Advertisement

Atomic Energy

, Volume 102, Issue 5, pp 395–401 | Cite as

Economics and nuclear weapons nonproliferation in nuclear power development scenarios

  • A. N. Rumyantsev
Article
  • 87 Downloads

Abstract

The method of quantile estimates of uncertainties is used to forecast the economic indices of objects of nuclear power and to analyze the uncertainties of the predicted estimates of the balance of nuclear materials and the most likely scenarios of nuclear weapons proliferation taking account of the salient aspects of the initial nuclear materials. It is shown that methods of numerical simulation that do not have evaluated intervals of determination of the physical parameters or an evaluated variance of the results do not contribute any additional information about the objects and processes being studied. It is concluded that the future development of nuclear power in our country requires state regulation of the fuel and energy complex and proliferation risk reduction requires decreasing access to and use of low-enrichment uranium, and the adoption of mixed uranium-plutonium-thorium fuel cycles.

Keywords

Uranium Plutonium Nuclear Power Plant Fuel Assembly Fuel Cycle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    N. N. Ponomarev-Stepnoi, V. V. Kuznetsov, A. Yu. Gagarinskii, et al., “The future of nuclear power: energy, ecology, safety,” At. Énerg., 93, No. 4, 327–342 (2002).Google Scholar
  2. 2.
    A. N. Rumyantsev and Yu. A. Ostroumov, “Method of quantile estimates of uncertainties in the analysis of the frequencies, development, and consequences of rare and low-probability accident events,” IAÉ im. I. V. Kurchatova Report No. 210.06-04/11 (1993).Google Scholar
  3. 3.
    A. N. Rumyantsev and Yu. A. Ostroumov, “Method of quantile estimates of uncertainties in the analysis of the frequencies, development, and consequences of rare and low-probability accident events,” Preprint IAÉ-6295/15 (2003).Google Scholar
  4. 4.
    A. N. Rumyantsev, “Forecasting the development of nuclear power and analysis of the uncertainties in the predicted estimates,” Preprint IAÉ-6296/15 (2003).Google Scholar
  5. 5.
    Ya. V. Shevelev, Normative Economic Theory of Socialism, Ékonomika, Moscow (1991).Google Scholar
  6. 6.
    C. Woelfel, The Desktop Encyclopedia of Corporate Finance & Accounting, Probus Publishing Co., Illinois (1987).Google Scholar
  7. 7.
    S. Shtants and M. Repa, “System for observing the accuracy and reliability of measurements of the temperature in VVÉR-440,” At. Énerg., 93, No. 2, 97–101 (2002).Google Scholar
  8. 8.
    V. B. Glebov, G. G. Kulikov, V. V. Khromov, et al., “Calculation of the sensitivity of reactor characteristics to constants taking account of the change in the nuclide composition of the reactor during a fuel run,” Vopr. At. Nauk. Tekh., Ser. Fiz. Yad. Reakt., No. 1, 11–17 (1991).Google Scholar
  9. 9.
    V. Sukhoruchkin, N. Ponomarev-Stepnoi, A. Rumyantsev, et al., “A new look at metrics for proliferation distance,” in: Proceedings of the INMM 41st Annual Meeting, New Orleans, Louisiana, USA (2000).Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2007

Authors and Affiliations

  • A. N. Rumyantsev
    • 1
  1. 1.Russian Science Center Kurchatov InstituteRussia

Personalised recommendations