Publications
2016
Langevin, Jared; Wen, Jin; Gurian, Patrick L.
Quantifying the human–building interaction: Considering the active, adaptive occupant in building performance simulation Journal Article
In: Energy and Buildings, vol. 117, pp. 372-386, 2016, ISSN: 0378-7788.
Abstract | Links | BibTeX | Tags: Agent-based modeling, Building performance modeling, Co-simulation, Occupant behavior, Thermal comfort
@article{LANGEVIN2016372,
title = {Quantifying the human–building interaction: Considering the active, adaptive occupant in building performance simulation},
author = {Jared Langevin and Jin Wen and Patrick L. Gurian},
url = {https://www.sciencedirect.com/science/article/pii/S037877881530267X},
doi = {https://doi.org/10.1016/j.enbuild.2015.09.026},
issn = {0378-7788},
year = {2016},
date = {2016-01-01},
journal = {Energy and Buildings},
volume = {117},
pages = {372-386},
abstract = {This paper introduces a Human and Building Interaction Toolkit (HABIT) for simulating the thermally adaptive behaviors and comfort of office occupants alongside building energy consumption. The toolkit uses the Building Controls Virtual Test Bed (BCVTB) to co-simulate a field-tested, agent-based behavior model with an EnergyPlus medium office model. The usefulness of the toolkit is demonstrated through a series of zone and building-level case study simulations that examine the wisdom of pairing local heating and cooling options with strategic thermostat set point offsets, judging from the energy, Indoor Environmental Quality (IEQ), and cost perspectives. Results generally suggest that trading efficient local heating/cooling options for whole space conditioning has both energy and comfort benefits, saving up to 28% of monthly HVAC energy while improving the acceptability of thermal conditions in a Philadelphia climate. Nevertheless, cost analysis shows that the fuel source of conserved energy must be considered – particularly in the case of personal heater use, which adds to electric plug loads and associated utility and CO2 emissions cost penalties. Moreover, costs from even small changes in simulated occupant productivity tend to overwhelm energy costs, suggesting the need to improve the accuracy and precision of available productivity models across multiple seasons and climates.},
keywords = {Agent-based modeling, Building performance modeling, Co-simulation, Occupant behavior, Thermal comfort},
pubstate = {published},
tppubtype = {article}
}
This paper introduces a Human and Building Interaction Toolkit (HABIT) for simulating the thermally adaptive behaviors and comfort of office occupants alongside building energy consumption. The toolkit uses the Building Controls Virtual Test Bed (BCVTB) to co-simulate a field-tested, agent-based behavior model with an EnergyPlus medium office model. The usefulness of the toolkit is demonstrated through a series of zone and building-level case study simulations that examine the wisdom of pairing local heating and cooling options with strategic thermostat set point offsets, judging from the energy, Indoor Environmental Quality (IEQ), and cost perspectives. Results generally suggest that trading efficient local heating/cooling options for whole space conditioning has both energy and comfort benefits, saving up to 28% of monthly HVAC energy while improving the acceptability of thermal conditions in a Philadelphia climate. Nevertheless, cost analysis shows that the fuel source of conserved energy must be considered – particularly in the case of personal heater use, which adds to electric plug loads and associated utility and CO2 emissions cost penalties. Moreover, costs from even small changes in simulated occupant productivity tend to overwhelm energy costs, suggesting the need to improve the accuracy and precision of available productivity models across multiple seasons and climates.
2015
Langevin, Jared; Gurian, Patrick L.; Wen, Jin
Tracking the human-building interaction: A longitudinal field study of occupant behavior in air-conditioned offices Journal Article
In: Journal of Environmental Psychology, vol. 42, pp. 94-115, 2015, ISSN: 0272-4944.
