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Optimisation of low exergy architecture in the tropics

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Optimisation of low exergy architecture in the tropics

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SUSTAINABLE FUTURE ENERGY 2012 and 10th SEE FORUM
Innovations for Sustainable and Secure Energy
21-23 November 2012, Brunei Darussalam
1
Paper Code: D08
Optimisation of Low Exergy Architectural Design in the Tropics
Chen Kian Wee1*, Arno Schlueter2, Patrick Janssen3
1 Singapore ETH Centre (SEC), Future Cities Laboratory (FCL)
2 Institute of Technology in Architecture, Department of Architecture, ETH Zürich, Switzerland
3 National University of Singapore
* Corresponding Author. Tel: (65)91596012, Fax: Nil, E-mail: kian.chen@arch.ethz.ch
Abstract: This paper describes the process of designing and optimising low exergy architectural design in the
tropical climate. The low exergy strategy used includes the separation of sensible and latent cooling and the use
of Building Integrated Photovoltaics (BIPV) for the generation of electricity. Low exergy emission cooling
systems such as radiant cooling panels and decentralised ventilation units are used. The radiant panels are
responsible for the sensible heat gain, while the latent heat gain is handled by the decentralised ventilation units.
The use of radiant panels has its limitation; if the sensible heat gain exceeds a certain limit the use of radiant
panels might not be feasible. Thus, a certain quality of building envelope is required. These constraints amount
to an architectural design issue where dependencies and interaction between the envelope design and building
systems are considered. The paper proposes an iterative design process that involves the use of parametric
modeling, simulation programs and optimisation techniques to help the architect to implement and explore
possible design options. A case study is described to illustrate the process; the BubbleZERO laboratory facade
design. The result of the design process will present to the architect a series of different designs that satisfy the
chosen criteria. This will greatly aid the architect in making design decision during the design process.
Keywords: Low exergy design, Parametric modeling, Performance driven design, Evolutionary algorithm in
architecture design
1. INTRODUCTION
The current building stock account for a significant amount of global CO2 emissions (Rogner, Zhou et al. 2007).
It is important for the building sector to reduce the CO2 emissions to minimise global warming. One of the major
contributing components is the burning of fossil fuels to power the operations of the building systems. Thus, it is
essential to reduce the energy consumption of building systems which is mainly caused by the heating
ventilation and air conditioning (HVAC) system in order to reduce the CO2 emissions, and substitute fossil
energy source with renewables. The conventional low energy architecture design strategies try to achieve this
objective by focusing on the use of passive systems. Low exergy design strategies take a more holistic approach
by incorporating both the passive and active systems.
In thermodynamics, exergy is defined as the maximum work that can be obtained from an energy flow. It
describes both the quality and quantity of an energy source. Exergy analysis is commonly used in the
optimisation of power station to maximise the production of exergy. In recent years exergy analysis has been
adapted for the analysis of energy consumption in buildings (Shukuya and Hammache 2002; Schmidt 2004). In
the building case, the aim is to reduce the amount of exergy input to sustain a comfortable indoor environment
for the users (Meggers and Leibundgut 2009). The exergy content of a heat flux moving out of an indoor
environment of temperature and outdoor reference temperature:
    
 (1)
Where Ex is the exergy content of the heat flux and Q is the heat flux in Joules (J), T o is the outdoor reference
temperature and Ti is the indoor temperature in Kelvin (K). If Ti < To , Q refers to the heat rejected from the
room and will be negative and (1-(To/Ti)) will be negative resulting in a positive exergy value (Jansen and
Woudstra 2010). For a room of temperature 25°C and an outdoor reference temperature of 32°C the exergetic
content needed to reject the heat is about 3%. The exergetic content of electricity is almost 100%. An exergy
approach would be to reduce the use of high exergy energy source and substitute it with an energy source of
appropriate exergetic content. The Building Systems Group at the ETH Zurich have extended the exergy
approach and implemented exergy strategies in building projects. They integrated an array of low exergy systems
to reduce the energy consumption. The key components of low exergy systems in temperate climates consist of
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heat pumps with ground boreholes, decentralised air supply units, P/V hybrid panels and radiant panels
(Meggers, Ritter et al. 2011). An attempt to transfer the technology from the temperate climate in Zurich to the
tropical climate in Singapore is carried out through the BubbleZERO research laboratory (Meggers, Bruelisauer
et al. 2012).
