Constraining Dense Matter Physics Using f-Mode Oscillations in Neutron Stars

In this paper, an investigation of the role of nuclear saturation parameters on f-mode oscillations in neutron stars is performed within the Cowling approximation. It is found that the uncertainty in the effective nucleon mass plays a dominant role in controlling the f-mode frequencies. The effect of the uncertainties in saturation parameters on previously-proposed empirical relations of the frequencies with astrophysical observables relevant for asteroseismology are also investigated. These results can serve as an important tool for constraining the nuclear parameter space and understand the behaviour of dense nuclear matter from the future detection of f-modes.

A comparison of uncertainty propagation techniques using NDaST: full, half or zero Monte Carlo?

Uncertainty propagation to keff using a Total Monte Carlo sampling process is commonly used to solve the issues associated with non-linear dependencies and non-Gaussian nuclear parameter distributions. We suggest that in general, keff sensitivities to nuclear data perturbations are not problematic, and that they remain linear over a large range; the same cannot be said definitively for nuclear data parameters and their impact on final cross-sections and distributions. Instead of running hundreds or thousands of neutronics calculations, we therefore investigate the possibility to take those many cross-section file samples and perform ‘cheap’ sensitivity perturbation calculations. This is efficiently possible with the NEA Nuclear Data Sensitivity Tool (NDaST) and this process we name the half Monte Carlo method (HMM). We demonstrate that this is indeed possible with a test example of JEZEBEL (PMF001) drawn from the ICSBEP handbook, comparing keff directly calculated with SERPENT to those predicted with NDaST. Furthermore, we show that one may retain the normal NDaST benefits; a deeper analysis of the resultant effects in terms of reaction and energy breakdown, without the normal computational burden of Monte Carlo (results within minutes, rather than days). Finally, we assess the rationality of using either full or HMMs, by also using the covariance data to do simple linear 'sandwich formula' type propagation of uncertainty onto the selected benchmarks. This allows us to draw some broad conclusions about the relative merits of selecting a technique with either full, half or zero degree of Monte Carlo simulation

Production and use of nuclear parameter covariance data: an overview of challenging cross cutting scientific issues

Nuclear data users’ requirements for uncertainty data started already in the seventies, when several fast reactor projects did use extensively “statistical data adjustments” to meet data improvement for core and shielding design. However, it was only ∼20–30 years later that a major effort started to produce scientifically based covariance data and in particular since ∼2005. Most work has been done since then with spectacular achievements and enhanced understanding both of the uncertainty evaluation process and of the data utilization in V&V. This paper summarizes some key developments and still open challenges.

Absolute Disintegration Rate of Finite Gold Sample: Determination by Coincidence Techniques

A method has been developed for absolute disintegration rate determination of finite-sized, radioactive samples. Measurements were made on a 15-mg gold foil. The average disintegration rate was 2.163X105 for 24 determinations with a precision of 2.3%. Subsequent measurements yielded precisions as low as 0.5%. Conditions of bias settings, decay corrections, and coincidence resolving times were widely varied. The scintillation, coincidence equipment, including novel pulse timing, are mentioned. Data corrections, including accidentals and particle A in detector B are discussed. It is shown that the corrections are empirical and do not limit the absolute nature of the measurements. Some of the nuclear parameter requirements and spectroscopic implications are indicated.