• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.320-328
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• 2003

This paper proposes a new nonlinear adaptive guidance law. Fourth order state equation for integrated guidance and control loop is formulated considering target uncertainties and control loop dynamics. The state equation is further changed into the normal form by nonlinear coordinate transformation. An adaptive nonlinear guidance law is proposed to compensate for the uncertainties In both target acceleration and control loop dynamics. The proposed law adopts the sliding mode control approach with adaptation fer unknown bound of uncertainties. The present approach can effectively solve the existing guidance problem of target maneuver and the limited performance of control loop. We provide the stability analyses and demonstrate the effectiveness of our scheme through simulations.

• Proceedings of the KSR Conference
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• 2006.11a
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• pp.171-180
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• 2006

The EMS system requires a very delicate suspension control to maintain constant air-gap between the magnet and the guide-way rail. To maintain a constant air-gap with attraction force, the EMS system dynamics is changed according to uncertainties and disturbances, and it also requires reliability against component failures. Since uncertainties and component failures are frequently caused in EMS system, it is very important to develop the robust and reliable control system. In this paper, we consider the design problem for robust and reliable controller in the presence of uncertainties and component failures.

• Structural Engineering and Mechanics
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• v.81 no.3
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• pp.293-303
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• 2022

As infrastructure ages and traffic load increases, serious public concerns have arisen for the well-being of bridges. The current health monitoring practice focuses on large-scale bridges rather than short span bridges. However, it is critical that more attention should be given to these behind-the-scene bridges. The relevant information about the construction methods and as-built properties are most likely missing. Additionally, since the condition of a bridge has unavoidably changed during service, due to weathering and deterioration, the material properties and boundary conditions would also have changed since its construction. Therefore, it is not appropriate to continue using the design values of the bridge parameters when undertaking any analysis to evaluate bridge performance. It is imperative to update the model, using finite element (FE) analysis to reflect the current structural condition. In this study, a FE model is established to simulate a concrete culvert bridge in New South Wales, Australia. That model, however, contains a number of parameter uncertainties that would compromise the accuracy of analytical results. The model is therefore updated with a neural network (NN) optimisation algorithm incorporating Monte Carlo (MC) simulation to minimise the uncertainties in parameters. The modal frequency and strain responses produced by the updated FE model are compared with the frequency and strain values on-site measured by sensors. The outcome indicates that the NN model updating incorporating MC simulation is a feasible and robust optimisation method for updating numerical models so as to minimise the difference between numerical models and their real-world counterparts.

• Korean Journal of Construction Engineering and Management
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• v.8 no.4
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• pp.203-213
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• 2007

In the past, several construction projects have exceeded their schedule resulting in financial losses to the owners; at present there are very few methods available to accurately forecast the completion date of a project. These nay be because of unforeseen outcomes that cannot be accounted for earlier and because of deficiency of proper tools to forecast completion date of said project. To overcome these difficulties, project managers may need a tool to predict the completion date at the early stage of project development. Bayesian Inference introduced in this paper is one such tool that can be employed to forecast project progress at all construction stages. Using this inference, project managers can combine an initially planned project progress (growth curve) with reported information from ongoing projects during the development, and in addition, dynamically revise this initial plan and quantify the uncertainty of completion date. This study introduces a theoretical model and proposes a mathematically information-based framework to forecast a project completion date that corresponds with the actual progress data and to monitor the modified uncertainties using Bayesian Inference.

• Journal of Korean Society for Atmospheric Environment
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• v.9 no.1
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• pp.1-10
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• 1993

A brief description on the greenhouse gases, the greenhoue effect, sea level changes, forcing of climate, the history of Earth's changing climate based on the IPCC REPORT and the records of the recent variation of the climate in the Republic of Kore is presented here for help enhancing awareness of the issues. The climate of the Earth has the potential to be changed on all timescales by the fluctuations of the concentrations of radioactively active greenhouse gases, solar radiation, aerosols and albedo. However, the rate of the recent global warming seems to be larger and rapid than any have occurred thorughout recorded history enough to draw the world-wide attention and worry concerned with the theme of environment and development. There are still uncertainties in the predictions relating to the timing, magnitude and the pattern of the climatic change due to the current incomplete understanding of various aspects of the complex processes. Nonetheless, the scientific results avaliable is sufficient to allow for decisive precautionary measures to be taken.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.10a
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• pp.70-73
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• 2001

