2. Structural Optimization including whole
life cost of a Timber Building using
evolutionary algorithms
Georgios K. Bekasa, Georgios E. Stavroulakisb
a,b Department of Production Engineering and Management, Technical University of
Crete, Greece
2
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
3. OUTLINE
• Objectives
• Optimization process and scenarios
• Life cycle costs of the examined subsystems
• Variables of the optimization problem
• Service lives prediction for the examined subsystems
3
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
4. OUTLINE
• Model
• Objective function
• Constraints
• Optimization methodology
• Conclusions
4
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole
life cost of a timber building using evolutionary algorithms
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
5. OBJECTIVES
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
5
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
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16 – 18th March 2016
6. OBJECTIVES
• Minimization of the whole life cost (initial construction cost
+ operational/maintenance costs) of the mechanical, the
energy and the structural subsystems of a timber building.
• Examined parameters: heating and cooling costs, building
envelope insulation profiles, window sizes, photovoltaic
array sizing, air-conditioning system type and number of
units, lighting control system, frame type (frame bay length
optimality), spacing among frames, sizing of cross sections.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
6
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
7. OBJECTIVES
• Modeling is based on the Eurocodes and KENAK (that is the
Greek national interpretation of European standard EN ISO
13790).
• The examined costs are based on real market data and when
it was considered helpful, statistical and machine learning
techniques were used to facilitate computational efficiency.
• Ultimately, the proposed approach allows for more efficiency
in the usage of resources.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
7
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
8. OPTIMIZATION PROCESS AND SCENARIOS
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life cost
of a timber building using evolutionary algorithms
8
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
9. OPTIMIZATION PROCESS AND SCENARIOS
• The present study -unlike similar ones- aims to a
holistic cost optimization (considering all the critical
mechanical, energy and structural subsystems) of a
timber building.
• Subsystems such as frame bay length optimality and
spacing among frames are very rarely encountered in
similar structural optimization studies.
• Furthermore, most similar energy performance
optimization studies focus mostly on minimizing
energy consumption -not the whole life cost- of each
critical subsystem.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
9
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
10. OPTIMIZATION PROCESS AND SCENARIOS
The relationship between the useful life of the optimized
subsystems and the whole life cost of the building, is
also examined by considering three different periods:
• Scenario 1:
15 years
• Scenario 2:
25 years
• Scenario 3:
35 years
Session 4- 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
10
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
11. LIFE CYCLE COSTS OF THE EXAMINED SUBSYSTEMS
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
11
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
12. LIFE CYCLE COSTS OF THE EXAMINED SUBSYSTEMS
The main considerations (that reflect a score of 50% economic efficiency
and 50% environmental friendliness), are the following:
• The mineral wool wall insulation profiles and the gypsum boards are
expected to end up in a landfill.
• The PV array requires replacement of the inverter (indicative useful life:
every 5-10 years). The periodic removal of the dust concentrated on the
panels is a negligible cost.
• The maintenance rates for the structural frames are considered to be
equal to 4% of their initial value per year, with a start point 5 years after
its construction .
• The maintenance rates for rest of the building are considered to be
equal to 1% of its initial value per year, with a start point 5 years after its
construction.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
12
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
13. LIFE CYCLE COSTS OF THE EXAMINED SUBSYSTEMS
• For the HVAC systems, the maintenance rate is considered to
be equal to 2% of their initial value (unaffected by inflation
rates) per year.
• The residual NP values of the building components
(windows, structural frames, walls, insulation profiles) will be
ignored, reflecting a predefined design assumption that the
building owner would not be interested to recycle them or
reuse them at the end of its life cycle.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
13
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
14. VARIABLES OF THE OPTIMIZATION PROBLEM
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
14
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
15. VARIABLES OF THE OPTIMIZATION PROBLEM
• Building envelope u-values.
• Area of windows (south elevation and north elevation). In the
simulation, it is assumed that area of windows at the south
elevation and north elevation can have a value between 20 and
150 m2.
