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Isomers produced by spontaneous fission of ²⁵²Cf were measured with the VESPA setup, composed of LaBr₃(Ce) detectors for fast γ-ray spectroscopy and an ionization chamber for detecting fission fragments. Identification of the isomers was derived from fission fragment-γ-γ coincidences. This paper presents the half-lives of 41 isomeric states measured with this setup, from less than a nanosecond up to tens of microseconds. Short-lived isomers in ⁹⁴Rb, ¹⁰⁸Tc, and ¹⁴⁷Ce are reported for the first time. In addition to this half-life analysis, the isomers are used to develop and test a nuclear charge calibration of the ionization chamber.

In this study, we applied the Total Monte Carlo (TMC) methodology in de-excitation simulations of primary fission fragments (FF) using the TALYS code. The goal was to develop and optimise a methodology to benchmark initial fission model assumptions on fission mass yield distributions, excitation energy sharing and angular momentum population. The study was performed on the thermal neutron induced fission of Pu-239(n(th),f). The work aimed at evaluating fission model deficiencies and parameter sensitivities. We systematically varied TALYS input data by generating 5000 random files through the GEF code, randomizing 94 model parameters that affect fission yields and energy distributions within 3% of their default values. This variation revealed significant changes in the fission observables, such as prompt neutron and gamma-ray multiplicities and energy spectra. The results indicate some systematic defects in the assumed excitation-energies and angular momenta. Another outcome from the study is the identification of a need for new correlation measurements on prompt neutrons and gamma-rays from the Pu-239(n(th),f) reaction, as well as an updated evaluation.

The VERDI fission spectrometer is designed to measure fragment velocities and kinetic energies to achieve high-precision yield measurements. It consists of two time-of-flight (TOF) sections, each hosting a micro-channel plate (MCP) and up to 32 passivated implanted planar silicon (PIPS) detectors. The main challenge to achieve accurate fragment velocities is the so-called plasma delay time (PDT) phenomena in the PIPS detectors. In this work, we present a dedicated experimental campaign at the LOHENGRIN fission-fragment recoil separator, to solve the pending PDT challenges. The PDT effect was systematically investigated, as a function of mass and energy, using a dedicated time-of-flight setup. In addition, the pulse height defect (PHD) was determined simultaneously. The studies were conducted for five PIPS detectors, in energies and mass numbers ranging from 20 to 110 MeV and A = 85 to 149, respectively. Using digital signal processing, an excellent timing resolution was achieved, reaching as low as 60 ps (one σ) for the heavy ions. The PDT revealed a strong positive correlation with the ion energy and a weak negative correlation with the mass. The experimental PDT values determined from five detectors confirm a consistent systematic behavior with respect to mass and energy. Some systematic discrepancies were exhibited by two detectors, possibly due to the use of different pre-amplification chains. The PDT measurements ranged between 1 and 3.5 ns, for heavy ions relative to α-particles. The PHD values showed also a strong correlation with the ion energy, and moreover with the ion mass. The PHD for heavy ions was found to range between 2 and 8 MeV, relative to α-particles. Finally, a two-dimensional parameterisation was developed to model the experimental PDT data, as a function of mass and energy. This new model, which is valid in the fission fragment mass and energy regime, will be of benefit for heavy-ion velocity measurements, using silicon detectors, as done in VERDI.

The Nuclear data Evaluation Pipeline of Uppsala University (NEPU) has been developed to perform reproducible data driven nuclear data evaluations. Until now, the pipeline has been used to perform evaluation above the resonance regions for structural materials. Cross-sections for neutron reactions of neutron energies in the range 100 keV to 5-10 MeV in structural materials fluctuate due to resonances in the excited states of the compound system.In this work, we describe the changes we have made to NEPU to allow it also to include energy ranges of cross-sections for neutron energies ranging from 1 to 5 MeV for Fe-56. NEPU uses TALYS. TALYS relies on the assumption that resonance fluctuations are averaged out. This assumption can be described as a model defect in the intermediate incident neutron energy region, where a large number of overlapping resonances causes the cross-section to fluctuate around the energy averaged value. We show how we have used Gaussian process regression to describe the model defects of TALYS to include the cross-section fluctuations in our evaluation pipeline.In addition to co-variance matrixes, NEPU produces random files. Each set of random files incorporate information of for example cross-sections and angular dependencies of the various reaction channels. The distribution of the sets of random files is capable of reflecting more complex covariances than the pure covariance matrixes. In addition, the random files can be used in the Total Monte Carlo technique.We will demonstrate the results of this work by showing how the models agree with nuclear data from the EXFOR database, after the model defect correction has been applied.

