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In this paper, we discuss the development of a nuclear data evaluation pipeline, based around the TALYS code system. The pipeline focuses on the evaluation of the fast neutron energy range, above the resolved resonances. A strong focus in development lies on automation and reproducibility, as well as the efficient use of large-scale computational infrastructure, to enable rapid testing of new algorithms and modified assumptions. Several novel concepts for nuclear data evaluation methodology are implemented. A particular problem in evaluating the neutron-induced reaction cross-section using TALYS, relates to the intermediate energy range. While TALYS only predicts the smooth energy-averaged cross-section, experiments reveal unresolved resonance-like structures. In this paper, we explore ways to treat this type of model defect using heteroscedastic Gaussian processes to automatically determine the distribution of experimental data around an energy-averaged cross-section curve.

The Total Monte Carlo (TMC) technique has proven to be a powerful tool to propagate uncertainties in nuclear data to the uncertainty in macroscopic quantities, such as neutron fluxes at detector positions and the criticality of reactor cores. Nuclear data uncertainties can be used to create self-consistent sets of cross-sections. Each set contains files generated by variations of nuclear model parameters to properly fit the model to the nuclear data, accounting for their uncertainty. These files are called random files. The random files reflect the covariances of the nuclear data due to the uncertainties of the nuclear physics model parameters. TMC uses particle transport codes, such as MCNP, to transport particles through arbitrarily complex geometries. Each set of random files is used in a separate transport code run. This allows for the propagation of uncertainties in nuclear data, which otherwise could be hard to account for in the transport codes. However, particle transport techniques are well-known to be computationally expensive. The Half Monte Carlo (HMC) technique uses the random files of the TMC technique but does not rely on transport codes to propagate the uncertainties of nuclear data to the uncertainty of the sought macroscopic quantity. Instead, it uses pre-calculated sensitivity matrices to calculate the difference in a macroscopic quantity, given the difference of the random files relative to the best estimate of the nuclear data evaluation. In this work, we demonstrate how to use the HMC technique to calculate the uncertainty of macroscopic quantities in integral experiments for a set of random files relative to the best nuclear data evaluation. In this paper, we demonstrate how HMC can be used to incorporate integral experiments into an automated nuclear data evaluation. After applying the Bayesian Monte Carlo method in conjunction with the HMC technique and random files of uranium-235 from the TENDL library on the Godiva experiment, we conclude that the HMC technique gives similar results to that of the TMC technique: the mean value and the standard deviation of ∆keff is -6.30 pcm and 1220 pcm, respectively.

In a Swedish citizen science project, more than 200 elementary school classes participated in collecting fungi, soil samples, and droppings from deer and wild boar, from all over Sweden. The samples have been sent to a laboratory at Uppsala University where they are being analyzed through gamma spectroscopy with a shielded HPGe detector. The main objective is to scan the samples for 137Cs from the Chernobyl accident and compare the data with measurements from 1986, but uptake of naturally occuring radionuclides like 40K and radon daughters will also be determined. Together with the soil samples, transfer factors will be derived, and correlations for these factors will be sought for different species of fungi and soil types. The potential for correlating the results with different biological processes will also be investigated, in part through the collected animal droppings. This is a work in progress where the present status of the experimental setup and methodology are presented. Issues with the initial approach for corrections are discussed and preliminary results are presented.

A growing trend in science is that research institutions reach out to members of the public for participating in research. The reasons for outreach are many, spanning from the desire to collect and/or analyse large sets of data efficiently, to the idea of including the general public on a very fundamental level in science-making and ultimately decision-making. The presented project is curriculum-based and carried out in 240 lower secondary school classes (pupils of age 13-16). The task, as designed by the participating universities, is to collect mushrooms, soil and animal droppings from different parts of Sweden, do preliminary sample preparation and analyses and send the samples to the university institutions for radioactivity measurement. Behind the project is a desire to compare today’s levels of 137Cs with those deposited right after the Chernobyl accident in 1986, but also to study the exchange of caesium between organisms as well as the impacts of biological and geological processes on uptake and retention. The scientific outcome is a geodatabase with the 137Cs activity (Bq/m2) present in the Swedish environment, where radioactivity data can be linked to the species (fungi, competing species, animals foraging), forest type, land type, land use and other environmental factors. The science question is of interest to the general public as foraging for mushrooms, as well as spending recreational time in forests is widely popular in Sweden. In this article, we will discuss the current status of the project and the observations we have made about how well the public can participate in scientific research. Focus will be on organization of the project, such as logistics, preparation of supportive material, feedback and communication between researchers and schools. We will present observations about the impact the project has had on the participants, based on quantitative and qualitative evaluations.

Neutron-induced fission cross sections of 235U and 238U are widely used as standards for monitoring of neutron beams and fields. An absolute measurement of these cross sections at an absolute scale, i.e., versus the H(n,p) scattering cross section, is planned with the white neutron beam under construction at the Neutrons For Science (NFS) facility in GANIL. The experimental setup, based on PPACs and ΔE-ΔE-E telescopes containing Silicon and CsI(Tl) detectors, is described. The expected uncertainties are discussed.