Authors: Mostafa H. Sharqawya,b, John H. Lienhard Va,*, Syed M. Zubairb
aNDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA
bCDepartment of Mechanical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
Summary
Exergy analysis is a powerful way to evaluate thermal system performance. Use of this technique is growing in desalination systems. The maximum amount of work which we can obtain from a system when it is brought to the state of environment from its initial state represents exergy. The system is considered to be at zero exergy when it reaches to the dead state which is the state of the environment. Seawater systems are comprised of water and different salts but in experiments and studies, an equivalent amount of sodium chloride is used to prepare solution. Properties of water, the solid (sodium chloride), and the solution can be found from the literature. The exergy of the system can be found using the following equation.
Solution to this equation for different conditions gives exergy for the given input conditions. To solve this equation, a problem exists which is the non-ideality of solution. To overcome this problem, an ideal gas mixture model is used. In this way, the exergy will have negative values at pressure less than the pressure of the dead state or that of the environment. Using thermodynamic properties, we can compute exergy. Correlations of seawater thermodynamics properties are used to compute exergy. The variation of seawater exergy as a function of pressure, temperature and salt concentration are calculated in a closed form of an ideal gas mixture. This model treated seawater as an ideal mixture of pure water and sodium chloride salt. It was found that the model considering the system as the ideal gas mixture shows unrealistic flow exergy and second law efficiency differs about 80% of the actual value. It shows that the analysis performed using this model is far from the correct value. This paper also shows that if the hypothesis is proved wrong, we can contribute this information to the scientific society for the improvement in model.
Reviewer: Aamir Alaud-din
aamiralauddin@gist.ac.kr