• Computational Structural Engineering
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• v.10 no.4
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• pp.337-347
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• 1997

The dynamic responses of highway bridges are varying depending on the features of either traveling vehicles or bridges. In this study, the probabilistic characteristics of dynamic amplification factors of highway bridges due to traveling heavy vehicles have been examined through analytical simulation processes. The truck with tandem axle and tractor with semitrailer are selected as the representative heavy vehicles, which are modeled with three dimensional 7-DOF and 12-DOF models, respectively. The analytical results have been compared with the experimental results of dynamic loading tests and the validity of the analytical models has been examined. Parametric studies on the means and extreme values of amplification factors have been performed with various traffic conditions such as vehicle types, vehicle weights, surface profiles, number of loading vehicles, loading positions, etc.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2674-2697
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• 2019

Identity authentication is a crucial line of defense for network security, and passwords are still the mainstream of identity authentication. So far trawling password attacking has been extensively studied, but the research related with personal information is always sporadic. Probabilistic context-free grammar (PCFG) and Markov chain-based models perform greatly well in trawling guessing. In this paper we propose a systematic targeted attacking model based on structure partition and string reorganization by migrating the above two models to targeted attacking, denoted as TG-SPSR. In structure partition phase, besides dividing passwords to basic structure similar to PCFG, we additionally define a trajectory-based keyboard pattern in the basic grammar and introduce index bits to accurately characterize the position of special characters. Moreover, we also construct a BiLSTM recurrent neural network classifier to characterize the behavior of password reuse and modification after defining nine kinds of modification rules. Extensive experimental results indicate that in online attacking, TG-SPSR outperforms traditional trawling attacking algorithms by average about 275%, and respectively outperforms its foremost counterparts, Personal-PCFG, TarGuess-I, by about 70% and 19%; In offline attacking, TG-SPSR outperforms traditional trawling attacking algorithms by average about 90%, outperforms Personal-PCFG and TarGuess-I by 85% and 30%, respectively.

• Wind and Structures
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• v.28 no.4
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• pp.225-238
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• 2019

In this paper a novel and efficient computational framework to estimate the stress range versus number of cycles curves experienced by a cable due to external excitations (e.g., seismic excitations, traffic and wind-induced vibrations, among others) is proposed. This study is limited to the wind-cable interaction governed by the Vortex Shedding mechanism which mainly rules cables vibrations at low amplitudes that may lead to their failure due to bending fatigue damage. The algorithm relies on a stochastic approach to account for the uncertainties in the cable properties, initial conditions, damping, and wind excitation which are the variables that govern the wind-induced vibration phenomena in cables. These uncertainties are propagated adopting Monte Carlo simulations and the concept of importance sampling, which is used to reduce significantly the computational costs when new scenarios with different probabilistic models for the uncertainties are evaluated. A high fidelity cable model is also proposed, capturing the effect of its internal wires distribution and helix angles on the cables stress. Simulation results on a 15 mm diameter high-strength steel strand reveal that not accounting for the initial conditions uncertainties or using a coarse wind speed discretization lead to an underestimation of the stress range experienced by the cable. In addition, parametric studies illustrate the computational efficiency of the algorithm at estimating new scenarios with new probabilistic models, running 3000 times faster than the base case.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.298-298
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• 2021

본 연구에서는 국내 6개 지역 서울, 강릉, 대전, 광주, 부산, 제주의 30년 치 시강우 자료에 해석적 확률모형(Analytical Probabilistic Models) 방법을 적용하여 도시 홍수 저감을 목적으로 하는 저류시설 설계를 위한 유출량 예측 정도를 지역별로 비교하고자 하였다. 강우 사상 분포의 해석적 확률모형을 적용하기 위해 무강우 시간을 결정하여 독립 호우를 결정하는데, 자기상관계수와 변동계수를 활용한 무강우 지속시간의 산정(IETD, Interevent Time Definition) 방법을 사용하였다. 해석적 확률모형인 유출량의 확률밀도함수(PDF, Probability Density Function)를 유도하기 위해서 불투수 지역과 투수 지역의 영향을 고려하여 유출계수를 적용하는 강우-유출 관계를 가지고 유출량을 정의하였다. 강우량, 강우 지속시간, 무강우시간과 같은 강우특성은 1변수 지수함수의 PDF를 따른다고 가정하였다. 확률모형 방법의 적합성을 판단하기 위해 결정된 IETD에 따라 각 지역별로 실제 강우 사상을 해석적 모델과 연속모의실험인 SWWM(Storm Water Management Model)에 적용하여 불투수율에 따른 유출량을 산정하였다. 각 방식으로 얻은 유출량 결과는 모든 지역에서 매우 유사하게 나타났고 결론적으로 우리나라에서 도시 홍수 저감을 위한 저류시설의 계획과 설계에 확률모형 방법이 적용 가능하다는 것을 확인할 수 있었다.

