• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2003년도 추계 학술발표회논문집
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• pp.344-351
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• 2003

In order to consider the characteristics of nonlinear dynamic responses of seismic isolated bridges reasonably, piers and isolators are modeled as a 2-DOF bilinear system. Then nonlinear time-history earthquake response analysis is accomplished many artificial input ground motions which were generated to reflect the characteristics of earthquakes. Damage probabilities and failure probabilities of each structural elements of the brides are calculated by using Monte-Carlo simulation method. Based on LCC evaluation considering various cost items of direct/indirect damage costs, the optimal design method of seismic isolated bridges is proposed. By using a sensitivity analysis about the design variables and a cost effectiveness evaluation in the viewpoint of LCC, the validity and the adequacy of proposed optimal design method are verified.

• 한국지진공학회논문집
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• 제28권4호
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• pp.215-222
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• 2024

Many older reinforced concrete (RC) buildings were constructed and designed with only gravity loads in mind. Columns in those buildings have insufficient reinforcement details that do not satisfy the requirements specified in current seismic design standards. This study aims to develop drift-based fragility functions for lightly RC columns. For this purpose, a database of 193 lightly RC columns was constructed to determine central and dispersion values of drift ratios for individual damage states. Additionally, to develop more accurate fragility functions of the columns, the failure mode of RC columns was incorporated into fragility functions. The classification procedure for column failure mode is proposed in this study. Fragility functions for older RC columns are constructed according to four different damage states. The main variables of the fragility functions proposed in this study are column properties and failure mode.

• 대한토목학회논문집
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• 제33권3호
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• pp.1007-1015
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• 2013

하중 발생과정에 따른 누적피해의 선형뿐만 아니라 비선형 거동을 해석할 수 있는 추계학적 확률모형이 수립되었다. 여러 종류의 피해강도함수를 도입하여 내용년수의 파괴확률과 비선형 누적피해의 거동이 자세히 해석되었다. 특히 본 연구에서는 저항한계를 임의의 분포함수를 갖는 확률변수로 취급하여 한계상태의 불확실성을 고려하였다. 또한 피복재에 대한 피해수준을 이용하여 처음으로 추계학적 확률모형을 경사제에 적용하였다. 실험 자료와의 비교를 통해 추정된 경사제 피복재에 대해 피해강도함수를 이용하여 내용년수에 따른 파괴확률과 비선형 누적피해의 거동을 해석하였다. 마지막으로 해석 결과를 이용하여 경사제 피복재의 보수 보강 시점과 최소한의 보수 보강규모를 정량적으로 산정할 수 있는 예방적 유지관리 방법을 제시하였다.

• 한국수자원학회논문집
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• 제44권1호
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• pp.1-8
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• 2011

본 연구는 패널자료(15개 시도의 20년간 자료)를 이용하여 홍수피해 비용과 복구비와의 상관관계에 대한 분석을 시도하였다. 패널 분석은 자료의 성격에 따라 고정효과모형 또는 확률효과모형을 사용하지만 본 분석은 두 모형을 함께 추정하였다. 예상대로 모든 변수들은 복구비와 정의 상관관계를 보였지만 사망자수와 이재민 수는 유의하지 않거나 오히려 음의 상관관계를 보이기도 하였다. 그리고 공공시설의 피해가 가장 중요한 인자였다. 무엇보다 중요한 것은 우리나라의 경우 복구비가 피해액이나 투자액에 비해 항상 높다는 것이다. 우리나라와는 반대로 일본의 경우 복구비가 가장 낮고 투자비가 가장 높다는 점을 미루어 볼 때 결국 적절한 투자가 향후 홍수피해는 물론 복구비도 낮출 수 있다는 점을 확인할 수 있었다.

• 한국수자원학회논문집
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• 제51권spc1호
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• pp.1149-1159
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• 2018

본 연구는 우리나라 113개 중권역에 대한 기후변화에 따른 미래 홍수 피해액의 예측을 위하여 26개 GCM 모형에서 생산한 강우자료와 1시간 최대 강수량, 10분 최대 강수량, 1일 강수량이 80 mm 초과한 일수, 일 최대 강수량, 연강수량, 유역고도, 시가화율, 인구 밀도, 자산 밀도, 도로와 같은 사회 간접 시설, 하천개수율, 하수도 보급률, 배수펌프시설, 유수지용량 및 과거 홍수 피해액 자료를 활용하였다. 구축된 자료에 대하여 구속 다중선형회귀 모형(Constrained Multiple Linear Regression Model)을 적용하여 홍수 피해액과 여타 입력자료 사이의 상관관계를 구축하고 RCP 4.5와 8.5에 대한 26개 GCM 모형 산정자료를 활용하여 미래 홍수 피해액을 예측하였다. 홍수피해에 주된 요인이 되는 연강수량, 극치 강우량 등 강우관련 요소들이 전반적으로 증가하며 이로 인하여 과거 홍수로 인한 피해액이 광범위하게 증가할 것으로 판단되고 특히 동해안 및 남강댐 유역에 미래의 홍수피해액이 높게 예측되는 경향을 보인다.

