نقاط قوت و ضعف روش ها برای تجزیه و تحلیل سیستم های هسته ای نوآورانه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|27976||2007||8 صفحه PDF||سفارش دهید||4270 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Nuclear Engineering and Design, Volume 237, Issue 9, May 2007, Pages 988–995
At present nuclear energy is in a transition situation. New efforts are being used trying to find the way to build more nuclear power. As the nuclear energy is an inherently multivariable system, the potential judgment at the ends tends to evolve towards multi criteria analysis methodologies trying to analyze innovative nuclear systems for the future. Nuclear energy has been an active energy player starting 50 years ago, and several times big efforts have been used trying to evaluate the potential of future development of nuclear energy depending on future scenarios using multi criteria analysis methods. Without the intention to be performed an assessment about what finally happens in the evolution of nuclear technology, performing only factual comparison and using only data available in the 1950s, in this work is analyzed if multi criteria analysis methods is sufficient to predict the final success of the currently available well-established commercial reactors. The conclusion is that if uncertainties are not included, the classical multi criteria methodologies evaluated could not be used to predict the successful deployment of PWR, BWR and CANDU, with the status of knowledge of 1956, and without including others factors and external non numerical judgment. Uncertainties produce compatible results with the further historical evolution, but if they have to be included with large margins and as a penalty in the figures of merit.
At present nuclear energy is in a transition situation, established as an excellent energy generator of reactors already built (Chinworth et al., 2001). New efforts are being used trying to find the way to build more nuclear power plants (NPP) with the exception of few countries. Options to introduce the so-called advanced design by short-term incentives (University of Chicago, 2004) until reach fully scale economy on these designs are explored. Several initiatives have been launched trying to analyze innovative nuclear systems (INS) for the future, particularly the US-led generation IV international forum (GIF) (DOE, 2002), and the IAEA's international project on innovative nuclear reactors and fuel cycles (INPRO) (IAEA, 2003). As the nuclear energy is an inherently multivariable system, with many aspects to be considered, the potential judgment at the ends tends to evolve towards multi criteria analysis methodologies (Saaty, 1990). As an example, INPRO considered six main criteria (or dimensions) for aggregation, called economy, safety, environment, sustainability, waste management, proliferation resistance and cross cutting issues. Such types of methodologies are intended to be used to discriminate between the different INS in order to detect options, for R&D funding for example. But nuclear energy has been an active energy player starting 50 years ago (IAEA, 2004), and several times big efforts has been used trying to evaluate the potential of future development of nuclear energy depending on future scenarios. Particularly in the conferences of atoms for peace in Geneva (United Nations, 1955, United Nations, 1958 and United Nations, 1964) in the 1950s and early 1960s, and international fuel cycle evaluation programme (INFCE) at IAEA headquarters in the 1970s (IAEA, 1980). At that time many forecast energy modeling were used. Different strategies to deploy different reactors concepts were proposed, and usually the advantages and disadvantages of the different options to fulfill for future energy needs were evaluated. But it is well known that many nuclear promises at the end were never realized, at least as was originally expected (Cohn, 1997). Then new questions could be done in the perspective of past experience. Could multi criteria analysis methods (Saaty, 1990) alone reproduce what happened in the last 25–50 years, if they are applied with the data available in the past? This question is relevant not because the future will be a copy of the past, it is because if a methodology could not be enough robust to understand 25–50 years of past history, how could be expected to project what could happened in the next 50–100 years? Usually numerical evaluation is taken as primary input to system selection, and additional factors and judgment were also usually included too in the selection process. But then is very clear that the prediction capacity could be improved or worsted depending on the quality of the strategic view behind this others factors and judgment. If it is very difficult with quantitative methods, more challenging could be with external judgment. At the end a robust forecast assessment methodology is one in which the errors are not unacceptably amplified in time, in which the independent variables are not cross correlated, etc. And the past history could be used to test the proposed methodologies, not to claim that this is a sufficient condition to assess the future, but such type of robustness history check is a necessary condition for such methodologies to be useful and credible at least as a minimum starting point. Then this assessment is not to study what finally happens in the last 50 years in nuclear energy, but to perform a factual analysis of the perspective of the different technologies on the past. Then the limitation of this approach is that could not be used to predict what's will happened with the assessment methods, and is limited to the robustness of present numerical methods to past history. We must emphasize the influence of the previous knowledge of the history of the power industry in the analysis with the proposed methodology. As an example an accident as the Chernobyl (a LWGR, the worst accident in nuclear power history) cannot be appointed for the present analysis.
نتیجه گیری انگلیسی
With the scope about to perform only a factual check of the prediction capacity of numerical evaluation methods, could be concluded that if uncertainties are not included, the classical multi criteria methodologies evaluated could not be used to predict the successful deployment of PWR, BWR and CANDU, with the status of knowledge of 1956. Uncertainties produce compatible results with the further historical evolution, but if they have to be included with large margins and as a penalty in the figures of merit. The results of this type of methodologies have shown that with proper evaluation of uncertainties the weight is valid in a range that could go from 10% up to 40%. The validity range could be large but could show coupling between variables: if there is some bias in one direction for one particular dimension, the other dimensions need to change in some particular direction to compensate the others, if the validity range is not large enough. The results shows than the uncertainties can correct some surprising figure (e.g. economy for organic reactors) but further studies are required to demonstrate the validity of such conclusion for others initial data (taken from open literature). Is very clear that there are other real issues were not considered in the 1950s (e.g. public acceptance) or weights that cannot be easily considered (e.g. the role of “lobbying”), but the objective was to perform a factual check of historic consistency of numerical evaluation methods alone. This type of historical check could not be used to predict future evolution, but could be used to select different methodologies, looking for methodologies in which the tolerance limits are less coupled, and to use methodologies less dependant on the different bias that could be involuntary introduced by the evaluators or experts. The lessons learned on the nuclear technology looks general enough to be useful for other technologies, but the only way to be sure if the conclusions are valid for other systems, is to check for other technologies very different from nuclear, for example less innovative options or low capital–high variable cost energy alternatives.