The layup optimization by genetic algorithm (GA) for the interlaminar strength of laminated composites with free edge is presented. For the calculation of interlaminar stresses of composite laminates with free edges, extended Kantorovich method is applied. In the formulation of GA, repair strategy is adopted for the satisfaction of given constraints. In order to consider the bounded uncertainty of material properties, convex modeling is used. Results of GA optimization with scattered properties are compared with those of optimization with nominal properties. The GA combined with convex modeling can work as a practical tool for maximum interlaminar strength design of laminated composite structures, since uncertainties are always encountered in composite materials and the optimal results can be changed.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.10 s.241
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• pp.1130-1138
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• 2005

A national standard system for the petroleum field has been developed to calibrate and test the oil flow meters in Korea. The operating system and the uncertainty of the system were evaluated by the peer reviewers of foreign national metrology institutes in 2002. Since the characteristics of the system might be changed by time, the uncertainty of the system is reevaluated with the consideration of the long term stability of the system. It is found that the system has a relative expanded uncertainty of 0.048 $\%$ in the range of $15\~120\;m^3/h$. According to the uncertainty budget, the uncertainties of the fluid density and the final mass measurement, which are temperature dependent, contribute about $94\%$ of the total uncertainty in the oil flow standard system

• Special Issue of the Society of Naval Architects of Korea
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• 2005.06a
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• pp.206-210
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• 2005

As design trends has changed to have flexible aft hull structure, increased power output and stiffer shafting system, owners and classification societies have more concerned about shaft alignment. In the shaft alignment analysis, there are many uncertainties which are related in propeller generated force, bearing stiffness, crank shaft model and etc. in this study, it is focused on the effect of crankshaft model by comparing between equivalent model and actual crankshaft model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.272-288
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• 1990

The uncertainty quantification process in probabilistic Risk Assessment usually involves a specification of the uncertainty in the input data and the propagation of this uncertainty to the final risk results. The distributional sensitivity analysis is to study the impact of the various assumptions made during the quantification of input parameter uncertainties on the final output uncertainty. The uncertainty importance of input parameters, in this case, should reflect the degree of changes in the whole output distribution and not just in a point estimate value. A measure of the uncertainty importance is proposed in the present paper. The measure is called the distributional sensitivity measure(DSM) and explicitly derived from the definition of the Kullback's discrimination information. The DSM is applied to three typical discrimination information. The DSM is applied to three typical cases of input distributional changes: 1) Uncertainty is completely eliminated, 2) Uncertainty range is increased by a factor of 10, and 3) Type of distribution is changed. For all three cases of application, the DSM-based importance ranking agrees very well with the observed changes of output distribution while other statistical parameters are shown to be insensitive.

• Atmosphere
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• v.26 no.3
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• pp.435-444
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• 2016

In spite of considerable progress in the recent decades, there still remain large uncertainties in numerical cloud models. In this study, effects of uncertainty in terminal velocity of graupel on cloud simulation are investigated. For this, a two-dimensional bin microphysics cloud model is employed, and deep convective clouds are simulated under idealized environmental conditions. In the sensitivity experiments, the terminal velocity of graupel is changed to twice and half the velocity in the control experiment. In the experiment with fast graupel terminal velocity, a large amount of graupel mass is present in the lower layer. On the other hand, in the experiment with slow graupel terminal velocity, almost all graupel mass remains in the upper layer. The graupel size distribution exhibits that as graupel terminal velocity increases, in the lower layer, the number of graupel particles increases and the peak radius in the graupel mass size distribution decreases. In the experiment with fast graupel terminal velocity, the vertical velocity is decreased mainly due to a decrease in riming that leads to a decrease in latent heat release and an increase in evaporative cooling via evaporation, sublimation, and melting that leads to more stable atmosphere. This decrease in vertical velocity causes graupel particles to fall toward the ground easier. By the changes in graupel terminal velocity, the accumulated surface precipitation amount differs up to about two times. This study reveals that the terminal velocity of graupel should be estimated more accurately than it is now.