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Ingeniería Y Competitividad, Volumen 19, No. 1, P. 230 - 240 (2017)
CIVIL ENGINEERING
Analysis of the environmental sustainability of buildings using
BIM (Building Information Modeling) methodology
INGENIERÍA CIVIL
Análisis de sostenibilidad ambiental de edicaciones empleando
metodología BIM (Building Information Modeling)
Yabin Jiménez-Roberto*, Juan Sebastián-Sarmiento*, Adriana Gómez-Cabrera**§, Gabriel Leal-del Castillo***
*Facultad de Ingeniería, Ingeniería Civil, Ponticia Universidad Javeriana. Bogotá, Colombia.
**Grupo de investigación Estructuras y Construcción, Ponticia Universidad Javeriana. Bogotá, Colombia.
***Departamento de Arquitectura, Grupo de investigación Ecosistemas Antrópicos,
Ponticia Universidad Javeriana. Bogotá, Colombia.
yabin.jimenez@javeriana.edu.co, j.sarmientoc@javeriana.edu.co,
§adrianagomez@javeriana.edu.co, gleal@javeriana.edu.co
(Recibido: Junio 13 de 2016 – Aceptado: Noviembre 01 de 2016)
Abstract
The construction sector is currently facing two important challenges with regard to minimizing the environmental impact
of its projects and improving the efcacy of the construction processes, providing clients with adequate solutions that meet
their requirements. In response to the need to complete projects that satisfy environmental requirements, methodologies for
project integration known as Building Information Modeling (BIM) have emerged in recent years. These methodologies
enable the generation of digital models that contribute to minimizing errors and to the early detection of incompatibilities,
and they allow participants to work in an integrated manner. These methodologies show notable synergy with sustainability,
as digital modeling provides information about the performance of projects during their useful life, enabling the analysis of
different options to minimize their environmental impact. The objective of the present study is to examine the performance
of a construction project in Colombia in terms of sustainability by using a BIM platform to determine the electrical energy
consumption, the carbon footprint of materials, and the total energy incorporated into the project using simulations. In
addition, the generation of alternative designs and the analysis of the results will be performed considering the economic
viability of the proposed scenarios.
Keywords: Building Information Modeling, energy modeling, GREEN BIM, sustainable construction.
Resumen
En la actualidad el sector construcción afronta dos importantes retos relacionados con disminuir el impacto ambiental de sus
proyectos y lograr una mayor eciencia en los procesos constructivos, entregando a los clientes soluciones apropiadas que
cumplan los requisitos. Como respuesta a la necesidad de lograr proyectos que respondan adecuadamente a las necesidades
del entorno han surgido en los últimos años metodologías de integración de proyectos, conocidas como Building Information
Modeling (BIM), que permiten generar modelos digitales de proyectos que contribuyen a minimizar errores, detectar
tempranamente incompatibilidades y permiten a los participantes trabajar de manera integrada. Estas metodologías tienen una
notable sinergia con la sostenibilidad, pues a partir de las modelaciones digitales es posible conocer aspectos el desempeño
de los proyectos durante su vida útil y poder analizar diferentes opciones que minimicen sus impactos ambientales. El
presente estudio se enfoca en determinar el desempeño, en términos de sostenibilidad, de un proyecto de construcción de
una edicación en Colombia, utilizando una plataforma BIM para determinar a partir de simulaciones el consumo energía
eléctrica, huella de carbono por materiales y la energía incorporada total del proyecto, generando diseños alternativos y
analizando los resultados contemplando la viabilidad económica de los escenarios planteados.
Palabras clave: Building Information Modeling, construcción sostenible, GREEN BIM, modelación energética.
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1. Introduction
Construction projects are increasingly complex,
and this situation has generated different
alternatives that promote an integrated project
management approach that takes all interested
parties into consideration. One of the alternatives
that has spread with great force in the past
decade is the BIM methodology or “Building
Information Modeling”, which consists of
the generation and management of data for a
project (usually a building project) during its
life cycle (Bryde et al., 2013). The adequate
implementation of BIM can have a positive
impact on the protability of a project and on
the compliance with specications (Xu et al.,
2014). A BIM model is the digital representation
of the components of a construction project
generated by creating associated graphs, data
attributes, and parametric rules that promote the
integrated work of all involved professionals.
This diminishes incompatibilities in the design,
generating value in the construction projects.
