In September 2018, CRA Consultant Lavinia Raganelli attended PSAM14 in California. PSAM (Probabilistic Safety Assessment & Management ) is the largest international conference on risk and safety assessment and it is held biennially. PSAM14 was held at the new UCLA Luskin Conference Center in Los Angeles.
Lavinia presented two papers; the first one was “A method for inclusion of uncertainties in seismic PSA” which summarises some of the results from her PhD*. She also presented the paper “The Latest Thinking of SMRs Impact on the Environment – A Probabilistic Approach” which summarises the work conducted by her colleague Bernat Cirera and Imperial College students on level 3 PSA for SMRs in the last two years. Both papers were well received and generated interesting discussions.
For Lavinia the most interesting points from the conference, in her opinion, were:
• Idaho National Laboratory is running a project using Fault Tree (FT) and Event Tree (ET) analysis to quantify cyber risk
• Dynamic Probabilistic Risk Assessment (PRA) work has gained much traction in the United States. Dynamic PRA is being researched and developed further at Sandia National Laboratories, Idaho National Laboratory, Nuclear Regulatory Commission (NRC) and various Universities. However, there are still issues in trying to summarise the results of dynamic PRA analysis and provide insights comparable to those from classic PRA models.
• A few Human Reliability data collection exercises are being undertaken in the world (Korea, US, Norway) and a dynamic human reliability model was developed in the US.
• There is a lot of interest and discussion around human and system reliability for space missions as NASA is planning to go to Mars within 10 years (and it take 3 years to get to Mars!).
• New regulatory guidance is being developed at International Atomic Energy Agency (IAEA) on multiunit PSA and at ANS on low power and shutdown PSA. The Korean regulator is also working on guidelines for multiunit PSA.
*Lavinia undertook an Engineering Doctorate in Uncertainty modelling for seismic PSA