By Javad Khazaii
This ebook specializes in one of the most energy-consuming HVAC platforms; illuminating large possibilities for strength discount rates in constructions that function with those platforms. the most dialogue is on, state of the art selection making methods, and algorithms in: determination making below uncertainty, genetic algorithms, fuzzy common sense, man made neural networks, agent dependent modeling, and video game conception. those tools are utilized to HVAC platforms, which will support designers pick out the easiest thoughts among the on hand pathways for designing and the construction of HVAC structures and functions. The dialogue extra evolves to depict how the constructions of the longer term can comprise those complex decision-making algorithms to turn into self sufficient and actually ‘smart’.
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Extra resources for Advanced Decision Making for HVAC Engineers: Creating Energy Efficient Smart Buildings
38 3 Data Centers 4. ASHRAE Datacom. (2009). , Vol. 6). Atlanta, GA: American Society of Heating, Refrigerating, and Air Conditioning Engineers. 5. American Society of Heating, Refrigerating and Air Conditioning Engineers. (2015). ASHRAE application handbook. Atlanta, GA: American Society of Heating, Refrigerating and Air Conditioning Engineers. 6. , Emerson, B. Design recommendations for highperformance Data Centers, Report of the Integrated Design Charrette, Conducted 2–5 February 2003, Rocky Mountain Institute (RMI), with funding from Pacific Gas & Electric Energy Design Resources program.
Keywords Total equivalent temperature differential method • Sol-air temperature • Transfer function method • Conduction transfer function • Time averaging method • Room transfer function • Cooling load factor • Cooling load temperature difference • Heat balance method • Radiant time series • Base building • Design building Load Calculations In designing the HVAC system for a building the first step is always to calculate the heat gain and heat loss during cooling and heating periods. From that point on, the designer will be capable of understanding and deciding what type and what size equipment should be selected to fulfill the comfort and functional criteria in the building.
Typical input data to the proposed building energy model would be as follows. Interior Space Conditions Cooling season: 75 F dry bulb and 50 % relative humidity. Heating season: 72 F. Floor to floor height: 13 ft. Wall height: 13 ft. Plenum depth: 4 ft. 06 cfm/ft2) Ventilation type: Office Space; Cooling EZ: Ceiling Supply 100 %, Ceiling Return; Heating Ez: Ceiling Supply < room temperature plus 15 F, 100 %. 06 cfm/ft2) Ventilation type: Conference rooms; Cooling EZ: Ceiling Supply 100 %, Ceiling Return; Heating Ez: Ceiling Supply < room temperature plus 15 F, 100 %.
Advanced Decision Making for HVAC Engineers: Creating Energy Efficient Smart Buildings by Javad Khazaii