Advantages such as an improved calculation
of the labor amounts, optimization of the
implementation programming, and diminished
administration costs associated with the project
and contingencies are evident (Barlish &
Sullivan, 2012; Cao et al., 2015). These models
initially include three dimensions that represent
the proposed project in a digital model, to
which the necessary dimensions can be added
according to the planned analysis of the building
project. These dimensions include cost and
timing of the project, analysis of sustainability,
construction operations, analysis of comfort,
and lighting among others. This provides a clear,
detailed and concise perception of the building
project during the planning and construction
stages (Love et al., 2014).
Another challenge faced by the construction
sector in recent years is how to minimize
the environmental impact of its activities.
According to the Intergovernmental Panel on
Climate Change (IPCC) established by the UN,
there is unequivocal evidence that the world’s
buildings account for 32% of the global energy
consumption and 19% of greenhouse gas
emissions. According to projections, the energy
consumption of buildings at a worldwide level
could be duplicated or even triplicated by the
year 2050. This report also revealed that the
immediate application of surveillance rules
both for new and remodeled buildings would
attenuate the existing risk. The main mitigation
strategies address the efciency of carbon,
the energy efciency of the technology, the
system and infrastructure efciency, and a
reduction of the demand for services through
the implementation of behavioral and lifestyle
changes. (Intergovernmental Panel on Climate
Change (IPCC), 2014). These two challenges
should not be addressed in a separate manner, as
an adequate management and the integration of
the parties involved in the construction projects
will generate interesting future impacts. BIM is
a powerful tool for dynamic decision making
during the entire life cycle of projects and has
become an avant-guard trend regarding the
concept of integration of projects known as
Integrated Project Delivery or IPD (Kent &
Becerik-Gerber, 2010), enabling and improving
collaboration and communication among the
parties involved in a project. This leads to
the generation of more efcient designs as a
result of the cooperation between the different
interested parties (Tenget al., 2012; Baiden &
Price, 2011). In addition, several companies
consider the IPD concept as the most efcient
method to integrate BIM as a design tool to
determine the performance of buildings in
terms of sustainability (Bynum et al., 2013;
Jones, 2014).
The sustainability dimension of the BIM model
includes different aspects, such as the analysis of
indoor thermal comfort, the simulation of energy
costs such as those associated with lighting, the
simulation of sources of renewable energy, and
the determination of the carbon footprint among
others. These novel trends for the application of
BIM methodology to the analysis of sustainability
have been termed GREEN BIM (Azhar et al.,
2011; Wong & Zhou, 2015; Sadeghifam et al.,
2015). Previous studies report that construction
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Ingeniería Y Competitividad, Volumen 19, No. 1, P. 230 - 240 (2017)
companies use BIM methodology with the
support of specialized software for the analysis
of sustainability, with the aim to reduce the
environmental impact of the construction
sector, and in many cases, this has become a
prerequisite of the projects on the part of the
client (Hwang & Ng, 2013; Zuo & Zhao, 2014;
Wong & Zhou, 2015). At a global scale, there
is denitely a need to invest in environmentally
sustainable designs to reduce the potential
progression of global warming (Hertwich &
Peters, 2009). Another recent study highlights the
importance of considering the carbon footprint
when choosing a system for the construction
of buildings. Five construction systems were
compared by estimating the carbon footprint
of each one and by considering the emissions
during the extraction and transport of materials,
the construction, operation, and end of the life of
the building using a computational method. The
results showed signicant differences among the
different designs, justifying the importance of
considering the carbon footprint as a variable in
the selection of a construction system (Moussavi-
Nadoushani & Akbarnezhad, 2015).
In Colombia, this trend has not been foreign
to the construction sector, and projects are
currently applying for international sustainability
certication systems. Additionally, Colombia
is the fourth country in Latin America with
the largest number of registered projects to
achieve Leadership in Energy & Environmental
Design (LEED) certication, a system proposed
by the US GREEN BUILDING COUNCIL
(USGBC) for the certication of buildings
(USGBC, 2016). The present study is a case
analysis of sustainability of a building using
BIM methodology, with the support of software
tools for the analysis of the applicability of this
methodology in the country. The limitations,
advantages and disadvantages of the proposed
tools and the results achieved are described. The
research focused on determining the performance
in terms of sustainability, considering the
Global Warming Potential (GWP) index, which
corresponds to an estimation of the equivalent
kilograms of CO2, as the main indicator of the
environmental impact of buildings. This analysis
considered global warming as the main challenge
faced by society (Ortiz et al., 2009) and that at a
global scale, there is a need to invest in reducing
the GWP associated with construction (Bynum
et al., 2013). In this way, it was possible to
determine the consumption of electrical energy,
the carbon footprint of materials, and the total
energy associated with the project under the
original de-sign and by analyzing alternative
designs.
