Fundamental physics drive Exergy which is based the lifetime research of the late  Dr Eli Yasni carried out at Technion University in Israel, Otago University in New Zealand and power stations around the world.

The physics in a nutshell;

• Requires all physical laws, conservation and balance equations to be obeyed

• Combines insights and research from many recognised thermodynamics experts

• Assesses the work available from the plant cycle under a reversible thermodynamic cycle using second law relationships and measured plant parameters.  

• There is a lot of current research published that concentrates on Exergy as a thermodynamic analysis tool making the industry familiar with the concepts but none that matched the insights of the patents

• It uses the proven (by Dr Yasni using rigorous mathematical proof) fact that reversible and irreversible cycles can map into each other based on boundary conditions when considered in geometric space – a process Dr Yasni called reversible mapping and a technique (also covered in the patent) to allow minimization of irreversible losses

• Uses conventional minmax optimisation techniques to find the optimum operating parameters for an equivalent reversible system that includes a mechanism to represent plant losses

• Takes the boundary conditions of the optimised reversible system and applies them to the real plant which results in power output being maximised for the real time conditions.

Because the results are based on rigorous analysis the recommendations for settings sometimes seem unusual or against common practice but because they are different from established practice they provide a distinct and significant competitive advantage to the plant owner

The Exergy analysis framework consists of a number of phases starting with phases that are high on specially written code and plant dependence with minimal unique IP and able to do done by competent power station engineers, through to phases with very high IP values and no specially written code for the plant (i.e. not dependent on specific plant characteristics) but requiring advanced mathematical understanding.  There is the potential to industrialise the first phases with the right skills and programmers.