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In addition to the regular Schwabe cycles of approximately 11 y, "prolonged solar activity minima" have been identified through the direct observation of sunspots and aurorae, as well as proxy data of cosmogenic isotopes. Some of these prolonged minima have been regarded as grand solar minima, which are arguably associated with the special state of the solar dynamo and have attracted significant scientific interest. In this paper, we review how these prolonged solar activity minima have been identified. In particular, we focus on the Dalton Minimum, which is named after John Dalton. We review Dalton's scientific achievements, particularly in geophysics. Special emphasis is placed on his lifelong observations of auroral displays over approximately five decades in Great Britain. Dalton's observations for the auroral frequency allowed him to notice the scarcity of auroral displays in the early 19th century. We analyze temporal variations in the annual frequency of such displays from a modern perspective. The contemporary geomagnetic positions of Dalton's observational site make his dataset extremely valuable because his site is located in the sub-auroral zone and is relatively sensitive to minor enhancements in solar eruptions and solar wind streams. His data indicate clear solar cycles in the early 19th century and their significant depression from 1798 to 1824. Additionally, his data reveal a significant spike in auroral frequency in 1797, which chronologically coincides with the "lost cycle" that is arguably located at the late Solar Cycle 4. Therefore, John Dalton's achievements can still benefit modern science and help us improve our understanding of the Dalton Minimum. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak is of great concern due to the high rates of infection and the large number of deaths worldwide. In this paper, we considered a Bayesian inference and failure mode and effects analysis of the modified susceptible-exposed-infectious-removed model for the transmission dynamics of COVID-19 with an exponentially distributed infectious period. We estimated the effective reproduction number based on laboratory-confirmed cases and death data using Bayesian inference and analyse the impact of the community spread of COVID-19 across the United Kingdom. We used the failure mode and effects analysis tool to evaluate the effectiveness of the action measures taken to manage the COVID-19 pandemic. We focused on COVID-19 infections and therefore the failure mode is taken as positive cases. The model is applied to COVID-19 data showing the effectiveness of interventions adopted to control the epidemic by reducing the reproduction number of COVID-19. Results have shown that the combination of Bayesian inference, compartmental modelling and failure mode and effects analysis is effective in modelling and studying the risks of COVID-19 transmissions, leading to the quantitative evaluation of the action measures and the identification of the lessons learned from the governmental measures and actions taken in response to COVID-19 in the United Kingdom. Analytical and numerical methods are used to highlight the practical implications of our findings. The proposed methodology will find applications in current and future COVID-19 like pandemics and wide quality engineering. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak is of great concern due to the high rates of infection and the large number of deaths worldwide. In this paper, we considered a Bayesian inference and failure mode and effects analysis of the modified susceptible-exposed-infectious-removed model for the transmission dynamics of COVID-19 with an exponentially distributed infectious period. We estimated the effective reproduction number based on laboratory-confirmed cases and death data using Bayesian inference and analyse the impact of the community spread of COVID-19 across the United Kingdom. We used the failure mode and effects analysis tool to evaluate the effectiveness of the action measures taken to manage the COVID-19 pandemic. We focused on COVID-19 infections and therefore the failure mode is taken as positive cases. The model is applied to COVID-19 data showing the effectiveness of interventions adopted to control the epidemic by reducing the reproduction number of COVID-19. Results have shown that the combination of Bayesian inference, compartmental modelling and failure mode and effects analysis is effective in modelling and studying the risks of COVID-19 transmissions, leading to the quantitative evaluation of the action measures and the identification of the lessons learned from the governmental measures and actions taken in response to COVID-19 in the United Kingdom. Analytical and numerical methods are used to highlight the practical implications of our findings. The proposed methodology will find applications in current and future COVID-19 like pandemics and wide quality engineering. [ABSTRACT FROM AUTHOR]

Fuel from UK's Advanced Gas-Cooled Reactors (AGRs) is being reprocessed, however reprocessing will cease in 2018 and the strategy for fuel that has not been reprocessed is for it to be placed into wet storage until it can be consigned to a geological disposal facility in around 2080. Although reprocessing of LWR fuel has been undertaken in the UK, and this option is not precluded for current and future LWRs, all utilities planning to operate LWRs are intending to use At-Reactor storage pending geological disposal. This strategy will result in a substantial change in the management of spent fuel that could affect the back end of the fuel cycle for over a century. This paper presents potential fuel storage scenarios for two options: the current nuclear power replacement strategy, which will see 16 GWe of new capacity installed by 2030 and a median strategy, intended to ensure implementation of the UK's carbon reduction target, involving 48 GWe of nuclear capacity installed by 2040. The potential scale, distribution and timing of fuel storage and disposal operations have been assessed and changes to the current industrial activity are highlighted to indicate potential effects on public acceptance of back end activities. [ABSTRACT FROM AUTHOR]

