By bringing two immiscible fluids at different temperatures into a direct contact heat exchanger (DCHE), bubble swarms are produced in the dual-loop ORC direct contact boiling heat transfer process. The aim of this paper is to make effort to explore the interplay between mixing state quality and heat transfer performance of fluids in the DCHE. Through flow visualization of this mixing process, a simple image analysis technique is introduced to represent the formation and evolution of vapor around the injected coolant droplets. Description of the boiling heat transfer process is here achieved by average volumetric heat transfer coefficient (VHTC). Experimental results attest that the proposed mixing index is powerful and sufficient compared with the Betti numbers method for the mixing quality quantification of bubbles inside DCHE. The synergistic association between the fluids mixing process and the heat transfer process is investigated by statistical regression model of new mixing index and VHTC. The contributions, including the data from monitoring practice in ORC heat transfer system and the proposed way, are presented to delve into the transient behaviors comparison of various fluids mixing and heat transfer processes conveniently.
MaG-yCaiJ-jZengW-w, et al.Analytical research on waste heat recovery and utilization of China’s iron & steel industry. Energy Procedia2012; 14: 1022–1028.
2.
LiP. Thermodynamic analysis of waste heat recovery of molten blast furnace slag. Int J Hydrogen Energy2017; 42: 9688–9695.
3.
ZhangHWangHZhuX, et al.A review of waste heat recovery technologies towards molten slag in steel industry. Appl Energy2013; 112: 956–966.
4.
XiaoQXuJWangH. Quantifying the evolution of flow boiling bubbles by statistical testing and image analysis: toward a general model. Sci Rep2016; 6: 31548–31548.
5.
VivianJManenteGLazzarettoA. A general framework to select working fluid and configuration of ORCs for low-to-medium temperature heat sources. Appl Energy2015; 156: 727–746.
6.
ZhouNWangXChenZ, et al.Experimental study on Organic Rankine Cycle for waste heat recovery from low-temperature flue gas. Energy2013; 55: 216–225.
7.
FreemanJHellgardtKMarkidesCN. Working fluid selection and electrical performance optimisation of a domestic solar-ORC combined heat and power system for year-round operation in the UK. Appl Energy2017; 186: 291–303.
8.
WangXLevyEKPanC, et al.Working fluid selection for organic Rankine cycle power generation using hot produced supercritical CO2 from a geothermal reservoir. Appl Therm Eng2019; 149: 1287–1304.
9.
LiJGeZDuanY, et al.Parametric optimization and thermodynamic performance comparison of single-pressure and dual-pressure evaporation Organic Rankine Cycles. Appl Energy2018; 217: 409–421.
10.
SongJGuC-wRenX. Influence of the radial-inflow turbine efficiency prediction on the design and analysis of the Organic Rankine Cycle (ORC) system. Energy Convers Manag2016; 123: 308–316.
11.
SongJGuC-wLiX-s. Performance estimation of Tesla turbine applied in small scale Organic Rankine Cycle (ORC) system. Appl Therm Eng2017; 110: 318–326.
12.
SongJGuC-w. 1-D model analysis of tesla turbine for small scale Organic Rankine Cycle (ORC) system. In: ASME Turbo Expo 2017: turbomachinery technical conference and exposition, New York: American Society of Mechanical Engineers, pp. V003T28A003–V003T28A003.
13.
Da LioLManenteGLazzarettoA. A mean-line model to predict the design efficiency of radial inflow turbines in organic Rankine cycle (ORC) systems. Appl Energy2017; 205: 187–209.
14.
PreißingerMSchatzSVoglA, et al.Thermoeconomic analysis of configuration methods for modular Organic Rankine Cycle units in low-temperature applications. Energy Convers Manag2016; 127: 25–34.
15.
PreißingerMBrüggemannD. Thermoeconomic evaluation of modular organic Rankine cycles for waste heat recovery over a broad range of heat source temperatures and capacities. Energies2017; 10: 269–269.
16.
ZhangSWangHTaoG, et al.Performance comparison and parametric optimization of subcritical Organic Rankine Cycle (ORC) and transcritical power cycle system for low-temperature geothermal power generation. Appl Energy2011; 88: 2740–2754.
17.
Al JuboriAMAl-DadahRMahmoudS. Performance enhancement of a small-scale organic Rankine cycle radial-inflow turbine through multi-objective optimization algorithm. Energy2017; 131: 297–311.
18.