2. LOW EXERGY DESIGN STRATEGIES IN THE TROPICS
The low exergy strategy tested in the bubbleZERO laboratory focuses on the separation of the latent and sensible
cooling. Latent cooling is the dehumidification of air supply and it is an exergy intensive process compared to
sensible cooling, thus it would be beneficial by separating the two processes. The sensible cooling process is the
removal of heat generated from occupancy load, plug load and solar heat gain load. Through initial calculation
there is a potential of up to 20% reduction in energy consumption. This is done with the use of the heat pump,
radiant panels and decentralised ventilation technologies.
2.1 Heat pump (Chiller)
The heat pump moves heat from a cooler to hotter region. The efficiency of a heat pump is limited by the Carnot
value of Coefficient of Performance (COP):

  





(2)
Where g is the Carnot factor, it is usually around 0.5. Thot is the temperature of the hotter region and Tcold is the
temperature of the colder region in (K). By reducing the temperature difference between the indoor space and the
reference environment one can increase the COP of the heat pump. This will in turn reduce the energy
consumption for cooling down the space according to equation 3.

  
   
(3)
Where Exin is the exergy needed to remove the heat in the space in (J), it is usually supplied in the form of
electricity.
2.2 Separation of latent and sensible cooling
The latent or the dehumidification load is dependent on the occupancy of the indoor space. The higher the
occupancy the more fresh and dehumidified air that is needed for the occupants. This is provided through the use
of decentralised ventilation units. For dehumidification, the heat pump will need to produce chilled water of
around 8°C. The sensible load in the room is removed by the radiant panels. The required water temperature for
cooling is about 18°C. However, there are some constraints associated with the use of radiant panels. The
cooling capacity is dependent on the availability of cooling surface and the temperature of the supplied water.
Thus, if the heat gain is too high and there is insufficient cooling surface the radiant panels are not powerful
enough to remove the sensible heat load. This relationship is illustrated in equation 4. The architectural
implications of these system parameters are outlined in Table 1.

  

(4)
Table 1 The architectural implication of using radiant panels
System Parameters
Architectural Implications
Heat Gain
Improve the passive system of the building mainly the
envelope quality, window wall ratio, shading etc.
Heat Removal Rate
Decrease the supply temperature of the water to the
radiant panels and increase the heat removal rate.
There are limit to how low the temperature can go due
to human comfort and condensation issue.
Cooling Surface Needed
Factor in the availability of cooling surface needed for
the cooling into the design of the building. This could
be a unique architectural feature that arises from the
system consideration.
The conventional cooling process of not separating the two processes will requires C chilled water for the
system, resulting in a lower COP of the heat pump due to the high temperature difference according to equation
3. While the separation of latent and sensible cooling significantly reduces the temperature difference for the
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sensible cooling it will result in a better performance for the overall system.
3. BUBBLEZERO FAÇADE DESIGN PROCESS
The BubbleZERO is a research laboratory for test bedding new low exergy systems in the tropics. The low
exergy systems include the heat pump, 18m2 of radiant panels and decentralised ventilation units. The façades
(highlighted in red in Figure 1) on both end are modular and are interchangeable. A new set of façade is planned
for the next phase of the research. The white colour pneumatic bubble skin is constantly reflecting heat while the
constant flow of air in the bubble skin acts as high performance insulation for the interior. Capillary tubes run
along the interior walls of the bubble skin to regulate the surface temperature, so we could simulate
BubbleZERO as a space in a larger building. This case study presents the preliminary design of the BubbleZERO
façade. The bubble skin is not altered in the experiment.
The exergy approach increases the efficiency of the building system through the manipulation of temperature
differences and result in the reduction of the energy consumption. At the same time, it also looks at the supply
side of the equation for clean energy sources to substitute the use of fossil fuels. With the abundance of sun light
in the tropics, the application of Building Integrated PhotoVoltaics (BIPV) resembles a potential exergy source.
