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Nomenclature Acronyms cp Average constant pressure specific heat (kJ/kg-K) h Specific enthalpy (kJ/kg) Ja Jacob number (-) P Pressure (Bar) EOS Equations of state FOM Figure of Merit GA Genetic Algorithm GWP Global Warming Potential HMIS Hazardous Materials Identification System Subscripts IMO International Maritime Organization LP Recuperated process 20 bar pressure limit NIST National Institute of Standards and Technology NO Recuperated process 120 bar pressure limit ODP Ozone Depletion Potential ORC Organic Rankine Cycle PP Pinch point SI Non-recuperated process 120 bar pressure limit SOLAS International Convention for the Safety of Life At Sea Symbols m ̇ Mass flow rate (kg/s) c Cold stream co Condensation e Evaporation ext External h Hot stream i Inlet int Internal max Maximum o Outlet pp Pinch point sh Superheater approach T Temperature (◦C) cerning the Figure of Merit (FOM) which is a figure able to predict the ORC plant thermal efficiency based on the ratio of the sensible and latent heat [7]. With the ongoing research within formulation of equa- tions of state (EOS) and the successive development of available EOS software packages, the number of fluids ac- cessible for theoretical calculations is increasing. A need thus arises for a methodology to evaluate a large number of fluids and an even larger number of mixtures of two or more fluids systematically. Drescher et al. [8] presented a method used for a screening of about 700 fluids based on the plant thermal efficiency. The results from thermody- namic screening of 30+ fluids have been presented by Saleh et al. [9] and Chen et al. [4]. Tchanche et al. [10] pre- sented a methodology of evaluation by awarding each can- didate fluid either a plus or a minus sign to signify whether or not the fluid is favoured regarding a number of criteria: pressure levels, expander volume, thermal and second law efficiencies, irreversibilities, toxicity, flammability, Ozone Depletion Potential (ODP) and GWP. Twenty fluids were evaluated in a ORC process with no super heating or re- cuperator. Dai et al. [11] used the genetic algorithm in a parametric study to determine the optimum fluid among ten in a subcritical ORC process. Papadopoulos et al. [12] used an unconventional multi-objective approach which aims at designing the molecule of ORC working fluids by looking at the resulting heat exchanger area, cost, toxic- ity, flammability, environmental and thermodynamic per- formances of a subcritical ORC process. This paper presents a generally applicable methodol- ogy for determining the optimum Rankine process layout and working fluid based on given boundary conditions and requirements. The method builds on the principles of nat- ural selection using the genetic algorithm (GA) and, com- pared with previous work, this methodology is pioneering in the sense that it includes at the same time both the process layout and working fluid selection. The evaluation is based on a number of rules which penalise solutions in order to remove thermodynamically inconsistent results. The method determines the optimal fluid among any num- ber of working fluids (and also mixtures of fluids though this is not included in this work), while optimising the pro- cess layout to the thermodynamic properties of the fluid. Fluids are evaluated across a chosen pressure range includ- ing supercritical states. All possible solutions are included in the solution domain, i.e. wet, isentropic and dry fluids with the enabling of superheating and recuperation when thermodynamically feasible. Also included in the evalua- tion are requirements for physical, fire and health hazard levels. The method is used to propose the best fluid alter- natives across a relevant temperature range (180-360◦C) useful for exhaust heat recovery in large ships. Focus is then on the engine design point at 255◦C and the reduction of the potentially highest work output caused by imposing various constraints on the process and fluid. A description of the proposed methodology in details is covered in section 2. Section 3 presents the findings from using the methodology. Further analysis of the re- sults is discussed in section 4, and the main conclusions are outlined in section 5. 2. Methodology In this section objectives, features and details of the applied methodology are explained. As the aim is to find the optimum process layout and fluid under varying con- straints, the method includes processes: a) at sub- and 2PDF Image | organic Rankine cycles for waste heat recovery in marine settings
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