• Computers and Concrete
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• v.2 no.4
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• pp.325-343
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• 2005

Chloride ingress is a common cause of deterioration of reinforced concrete located in coastal zone. Modeling the chloride ingress is an important basis for designing reinforced concrete structures and for assessing the reliability of an existing structure. The modeling is also needed for predicting the deterioration of a reinforced structure. The existing deterministic solution for prediction model of corrosion initiation cannot reflect uncertainties which input variables have. This paper presents an approach to the fuzzy arithmetic based modeling of the chloride-induced corrosion of reinforcement in concrete structures that takes into account the uncertainties in the physical models of chloride penetration into concrete and corrosion of steel reinforcement, as well as the uncertainties in the governing parameters, including concrete diffusivity, concrete cover depth, surface chloride concentration and critical chloride level for corrosion initiation. There are a lot of prediction model for predicting the time of reinforcement corrosion of structures exposed to chloride-induced corrosion environment. In this work, RILEM model formula and Crank's solution of Fick's second law of diffusion is used. The parameters of the models are regarded as fuzzy numbers with proper membership function adapted to statistical data of the governing parameters instead of random variables of probabilistic modeling of Monte Carlo Simulation and the fuzziness of the time to corrosion initiation is determined by the fuzzy arithmetic of interval arithmetic and extension principle. An analysis is implemented by comparing deterministic calculation with fuzzy arithmetic for above two prediction models.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4367-4381
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• 2023

Nuclear power plants are increasingly being equipped with digital I&C systems. Although some probabilistic safety assessment (PSA) models for the digital I&C of nuclear power plants have been constructed, there is currently no specific internationally agreed guidance for their modeling. This paper presents an initiative by the OECD Nuclear Energy Agency called "Digital I&C PSA - Comparative application of DIGital I&C Modelling Approaches for PSA (DIGMAP)", which aimed to advance the field towards practical and defendable modeling principles. The task, carried out in 2017-2021, used a simplified description of a plant focusing on the digital I&C systems important to safety, for which the participating organizations independently developed their own PSA models. Through comparison of the PSA models, sensitivity analyses as well as observations throughout the whole activity, both qualitative and quantitative lessons were learned. These include insights on failure behavior of digital I&C systems, experience from models with different levels of abstraction, benefits from benchmarking as well as major contributors to the core damage frequency and those with minor effect. The study also highlighted the challenges with modeling of large common cause component groups and the difficulties associated with estimation of key software and common cause failure parameters.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.2
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• pp.176-183
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• 2008

In this paper, three classical overtopping models: Owen model, Van der Meer & Janssen model and Hedges & Reis model were used to calculate the failure probability of wave overtopping of seawalls. Among of them, the Hedges & Reis model was regarded as a moderate method to analyze the failure probability of wave overtopping of seawalls and the probabilistic assessments of wave overtopping were carried out for a constructing seawall at Busan in Korea by Level II and Level III reliability methods. Considering the cost of construction, an appropriate crest level was proposed for a certain rate of wave overtopping at a lower failure probability.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.1
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• pp.13-17
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• 2018

According to the recent blackouts, large blackouts can be described by cascading outages. Cascading outage is defined by sequential outages from an initial disturbance. Sequential and probabilistic approach are necessary to minimize the blackout damage caused by cascading outages. In addition, conventional cascading outage analysis models are computationally complex and have time constraints, it is necessary to develop the new analytical techniques. In this paper, we propose the advance visualization model for probabilistic analysis of cascading failure risks. We introduce the visualization model for identifying size of cascading and potential outages and estimate the propagation rate of sequential outage simulation. The proposed model is applied to Korean power systems.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.513-519
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• 2013

The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.

• Transactions on Electrical and Electronic Materials
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• v.18 no.6
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• pp.350-358
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• 2017

Recently, owing to increased interest in low-carbon energy supplies, renewable energy sources such as photovoltaics and wind turbines in distribution networks have received considerable attention for generating clean and unlimited energy. The presence of energy storage systems (ESSs) in the promising field of active distribution networks (ADNs) would have direct impact on power system problems such as encountered in probabilistic distributed generation (DG) model studies. Hence, the optimal procedure is offered herein, in which the simultaneous placement of an ESS, photovoltaic-based DG, and wind turbine-based DG in an ADN is taken into account. The main goal of this paper is to maximize the net present value of the loss reduction benefit by considering the price of electricity for each load state. The proposed framework consists of a scenario tree method for covering the existing uncertainties in the distribution network's load demand as well as DG. The collected results verify the considerable effect of concurrent installation of probabilistic DG models and an ESS in defining the optimum site of DG and the ESS and they demonstrate that the optimum operation of an ESS in the ADN is consequently related to the highest value of the loss reduction benefit in long-term planning as well. The results obtained are encouraging.