• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.4
• /
• pp.602-608
• /
• 2002

The flexible structure like solar array and antenna in spacecraft shows very sensitive responses to the inner or outer disturbance and noise. And the spacecraft becomes more complex and larger as it has various mission and role. But since the spacecraft need to have the limited mass, the thin and light material should be selected and this necessity induces the decrease d natural frequency and structural stiffness. It reduces the ability of adapting to the disturbance and induces the structural unstability. Certainly, the disturbance does not only make the structural unstability, but also give the bad effect to the precise attitude control. So it is necessary to control the vibration in the space. In this paper, the flexible structure control modeling with piezo sensor and piezo actuator is developed. The model uncertainty of damping ratio is overcome by robust control. The system equation is induced by the finite element method.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.26 no.2
• /
• pp.95-103
• /
• 2022

In order to evaluate the earthquake safety of equipment in structures, it is essential to analyze the In-Structure Response Spectrum (ISRS). The ISRS has a peak value at the frequency corresponding to the structural vibration mode, but the frequency and amplitude at the peak can vary because of many uncertain parameters. There are several seismic design criteria for ISRS peak-broadening for fixed base structures. However, there are no suggested criteria for constructing the design ISRS of seismically isolated structures. The ISRS of isolated structures may change due to the major uncertainty parameter of the isolator, which is the shear stiffness of the isolator and the several uncertainty parameters caused by the nonlinear behavior of isolators. This study evaluated the effects on the ISRS due to the initial stiffness of the bi-linear curve of isolators and the variation of effective stiffness by the input ground motion intensity and intense motion duration. Analyzing a simplified structural model for isolated base structure confirmed that the ISRS at the frequency of structural mode was amplified and shifted. It was found that the uncertainty of the initial stiffness of isolators significantly affects the shape of ISRS. The variation caused by the intensity and duration of input ground motions was also evaluated. These results suggested several considerations for generating ISRS for seismically isolated structures.

• Geomechanics and Engineering
• /
• v.36 no.5
• /
• pp.475-487
• /
• 2024

Many uncertainties affect the stability assessment of rock structures. Some of these factors significantly influence technology decisions. Some of these factors belong to the geological domain, and spatial uncertainty measurements are useful for structural stability analysis. This paper presents an integrated approach to study the stability of rock structures, including spatial factors. This study models two main components: discrete structures (fault zones) and well known geotechnical parameters (rock quality indicators). The geostatistical modeling criterion are used to quantify geographic uncertainty by producing simulated maps and RQD values for multiple equally likely error regions. Slope stability theorem would be demonstrated by modeling local failure zones and RQDs. The approach proided is validated and finally, the slope stability analysis method and fuzzy Laypunov criterion are applied to mining projects with limited measurement data. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and fuzzy theory.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2008.04a
• /
• pp.387-390
• /
• 2008

The importance of the life cycle cost analysis for construction projects of bridge has been recognized over the last decades. Accordingly, theoretical models, guidelines, and supporting softwares have been developed for the life cycle cost analysis of bridges. However, it is difficult to predict life cycle cost considering uncertainties precisely. This paper presents methodology for optimal design of substructure for a steel box bridge. Total life cycle cost for the service life is calculated as sum of initial cost, damage cost considering uncertainty, maintenance cost, repair and rehabilitation cost. The optimization method is applied to design of a bridge substructure with minimal cost, in which the objective function is set to life cycle cost and constraints are formulated on the basis of Korean Bridge Design Specification. Initial cost is calculated based on standard costs of the Korea Construction Price Index and damage cost on the damage probabilities to consider the uncertainty of load and resistance. An advanced first-order second moment method is used as a practical tool for reliability analysis using damage probability. Maintenance cost and cycle is determined by a stochastic method and user cost includes traffic operation costs and time delay costs.