• Human Ecology Research
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• 제53권6호
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• pp.655-665
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• 2015

This study classified respondents by food-lifestyle and investigated differences in diet-related attitudes and demographic variables among food-lifestyle groups. Diet-related attitudes consisted of variables such as interest in diet, trial number of diet, diet period, weight loss, diet motivation, verification of products approved by the Ministry of Food and Drug Safety, verification of manufacturer's reliability, examination of damage cases and side effects, and awareness of consumer protection law. This study administered a questionnaire survey to adults between the ages of 20 and 39 who lived in Daegu and Uijeongbu from November 17th to December 14th 2014. Data collected from 293 respondents were analyzed using descriptive statistics, factor analyses, cluster analysis, analysis of variance (ANOVA) and chi-square tests. Four clusters (passive eating habit group, active eating habit group, convenience oriented group, and taste and health oriented group) were developed according to four factors of food-lifestyle (health-conscious, popularity-seeking, taste-seeking, convenience-seeking). The results of the ANOVA and chi-square tests indicated significant differences in interest in diet, awareness of consumer protection law, verification of products approved by the Ministry of Food and Drug Safety, verification of manufacturer's reliability, examination of damage cases and side effects, gender, education levels and household monthly income levels among food-lifestyle groups.

• 한국인공지능학회지
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• 제10권1호
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• pp.1-7
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• 2022

In this paper, a study was conducted to predict natural disasters in Afghanistan based on machine learning. Natural disasters need to be prepared not only in Korea but also in other vulnerable countries. Every year in Afghanistan, natural disasters(snow, earthquake, drought, flood) cause property and casualties. We decided to conduct research on this phenomenon because we thought that the damage would be small if we were to prepare for it. The Azure Machine Learning Studio used in the study has the advantage of being more visible and easier to use than other Machine Learning tools. Decision Forest is a model for classifying into decision tree types. Decision forest enables intuitive analysis as a model that is easy to analyze results and presents key variables and separation criteria. Also, since it is a nonparametric model, it is free to assume (normality, independence, equal dispersion) required by the statistical model. Finally, linear/non-linear relationships can be searched considering interactions between variables. Therefore, the study used decision forest. The study found that overall accuracy was 89 percent and average accuracy was 97 percent. Although the results of the experiment showed a little high accuracy, items with low natural disaster frequency were less accurate due to lack of learning. By learning and complementing more data, overall accuracy can be improved, and damage can be reduced by predicting natural disasters.

• 대한간호학회지
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• 제53권4호
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• pp.480-495
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• 2023

Purpose: This study aimed to develop and test a structural equation model on social re-adjustment of individuals with stroke based on a literature review and Roy's adaptation model. Methods: This study involved 321 participants who had a stroke and visited the outpatient department after discharge. The hypothetical model was developed based on Roy's adaptation model and a comprehensive review of previous literature on the topic. The model comprised four exogenous variables (neurological damage, gender [man], age, and social support) and five endogenous variables (activities of daily living, acceptance of disability, depression, rehabilitation motivation, and social re-adjustment). The data were analyzed using SPSS Windows software version 22.0 and AMOS 23.0. Results: Out of 28 research hypotheses, 18 were supported, and they indicated approximately 64% probability of social re-adjustment. Social re-adjustment is directly and significantly affected by age, social support, activities of daily living, and depression. Social re-adjustment is indirectly affected by neurological impairment, gender (men), age, social support, and rehabilitation motivation. Conclusion: Continuous assistance and care should be provided for individuals with disabilities caused by sudden neurological damage to facilitate gradual improvement in their social re-adjustment. To enhance social re-adjustment, especially among older adults, newly developed interventions should focus on improving their activities of daily living, preventing depression, and enhancing support from family and healthcare personnel.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.307-312
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• 2008

Local damage may cause sequential collapse of structure, which is called progressive collapse. Current progressive collapse analysis is based on the mean value of design variables. This deterministic approach has a low reliability as it doesn't consider uncertainty of variables. In this study the sensitivity of design variables for progressive collapse of structure is evaluated by Monte Calro simulation and Tornado diagram. The analysis results show that the behaviour of model structures is highly sensitive to variation of the yield force of beams and the structural damping ratio.

• Smart Structures and Systems
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• 제22권5호
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.