Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
권호 표지

Application of Dynamic Reliability Analysis Method to the CANDU Pressurizer System

  • Published : 1998.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

DYLAM (Dynamic Logical Analytical Methodology) and its related methodologies are reviewed and found to have many favorable characteristics. Previous studies have shown that the DYLAM methodology represents an appropriate tool to study dynamic analysis. A hybrid model which is a synthesis of the DYLAM model, a system thermodynamic simulation model and a neural network predicative model, is implemented and used to analyze dynamically the CANDU pressurizer system. This study demonstrates that the hybrid model for system reliability analyses is effective.

Keywords

References

  1. EUR 15266EN The DYLAM Approach for the Reliability Analysis of Systems with Dynamic Interactions G.Cojazzi;P.C. Cacciabue
  2. ISEI/IE 2502/93 A Human Factor Methodology for Safety Assesment based on the DYLAM Approach Cacciabue;G. Cojazzi
  3. Reliability Engineering and System Safety v.43 Risk Assessment for Dynamic System : An Overview N.Siu
  4. Nuc. Sci. and Eng. v.77 Event Sequences and Consequence Spectrum : A Methodology for Probabilistic Transient Analysis Amendola;G. Reina
  5. Reliability Engineering and System Safety v.22 Accident Sequence Dynamic Simulation versus Event Trees A.Amendola
  6. Practical Neural Network Recipe in $C^{++}$ Timothy Masters
  7. Ellis Horwood Workshops Techniques and Application of Neural Metwork Malcom Taylor;Paulo Lisboa
  8. Reliability Engineering and system safety v.36 Expanding the Scope of DYLAM Methodology to Study the Dynamic Reliability of Complex Systems : the case of chemical and volume control in nuclear power plants Cacciabue, A.Carpinano;C. Vivalda
  9. IEI/SET 2/92/92 DYLAM-3, A Dynamic methodology for Reliability Analysis and Consequences Evaluation Industrial Plant. Theory and How to use Cojazzi, G.;Cacciabue, P.C.;Parisi, P.
  10. ASCA Technical Paper Integrated Plant Management System Risk & Safety Management Consortium
  11. Application of neural networks to modeling and control G.F.Page, Gomm;D. Williams
  12. Artificial Intelligence, A Modern Approach Stuart Russel;Peter Norvig