Physical and Numerical Difficulties in Computer Modelling of Pellet-Cladding Contact Problems for Burned-Up Fuel

The importance of fuel reliability is growing due to the deregulated electricity market and the demands on operability and availability to the electricity grid of nuclear units. Under these conditions of fuel exploitation, the problems of PCMI (Pellet-Cladding Mechanical Interaction) are very important from the point of view of fuel rod integrity and reliability. Severe loading is thermophysically and mechanically expressed as a greater probability of cladding failure especially during power maneuvering. We have to be able to make a realistic prediction of safety margins, which is very difficult by using computer simulation methods. NRI (Nuclear Research Institute) has recently been engaged in developing 2D and 3D FEM (Finite Element Method) based models dealing with this problem. The latest effort in this field has been to validate 2D r-z models developed in the COSMOS/M system against calculations using the FEMAXI-V code. This paper presents a preliminary comparison between classical FEM based integral code calculations and new models that are still under development. The problem has not been definitely solved. The presented data is of a preliminary nature, and several difficult problems remain to be solved.

Determination of thermal response of Carrara and Sneznikovsky marble used as building material

Physical weathering of marble, widely used as a cladding material on buildings, is one of the most common damaging mechanism caused by anisotropic thermal expansion of calcite grains. The extent of marble deterioration depends mainly on stone fabric and texture. Dry cuboids of Carrara marble and marble from Dolni Morava quarry were subjected to microscopic analysis and thermal cycling, to determine the thermal expansion related to stone fabric and predominant lattice orientation of grains (i.e. texture)

Application of multi-modal 2D and 3D imaging and analytical techniques to document and examine coins on the example of two Roman silver denarii

This case study is applying imaging and analytical techniques from multiple scientific disciplines to digitise coins and evaluate 3D multi-modal visualisation. Two ancient Roman silver denarii were selected as test objects to establish whether the proposed digital recording methods can support professional numismatic comparison of features and properties. The coins raise questions concerning their provenance, authenticity, design, purpose of issue and historic usage, but they also pose considerable recording challenges due to their material and surface properties, which are the main focus in this paper. The coins have been examined by the following techniques: dome photography for image sets for PTM/RTI visualisation and photometric stereo; X-ray microtomography for detection of cracks or impurities; Scanning Electron Microscopy for detailed surface investigation; Energy-Dispersive X-ray Spectroscopy for elemental analysis; micro X-ray fluorescence spectrometry mapping; 3D laser and structured light scanning for 3D spatial capture; photogrammetry/structure from motion, focus-stacking. The results indicate the feasibility of such techniques for museum documentation and as contribution to scientific examination of coins in general

The Challenge of Machine Learning in Space Weather Nowcasting and Forecasting

The numerous recent breakthroughs in machine learning (ML) make imperative to carefully ponder how the scientific community can benefit from a technology that, although not necessarily new, is today living its golden age. This Grand Challenge review paper is focused on the present and future role of machine learning in space weather. The purpose is twofold. On one hand, we will discuss previous works that use ML for space weather forecasting, focusing in particular on the few areas that have seen most activity: the forecasting of geomagnetic indices, of relativistic electrons at geosynchronous orbits, of solar flares occurrence, of coronal mass ejection propagation time, and of solar wind speed. On the other hand, this paper serves as a gentle introduction to the field of machine learning tailored to the space weather community and as a pointer to a number of open challenges that we believe the community should undertake in the next decade. The recurring themes throughout the review are the need to shift our forecasting paradigm to a probabilistic approach focused on the reliable assessment of uncertainties, and the combination of physics-based and machine learning approaches, known as gray-box.Comment: under revie

Tetra­kis(μ-2-methyl­benzoato)bis­[(2-methyl­benzoic acid)copper(II)]

In the title centrosymmetric dinuclear compound, [Cu2(C8H7O2)4(C8H8O2)2], four o-toluate anions form a cage around two Cu atoms in a syn–syn configuration. Two more o-toluic acid mol­ecules are apically bonded to the Cu atoms, which show a square-pyramidal coordination geometry. The acid H atoms are hydrogen bonded to the cage carboxyl O atoms [O⋯O = 2.660 (2) Å]. The mol­ecular packing forms a puckered pseudo-hexa­gonal close-packed layer in the (h00) plane, with soft inter­molecular H⋯H contacts (2.46–2.58 Å)

Tetra­kis(μ-4-ethyl­benzoato-κ2 O:O′)­bis­[(4-ethyl­benzoic acid-κO)copper(II)]

The molecule of the title compound, [Cu2(C9H9O2)4(C9H10O2)2], lies on a center of inversion. It consists of four bridging ethyl­benzoate ligands, forming a cage around two Cu atoms in a syn–syn configuration, and two monodentate ethyl­benzoic acid ligands bonded apically to the square-planar Cu atoms. The Cu⋯Cu distance is 2.6047 (5) Å

Geomagnetic storm dependence on the solar flare class

Content. Solar flares are often used as precursors of geomagnetic storms. In particular, Howard and Tappin (2005) recently published in A&A a dependence between X-ray class of solar flares and Ap and Dst indexes of geomagnetic storms which contradicts to early published results. Aims. We compare published results on flare-storm dependences and discuss possible sources of the discrepancy. Methods. We analyze following sources of difference: (1) different intervals of observations, (2) different statistics and (3) different methods of event identification and comparison. Results. Our analysis shows that magnitude of geomagnetic storms is likely to be independent on X-ray class of solar flares.Comment: 3 pages, 1 tabl