This is demonstrated in the design process of the new façade of the BubbleZERO laboratory where BIPV are
integrated into the façade design. The façade will also affect the daylighting for the interior space. For example,
if longer shades are added it will reduce the heat gain but at the same time reduce the interior daylighting. Thus,
the design requires the architect to not just look at the energy aspect but also many other issues such as
daylighting and costing in the project.
The pilot study of the BubbleZERO is a reference for the future façade design. The project has many existing
limitations such as the orientation, window size and glazing materials M-glass which was kept constant for the
experiment. But it is a simple and clear example to test out the exergy strategy and the design method proposed.
Figure 1 BubbleZERO laboratory
4. DESIGN METHOD
An iterative design method is used to explore and optimise possible low exergy design options. The design
method uses parametric modeling for generating design variants, evaluation methods for assessing the
performance of the design variants and lastly the use of optimisation technique to optimise the design. The low
exergy strategy described in section 2 will act as the basis for the design method.
Parametric modeling in architecture is the description of a design project using a series of parameters. These
parameters could be materials, geometrical, spatial configuration or even building systems properties. The
parameters are constrained or relational to each other. The parametric model is capable of generating design
variants by altering the parameters. This parametric model is referred to as the design schema (Janssen 2004).
The design schema captures the design intention of the architect and it is also influenced by the low exergy
strategy proposed. Recent development in Computer Aided Design (CAD) tools have made parametric 3d
modeling accessible to architects. Programs such as Rhinoceros Grasshopper, Generative Components and
Houdini 3d have made constructing parametric models manageable.
The evaluation methods can vary from complex simulations to just a simple cost factor calculation of the design
project. The generated design variants will be evaluated and an optimisation technique will be employed to
optimise the design variants based on feedback from the evaluations. In the design process, the architect will try
out different schema to test different design ideas and previous design schemas will serve as feedback for the
next schemas.
3.1 Evaluation methods
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In this case study four evaluation methods were used. The Envelope Thermal Transfer Value (ETTV) (Chua and
Chou 2010) was used for calculating the solar heat gain. The rest of the internal load was estimated and added
onto the solar heat gain. Substituting the internal load into the radiant panel equation, one could obtain the
surface area needed for the cooling. A 50W/m2 heat removal rate is assumed, this is the heat removal rate in
which 18°C chilled water can provide. Therefore, if a design variant has enough surface area to provide the
necessary cooling it will separate the sensible and latent cooling and have a higher COP and reduce the energy
consumption. On the other hand if a design variant does not have enough surface area for cooling, it will not be
able to separate its latent and sensible cooling and it will have a lower COP and therefore have higher energy
consumption. In this case, the cooling surface area available in the BubbleZERO is 18m2 as there are already
radiant panels installed. The energy consumption is measure in Watts (W).
For lighting simulation Radiance (Ward 1994) was used for both the evaluation of solar irradiation falling on the
façade for calculating energy generation from BIPV and also the daylighting evaluation. The Radiance
simulation calculates the amount of solar irradiation falling on potential surfaces on the façade in a year, which
surfaces are the potential surfaces are determined by the design schema. BIPV of 15% efficiency was assumed to
be used. It is expected that 15% of the total solar irradiation will be converted to electricity. The electricity
produced is measured in (Kwh/annual).
For the daylighting evaluation an interior grid was created where each point on the grid is measuring the
daylighting in lux. 300 lux is the level of daylighting required for doing task of general purposes such as reading
and writing. Thus, the evaluation method expresses the number of points that is receiving 300lux over the total
number of points as a ratio and expresses it as a percentage.
The last evaluation method is a simple cost calculation of the materials used for the façade. There are in total
four different materials used for the façade. The better performance material will cost more compared to the
lower performing material. A cost factor is assigned to each material (Table 2). The cost is the multiplication of
the cost factor by the area of the material used and eventually the sum of all the individual material cost.