2. Methodology
The project was designed for a building in the
city of Bogotá D.C. that consists of nine oors
and a basement in a total building area of 11
400 m2 and a lot of 1100 m2. According to the
information provided, this building is intended
for use mainly as ofce space. The foundation of
the building consists of several deep foundation
piles constructed by manually digging caissons
using an inverted cone ring system, embedded
at a depth of 8 to 14 meters. The caissons are
connected by grade beams. Additionally, there is
a containment system consisting of conventional
walls in 30 cm thick reinforced concrete with
a height of 4 to 7 meters. The structure of the
building is based on reinforced concrete and
a metallic structure, with glass façades and
oating façades with a sandwich-type cover. The
interior consists of rooms separated by walls
of concrete masonry, although there are also
glass and prefabricated walls to a lesser extent.
A BIM model of the building was generated
initially, followed by an analysis of the energy
consumption and carbon footprint.
2.1 BIM model
The BIM model was developed using the
ArchiCAD 18 software based on previous
information on the architectural and structural
plans of the building. This provided information
on the stairs, façades, the type of metallic
structure, and the types of doors and windows
among others. An image of the model is presented
in Figure 1.
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Ingeniería Y Competitividad, Volumen 19, No. 1, P. 230 - 240 (2017)
Figure 1. BIM model of the building.
When the architectural modeling was nished
and linked to the structural model, several
inconsistencies between the two designs were
identied, especially at a higher level, where
the structure is metallic. Although the analysis
and reporting of these inconsistencies was not
included in the planned work, as an additional
experience, this information was shared with
the persons in charge of the construction, which
provided feedback on the construction process of
the work underway. This is one of the advantages
of the early implementation of the BIM model
during the design integration phase.
Additionally, information was collected on
lighting and the mechanical ventilation and air
conditioning systems that were considered for
this building. For the lighting, the values used as
design parameters were derived from the technical
design of the lighting system to be installed,
such as potency, useful life, color temperature,
luminosity (lumens), and reference values. These
are the basic criteria that were used as a starting
point to search for design alternatives.
In this model, the types of material used and
budgeted in the construction of the building were
considered, and the database was consolidated
with the physical properties required by the
ArchiCAD program, which are as follows:
Thermal conductivity: this refers to the amount/
velocity of the heat transmitted by a material. Units
of measurement: W/mK (watts per Kelvin meter).
Density: Mass per unit of volume. Unit of
measurement: Kg/m3.
Incorporated energy: “The sum of all primary
energy consumed in the fabrication and supply
of products, including extraction, processing
and rening, transport, production, packaging
and shipping to the destination in immediate
use conditions without the need for further
manipulation”. Unit of measurement: J/Kg K
(Joule per kilogram Kelvin).
Incorporated carbon: dened as “the total amount
of carbon dioxide emission or that of equivalent
gases associated with the energy incorporated into
a product”. Unit of measurement: KgCO2/Kg.
Thermal transmittance or U value: This is one
of the most important physical properties that
denes environmental design. It corresponds to the
measurement of the heat that ows per unit of time
and surface through an element of construction.
According to the type of material, the covering
structure and the thickness, a greater or lesser thermal
bridge is generated. The U value represents the
speed of the transfer of heat, with a greater thickness
and smaller thermal conductivity generating a lower
thermal ow. Unit of measurement: W/m2 K (watt
per square meter Kelvin).
It is important to clarify that information on
incorporated energy and carbon was not found
in either the project documents or the technical
specications provided by the suppliers or under
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Ingeniería Y Competitividad, Volumen 19, No. 1, P. 230 - 240 (2017)
consultation with the latter; therefore, the default
values included by ArchiCAD in its library of
materials, which are derived from international
research, were used.
2.2 BEM model
The term Building Energy Model or BEM refers
to a simulation tool for the calculation of thermal
charge and energy utilization for residential and
commercial buildings. These models are normally
used in the design of new buildings and in the
renovation of existing buildings with the objective
of predicting the use of energy based on the
architecture and ventilation systems, heating, and air
conditioning. This type of model has existed since
the 80s and has been further developed to become
more detailed and precise. Therefore, current
programs have the capacity to perform simulations
taking into consideration the construction materials
in combination with ventilation, heating and air
conditioning systems. In addition, it is possible to
model methods for energy conservation, such as the
use of renewable energy (Ryan & Sanquist, 2012).
