ADVANCED MODELING AND REFRIGERANT FLOW PATH OPTIMIZATION FOR AIR-TO-REFRIGERANT HEAT EXCHANGERS WITH GENERALIZED GEOMETRIES

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dc.contributor.advisorRadermacher, Reinhard Ken_US
dc.contributor.advisorAute, Vikrant Cen_US
dc.contributor.authorLi, Zhenningen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2020-02-01T06:44:19Z
dc.date.available2020-02-01T06:44:19Z
dc.date.issued2019en_US
dc.description.abstractAir-to-refrigerant heat exchangers are key components of the heating, ventilation, air-conditioning and refrigeration systems. The evolving simulation and manufacturing capabilities have given engineers new opportunities in pursuing complex and cost-efficient heat exchanger designs. Advanced heat exchanger modeling tools are desired to adapt to the industrial transition from conventional refrigerants to low Global Warming Potential (low-GWP) refrigerants. This research presents an advanced heat exchanger performance prediction model which distinguishes itself as a cutting-edge simulation tool in the literature to have capabilities, such as to (i) model heat exchangers with variable tube shape and topology, (ii) improved numerical stability, (iv) multiple dehumidification models to improve evaporator prediction, and (v) CFD-based predictions for airflow maldistribution. Meanwhile, HX performance is significantly influenced by the refrigerant flow path arrangements. The refrigerant flow path is optimized for various reasons such as to (i) mitigate the impact of airflow maldistribution, (ii) reduce material/cost, (iii) balance refrigerant state at the outlet of each circuit, and (iv) ensure overall stable performance under a variety of operating conditions. This problem is particularly challenging due to the large design space which increases faster than n factorial with the increase in the number of tubes. This research presents an integer permutation based Genetic Algorithm (GA) to optimize the refrigerant flow path of air-to-refrigerant heat exchangers. The algorithm has novel features such as to (i) integrate with hybrid initialization approaches to maintain the diversity and feasibility of initial individuals, (ii) use effective chromosome representations and GA operators to guarantee the chromosome (genotype) can be mapped to valid heat exchanger designs (phenotype), and (iii) incorporate real-world manufacturability constraints to ensure the optimal designs are manufacturable with the available tooling. Case studies have demonstrated that the optimal designs obtained from this algorithm can improve performance of heat exchangers under airflow maldistribution, reduce defrost energy and assure stable heat exchanger performance under cooling and heating modes in reversible heat pump applications. Comparison with other algorithms in literature shows that the proposed algorithm exhibits higher quality optimal solutions than other algorithms.en_US
dc.identifierhttps://doi.org/10.13016/ilj0-n9vy
dc.identifier.urihttp://hdl.handle.net/1903/25479
dc.language.isoenen_US
dc.subject.pqcontrolledEngineeringen_US
dc.subject.pqcontrolledEnergyen_US
dc.subject.pqcontrolledThermodynamicsen_US
dc.subject.pquncontrolledAir-to-refrigerant Heat Exchangeren_US
dc.subject.pquncontrolledCFDen_US
dc.subject.pquncontrolledCircuitry Optimizationen_US
dc.subject.pquncontrolledGenetic Algorithmen_US
dc.subject.pquncontrolledInteger Permutationen_US
dc.subject.pquncontrolledNumerical Modelingen_US
dc.titleADVANCED MODELING AND REFRIGERANT FLOW PATH OPTIMIZATION FOR AIR-TO-REFRIGERANT HEAT EXCHANGERS WITH GENERALIZED GEOMETRIESen_US
dc.typeDissertationen_US

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