연안 해상 바람 자원 평가에 적용되는 해상풍 위성자료 동화특성을 평가하기 위하여 수치실험을 실시하였다. 사용된 위성자료는 미항공우주국의 QuikSCAT과 유럽우주국의 ASCAT이다. 해상풍 위성자료 동화과정은 연안지역 바람 자원 평가의 정확성을 향상시키는 주요한 요소의 하나이다. QuikSCAT의 관측 가능한 빔폭이 상대적으로 넓기 때문에 QuikSCAT 해상풍 자료를 동화하여 제시된 연안 바람장이 ASCAT를 사용한 바람장보다 약간 높은 정확도를 제시한다. 그러나 센서의 직하 부근의 바람장은 상대적으로 ASCAT의 예측 정확도가 높게 나타난다. 이러한 해상풍 위성자료의 동화효과는 6시간 정도 지속되기 때문에 정확한 연안지역 바람장을 평가하기 위해서는 센서의 공간해상도뿐 아니라 시간해상도가 높은 해상풍 위성자료 동화 과정이 필요하다.

국가적으로 개발도상국 국제협력 지원이 추진되고 있으며, 특히 해양안전 분야에서도 교육훈련 및 정보체계 개발지원이 이루어지고 있다. 국제협력 시 적용되는 해양안전 정보시스템은 수원국에서 생산되는 해양안전정보 처리가 가능하여야 하고, 수원국에서 개발된 시스템 간의 정보 교환이 원활해야 한다는 특징이 있다. 따라서 해양안전정보 시스템은 국제수로기구에서 제정한 범용수로데이터모델 기반의 시스템 구축이 반드시 필요하다. 본 연구에서는 국제수로기구에서 개발한 범용수로데이터 모델인 S-100 표준과 범용수로데이터 모델의 운용절차에 대해 분석하였다. 또한 범용수로데이터모델의 해양안전 분야 국제협력 사례로 유출유 대응시스템에 적용하여 전자해도 기반의 유출유 대응시스템을 개발하였으며, 범용수로데이터모델의 해양안전 분야 적용 결과를 고찰 하였다.

포장의 동결깊이는 30년간의 기온자료를 분석하여 만든 동결지수를 근거로 하여 동상방지층의 두께를 결정한다. 본 연구에서의 현장계측 지역은 동결지수에 따라 동결지수 550~650℃·일, 450~550℃·일, 350~450℃·일로 구분하여 지역을 선정하였고, 각 지역별로 절토부, 절성경계부, 저성토부(2m 이하 성토부) 구간으로 단면을 구분하였다. 각 단면에 동상방지층 유 무를 구분하여 포장층별로 계측기(온도, 함수비)를 설치하고 데이터를 수집하였다. 현장 모니터링 시스템을 통하여 수집된 데이터 분석을 통하여 포장된 도로의 동결깊이를 결정하는데 이용할 수 있다. 연구 결과, 동상방지층이 없을 경우 동결지수 550~650℃·일 지역에서는 대기온도에 따라 겨울철 노상층의 온도가 0℃ 이하로 나타났고, 동결지수 450~550℃·일 지역에서는 지역별로 상이했으며, 동결지수 350~450℃·일 지역에서는 동상방지층이 없어도 노상층의 온도가 0℃ 이하로 나타나지 않았다. 또한, 포장 단면별로 동결깊이를 비교한 결과 대기온도에 따라 동결깊이는 절토부가 가장 높았으며, 절성경계부, 저성토부 순으로 단면별 차이가 나타났다.

