The design and analysis of buildings includes many aspects such as resilience, energy, water, occupant experience, and operations and maintenance. In relation to climate analyses alone, specialized techniques are being developed to study past climate, leverage real-time weather information, plan for forecasted climate, tackle microclimate effects, and the like. Some advanced automation workflows employ non-traditional simulation engines using targeted reduced order modeling techniques. Although these workflows are evolving at a rapid pace, climate data models have not kept up with them. When simulation tools were developed, many implemented dissimilar climate information models, resulting in competing formats. So, while engine-neutral data is sometimes represented using mutually incompatible data structures and data dictionaries, other types of climate information may be unavailable because these files are restricted to inputs supported by their respective simulation engines. Also, the separate distribution of statistical data such as design day information, climate zones classification, etc., is a frequent source of design and analysis inconsistency. This paper demonstrates why a standard definition is necessary for climate information to implement intelligent automation workflows and to take advantage of contemporary computing techniques.
| File Size : | 1
file
, 2.4 MB |
| Note : | This product is unavailable in Russia, Belarus |
| Number of Pages : | 8 |
| Product Code(s) : | D-BSC20-C034 |
| Published : | 2020 |
| Units of Measure : | Dual |
