TURING MACHINE APPROACH TO SOLVE PSYCHROMETRIC ATTRIBUTES
H. Zhang, Richard S. Gates, D. G. Colliver · Transactions of the ASAE · 1997
A technique for selecting psychrometric equations and their solution order is presented. The solution order fora given psychrometric problem is not always readily identifiable. Furthermore, because the psychrometric equations canbe solved in many different sequences, the solution process can become convoluted. For example, if atmospheric pressure,dry-bulb temperature and relative humidity are known and it is desired to determine the other 12 psychrometric attributes,then there are approximately 37,780 different orders in which to solve the equations to determine the other parameters.The tasks of identifying these many possible combinations of equations, and selecting an appropriate one, is called adecision problem in computation theory. One technique for solving decision problems is a Turing machine computationalmodel. We have constructed a Turing machine which we refer to as a Psychrometric Turing Machine (PTM), to solve allpossible psychrometric problems. The PTM selects the optimal equation order based upon a user-specified optimalitycriterion of CPU cycles. A solution is comprised of a series of functions based on equations found in the 1993 ASHRAEHandbookFundamentals. The PTM is shown to be a practical application to a non-deterministic, multiple-pathproblem. It required 700 ms on an engineering workstation (100 MHz, Sparc 10) to search all possible combinations anddetermine the optimal solution route for the most complicated two-to-all psychrometric problem. For a particularpsychrometric problem, once the equation order is found, these equations can be used to determine the unknownattributes from the known attributes in a consistent manner that is in some sense optimal. We demonstrate the applicationof the PTM with several examples: a psychrometric calculator, a source code generator, and a listing of the optimalfunction call sequence for most two-to-all psychrometric problems encountered.