Table 2 Material and cost factor
Material
U Value
Cost Factor
(3mm steel cladding/20mm expanded p
olystyrene/3mm steel cladding/20mm
wood chipboard)
1.145
1.5
(3mm steel cladding/20mm polyuretha
ne foam/3mm steel cladding/20mm wo
od chipboard)
0.881
2
(3mm steel cladding/10mm expanded
polystyrene/3mm steel cladding/10mm
wood chipboard)
1.9
1
(3mm steel cladding/10mm
polyurethane foam/3mm steel
cladding/10mm wood chipboard)
1.54
1.3
3.2 Evolutionary algorithm (EA)
The optimsation algorithm used is the EA. EA is an optimisation algorithm inspired by biological evolution, in
which mechanism such as crossover, mutation and selection are used to generate fitter individuals. A fitness
function is used to determine whether an individual is performing well. In the context of an architecture design,
an individual will be a design variant generated from a design schema and the fitness functions would be the
evaluation methods. At each cycle of the EA:
1. A population of 100 design variants are randomly generated by assigning parameter values to the
design schema
2. Each design variant is evaluated and assigned scores for the evaluation methods. Each evaluation
method is to be either minimise or maximise. The energy consumption and cost factor are to be
minimise, while the energy production from BIPV and daylighting is to be maximized.
3. A sub-population of 50 design variants are randomly selected from the main population and pareto
ranked according to their scores.
4. 25 design variants at the bottom of the ranking will be “killed” and 25 new design variants will be
“reproduced” from the better performing design variants. The reproduction process is done through
crossover techniques and the mutation rate is 0.01
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5. The cycle is repeated from step 2 with the newly produced design variants. As a result better
performing design variants are generated with each generation.
6. The EA cycle stops as specified by the users.
Lastly, a scientific workflow system is used to link the environmental simulation, CAD and optimisation
algorithm programs together. It is a design environment which enables the architect to manipulate and manage
the design process (Chen, Janssen et al. 2012).
5. PILOT STUDY
4.1 Design schema 1
Figure 2 Design schema 1
Design schema 1 (Figure 2) is described as follows:
a) A façade is divided into two panels, they can be divided either horizontally or vertically.
b) Each panel is assigned one of the four materials, each colour represent a different material.
c) One or both of the panel can be chosen to be the window. The material of the glass is the M-glass which
is given to the BubbleZERO project.
d) Each window can have a shade of maximum 1 meter or without any shade.
e) This façade will be applied to one of the four façade of the bubbleZERO. This is repeated 4 times to
generate façades for the four sides. The facade with the door is an exception, where the placement of the
door needs to be considered. The schema has 18 parameters in total.
Figure 3 Means of the four evaluations throughout the optimisiation of schema 1
As one can see the optimisation got stagnant after the 20th generation. This is mainly due to the limitation
of the parametric model. The parameters are too constraint resulting in a quick convergence of the result. A
filtering process was done to look at the better performing design variants. A quick look at the design
variants produced showed designs of low variability. However, the designs did perform well in terms of
daylighting, energy consumption and cost. Thus, these results would serve as a benchmark for the later
schemas for comparison.
Figure 4 Schema 1 design variants facades
4.2 Design schema 2
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Figure 5 Design schema 2
Design schema 2 (Figure 5) is described as follows:
a) A façade is divided into two panels, they can be divided either horizontally or vertically.
b) The 2 panels are divided into 2 smaller panels, resulting in 4 panels in total. The division lines are
allowed to move along the panels and outwards and inwards.
c) The m-glass window can be on either side of the panels, on both side, or on neither of the panels.
d) Each panel will be assigned a material and it is represented by a colour. Panels that are not windows are
potential solar panels.
e) This façade will be applied to one of the four façade of the bubbleZERO. This is repeated four times to
generate façade for the four sides. The facade with the door is an exception, where the placement of the
door needs to be considered. The schema has 47 parameters in total.
Figure 6 Means of the four evaluations throughout the optimisiation of schema 2
Design schema 2 is an attempt to integrate the shading in design schema 1 by tilting the façade to shade itself
from the sun. Design schema 2 tries to achieve a similar performance with design schema 1 by having a
combination of different tilting angle, materials and the low exergy systems. The design variants produced are of
higher variability compared to design schema 1. However, it does not perform as well as schema 1. Despite,
more appealing architecturally the tilting of the façade decreases the performance of the daylighting and the lack
of shading has significant effect on the energy consumption. This also affects the costing evaluation where better
insulation is required in order to use low exergy systems.
