• Journal of Korea Water Resources Association
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• v.35 no.2
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• pp.173-186
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• 2002

Rainfall-runoff model is usually used in estimating the design flood, and the most important elements in this model are probable rainfall and unit hydrograph. So, it is the most important step to estimate probable rainfall reasonably and exactly. If a basin area exceeds a certain scale, probable areal rainfall should be used as probable rainfall, but, Probable point- mean rainfall be usually used in Korea. Consequently, probable rainfall is used too high and unit hydrograph is used relatively too low. Thus the improvement is unavoidable. So, in this study, the parameters are proposed that transform the 1day, 2day rainfall to 24hr, 48hr rainfall, and areal rainfall data series are composed by using the same time rainfall data. Also, the areal reduction factor(ARF) is developed as the increase of area by the calculated probable point mean rainfall and probable areal rainfall by frequency analysis in Han-River basin. It can be the measure to easily transform probable point- mean rainfall to probable areal rainfall.

• Composites Research
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• v.23 no.2
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• pp.40-47
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• 2010

In this paper, the hybrid response surface method(HRSM) is proposed and examined. Hybrid response surface method calculate a approximate model repeatedly based on MPP coordinates. To verify the performance, probability of failure, MPP(Most Probable failure Point) and reliability index are calculated for nonlinear function and composite laminated plate by using reliability analysis method and compared with results by using typical response surface method(RSM). Probability of failure is calculated under the assumption of the nonlinear limit state equation and given failure criterion. The results of proposed method shows performance improvement in estimating the probability of failure.

• Structural Engineering and Mechanics
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• v.76 no.6
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• pp.675-685
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• 2020

As the classical response surface method (RSM), the polynomial RSM is so easy-to-apply that it is widely used in reliability analysis. However, the trade-off of accuracy and efficiency is still a challenge and the "curse of dimension" usually confines RSM to low dimension systems. In this paper, based on the univariate decomposition, the polynomial RSM is executed in a new mode, called as DPRSM. The general form of DPRSM is given and its implementation is designed referring to the classical RSM firstly. Then, in order to balance the accuracy and efficiency of DPRSM, its adaptive order revision around the most probable point (MPP) is proposed by introducing the univariate polynomial order analysis, noted as RDPRSM, which can analyze the exact nonlinearity of the limit state surface in the region around MPP. For testing the proposed techniques, several numerical examples are studied in detail, and the results indicate that DPRSM with low order can obtain similar results to the classical RSM, DPRSM with high order can obtain more precision with a large efficiency loss; RDPRSM can perform a good balance between accuracy and efficiency and preserve the good robustness property meanwhile, especially for those problems with high nonlinearity and complex problems; the proposed methods can also give a good performance in the high-dimensional cases.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.889-896
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• 2006

The concept of reliability has been applied to the topology optimization based on a reliability index approach or a performance measure approach. Since these approaches, called double-loop single vector approach, require the nested optimization problem to obtain the most probable point in the probabilistic design domain, the time for the entire process makes the practical use infeasible. In this work, new reliability-based topology optimization method is proposed by utilizing single-loop single-vector approach, which approximates searching the most probable point analytically, to reduce the time cost. The results of design examples show that the proposed method provides efficiency curtailing the time for the optimization process and accuracy satisfying the specified reliability.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.9 s.252
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• pp.1116-1123
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• 2006

In this study, the effective method for reliability estimation is proposed using tow-staged kriging metamodel and genetic algorithm. Kriging metamodel can be determined by appropriate sampling range and the number of sampling points. The first kriging metamodel is made based on the proposed sampling points. The advanced f'=rst order reliability method is applied to the first kriging metamodel to determine the reliability and most probable failure point(MPFP) approximately. Then, the second kriging metamodel is constructed using additional sampling points near the MPFP. These points are selected using genetic algorithm that have the maximum mean squared error. The Monte-Carlo simulation is applied to the second kriging metamodel to estimate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.

• Advances in concrete construction
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• v.10 no.6
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• pp.527-536
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• 2020

In this study, a process is proposed to calculate analytical correction values for the vertical shortening of all columns on all floors in a high-rise building that minimizes the error between the structural analysis predictions and values measured during construction. The weight ratio and the most probable value were accordingly considered based on the properties of the shortening value analyzed at several points in each construction stage and the distance between these measured points and unmeasured points at which the shortening was predicted. The effective range and shortening value normalization were considered using the column grouping concept. These tools were applied to calculate the error ratio between the predicted and measured values on a floor where a measured point exists, and then determine the estimated error ratio and estimated error value for the unmeasured point using this error ratio. At points on a floor where no measured point exists, the estimated error ratio and the estimated error value were calculated by applying the most probable value considering the weight ratio for the nearest floor where measured points exist. In this manner, the error values and estimated error values can be determined at all points in a structure. Then, the analytical correction value, defined as this error or estimated error value, was applied by adding it to the predicted value. Finally, the adequacy of the proposed correction method was verified against measurements by applying the analytical corrections to all unmeasured points based on the points where the measurement exists.

