risk monitor
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2021 ◽  
Author(s):  
Yuhang Zhang ◽  
Zhijian Zhang ◽  
He Wang ◽  
Lixuan Zhang ◽  
Dabin Sun

Abstract To ensure nuclear safety and prevent or mitigate the consequences of accidents, many safety systems have been set up in nuclear power plants to limit the consequences of accidents. Even though technical specifications based on deterministic safety analysis are applied to avoid serious accidents, they are too poor to handle multi-device managements compared with configuration risk management which computes risks in nuclear power plants based on probabilistic safety assessment according to on-going configurations. In general, there are two methodologies employed in configuration risk management: living probabilistic safety assessment (LPSA) and risk monitor (RM). And average reliability databases during a time of interest are employed in living probabilistic safety assessment, which may be naturally applied to make long-term or regular management projects. While transient risk databases are involved in risk monitor to measure transient risks in nuclear power plants, which may be more appropriate to monitor the real-time risks in nuclear power plants and provide scientific real-time suggestions to operators compared with living probabilistic safety assessment. And this paper concentrates on the applications and developments of living probabilistic safety assessment and risk monitor which are the mainly foundation of the configuration risk management to manage nuclear power plants within safe threshold and avoid serious accidents.


2021 ◽  
Vol 208 ◽  
pp. 107403
Author(s):  
D. Ferretto ◽  
G. Mazzini ◽  
W. Ambrosini ◽  
R. Aldorf ◽  
M. Hrehor

2021 ◽  
Vol 53 (1) ◽  
pp. 103-110
Author(s):  
Bing Zhang ◽  
Shanqi Chen ◽  
Zhixian Lin ◽  
Shaoxuan Wang ◽  
Zhen Wang ◽  
...  

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
B Naghavi ◽  
A Alizadehasl ◽  
P Sadeghipour ◽  
J Moosavi ◽  
O Shafe ◽  
...  

Abstract Background Post-pulmonary emboli impairment (PPEI), comprised significant morbidity and mortality. A single center registry of patients with PE was established in order to estimate patients' risk, monitor clinical management and develop a simple model to assess the risk for PPEI for the entire spectrum of patients treated in general clinical practice. Methods For developing the mentioned model, apart from approved imaging parameters, potential novel imaging parameters were also evaluated. Recovery were assessed according to Pulmonary Embolism Thrombolysis (PEITHO) trial definition (Figure 1). Results 140 patients have been registered with at least 6-month imaging follow up. PPEI was confirmed in 75 (53.6%) patients with PE. The prognostic value of traditional and novel imaging parameters on 6-month complete recovery were summarized in Table. A multivariable logistic regression model was developed using 140 patients. Previous PE, HRfollowing five in-hospital-parameters accounted for simple prognostic model for incomplete recovery: history of PE, heart rate≥110, serum blood urea nitrogen level, RV/LV ratio and right atrium area, The overall prediction ability was excellent with 80.6 overall percentage for PPEI. Conclusions PPPEI rate was considerable in our study. Our proposed simple prediction model might have a role on identification of patients at risk for PPEI. Figure 1 Funding Acknowledgement Type of funding source: None


Author(s):  
Yingfei Ma ◽  
Zhijian Zhang ◽  
He Wang ◽  
Sijuan Chen ◽  
Anqi Xu ◽  
...  

Reliability data works as the basis of risk monitor of nuclear power plant. The failure modes of the equipment in a nuclear power plant can be divided into operation failure, demand failure and standby failure. A standby equipment is affected by the demand stress and the standby stress simultaneously, so the method of reliability data analysis must consider the two types of failure. The reliability data in online risk monitor should reflect the change of equipment reliability with time, including standby equipment. A method to deal with the reliability data of the standby equipment is presented in this paper. This model takes into account the failure of the equipment during the spare time and the failure of the starting time. Considering the characteristics of the reliability data in the nuclear power plant, the method of parameter estimation is studied. Finally, this method is applied to online risk monitor in nuclear power plant and the suggestion of reliability data application is put forward.


2017 ◽  
Vol 54 (5) ◽  
pp. 552-568 ◽  
Author(s):  
Zhanguo Ma ◽  
Hidekazu Yoshikawa ◽  
Takashi Nakagawa ◽  
Ming Yang

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