Experimental and Numerical Analysis of a PCM-Supported ...

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temperature is at its maximum level, and moves downwards due to stratification of both liquid and gas phases as well as the low effective thermal conductivity of PCM along the packing height. Thereafter, a sensible heat component increases the PCM temperature until reaching the steady state conditions. Since the melting front moves in time downward in the bed, this looks like propagating waves or a “sea snake” rising up from the bottom. Little peaks of temperatures above the melting range can be observed near the top of the bed, these may represent some locations just around the breakeven points during the transient period with the gas phase temperature profile (reference is made to figure 5.4), and perhaps also due to melting of PCM over a mushy region rather than a sharp melting front. Table 6.4: Inlet and geometrical parameters within a sample simulation run Parameter Value Units Inlet water temperature 358 K Water flow rate 400 l/hr Packed height 0.39 m Column diameter 0.4 m Inlet and initial air temperature 298 K Initial PCM temperature 298 K Air velocity 0.13 m/s Figure (6.7) shows the temperature history of liquid water along the packing height. The water temperature decreases through its path from top to bottom, where it reaches the minimum. The outlet water temperature increases over time due to continuous decrease in the temperature difference and heat transfer rates between water and both gas and solid phases. Figures (6.8) and (6.9) represent the temperature and concentration fields respectively of the gas phase during simultaneous heating and humidification processes. It can be seen from the figure that the concentration also increases with time and packed bed height, to reach its maximum value of 21mol/m 3 . The time evolution and final profiles of the fluid temperatures and concentration fields is really governed by the existence of a conductive packing medium and its thermophysical properties, otherwise the system would behave stationary and reach steady state in a very short time like other distillation columns and cooling towers packed with non-conductive media. 6.5 Conclusions In this chapter, the numerical solution procedures and strategy were introduced and applied for solving the governing energy and mass balances of the evaporator mathematical model as an example. Geometric representation of the complex packed bed geometry was replaced by representation of uni-dimensional domain. This enabled to solve the mathematical model both in COMSOL Multiphysics and 137
MATLAB using the approach of “Inter-penetrating Continua” based on the “volume averaging technique”. The simulation models for different components have been verified upon realizing a wide variety of experimentation results. Comparison with the experimentation results indicated good agreement between predicted and measured parameters. Some important lessons have been learned from the validation experiments. Based on the experimental results, the most appropriate empirical correlations for the model have been defined. This allowed more control on various influencing parameters and was projected on the main HDH system’s model which will be used as the main tool for numerical optimization. The individual components models as well as the lumped simulation model for the HDH plant may be regarded as real predictive models for their associated physical systems. On the other hand, for getting more insight and better understanding of various transport phenomena that take place in the system, extra sample of the numerical results were presented. Analysis of the sample results gave more insight in the system behavior and ascertained the role of thermal energy management of the conductive packing media. Bottom Top Figure 6.6: Time evolution of PCM temperature along the packed height 138
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Technische Universität München In
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It is my pleasure to thank Prof. Th
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Contents List of figures ..........
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5.3 Functional description ........
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List of Figures Figure 1.1: Cost br
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78cm; Top: Evaporator, Bottom: Cond
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xii
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m Mass flow rate; [kg.s -1 ] m eva
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ed c coll cond cw d d e or eff evap
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1 Introduction The first part of th
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summarized in figure (1.2). Thermal
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1.3.2 Selection criteria of desalin
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of energy storage or hybridization
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Desalination development focuses on
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Introduction of the indirect type s
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2 Literature Survey 2.1 Introductio
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There is actually a commercial prod
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Q m H c ( T T1) c ( T 2 T ) (2.2)
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(solid-liquid) have a storage densi
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(iii) a sharp melting temperature.