2.2.1 Surrounding denitions
To generate the BEM model, the project was rst
georeferenced using Google Earth (.kmz), with
the coordinates latitude, longitude, and elevation
(Figure 2).
Figure 2. Project location data.
2.2.2 Weather data
The Ecodesigner STAR® platform, which was
used for the sustainability analysis, automatically
included general weather data for the city of Bogotá
imported from ASHRAE IWEC (International
Weather for Energy Calculation). These data were
provided by EERE (Energy Efciency & Renewable
Energy) of the United States Department of Energy.
2.2.3 Denition of thermal block
A thermal block for the Ecodesigner STAR®
platform is the collection of zones (spaces) that have
similar energy demands, human load, and usage.
These spaces are included in the three dimensional
model, with the tool “Zone” representing the air
contained in the interior of the structure that is in
contact with architectural elements such as walls,
doors, and windows among others. Each thermal
block is assigned independent energy demand and
usage parameters; for the building analyzed, a total
of 152 zones were dened that were contained in 12
previously proposed thermal blocks. The generation
of zones is illustrated in Figure 3.
Figure 3. Organization of Zones into Thermal Blocks.
2.2.4 Denition of operation proles
Operation proles determine the type of usage of the
thermal block as well as the thermal demands and
human load. Then, the hours of usage or operation
for each zone are introduced into the daily schedule.
In the rst place, the range of dates of operation of
the thermal blocks was dened according to their
usage. This information allows calculation of the
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Ingeniería Y Competitividad, Volumen 19, No. 1, P. 230 - 240 (2017)
thermal gain per person, which refers to the amount
of energy emitted by the persons in the interior of
the building. This value varies according to the
physical activity level of the individuals included
and ranges from approximately 72 to 990 Watts per
person. The internal thermal gain due to lighting
can also be calculated, which refers to the potency
of the lighting system assigned to each thermal
block. The initial potency values were obtained
from the current design of the building, and lastly
the thermal gain due to equipment is added,
which consists of the total energy expenditure of
computers and other electrical devices per unit of
area. Table 1 shows the entry data corresponding to
the initial design.
Thermal Block
Human
Heat Gain
(W/m2)
Lighting
Data
(W/m2)
Equipment
Data
(W/m2)
Auditoriums 22.84 7.57 3.72
Bathrooms x 1 39.99 7.46 2.00
Bathrooms x 5 41.92 9.98 2.00
Dining Hall 53.24 8.20 30.45
Hallways 24.77 6.75 2.00
Storage Area 24.89 4.45 2.00
Ofces + 20 31.00 11.65 36.49
Ofces x 3 31.68 12.33 25.34
Ofces x 5 29.47 10.58 25.91
Ofces x 9 25.92 12.20 32.77
Halls 59.24 10.10 9.44
Table 1. Internal heat gain of the operation
proles for the different thermal blocks used.
2.2.5 Denition of construction systems –
Ventilation and Refrigeration
Later, construction systems associated with the
ventilation and refrigeration equipment of the
building were taken into account. Information
was collected on the mechanical ventilation and
air conditioning systems included in the design.
Regarding the specications of the mechanical
ventilation system used in the design of the building,
information on ow and external pressure of the
building were mainly included in the mechanical
ventilation data. Data on ow or air volume, capacity
of the equipment, and external static pressure were
considered for the refrigeration system.
2.2.6 Factors affecting the origin and cost of
electrical energy
The Ecodesigner STAR® platform enables the
entry of factors as percentages according to their
involvement in the production of electrical energy. On
the basis of these resources, the Ecodesigner STAR®
platform estimates the CO2 carbon footprint emission
(Kg/kWh). Despite the fact that the electrical energy
in Colombia is mostly derived from hydraulic sources,
the energy consumption of a building constitutes one
of the main sources of carbon footprint associated
with the construction of buildings.
2.2.7 Link between BIM and BEM models –
Energy Modeling
To generate a complete model that enables energy
simulation, a connection must be established bet-
ween the architectural parameters and the zones
representing the interior air of the structure. The
Ecodesigner STAR® platform recognizes the
architectural elements that cover the surface of the
zones as structures and/or openings that directly
affect the thermal behavior of a building. Therefore,
it is essential to verify that the architectural model
covers the interior volumes of the structure;
otherwise, the results obtained with the energy
simulation are obsolete because of false air currents
and unknown volumes and temperatures. Figure
4 shows the link between the BIM model and the
zones representing the BEM model.
