Welding is the most widely used technology for manufacturing in the automobile, and shipbuilding industries. Fiber laser welding is rapidly introduced into the field to minimize welding distortion and fast welding speed. Although it is advantageous to use finite element analysis to predict welding distortion and find optimized welding conditions, there are various heat source model for fiber laser welding. In this study, a welding heat source was proposed using a multi-layered heat source model that encompasses most of the existing various welding heat source models: conical shape, curved model, exponential model, conical-cylindrical model, and conical-conical model. A case study was performed through finite element analysis using the radius of each layer and the ratio of heat energy of the layer as variables, and the variables were found by comparing them with the actual experimental results. For case study, by applying Adaptive simulated annealing, one of the global optimization algorithms, we were able to find the heat source model more efficiently.

Phenylethanol (PhE)에서 야기되는 피부 부작용 문제를 극복하기 위한 대안으로 phenylethanol galactoside (PhE-gal)에 대하여 연구하였다. 그 중에서도 대장균 효소 β-galalactosidase (β-gal)을 이용하여 PhE로부터 PhE-gal를 합성하는 반응의 최적 조건에 대하여 조사하였다. 그리고, 용매 분획연구를 수행하여 PhE-gal의 특성도 조사하였다. 반응조건 중에서 반응액의 β-gal 농도, PhE 농도, 반응액의 pH, 그리고 온도에 대하여 조사한 결과, 최적 β-gal의 농도는 0.45 U/ml, 최적 반응물 PhE의 농도는 1.0%, 최적 반응액의 pH는 8.0, 최적 반응온도는 40℃ 였다. 그리고, 최적 반응조건에서 48 시간까지의 반응을 관찰하였는데, 약 81.9 mM의 PhE로부터 약 47.4 mM의 PhE-gal이 합성되었고, PhE로부터 PhE-gal로의 전환수율은 약 57.9% 정도였다. 또한, PhE와 PhE-gal이 포함된 반응물을 용매 EA와 MC로 분획한 결과, 물 층으로 대부분의 PhE-gal이 분획 되었고, 용매 층으로는 PhE가 분획 되었다. 그러나, 물 층으로의 PhE-gal의 분획이 용매 MC를 사용할 때, 더 분명하고 명확하게 나타났으며, 용매 EA를 이용한 분획에서는 명확히 물 층으로 PhE-gal이 분획 되지 않았다. 앞으로, PhE-gal을 화장품에 사용할 수 있는 첨가물(방부제)로 개발하기 위한 후속연구를 계속 진행할 예정이다.

This paper describes a novel zero-stress member selecting method for sizing optimization of truss structures. When a sizing optimization method with static constraints is implemented, the member stresses are affected sensitively with changing the variables. However, because some truss members are unaffected by specific loading cases, zero-stress states are experienced by the elements. The zero-stress members could affect the computational cost and time of sizing optimization processes. Feature selection approaches can be then used to eliminate the zero-stress member from the whole variables prior to the process of optimization. Several numerical truss examples are tested using the proposed methods.

PURPOSES : The purpose of this study is to build an optimization model using the capacity and initial travel speed of the volume delay functions for network calibration performed in the traffic demand analysis process. METHODS : The optimization model contains an error term between the observed traffic volume and estimated traffic volume, based on the user equilibrium principle, and was constructed as a bi-level model by applying range constraints on capacity and travel time. In addition, we searched the split section to apply the method of adjusting the section instead of adjusting the single link. The optimization model is constructed by applying the warm-start method using the bush of the origin-based model so that parameter adjustment and traffic assignment are repeatedly executed within the model and the convergence of the model configured %RSSE. RESULTS : As a result of analysis using the toy network, the optimization model is that the observed traffic volume is estimated when there are no restrictions and, when the constraint conditions were set, the error with the observed traffic volume and error rate was significantly reduced. As a result of the comparative analysis of the trial-and-error methods, KTDB optimum values, and optimization models in empirical analysis using a large-scale network, the evaluation indexes (e.g., RMSE and %RMSE) were significantly improved by applying the optimization model. CONCLUSIONS : Based on the empirical analysis, the optimization model of this study can be applied to large-scale networks and it is expected that the efficiency and reliability of road network calibration will be improved by repeatedly performing parameter adjustment and traffic assignment within the model.

