Lloyd's Register, SSM to improve emergency response tool

20 January 2015


Lloyd's Register Consulting is partnering with the Swedish Radiation Safety Authority (SSM) to enhance the source term prediction software RASTEP and support the decision-making process for emergency response.

RASTEP (RApid Source TErm Prediction) is a diagnosis tool to aid decision-making during accidents at nuclear power plants. It helps operators understand potential probabilities of issues happening given a set of conditions. This output is essential for an operator's offsite emergency response planning process, Lloyd's Register says.

By improving the way the questions are organised and the detail in the graphical illustrations, the improvements will provide better clarity on decision making for nuclear operators, and help to inform on predicted or likely consequences. This will enable improved offsite emergency response initiatives for industry and better protect the public.

Head of reactor technology and analysis at SSM, Annelie Bergman, said the Swedish regulator has had a long and fruitful experience working with Lloyd's Register Consulting to achieve a tool that will allow quicker and more efficient emergency management at SSM in case of a nuclear accident.

"In an emergency situation, SSM's advice is important for decision makers at the county administrative boards which decide on the right measures to protect the population," she added.

The need for improving accident diagnosis tools and forecasting likely scenarios was asserted by the Fukushima disaster. It has led to a greater focus on strengthening the nuclear industry's Defence in Depth (DiD) safety philosophy. Lloyd's Register said that the joint-industry partnership aims to enhance the application of 'Level 5' DiD which provides guidelines for mitigating the consequences of radioactive material release through appropriate offsite emergency response.

The project, which was launched this month, is scheduled for completion by August 2015.


Photo: The Fukushima accident highlighted the need to improve accident diagnosis tools



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