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The hypothesis of a connection between the onset (or intensification) of Northern Hemisphere Glaciation, the stepwise increase in African aridity (and climate variability), and an important mammalian (including hominin) species turnover is a textbook example of the initiation of a scientific idea and its propagation in science. It is, however, also an example of the persistent popularity of a hypothesis despite mounting evidence against it. A critical review of key publications on the topic and statistical re-analysis of key records of global ice volume and African climate leads to three conclusions: (1) The Northern Hemisphere Glaciation was a gradual process occurring between ∼3.5 and 2.5 Ma, not a single event at ∼2.8 Ma or at any other time. (2) A consistent stepwise (+/−0.2 Ma) transition toward greater aridity in Africa at ∼2.8 Ma does not exist; instead, there are regionally different, gradual transitions partly in connection with the intensification of the Northern Hemisphere Glaciation, but above all with the establishment of the tropical Walker Circulation after ∼2 Ma. (3) Mammalian (including hominin) species turnovers at this time also appear to have been gradual, rather than stepwise.

The paper presents different methods for evaluating sensitivities and uncertainties of the effective delayed neutron fraction (βeff) with respect to microscopic nuclear data in the framework of the SCALE 6.2 code system. The prompt k ratio method is used to calculate βeff approximately. Sensitivities of βeff to microscopic reaction data are calculated with deterministic linear perturbation theory from sensitivities of the multiplication factor, and by performing linear regression analysis on results obtained from random sampling. The latter approach is also applied for estimating sensitivities of kinetic parameters in six delayed neutron groups, as obtained by adjoint flux weighting in lattice calculations, to nuclear reactions. Finally, it is demonstrated that the uncertainties of βeff strongly depend on the choice of the covariance data set; in particular, the use of SCALE 6.2 covariance data for the average number of delayed neutrons per fission in some cases leads to very high βeff uncertainties.

The paper presents solutions for the neutron transport sub-exercises regarding pin cells, fuel assemblies, and supercells of the OECD/NEA UAM-SFR Benchmark. For this, the GRS XSUSA methodology is applied with a recently introduced approach performing linear regression analysis on the output samples, denoted as XSUSA(LR). The main purpose for this is to calculate sensitivity profiles and the main contributions to the total output uncertainties via the first-order uncertainty propagation formula, i.e. by multiplying the corresponding total/partial nuclear data covariance matrices with the total/partial sensitivity vectors. Confidence intervals were estimated by applying Jackknife resampling. Implicit effects are considered. All output uncertainties are compared to the corresponding values calculated with deterministic linear perturbation theory using TSUNAMI from SCALE 6.2.3. Various optimizations were applied with respect to nuclear data and problem geometry. The output uncertainties are significant – around 1.5% for multiplication factors and 5% for Doppler and sodium void reactivity effects.

The impact of nuclear data uncertainties is studied for the reactor power and the reactivity during control rod withdrawal transients with reactivity insertions of 0.5$ and 0.97$, respectively, for a PWR mini-core model. Multi-group cross sections, the multiplicities of both prompt and delayed neutrons, and fission spectra are varied by the application of the random sampling-based method XSUSA with covariance data of SCALE 6.1 supplemented by JENDL-4.0. The varied multi-group data are used by TRITON/NEWT to generate varied 2-group cross sections, which are then applied in neutron-kinetic/thermal-hydraulic calculations with DYN3D-ATHLET. A significant impact on both the reactivity uncertainty and the power uncertainty is observed. Since the distributional properties of the output time series vary across the problem time, the distribution-free Wilks tolerance limit is applied as a robust uncertainty measure to complex time series patterns. The most contributing nuclide reactions to the power uncertainty are identified via sensitivity analysis. (C) 2019 Elsevier Ltd. All rights reserved.