This paper explores the adaptive optimal design of Active Thermally Insulated (ATI) windows to significantly improve energy efficiency. The ATI window design uses ther- mostats to actively control thermoelectric (TE) units and fans to regulate the overall ther- modynamic properties of the windows. The windows are used to maintain a comfortable indoor temperature. Since weather conditions vary with different geographical locations and with time, the thermodynamic properties of the windows should adapt accordingly. The electric power supplied to the TE units and the fans are dynamically controlled so as to provide an optimal operation under varying weather conditions. Optimization of the ATI window design is a multiobjective problem. The problem minimizes both the heat trans- ferred through the window and electric power consumption. The heat transfer through the ATI windows is analyzed using FLUENT; and the optimization is performed using MAT- LAB. Since the computational expense of optimization for numerous weather conditions is excessive, the power supplies are optimized under a reasonably small number of weather conditions. Based on the optimal results obtained for these conditions, a surrogate model is developed to represent the optimal results in a wide range of weather conditions. The surrogate model is used to evaluate optimal power supplies with respect to different val- ues of outside temperature, wind speed, and intensity of solar radiation. Thermometers, anemometers, and solar radiation sensors are used to sense these weather conditions. With the inputs from the sensors, the thermostats determine the operating conditions and cal- culate the corresponding optimal power supplies using the surrogate model. Since the ATI windows are operated with optimal power supplies, high energy efficiency is achieved.

1. Adaptive Optimal Design of Active Thermally
Insulated (ATI) Windows Using Surrogate Modeling
Junqiang Zhang, Achille Messac, Souma Chowdhury, and Jie Zhang
Rensselaer Polytechnic Institute
Department of Mechanical, Aerospace, and Nuclear Engineering
Multidisciplinary Design and Optimization Laboratory
6th AIAA Multidisciplinary Design Optimization Specialist Conference
April 2010, Orlando, FL

2. 2
Outline
• Motivation
• Active Window Technology Overview
• ATI Window Design
• Modeling
• Adaptive Optimization
• Surrogate Model of Optimal Operations
• Results and Comparisons
• Concluding Remarks

3. 3
Motivation
53% energy consumed by HVAC
systems in residential buildings
44% energy consumed by HVAC
systems in commercial buildings
• Windows occupy only 10% to 15% of the wall area
• Windows can contribute 25% to 30% of the heat gain
Department of Energy, “Buildings Energy Data Book”, 2005, http://buildingsdatabook.eere.energy.gov/
Energy Information Administration, “Commercial Buildings Energy Consumption Survey”, 2003, http://www.eia.doe.gov/emeu/cbecs/

4. 4
Types of Active Windows
Heat extraction double skin facades
Absorb the sun’s
heat outside
Switchable window coatings
Change optical
properties to limit
solar heat gain
Active control of shading systems
Block incident
sunlight to limit
solar heat gain
Thermoelectric Windows
Outside
Inside

5. 5
Thermoelectric (TE) Units
• TE Units can be very small and operate with no moving
parts, making them ideal to fit inside building envelopes or
in the small space of the window frames.
• A TE unit will form hot and cold sides when subjected to
electric current.
Melcor Center Hole Series
Thermoelectric Cooler
Hot Side
Cold Side
Heat Flow

6. 6
ATI Window Design
Window Front View Cross Section of Side View
6
Side Channel
Clear glass
Side Channel
Fans
Heating air flow in Winter
1 m
.5 m
TE Units
& Fin
Dividing Wall
6 mm
Air
Clear Glass
Tinted pane
24 mm
Out In
12 mm
Inner
Pane
Middle
Pane
Outer
Pane

7. 7
ATI Window Design
• Thermometer, anemometer, and solar radiation sensor
are used to detect weather conditions.
• Thermostat receive signals from the sensors and adjust
the electric power supplies of TE units and fans
according to different weather conditions.
• Actively regulate the overall thermodynamic properties
of the air in the gap between the inner pane and the
middle pane to benefit the building occupants.

8. 8
Modeling
• Motivation
• Active Window Technology Overview
• ATI Window Design
• Modeling
• TE models
• CFD Model
• Outside Heat sinks
• Thermostats and weather condition sensors
• Optimization
• Surrogate Model of Optimal Operation
• Comparison of Energy Efficiency
• Concluding Remarks

9. 9
TE Units Analysis
• The cold side absorbs heat based on the number of TE units, Nte, the
electrical current, Ite, the cold side temperature, Tc, and the temperature
difference, DTte
• The hot side releases the heat absorbed from cold side and the heat
converted from the electric power
Peltier effect: induce heat flow in the direction of electric current
Joules effect: heat generated because of electrical resistance
Conduction: heat transfer because of temperature gradient

10. Computational Fluid Dynamics (CFD) Model
• A CFD model is meshed by Gambit
• A steady-state heat transfer process is
simulated in FLUENT
• The outer pane, the middle pane, and the
air gap between them, are modeled as an
equivalent thermal resistance.
• Solar heating of the panes is modeled as
volumetric heat generation.
• The air flow and associated heat flux in the
ATI window are evaluated
• Qconv: the heat flux through the inner pane
10

11. Solar Insolation
• Accounting for the thermal
heat flux, Qconv , from FLUENT,
and the solar heat, Qsolar , the
total heat gain is QATI
Cross Section
Reflected
SR
Absorbed
SA
Solar radiation
Esky
11
• The incident solar radiation
is reflected from the outer
pane, absorbed by the panes,
or transmitted into the room

12. Heat Sink Analysis
• Pin spacing is defined by
the equation below.
• Pin diameter is 2.5 mm
Stanescu, G., Fowler, A. J., and Bejan, A., “The optimal spacing of cylinders in free-stream cross-flow forced convection,” International Journal of Heat and Mass Transfer, Vol. 39, No. 2, 1996, pp. 311–317
12
A p
S
d
W
TE Units
H
L

13. Fan Model
13
Top Left Top Right
Bottom Left Bottom Right
Left Most
Center Right
Center Left
Right Most

14. Fan Model
14
The Pressure Gradients of Fans
Δpavg : average pressure gradient produced by fans
k : the slope of the pressure gradients
• A linear pressure gradient profile is assumed.
• The total electric power consumption of all fans is less than
6% of that of the TE units. It is not minimized.

