TURING MACHINE APPROACH TO SOLVE PSYCHROMETRIC ATTRIBUTES
| Autor: | Donald G. Colliver, Hanzhong Zhang, Richard S. Gates |
|---|---|
| Rok vydání: | 1997 |
| Předmět: |
Mathematical optimization
Sequence Source code Optimality criterion Computer science media_common.quotation_subject Subroutine Decision problem Agricultural and Biological Sciences (miscellaneous) Turing machine symbols.namesake Theory of computation symbols Algorithm media_common Generator (mathematics) |
| Zdroj: | Transactions of the ASAE. 40:823-831 |
| ISSN: | 2151-0059 |
| DOI: | 10.13031/2013.21292 |
| Popis: | A technique for selecting psychrometric equations and their solution order is presented. The solution order for a given psychrometric problem is not always readily identifiable. Furthermore, because the psychrometric equations can be 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 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. The PTM selects the optimal equation order based upon a user-specified optimality criterion of CPU cycles. A solution is comprised of a series of functions based on equations found in the 1993 ASHRAE Handbook—Fundamentals. The PTM is shown to be a practical application to a non-deterministic, multiple-path problem. It required 700 ms on an engineering workstation (100 MHz, Sparc 10) to search all possible combinations and determine the optimal solution route for the most complicated “two-to-all” psychrometric problem. For a particular psychrometric problem, once the equation order is found, these equations can be used to determine the unknown attributes from the known attributes in a consistent manner that is in some sense optimal. We demonstrate the application of the PTM with several examples: a psychrometric calculator, a source code generator, and a listing of the optimal function call sequence for most “two-to-all” psychrometric problems encountered. |
| Databáze: | OpenAIRE |
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