Nearly 30% of the input energy to a diesel engine is wasted through the exhaust gas; thus, considerable attention has been directed toward developing efficient heat recovery systems for these engines. Given the demonstrated ability of nanofluids to boost the heat transfer rate of heat exchangers, these heat transfer fluids merit consideration for use in diesel exhaust heat recovery systems. In this study, the effects of employing nanofluids on the optimum design of these systems are investigated. An existing heat diesel engine exhaust heat recovery system is modeled to work with Al2O3/water and a modified imperialist competitive algorithm is employed for the optimization. Seven variables consisting of five heat exchanger geometric characteristics together with nanoparticle volume fraction and coolant mass flow rate are considered as design variables. The heat exchanger cost and charging rate of the storage tank are optimization objectives, while the greenhouse gas savings of the heat recovery system are assessed for measuring the environmental impact of the energy recovery. The results indicate that the proposed approach can overcome the challenge of finding the near-optimal design of this complex system and using nanofluids enhances the performance of the heat recovery heat exchanger.
PandiyarajanVPandianMCMalanEet al.Experimental investigation on heat recovery from diesel engine exhaust using finned shell and tube heat exchanger and thermal storage system. Appl Energ2011; 88: 77–87.
2.
AgudeloAFGarcía-ContrerasRAgudeloJRet al.Potential for exhaust gas energy recovery in a diesel passenger car under European driving cycle. Appl Energ2016; 174: 201–212.
3.
GhazikhaniMHatamiMGanjiDDet al.Exergy recovery from the exhaust cooling in a DI diesel engine for BSFC reduction purposes. Energy2014; 65: 44–51.
4.
HatamiMBootMGanjiDet al.Comparative study of different exhaust heat exchangers effect on the performance and exergy analysis of a diesel engine. Appl Therm Eng2015; 90: 23–37.
5.
HatamiMGanjiDGorji-BandpyM. Experimental investigations of diesel exhaust exergy recovery using delta winglet vortex generator heat exchanger. Int J Therm Sci2015; 93: 52–63.
6.
HatamiMGanjiDGorji-BandpyM. Experimental and numerical analysis of the optimized finned-tube heat exchanger for OM314 diesel exhaust exergy recovery. Energ Convers Manage2015; 97: 26–41.
7.
YousefiMKimJHHooshyarDet al.A practical multi-objective design approach for optimum exhaust heat recovery from hybrid stand-alone PV-diesel power systems. Energ Convers Manag2017; 142: 559–573.
8.
YangFZhangHSongSet al.Thermoeconomic multi-objective optimization of an organic Rankine cycle for exhaust waste heat recovery of a diesel engine. Energy2015; 93: 2208–2228.
9.
ReginAFSolankiSSainiJ. An analysis of a packed bed latent heat thermal energy storage system using PCM capsules: numerical investigation. Renew Energ2009; 34: 1765–1773.
10.
HadidiAHadidiMNazariA. A new design approach for shell-and-tube heat exchangers using imperialist competitive algorithm (ICA) from economic point of view. Energ Convers Manage2013; 67: 66–74.
11.
YousefiMHooshyarDKimJHet al.Modeling and thermo-economic optimization of a biomass heat recovery exchanger operating on Al2O3-water nanofluid. Int Commun Heat Mass Trans2017; 82: 63–73.
12.
GargJet al.Enhanced thermal conductivity and viscosity of copper nanoparticles in ethylene glycol nanofluid. J Appl Phys2008; 103: 074301–074301.
13.
GargPAlvaradoJLMarshCet al.An experimental study on the effect of ultrasonication on viscosity and heat transfer performance of multi-wall carbon nanotube-based aqueous nanofluids. Int J Heat Mass Trans2009; 52: 5090–5101.
14.
AghabozorgMHRashidiAMohammadiS. Experimental investigation of heat transfer enhancement of Fe2O3-CNT/water magnetic nanofluids under laminar, transient and turbulent flow inside a horizontal shell and tube heat exchanger. Exp Therm Fluid Sci2016; 72: 182–189.
15.
AhmedHEAhmedMYusoffM. Heat transfer enhancement in a triangular duct using compound nanofluids and turbulators. Appl Therm Eng2015; 91: 191–201.
16.
GoodarziMet al.Investigation of heat transfer performance and friction factor of a counter-flow double-pipe heat exchanger using nitrogen-doped, graphene-based nanofluids. Int Commun Heat Mass Trans2016; 76: 16–23.
17.
HuangDWuZSundenB. Pressure drop and convective heat transfer of Al2O3/water and MWCNT/water nanofluids in a chevron plate heat exchanger. Int J Heat Mass Transf2015; 89: 620–626.
18.
KarimzadehkhoueiMYalcinSEŞendurKet al.Pressure drop and heat transfer characteristics of nanofluids in horizontal microtubes under thermally developing flow conditions. Exp Therm Fluid Sci2015; 67: 37–47.
RajaMVijayanRDineshkumarPet al.Review on nanofluids characterization, heat transfer characteristics and applications. Renew Sust Energ Rev2016; 64: 163–173.
21.
KernDQ. Process heat transfer, New York: Tata McGraw-Hill Education, 1950.
22.
ZhaiYXiaGLiuXet al.Heat transfer enhancement of Al2O3-H2O nanofluids flowing through a micro heat sink with complex structure. Int Commun Heat Mass Trans2015; 66: 158–166.
23.
LeongKSaidurRMahliaTet al.Modeling of shell and tube heat recovery exchanger operated with nanofluid based coolants. Int J Heat Mass Trans2012; 55: 808–816.
24.
WaspEJKennyJPGandhiRL. Solid–liquid flow: slurry pipeline transportation. [Pumps, valves, mechanical equipment, economics]. Ser Bulk Mater Handl1977; 1. Conference on 25–28 September 2007, Singapore, Singapore.
25.
HamiltonRCrosserO. Thermal conductivity of heterogeneous two-component systems. Ind Eng Chem Fund1962; 1: 187–191.
26.
BrinkmanH. The viscosity of concentrated suspensions and solutions. J Chem Phys1952; 20: 571–571.
27.
BashirnezhadKet al.Viscosity of nanofluids: a review of recent experimental studies. Int Commun Heat Mass Trans2016; 73: 114–123.
28.
AminiMBazarganM. Two objective optimization in shell-and-tube heat exchangers using genetic algorithm. Appl Therm Eng2014; 69: 278–285.
29.
SinnottR. Chemical engineering design, Coulson & Richardson’s chemical engineering series2005; vol 6, Oxford: Elsevier Butterworth Heinemann.
30.
Wasp EJ, Kenny JP and Gandhi RL. Solid -liquid flow: slurry pipeline transportation. [Pumps, valves, mechanical equipment, economics]. Ser Bulk Mater Handl (United States) 1977; 1:4.
31.
YousefiMYousefiMDarusAN. A modified imperialist competitive algorithm for constrained optimization of plate-fin heat exchangers. Proc IMechE, Part A: J Power and Energy2012; 226: 1050–1059.
32.
TaalMBulatovIKlemešJet al.Cost estimation and energy price forecasts for economic evaluation of retrofit projects. Appl Therm Eng2003; 23: 1819–1835.
33.
Mayer A. Number-based emission limits, VERT-DPF-verification procedure and experience with 8000 retrofits. VERT, Switzerland, 2004.
34.
U.S Energy Information Administration, www.eia.gov (accessed 8 November 2017).
35.
YousefiMHooshyarDAhmadRBet al.A practical review on the application of constraint handling strategies in evolutionary computation from an engineering point of view. Int Rev Model Simul2015; 8: 75–83.
