S.C. Kaushik

Computer-aided conceptual thermodynamic design of a two-stage dual fluid absorption cycle for solar refrigeration

Abstract This communication presents thermodynamic assessment of a two-stage dual fluid absorption refrigeration system using H 2 OLiBr and NH 3 H 2 O as working fluids at the first and second stage, respectively. Both stages are assumed to be operated with hot water available from separate solar collectors. In the cascading of two-stage absorption systems, the evaporator of the first stage produces cooling water which is circulated in the absorber of the second stage. It is found that two-stage systems can be used for the production of very low temperatures using moderate generator temperatures at the first stage. The effects of generator temperature, absorber temperature and condenser temperature on the coefficient of performance, minimum evaporator temperature and effective refrigeration produced are also presented.

Thermodynamic feasibility of an absorber heat recovery cycle for solar airconditioning

Abstract A feasibility analysis of a water-lithium bromide absorber heat recovery (AHR) absorption cooling system, suitable for solar airconditioning is presented. In the proposed system the absorber heat (which is usually rejected to the surroundings in the conventional H2OLiBr system) could be utilized to some extent for reducing the heat input requirement at the generator and hence improving the coefficient of performance. The analysis was carried out for the production of 278 K and 283 K evaporator temperatures with identical condenser and absorber temperatures of 303 K. The effects of generator temperature, condenser and absorber temperatures on the coefficient of performance and relative circulation are discussed. It is concluded that an absorber heat recovery cycle yields a higher COP as compared to the basic cycle at higher generator temperatures, unlike aqua-ammonia absorption systems.

Modeling and simulation studies on single/double-effect absorption cycle using water-multicomponent salt (MCS) mixture☆

Abstract This communication presents an investigation on modeling and simulation studies of single/double-effect absorption cooling systems using a water-multicomponent salt mixture vis-a-vis waterLiClCaCl2Zn(NO3)2 solution as a working fluid. The computer modeling/simulation is based on mass, material, and heat balance equations for each component of the system. Effects of different input variables used for the computer modeling and simulation studies are investigated and a detailed parametric study of the double-effect cycle is carried out. A comparative study of the water-multicomponent salt (MCS) mixture and the conventional waterLiBr mixture is also presented for both single-stage and double-effect absorption cycles. It is found that the cooling COP of the double-effect cycle is nearly twice that of the single-stage cycle for both of the working fluids under the same operating conditions. The COP is higher for the water-multicomponent salt (MCS) mixture than for the waterLiBr case. The system feasibility and constraints are also discussed.

Multi-objective optimization of two stage series connected thermo-electric generator using genetic algorithm

Two-stage thermoelectric generator in exo-reversible mode is thermodynamically optimized in view of finite time thermodynamics (FTT) and multi-objective genetic algorithm (MOGA). Electrically series configuration with only internal irreversibilities of thermoelectric generator has been considered for investigation in the current research. Power output and thermal efficiency of the aforementioned system are considered as dual objective functions obtained from FTT technique. These two objectives are maximized at the same time with the use of multi objective genetic algorithm. For MOGA optimization of thermoelectric generator, five decision variables as number of thermoelectric element pairs at the bottom and top stage as m and n, heat source temperature and heat sink temperature and working electric current has been considered in the current study. MATLAB environment is used to obtain the Pareto Optimal frontier between power output and thermal efficiency and their best optimal values are selected by Fuzzy Bellman-Zadeh decision making technique. A comparative analysis of single objective and dual objective optimization of aforementioned objectives has been carried out and discussed.

Simulation model and thermodynamic design of an advanced absorption heat pump for solar space heating

Abstract This paper presents a simulation model and design aspects of an advanced absorption heat pump suitable for solar space heating. The system consists of two stage refrigerant vapour generation within the absorption cycle along with two heat recuperators between these generators and the absorber. During heat pump operation, the evaporator absorbs heat at low temperature from the outside atmospheric air, while heat rejected by the absorber and condenser is used to warm the interior air of the space to be heated. A conceptual thermodynamic design based on a simulation model satisfying heat, mass and material balance equations for each of the system components has been obtained for the improved absorption heat pump system. The simulation model employing input heat supply, pumping power and ambient conditions as input variables is capable of predicting the heat pump performance under optimum design and off-design conditions. It is found that the proposed heat pump system is thermodynamically feasible for solar space heating for a wide range of operating parameters and ambient conditions.

