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Research on Architectural Form Optimization
Method Based on Environmental
Performance-Driven Design
Jinghua Song(B)and Sirui Sun
School of Urban Design, Wuhan University, Wuhan 430072, China
113318088@qq.com, three.530@qq.com
Abstract. In the context of contemporary environment and society, the architec-
tural form optimization based on Environmental performance-driven design is a
method by using environmental performance data to optimize the architectural
form. Its value lies in dealing with the interaction between architecture and envi-
ronment, and developing architecture with environmental sustainability. This the-
sis summarizes the similarities and differences between performance-driven form
design and traditional bionic form design. The traditional bionic design separates
the bionic object from its complex living environment, and its simple imitation
tends to fall into the local rather than the global optimum. However, performance-
driven design is different from bionic design. It advocates environmental factors as
a driving factor rather than a confrontational factor. It is a systematic global optimal
method for studying architectural form. This paper puts forward the specific archi-
tectural form optimization simulation process based on the performance-driven
thought. Taking the multilayer parking building design of the riparian zone on the
south bank of Chongqing as an example, the parametric design method is used to
obtain architectural optimization form adapted to the environment.
Keywords: Performance-driven design ·Form optimization ·Environmental
adaptability
1 Introduction
With the continuous development of environment, society, economy and technology, the
relationship between architecture and environment has been increasingly discussed. The
study of the relationship between architecture and environment will inevitably involve
environmental adaptability, which comes from the theory of environmental adaptability.
This theory was originally derived from the field of biological research at the end of the
19th century, marked by Darwin’s theory of natural selection, and was applied to the field
of architecture and urban research by the 1850s [1]. The theory is the ideological and
theoretical basis of the research in this paper. Buildings should have relative adjustment
ability in a specific environment to adapt to the complex changes of the environment.
Buildings can be used as a medium to respond to the environment, and it can be presented
as a dynamic intelligent collection through interaction with the environment.
© The Author(s) 2021
P. F. Yuan et al. (Eds.): CDRF 2020, Proceedings of the 2020 DigitalFUTURES, pp. 217–228, 2021.
https://doi.org/10.1007/978-981-33-4400-6_21
218 J. Song and S. Sun
The external environmental data of buildings generally have the characteristics of
complexity, periodicity, immediacy and combination [2]. Through the design, the envi-
ronment interacts with the building, combining the environmental performance data with
the building. A new mode of thinking is integrated into the Multivariate complex system
of architecture, environment and people, making to interact and respond from among
the architecture, environment and people (Fig. 1).
2 Performance-Driven Design and Its Advantages
2.1 Performance-Driven Design Theory
Along with the construction, engineering and other industries into the sustainable low-
carbon era, the building performance has attracted more and more attention. Simulation
technology has quantified the building performance, so architects can incorporate perfor-
mance analysis into the design workflow. Performance-driven design involves computer-
aided optimization techniques that make performance the standard for driving design
[3]. Performance simulation technology has been widely used in architectural design for
a long time, but in the early stage, it is only used as a design evaluation condition rather
than a driving factor of form generation and optimization. In the field of aviation, perfor-
mance simulation data is used as the design driving force to improve the aerodynamic
performance of aircraft, so the performance-driven design method is derived.
Under the action of driving factors and in the process of architectural form shaping,
performance-driven design can stimulate the new possibility of building in organiza-
tion, space, form and performance. Make full use of the natural environment energy to
drive architectural form generation and optimization, which can not only respond to the
changes of wind environment, light environment, thermal environment, water environ-
ment and so on, but also intelligently respond to the external climate conditions of the
building based on the energy flow and transfer [4]. The original intention of this study is
to start with rational analysis and capture of environmental parameters, and to optimize
the overall form of the building under the influence of environmental parameters such
as water flow, wind, light and landscape [5].
2.2 Performance-Driven Design Advantages Compared with Bionic Form Design
It is generally believed that the bionic architecture is obtained by using the bionic form
design method. Bionic architecture is a kind of architecture which imitates the effective
system specialty of some organisms in the aspects of architectural environment, function,
form and organizational structure, and it is more in line with the laws of nature and
requirements of human nature [6]. In the category of bionic concept, the bionic form
design thought such as life-form characteristic bionic, bionic configuration and bionic
structure is close to the performance-driven design thought, which have both certain
similarities and differences.
From the perspective of similarity, the goals of performance-driven design and bionic
form design are to adapt to the laws of nature. Architecture must adapt to the environment
to achieve the symbiotic relationship between human and nature. The buildings are
Research on Architectural Form Optimization Method 219
integrated into the circulation system connected with the environment, so as to make
more rational use of resources, maximize the use efficiency of energy and materials,
reduce the energy consumption of the buildings, make the buildings become a part
of the local ecosystem, and make the nature become part of the buildings [6]. Both
performance-driven design and bionic form design are architectural form design theory
based on the development of environmental adaptability theory.