15. Control Systems
TE Units
15
Outside Temperature
Wind Speed
Solar Radiation
Thermometer
Anemometer
Light Sensor
Thermostat
Processor
Memory
TE Units Power
Controller
Fan Power
Controller
Fans
• Thermometer, anemometer, and light sensor are used to
sense outside temperatures, wind speeds, and intensity of
solar radiation.
• Thermostat is used to control electric power supplied to TE
units and fans.

16. Weather Conditions
16
Indoor weather conditions:
• Indoor temperature: 75 ℉ (297 K)
• Indoor heat transfer coefficient: 3.6 W/m2
Outside weather conditions:
• Outside temperature: 7 to 97 ℉ (259 to 309 K)
• Wind speed: 0 to 21.5 m/s
• Solar radiation: 0 to 1000 W/m2
• Number of weather conditions: 10 x 3 (the small set population size)
• Combinations: Sobol’s Quasirandom sequence generator algorithm
Heating condition: Outside T < Inside T (usually in winter)
Cooling condition: Outside T > Inside T (usually in summer)
“Comparative Climatic Data for the United States through 2008,” Tech. rep., http://www.noaa.gov.
Colaco, M. J., Dulikravich, G. S., and Sahoo, D., “A response surface method-based hybrid optimizer”, Inverse Probl Sci Eng, Vol. 6, No. 16, 2008, pp. 717–
7S4o1bol, I. M., “Uniformly Distributed Sequences with an Additional Uniform Property,” USSR Computational Mathematics and Mathematical Physics, Vol. 16, 1976, pp. 236–242.

17. 17
Adaptive Optimization Problems
Heating Cooling

18. Approximation of CFD Model
• Local surrogate models are built during the
optimization to reduce computational time.
• Trust region method is used to manage the
approximation
• Surrogate model was created using extended radial
basis functions (ERBF)
18

19. Weather Conditions and Optimization Results
19
No. 1 2 3 4…… 28 29 30
Outside T (K) 284.0 296.5 271.5 277.8…… 298.8 273.8 280.1
Outside T (℉) 51.5 74.0 29.0 40.3…… 78.2 33.2 44.5
Wind speed (m/s) 10.75 5.38 16.13 8.06…… 0.34 11.09 3.02
Solar radiation (W/m2) 500 750 250 625…… 359 859 234
Vte (V) 1.14 0.97 3.28 1.34…… 1.37 1.86 1.84
Δpavg (Pa) 0.96 0.95 1.77 1.00…… 1.75 1.89 2.00
k 0.07 0.07 0.02 0.08…… 0.01 0.01 0.02
Red: heating conditions (Outside T < Inside T)
Blue: cooling conditions (Outside T > Inside T)

20. Optimization Convergence History
20
Convergence History of f(x) under Weather Condition 2
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Number of Function Evaluations

21. Surrogate Models of Optimal Operations
21
Quadratic Response Surface Method
Optimal

22. Surrogate Models of Optimal Operations
• The three functions are stored in the memories of the thermostats
• With the inputs from the sensors, the thermostat evaluates Vte , Δpavg, and k.
• Within the defined ranges of weather conditions, the operation of ATI
22
windows is optimal.
Outside Temperature
Wind Speed
Solar Radiation
Surrogate
Model
(Thermostat)
Inputs
Vte
Δpavg
k
TE Units Power
Controller
Fan Power
Controller
Power of
TE Units
Power of
Fans
Outputs

23. Comparison with Passive Windows
3-Pane
23
• Calculate the amounts of heat
transferred through passive 3-
pane window in the same
weather conditions by
WINDOW software.
• WINDOW is a software developed by
Lawrence Berkeley National Laboratory
to analyze window thermal and optical
performance.
Clear Glass
Air Gap
Bronze Glass

24. Comparison of Heat Flux
24
Heating conditions (higher is better)
Convective Heat (W)
Weather Condition Number
+: Out -> In
− : In -> Out

25. 25
Comparison of Heat Flux
Cooling Conditions (lower is better)
Convective Heat (W)
Weather Condition Number
+: Out -> In
− : In -> Out

26. Comparison of Energy Efficiency
26
Coefficient Of Performance (COP) is a measurement of energy efficiency.
The COP of a standard HVAC system is about 3.
The COP of an ATI window, COPATI, is defined as how much heat flux is reduced,
compared with a passive window with the same structure, divided by the electric
power used.

27. Comparison of Energy Efficiency
27
45
40
35
30
25
20
15
10
5
3
0
COP of ATI Window
COP of HVAC
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Weather Condition Number
Heating conditions: COP of the ATI windows is generally higher.

28. 28
Concluding Remarks
• Adaptive optimization is performed to optimize the
performance of the ATI window under different weather
conditions.
• Provide active control of the ATI window to adapt to different
weather conditions using surrogate modeling.
• High energy efficiency is generally achieved under heating
conditions.

29. 29
Thank you

30. Questions
30