Abstract | Links | BibTeX | Tags: Longitudinal field studies, Occupant behavior, Office buildings, Thermal acceptability, Thermal comfort
@article{LANGEVIN201594,
title = {Tracking the human-building interaction: A longitudinal field study of occupant behavior in air-conditioned offices},
author = {Jared Langevin and Patrick L. Gurian and Jin Wen},
url = {https://www.sciencedirect.com/science/article/pii/S0272494415000225},
doi = {https://doi.org/10.1016/j.jenvp.2015.01.007},
issn = {0272-4944},
year = {2015},
date = {2015-01-01},
journal = {Journal of Environmental Psychology},
volume = {42},
pages = {94-115},
abstract = {This paper presents findings from a one-year longitudinal case study of occupant thermal comfort and related behavioral adaptations in an air-conditioned office building. Long-term data were collected via online daily surveys and datalogger measurements of the local thermal environment and behavior. Behavioral outcomes are examined against both environmental and personal thermal comfort variables. Key personal variables include one's currently acceptable range of thermal sensations, which significantly explains inter-individual variations in thermal comfort responses. Results also show substantial between-day clothing adjustments and elevated metabolic rates upon office arrival, which may affect subsequent thermal comfort and behavior trajectories. Behavior sequencing appears complex, with multiple behaviors sometimes observed within a short time period and certain behaviors subject to contextual constraints. By elucidating the nature of the human-building interaction, the paper's findings may inform the improved measurement, modeling, and anticipation of occupant behavior as part of future sustainable building design and operation practices.},
keywords = {Longitudinal field studies, Occupant behavior, Office buildings, Thermal acceptability, Thermal comfort},
pubstate = {published},
tppubtype = {article}
}
This paper presents findings from a one-year longitudinal case study of occupant thermal comfort and related behavioral adaptations in an air-conditioned office building. Long-term data were collected via online daily surveys and datalogger measurements of the local thermal environment and behavior. Behavioral outcomes are examined against both environmental and personal thermal comfort variables. Key personal variables include one’s currently acceptable range of thermal sensations, which significantly explains inter-individual variations in thermal comfort responses. Results also show substantial between-day clothing adjustments and elevated metabolic rates upon office arrival, which may affect subsequent thermal comfort and behavior trajectories. Behavior sequencing appears complex, with multiple behaviors sometimes observed within a short time period and certain behaviors subject to contextual constraints. By elucidating the nature of the human-building interaction, the paper’s findings may inform the improved measurement, modeling, and anticipation of occupant behavior as part of future sustainable building design and operation practices.
Langevin, Jared; Wen, Jin; Gurian, Patrick L.
Simulating the human-building interaction: Development and validation of an agent-based model of office occupant behaviors Journal Article
In: Building and Environment, vol. 88, pp. 27-45, 2015, ISSN: 0360-1323, (Interactions between human and building environment).
Abstract | Links | BibTeX | Tags: Agent-based modeling, Human-building interaction, Occupant behavior, Thermal acceptability, Thermal comfort
@article{LANGEVIN201527,
title = {Simulating the human-building interaction: Development and validation of an agent-based model of office occupant behaviors},
author = {Jared Langevin and Jin Wen and Patrick L. Gurian},
url = {https://www.sciencedirect.com/science/article/pii/S0360132314004090},
doi = {https://doi.org/10.1016/j.buildenv.2014.11.037},
issn = {0360-1323},
year = {2015},
date = {2015-01-01},
journal = {Building and Environment},
volume = {88},
pages = {27-45},
abstract = {This paper develops and validates an agent-based model (ABM) of occupant behavior using data from a one-year field study in a medium-sized, air-conditioned office building. The full ABM is presented in detail using a standard protocol for describing this type of model. Simulated occupant “agents” in the full ABM behave according to Perceptual Control Theory, taking the most immediate, unconstrained adaptive behaviors as needed to maintain their current thermal sensation within a reference range of seasonally acceptable sensations. ABM validation assigns simulated agents the personal characteristics and environmental context of real office occupants in the field study; executes the model; and compares the model's ability to predict observed fan, heater, and window use to the predictive abilities of several other behavior modeling options. The predictive performance of the full ABM compares favorably to that of the other modeling options on both the individual and aggregate outcome levels. The full ABM also appears capable of reproducing more familiar regression relationships between behavior and the local thermal environment. The paper concludes with a discussion of the model's current limitations and possibilities for future development.},
note = {Interactions between human and building environment},
keywords = {Agent-based modeling, Human-building interaction, Occupant behavior, Thermal acceptability, Thermal comfort},
pubstate = {published},
tppubtype = {article}
}
This paper develops and validates an agent-based model (ABM) of occupant behavior using data from a one-year field study in a medium-sized, air-conditioned office building. The full ABM is presented in detail using a standard protocol for describing this type of model. Simulated occupant “agents” in the full ABM behave according to Perceptual Control Theory, taking the most immediate, unconstrained adaptive behaviors as needed to maintain their current thermal sensation within a reference range of seasonally acceptable sensations. ABM validation assigns simulated agents the personal characteristics and environmental context of real office occupants in the field study; executes the model; and compares the model’s ability to predict observed fan, heater, and window use to the predictive abilities of several other behavior modeling options. The predictive performance of the full ABM compares favorably to that of the other modeling options on both the individual and aggregate outcome levels. The full ABM also appears capable of reproducing more familiar regression relationships between behavior and the local thermal environment. The paper concludes with a discussion of the model’s current limitations and possibilities for future development.