국가적으로 개발도상국으로의 국제협력에 관한 투자가 이루어지고 있으며, 해사안전을 위해 우리나라의 발전된 정보통신 기술을 접 목한 해양안전 정보 분야에 관한 지원도 수행되고 있다. 해양안전정보는 지도 상에 표시되어 사용자의 의사결정을 지원하고 있으며 일반적으로 유사 전자해도가 사용되고 있다. 해사 분야의 사용자들은 선박에서 사용되는 공인 전자해도에 친숙하기 때문에 해양안전분야의 국제협력 사업 추진을 위해서는 전자해도 기반의 시스템 구축이 요구된다. 전자해도에 해양안전정보 등의 부가정보를 추가하기 위해서는 수로데이터 모델 기 반의 시스템 구축이 요구되며, 이를 통해 전자해도 뿐만 아니라 다양한 해양안전 정보를 중첩할 수 있다. 본 연구에서는 해양안전정보 분야 중 유출유사고대응시스템에 전자해도를 적용하기 위해 수로데이터 모델에 관한 표준을 분석하고 뷰어 프로그램을 개발하였으며, 본 프로그램을 기 반으로 한 환경민감정보 표현 방안을 제안 하였다.

RAM(Reliability, Availability, Maintainability) is important performance factor to keep combat readiness and optimize operational and maintenance cost of weapon systems. This paper discusses the method to establish RAM for combat readiness by using field

Models are useful tools for understanding and improving biological control of arthropod pests by means of natural enemies. Thus, models can be applied to simulate various scenarios in order to identify optimal control strategies. Although simulations can never replace real experiments, they can often serve as guidelines for choosing relevant field experiments and thereby save a lot of laborious and costly field work. Whereas the processes underlying population dynamics (e.g. dispersal, functional response, mutual interference) can be studied under laboratory conditions, large-scaled experiments in the field or in greenhouses are unsuited for this purpose. Instead such experiments may provide information about the patterns (e.g. spatial distributions of prey and predators) generated by the underlying processes. A major purpose of modeling is to link the patterns to the processes that generate these patterns. Petri-dish and single plant experiments have clearly demonstrated the capacity of predacious mite Phytoseiulus persimilis to feed effectively on the two-spotted spider mite Tetranychus urticae. This quickly leads to reductions in the abundance of prey, followed by a decline in predator abundance and eventual extinction. However, when larger systems, consisting of many hundred plants, are infested with the two mite species, extinction of one or both species seems less likely at the system level, although it may still occur at the individual plant level. The qualitative difference between small and large systems with respect to persistence and extinction risks is attributed to the fact that mites move among plants, but to prove that dispersal per se plays a role for the overall dynamics is hard to demonstrate experimentally. To circumvent this problem, I developed a stochastic simulation model of a greenhouse system that explicitly incorporates within and between plant dynamics. The model is used for analyzing a series of experiments with biological control of spider mites in multi-plant systems. In these experiments, the number of plants as well as their connectivity and the numbers of introduced mites were varied in order to examine whether these factors affect e.g. the predator-prey ratio or the time to extinction of one or both species. In my presentation I will also demonstrate an interactive version of the model (called DynaMite). It allows the user to interfere in the system during a simulation so as to mimic the options a grower has in order to prevent losses and to maximize his profit. Such options include spraying with acaricides, releasing predators, and replanting in substitute of damaged plants. By choosing different control strategies, the user may gradually improve his skills according to the principle of learning by experience. The model can be freely downloaded from http://www1.bio.ku.dk/ansatte/beskrivelse/?id=43077

This paper shows application guide of dependability data from the field, life cycle costing, and maintainability. Moreover, this study introduces mathematical expressions and predictions for reliability, availability and maintainability. This paper also shows compliance test procedures for steady-state availability, and application of Markov techniques.

Field data have been recorded as the time to failure or the number of failure of systems. We consider the time to failure and covariate variables in some pre-specified follow-up or warranty period. This paper aims to investigate study on the reliability estimation when some additional field data can be collected within-warranty period or after-warranty period. A various likelihood-based methods are outlined and examined for exponential or Weibull distribution.

This paper is concerned with the method of estimating lifetime distribution for field data in warranty period and for a situation where some additional field data can be gathered after the warranty period. Implementing the proposed methods in this paper will result in obtaining the more precise product life time estimation and product improvement.