• Area of windows (all other elevations). It is assumed that area of
windows can have a value between 10.50 and 100 m2.
• ggl value (window glass solar heat gain coefficient; it is assumed
that it can have a value between 0.29 and 0.55).
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
15
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
16. VARIABLES OF THE OPTIMIZATION PROBLEM
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
16
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
17. VARIABLES OF THE OPTIMIZATION PROBLEM
• Type of air conditioning system based on its energy parameters
(SCOP (Seasonal coefficient of performance), SEER (Seasonal
energy efficiency ratio), Power in kW). 25 different A/C types
were considered.
• Number of A/C units: between 1 and 15.
• Variable examining whether the existence of lighting control is a
cost-effective decision or not.
• Heating energy needs during the day of winter that exhibits the
lowest levels of solar irradiation that can be covered by a
photovoltaic panel array, in a way that a 4-day autonomy is also
ensured: between 0 and 20 kWp.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
17
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
18. VARIABLES OF THE OPTIMIZATION PROBLEM
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
18
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
19. VARIABLES OF THE OPTIMIZATION PROBLEM
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
19
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
20. VARIABLES OF THE OPTIMIZATION PROBLEM
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole
life cost of a timber building using evolutionary algorithms
20
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
21. VARIABLES OF THE OPTIMIZATION PROBLEM
• Variable related to the spacing between the structural frames (4 possible choices
corresponding to a number of equally spaced frames between 3 (30/3 = 10 m) and 6
(30/6 = 5 m)).
• Variable related to the form of the frames that compose the building whose change
influences the number of bays (4 possible choices leading to a total number of
beam-column elements between 13 and 19).
• Variables related to the lengths of the front beams. The front elevation is considered
to be the one that is equal to 35 m, therefore the front beams are the ones along
that direction. Each front beam length is considered to have a value between 3 and 6
meters.
• Variables related to the cross sections of the ground floor columns that compose
the structural frames. The following cross sections were considered in the
simulation: b = 100 mm h = 100 mm, b = 125 mm h = 125 mm, b = 150 mm h = 150 mm, b = 175 mm h = 175 mm, b =
200 mm h = 200 mm, b = 225 mm h = 225 mm, b = 250 mm h = 250 mm, b = 275 mm h = 275 mm, b = 300 mm h = 300
mm, b = 325 mm h = 325 mm, b = 350 mm h = 350 mm, b = 375 mm h = 375 mm, b = 400 mm h = 400 mm, b = 425 mm h
= 425 mm, b = 450 mm h = 450 mm, b = 475 mm h = 475 mm, b = 500 mm h = 500 mm. (Where: b is the smaller
dimension, h is the larger dimension). Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
21
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
22. VARIABLES OF THE OPTIMIZATION PROBLEM
• Variables related to the cross sections of the upper floor
columns that compose the structural frames (same as above).
• Variables related to the cross sections of the front beams that
compose the structural frames. The following cross sections
were considered: b = 100 mm h = 200 mm, b = 110 mm h = 210 mm, b = 120 mm h = 220 mm, b
= 130 mm h = 230 mm, b = 140 mm h = 240 mm, b = 150 mm h = 250 mm, b = 160 mm h = 260 mm, b = 170
mm h = 270 mm, b = 180 mm h = 280 mm, b = 190 mm h = 290 mm, b = 200 mm h = 300 mm, b = 210 mm h
= 310 mm, b = 220 mm h = 320 mm, b = 230 mm h = 330 mm, b = 240 mm h = 340 mm, b = 250 mm h = 350
mm.
• Variables related to the cross sections of the back beams that
compose the structural frames (same as above).
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
22
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
23. SERVICE LIVES PREDICTION FOR THE EXAMINED
SUBSYSTEMS
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
23
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
24. SERVICE LIVES PREDICTION FOR THE EXAMINED
SUBSYSTEMS
• Building Exteriors, Doors and Windows: 80 years.
