• Wind and Structures
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• v.38 no.5
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• pp.355-366
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• 2024

Severe natural multi-hazard events can cause damage to infrastructure and economic losses of billions of dollars. The challenges of modeling these losses include dependency between hazards, cause and sequence of loss, and lack of available data. This paper presents and explores multi-hazard loss modeling in the context of the combined wind and rain vulnerability of mid/high-rise buildings during hurricane events. A component-based probabilistic vulnerability model provides the framework to test and contrast two different approaches to treat the multi-hazards: In one, the wind and rain hazard models are both decoupled from the vulnerability model. In the other, only the wind hazard is decoupled, while the rain hazard model is embedded into the vulnerability model. The paper presents the mathematical and conceptual development of each approach, example outputs from each for the same scenario, and a discussion of weaknesses and strengths of each approach.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.37-46
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• 2012

The change of rainfall pattern and hydrologic factors due to climate change increases the occurrence probability of agricultural reservoir water shortage. Water supply assessment of reservoir is usually performed current reservoir level compared to historical water levels or the simulation of reservoir operation based on the water budget analysis. Since each reservoir has the native property for watershed, irrigation district and irrigation water requirement, it is necessary to improve the assessment methods of agricultural reservoir water capability about water resources system. This study proposed a practical methods that water supply vulnerability assessment for an agricultural reservoir based on a concept of probabilistic reliability. The vulnerability assessment of water supply is calculated from probability distribution of water demand condition and water supply condition that influences on water resources management and reservoir operations. The water supply vulnerability indices are estimated to evaluate the performance of water supply on agricultural reservoir system, and thus it is recommended a more objective method to evaluate water supply reliability.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.6
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• pp.383-389
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• 2013

Analysis and review of survivability is one of the most important aspects when naval vessels are designed. Because aiming points of threat towards the naval vessels in the battle field could not be estimated exactly, probabilistic and statistic approach is frequently introduced to evaluate and enhance the vessel survivability. Some commercial survivability analysis programs are used to perform the analysis for enhancement of susceptibility, vulnerability and recoverability but, they are usually classified and impossible to be exported to other countries because of their national security. In this paper, a simplified vulnerability analysis program is developed to evaluate the vulnerability of the warship in aspects of structure, redundancy and its mission capability at the conceptual design stage. To verify the developed program, the analysis results were compared with those of the commercial program MOTISS(Measure of Total Integrated System Survivability).

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.77-85
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• 2013

The efficient operation and management strategies of reservoirs in irrigation periods of drought events are an essential element for drought planning and countermeasure. Korea Rural Community Corporation has developed the real-time water level observation system of agricultural reservoirs to efficiently operate reservoirs, however, it is not possible to predict drought conditions, and only provides information of current situation. Hence, it is necessary to evaluate accurate irrigation vulnerability and efficiently reservoir operation rules using current water level. In this paper, the improvement methods of reservoir operation planning were developed with water supply vulnerability characteristic curves comparing to automatic water gauge at agricultural reservoirs. The 11 reservoirs were simulated applying the reservoir operation rules which was determined by irrigation vulnerability characteristic curves criteria and real time water level, and evaluated water supply situation in 2012 year. The analysis of results can be identified probabilistic possibility of water supply failures compared with the existing reservoir operation criteria. These results of efficient reservoir operation rules can be achieved enable irrigation planners to optimally manage available water resources for decision making, and contributed to maintain the water supply according to demand strategy for agricultural reservoirs management.

• Journal of Ocean Engineering and Technology
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• v.19 no.1 s.62
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• pp.26-32
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• 2005

Recent earthquakes, measuring over a magnitude of 5.0, on the eastern coast of Korea, have aroused interest in earthquake analyses and the seismic design of caisson-type breakwaters. Most earthquake analysis methods, such as equivalent static analysis, response spectrum analysis, nonlinear analysis, and capacity analysis, are deterministic and have been used for seismic design and performance evaluation of coastal structures. However, deterministic methods are difficult for reflecting on one of the most important characteristics of earthquakes, i.e. the uncertainty of earthquakes. This paper presents results of probabilistic seismic hazard assessment(PSHA) of an actual caisson-type breakwater, considering uncertainties of earthquake occurrences and soil properties. First, the seismic vulnerability of a structure and the seismic hazard of the site are evaluated, using earthquake sets and a seismic hazard map; then, the seismic risk of the structure is assessed.