From the perspective of difference, in the first place, performance-driven design
takes performance goals as the driving force, and with the help of computer analysis
ability, it can create more diverse form and function solutions under the premise of
meeting the comprehensive performance requirements. Select the best scheme through
simulation optimization and achieve the optimal solution of multi-objective problem [7].
In the second place, performance-driven design process maximizes the driving effect of
performance indicators on the design scheme, it avoids the rework of the design scheme
due to the non-compliance of performance indicators and improves the design efficiency.
These two advantages promote the application of performance-driven design theory in
architectural creation. The bionic form design is more to pursue the goal of the harmony
between the architecture and the image of biology. It regards the unity of functional
image as the objective basis of harmony and lacks the essential connection [8]. However,
performance-driven form design breaks through a single perspective, and it is mainly
based on the performance of the system rather than the expression of the function or
form, which focuses on performance, that is, function and efficiency [9]. Therefore,
the performance-driven form design is a more in-depth development of the bionic form
design in dealing with the relationship between architecture and environment.
3 Performance-Driven Architectural Form Optimization Method
3.1 Combined with Parametric Design
The performance-driven parametric design is a design method that combines
performance-driven design with the design of “parametric model”. Parametric model
is a computer design model, which is based on the geometry. This geometry, itself, con-
tains two fixed features, known as constrained and variable attributes. Parametric design
is the form of development based on a set of relations and variables (parameters) [10].
In the parametric model, when a new alternative solution is sought, the parameters will
change accordingly. Therefore, it is necessary to adjust the new values of the parameters
to respond to such changes, and to define different architectural forms [11].
Under the environment relation, the performance-driven parametric design method
combines the parameters of the environmental performance data with the architectural
form. This method enables the computer to generate architectural forms based on the
building space, structure, materials, and physical environmental parameters such as
wind, light, heat and sound, so as to make architectural forms respond to environmental
performance [4].
220 J. Song and S. Sun
4 Form Optimization Simulation Process Establishment
There is certain discreteness in architectural design so that the design process itself
can be simulated by computer. To explore the generation and optimization of archi-
tectural form, we need to use performance-driven design thought to find an effective
simulation method based on complex models to help complete the design process. The
steps of simulation optimization design combined with performance-driven thought are
as follows: firstly, traditional design method is adopted for conceptual design; secondly,
model is established; thirdly, simulation program is used to analyse one or more related
performances; and fourthly, simulation results are analysed and evaluated. On this basis,
the design and model are modified repeatedly to find certain rules and the optimal form
interval, so as to further drive the detailed design and obtain the target (Fig. 2).
Fig. 1. Diagram of interaction response among
architecture, environment and people
Fig. 2. The thought process diagram for
performance-driven simulation
optimization
Figure 3shows a block diagram of the performance-driven form optimization simu-
lation process. This paper will only discuss the use of water flow factor as a driving factor
in relation to case studies. According to the overall analysis, the preliminary architec-
tural form is designed, and then the parameters of form optimization and the reasonable
numerical constraint range are determined. Architects use rhino and grasshopper to build
the model, and require that the relevant data of the model must be in the range of parame-
ter numerical constraints, so as to reduce the differences of the optimization results. The
simulation process is optimized by the performance simulation platform of Phoenics
or RhinoCFD, and the results of stage optimization are obtained. Analyse the data of
the results of each stage, and summarize the numerical range of the optimal form that
meets the requirements. Combined with other constraints, the optimal form is selected
for detailed design, and the final architectural form is obtained.
5 Design Practice
5.1 Project Background
The project is located in the riparian zone of “Egongyan Bridge-Shijiayan” on the south
bank of Chongqing (Fig. 4). According to the overall goal of comprehensive control
planning of the riparian zone and the natural topographic conditions of the riparian
zone, the urban multilayer parking building is designed within the project area of Height
Research on Architectural Form Optimization Method 221
Fig. 3. The performance-driven design generates optimized simulation block diagram
range 186–199 m (Fig. 5). The building site is located in the height range of 180–193 m,
which is the urban construction control area of the water level against 5–50-year recurrent
floods. The purpose of this study is to demonstrate that the overall form of the design
scheme adapts to the site environment. The architectural form should have the flood
protection ability in special period. In addition, the building can provide a leisure places
for citizens and make it a vibrant riverside area in the city.
5.2 Design Parameters Selection and Numerical Constraint
According to the general design requirements of the project, the architect first needs to
do a lot of analysis on the site conditions and functionality. Next, the architect needs to
define the basic spatial form of the building, select the corresponding parameters and
numerical constraints, so as to ensure that the optimization goal of architectural form
meets the design requirements and the rationality of space use.
