and coupling. An entire structure can firstly be divided into several substructures according to different functions, geometric and dynamic characteristics. Substructural displacements are expressed exactly by retained mid-order fixed-interfacial normal modes and residual constraint modes. Substructural interfacial degree-of-freedoms are eliminated by interfacial displacements compatibility and forces equilibrium between adjacent substructures. Then substructural mode vibration equations are coupled to form an exact-condensed synthesized structure equation, from which structural mid-order modes are calculated accurately. Furthermore, substructural frequency-response function equations are coupled to yield an exact-condensed synthesized structure vibration equation in frequency domain, from which the generalized structural frequency-response functions are obtained. Substructural frequency-response functions are calculated separately by using the generalized frequency-response functions, which can be assembled into an entire-structural frequency-response function matrix. Substructural power spectral density functions are expressed by the exact-synthesized substructural frequency-response functions, and substructural random responses such as correlation functions and mean-square responses can be calculated separately. The accuracy and capacity of the proposed substructure synthesis method is verified by numerical examples.

• Communications for Statistical Applications and Methods
• /
• v.7 no.3
• /
• pp.741-757
• /
• 2000

In may experimental situations, whenever a block design is used, the block effect is usually considered to be fixed. There are, however, experimental situations in which it should be treated as random. The choice of a blocking arrangement for a response surface design can have a considerable effect on estimating the mean response and on the size of he prediction variance even if the experimental runs re the same. Therefore, care should be exercised in the selection of blocks. In this paper, in the presence of a random block effect, we propose a graphical method or evaluating the effect of blocking in response surface designs using cuboidal regions. This graphical method can be used to investigate how the blocking has influence on the prediction variance throughout all experimental regions of interest when this region is cuboidal, and compare the block effects in the cases of the orthogonal and non-orthogonal block designs, respectively.