• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.141-147
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• 2024

In this study, micro CT images were used to confirm the tensile fracture strength according to the pore distribution characteristics of 3D printed concrete. Unlike general specimens, concrete structures printed by 3D printing techniques have the direction of pores (voids) depending on the stacking direction and the presence of filaments contact surfaces. Accordingly, the pore distribution of 3D printed concrete specimens was analyzed through quantitative and qualitative methods, and the tensile strength by direction was analyzed through a finite element technique. It was confirmed that the pores inside the 3D printed specimen had directionality, resulting in their anisotropic behavior. This study aims to analyze the characteristics of 3D concrete printing specimen and correlate them with simulation-based mechanical properties to improve performance of 3D printed material and structure.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.175-175
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• 2018

우리나라에서 발생하는 대규모 자연재해의 상당부분은 강우에 의한 홍수피해이다. 최근 이러한 홍수피해는 기후변화와 더불어 극한강우 현상의 빈발에 의한 새로운 재해양상으로 전개되고 있으며, 이에 따라 정부에서도 재해발생시 원상복구의 개념이 아닌 항구복구의 개념으로 복구사업을 수행하고 있다. 그러나 설계에 기후변화에 대한 영향을 반영하고 있지 못하기 때문에 기후변화에 의하여 미래에 발생할 극한강우로 반복적인 피해가 예상되고 있으므로 기존의 방재성능목표 강우량의 설정 방법에 대한 개선이 필요하다. 전 세계적으로 이러한 기후변화에 의한 현상을 모의하기 위한 연구로 전지구기후모델(Global Climate Model, 이하 GCM)과 지역기후모델(Reginal Climate Model, 이하 RCM)을 사용하고 있다.우리나라 기상청에서도 CMIP5 국제사업의 표준 실험체계를 통해 전지구 기후변화 시나리오 산출을 위해서 영국 기상청 해들리센터의 GCM인 HadGEM2-AO를 도입하였다. 또한 한반도 기후변화 시나리오를 산출하기 위해 HadGEM3-RA 모형을 이용하여 전지구 기후변화 시나리오를 역학적으로 상세화하고 이를 한반도에 대해 12.5km 공간 해상도로 일 자료를 제공하고 있다. 하지만 유역규모 혹은 지점규모에서 사용하기 위해서는 이러한 일자료의 시 공간적인 상세화기법이 요구된다. 본 연구에서는 기후변화를 고려한 방재성능목표 강우량 개선 방향을 제안하기 위해 다양한 연구단에서 도출된 상세화 결과를 수집하고 비교분석을 통해 기후변화를 고려하고자 하였다. 다양한 연구기관에서 생산된 미래 확률 전망을 살펴본 결과, 동일한 GCM자료를 사용하더라도 상세화 방법론에 따라 서로 다른 결과가 도출되는 것을 확인하였다. 미래 예측의 불확실성을 고려하면 특정한 방법론이 우수하다고 평가하기는 어려움에 따라 앙상블 평균을 활용한 개선방향을 제안한다. 본 연구의 결과는 전국 지자체의 강우특성만을 고려한 것으로, 연안지역의 경우 해수면 상승을 고려하여 추가적인 대책이 필요할 것으로 판단된다.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.13 no.1
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• pp.63-72
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• 2015

The low and intermediate-level radioactive waste generated in Korea is disposed of at Wolsong Disposal Facility. For the safety of a disposal facility, it must be assessed by considering some abnormal scenarios including human intrusion as well as those by natural phenomena. The human intrusion scenario is a scenario that an incognizant man of the disposal facility will be occurred by the drilling. In this paper, the well usage scenario was classified into the human intrusion event as the probability of the well drilling is very low during the man's lifecycle and then was assessed by using conservative assumptions. This scenario was assessed using the dilution factor of contaminants released from a disposal facility and then it was introduced the applied methodology in this study. The assessed scenario using this methodology is satisfied the regulatory limits.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.29-39
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• 2012

The main objective is to predict the future degradation and maintenance budget for a suspension bridge system. Bayesian inference is applied to find the posterior probability density function of the source parameters (damage indices and serviceability), given ten years of maintenance data. The posterior distribution of the parameters is sampled using a Markov chain Monte Carlo method. The simulated risk prediction for decreased serviceability conditions are posterior distributions based on prior distribution and likelihood of data updated from annual maintenance tasks. Compared with conventional linear prediction model, the proposed quadratic model provides highly improved convergence and closeness to measured data in terms of serviceability, risky factors, and maintenance budget for bridge components, which allows forecasting a future performance and financial management of complex infrastructures based on the proposed quadratic stochastic regression model.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.173-184
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• 2023

