کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
261945 504006 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Using synthetic population data for prospective modeling of occupant behavior during design
ترجمه فارسی عنوان
با استفاده از داده های جمعیت مصنوعی برای مدل سازی آینده ساز رفتار ساکنان در طول طراحی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی


• Design work precedes building occupancy but designers should still consider occupant behavior.
• The transferability of occupant behavior data depends on incorporation of key contextual factors.
• Creating a synthetic set of generic building occupants captures aspects of context, is feasible and helpful in design practice, and is available now for commercial buildings.

This paper addresses the challenge of incorporating occupant behavior into building performance simulation models used during the design process—that is, before the actual occupants are known. It proposes the use of synthetic population data, an approach that is novel in building performance modeling although common in urban planning and public health. A simpler approach embodied in the ASHRAE Fundamentals volume is to report standard distributions of values for behavioral variables, assuming that parameters vary independently of one another when in fact many co-vary or are interdependent. An alternative approach calibrates models of occupant behavior against actual occupants in specific existing buildings, but this raises questions of transferability. Needed is a database of “generic” occupants that designers can use prospectively during the design process. This paper documents a process of combining disparate field studies of commercial buildings into a larger occupant behavior database and generating a statistically similar synthetic data set that can be shared without compromising confidentiality requirements associated with field studies. The synthetic data set successfully incorporates much of the covariance structure of the underlying field data and supports multivariate modeling. Its scope and structure necessarily serve the needs of the associated modeling framework. Cooperative and systematic sharing of data by field researchers is crucial for building large enough data sets to serve as a behaviorally-robust basis for building design.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy and Buildings - Volume 126, 15 August 2016, Pages 415–423
نویسندگان
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