본 연구에서는 철골편심가새골조 시스템을 대상으로 다목적최적화기법을 통해 설계를 수행하고 그 결과를 분석하였다. 최적화 설 계를 위해 유전 알고리즘의 일종인 NSGA-II를 활용하였다. 여기서, 목적함수는 이율배반적 관계를 갖는 구조물량과 층간변위로 하여 최소화되고, 제약조건에는 구조기준에서 요구하는 내력비, 링크의 회전각 등을 포함하였다. 제약조건은 최적화 알고리즘 내에서 각 항목을 위반할수록 목적함수 값을 크게 증가시키는 벌금함수의 형태를 가지고 있다. 설계기준에서 EBF 시스템의 설계규정은 링크 부재만 항복이 허용되며 나머지 부재는 링크 항복 시 발생되는 부재력을 탄성상태에서 견디도록 의도한 역량설계법에 기초한다. 그러나 최적화를 통해 도출된 결과 중 일부는 구조기준의 설계조항은 만족하지만 특정층 링크에 소성변형이 집중되어 연약층을 형성함 으로써 기준에서 의도하는 역량설계의 원칙을 위배하는 결과가 나타났다. 이를 해결하기 위해 모든 링크의 전단 초과강도계수 중 최 대값이 최소값의 1.25배를 넘지 않도록 하는 제약식을 추가하였다. 새로운 제약식을 추가한 경우 모든 최적해는 설계기준과 역량설계의 원칙을 준수하는 것으로 나타났다. 모든 설계안에서 보 경간에 대한 링크의 길이비는 전단링크의 범주에 해당하는 10% ~ 14%였다. 전체적으로 설계안들은 링크의 초과강도 계수비가 가장 지배적인 제약으로 작용하였으며, 구조기준의 요구사항 중 층간변위와 내력비 등의 항목에서 허용치에 비해 매우 보수적으로 설계되었다.

본 연구에서 흰목이버섯의 추출조건별 추출수율과 기능성 성분의 함량을 비교하여 최적 추출조건을 분석하였으며, 모든 분석에서 R²이 0.9331~0.9462로 유의성을 보이는 것을 확인하였다. 각 독립변수에 따른 추출수율과 ergothioneine, β-glucan 성분을 분석한 결과 추출수율은 추출온도와 추출시료농도에 반비례했으며, 추출시간에는 큰 영향이 없었다. Ergothioneine 성분은 온도가 증가할수록 증가하며, 추출시간은 4.33 h가 가장 높았고 시료량에 큰 영향이 없었다. β-glucan 성분은 온도가 증가할수록 감소했으며, 추출시간에 큰 영향이 없었고 시료량이 21.2 mg/mL에서 가장 높았다. 모든 종속변수의 최대 독립변수는 온도 60 o C, 추출시간 4.33 h, 추출시료농도 16.6 mg/mL에서 추출수율 24.9%, ergothioneine 성분함량 66.8 ug/g, β-glucan 성분함량 34.9 g/100 g으로 나타났다.

생강의 기능성 소재화를 위해 흑생강을 제조함에 있어 숙성 조건 최적화를 위한 숙성 온도(75.0~90.0℃, X1)와 시간(18.0~72.0 hr, X2)을 독립변수로 하고 중심합성계획에 따른 11구간의 조건에서 제조된 흑생강의 이화학적 특성 및 항산화 활성을 측정하였다. 흑생강의 수율은 모든 조건에서 60% 이상이었다. 흑생강의 명도와 황색도, 6-shogaol, 총 페놀 및 플라보노이드 함량은 숙성 온도가 높고 시간이 길어질수록 증가되는 경향이었다. 특히 흑생강의 6-shogaol, 총 페놀 함량 및 항산화 활성은 90℃에서 45 hr 숙성 시 최대값을 보였다. 반응표면분석법에 의한 흑생강의 제조 시 예측된 최적 조건은 89.97℃ 및 21.60 시간이었으며, 실측값은 예측값의 92.7~101.6%의 범위였다.

