The REVE (REactor for Virtual Experiments) project is an international joint effort aimed at developing multiscale modelling computational toolboxes capable of simulating the behaviour of materials under irradiation at different time and length scales. Well grounded numerical techniques such as molecular dynamics (MD) and Monte Carlo (MC) algorithms, as well as rate equation (RE) and dislocation-defect interaction theory, form the basis on which the project is built. The goal is to put together a suite of integrated codes capable of deducing the changes in macroscopic properties starting from a detailed simulation of the microstructural changes produced by irradiation in materials. To achieve this objective, several European laboratories are closely collaborating, while exchanging data with American and Japanese laboratories currently pursuing similar approaches. The material chosen for the first phase of this project is reactor pressure vessel (RPV) steel, the target macrosocopic magnitude to be predicted being the yield strenght increase (Δσy) due, essentially, to irradiation-enhanced formation of intragranular solute atom precipitates or clouds, as well as irradiation induced defects in the matrix, such as point defect clusters and dislocation loops. A description of the methodological approach used in the project and its current state is given in the paper. The development of the simulation tools requires a continuous feedback from ad hoc experimental data. In the framework of the REVE project SCK·CEN has therefore performed a neutron irradiation campaign of model alloys of growing complexity (from pure Fe to binary and ternary systems and a real RPV steel) in the Belgian test reactor BR2 and is currently carrying on the subsequent materials characterisation using its hot cell facilities. The paper gives the details of this experimental programme — probably the first large-scale one devoted to the validation of numerical simulation tools — and presents and discusses the first available results, with a view to their use as feedback for the improvement of the computational modelling.

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