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melt and freeze without segregation
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However, the stored heat is less va
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parameters on the heat transfer and
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categories. The first category is b
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to 550 kWh/m 3 of distilled water a
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The enthalpy and humidity of the sa
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Air mass flow rate [kg/h] GOR [-] 1
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On the other hand, the efficiency o
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2.8.4.2 Effect of air to water mass
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distillate rate. The system was not
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were; EnviPac Gr.1, 32 mm, and VFF
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Figure 2.15: Height versus air temp
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The performance of the condenser is
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Klausner and Mei [136] described a
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The impact of the collector cost ca
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exchanger and energy storage in one
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3 Scope of the Study This chapter p
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packing where it gets in direct con
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In fact there is a tradeoff between
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The energy flow between all and eac
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4 Theoretical Analysis and Modeling
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The two-energy equation models whic
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solid-liquid phase change inside th
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assumed by conduction in both axial
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the air pressure drop ∆P per unit
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evaporation rate per unit volume of
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where β t , β c , ρ ref , c ref
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the viscous transport and introduce
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liquid and solid phases, respective
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4.2.3.3 Liquid and gas hold-ups Liq
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Several models and approaches for m
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where G=ρU d /ε g is the pore mas
Page 106 and 107: k k eff s 1 3 2 (4.55) This cor
Page 108 and 109: uncertainties associated with the f
Page 110 and 111: 1 2 (4.62) d1 capp c2 c1 c2 1
Page 112 and 113: [58] evaluated the cooling tower ai
Page 114 and 115: 1 exp NTU 1 C r, cond cond (4
Page 116 and 117: A HE QHE U T HE LM (4.81) Where Q
Page 118 and 119: c M f b (4.86) M b S S f where r
Page 120 and 121: that form the study logical foundat
Page 122 and 123: 5 Experimental Analysis This chapte
Page 124 and 125: 5.2 Measuring Techniques K-type the
Page 126 and 127: The product condensed water was mea
Page 128 and 129: operating limits. In light of the l
Page 130 and 131: In the last two cases, the inlet ho
Page 132 and 133: performance and its threshold value
Page 134 and 135: It could be interpreted that this p
Page 136 and 137: Evaporator Condenser Figure 5.8: Av
Page 138 and 139: within the inaccuracy margins. The
Page 140 and 141: The last two cases of boundary cond
Page 142 and 143: natural air flow in the system. In
Page 144 and 145: 6 Model Implementation and Validati
Page 146 and 147: x t u x u 0 0 , (6.5) and for a s
Page 148 and 149: Next time step validation were the
Page 150 and 151: The evaporator and condenser both w
Page 152 and 153: Figure 6.2: Evolution of inlet and
Page 154 and 155: Figure 6.4: Evolution of inlet and
Page 158 and 159: Bottom Top Figure 6.7: Evolution of
Page 160 and 161: 7 Parameters Analysis of the Evapor
Page 162 and 163: Figure 7.1: Effect of packing size
Page 164 and 165: e 0.45 kPa under natural convection
Page 166 and 167: aspect ratio under constant bed vol
Page 168 and 169: Figure 7.7: Effect of inlet hot wat
Page 170 and 171: well as the time required to reach
Page 172 and 173: Figure 7.10: Effect of packing medi
Page 174 and 175: 40°C respectively. This gives flex
Page 176 and 177: the condensate rate, productivity f
Page 178 and 179: esult, rather than PCM media which
Page 180 and 181: Figure 7.18: Effect of PCM thermal
Page 182 and 183: 8 Optimization of HDH plant In this
Page 184 and 185: The MATLAB model describes how the
Page 186 and 187: less steep than that of the distill
Page 188 and 189: 8.3.4 Effect of hot water flow rate
Page 190 and 191: storage materials and thus it can h
Page 192 and 193: for latent heat storage would be ob
Page 194 and 195: When T m becomes sufficiently highe
Page 196 and 197: 9 Summary and conclusions 9.1 Summa
Page 198 and 199: productivities at any cooling water
Page 200 and 201: [13] Vafai K., Sozen M. An investig
Page 202 and 203: [48] Crone S., Bergins C., and Stra
Page 204 and 205: [79] Tiwari G.N. and Yadav Y.P. (78
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[109] Mehling H., Hiebler S. and Zi
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[139] Belessiotis V, Delyannis E (2
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Appendices Appendix A A1. PCM Therm
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A3. Constants and Thermo-physical p
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From the above correlation, the con
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The Ergun analogy factor J h repres
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Equation (C.7) represents an overal
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Appendix D D1. Cooling tower theory
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A m w = the plan or cross sectiona
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