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Earthquakes, Tsunamis and Nuclear Risks: Prediction and Assessment Beyond the Fukushima Accident

Earthquakes, Tsunamis and Nuclear Risks: Prediction and Assessment Beyond the Fukushima Accident

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This book covers seismic probabilistic risk assessment (S-PRA) and related studies which have become more important to increase the safety of nuclear facilities against earthquakes and tsunamis in the face of the many uncertainties after the Fukushima accident. The topics are (1) Active faults and active tectonics important for seismic hazard assessment of nuclear facilities,(2) Seismic source modeling and simulation and modeling techniques indispensable for strong ground motion prediction, and (3) PRA with external hazard and risk communication. The Fukushima accident has showed us the limitations of the deterministic evaluation approach to external events (an earthquake and tsunami) in which there are many uncertainties. Furthermore, public anxiety regarding nuclear safety because of an unexpected threat caused by an earthquake or tsunami is growing. The current policy on the estimation of the design basis of ground motion as well as tsunami height still has not been improved following the Fukushima accident. In particular, the risk concept in a nuclear system regarding seismic motion and a tsunami beyond the design basis is indispensable. Therefore, research and development for PRA enhancing nuclear safety are being actively pursued not only in Japan but also worldwide. This book provides an opportunity for readers to consider the future direction of nuclear safety vis-à-vis natural disasters.

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This work has been downloaded 137 times via unglue.it ebook links.
  1. 27 - pdf (CC BY-NC) at OAPEN Library.
  2. 31 - mobi (CC BY-NC) at Unglue.it.
  3. 37 - pdf (CC BY-NC) at Unglue.it.
  4. 42 - epub (CC BY-NC) at Unglue.it.

Keywords

  • Active fault
  • Earthquake source modeling
  • Environmental management
  • Natural disasters
  • Nuclear risk communication
  • Nuclear uncertainty
  • PRA
  • Probabilistic risk assessment
  • Strong ground motion prediction
  • The environment

Links

DOI: 10.1007/978-4-431-55822-4
web: https://link.springer.com/book/10.1007/978-4-431-55822-4

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