• Journal of the Korean Geotechnical Society
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• v.36 no.6
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• pp.17-34
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• 2020

In response spectrum analysis of pile-supported structure, an amplified seismic wave should be used as the input ground acceleration through the site-response analysis. However, each design standard uses different input ground acceleration criteria, which leads to confusion in determining the appropriate input ground acceleration. In this study, the ground accelerations were calculated through dynamic centrifuge model test, and the response spectrum analysis was performed using the calculated ground acceleration. Then, the moments derived from the test and analysis were compared, and a method for determining the appropriate input ground acceleration in response spectrum analysis was presented. Comparison of the experimental and simulated results reveals that modeling of the ground using elastic springs allows proper simulation of the natural period of the structure, and the use of a seismic wave that is amplified at the ground surface as the input ground acceleration provided the most accurate results for the response analysis of pile-supported structures in sands.

• Journal of Food Hygiene and Safety
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• v.16 no.2
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• pp.103-110
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• 2001

Predictive food microbiology(PFM) is an emerging area of food microbiology since the later 1980’s. It does apply mathematical models to predict the responses of microorganism to specified environmental variables. Although, at present, PFM models do not completely developed, models can provide very useful information for microbiological responses in HACCP(Hazard Analysis Critical Control Point) system and Risk Assessment. This study illustrates the possible use of PFM models(PMP: Pathogen Modeling Program win5.1) with milk in several elements in the HACCP system, such as conduction of hazard analysis and determination of CCP(Critical Control Points) and CL(Critical Limits). The factors likely to affect the growth of the pathogens in milk involved storage fixed factors were pH 6.7, Aw 0.993 and NaCl 1.3%. PMPwin5.1 calculated generation time, lag phase duration, time to level of infective dose for pathogens across a range of storage (Critical Control Points) and CL(Critical Limits). The factors likely to affect the growth of the pathogens in milk involved storage temperature, pH, Aw and NaCl content. The factors likely to affect the growth of the pathogens in milk involved storage temperature, pH, Aw and NaCl content. The variable factor was storage temperature at the range of 4~15$^{\circ}C$ and the fixed factors were pH 6.7, Aw 0.993 and NaC 1.3%. PMPwin5.1 calculated generation time, lag phase duration, time to level of infective dose for pathogens across a range of storage temperature.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.77-86
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• 2020

Power quality problems caused by feeder voltage drop and extension construction cost problems can occur with the increasing utilization rates of the existing fixed-type EV (electric vehicle) charger. Moreover, EV users might not be able to access the EV charger due to a lack of EV charging facilities. Therefore, this paper proposes an MPSD (movable power supply device) for EVs to overcome user inconvenience caused by the insufficient number of chargers and extension cost issues. The proposed MPSD was mainly composed of a PV (photovoltaic) system, ESS (energy storage system), EV charging system, and monitoring and control system. Furthermore, there are three operation modes available to enhance the flexibility of the MPSD application, depending on the situation. This paper also presents an economical evaluation modeling using the present worth method to consider the cost and benefit elements. The simulation results based on proposed modeling showed that MPSD is more economical than the existing EV charger. Moreover, its profit can be increased significantly depending on the distance to the installation point.

• Progress in Medical Physics
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• v.21 no.3
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• pp.304-310
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• 2010

Less execution of the electron arc treatment could in large part be attributed to the lack of an adequate planning system. Unlike most linear accelerators providing the electron arc mode, no commercial planning systems for the electron arc plan are available at this time. In this work, with the expectation that an easily accessible planning system could promote electron arc therapy, a commercial planning system was commissioned and evaluated for the electron arc plan. For the electron arc plan with use of a Varian 21-EX, Pinnacle3 (ver. 7.4f), with an electron pencil beam algorithm, was commissioned in which the arc consisted of multiple static fields with a fixed beam opening. Film dosimetry and point measurements were executed for the evaluation of the computation. Beam modeling was not satisfactory with the calculation of lateral profiles. Contrary to good agreement within 1% of the calculated and measured depth profiles, the calculated lateral profiles showed underestimation compared with measurements, such that the distance-to-agreement (DTA) was 5.1 mm at a 50% dose level for 6 MeV and 6.7 mm for 12 MeV with similar results for the measured depths. Point and film measurements for the humanoid phantom revealed that the delivered dose was more than the calculation by approximately 10%. The electron arc plan, based on the pencil beam algorithm, provides qualitative information for the dose distribution. Dose verification before the treatment should be mandatory.