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SCIENCE CHINA Technological Sciences, Volume 59 , Issue 10 : 1486-1493(2016) https://doi.org/10.1007/s11431-016-0312-3

Application of entransy dissipation based thermal resistance to design optimization of a novel finless evaporator

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  • ReceivedApr 20, 2016
  • AcceptedJul 29, 2016
  • PublishedSep 14, 2016

Abstract

Entransy has been applied and studied in a broad range of heat transfer optimizations recently. Current study proposes the entransy of evaporators to conduct the optimization of heat exchangers in heating, ventilation, air conditioning and refrigeration systems. A novel finless bare tube heat exchanger was studied using a validated heat exchanger modeling tool. The capacity based optimization and entransy dissipation based thermal resistance were used and compared. The applicability of using entransy dissipation based thermal resistance in this type of heat exchanger optimization has been discussed. It has been demonstrated that minimizing entransy dissipation and maximizing capacity are equivalent to optimizing evaporators with fixed flow rates and different when optimizing evaporators with variable flow rates and the deviation is negligible when heat exchanger capacity is small (~1 kW) and more obvious as heat exchanger capacity increases. Thus entransy dissipation based thermal resistance could be used as an alternative optimization index to capacity for evaporators with fixed flow rate and small capacity evaporators with variable flow rates and should be used individually with capacity as an optimization index for evaporators with large capacity and variable flow rates.


Acknowledgment

This work was supported by the sponsors of the Energy Efficiency and Heat Pumps Consortium and Modeling and Optimization Consortium at the Center for Environmental Energy Engineering (CEEE) of the University of Maryland and Heat Transfer Technologies LLC for manufacturing the heat exchanger prototype.


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  • Figure 1

    Bare tube heat exchanger prototype.

  • Figure 2

    (Color online) Max. Q and Min. Cost. (a) Problem 1, at fixed AFR; (b) Problem 2, at variable AFR.

  • Figure 3

    (Color online) Min. Ren and Min. Cost. (a) Problem 3, at fixed AFR; (b) Problem 4, at variable AFR.

  • Figure 4

    (Color online) Min. Ren and Min. Cost (capacity). (a) Problem 3, at fixed AFR; (b) Problem 4, at variable AFR.

  • Figure 5

    (Color online) Min. Ns1 and Min. Cost. (a) Problem 5, at fixed AFR; (b) Problem 6, at variable AFR.

  • Figure 6

    (Color online) Min. Ns1and Min. Cost (capacity). (a) Problem 5, at fixed AFR; (b) Problem 6, at variable AFR.

  • Table 1   Objectives and constraints for different BTHX evaporator optimization problems

    Problem

    1

    2

    3

    4

    5

    6

    Objectives

    Max.

    Q

    Max.

    Q

    Min. Ren

    Min. Ren

    Min.

    Ns1

    Min.

    Ns1

    Min.

    Cost

    Min. Cost

    Min. Cost

    Min. Cost

    Min. Cost

    Min. Cost

    Constraints

    ΔPr£20 kPa, ΔPa£100 Pa, Vhx£Vbase

    AFR variable

    No

    Yes

    No

    Yes

    No

    Yes

  • Table 2   Boundary conditions for BTHX evaporator design variables

    Parameters

    Lower bound

    Upper bound

    Tube length (mm)

    52

    552

    Tube OD (mm)

    0.59

    2

    Horizontal spacing (mm)

    0.7

    3

    Vertical spacing (mm)

    0.7

    3

    Number of tubes per bank (ea)

    100

    140

    Number of tube banks (ea)

    1

    6

    AFR (m3/s)

    0.02

    0.1

  • Table 3   Working fluids inlet conditions for BTHX evaporator

    Parameters

    Air side

    Refrigerant side

    Fluid

    Moist air

    R410A

    Inlet temperature (K)

    299.85

    278.15

    Inlet relative humidity (%)

    51

    -

    Inlet pressure (kPa)

    101.3

    -

    Inlet quality

    -

    0.15

    Mass flow rate (kg/s)

    -

    0.005

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