BahadormaneshNRahatSYaraliM. Constrained multi-objective optimization of radial expanders in organic Rankine cycles by firefly algorithm. Energy Convers Manag2017; 148: 1179–1193.
19.
MaaloufSKsayerEBClodicD. Investigation of direct contact condensation for wet flue-gas waste heat recovery using Organic Rankine Cycle. Energy Convers Manag2016; 107: 96–102.
20.
BaqirASMahoodHBHameedMS, et al.Heat transfer measurement in a three-phase spray column direct contact heat exchanger for utilisation in energy recovery from low-grade sources. Energy Convers Manag2016; 126: 342–351.
21.
LiuXGongJZhangZ, et al.An image analysis technique for the particle mixing and heat transfer process in a pan coater. Powder Technol2016; 295: 161–166.
22.
AliSHabchiCMenanteauS, et al.Three-dimensional numerical study of heat transfer and mixing enhancement in a circular pipe using self-sustained oscillating flexible vorticity generators. Chem Sci Eng2017; 162: 152–174.
23.
LiuH-lLiHHeY-l, et al.Heat transfer and flow characteristics in a circular tube fitted with rectangular winglet vortex generators. Int J Heat Mass Transf2018; 126: 989–1006.
24.
HimoRHabchiC. Coherent flow structures and heat transfer in a duct with electromagnetic forcing. Phys Fluid2018; 30: 043605–043605.
25.
XiaoQPanJLvZ, et al.Measure of bubble non-uniformity within circular region in a direct-contact heat exchanger. Int J Heat Mass Transf2017; 110: 257–261.
26.
HuangJXuJSangX, et al.Quantifying the synergy of bubble swarm patterns and heat transfer performance using computational homology. Int J Heat Mass Transf2014; 75: 497–503.
27.
HawladerMNAWahedMA. Analyses of ice slurry formation using direct contact heat transfer. Appl Energy2009; 86: 1170–1178.
28.
WangYLiuXDingX, et al.Experimental investigation on the performance of ORC power system using zeotropic mixture R601a/R600a. Int J Energy Res2017; 41: 673–688.
29.
XiaoQYangKWuM, et al.Complexity evolution quantification of bubble pattern in a gas-liquid mixing system for direct-contact heat transfer. Appl Therm Eng2018; 138: 832–839.
30.
FuHWangYHuangQ, et al.Direct contact evaporation heat transfer coefficient and drobble size distribution in a 2D column. Appl Therm Eng2016; 96: 568–575.
31.
JinYHuRWangY, et al.The effect of Dixon rings on direct contact heat transfer performance: comparison of counter and co-current evaporation. Appl Therm Eng2017; 117: 762–772.
32.
LiuXZhangCZhanJ. Quantitative comparison of image analysis methods for particle mixing in rotary drums. Powder Technol2015; 282: 32–36.
33.
BaqirASMahoodHBCampbellAN, et al.Measuring the average volumetric heat transfer coefficient of a liquid–liquid–vapour direct contact heat exchanger. Appl Therm Eng2016; 103: 47–55.
34.
AbdulrahmanM. CFD simulations of direct contact volumetric heat transfer coefficient in a slurry bubble column at a high gas temperature of a helium–water–alumina system. Appl Therm Eng2016; 99: 224–234.
35.
XiaoQTPanJXXuJX, et al.Hypothesis-testing combined with image analysis to quantify evolution of bubble swarms in a direct-contact boiling heat transfer process. Appl Therm Eng2016; 113: 851–857.
36.
XiaoQGaoQZhangJ, et al.Extraction and evolution of bubbles attributes in a two-phase direct contact evaporator. Int J Heat Mass Transf2018; 124: 761–768.
37.
HuangJXiaoQLiuJ, et al.Modeling heat transfer properties in an ORC direct contact evaporator using RBF neural network combined with EMD. Energy2019; 173: 306–316.
38.
Gameiro M, Mischaikow K and Wanner T. Evolution of pattern complexity in the Cahn – Hilliard theory of phase separation. Acta Materialia 2005; 53: 693–704.
39.
Huang J. Research on heat transfer performance and optimization of ORC direct contact steam generator. PhD Thesis, Kunming University of Science and Technology, China, 2013.
40.
FinnieGJKruytNYeM, et al.Longitudinal and transverse mixing in rotary kilns: a discrete element method approach. Chem Sci Eng2005; 60: 4083–4091.
