[en] An outline is presented of the Italian fusion theoretical and experimental research program being carried out at CNEN-Euratom in Frascati, CNR-Euratom in Milan, and CNR-Euratom in Padua. (U.K.)

[en] In a previous work, constrained regression has been applied in order to estimate both the accuracy and the precision of a scale system, under the condition of a constant systematic bias model. The present work approaches the problem of the robustness of such estimator with respect to a possible unadequacy of the model. The consideration of both procedures, the unconstrained and the constrained ones, leads to an estimator, which improves the estimate and is more robust in singling out the aberrant scales

[en] Two main aspects have to be taken into account in studying a nuclear accident scenario when using nuclear safety codes as an information source. The first one concerns the behavior of the code response and the set of assumptions to be introduced for its modelling. The second one is connected with the uncertainty features of the code input, often modelled as a probability density function (pdf). The analyst can apply two well-defined approaches depending on whether he wants major emphasis put on either of the aspects. Response Surface Methodology uses polynomial and inverse polynomial models together with the theory of experimental design, expressly developed for the identification procedure. It constitutes a well-established body of techniques able to cover a wide spectrum of requirements, when the first aspect plays the crucial role in the definition of the objectives. Other techniques such as Latin hypercube sampling, stratified sampling or even random sampling can fit better, when the second aspect affects the reliability of the analysis. The ultimate goal for both approaches is the selection of the variable, i.e. the identification of the code input variables most effective on the output and the uncertainty propagation, i.e. the assessment of the pdf to be attributed to the code response. The main aim of this work is to present a sensitivity analysis method, already tested on a real case, sufficiently flexible to be applied in both approaches mentioned

[en] A simulation study of a PWR station black-out ATWS has been performed by applying Response Surface Methodology (RSM) on the data obtained by inspecting the ALMOD code. The case under study has shown that the a priori information which alone could be inadequate, is optimally utilized if coupled with a preliminary sensitivity analysis through RSM techniques. In particular the engineering selection of the model variables and the rank order of the remaining ones had to be modified after an RSM preliminary sensitivity analysis. An other qualifying feature of the exercise is the use of randomization of the variables not included in the model in order to coherently exploit the methodology in its full efficiency. This procedure is able to give a figure of merit of the global importance of the neglected variables through the analysis of residuals. Results show that the proposed technique is an effective tool for selecting the most important accident variables and that the body of information gained is significant with respect to the number of observations performed

[en] A simulation study of a station black-out ATWS has been performed by applying Response Surface Methodology (RSM) on the data obtained by inspecting the ALMOD code. The case under study has shown that the a priori information which alone could be inadequate, is optimally utilized if coupled with a preliminary sensitivity analysis through RSM techniques. In particular the engineering selection of the model variables and the rank order of the remaining ones had to be modified after an RSM preliminary sensitivity analysis. Another qualifying feature of the exercise is the use of the randomization of the variables not included in the model in order to coherently exploit the methodology in its full efficiency. This procedure is able to give a figure of merit of the global importance of the neglected variables through the analysis of residuals. Results show that the proposed technique is an effective tool for selecting the most important accident variables and that the body of information gained is significant with respect to the number of observations performed. (orig.)

[en] A reliable evaluation of fuel temperature is a key safety requirement in the design of the fuel assembly of a nuclear reactor, especially in the case of a LMFBR whose efficient operation requires high thermal performance fuel. The physico-chemical properties such as density, oxygen to metal ratio and thermal conductivity of a typical LMFBR mixed-oxide fuel, which are known to change in a remarkable way under irradiation, strongly affect the temperature profile within the fuel pellet. A statistical analysis of the temperature values in the fuel of the Italian Fast Reactor PEC, has been performed by means of the RSM code (Response Surface Methodology) coupled to a Monte-Carlo Technique (MUP code), in order to demonstrate that the melting risk is substantially negligible. (orig.)