• Journal of Korean Society of Water and Wastewater
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• v.12 no.3
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• pp.99-106
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• 1998

This paper presents a procedure for determining the design rainfall depth and the design rainfall intensity at Incheon city area in Korea. In this study the eight probability distributions are considered to estimate the probable rainfall depths for 11 different durations. The Kolmogorov - Smirnov test and the Chi-square test are adopted to test each distribution. The probable rainfall intensity formulas are then determined by i) the least squares (LS) method, ii) the least median squares (LMS) method, iii) the reweighted least squares method based on the LMS (RLS), and iv) the constrained regression (CR) model. The Talbot, the Sherman, the Japanese, and the Unified type are considered to determine the best type for the Incheon station. The root mean squared (RMS) errors are computed to test the formulas derived by four methods. It is found that the Unified type is the most reliable and that all methods presented herein are acceptable for determining the coefficients of rainfall intensity formulas from an engineering point of view.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.32-39
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• 2000

Probabilistic structural design optimization, which is characterized by the so-called probabilistic. constraints which introduce permissible probability of violation, is preferred to deterministic design optimization since unpredictable inherent uncertainties and randomness in structural and environmental properties are to be taken quantitatively into account by probabilistic design optimization. In this paper, the well-known reliability index based MPFP(Most Probable Failure Point) search approach and the newly introduced target performance measure based MPTP(Minimum Performance Target Point) search approach are summarized and compared. The present comparison focuses on the number of iterations required for the estimation of probabilistic constraints and a technique for improvement which removes exhaustive iterations is presented as well. A 10 bar truss problem is examined for this.

• Economic and Environmental Geology
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• v.29 no.3
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• pp.335-343
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• 1996

The dipole-dipol electrical resistivity survey was conducted to investigate the probable contamination of the Han river by leachate from the near-by Nanjido Landfill. The survey line of 3 km was set along the unpaved road toward the Han river. For the convenience of the field work, the survey line was divided into four segments. The complete two-dimensional resistivity section was constructed by connecting the inversion result of each segment. Gravity survey was also carried out along the profile parallel to the resistivity line. Near surface resistivity generally appeared to be of very low value in most part of the survey area and the boundary between the alluvium layer and underlying basement rocks is well discriminated on the resistivity section. These results agree well with those of the preceding Schlumberger depth sounding made at adjacent area by Lee and fun (1995). The variation of thickness of the alluvium layer delineated by gravity anomaly profile also correlates well with the result of the resistivity survey on the qualitative basis. The problem of contamination by leachate from the Nanjido Landfill, where various waste materials have been dumped without any proper treatment facilities, has been remains unsolved yet. Therefore, we present the most probable passages of leachate flow based on the survey results and have briefly discussed about measure for contamination control. Considering the thickness of alluvium and the possible existence of fractured zone, the middle point between 1st and 2nd landfill and the midst of 1st landfill are the most hazardous regions to make leachates flow into the Han river. Since large amounts of leachates are observed from the test wells located on the lines extending from the border between the 1st and 2nd landfill and the middle of the lst landfill, contamination protection barriers are strongly recommended near these regions.

• Structural Engineering and Mechanics
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• v.55 no.5
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• pp.979-999
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• 2015

This paper proposes a novel reliability analysis method which computes reliability index, most probable point and probability of failure of uncertain systems more efficiently and accurately with compared to Monte Carlo, first-order reliability and response surface methods. It consists of Initial and Simulation steps. In Initial step, a number of space-filling designs are selected throughout the variables space, and then in Simulation step, performances of most of samples are estimated via interpolation using the space-filling designs, and only for a small number of the samples actual performance function is used for evaluation. In better words, doing so, we use a simple interpolation function called "reduced" function instead of the actual expensive-to-evaluate performance function of the system to evaluate most of samples. By using such a reduced function, total number of evaluations of actual performance is significantly reduced; hence, the method can be called Reduced Function Evaluations method. Reliabilities of six examples including series and parallel systems with multiple failure modes with truncated and/or non-truncated random variables are analyzed to demonstrate efficiency, accuracy and robustness of proposed method. In addition, a reliability-based design optimization algorithm is proposed and an example is solved to show its good performance.