With the spread of smart manufacturing, one of the key topics of the 4th industrial revolution, manufacturing systems are moving beyond automation to smartization using artificial intelligence. In particular, in the existing automatic machining, a number of machining defects and non-processing occur due to tool damage or severe wear, resulting in a decrease in productivity and an increase in quality defect rates. Therefore, it is important to measure and predict tool life. In this paper, v-ASVR (v-Asymmetric Support Vector Regression), which considers the asymmetry of є-tube and the asymmetry of penalties for data out of є-tube, was proposed and applied to the tool wear prediction problem. In the case of tool wear, if the predicted value of the tool wear amount is smaller than the actual value (under-estimation), product failure may occur due to tool damage or wear. Therefore, it can be said that v-ASVR is suitable because it is necessary to overestimate. It is shown that even when adjusting the asymmetry of є-tube and the asymmetry of penalties for data out of є-tube, the ratio of the number of data belonging to є-tube can be adjusted with v. Experiments are performed to compare the accuracy of various kernel functions such as linear, polynomial. RBF (radialbasis function), sigmoid, The best result isthe use of the RBF kernel in all cases

Human and material resource planning is one representative example of Operations Research. Resource planning is important not only in civilian settings but also in military ones. In the Air Force, flight scheduling is one of the primary issues that must be addressed by the personnel who are connected to flight missions. However, although the topic is of great importance, relatively few studies have attempted to resolve the problem on a scientific basis. Each flight squadron has its own scheduling officers who manually draw up the flight schedules each day. While mistakes may not occur while drafting schedules, officers may experience difficulties in systematically adjusting to them. To increase efficiency in this context, this study proposes a mathematical model based on a binary variable. This model automatically drafts flight schedules considering pilot’s mission efficiency. Furthermore, it also recommends that schedules be drawn up monthly and updated weekly, rather than being drafted from scratch each day. This will enable easier control when taking the various relevant factors into account. The model incorporates several parameters, such as matching of the main pilots and co-pilots, turn around time, availability of pilots and aircraft, monthly requirements of each flight mission, and maximum/minimum number of sorties that would be flown per week. The optimal solution to this model demonstrated an average improvement of nearly 47% compared with other feasible solutions.

The purpose of this study is to optimize the rice starch and rice protein content ratio for the replacement of fish paste in eomuk using a response surface methodology. The experiment was designed based on the independent variables. The rice starch content (X1: 10, 20, 30%) and rice protein content (X2: 1, 3, 5%) were examined, along with the viscosity (Y1), color (Y2: L, Y3: a, Y4: b), and sensory evaluation of the dough (Y5: Color, Y6: Flavor, Y7: Off flavor, Y8: Taste, Y9: Hardness, Y10: Cohesiveness, Y11: Springiness, Y12: Chewiness, Y13: Overall acceptance), with the results being set as dependent variables. The p value of Y1, Y2, Y5, Y7, Y9, Y10, Y11, Y12, and Y13 showed a level of <0.05 excluding Y6 and Y8. R2 value was high at 0.80-0.95 so that these rice starch and rice protein contents were significantly affected in terms of the quality and sensory preference of eomuk; therefore, the optimal conditions of X1 and X2 were 19.99% and 2.91%, respectively. Under these optimal conditions, the predicted values of acceptance were Y5 (5.44), Y7 (5.36), Y9 (5.22), Y10 (5.46), and Y13 (6.11). These results will be the basis for building a method for obtaining a rice material. Also, they are expected to promote rice consumption through the development of processed foods using rice material.

In this study, a model to optimize residual chlorine concentrations in a water supply system was developed using a multi-objective genetic algorithm. Moreover, to quantify the effects of optimized residual chlorine concentration management and to consider customer service requirements, this study developed indices to quantify the spatial and temporal distributions of residual chlorine concentration. Based on the results, the most economical operational method to manage booster chlorination was derived, which would supply water that satisfies the service level required by consumers, as well as the cost-effectiveness and operation requirements relevant to the service providers. A simulation model was then created based on an actual water supply system (i.e., the Multi-regional Water Supply W in Korea). Simulated optimizations were successful, evidencing that it is possible to meet the residual chlorine concentration demanded by consumers at a low cost.