Presently, the general seismic fragility evaluation method for a bridge system composed of member elements with different nonlinear behaviors against strong earthquakes has been to evaluate at the element-level. This study aims to develop a system-level seismic fragility evaluation method that represents a structural system. Because the seismic behavior of bridges is generally divided into transverse and longitudinal directions, this study evaluated the system-level seismic fragility in both directions separately. The element-level seismic fragility evaluation in the longitudinal direction was performed for piers, bridge bearings, pounding, abutments, and unseating. Because pounding, abutment, and unseating do not affect the transverse directional damages, the element-level seismic fragility evaluation was limited to piers and bridge bearings. Seismic analysis using nonlinear models of various structural members was performed using the OpenSEES program. System-level seismic fragility was evaluated assuming that damage between element-levels was serially connected. Pier damage was identified to have a dominant effect on system-level seismic fragility than other element-level damages. In other words, the most vulnerable element-level seismic fragility has the most dominant effect on the system-level seismic fragility.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.293-293
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• 2021

자연유량이란 인위적 행위에 의한 하천의 유량 변화가 없는 개발되지 않은 상태의 하천유량을 말하며, 실제 유량을 측정하거나 관측자료를 활용한 장기유출모형을 통해 산정할 수 있다. 미계측 유역에 대한 강우-유출 모형 구축시, 무엇보다 실제 미계측유역에 적용시 나타날 수 있는 문제점을 최소화할 수 있는 방향으로 모형 개발이 이루어지는 것이 필요하다. 강우-유출 모형 매개변수의 수가 많아질수록 과적합(over-fitting)의 발생 소지가 증가하게 되며, 지역화 모형 구축시 불확실성을 더욱 가중시키게 된다. 이러한 이유로, 모형의 검정보다는 검증에 초점이 맞춰져 있어야 하며, 더불어 사용되는 강우-유출 모형의 매개변수가 적어야 한다. 본 연구에서는 대표 강우-유출모형의 선정시 여러 평가 기준 중 예측의 정확성 측면에서 통계적 지표를 통해 모형의 수행능력에 중점을 두었으며, 적은 개수의 매개변수를 갖음에도 불구하고 상대적 우수한 모의결과를 제공하는 GR4J(Ge'nie Rural a 4 parame tres Journalier)모형을 최적 유출모형으로 선정하여 댐 상류유역에 대한 자연유량 재현성능을 평가하였다. 최종적으로 강우-유출모형의 최적매개변수와 유역특성인자 사이의 상호연관성을 고려해 매개변수를 지역화하기 위하여, 본 연구에서는 두 가지 이상의 변량에 대한 상관성을 효과적으로 재현하는데 효과적이며, 자유로운 주변확률분포 선택과 결합확률분포의 추정이 용이한 장점이 있는 Copula 함수를 활용하였다. 제시된 방법론에 대한 적합성을 평가하기 위해 교차검증 관점에서 지역화된 매개변수의 적합성을 검토하였으며, 본 연구에서 도출된 결과는 유역특성에 따른 미계측유역의 자연유량 산정시 지역 매개변수를 강우-유출모형에 활용함으로써 신뢰성 있는 자연유량 산정 결과를 제공할 수 있을 것으로 판단된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.592-599
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• 2015

In big data environment, we need new approach for big data analysis, because the characteristics of big data, such as volume, variety, and velocity, can analyze entire data for inferring population. But traditional methods of statistics were focused on small data called random sample extracted from population. So, the classical analyses based on statistics are not suitable to big data analysis. To solve this problem, we propose an approach to efficient big data analysis. In this paper, we consider a big data analysis using principal component analysis, which is popular method in multivariate statistics. To verify the performance of our research, we carry out diverse simulation studies.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1586-1593
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• 2010

Vocabulary recognition error correction method has probabilistic pattern matting and dynamic pattern matting. In it's a sentences to based on key-word by semantic analysis. Therefore it has problem with key-word not semantic analysis for morphological changes shape. Recognition rate improve of vocabulary unrecognized reduced this paper is propose. In syllable restoration algorithm find out semantic of a phoneme recognized by a phoneme semantic analysis process. Using to sentences restoration that morphological analysis and morphological analysis. Find out error correction rate using phoneme likelihood and confidence for system parse. When vocabulary recognition perform error correction for error proved vocabulary. system performance comparison as a result of recognition improve represent 2.0% by method using error pattern learning and error pattern matting, vocabulary mean pattern base on method.

• Journal of Korean Society for Quality Management
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• v.41 no.1
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• pp.135-148
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• 2013

Purpose: This paper presents a method to evaluate the stockpile reliability of propelling charge for performance and storage safety with storage time. Methods: We consider a performance failure level is the amount of muzzle velocity drop which is the maximum allowed standard deviation multiplied by 6. The lifetime for performance is estimated by non-linear regression analysis. The state failure level is assumed that the content of stabilizer is below 0.2%. Because the degradation of stabilizer with storage time has both distribution of state and distribution of lifetime, it must be evaluated by stochastic process method such as gamma process. Results: It is estimated that the lifetime for performance is 59 years. The state distribution at each storage time can be shown from probability density function of degradation. It is estimated that the average lifetime as $B_{50}$ life is 33 years from cumulative failure distribution function curve. Conclusion: The lifetime for storage safety is shorter than for performance and we must consider both the lifetime for storage safety and the lifetime performance because of variation of degradation rate.