TURING MACHINE APPROACH TO SOLVE PSYCHROMETRIC ATTRIBUTES

A technique for selecting psychrometric equations and their solution o rder is presented. The solution order for a given psychrometric proble m is not always readily identifiable. Furthermore, because the psychro metric equations can be solved in many different sequences, the soluti on process can become convoluted. For example, if atmospheric pressure , dry-bulb temperature and relative humidity are known and it is desir ed 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 task of identifying these many possible combinations of equations, and selecting an appropriate one, is called a decision problem in computation theory. One technique for solving decision problems is a Turing machine computational model. We have constructed a Turing machine which we refer to as a Psychrometric Turing Machine (PTM), to solve all possible psychrometric problems. T he PTM selects the optimal equation order based upon a user-specified optimality criterion of CPU cycles. A solution is comprised of a serie s of functions based on equations found in the 1993 ASHRAE Handbook-Fu ndamentals. The PTM is shown to be a practical application to a non-de terministic, multiple-path problem. It required 700 ms on an engineeri ng workstation (100 MHz, Spare 10) to search all possible combinations and determine the optimal solution route for the most complicated ''t wo-to-all'' psychrometric problem. For a particular psychrometric prob lem, once the equation order is found, these equations cart be used to determine the unknown attributes from the known attributes in a consi stent manner that is in some sense optimal. We demonstrate the applica tion of the PTM with several examples: a psychrometric calculator a so urce code generator; and a. listing of the optimal function call seque nce for most ''two-to-all'' psychrometric problems encountered.