Wind, Sun, Surface Temperature, and Heat Island

Critical Variables for High-Resolution Outdoor Thermal Comfort

Chris Mackey + Mostapha Sadeghipour Roudsari

Building Simulation, 2017

Wind, Sun, Surface Temperature, and Heat Island: Critical Variables for High-Resolution Outdoor Thermal Comfort

Outdoor Comfort is Difficult to Model�Building the Most Accurate Model�Removing Factors from the Model�Final Sensitivity Analysis��

AGENDA

OUTDOOR THERMAL COMFORT IN URBAN AREAS

… is difficult to model because one must account for:

• Urban Heat Island (UHI)
• Spatial Wind Patterns
• Urban Surface Temperatures
• Human-Sky Heat Exchange (Solar + Infrared)

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OUTDOOR THERMAL COMFORT IN URBAN AREAS

Sun

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Heat Island

Wind

Surface�Temperature

weather data

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geometry

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Thermal Comfort Model

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CENTRALIZED MODEL

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urban materials

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Sun

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Heat

Island

Wind

Surface�Temperature

weather data

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geometry

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DISTRIBUTED MODEL

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materials

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Thermal Comfort Model

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GOAL OF THIS WORK

• Model a site in Singapore to as high an accuracy possible with the distributed method.
• Systematically remove variables to find those that are most important.

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GOAL OF THIS WORK

Site chosen for its diverse microclimates.

Outdoor Comfort is Difficult to Model�Building the Most Accurate Model�Removing Factors from the Model�Final Sensitivity Analysis��

AGENDA

URBAN HEAT ISLAND

Modeled with the MIT Urban Weather Generator¹, which accounts for:

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• Urban geometry
• Urban materials
• Vegetation cover
• Anthropogenic heat

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Using an urban energy balance.

¹ Bueno, B; Norford, L.; Hidalgo, J; Pigeon, G. (2013) The Urban Weather Generator. Journal of Building Performance Simulation 6, no. 4: 269–81.

SURFACE TEMPERATURE

Modeled with EnergyPlus. This accounts for:

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• Solar distribution, shading and absorption by surfaces
• Radiative heat transfer between surfaces
• Conduction to the building interior

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• Convective heat transfer used standard outdoor coefficients (not informed by CFD)

SKY HEAT TRANSFER

Modeled using a modified version of the SolarCal³ method. This accounts for:

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• Shortwave direct + diffuse solar distribution over the human

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• Longwave radiative heat loss from the person to the sky

Slow Full-Body Solar Radiation Study

Faster SolarCal Method

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Direct Sun View

Diffuse Sky View

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Extra Coefficients

³ Arens, E; Hoyt, T.; Zhou, X; Huang, L; Zhang, H; and Schiavon, S. (2015). Modeling the Comfort Effects of Short-Wave Solar Radiation Indoors. Building and Environment, 88 : 3–9.

WIND PATTERNS

Modeled with 36 CFD simulations using OpenFOAM², each of which is from a different direction.

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• Wind factors were generated from each simulation:

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• Wind factors for an hourly direction were multiplied by hourly wind speed.
• This gave spatial maps of wind speed for every hour of the year.

² Robertson, E; Choudhury, V; Bhushan, S; Walters. D.K. (2015). Validation of OpenFOAM Numerical Methods and Turbulence Models for Incompressible Bluff Body Flows. Computers & Fluids 123: 122–45.

WF =

speed at a given location

meteorological speed

MOST ACCURATE MICROCLIMATE MAP

Typical Week

Cold Week

Hot Week

MOST ACCURATE MICROCLIMATE MAP

Outdoor Comfort is Difficult to Model�Building the Most Accurate Model�Removing Factors from the Model�Final Sensitivity Analysis��

AGENDA

REMOVING CFD SIMULATIONS | 18 SIMULATIONS

REMOVING CFD SIMULATIONS | 12 SIMULATIONS

REMOVING CFD SIMULATIONS | 9 SIMULATIONS

REMOVING CFD SIMULATIONS | 6 SIMULATIONS

REMOVING CFD SIMULATIONS | 4 SIMULATIONS

REMOVING CFD SIMULATIONS | 3 SIMULATIONS

REMOVING CFD SIMULATIONS | 2 SIMULATIONS

REMOVING CFD SIMULATIONS | LOG LAW EVERYWHERE

REMOVING CFD SIMULATIONS

REMOVING URBAN HEAT ISLAND

REMOVING SURFACE TEMPERATURE

REMOVING SKY HEAT EXCHANGE

Outdoor Comfort is Difficult to Model�Building the Most Accurate Model�Removing Factors from the Model�Final Sensitivity Analysis��

AGENDA

SENSITIVITY ANALYSIS | BUILDING MICROCLIMATE MAPS

SENSITIVITY ANALYSIS | METEOROLOGIST RECOMMENDATIONS

THANK YOU