2013
Langevin, Jared; Wen, Jin; Gurian, Patrick L.
In: Building and Environment, vol. 69, pp. 206-226, 2013, ISSN: 0360-1323.
Abstract | Links | BibTeX | Tags: Bayesian probit analysis, Office occupants, Thermal acceptability, Thermal comfort, Thermal preference, Thermal sensation
@article{LANGEVIN2013206,
title = {Modeling thermal comfort holistically: Bayesian estimation of thermal sensation, acceptability, and preference distributions for office building occupants},
author = {Jared Langevin and Jin Wen and Patrick L. Gurian},
url = {https://www.sciencedirect.com/science/article/pii/S0360132313002151},
doi = {https://doi.org/10.1016/j.buildenv.2013.07.017},
issn = {0360-1323},
year = {2013},
date = {2013-01-01},
journal = {Building and Environment},
volume = {69},
pages = {206-226},
abstract = {The three concepts of thermal sensation, acceptability, and preference each contribute to a holistic understanding of a building occupant's thermal comfort and how it can be effectively predicted. Nevertheless, there is currently no integrated framework for evaluating sensation, acceptability, and preference together as part of thermal comfort assessment in the built environment. Indeed, the only relation given between these variables in existing comfort guidelines - the Predicted Mean Vote – Predicted Percentage Dissatisfied (PMV–PPD) curve – rests on the tenuous assumption that occupants only find sensations at or near “Neutral” to be acceptable. This paper uses occupant response data from both the laboratory and field settings to develop an integrated approach for assessing office occupant thermal comfort through the multiple lenses of thermal sensation, acceptability, and preference. Specifically, probability distributions are developed for each of these comfort variables using Bayesian probit analysis. Given these distributions, we present revised PMV–PPD curves for field offices, and construct a new set of curves that represent the relationship between PMV and direct thermal acceptability and preference ratings. The probit analysis reveals that PMV is a significant predictor of thermal sensation distribution in the field; suggests that thermal acceptability and preference responses are subject to seasonal influences; and shows differences in thermal sensation, acceptability, and preference distributions for occupants in Air-Conditioned and Naturally Ventilated buildings. The usefulness of the developed distributions to practical thermal comfort assessments is discussed, as is the potential for these distributions to be updated in the future as more data are collected.},
keywords = {Bayesian probit analysis, Office occupants, Thermal acceptability, Thermal comfort, Thermal preference, Thermal sensation},
pubstate = {published},
tppubtype = {article}
}
The three concepts of thermal sensation, acceptability, and preference each contribute to a holistic understanding of a building occupant’s thermal comfort and how it can be effectively predicted. Nevertheless, there is currently no integrated framework for evaluating sensation, acceptability, and preference together as part of thermal comfort assessment in the built environment. Indeed, the only relation given between these variables in existing comfort guidelines – the Predicted Mean Vote – Predicted Percentage Dissatisfied (PMV–PPD) curve – rests on the tenuous assumption that occupants only find sensations at or near “Neutral” to be acceptable. This paper uses occupant response data from both the laboratory and field settings to develop an integrated approach for assessing office occupant thermal comfort through the multiple lenses of thermal sensation, acceptability, and preference. Specifically, probability distributions are developed for each of these comfort variables using Bayesian probit analysis. Given these distributions, we present revised PMV–PPD curves for field offices, and construct a new set of curves that represent the relationship between PMV and direct thermal acceptability and preference ratings. The probit analysis reveals that PMV is a significant predictor of thermal sensation distribution in the field; suggests that thermal acceptability and preference responses are subject to seasonal influences; and shows differences in thermal sensation, acceptability, and preference distributions for occupants in Air-Conditioned and Naturally Ventilated buildings. The usefulness of the developed distributions to practical thermal comfort assessments is discussed, as is the potential for these distributions to be updated in the future as more data are collected.