Jae-Boong Choi

Qualitative RBI Analysis in Considered with Uncertain Variables by Probabilistic Distribution

Plants which are having conditions of high temperature and pressure always are exposed to danger. In order to prevent unexpected accidents, safety management that can effectively and appropriately examine facilities is required in plant operation. RBI(Risk-Based Inspection) technology in API 581 is one of standard management technique for evaluating risk on petroleum plants. There are qualitative and quantitative assessments in RBI methodology. Quantitative evaluation step is complex and required much information, so high-risk facilities in plant are selected firstly by qualitative method. Qualitative RBI is performed by choosing the answer in prepared questionnaire. However, it is difficult to believe thoroughly results from survey including ambiguous information. In this study, the procedure of qualitative RBI analysis with considering probability distribution concept were proposed by using Monte Carlo simulation method in order to increase reliability in spite of uncertain factors. In addition, qualitative risk of cooling system for LNG plant was evaluated using proposed procedure. Although 20 items of total 39 assessment items are applied to uncertain factors, risk section of high probability(89%) were verified. The detailed results were described in manuscript.

Development of Comfort Control Logic for VRF System in Summer Season by using 3 Environment Factors(Temperature, Humidity and Air flow)

This paper investigates the simplified comfort index and control logic for VRF (Variable Refrigerant Flow) system by using 3 environmental factors such as temperature, humidity and air flow. Indoor test under thermal load was conducted to explore relationship of each environment factors that is related to simplified comfort index. Simplified comfort function that has 3 environmental variables was proposed based on survey results. Each factor is measured and comfort preference was surveyed by more than 30 subjects in the indoor comfort test. Moreover, control logic for VRF system was developed and then simulated by using thermal load calculation method and verified with test. The proposed comfort function was in good agreement with survey results, and also verification test trend of comfort change and maintenance are quite similar with survey. Furthermore, through the additional test data analysis some differences of comfort according to position of people staying in the test room were additionally investigated by air flow. People being under an exit of air in the indoor air-conditioner feel more comfortable condition and speed of response to comfort change is relatively fast.