• 대한기계학회논문집
• /
• 제13권5호
• /
• pp.1032-1043
• /
• 1989

본 연구에서는 해석적으로 열적 입구 길이를 규명하는데 필요한 와류 열확산 계수를 실험 결과를 이용하여 결정하고, 시험관 입구의 형상 변화가 열전달 특성에 미치는 영향을 실험적으로 결정하며, 열적 입구 길이 영역에서 국소 열전달 계수를 표시할 수 있는 실험식을 제시하고, 유체의 전단율에 따른 점성 계수의 실험 결과와 점탄성 유체의 특성시간을 이용한 새로운 무차원 수인 Weissenberg수를 결정하여 퇴화 현상을 분석하고저 한다.

• Nuclear Engineering and Technology
• /
• 제53권8호
• /
• pp.2534-2546
• /
• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.