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The OECD-NEA High Priority Request List (HPRL) is a point of reference to guide and stimulate the improvement of nuclear data for nuclear energy and other applications, and a tool to bridge the gap between data users and producers. The HPRL is application-driven and the requests are submitted by nuclear data users or representatives of the user’s communities. A panel of international experts reviews and monitors the requests in the framework of an Expert Group mandated by the NEA Nuclear Science Committee Working Party on International Nuclear Data Evaluation Cooperation (WPEC). After approval, individual requests are classified to three categories: high priority requests, general requests, and special purpose requests (e.g., dosimetry, standards). The HPRL is hosted by the NEA in the form of a relational database publicly available on the web. This paper provides an overview of HPRL entries, status and outlook. Examples of requests successfully completed are given and new requests are described with emphasis on updated nuclear data needs in the fields of nuclear energy, neutron standards and dosimetry.

A lot of research work has been carried out in fine tuning model parameters to reproduce experimental data for neutron induced reactions. This however is not the case for proton induced reactions where large deviations still exist between model calculations and experiments for some cross sections. In this work, we present a method for searching both the model and model parameter space in order to identify the ’best’ nuclear reaction models with their parameter sets that reproduces carefully selected experimental data. Three sets of experimental data from EXFOR are used in this work: (1) cross sections of the target nucleus (2) cross sections of the residual nuclei and (3) angular distributions. Selected models and their parameters were varied simultaneously to produce a large set of random nuclear data files. The goodness of fit between our adjustments and experimental data was achieved by computing a global reduced chi square which took into consideration the above listed experimental data. The method has been applied for the adjustment of proton induced reactions on 59Co between 1 to 100 MeV. The adjusted files obtained are compared with available experimental data and evaluations from other nuclear data libraries.

The CIELO collaboration has studied neutron cross sections on nuclides that significantly impact criticality in nuclear technologies – 16O, 56Fe, 235,8U and 239Pu – with the aim of improving the accuracy of the data and resolving previous discrepancies in our understanding. This multi-laboratory pilot project, coordinated via the OECD/NEA Working Party on Evaluation Cooperation (WPEC) Subgroup 40 with support also from the IAEA, has motivated experimental and theoretical work and led to suites of new evaluated libraries that accurately reflect measured data and also perform well in integral simulations of criticality.

The TALYS Evaluated Nuclear Data Library (TENDL) has now 8 releases since 2008. Considerable experience has been acquired for the production of such general-purpose nuclear data library based on the feedback from users, evaluators and processing experts. The backbone of this achievement is simple and robust: completeness, quality and reproducibility. If TENDL is extensively used in many fields of applications, it is necessary to understand its strong points and remaining weaknesses. Alternatively, the essential knowledge is not the TENDL library itself, but rather the necessary method and tools, making the library a side product and focusing the efforts on the evaluation knowledge. The future of such approach will be discussed with the hope of nearby greater success.

Two distinct methods of propagation for basic nuclear data uncertainties to large scale systems will be presented and compared. The “Total Monte Carlo” method is using a statistical ensemble of nuclear data libraries randomly generated by means of a Monte Carlo approach with the TALYS system. These libraries are then directly used in a large number of reactor calculations (for instance with MCNP) after which the exact probability distribution for the reactor parameter is obtained. The second method makes use of available covariance files and can be done in a single reactor calculation (by using the perturbation method). In this exercise, both methods are using consistent sets of data files, which implies that covariance files used in the second method are directly obtained from the randomly generated nuclear data libraries from the first method. This is a unique and straightforward comparison allowing to directly apprehend advantages and drawbacks of each method. Comparisons for different reactions and criticality-safety benchmarks from 19F to actinides will be presented. We can thus conclude whether current methods for using covariance data are good enough or not.

The increasing need for cross sections far from the valley of stability poses a challenge for nuclear reaction models. So far, predictions of cross sections have relied on more or less phenomenological approaches, depending on parameters adjusted to available experimental data or deduced from systematical relations. While such predictions are expected to be reliable for nuclei not too far from the experimentally known regions, it is clearly preferable to use more fundamental approaches, based on sound physical bases, when dealing with very exotic nuclei. Thanks to the high computer power available today, all major ingredients required to model a nuclear reaction can now be (and have been) microscopically (or semi-microscopically) determined starting from the information provided by a nucleon-nucleon effective interaction. We have implemented all these microscopic ingredients in the TALYS nuclear reaction code, and we are now almost able to perform fully microscopic cross section calculations. The quality of these ingredients and the impact of using them instead of the usually adopted phenomenological parameters will be discussed.

We review our calculated energy-, spin- and parity-dependent nuclear level densities based on the microscopic combinatorial model described in ref. [1]. We show that this model predicts the experimental sand p-wave neutron resonance spacings with a degree of accuracy comparable to that of the best global models available and also provides reasonable description of low energies cumulative number of levels as well as of the experimental data obtained by the Oslo group [2]. We also provide a renormalization recipe which enables to play with the tabulated results for practical applications. Finally, we study the impact of temperature dependent calculation on s-wave neutron resonance spacings.