Abstract
We would approach the problem of optimization quoting some lines of the single book of artificial intelligence that we know to be written for thermal systems [2]:
“The term optimization is one of the most misused concepts in the field of Engineering. When reading a technical report about some “optimization” performed on a process or a single component, it is often clear that, in the course of the “optimization” procedures, there was confusion about what was being optimized with respect to what, or what was to be kept constant. Most disappointing thought is the fact that in the quest for an idealized optimum point, frequently configuration, operation and maintenance issues are entirely neglected or grossly underestimated, and a solution obtained via a purely mathematical procedure is presented as the solution to the given design-andoptimization problem. Thus, neighboring “quasi-optima” are disregarded, that in real engineering applications often represent the most convenient solution”.
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References
Bejan, A., Tsatsaronis, G., Moran, M., (1996), Thermal Design and Optimization, John Wiley & Sons, New York.
Sciubba, E., Melli, R., (1998), Artificial Intelligence in Thermal Systems Design: Concepts and Applications, Nova Science Publishers, Inc., Commack, New York.
Stosic, N., Smith, I., Kovacevic, A., Optimisation of Screw Compressor Design, The XVI International Compressor Engineering Conference. Purdue, Lafayette, IN, July 16–19th 2002.
Ionita, C.I., Extending Thermoeconomic Analysis by Cost-to-Quality Optimization, ECOS 2002, Berlin, Germany, pp. 1434–1441.
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© 2003 Springer Science+Business Media Dordrecht
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Ionita, I.C. et al. (2003). Cost-to-Quality Optimization of Refrigeration. In: Kakaç, S., Smirnov, H.F., Avelino, M.R. (eds) Low Temperature and Cryogenic Refrigeration. NATO Science Series, vol 99. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0099-4_7
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DOI: https://doi.org/10.1007/978-94-010-0099-4_7
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