• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1597-1600
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• 1991

In this paper, we describe a notion of sensor modeling method in multisensor data fusion using fuzzy set theory. Each sensor module is characterized by its fuzzy constraints to specific features of environment. These sensor fuzzy constraints can be imposed on multisensory data to verify their degree of truth and compatibility toward the final decision making. In comparison with other sensor modeling methods, such as probabilistic models or rule-based models, the proposed method is very simple and can be easily implemented in intelligent robot systems.

• Wind and Structures
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• v.13 no.2
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• pp.191-206
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• 2010

Windborne debris is a major cause of structural damage during severe windstorms and hurricanes owing to its direct impact on building envelopes as well as to the 'chain reaction' failure mechanism it induces by interacting with wind pressure damage. Estimation of debris risk is an important component in evaluating wind damage risk to residential developments. A debris risk model developed by the authors enables one to analytically aggregate damage threats to a building from different types of debris originating from neighboring buildings. This model is extended herein to a general debris risk analysis methodology that is then incorporated into a vulnerability model accounting for the temporal evolution of the interaction between pressure damage and debris damage during storm passage. The current paper (Part I) introduces the debris risk analysis methodology, establishing the mathematical modeling framework. Stochastic models are proposed to estimate the probability distributions of debris trajectory parameters used in the method. It is shown that model statistics can be estimated from available information from wind-tunnel experiments and post-damage surveys. The incorporation of the methodology into vulnerability modeling is described in Part II.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.387-394
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• 2017

Seismic probabilistic risk assessment (SPRA) requires a large number of simulations to evaluate the seismic vulnerability of structural and nonstructural components in nuclear power plants. The effect of structural modeling and analysis assumptions on dynamic analysis of 3D and simplified 2D stick models of auxiliary buildings and the attached nonstructural components is investigated. Dynamic characteristics and seismic performance of building models are also evaluated, as well as the computational accuracy of the models. The presented results provide a better understanding of the dynamic behavior and seismic performance of auxiliary buildings. The results also help to quantify the impact of uncertainties associated with modeling and analysis of simplified numerical models of structural and nonstructural components subjected to seismic shaking on the predicted seismic failure probabilities of these systems.

• Tunnel and Underground Space
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• v.15 no.2 s.55
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• pp.145-156
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• 2005

MODFLOW, 3-D finite difference code, is widely used to model groundwater flow and has been used to assess the effect of excavations on the groundwater system due to construction of subways and mountain tunnels. The results of numerical analysis depend on boundary conditions, initial conditions, conceptual models and hydrogeological properties. Therefore, its accuracy can only be enhanced using more realistic and field oriented input parameters. In this study, SA(simulated annealing) was used to integrate hydraulic conductivities from a few of injection tests with geophysical reference images. The realizations of hydraulic conductivity random field are obtained and then groundwater flows in each geostatistically equivalent media are analyzed with a numerical simulation. This approach can give probabilistic results of groundwater flow modeling considering the uncertainty of hydrogeological medium. In other words, this approach makes it possible to quantify the propagation of uncertainty of hydraulic conductivities into groundwater flow.

• Computers and Concrete
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• v.26 no.2
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• pp.127-136
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• 2020

There is an inherent randomness for concrete microstructure even with the same manufacturing process. Meanwhile, the concrete material under the aqueous environment is usually not fully saturated by water. This study aimed to develop a stochastic micromechanical framework to investigate the probabilistic behavior of the unsaturated concrete from microscale level. The material is represented as a multiphase composite composed of the water, the pores and the intrinsic concrete (made up by the mortar, the coarse aggregates and their interfaces). The differential scheme based two-level micromechanical homogenization scheme is presented to quantitatively predict the concrete's effective properties. By modeling the volume fractions and properties of the constituents as stochastic, we extend the deterministic framework to stochastic to incorporate the material's inherent randomness. Monte Carlo simulations are adopted to reach the different order moments of the effective properties. A distribution-free method is employed to get the unbiased probability density function based on the maximum entropy principle. Numerical examples including limited experimental validations, comparisons with existing micromechanical models, commonly used probability density functions and the direct Monte Carlo simulations indicate that the proposed models provide an accurate and computationally efficient framework in characterizing the material's effective properties. Finally, the effects of the saturation degrees and the pore shapes on the concrete macroscopic probabilistic behaviors are investigated based on our proposed stochastic micromechanical framework.

