In this paper, several types of torque distribution functions (TDFs) are presented for the instantaneous torque control of switched reluctance motor (SRM) drives. To verify the feasibility and effectiveness of the proposed TDFs, two different categories—parameter non-adaptive and parameter adaptive functions—are introduced and analyzed. These different types of TDFs are systematically implemented in instantaneous torque control schemes to enhance the performance of SRM drives. The proposed torque control method, incorporating these various TDFs, is modeled and simulated in PSIM software to validate the presented control schemes. Simulation results demonstrate the effectiveness of the proposed approach in achieving precise torque control and improving the dynamic performance of SRM drives.

This study determined the minimum size of a representative molecular structure for use in future dynamic analyses of asphalt binders. The minimum representative size, considering factors such as aging, additive types, and temperature variations, was established using density and radial distribution functions. This approach ensures that the structure reflects temperature-dependent property changes, which are critical characteristics of asphalt binders. In this study, the structure of asphalt-binder molecules was generated using the composition proposed by Li and Greenfield (2014) for AAA1. To assess the appropriateness of the molecular structure size, we generated additional structures, X2 and X3, maintaining the same composition as X1, but with two and three times the number of molecules, respectively, as suggested by Li and Greenfield (2014). Silica and lignin were considered as additives, and the aging conditions examined included unaged, short-term aging, and long-term aging. In addition, 11 temperature conditions were investigated. The density and radial distribution functions were plotted and analyzed. The variables influencing the density and radial distribution functions were set as the aging degree of the asphalt binder (unaged, short-term aging, long-term aging), 11 temperature conditions ranging from 233 to 433 K in 20 K intervals, structure size (X1, X2, and X3), and the presence of additives (no additives, silica, and lignin). For density, clear differences were observed based on the degree of aging, temperature conditions, and presence of additives, whereas the structure size did not significantly affect the density. In terms of radial distribution functions, the X1 structure reflected differences based on the degree of aging and the presence of additives but was limited in exhibiting temperature-dependent variations. In contrast, the X3 structure effectively captured temperature-dependent trends, indicating that the size of the molecular structure is crucial when evaluating energy calculations or physical tensile strength, necessitating careful assessment.

In engineering problems, many random variables have correlation, and the correlation of input random variables has a great influence on reliability analysis results of the mechanical systems. However, correlated variables are often treated as independent variables or modeled by specific parametric joint distributions due to difficulty in modeling joint distributions. Especially, when there are insufficient correlated data, it becomes more difficult to correctly model the joint distribution. In this study, multivariate kernel density estimation with bounded data is proposed to estimate various types of joint distributions with highly nonlinearity. Since it combines given data with bounded data, which are generated from confidence intervals of uniform distribution parameters for given data, it is less sensitive to data quality and number of data. Thus, it yields conservative statistical modeling and reliability analysis results, and its performance is verified through statistical simulation and engineering examples.

본 연구의 목적은 선형, 쌍곡선, 베타 함수를 이용하여 상추의 주요 온도를 예측하기 위함이다. 상추 종자를 항온 생육상에서 발아시켰다. 온도처리는 10oC, 14oC, 16oC, 20oC, 24oC, 28oC와 32oC였다. 100개의 종자를 9cm 페트리디쉬에 필터페이퍼 2장을 깔고 4반복 실시하였다. 유근이 1mm 나왔을 때를 발아로 하였다. 시간에 따른 발아율은 로지스틱 함수로 계산하였다. 최저, 최적, 최고 온도는 50% 발아한 시점의 역수를 온도에 따른 함수로 표기하여 나타내었다. 선형 함수의 경우, 최저, 최적, 최고 온도는 각각 7.9oC, 23.3oC, 28.0oC였으며, 쌍곡선 함수의 경우, 최저, 최적, 최고 온도는 각각 9.7oC, 19.5oC, 29.4oC였으며, 베타 함수인 경우, 최저, 최적, 최고 온도 는 각각 3.7oC, 20.7oC, 32.0oC였다. 최저, 최적, 최고 온도 범위는 각각 3.7~7.9oC, 19.5~23.3oC, 28.0~32.0oC이었다.

본 논문에서는 소형 해상 부유체의 위기 평가를 위한 확률기반 위기평가기법(PET)에서 표본 데이터에 최적인 누적분포함수(CDF) 추정에 관한 평가절차와 실험결과를 기술하였다. CDF는 PET에서 부유체의 위기수준을 평가하기 위한 위기허용기준의 참조 값을 제공하기 위한 것으로, 부유체 모델의 롤(Roll), 피치(pitch), 히브(Heave) 등의 운동응답함수에 대한 표본 데이터에서 추정할 수 있다. 본 연구에서는 여덟가지 정형화된 분포함수와 최대우도추정기법을 적용하여 표본 데이터에 대해서 최대우도를 갖는 CDF들을 평가하였다. 분포함수들의 적합도 검정 실험을 통해서, 베타 분포가 롤과 피치 표본 데이터에 대해서 평균 확률오차 δ(0≤δ≤1.0)가 가장 작은 0.024와 0.022로 최적임을 나타냈고, 히브 표본 데이터에 대해서는 감마 분포가 δ가 가장 작은 0.027로 최적임을 나타냈다. 본 연구에서 제안한 방법은 표본 데이터의 최적분포 추정을 위한 다양한 분야에 적용 가능할 것으로 기대된다.