• Structural Engineering and Mechanics
• /
• v.63 no.1
• /
• pp.47-53
• /
• 2017

The fundamental goal of this study is to minimize the uncertainty of the median fragility curve and to assess the structural vulnerability under earthquake excitation. Bayesian Inference with Markov Chain Monte Carlo (MCMC) simulation has been presented for efficient collapse response assessment of the independent intake water tower. The intake tower is significantly used as a diversion type of the hydropower station for maintaining power plant, reservoir and spillway tunnel. Therefore, the seismic fragility assessment of the intake tower is a pivotal component for estimating total system risk of the reservoir. In this investigation, an asymmetrical independent slender reinforced concrete structure is considered. The Bayesian Inference method provides the flexibility to integrate the prior information of collapse response data with the numerical analysis results. The preliminary information of risk data can be obtained from various sources like experiments, existing studies, and simplified linear dynamic analysis or nonlinear static analysis. The conventional lognormal model is used for plotting the fragility curve using the data from time history simulation and nonlinear static pushover analysis respectively. The Bayesian Inference approach is applied for integrating the data from both analyses with the help of MCMC simulation. The method achieves meaningful improvement of uncertainty associated with the fragility curve, and provides significant statistical and computational efficiency.

• Smart Structures and Systems
• /
• v.22 no.4
• /
• pp.399-411
• /
• 2018

The difficulty in modeling complex nonlinear structures lies in the presence of significant sources of uncertainties mainly attributed to sudden changes in the structure's behavior caused by regular aging factors or extreme events. Quantifying these uncertainties and accurately representing them within the complex mathematical framework of Structural Health Monitoring (SHM) are significantly essential for system identification and damage detection purposes. This study highlights the importance of uncertainty quantification in SHM frameworks, and presents a comparative analysis between intrusive and non-intrusive techniques in quantifying uncertainties for SHM purposes through two different variations of the Kalman Filter (KF) method, the Ensemble Kalman filter (EnKF) and the Polynomial Chaos Kalman Filter (PCKF). The comparative analysis is based on a numerical example that consists of a four degrees-of-freedom (DOF) system, comprising Bouc-Wen hysteretic behavior and subjected to El-Centro earthquake excitation. The comparison is based on the ability of each technique to quantify the different sources of uncertainty for SHM purposes and to accurately approximate the system state and parameters when compared to the true state with the least computational burden. While the results show that both filters are able to locate the damage in space and time and to accurately estimate the system responses and unknown parameters, the computational cost of PCKF is shown to be less than that of EnKF for a similar level of numerical accuracy.

• Structural Engineering and Mechanics
• /
• v.87 no.3
• /
• pp.231-242
• /
• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• Structural Engineering and Mechanics
• /
• v.25 no.3
• /
• pp.275-289
• /
• 2007

In this paper a brief overview of methods to assess the reliability of mechanical systems and structures is presented. A selection of computational procedures, stochastic structural dynamics, stochastic fatigue crack growth and reliability based optimization are discussed. It is shown that reliability based methods may form the basis for a rational decision making.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.9
• /
• pp.263-269
• /
• 2022

The global financial crisis of 2008-2009 and the COVID-19 pandemic that started in 2019 along with the slow and unstable recovery of the global economy have raised concerns about the impact of global uncertainty on the macroeconomics of the countries. The paper used the Structural Vector Autoregression (SVAR) model to examine the impact of global uncertainty shocks on Vietnam's economy from the period 2008-2022. We found that Vietnam's output dropped following the shock of global uncertainty, the peak was in the third month, and lasted for one year. Inflation in Vietnam had a rapid downturn in the first month, peaked in the seventh month, and took a long time to cease. When the economy experienced the shock of increased global uncertainty, Vietnam's policy interest rate was adjusted downward. Additionally, we included a long-term interest rate to consider the overall impact of monetary policy into account. A decreasing trend was also found with this rate. The global uncertainty shock effects acted as the aggregate demand shocks, reducing output and inflation as the uncertainty increases and vice versa, thus monetary policy can be used to regulate Vietnam's economy to deal with negative shocks without the trade-offs between output and inflation as aggregate supply shocks.

• Structural Engineering and Mechanics
• /
• v.53 no.4
• /
• pp.819-831
• /
• 2015

In this paper, we propose a new method for taking into account uncertainties based on the projection on polynomial chaos. The new approach is used to determine the dynamic response of a spur gear system with uncertainty associated to gear system parameters and this uncertainty must be considered in the analysis of the dynamic behavior of this system. The simulation results are obtained by the polynomial chaos approach for dynamic analysis under uncertainty. The proposed method is an efficient probabilistic tool for uncertainty propagation. It was found to be an interesting alternative to the parametric studies. The polynomial chaos results are compared with Monte Carlo simulations.