• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.1-2
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• 2011

Hybrid rockets have lately attracted attention as a strong candidate of small, low cost, safe and reliable launch vehicles. A significant topic is that the first commercially sponsored space ship, SpaceShipOne vehicle chose a hybrid rocket. The main factors for the choice were safety of operation, system cost, quick turnaround, and thrust termination. In Japan, five universities including Hokkaido University and three private companies organized "Hybrid Rocket Research Group" from 1998 to 2002. Their main purpose was to downsize the cost and scale of rocket experiments. In 2002, UNISEC (University Space Engineering Consortium) and HASTIC (Hokkaido Aerospace Science and Technology Incubation Center) took over the educational and R&D rocket activities respectively and the research group dissolved. In 2008, JAXA/ISAS and eleven universities formed "Hybrid Rocket Research Working Group" as a subcommittee of the Steering Committee for Space Engineering in ISAS. Their goal is to demonstrate technical feasibility of lowcost and high frequency launches of nano/micro satellites into sun-synchronous orbits. Hybrid rockets use a combination of solid and liquid propellants. Usually the fuel is in a solid phase. A serious problem of hybrid rockets is the low regression rate of the solid fuel. In single port hybrids the low regression rate below 1 mm/s causes large L/D exceeding a hundred and small fuel loading ratio falling below 0.3. Multi-port hybrids are a typical solution to solve this problem. However, this solution is not the mainstream in Japan. Another approach is to use high regression rate fuels. For example, a fuel regression rate of 4 mm/s decreases L/D to around 10 and increases the loading ratio to around 0.75. Liquefying fuels such as paraffins are strong candidates for high regression fuels and subject of active research in Japan too. Nakagawa et al. in Tokai University employed EVA (Ethylene Vinyl Acetate) to modify viscosity of paraffin based fuels and investigated the effect of viscosity on regression rates. Wada et al. in Akita University employed LTP (Low melting ThermoPlastic) as another candidate of liquefying fuels and demonstrated high regression rates comparable to paraffin fuels. Hori et al. in JAXA/ISAS employed glycidylazide-poly(ethylene glycol) (GAP-PEG) copolymers as high regression rate fuels and modified the combustion characteristics by changing the PEG mixing ratio. Regression rate improvement by changing internal ballistics is another stream of research. The author proposed a new fuel configuration named "CAMUI" in 1998. CAMUI comes from an abbreviation of "cascaded multistage impinging-jet" meaning the distinctive flow field. A CAMUI type fuel grain consists of several cylindrical fuel blocks with two ports in axial direction. The port alignment shifts 90 degrees with each other to make jets out of ports impinge on the upstream end face of the downstream fuel block, resulting in intense heat transfer to the fuel. Yuasa et al. in Tokyo Metropolitan University employed swirling injection method and improved regression rates more than three times higher. However, regression rate distribution along the axis is not uniform due to the decay of the swirl strength. Aso et al. in Kyushu University employed multi-swirl injection to solve this problem. Combinations of swirling injection and paraffin based fuel have been tried and some results show very high regression rates exceeding ten times of conventional one. High fuel regression rates by new fuel, new internal ballistics, or combination of them require faster fuel-oxidizer mixing to maintain combustion efficiency. Nakagawa et al. succeeded to improve combustion efficiency of a paraffin-based fuel from 77% to 96% by a baffle plate. Another effective approach some researchers are trying is to use an aft-chamber to increase residence time. Better understanding of the new flow fields is necessary to reveal basic mechanisms of regression enhancement. Yuasa et al. visualized the combustion field in a swirling injection type motor. Nakagawa et al. observed boundary layer combustion of wax-based fuels. To understand detailed flow structures in swirling flow type hybrids, Sawada et al. (Tohoku Univ.), Teramoto et al. (Univ. of Tokyo), Shimada et al. (ISAS), and Tsuboi et al. (Kyushu Inst. Tech.) are trying to simulate the flow field numerically. Main challenges are turbulent reaction, stiffness due to low Mach number flow, fuel regression model, and other non-steady phenomena. Oshima et al. in Hokkaido University simulated CAMUI type flow fields and discussed correspondence relation between regression distribution of a burning surface and the vortex structure over the surface.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.