Thermodynamic modelling and analysis of thermoelectric cooling system

Exergy analysis has gained significance in analysing the thermal energy systems since it locates and quantifies the irreversibilities in the system. This paper investigates the thermoelectric cooler through exergy analysis. Four thermodynamic models of the thermoelectric cooler considering the internal and external irreversibilities are developed with temperature dependent material properties and then analysed in MATLAB Simulink environment for various operating temperatures. Moreover, analytical expressions for exergy efficiency and irreversibilities for the thermoelectric cooler are developed. The results show that the exergy efficiency of the thermoelectric cooler is lower than the energy efficiency for all thermodynamic models. For a typical operating condition in the irreversible thermoelectric cooler with 31 thermocouples and with TH and TC of 303K and 293K respectively, the maximum energy and exergy efficiency obtained are 2.61 and 8.91% at optimum current of 5.88A. The results also shows that the effect of internal irreversibilities is more pronounced than the external irreversibilities in the performance of thermoelectric cooling system. The effects of irreversible heat transfer and the contact resistance in the exergy efficiency are also studied. This study will be helpful in designing the actual thermoelectric cooling systems.

Multi-objective optimization of thermo-electric heat pump using genetic algorithm and fuzzy Bellman-Zadeh decision making

An exo-reversible two-stage thermoelectric heat pump is thermodynamically optimized in consideration of finite time thermodynamics and multi-objective optimization using non-dominated sorted genetic algorithm (NSGA) approaches. The two stages of thermoelectric heat pump are assumed to be in electrically series configuration and only internal irreversibilities for the above mentioned system has been taken into consideration. Heating capacity (Qh) and Coefficient of Performance (COP) of the system are taken as dual objective functions, which are derived by FTT approach. These two objectives are maximized concurrently using NSGA. Authors have considered five decision variables as working electric current (I), number of thermoelectric element pairs at the top and bottom stage as n and m, heat source temperature (Th) and heat sink temperature (Tc) for multi-objective optimization of thermoelectric heat pump. MATLAB environment is used to obtain the Pareto Optimal frontier between COP and heating capacity and their best optimal values are selected by Bellman-Zadeh decision making technique. A comparative analysis of single objective and dual objective optimization of aforementioned objectives has been carried out along with along with the effect of various performance parameters on dual objective analysis are discussed and presented graphically.

Multi-objective optimization of an irreversible regenerative Brayton cycle using genetic algorithm

An irreversible regenerative Brayton cycle is thermodynamically optimized in the view of finite time thermodynamic (FTT) and multi-objective genetic algorithm (MOGA) approaches. Power output and thermal efficiency of the model are considered as dual objective functions. These two objectives for a given model are derivedusing FTT approach. Maximization of two objectives is done at the same time using MOGA. Five decision variables such as effectiveness of source-side heat exchanger, effectiveness of sink-side heat exchanger, effectiveness of regenerator-side heat exchanger, source temperature, and temperature of the working fluid are considered. Pareto optimal frontier between power output and thermal efficiency is obtained in MATLAB environment. The best optimal values of power output and thermal efficiency are selected from Pareto frontier using TOPSIS, LINMAP and Shannon Entropy decision making methods. Moreover, results obtained from three decision making methods are compared and best amongst them are selected. Finally, effect of various performance parameters on dual objectives are discussed and presented on graphs.

Multi-objective optimization of solar powered ericsson cycle using genetic algorithm and fuzzy decision making

Solar driven Ericsson heat engine has been considered for multi-objective thermodynamic optimization. Multi-objective genetic algorithm (MOGA) and finite time thermodynamic (FTT) approaches are implemented for optimization of power output and thermal efficiency which are considered as objectives in the study. Simultaneous optimization of power output and thermal efficiency are achieved using evolutionary algorithm based on MOGA. Various effectiveness of heat exchangers and temperatures of source and sink side working fluid are considered as decision variables. Pareto front between dual objectives is found in MATLAB 7.8. Further, Fuzzy Bellman-Zadeh decision making method is used to extract best optimal values of dual objective. Simultaneous optimization of power output and thermal efficiency of proposed model is obtained at optimal values of source side heat exchanger effectiveness, sink side heat exchanger effectiveness, regenerator side heat exchanger effectiveness, and source side working fluid and sink side working fluid as 0.79, 0.79, 0.88, 901 K and 436 K respectively.