A Decision Support System for the Off-Site Emergency Protective Actions Based on the OILs for Nuclear Emergencies

Author(s):  
YongSheng Ling

Deterministic health effects can be prevented and the risk of stochastic health effects can be reduced by taking protective actions before or shortly after a release. These actions must be based on plant conditions and then refined subsequently based on environmental measurements. Operational intervention levels (OILs) are some calculated values (e.g., ambient dose rate or radionuclide concentration) measured by instruments or determined by laboratory analysis that correspond to a GIL or GAL. Through the use of the OILs, the environmental data are assessed primarily, which are quantities directly measured by the field instrument. Default OILs have been calculated in advance on the basis of the characteristics of severe reactor accidents. These default OILs are used to assess environmental data and take protective actions until sufficient environmental samples are taken and analyzed to provide a basis for their revision. This approach allows data to be quickly evaluated, and decisions on protective actions to be promptly made. A decision support system of the off-site emergency protective actions based on the OILs for nuclear emergencies was discussed in this paper. The system accesses the environmental data through the default OILs and the revisions of OILs. It is applied to Daya Bay Nuclear Power Plant. In the early release, according to the characteristic of the plant, the system provides the approach to calculate the default OILs based on the accident source terms described in Reactor Safety Study of USA. Also some real factors are considered, including the meteorological parameters. When sufficient environmental samples are taken and analyzed to provide a basis for their revision, the default OILs can be revised or recalculated by them. In the entire emergency planning zone, the environmental data will be assessed through the use of those OILs to provide the advice of protective measures.

2014 ◽  
pp. 124-130
Author(s):  
Miki Sirola ◽  
Golan Lampi ◽  
Jukka Parviainen

Computerized decision support system field covers many methodologies and application areas. In this paper Self-Organizing Map (SOM) and knowledge-based techniques are used in combination to reason problematic situations in failure management. A process model that consists of individual connected process components has been developed. A primary circuit of a boiling water nuclear power plant including two branches has been composed. A failure management scenario is thoroughly analyzed and solved with the SOM based decision support system. The structure and reasoning of the Computerized Decision Support System (CDSS) is also shortly discussed. The process model is demonstrated together with the CDSS and shown to be useful. The tool helps operators decision making with various visualizations, and by giving concrete recommendations for possible control actions or other acts.


Author(s):  
Jan B. de Jonge ◽  
Onno A. J. Peters

While shipping large and heavy cargo like jack-up rigs or semi-submersibles, the Motion Monitoring and Captain Decision Support system is a valuable tool to ensure a safe and economical voyage. Using the dynamic characteristics of the vessel, in combination with 5-day weather forecasts and design limits like maximum accelerations at the cargo location, roll motion and/or leg bending moments, more and better information is available to the Master to choose safe route, heading and speed. This way the best knowledge of what to expect is contributing to the safety of cargo, vessel and crew. The Octopus onboard system gathers a large amount of information about ship position, speed, heading, nowcast weather data and corresponding ship motion data. Reference is made to the paper of Peters [2] for background information of the Octopus Motion Monitoring and Decision Support system and an overview of methods used by the motion measurement system. In May 2008 the first Dockwise vessel started to gather weather and ship motion data. It is estimated that each vessel gathers around 50.000 nautical miles of data in a year, which is all collected in a database. The paper presents how this information is used for general research to environmental data, ship motion data and comparison to design values. Scatter diagrams from nowcast weather data can be produced. After collecting a certain amount of measurements, so called Dockwise scatter diagrams could be used as input for future voyage calculations. With this engineering approach Masters decisions for weather routing and bad weather avoidance is taken into account. This could lead for example to reduced design wave for a passage around the Cape of Good Hope. Now casted weather data and ship motions data is compared to design values from the cargo securing manual. Statistics like maximum difference, average difference give extensive data and insight in the operational margin of Dockwise transports. The calculation of the operational margin is independent of the standard safety margin valid for each transport. The conclusion is that the recorded nowcast significant wave height for the analyzed voyages never exceeded 5.0 [m]. With larger design wave heights the minimum operational margin increases to more than 40%, while the lowest operational margin occurs at design wave heights around 4.5 [m]. The database built by gathering all relevant information from the system and from crew observations, increases insight in the operational margins, which contributes to increased knowledge and safety.


2012 ◽  
Vol 249 ◽  
pp. 413-418 ◽  
Author(s):  
Min-Han Hsieh ◽  
Sheue-Ling Hwang ◽  
Kang-Hong Liu ◽  
Sheau-Farn Max Liang ◽  
Chang-Fu Chuang

Author(s):  
Fernanda Bruno dos Santos ◽  
Ana Carolina Gama e Silva Assaife ◽  
Marcos Roberto da Silva Borges ◽  
Jose Orlando Gomes ◽  
Paulo Victor Rodigues de Carvalho

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