• Mineral wool insulation profiles: 50 years.
• Photovoltaic panels: 25 years.
• HVAC systems: 15 years.
• Structural timber: 50 years.
• Lighting control systems: 15 years.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
24
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
25. MODEL
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
25
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
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16 – 18th March 2016
26. MODEL
• A two-storey
timber office
building, located
on Athens,
Greece.
• Plan view:
Rectangular
shaped, 30x35 m.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
26
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
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16 – 18th March 2016
27. MODEL
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
27
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
•Identical roof
and wall
insulation
profiles.
•A 5-day working
week, a 12-hrs
occupancy and
a continuous
type of heating
is assumed.
28. OBJECTIVE FUNCTION
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
28
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
29. OBJECTIVE FUNCTION
• total cost = cost of insulation + Heating cost*Number of
years + Cooling cost*Number of years + cost of A/C system +
cost of windows + cost of roof + cost of walls + HVAC system
maintenance and replacements + general building
maintenance + cost of the floor slab + cost of photovoltaic
array + PV array maintenance and replacements costs +
frame costs + frame maintenance + illumination costs +
illumination control system cost + illumination control system
replacement cost + ∑pi
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
29
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
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16 – 18th March 2016
30. CONSTRAINTS
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
30
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
31. CONSTRAINTS
• The total area of the building windows should ensure
sufficient natural illumination and ventilation (at least 10%
of the total area of the building).
• The power of the heating system and the cooling system is
determined and through the constraints it is ensured that
the heating and the cooling needs are covered for the most
adverse days of the winter and the summer respectively.
• Functional structural constraints (ULS, SLS) are imposed
after a structural analysis for each beam and column, in
accordance with Eurocode 5.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
31
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
32. OPTIMIZATION METHODOLOGY
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
32
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
33. OPTIMIZATION METHODOLOGY
• Simulated annealing as well
as Genetic algorithms via the
use of the optimization
toolbox of Matlab.
• The second method in all
scenarios was found to be
faster.
• Nevertheless, the first
method is more suitable after
some relaxation of the
optimization search space
(when several initial optima
have been found).
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
33
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
34. CONCLUSIONS
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
34
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
35. CONCLUSIONS
• No optimal front beam length was less than 4.62 m. Moreover, the
optimal total number of elements in the building elevation that is
equal to 35 m, is 13 and the optimal spacing between frames -in
the building elevation that is equal to 30 m- is 10 m.
• For all scenarios, the most cost-effective combination for the HVAC
system is that of 3 units composed of A/C systems that fall into the
A-energy class category.
• For all scenarios, it seems more preferable to primarily place the
larger total area of windows on the north elevation (the elevation
with the least amount of solar gains) and secondarily on the south
elevation (the elevation with the highest amount of solar gains).
This is related to the chosen geographic location.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
35
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
36. CONCLUSIONS
• Due to the occupancy profile of the building it seems that for the
examined rates and periods of times the optimal mechanical
equipment does not change during the examined life cycle
periods.
• This is not necessarily the truth for other types of buildings; due to
the type and occupancy level of the building considered in the
simulation, a fast pay-off is attained that excludes other types of
photovoltaic arrays and combinations of A/C systems for the
examined periods from being the optimal solution.
• For all the examined scenarios, using a lighting control system is
not a cost-effective decision.
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
36
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016
37. Structural Optimization including whole
life cost of a Timber Building using
evolutionary algorithms
Georgios K. Bekasa, Georgios E. Stavroulakisb
a,b Department of Production Engineering and Management, Technical University of
Crete, Greece
37
Session 4 - 17.03.16
Georgios K. Bekas et.al - Structural optimization including whole life
cost of a timber building using evolutionary algorithms
EUROPE & THE
MEDITERRANEAN
TOWARDS A SUSTAINABLE
BUILT ENVIRONMENT.
Excelsior Grand Hotel
Valletta, Malta.
16 – 18th March 2016