Figure 7 Schema 2 design variants
4.3 Design schema 3
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Figure 8 Design schema 3
Design schema 3 (Figure 8) is described as follows:
The design schema 3 is an improvement of design schema 2. The tilting of the façade was not sufficient in solely
providing shades from the sun. A new parameter of shades for the windows was added to the schema. (a) (c)
are the same as design schema 2.
d) Each panel will be assigned a material and it is represented by a colour. Panels that are not windows are
potential solar panels. Windows can have shading devices with a horizontal extension between 0 m and
0.4m. At the same time the shading devices also provide the area for potential solar energy generations.
e) This façade will be applied to one of the four façade of the bubbleZERO. This is repeated four times to
generate façade for the four sides. The facade with the door is an exception, where the placement of the
door needs to be considered. The schema has 60 parameters in total.
Design schema 3 attempts to combine the benefit of the previous two schemas by introducing a form of shading
element to complement design schema 2. It is assumed that both shading and tilting decrease the energy
consumption. The extra shading surfaces will provide more surfaces for potential installation of solar panels.
Figure 9 describes the optimisation process through the means of each evaluation method. The introduction of
the shades manage to improve the generation of energy as there are more horizontal surfaces for receiving solar
irradiation. The performance of the daylighting is better as there is more space for negotiation with the extra
mechanism of the shading. Lastly, the cost factor also performs better as shading is a cheap solution compared to
using better insulation. However, the energy consumption is of similar performance to schema 2.
Figure 9 Means of the four evaluations throughout the optimisiation of schema 3
Figure 10 shows a series of the parallel plots that gives a more detailed description of the EA process. Each plot
shows the design variants generated in 20 generations. One can see as the EA proceeds the design variants
perform better, it is interesting to note within around 20 generations all design variants that was not able to
employ low exergy systems were eliminated. One can observe from generation 121 to 180, there is a split at the
energy generation axis. The split is due to the use of shade or just having well insulated materials, as these two
mechanisms produces similar results for the rest of the three evaluation methods. However, from generations
161-180 the EA is slowly moving towards well-balanced solutions of shades and appropriately insulated
materials.
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Figure 10 Parallel plot of the evolution process
Figure 11 Design variants of design schema 3
A simple filtering process was used to choose among the 4000 design variants. The designer wants to get
the best performing solution of the evaluation methods. A filter was carried out with the following ranges.
Energy consumption between 538W and 500W, energy produced between 2500kwh/a and 2000kwh/a,
daylighting between 100% to 80% and cost factor between 11 and 8. The filter eliminated most of the
design variants and 15 design variants were left. The architect can further examine the 15 design variants
and continue to develop a more detailed design scheme for later stage of design.
5. CONCLUSION
The integrated design process shown is capable to aid the architect in his explorations of possible design options.
It is possible to satisfy the performance criteria by maintaining design quality and architectural intention. By
incorporating both active and passive systems, it is possible to generate designs of certain variability but at the
same time of similar performances. This will expose the architect to more design possibilities instead of the
usual more restrictive perspective of just manipulating the passive systems.
The optimisation technique EA requires the generation of thousands of design variants. This is suitable for big
scale design projects with more parameters where there is a significant variability between the design variants
generated. However, for a small scale design project the thousands of design variants generated have little
variability. Thus the research will look at other possible optimisation techniques; one example is Micro Genetic
Algorithm. It generates five to ten design variants in a generation for optimisation, the number of design variants
is more manageable for design project of a smaller scale.
The low exergy approach provides a more holistic perspective to achieve sustainable buildings while the
parametric modeling, evaluation method and optimisation technique is actively engaged in an integrated design
process. It provides feedback for the architect on the chosen design schema, by examining and analysing the
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results the architect can extrapolate the potential of a design concept and improve it in the next design schema.
Further investigations include looking at different low exergy strategies applicable in the tropics and extracting
its architectural implications. These will be formalised to refine the design process to facilitate the design of low
exergy architecture in the tropics. The pilot study shows the feasibility of the design method. The research will
look at case studies of bigger scale and flexibility to test out the design method.