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.

A key to the verification of nuclear weapon dismantling is the identification of presence respectively absence of fissile materials in items, specifically weapons grade plutonium and/or high enriched uranium. In the case of plutonium, spontaneous fission of minority isotopes enables its detection through emitted neutrons, making passive use of neutrondetectors an attractive path. In the case of high enriched uranium, the emission of spontaneous fission neutrons is negligible, making its detection difficult. However, using active interrogation where an external neutron source irradiates the item under investigation, induced fission neutrons are emitted from high enriched uranium as well as from weapons grade plutonium. Liquid organic scintillation detectors are a promising route to detect fission neutrons for verification of nuclear disarmament. These detectors are sensitive to fast neutrons, which are characterized by low self-attenuation in most materials. In addition, while the detector is sensitive to gamma radiation, it can be effectively discriminated by pulse shape analysis. This work details the assessment of the applicability of a liquid organic scintillator for fast neutron detection for use in verification of nuclear weapon dismantling. The assessment was performed as a part of the BeCamp2 measurement campaign organized by SCK-CEN, where a delegation from the Alva Myrdal Centre on Nuclear Disarmament of Uppsala University participated. As a part of the campaign, 19 items with unknown content were assessed, with three different aims: template matching, determining the absence of nuclear material, and a technology challenge using active interrogation In this first stage, where the content of the items is still not disclosed, it was concluded that the equipment was able to identify the presence of spontaneous fission content in items, using passive interrogation mode, within the measurement time constraints. Gamma and neutron spectrum comparison was a valuable tool for template matching, and active interrogation measurements enabled the detection of fissile content in interrogated items. Our preliminary assessment is that liquid organic scintillator detectors have the potential to be part of the toolbox that will support the technical verification of nuclear weapons dismantlement. Lessons learned from the campaign are discussed with focus on advantages and disadvantages of the technique, and possibilities for further development of the analysis.

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.

Radionuclide monitoring is a proven means of non-intrusive verification of the nuclear test ban treaty. In addition to that, the potential use of radionuclide monitoring spans beyond the detection of nuclear test explosions, since radionuclides can also be released and detected from operations of nuclear fuel cycle facilities, such as the reactor operation and nuclear reprocessing of plutonium production.

In this work, we consider the use of coincidence and anticoincidence techniques as a means to increase the sensitivity in radionuclide monitoring, in terms of improved minimum detectable amount for radionuclides of interest to filter stations used in radionuclide monitoring. In particular, a multi-detector setup is currently being prepared for the evaluation of the technique, and to provide validation data for a coincidence detector simulation codes.

In this presentation, we will describe the multi-detector setup assembled for enabling the evaluation of various types of spectrometry, including 1) gamma-gamma coincidence (from dual detectors and up to five High Purity Germanium (HPGe) detectors), 2) anticoincidence using BGO active shield with single HPGe detector, as well as use of multiple detectors in add-back mode, i.e. simply using the combined detector volume for increased efficiency of single gamma rays. We will present the results of measurements of a calibration sample, and provide a discussion on the advantages and disadvantages of the tested techniques in the context of radionuclide monitoring.

Fuel performance codes are used to forecast fuel behavior and ensure safe operation. These analyses must typically include prediction uncertainties, and fuel performance models need calibration. Consequently, code calibration must derive the best estimates and corresponding uncertainties of model parameters for subsequent propagation.

Bayesian calibration is popular for generating the probability distribution of model parameters. However, model inadequacy disrupts these techniques, typically resulting in underestimated uncertainties. Earlier research showcased the incorporation of model inadequacy by model parameter inflation. The method demands cheap code predictions and derivatives, which required further research to develop differentiated Gaussian process surrogates.

This work combines those techniques into a complete methodology. We demonstrate it by calibrating Transuranus against fission gas release and cladding oxidation data. The result is model parameter uncertainties that primarily explain the discrepancies between the predictions and corresponding measurements, except when the output behaves highly non-linearly.