This paper validates a system identification method using mathematical optimization using sea trial measurement data as a benchmark. A fast time simulation tool, SIMOPT, and a Rheinmetall Defence mathematical model have been adopted to conduct initial hydrodynamic coefficient estimation and simulate ship modelling. Calibration for the environmental effect of sea trial measurement and sensitivity analysis have been carried out to enable a simple and efficient optimization process. The optimization process consists of three steps, and each step controls different coefficients according to the corresponding manoeuvre. Optimization result of Step 1, an optimization for coefficient on x-axis, was similar compared to values applying an empirical regression formulae by Clarke and Norrbin, which is used for SIMOPT. Results of Steps 2 and 3, which are for linear coefficients and nonlinear coefficients, respectively, was differ from the calculation results of the method by Clarke and Norrbin. A comparison for ship trajectory of simulation results from the benchmark and optimization results indicated that the suggested stepwise optimization method enables a coefficient tuning in a mathematical way.

Forced vibration testing is important for correlating the mathematical model of a structure with the realone and for evaluating the performance of the real structure. There exist various techniques available for evaluating the seismic performance using dynamic and static measurements. In this paper, full scale forced vibration tests simulating earthquake response are implemented by using a hybrid mass damper. The finite element(FE) model of the structure was analytically constructed using ANSYS and the model was updated using the results experimentally measured by the forced vibration test. System identification of real-scaled 5 story building structure which is located in UNISON INC. is conducted on the updated FE model.

In order to control seismic responses of building structures effectively and stably, it is very important to estimate the dynamic characteristics of target structure exactly based on input-output signal data. In this paper, it is shown that Subspace Identification Method is able to be applied effectively to system identification of building structures. To verify the efficiency of Subspace Identification Method, the vibration experiments were conducted on a specimen structure which is a 5-storied building structure model consisted of H-shaped steel beam, and the simulated seismic responses of the identified structure model were compared with the observed ones under the same excitation. It was observed that the experimental results coincided with the analyzed ones proposed in this paper.

Large span roof structures require an analysis of their static and dynamic behavior depending on the physical parameters defining the structures. Therefore, it is highly desirable to estimate the parameters from observations of the system. However, the study of the behavior of such structures shows the existence of critical parameters. A small change in such parameters causes a significant change in the motion behavior. In this paper we study the parameter identification problem for shallow sinusoidal arches considering damping effect.

This paper introduces a HGS(Hybrid Grobal Search) method of cable system identification. This method is based on GA(Genetic Algorithms) and LOA(Local Optimization Algorithm) and combines GA and LOA. GA has a advantage of grobal search and LOA has shown a rapid and accurate solution. It is verified the accuracy and effectiveness of the proposed method through a set of numerical test.