Fuzzy model for assessment of comfortable conditions during design of air conditioning systems

Николай Иванович Бабич

Abstract


The primary and highly important step in the process of designing individual objects and their systems is developing the Terms of Reference (TOR) for design.

The most important requirement for the TOR lies in its completeness. The more detailed information the mechanical engineer obtains, the more certain timeframes and quality of design will be. Today, when designing air conditioning and humidification (C&H) systems, most engineers use regulatory documents.

But it is becoming increasingly important to take into account individual characteristics of a person during the formation of comfortable conditions parameters.

It should be noted that there are many individual parameters and it is quite difficult to define clearly the required vector of such parameters, as well as the values for each of them; hence, a fuzzy logic method should be applied.

As a result of simulation, a fuzzy model was developed for assessing comfort conditions in living accommodations.

Fuzzy model will greatly improve the quality of design works, namely the formation of technical documentation about design objects


Keywords


fuzzy model; individual characteristics; comfort conditions; temperature; relative humidity; design

References


Ананьев, В.А. Системы вентиляции и кондиционирования. Теория и практика: Учебное пособие [Текст] / В.А. Ананьев, Л.Н. Балуева, А.Д. Гальперин. – М.: «Евроклимат», изд- во «Арина», 2000. – С. 416

Кувшинов, Ю.Я. Теоретические основы обеспечения микроклимата помещения [Текст] / Ю.Я. Кувшинов. – М.: АСВ, 2007. – С.212

ГОСТ 30494-96 «Здания жилые и общественные. Параметры микроклимата в помещениях» [Текст].

Кокорин, О.Я. Установки кондиционирования воздуха. Основы расчета и проектирования. Изд. 2-е, перераб. и доп. [Текст] / О.Я.

Кокорин.– М.: Машиностроение, 1978. – С.264

Антощук, С.Г. Модель автоматизации процессов поддержания теплового комфорта в обитаемом помещении [Текст] / С.Г. Антощук, Н.И. Бабич, В.Г. Панов, Л.Ф. Бурдыка.– Холодильна техніка і технологія. – 2012. – № 1 (135). – С.54

Fanger, P. O. Thermal Comfort-Analysis and Applications in Environmental Engineering [Текст] / P. O. Fanger. – Danish Technical Press. – Copenhagen, 1970. – P. 88 – 90.

Новак, В. Математические принципы нечеткой логики [Текст] / В. Новак, И. Перфильева, И. Мочкорж. – Пер. с англ.; Под ред. Аверкина А.Н. – М.: ФИЗМАТЛИТ, 2006. – 252 с.

Леденева, Т.М. Обработка нечеткой информации [Текст] : учебное пособие / Т.М. Леденева. – Воронеж: Воронежский государственный университет, 2006. – 233 с.

Алтунин, А. Е. Модели и алгоритмы принятия решений в нечетких условиях: монография [Текст] / А. Е. Алтунин, М. В. Семухин. – Тюмень : Тюменский государственный университет, 2000. – 352 с.

Кондратенко, В. Ю. Об’єктно-орієнтовані моделі для синтезу інтелектуальних систем з нечіткою логікою [Текст] / В. Ю. Кондратенко, В. С. Яценко. – Праці Одеського національного політехнічного університету, 2006. – С. 54 – 60.

Kandel, A. Fuzzy Control Systems [Текст] / А. Kandel, G. Langholz. – CRC Press LLC, 1993. – P. 187.

Ananev, V., Balueva, L., Halperin, A. (2000). HVAC system. Theory and Practice: Textbook. M.: "Evroklimat", published in "Arina", 416.

Kuvshinov, Y. (2007). Theoretical wasps nova provide indoor climate. M.: DIA, 212.

GOST 30494-96 "Residential and public buildings. The parameters of indoor climate."

Kokorin, O. (1978) Installation of air conditioning. Basis of calculation and design. Ed. 2nd, revised. and add. M.: Mechanical Engineering, 264.

Antoshuk, S., Babich, N., Panov, V., Burdyka, L. (2012). Model automation maintain thermal comfort in the room. A cooling engineering and technology, 54.

Fanger, P. (1970). Thermal Comfort-Analysis and Applications in Environmental Engineering. Danish Technical Press, 88– 90.

Novak, V., Perfilieva, I., Mochkorzh, I. (2006). Mathematical principles of fuzzy logic. Trans. from English., ed. Averkina, M.: FIZMATLIT, 252.

Ledeneva, T. (2006). Fuzzy information processing: a manual. Voronezh State University, 233.

Altunin, A., Semukhin, M. (2000). Models and algorithms for decision making in fuzzy environment: monograph. Tyumen State University, 352.

Kondratenko, V., Yatsenko, V. (2006). Object-oriented models for synthesis intelligent fuzzy systems. Proceedings ONPU, 54.

Kandel, A., Langholz, G. (1993). Fuzzy Control Systems. CRC Press LLC, 187.


GOST Style Citations








Copyright (c) 2014 Николай Иванович Бабич

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN (print) 1729-3774, ISSN (on-line) 1729-4061