ANS:A - Ponchan-Savarit method is more accurate than McCabe-Thiele method to determine the number of theoretical stages required for the separation of non-ideal binary system by distillation.

The Ponchon-Savarit method and the McCabe-Thiele method are both techniques used to analyze distillation processes and determine the number of theoretical stages required for separation. However, they have different approaches and applicability depending on the characteristics of the system.

1. McCabe-Thiele Method:
   • The McCabe-Thiele method is a graphical approach primarily used for ideal binary distillation systems.
   • It relies on constructing equilibrium and operating lines on a graphical plot (McCabe-Thiele diagram) to determine the number of theoretical stages required for separation.
   • It assumes ideal behavior, such as constant relative volatility and ideal liquid and vapor phase behavior.
2. Ponchon-Savarit Method:
   • The Ponchon-Savarit method is a rigorous graphical and numerical technique used to analyze distillation processes, including non-ideal systems.
   • It accounts for non-idealities such as variable relative volatility, non-linear equilibrium curves, and non-constant molar overflow.
   • It involves iterative calculations and graphical representations to determine the number of theoretical stages and other design parameters.
   • The method is more complex and computationally intensive compared to the McCabe-Thiele method but provides more accurate results for non-ideal systems.

Comparison:

• The Ponchon-Savarit method is indeed more accurate than the McCabe-Thiele method when dealing with non-ideal binary systems. Its ability to handle non-idealities makes it suitable for a wider range of separation processes.
• However, the Ponchon-Savarit method requires more computational effort and is often more complex to apply compared to the simpler graphical approach of the McCabe-Thiele method.

In summary, while both methods are valuable tools for distillation analysis, the Ponchon-Savarit method is preferred for systems with significant non-idealities, where accuracy is paramount, albeit at the cost of increased computational complexity.