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Title: Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus

Abstract

The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, HVAC system performance, and occupant comfort. Therefore, indoor climate data is generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies is influenced by weather, occupant behavior and internal loads, and is generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The

Authors:
 [1];  [2];  [2];  [3]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Building Technologies Research and Integration Center; Tufts Univ., Medford, MA (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Building Technologies Research and Integration Center
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Building Technologies Research and Integration Center; Tennessee Technological Univ., Cookeville, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Building Technologies Research and Integration Center (BTRIC)
Sponsoring Org.:
USDOE Office of Science (SC), Workforce Development for Teachers and Scientists (WDTS) (SC-27)
OSTI Identifier:
1356931
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Building Physics
Additional Journal Information:
Journal Volume: 41; Journal Issue: 3; Journal ID: ISSN 1744-2591
Publisher:
SAGE
Country of Publication:
United States
Language:
English
Subject:
29 ENERGY PLANNING, POLICY, AND ECONOMY; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 42 ENGINEERING; Indoor climate; probabilistic modeling; building simulation; moisture buffering; relative humidity

Citation Formats

Buechler, Elizabeth D., Pallin, Simon B., Boudreaux, Philip R., and Stockdale, Michaela R. Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus. United States: N. p., 2017. Web. doi:10.1177/1744259117701893.
Buechler, Elizabeth D., Pallin, Simon B., Boudreaux, Philip R., & Stockdale, Michaela R. Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus. United States. doi:10.1177/1744259117701893.
Buechler, Elizabeth D., Pallin, Simon B., Boudreaux, Philip R., and Stockdale, Michaela R. Tue . "Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus". United States. doi:10.1177/1744259117701893. https://www.osti.gov/servlets/purl/1356931.
@article{osti_1356931,
title = {Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus},
author = {Buechler, Elizabeth D. and Pallin, Simon B. and Boudreaux, Philip R. and Stockdale, Michaela R.},
abstractNote = {The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, HVAC system performance, and occupant comfort. Therefore, indoor climate data is generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies is influenced by weather, occupant behavior and internal loads, and is generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The},
doi = {10.1177/1744259117701893},
journal = {Journal of Building Physics},
number = 3,
volume = 41,
place = {United States},
year = {Tue Apr 25 00:00:00 EDT 2017},
month = {Tue Apr 25 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
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