Figure 4. Link between the BIM and BEM models.
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In the link between the BIM and BEM models, the
program automatically calculates the U value of
each element according to the previously determined
thermal properties of the materials and the thickness.
2.2.8 Possible alternatives to improve the
performance of a building
To perform simulations representative of alternative
scenarios, the following alternatives were dened
to improve the performance of the building.
Scenario 1 – Implementation of solar panels for
the supply of renewable energy: The rst scenario
was based on the use of the renewable energy
of the building through the installation of solar
panels on the shell of the building. The maximum
possible number of panes was modeled, excluding
the areas of circulation and maintenance of the
roof. The installation of 228 solar panels was
modeled with the characteristics listed in Table 2:
Type of cell of the panel Polycrystalline
Nominal power (W) 250
Efciency of the panel P (%) 15.2
Temperature power coefcient (% / ºC) –0.47
Panel length (m) 1.652
Panel width (m) 0.994
Total area of the panel 1.642
Table 2. Characteristics of the simulated panels.
The simulated placement of the panels is shown
in Figure 5:
Figure 5. Photovoltaic roof panels.
Scenario 2 – Lighting change: The second alternative
scenario proposed a change from the uorescent
lighting system proposed in the design to LED
type lighting. The modication of approximately
50% of the total lighting system was planned while
maintaining the same lighting requirements of the
interior of the building.
Alternative design proposal: This is the combination
of the two previously mentioned scenarios.
3. Results and analysis
3.1. Temperature and thermal comfort of the
building
Within the architectural design, an analysis of
the building temperature was not considered,
which could affect the thermal comfort of the
nal users and the operation of the ventilation
and refrigeration systems of the building. This
calculation can be performed for the different
zones of the building, taking into consideration the
environmental conditions of the project and the
thermal properties of the materials. For the case in
study, in many instances the simulation resulted in
a temperature that was higher than the estimated
thermal comfort in a range of 20 to 26°C. Figure 6
shows an example of an analysis of the ofce zone.
Figure 6. Initial Design – Daily Temperature
Prole. Source: Own.
3.2. Energy consumption and CO2 emissions
Regarding scenario 1, the savings are shown in
Table 3.
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Electrical energy
(kWh/a)
CO2 emission
(kg/a)
Initial design 592,698 106,685
Solar panels 508,646 91,556
Savings 14.18% 15,129
Table 3. Savings generated through the use of solar
panels. Own source.
A comparison of the total direct cost of the design
budget indicates that an additional investment of
1% of this value is needed to produce renewable
energy through the installation of solar panels.
Regarding scenario 2, the implementation of the
LED design represents considerable savings on
the electrical consumption as shown in Table 4:
Electrical energy
(kWh/a)
CO2 emission
(kg/a)
Initial design 592,698 106,685
LED lighting 474,359 85,384
Savings 20.0% 21,301
Table 4. Savings generated through the use
of LED lighting.
A comparison of the total direct cost of the ori-
ginal design budget indicates that an ad-ditional
investment of 2.6% of this value is needed for the
implementation of the changes. It is important to
note that this type of lighting lasts 2 to 3 times
longer than the lighting proposed in the original
design. Regarding the results of scenario 3 of
the alternative design, the savings are shown in
Table 5:
Electrical energy
(kWh/a)
CO2 emission
(kg/a)
Initial design 592,698 106,685
Alternative design 396,084 71,295
Savings 33.2% 35,390
Table 5. Savings generated through the use of
LED lighting and solar panels.
A comparison of the total direct cost of the
original design budget indicates that an additional
investment of 3.4% of the total cost of the project
is needed to implement the proposed changes.
Figure 7 shows a comparison of the necessary
investment for each case analyzed and the savings
in terms of energy.
Figure 7. Direct cost of the project and annual
electrical energy cost for each analyzed case.
The operation of the building generates carbon
dioxide emissions that are registered annually
in the reports. In addition to contamination
derived from usage, the building generates
a carbon footprint associated with its own
construction; this includes the materials used and
the construction processes planned for the total
development of the project. The construction area
of the project occupied a total of 11,400 m2, and
Figure 8. Projection of accumulated emissions for
each proposed design for the building.
