• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.267-273
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• 2003

Steel fiber may be used to raise the effectiveness and safety of reinforced concrete structure and to relax its brittle-fracture behavior. However it is to be clearly stated that the uncertainty for the strength of fiber reinforced concrete(SFRC) is rather increased. Therefore, it is necessary to evaluate the safety of SFRC beam using reliability analysis incorporating realistic uncertainty. This study presents the statistical data and proposes the limit state model to analyze the reliability of SFRC bear In order to verify the efficiency of the proposed limit state model, its numerical application and sensitivity analysis were performed for a continuous SFRC beam. From the results of the numerical analysis, it is founded that the reliability of SFRC beam is significantly difficult from the conventional RC beams and proposed limit state model (or SFRC beam is more rational compared with that for conventional RC beams. Then it may be stated that the reliability analysis of SFRC beams must be carried out for the development of design criteria and the safety assessment.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.123-132
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• 2014

Inflation uncertainty is known to have deleterious effects on facilities investment by disturbing the corporate decision on the opportunity cost of investment. In this paper, we test the validity of this hypothesis in Korea by estimating the inflation uncertainty with both a time-varing parameter model with GARCH disturbances and the relative price volatility and then, estimate the facilities investment equation which includes those uncertainty indicators. The uncertainty indexes estimated by the above-mentioned methods continue to fluctuate even after the inflation rate has dropped dramatically reflecting the structural changes of Korea's economy since the financial crisis in 1997. As a result of estimation of the investment equation by both OLS and GMM, we find the inflation uncertainty has a negative effect on facilities investment with a statistical significance. Moreover, by means of Markov-switching regression model utilized to verify the non-linearity of this relationship, we draw a conclusion that this negative effect of inflation uncertainty heightens asymmetrically during the downturn periods of business cycle.

• Journal of Convergence for Information Technology
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• v.8 no.3
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• pp.183-191
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• 2018

This study is to examine the effects of Socially Prescribed Perfectionism on depression by Intolerance of Uncertainty and Unconditional Self Acceptance, and to well being to improve the positive life of college students. This study is conducted on 238 college students who are influenced by Socially Prescribed Perfectionism, Intolerance of Uncertainty, Unconditional Self Acceptance, and Depression. This study analyzed a questionnaire consisted of a sub-component of the Multidimensional Perfectionism Scale (MPS), a Intolerance of Uncertainty Scale(IUS), an Unconditional Self Acceptance Questionnaire-R(USAQ-R), and a depression scale (CES-D) and verified correlation analysis and structural equation model. The results of this study showed that socially prescribed perfectionism had significant negative correlations with intolerance of uncertainty, and had significant positive correlation with unconditional self acceptance. The results of the structural equation model showed full mediating effect of the intolerance of uncertainty and unconditional self acceptance between Socially prescribed perfectionism and depression, Finally, implications and suggestions are suggested in this study.

• Journal of the Korean Society of Safety
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• v.27 no.1
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• pp.76-85
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• 2012

This paper proposes a robust damper design technique for adjacent structures against model uncertainty. This approach introduces multi-objective optimization based system identification using measurement information which enables reasonable selection of the perturbation range in the robust design. Moreover, in order to improve the numerical efficiency in sampling the structural models required for the robust design of large structures, we define new objective functions which enable us to minimize the number of candidate models suitable to the purpose of the robust design. In addition, the performance index is newly employed to evaluate the robust performance of the sampled structural models, and the robust design has been performed according to the performance index. As a numerical example to demonstrate the efficiency of the proposed method, 5-story and 10-story two adjacent buildings are taken into account, and the existing and newly proposed robust design approaches are compared with each other. The results demonstrate that the proposed approach can guarantee more robust damper system only using small number of samples of the structural models because of using the measurement information which leads to improvement in the numerical efficiency, compared with the existing robust design methods.

• Smart Structures and Systems
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• v.17 no.2
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• pp.209-230
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• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.

• Structural Engineering and Mechanics
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• v.80 no.6
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• pp.677-688
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• 2021

The building design codes and standards in many countries usually are either fully or partially adopted from the international codes. However, regional conditions like the quality of construction industry and different statistical parameters of load and resistance have essential roles in the code calibration of building design codes. This paper presents a probabilistic approach to assess the reliability level of adopted national building codes by simulating design situations and considering all load combinations. The impact of the uncertainty of wind and earthquake loads, which are entirely regional condition dependent and have a high degree of uncertainty, are quantified. In this study, the design situation is modeled by generating thousands of numbers for load effect ratios, and the reliability level of steel elements for all load combinations and different load ratios is established and compared to the target reliability. This approach is applied to the Iranian structural steel code as a case study. The results indicate that the Iranian structural steel code lacks safety in some load combinations, such as gravity and earthquake load combinations, and is conservative for other load combinations. The present procedure can be applied to the assessment of the reliability level of other national codes.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.351-359
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• 2015

In order to exactly evaluate the seismic collapse capacity of a structure, probabilistic approach is required by considering uncertainties related to its structural properties and ground motion. Regardless of the types of uncertainties, they influence on the seismic response of a structures and their effects are required to be estimated. An incremental dynamic analysis(IDA) is useful to investigate uncertainty-propagation due to ground motion. In this study, a 3-story steel moment-resisting frame is selected for a prototype frame and analyzed using the IDA. The uncertainty-propagation is assessed with categorized parameters representing epistemic uncertainties, such as the seismic weight, the inherent damping, the yield strength, and the elastic modulus. To do this, the influence of the uncertainty-propagation to the seismic collapse capacity of the prototype frame is probabilistically evaluated using the incremental dynamic analyses based on the Monte-Carlo simulation sampling with the Latin hypercube method. Of various parameters related to epistemic uncertainty-propagation, the inherent damping is investigated to be the most influential parameter on the seismic collapse capacity of the prototype frame.

• Journal of Distribution Science
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• v.11 no.10
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• pp.73-79
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• 2013

Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.10a
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• pp.501-508
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• 2000

It is demanded to find the dynamic model of a real structure to design a controller. However, as the structure has inherently infinite number of degree-of-freedom, it is impossible to obtain an exact dynamic model of the structure. Instead a reduction model with finite degree-of-freedom is used for the design of a controller. So there exists uncertainty between a real model and a reduction model which causes poor performance of control. All these uncertainties can degrade the control performance and even cause the control instability. Thus, robust control strategy considering the above uncertainties can be an alternative one to guarantee the performance and stability of the control. This study deals with the experimental verification of robust controller design for the active mass driver. $\mu$-synthesis technique is employed as a robust control strategy. Some weights are chosen based on the difference between the initial plant with which the controller is designed and the perturbed plant to be controlled having the actuator uncertainty. The robustness of $\mu$-synthesis technique is compared with the result of LQG strategy, which does not consider the uncertainty.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.10b
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• pp.656-661
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• 1998

This paper presents a method of statistical analysis and sensitivity analysis of creep and shrinkage effects in PSC box girder bridges. The statistical and sensitivity analyses are performed by using the numerical simulation of Latin Hypercube sampling. For each sample, the time-dependent structural analysis is performed to produce response data, which are then statistically analyzed. The probabilistic prediction of the confidence limits on long-term effects of creep and shrinkage is then expressed. Three measures are examined to quantify the sensitivity of the outputs to each of the input variables. These are rank correlation coefficient(RCC), partial rank correlation coefficient(PRCC) and standardized rank regression coefficient(SRRC) computed on the ranks of the observations. Probability band widens with time, which indicates an increase of prediction uncertainty with time. The creep model uncertainty factor and the relative humidity appear as the most dominant factors with regard to the model output uncertainty.