This paper discusses concepts for three-component fuel bundles containing plutonium, uranium and thorium for use in pressurised heavy water reactors, and cases for and against implementation of such a nuclear energy system in the United Kingdom. Heavy water reactors are used extensively in Canada, and are deploying within India and China, whilst the UK is considering the use of heavy water reactors to manage its plutonium inventory of 140 tonnes. The UK heavy water reactor proposal uses a mixed oxide (MOX) fuel of plutonium in depleted uranium, within the enhanced CANDU-6 (EC-6) reactor. This work proposes an alternative heterogeneous fuel concept based on the same reactor and CANFLEX fuel bundle, with eight large-diameter fuel elements loaded with natural thorium oxide and 35 small-diameter fuel elements loaded with a MOX of plutonium and reprocessed uranium stocks from UK MAGNOX and AGR reactors. Indicative neutronic calculations suggest that such a fuel would be neutronically feasible. A similar MOX may alternatively be fabricated from reprocessed<5% enriched light water reactor fuel, such as the fuel of the AREVAEPR reactor, to consume newly produced plutonium from reprocessing, similar to the DUPIC (direct use of PWR fuel in CANDU) process. [ABSTRACT FROM AUTHOR]

Freshwater ecosystems are particularly at risk from climate change due to the intrinsic link between the physical properties of the water environment and those species that live there. Mayflies, stoneflies and caddisflies are key indicators of the health of freshwater environments and their biological traits and ecological preferences determine their vulnerability to climate change. Traits and preferences for 289 British species were analysed, with voltinism, length of flight period, altitudinal preference and affinity to headwaters being the main factors causing vulnerability. Sixteen species were deemed to be at risk from climate change. These species are distributed across Great Britain, but particular hotspots of vulnerability are present in upland areas. These areas should be targeted with mitigation measures to reduce the impacts of climate change on populations of aquatic insects. [ABSTRACT FROM AUTHOR]

Significant geoelectric fields are produced by the interaction of rapidly varying magnetic fields with the conductive Earth, particularly during intense geomagnetic activity. Though usually harmless, large or sustained geoelectric fields can damage grounded infrastructure such as high-voltage transformers and pipelines via geomagnetically induced currents (GICs). A key aspect of understanding the effects of space weather on grounded infrastructure is through the spatial and temporal variation of the geoelectric field. Globally, there are few long-term monitoring sites of the geoelectric field, so in 2012 measurements of the horizontal surface field were started at Lerwick, Eskdalemuir and Hartland observatories in the UK. Between 2012 and 2020, the maximum value of the geoelectric field observed was around 1 V/km in Lerwick, 0.5 V/km in Eskdalemuir and 0.1 V/km in Hartland during the March 2015 storm. These long-term observations also allow comparisons with models of the geoelectric field to be made. We use the measurements to compute magnetotelluric impedance transfer functions at each observatory for periods from 20 to 30,000 s. These are then used to predict the geoelectric field at the observatory sites during selected storm times that match the recorded fields very well (correlation around 0.9). We also compute geoelectric field values from a thin-sheet model of Britain, accounting for the diverse geological and bathymetric island setting. We find the thin-sheet model captures the peak and phase of the band-passed geoelectric field reasonably well, with linear correlation of around 0.4 in general. From these two modelling approaches, we generate geoelectric field values for historic storms (March 1989 and October 2003) and find the estimates of past peak geoelectric fields of up to 1.75 V/km in Eskdalemuir. However, evidence from high voltage transformer GIC measurements during these storms suggests these estimates are likely to represent an underestimate of the true value. [ABSTRACT FROM AUTHOR]

The babbitt-steel bimetal sliding bearing material prepared by the MIG brazing has been applied in many fields. In the application, usually only the bonding force is tested, and the fatigue strength is not evaluated. For this reason, this study referred to the test method for the fatigue strength of bearing materials of internal combustion engines, used the sapphire test machine (Dana Glacier Vandervell Bearings, UK) to inspect the SnSb11Cu6 babbitt-steel bimetal material prepared by MIG brazing, and analyzed the test results in depth. The test results show that, the fatigue strength of the bimetal material is more than 40 MPa. In comparison, according to the same test method and conditions on the same sapphire test machine, the fatigue strength of the SnSb11Cu6 babbitt-steel bimetal bearing material obtained by the centrifugal casting method after optimizing process was usually around 35 MPa. Therefore, the MIG brazing could produce higher fatigue strength for SnSb11Cu6 babbitt-steel bimetal bearing material. In addition, in this study, the process of fatigue failure was usually that after the microcracks were generated on the surface, they expanded to the inside of the lining, thereby resulting in spalling. This study has guiding significance for engineering practice and scientific research. [ABSTRACT FROM AUTHOR]