• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.7
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• pp.679-688
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• 2010

The major objective of the present study is to extend the applications of inverse analysis to more realistic engineering fields with a complex combustion process rather than the traditional simple heat-transfer problems. In order to do this, the unknown initial mass fractions of $CH_4/O_2$ are estimated from the temperature measurement data by inverse analysis in the practical diffusion-controlled turbulent combustion problem. In order to ensure efficient inverse analysis, the repulsive particle swarm optimization (RPSO) method, which belongs to the class of stochastic evolutionary global optimization methods, is implemented as an inverse solver. Based on this study, it is expected that useful information can be obtained when inverse analysis is used in the diagnosis, design, or optimization of real combustion systems involving unknown parameters.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.397-402
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• 2013

In super-tall building construction projects, schedule risk factors which vertically change and are not found in the low and middle-rise building construction influence duration of a project by vertical attribute; and it makes hard to estimate activity or overall duration of a construction project. However, the existing duration estimating methods, that are based on quantity and productivity assuming activities of the same work item have the same risk and duration regardless of operation space, are not able to consider the schedule risk factors which change by the altitude of operation space. Therefore, in order to advance accuracy of duration estimation of super-tall building projects, the degree of changes of these risk factors according to altitude should be analyzed and incorporated into a duration estimating method. This research proposes a simulation model using Monte Carlo method for estimating activity duration incorporating schedule risk factors by weather conditions in a super-tall building. The research process is as follows. Firstly, the schedule risk factors in super-tall building are identified through literature and expert reviews, and occurrence of non-working days at high altitude by weather condition is identified as one of the critical schedule risk factors. Secondly, a calculating method of the vertical distributions of the weather factors such as temperature and wind speed is analyzed through literature reviews. Then, a probability distribution of the weather factors is developed using the weather database of the past decade. Thirdly, a simulation model and algorithms for estimating non-working days and duration of each activity is developed using Monte-Carlo method. Finally, sensitivity analysis and a case study are carried out for the validation of the proposed model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.3
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• pp.124-131
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• 2012

This study was carried out to evaluate a possible change in freeze risk for 'Changhowon Hwangdo' peach buds in three major peach growing areas under the future climate projected by RCP8.5 emission scenario. Mean values of the monthly temperature data for the present decade (2000s) and the future decades (2020s, 2050s, 2080s) were extracted for farm lands in Icheon, Chungju, and Yeongcheon-Gyeongsan region at 1km resolution and 30 sets of daily temperature data were generated randomly by a stochastic process for each decade. The daily data were used to calculate a thermal time-based dormancy depth index which is closely related to the cold tolerance of peach buds. Combined with daily minimum temperature, dormancy depth can be used to estimate the potential risk of freezing damage on peach buds. When the freeze risk was calculated daily for the winter period (from 1 November to 15 March) in the present decade, Icheon and Chungju regions had high values across the whole period, but Yeongcheon-Gyeongsan regions had low values from mid-December to the end of January. In the future decades, the frequency of freezing damage would be reduced in all 3 regions and the reduction rate could be as high as 75 to 90% by 2080's. However, the severe class risk (over 80% damage) will not disappear in the future and most occurrences will be limited to December to early January according to the calculation. This phenomenon might be explained by shortened cold hardiness period caused by winter warming as well as sudden cold waves resulting from the higher inter-annual climate variability projected by the RCP8.5 scenario.