@article {32156,
	title = {An inverse approach to solving zone air infiltration rate and people count using indoor environmental sensor data},
	journal = {Energy and Buildings},
	volume = {198},
	year = {2019},
	month = {Jan-09-2019},
	pages = {228 - 242},
	abstract = {<p>Physics-based simulation of energy use in buildings is widely used in building design and performance rating, controls design and operations. However, various challenges exist in the modeling process. Model parameters such as people count and air infiltration rate are usually highly uncertain, yet they have significant impacts on the simulation accuracy. With the increasing availability and affordability of sensors and meters in buildings, a large amount of measured data has been collected including indoor environmental parameters, such as room air dry-bulb temperature, humidity ratio, and CO2 concentration levels. Fusing these sensor data with traditional energy modeling poses new opportunities to improve simulation accuracy. This study develops a set of physics-based inverse algorithms which can solve the highly uncertain and hard-to-measure building parameters such as zone-level people count and air infiltration rate. A simulation-based case study is conducted to verify the inverse algorithms implemented in EnergyPlus covering various sensor measurement scenarios and different modeling use cases. The developed inverse models can solve the zone people count and air infiltration at sub-hourly resolution using the measured zone air temperature, humidity and/or CO2 concentration given other easy-to-measure model parameters are known.</p>},
	keywords = {energyplus, infiltration, Inverse problems, people count, sensor data, zone air parameters},
	issn = {03787788},
	doi = {10.1016/j.enbuild.2019.06.008},
	author = {Li, Han and Hong, Tianzhen and Sofos, Marina}
}
@article {32158,
	title = {Validation of an inverse model of zone air heat balance},
	journal = {Building and Environment},
	volume = {161},
	year = {2019},
	month = {Jan-08-2019},
	pages = {106232},
	abstract = {<p>This paper presents the validation method and results of an inverse model of zone air heat balance. The inverse model, implemented in EnergyPlus and published in a previous article [1], calculates highly uncertain model parameters such as internal thermal mass and infiltration airflow by inversely solving the zone air heat balance equation using the easy-to-measure zone air temperature data. The paper provides technical details of validation from the experiments using LBNL{\textquoteright}s Facility for Low Energy eXperiment in Buildings (FLEXLAB) that measures zone air temperature under the controlled experiment of two levels of internal mass and four levels of infiltration airflow. The simulation results of the zone infiltration airflow and internal thermal mass from the inverse model agree well with the measured data from the FLEXLAB experiments. The validated inverse model in EnergyPlus can be used to enhance the energy modeling of existing buildings that enables energy performance assessments for energy efficiency improvements.</p>},
	keywords = {Energy simulation, energyplus, infiltration, internal thermal mass, inverse model, sensor data},
	issn = {03601323},
	doi = {10.1016/j.buildenv.2019.106232},
	author = {Lee, Sang Hoon and Hong, Tianzhen}
}