• Journal of Food Hygiene and Safety
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• v.33 no.3
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• pp.157-161
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• 2018

The objective of this study was to develop software to predict the kinetic behavior and the probability of foodborne bacterial growth on processed meat products. It is designed for rapid application by non-specialists in predictive microbiology. The software, named Foodborne bacteria Animal product Modeling Equipment (FAME), was developed using Javascript and HTML. FAME consists of a kinetic model and a probabilistic model, and it can be used to predict bacterial growth pattern and probability. In addition, validation and editing of model equation are available in FAME. The data used by the software were constructed with 5,400 frankfurter samples for the kinetic model and 345,600 samples for the probabilistic model using a variety of combinations including atmospheric conditions, temperature, NaCl concentrations and $NaNO_2$ concentrations. Using FAME, users can select the concentrations of NaCl and $NaNO_2$ meat products as well as storage conditions (atmosphere and temperature). The software displays bacterial growth patterns and growth probabilities, which facilitate the determination of optimal safety conditions for meat products. FAME is useful in predicting bacterial kinetic behavior and growth probability, especially for quick application, and is designed for use by non-specialists in predictive microbiology.

• Computers and Concrete
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• v.6 no.2
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• pp.133-153
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• 2009

Discrete element modeling (DEM) in concrete technology is concerned with design and use of models that constitute a schematization of reality with operational potentials. This paper discusses the material science principles governing the design of DEM systems and evaluates the consequences for their operational potentials. It surveys the two families in physical discrete element modeling in concrete technology, only touching upon probabilistic DEM concepts as alternatives. Many common DEM systems are based on random sequential addition (RSA) procedures; their operational potentials are limited to low configuration-sensitivity features of material structure, underlying material performance characteristics of low structure-sensitivity. The second family of DEM systems employs concurrent algorithms, involving particle interaction mechanisms. Static and dynamic solutions are realized to solve particle overlap. This second family offers a far more realistic schematization of reality as to particle configuration. The operational potentials of this family involve valid approaches to structure-sensitive mechanical or durability properties. Illustrative 2D examples of fresh cement particle packing and pore formation during maturation are elaborated to demonstrate this. Mainstream fields of present day and expected application of DEM are sketched. Violation of the scientific knowledge of to day underlying these operational potentials will give rise to unreliable solutions.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.342-348
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• 2017

Precursor analysis is widely used in the nuclear industry to judge the significance of events relevant to safety. However, in case of events that may damage equipment through effects that are not ordinary functional dependencies, the analysis may not always fully appreciate the potential for further evolution of the event. For fires, which are one class of such events, this paper discusses modelling challenges that need to be overcome when performing a probabilistic precursor analysis. The events used to analyze are selected from the Organisation for Economic Cooperation and Development (OECD) Fire Incidents Records Exchange (FIRE) Database.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.613-615
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• 2002

특징점 기반의 지문 정합 시스템은 동일 특징점의 검색을 통하여, 주어진 두 지문의 동일 여부를 결정하는 것을 목적으로 하고 있다. 정합과정의 검색 단계에서 동일 특징점으로 결정된 두 특징점간 거리 및 각도차의 분포를 확률적으로 모델링함으로써, 검색된 동일 특징점의 신뢰도를 높이고자 하였으며 전체적으로 지문 정합시스템의 성능향상을 목적으로 한다. 본 논문에서는 확률기법을 사용한 동일 특징점 유사도 산출 방법과 이를 통한 지문의 동일여부 결정방법을 제시하였으며 구현결과, EER의 경우 2.64%에서 0.78%로 70%의 감소효과를 얻을 수 있었다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.2
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• pp.33-42
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• 1983

Outage cost inclusion in operational simulation is very important subject in generation planning. Conventional discretized one in probabilistic simulation has unavoidably insufficient modeling and costly computation time. Now that the analytic operational simulation is possible, the outage cost inclusion is desired. With this inclusion the objective function of operational simulation becomes convex, so that analytic manipulation is easier. The derivation of outage cost is made in this paper, and the effects is evaluated. Further marginal cost is mentioned.