Modelling the weathering process of stored liquefied natural gas (LNG)

Weathering occurs in stored liquefied natural gas (LNG) due to the removal of the boil-off gas (BOG) from the LNG container and results in the remaining LNG being richer in heavier components. A model has been developed to predict stored LNG weathering in containment tanks, typically used in regasification. The model integrates a vapour-liquid equilibrium model, and a realistic heat transfer model. It provides a number of advances on previously developed models: (i) heat ingress is calculated based on outside temperature and LNG composition, allowing for daily/seasonal variations; (ii) boil-off-ratio is not an input; (iii) LNG density is estimated using an experimentally based correlation. The model was validated using real industry data and the agreement obtained in predicting overall composition, density and amount vaporized was within industry requirements. Two modelling approaches have been developed: (i) assuming thermodynamic equilibrium between vapour and liquid; and (ii) assuming heat exchange between the two phases. Both models were run in a predictive mode to assess the BOG under different scenarios. One of the main results of this work is that the BOG generation is 25% less when considering the non-equilibrium approach, which will have a significant impact on industry where simple equilibrium models are used. In the initial stages of weathering nitrogen content of LNG has a marked effect on BOG generation. Even 0.5% mol of nitrogen leads to nearly 7% BOG decrease, making the initial BOG unmarketable. That is a result of preferential evaporation of nitrogen and increase in the direct differential molar latent heat. In the final stages of weathering the heavier hydrocarbons govern the BOG dynamics, which becomes a strong function of initial composition and the LNG remaining in the tank.Open Acces

Spherulite formation in obsidian lavas in the Aeolian Islands, Italy

The authors wish to gratefully acknowledge Andy Tindle (The Open University) for assistance with EMP analyses, and Richard Darton and David Evans (Keele University) for assistance with XRD and Prof Alun Vaughan and Nicola Freebody (University of Southampton) with Raman analyses. LAB is grateful to Sophie Blanchard for support with MATLAB. The authors acknowledge support from Keele University, and grants from the Mineralogical Society (UK and Ireland) and Volcanic and Magmatic Studies Group. The authors thank Silvio Mollo and Francesca Forni for their detailed and helpful comments.Peer reviewedPublisher PD

Automated Analysis of Compositional Multi-Agent Systems

Abstract. An approach for handling the complex dynamics of a multi-agent system is based on distinguishing aggregation levels. The behaviour at a given aggregation level is specified by a set of dynamic properties at that level, expressed in some (temporal) language. Such behavioural specifications may be complex and difficult to analyse. To enable automated analysis of system specifications, a simpler format is required. To this end, a specification at a lower aggregation level can be created, describing basic steps in the processes of a system. This paper presents a method and tool to support the automated creation of such a specification, as a refinement of a given higher level specification. The generated specification has a simple format which can easily be used for analysis. This paper describes an approach for automated verification of logical consequences of specifications using model checking techniques