Design and optimisation of organic Rankine cycles for waste heat recovery in marine applications using the principles of natural selection

Power cycles using alternative working fluids are currently receiving significant attention. Selection of working fluid among many candidates is a key topic and guidelines have been presented. A general problem is that the selection is based on numerous criteria, such as thermodynamic performance, boundary conditions, hazard levels and environmental concerns. A generally applicable methodology, based on the principles of natural selection, is presented and used to determine the optimum working fluid, boiler pressure and Rankine cycle process layout for scenarios related to marine engine heat recovery. Included in the solution domain are 109 fluids in sub and supercritical processes, and the process is adapted to the properties of the individual fluid. The efficiency losses caused by imposing process constraints are investigated to help propose a suitable process layout. Hydrocarbon dry type fluids in recuperated processes produced the highest efficiencies, while wet and isentropic fluids were superior in non-recuperated processes. The results suggested that at design point, the requirements of process simplicity, low operating pressure and low hazard resulted in cumulative reductions in cycle efficiency. Furthermore, the results indicated that non-flammable fluids were able to produce near optimum efficiency in recuperated high pressure processes

Valorisation of Biowastes for the Production of Green Materials Using Chemical Methods

With crude oil reserves dwindling, the hunt for a sustainable alternative feedstock for fuels and materials for our society continues to expand. The biorefinery concept has enjoyed both a surge in popularity and also vocal opposition to the idea of diverting food-grade land and crops for this purpose. The idea of using the inevitable wastes arising from biomass processing, particularly farming and food production, is, therefore, gaining more attention as the feedstock for the biorefinery. For the three main components of biomass—carbohydrates, lipids, and proteins—there are long-established processes for using some of these by-products. However, the recent advances in chemical technologies are expanding both the feedstocks available for processing and the products that be obtained. Herein, this review presents some of the more recent developments in processing these molecules for green materials, as well as case studies that bring these technologies and materials together into final products for applied usage

The combustion of n-butanol/diesel fuel blends and its cyclic variability in a direct injection diesel engine

An experimental study is conducted to evaluate the effects of using blends of diesel fuel with n-butanol (normal butanol) up to 24 per cent (by volume), which is a promising fuel that can be produced from biomass (bio-butanol), on the combustion behaviour of a standard, high-speed, direct injection (DI), ‘Hydra’ diesel engine located at the authors’ laboratory. Combustion chamber and fuel injection pressure diagrams are obtained at four different loads using a developed, high-speed, data acquisition, and processing system. A heat release analysis of the experimentally obtained cylinder pressure diagrams is developed and used. Plots of histories in the combustion chamber of the gross heat release rate and other related parameters reveal some interesting features, which shed light on the combustion mechanism when using these blends. These results, combined with the differing physical and chemical properties of the n-butanol against those for the diesel fuel, aid the correct interpretation of the observed engine behaviour performance based on and emissions. Moreover, given the concern for the rather low cetane number of the n-butanol that may promote cyclic (combustion) variability, its strength is also examined as reflected in the pressure indicator diagrams, by analysing for the maximum pressure and its rate, dynamic injection timing and ignition delay, by using stochastic analysis for averages, standard deviations, probability density functions, autocorrelation, power spectra, and cross-correlation coefficients. </jats:p