Numerical experiments of some Krylov subspace methods for black oil model

This paper discusses preconditioned Krylov subspace methods for solving large scale linear systems that originate from oil reservoir numerical simulations. Two types of preconditioners, one being based on an incomplete LU decomposition and the other being based on iterative algorithms, are used together in a combination strategy in order to achieve an adaptive and efficient preconditioner. Numerical tests show that different Krylov subspace methods combining with appropriate preconditioners are able to achieve optimal performance.

Modeling and experiments on an isothermal fatigue test for solder joints

This paper investigates an isothermal fatigue test for solder joints developed at the NPL. The test specimen is a lap joint between two copper arms. During the test the displacement at the ends of the copper are controlled and the force measured. The modeling results in the paper show that the displacement across the solder joint is not equal to the displacement applied at the end of the specimen. This is due to deformation within the copper arms. A method is described to compensate for this difference. The strain distribution in the solder was determined by finite element analysis and compared to the distribution generated by a theoretical 'ideal' test which generates an almost pure shear mode in the solder. By using a damage-based constitutive law the shape of the crack generated in the specimen has been predicted for both the actual test and the ideal pure shear test. Results from the simulations are also compared with experimental data using SnAgCu solder.

Multicomponent gas-mixture measurements using an array of gas sensors and an artificial neural-network

An Electronic Nose is being jointly developed between the University of Greenwich and the Institute of Intelligent Machines to detect the gases given off from an oil filled transformer when it begins to break down. The gas sensors being used are very simple, consisting of a layer of Tin Oxide (SnO2) which is heated to approximately 640 K and the conductivity varies with the gas concentrations. Some of the shortcomings introduced by the commercial gas sensors available are being overcome by the use of an integrated array of gas sensors and the use of artificial neural networks which can be 'taught' to recognize when the gas contains several components. At present simulated results have achieved up to a 94% success rate of recognizing two component gases and future work will investigate alternative neural network configurations to maintain this success rate with practical measurements.

Practical solvent system selection for counter-current separation of pharmaceutical compounds

Counter-current chromatography (CCC) is a technique that shows a lot of potential for large scale purification. Its usefulness in a "research and development" pharmaceutical environment has been investigated, and the conclusions are shown in this article. The use of CCC requires the development of an appropriate solvent system (a parameter of critical importance), a process which can be tedious. This article presents a novel strategy, combining a statistical approach and fast HPLC to generate a three-dimensional partition coefficient map and rapidly predict an optimal solvent system. This screen is performed in half a day and involves 9 experiments per solvent mixture. Test separations were performed using that screen to ensure the validity of the method.