Working Fluid Design for Organic Rankine Cycle

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Working Fluid Design for Organic Rankine Cycle ( working-fluid-design-organic-rankine-cycle )

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Chapter 2 Background The following chapter presents a brief review on the design methods for molecules in particular the CAMD and the Continuous Molecular Targeting approach to CAMD (CoMT-CAMD), working fluid candidates and ORC turbogenerators for automotive heat recovery. 2-1 Computer Aided Molecular Design (CAMD) In principle, computer aided molecular design is the inverse of property prediction based on group contribution methods. The design of molecules is based on a systematic combination of a number functional molecular groups to develop a molecule with certain chemical struc- ture and of particular physical and chemical properties which are calculated using Group Contribution methods that utilize databases containing the registered contributions of each functional group comprising the developed molecule. This, in addition to knowledge- or optimization-based technologies for screening molecules with desired properties, constitute the CAMD method. Papadopoulos et. al. [13] employed CAMD to design ORC working fluids. Figure 2-1 illustrates the traditional CAMD approach for design of fluids. From Fig- ure 2-1, it is clear that the constraints on property values are obtained from a process-design optimization and the components are generated in the molecular-design step. The final se- lection of the fluid is based on a process wide objective such as cost, energy efficiency, etc. In such a method, there exists a possibility of ignoring the ideal candidate during the molecular design step as there is no feedback on the actual performance of the process for the component generated. Thus it is essential to integrate the molecular design with the process design. Bar- dow et. al [16] in their work, introduced a novel approach towards CAMD which establishes this integration between fluid and process properties. The following section introduces the continuous-molecular targeting approach to CAMD. Master of Science Thesis Akshay Hattiangadi

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