Because of the small number of spacecraft available in the Earth’s magnetosphere at any given time, it is not possible to obtain direct measurements of the fundamental quantities, such as the magnetic field and plasma density, with a spatial coverage necessary for studying, global magnetospheric phenomena. In such cases, empirical as well as physics-based models are proven to be extremely valuable. This requires not only having high fidelity and high accuracy models, but also knowing the weakness and strength of such models. In this study, we assess the accuracy of the widely used Tsyganenko magnetic field models, T96, T01, and T04, by comparing the calculated magnetic field with the ones measured in-situ by the GOES satellites during geomagnetically disturbed times. We first set the baseline accuracy of the models from a data-model comparison during the intervals of geomagnetically quiet times. During quiet times, we find that all three models exhibit a systematic error of about 10% in the magnetic field magnitude, while the error in the field vector direction is on average less than 1%. We then assess the model accuracy by a data-model comparison during twelve geomagnetic storm events. We find that the errors in both the magnitude and the direction are well maintained at the quiet-time level throughout the storm phase, except during the main phase of the storms in which the largest error can reach 15% on average, and exceed well over 70% in the worst case. Interestingly, the largest error occurs not at the Dst minimum but 2–3 hours before the minimum. Finally, the T96 model has consistently underperformed compared to the other models, likely due to the lack of computation for the effects of ring current. However, the T96 and T01 models are accurate enough for most of the time except for highly disturbed periods.

In this study, a batch least square estimator that utilizes optical observation data is developed and utilized to determine geostationary orbits (GEO). Through numerical simulations, the effects of error sources, such as clock errors, measurement noise, and the a priori state error, are analyzed. The actual optical tracking data of a GEO satellite, the Communication, Ocean and Meteorological Satellite (COMS), provided by the optical wide-field patrol network (OWL-Net) is used with the developed batch filter for orbit determination. The accuracy of the determined orbit is evaluated by comparison with two-line elements (TLE) and confirmed as proper for the continuous monitoring of GEO objects. Also, the measurement residuals are converged to several arcseconds, corresponding to the OWL-Net performance. Based on these analyses, it is verified that the independent operation of electro-optic space surveillance systems is possible, and the ephemerides of space objects can be obtained.

In this study, prototype DAU with LoRa wireless communication module is designed and manufactured. Also, the customized software is developed for the automatic data transmission to end-user from ThingPlug server of SK telecom LoRa network. For verification of the developed wireless monitoring system, DAU was installed on bridge construction site. The reliability of data and operational stability was evaluated by comparison with data from conventional monitoring system.

The Optical Wide-field patroL-Network (OWL-Net) is a global optical network for Space Situational Awareness in Korea. The primary operational goal of the OWL-Net is to track Low Earth Orbit (LEO) satellites operated by Korea and to monitor the Geostationary Earth Orbit (GEO) region near the Korean peninsula. To obtain dense measurements on LEO tracking, the chopper system was adopted in the OWL-Net’s back-end system. Dozens of angle-only measurements can be obtained for a single shot with the observation mode for LEO tracking. In previous work, the reduction process of the LEO tracking data was presented, along with the mechanical specification of the back-end system of the OWL-Net. In this research, we describe an integrity assessment method of time-position matching and verification of results from real observations of LEO satellites. The change rate of the angle of each streak in the shot was checked to assess the results of the matching process. The time error due to the chopper rotation motion was corrected after re-matching of time and position. The corrected measurements were compared with the simulated observation data, which were taken from the Consolidated Prediction File from the International Laser Ranging Service. The comparison results are presented in the In-track and Cross-track frame.

Recently, measurement monitoring is actively used for safety management of facilities. However, since the field measurement data contains many outliers, a preprocessing process is required for reliable behavior analysis of the data. In this paper, we present a detection method of time series outliers and its applications. And we propose precautions for the preprocessing process.