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[4] Janssen, P. H. T. (2004). A design method and a computational architecture for generating and evolving
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SIGGRAPH.
... However, there are limitations and constraints for implementing this strategy; the sensible heat load needs to be within the cooling capacity of the high temperature cooling systems used and systems like radiant panels will require sufficient surface area for the cooling down the space. (Chen et al, 2012b). ...
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Chapter 1 describes the characteristics of a thermodynamic concept, exergy, in association with building heating and cooling systems. Exergy is the concept that explicitly indicates 'what is consumed'. All systems, not only engineering systems but also biological systems including the human body, work feeding on exergy, consuming its portion and thereby generating the corresponding entropy and disposing of the generated entropy into their environment. The whole process is called 'exergy-entropy process'. The features of 'warm' exergy and 'cool' exergy and also radiant exergy are outlined. General characteristics of exergy-entropy process of passive systems, which would be a prerequisite to realize low exergy systems, are discussed together with the exergy-entropy process of the global environmental system. Chapter 2 introduces the various forms of exergy and the mathematical formulations used to evaluate them. The exergy balance on an open steady state system, which is much more relevant to thermodynamic analysis of energy systems, is also described, as well as the different exergetic efficiency factors introduced in the thermodynamic analysis of energy systems. Next, an exergy analysis example is outlined through an air-conditioning application. Air-conditioning applications are widely used in heating and cooling of buildings. Chapter 3 introduces an example of exergy calculation for space heating systems. The issues to have a better understanding of low-exergy systems for heating and cooling are raised. It is suggested that a prerequisite for low exergy systems would be rational passive design of building envelope systems.
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Low exergy (LowEx) building systems create more flexibility and generate new possibilities for the design of high performance buildings. Instead of maximizing the barrier between buildings and the environment using thick insulation, low exergy systems maximize the connection to the freely available dispersed energy in the environment. We present implementations of LowEx technologies in prototypes, pilots and simulations, including experimental evaluation of our new hybrid PV-thermal (PV/T) panel, operation of integrated systems in an ongoing pilot building project, and cost and performance models along with dynamic simulation of our systems based on our current office renovation project. The exploitation of what we call ”anergy sources” reduces exergy use, and thus primary energy demand. LowEx systems provide many heating and cooling methods for buildings using moderate supply temperatures and heat pumps that exploit more valuable anergy sources. Our implementation of integrated LowEx systems maintains low temperature-lifts, which can drastically increase heat pump performance from the typical COP range of 3–6 to values ranging from 6 to 13.
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This paper aims to study the various parameters that affect the energy performance of commercial buildings in Singapore. The parameters are diverse, ranging from characteristics of construction of the walls and windows, to the various system settings and types within the building. Building energy performance is measured via two key indexes, namely, the Envelope Thermal Transfer Value (ETTV) and the annual cooling energy requirement (Ec). Parameters related to these two indexes are identified. An additional parameter, the solar absorptance of the wall, is further incorporated to calibrate the ETTV equation. A relative ranking on the functional parameters of ETTV has been performed to evaluate their effectiveness in lowering the ETTV of buildings. In addition, the impact of using cladding on ETTV is also studied. A correlation for Ec, expressed in the form of a simple linear equation, has been developed. This correlation accounts for the internal building loads, envelope loads, operating schedules and efficiency of the cooling equipment. Finally, ETTV and Ec have been employed to study the effects of chiller over-sizing and ventilation rates on building cooling energy. In the pursuit for better energy-efficient buildings, the approach presented in this paper contributes to the construct of sustainable energy-efficient built-environment.
Conference Paper
This paper describes a physically-based rendering system tailored to the demands of lighting design and architecture. The simulation uses a light-backwards ray-tracing method with extensions to efficiently solve the rendering equation under most conditions. This includes specular, diffuse and directional-diffuse reflection and transmission in any combination to any level in any environment, including complicated, curved geometries. The simulation blends deterministic and stochastic ray-tracing techniques to achieve the best balance between speed and accuracy in its local and global illumination methods. Some of the more interesting techniques are outlined, with references to more detailed descriptions elsewhere. Finally, examples are given of successful applications of this free software by others.