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Ingeniería Y Competitividad, Volumen 19, No. 1, P. 230 - 240 (2017)
Lifecycle of the building (years) 50
Investment for the implementation of
the alternative proposal (COP) 1,228,795,550
Energy cost (COP/kWh) 270
Annual electrical energy savings (kWh) 53,085,780
Annual increase in public services (%) 3.0%
Capital cost for the entity of project
development (%) 3.0%
Table 6. Input parameters for the cash ow
statement of the alternative design.
In this manner, variables important for the deter-
mination of the viability of the investment can
be calculated, such as the present net value, the
internal return rate, and the return period. Similarly,
it was assumed that the income in this cash ow
was the annual savings in terms of electrical energy
according to the proposed alternative design. The
expenditure considered for this cash ow was a
value corresponding to the investment necessary for
the implementation of the elements that compose
the alternative design (Figure 9).
after distributing the contaminating load over the
entire surface, the contamination associated with
the building was calculated as 358.37 Kg/m2.
The contaminating load per unit of construction
area for the suggested alternative was 355.14 Kg/
m2. The contaminating load for the alternative
design could reach signicantly lower values
compared with that of the initial design if
sufcient information is available regarding the
materials used in our country. Figure 8 shows a
comparative analysis of CO2 emissions for each
scenario, including the original design, taking
into account that these emissions are generated
starting in the year in which the building becomes
fully functional, which is the year 2016. This
analysis is performed considering a life cycle for
this building of 50 years.
To determine the feasibility of the design proposal,
it is necessary to perform a projection of the cost of
the energy demand of the building. For this purpose,
a cash ow statement was drawn considering the
parameters included in Table 6:
Figure 9. Free cash ow for the implementation of the proposed alternative design.
Net present value - NPV (COP) 1,425,493,450
Internal return rate - ITR (%) 6.51%
Return period (years) 17
According to this cash ow, the following nancial
indicators were calculated for the year 2015 (Table 7):
Table 7. Financial indicators corresponding to
the investment necessary for the implementation
of the proposed alternative design.
4. Conclusions
The construction sector currently has virtual tools
available that are not widely used that enable the
optimization of designs to better respond to client
requests and to the environmental impact generated
by its activity. Digital models should be required by
project developers because they add value to projects
by analyzing different scenarios, the analysis of
which would be complex without these models.
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The present study indicated that the annual
consumption of the original design of the building
was 592.698 kWh/a and the CO2 emission was
106.685 Kg CO2/a. The combined alternative
design, which requires an additional investment
of 3.4%, was predicted to have an annual energy
consumption of 396.084 kWh/a and a CO2
emission of 71.295 Kg CO2/a. This suggests a
potential savings in the consumption of electrical
energy of up to 33.2%.
The two proposed scenarios would also
independently generate considerable savings with
minimal investments. Additional investments
of 0.8% and 2.6% of the budget of the original
design are required to implement scenarios 1
and 2, respectively, achieving savings in the
consumption of electrical energy of 14.2% and
19.97%, respectively. These percentages can be
implemented if sustainability is considered as a
factor from the time of conception of the project.
Under the economical terms, the construction
of the building with the proposed alternative
design is feasible under the nancial indicators of
NPV and ITR, since the NPV is greater than the
additional investment costs, and the ITR is greater
than the capital commitment costs.
The implementation of energy models with the tools
used in this case requires special care from the start
of the BIM model by dening the thermal blocks and
becoming familiar with the properties of the materials
to be used. In this manner, it is possible to perform an
adequate and rapid BEM modeling with the objective
of achieving a precise, consistent, and error free
energy simulation that can provide information on the
energy and thermal comfort aspects.
To improve the accuracy of the incorporated energy
and carbon values for the buildings in our country
it is necessary to conduct studies on these values
for the construction materials used in Colombia, as
these depend directly on the processes of extraction
of raw matter, production, and transfer among
others. In addition, to perform a more precise
energy simulation, it is necessary to have the Total
Solar Transmission (TST, %) and Direct Solar
Transmission (DST, %) values for the window
system used.
An important advantage of the Ecodesigner STAR
platform is the generation of comparative reports
addressing the energy simulations in comparison
with a basic line. This allows an analysis of the type
“What if”. In addition, it allows the combination
of different scenarios in a virtual surrounding that
imitates reality, and it permits consideration of
additional data that may aid decision making to
achieve the construction of sustainable buildings that
can respond to the specic needs of the environment
while minimizing the carbon footprint.
5. Acknowledgements
The authors thank Ponticia Universidad
Javeriana for its support of the research project
that was the basis of this article with ID PPTA
00005797 “Integración de herramientas digitales
para planeación y control de proyectos civiles”.
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