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Ansiashrae Standard 2052023 Representation Of Performance Data For Hvacr And Other Facility Equipment Ashrae

  • SKU: BELL-58324330
Ansiashrae Standard 2052023 Representation Of Performance Data For Hvacr And Other Facility Equipment Ashrae
$ 31.00 $ 45.00 (-31%)

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Ansiashrae Standard 2052023 Representation Of Performance Data For Hvacr And Other Facility Equipment Ashrae instant download after payment.

Publisher: ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers)
File Extension: PDF
File size: 1.17 MB
Pages: 97
Author: ASHRAE
Language: English
Year: 2023

Product desciption

Ansiashrae Standard 2052023 Representation Of Performance Data For Hvacr And Other Facility Equipment Ashrae by Ashrae instant download after payment.

Mechanical equipment uses fuel and/or electricity and emits carbon during operation. Simulation models allow prediction of these impacts given information about how the equipment performs under all conditions. The lack of detailed equipment performance data in readily-usable forms has hampered the application of building simulation models since their invention in the 1960s and 1970s. Data are often not available or published in inconsistent formats, forcing simulation users to resort to default information and/or time consuming (and error-prone) reformatting.

Standard 205 addresses this deficiency by defining common data models and serialization formats for facility equipment performance data, allowing automated exchange among data sources (manufacturers), simulation models, and other engineering applications. The formats and procedures specified by Standard 205 are developed under ASHRAE and ANSI consensus processes with participation of equipment manufacturers, application software developers, and engineering practitioners. The intent is that all data publishers write common-format data files and all application software include procedures to read files using that format. Standard procedures will improve the accuracy and consistency of model results relative to the mix of correlation and application-specific approaches traditionally used.

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