• Journal of The Geomorphological Association of Korea
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• v.20 no.4
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• pp.85-99
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• 2013

The objective of this paper is to analyze the spatial distribution of errors in the DEM generated using waterlines from multi-temporal remote sensing data and to assess flood vulnerability. Unlike conventional research in which only global statistics of errors have been generated, this paper tries to quantitatively analyze the spatial distribution of errors from a probabilistic viewpoint using geostatistical simulation. The initial DEM in Baramarae tidal flats was generated by corrected tidal level values and waterlines extracted from multi-temporal Landsat data in 2010s. When compared with the ground measurement height data, overall the waterline-based DEM underestimated the actual heights and local variations of the errors were observed. By applying sequential Gaussian simulation based on spatial autocorrelation of DEM errors, multiple alternative error distributions were generated. After correcting errors in the initial DEM with simulated error distributions, probabilities for flood vulnerability were estimated under the sea level rise scenarios of IPCC SERS. The error analysis methodology based on geostatistical simulation could model both uncertainties of the error assessment and error propagation problems in a probabilistic framework. Therefore, it is expected that the error analysis methodology applied in this paper will be effectively used for the probabilistic assessment of errors included in various thematic maps as well as the error assessment of waterline-based DEMs in tidal flats.

• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.367-392
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• 2020

The specific characteristics of near-field earthquake records can lead to different dynamic responses of bridges compared to far-field records. However, the effect of near-field strong ground motion has often been neglected in the seismic performance assessment of the bridges. Furthermore, damage to horizontally curved multi-frame RC box-girder bridges in the past earthquakes has intensified the potential of seismic vulnerability of these structures due to their distinctive dynamic behavior. Based on the nonlinear time history analyses in OpenSEES, this article, assesses the effects of near-field versus far-field earthquakes on the seismic performance of horizontally curved multi-frame RC box-girder bridges by accounting the vertical component of the earthquake records. Analytical seismic fragility curves have been derived thru considering uncertainties in the earthquake records, material and geometric properties of bridges. The findings indicate that near-field effects reasonably increase the seismic vulnerability in this bridge sub-class. The results pave the way for future regional risk assessments regarding the importance of either including or excluding near-field effects on the seismic performance of horizontally curved bridges.

• Journal of the Korea Concrete Institute
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• v.20 no.1
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• pp.51-58
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• 2008

Analytical probabilistic vulnerability analysis requires extensive computing effort as a result of the randomness in both input motion and response characteristics. In this study, a new methodology whereby a set of vulnerability curves are derived based on the fundamental response quantities of stiffness, strength and ductility is presented. A response database of coefficients describing lognormal vulnerability relationships is constructed by employing aclosed-form solution for a generalized single-degree-of-freedom system. Once the three fundamental quantities of a wide range of structural systems are defined, the vulnerability curves for various limit states can be derived without recourse to further simulation. Examples of application are given and demonstrate the extreme efficiency of the proposed approach in deriving vulnerability relationships.

• Steel and Composite Structures
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• v.21 no.1
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• pp.93-107
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• 2016

Seismic fragility analysis is a probabilistic decision-making framework which is widely implemented for evaluating vulnerability of a building under earthquake loading. It requires ingredient named probabilistic model and commonly developed using statistics requiring collecting data in large quantities. Preparation of such a data-base is often costly and time-consuming. Therefore, in this paper, by developing generic seismic drift demand model for regular-multi-story steel moment resisting frames is tried to present a novel application of the probabilistic decision-making analysis to practical purposes. To this end, a demand model which is a linear function of intensity measure in logarithmic space is developed to predict overall maximum inter-story drift. Next, the model is coupled with a set of regression-based equations which are capable of directly estimating unknown statistical characteristics of the model parameters.To explicitly address uncertainties arise from randomness and lack of knowledge, the Bayesian regression inference is employed, when these relations are developed. The developed demand model is then employed in a Seismic Fragility Analysis (SFA) for two designed building. The accuracy of the results is also assessed by comparison with the results directly obtained from Incremental Dynamic analysis.

• Structural Engineering and Mechanics
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• v.34 no.1
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• pp.15-38
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• 2010

In order to predict the shear strengths of reinforced concrete beams, many deterministic models have been developed based on rules of mechanics and on experimental test results. While the constant and variable angle truss models are known to provide reliable bases and to give reasonable predictions for the shear strengths of members with shear reinforcement, in the case of members without shear reinforcement, even advanced models with complicated procedures may show lack of accuracy or lead to fairly different predictions from other similar models. For this reason, many research efforts have been made for more accurate predictions, which resulted in important recent publications. This paper develops probabilistic shear strength models for reinforced concrete beams without shear reinforcement based on deterministic shear strength models, understanding of shear transfer mechanisms and influential parameters, and experimental test results reported in the literature. Using a Bayesian parameter estimation method, the biases of base deterministic models are identified as algebraic functions of input parameters and the errors of the developed models remaining after the bias-correction are quantified in a stochastic manner. The proposed probabilistic models predict the shear strengths with improved accuracy and help incorporate the model uncertainties into vulnerability estimations and risk-quantified designs.