Considering the influence of boundary line of building and the overall terrain environ-
ment on the architectural form, we have chosen the building length-width ratio, building
orientation (Fig. 6), building height and number of floors as design parameters. Accord-
ing to the analysis, the numerical constraint of the building length-width ratio is limited
to 1.6–3.3, and the architectural forms lower or higher than this range all show certain
irrationality. For example, the building space is not suitable for the function or the poor
fit with the terrain. The building orientation is limited to 25–30° north-northwest, so as
to adapt to the terrain conditions and get a good riverside viewing effect. At the same
222 J. Song and S. Sun
Fig. 4. The land area of the riparian zone Fig. 5. The Scope of project site
time, the building can follow the water flow direction of the Yangtze River, reducing
the problems caused by special circumstances. In addition, in order to avoid breaking
through the requirements of the optimal design scheme, we also limit the total building
area and the building footprint as parameters. The specific parameter numerical range
are shown in Table 1.
Table 1. The constraint conditions on parameter range of architectural form optimization design
Parameter name Numerical constraints Unit
1 Building length-width
ratio
1.6–3.3 –
2 Building orientation North-northwest 25–30 °
3 Building height 13.5–16.5 m
4Number of floors 3 –
5Total building area 13500–16500 m2
6 Building footprint 4500–6000 m2
5.3 Setting Simulation Parameters
5.3.1 Water Velocity
The engineering reach is located in the upper reaches of the confluence area of the Yangtze
River and Jialing River, and is called the Dumb Cave reach. The flood fluctuation of the
two rivers will affect the water level in this reach. By analysing the historical data of
Zhutuo hydrological station, Cuntan hydrograph station, Beibei hydrograph station and
Egongyan stage gauging station, the water velocity of simulation is 2.37 m/s.
Research on Architectural Form Optimization Method 223
5.3.2 Water Flow Direction
According to the water flow direction of the whole Yangtze River, in the engineering reach
and from the upstream to the downstream, the water flow direction of simulation is north-
northwest direction (considering a single direction temporarily to facilitate calculation
and simulation).
5.3.3 Water Level Height
The numerical values of water level height related to the building are shown in Table 2.
The water level height of simulation is the water level against 5-year recurrent floods—
185.6 m.
Table 2. The characteristic water level height value associated with the building
Water level name Water level height/m Relative building height/m
1Water level against 50-year
recurrent floods
191.7 11.7
2Water level against 5-year
recurrent floods
185.6 5.6
3General highest water level 173.0 −7
4General lowest water level 164.5 −15.5
Note: Yellow Sea Elevation
5.4 Form Optimization Process Diagram
The whole simulation process of form optimization is adjusted in multiple stages. The
initial conceptual design was the traditional block shape. But through the Phoenics water
flow simulation analysis, the concave space of the building will be affected by the severe
impact of the water flow, which is not conducive to the overall structural performance.
Therefore, the architectural form is pushed outwards to gradually weaken the boundary
of the rectangular block, so as to adopt a soft curve form. Finally, we get the spindle
shape with better performance. And on this basis, we find the optimal performance range
by changing the building length-width ratio and shape for many times. Figure 7shows
the evolution process of architectural form in simulation and optimization. Figure 8and
Fig. 9respectively show the pressure value diagram and the velocity value diagram of
the water level against 5-year recurrent floods in 18 phases schemes.
5.5 Result Analysis
The shape coefficient of building (the ratio of the external surface area of the building
in contact with the outdoor atmosphere to its volume) is chosen to describe the architec-
tural form characteristics. According to research, the smaller the external surface area
224 J. Song and S. Sun
Fig. 6. Diagram for determination of building
aspect ratio and building orientation
Fig. 7. Optimization of architectural
form evolution
Fig. 8. The pressure value diagram of simulation process
allocated on the unit building volume, the smaller the impact of water flow on architec-
tural form in the special period, that is, the more conducive to the stability of the overall
structural performance of the building. We extract the corresponding maximum and
minimum pressure values (velocity values) from each stage of simulation and average
them. And then, combined with the shape coefficient of building, the average pressure
value and the average velocity value, we find out the relationship among them and get
the optimal form numerical range. Table 3shows the relevant data values of the above
18 simulation phases. The data values of every phase are within the effective range of
the design parameters.
Research on Architectural Form Optimization Method 225
Fig. 9. The velocity value diagram of simulation process
Figure 10 shows the line chart of the relationship among the average pressure value,
average velocity value and the shape coefficient of every simulation phase (the numerical
variation range of the shape coefficient is too small, so we expand the numerical value
by 10 times in order to clearly present the curve variation rule). In the simulation of the
architectural form No. 1 to No. 13, the average pressure value, average velocity value
and the shape coefficient have a general trend of gradually decreasing, which indicates
that the effect of water pressure on them decreases with the change of form; the shape
coefficient of the architectural form No. 14 to No. 18 tends to a relatively stable value,
but the corresponding average pressure value and velocity value show an upward trend.
To sum up, the architectural form No. 13 and No. 14 are relatively better. By designing
them in detail and again using Phoenics simulation, the building is least affected by
the water level against 5-year and 50-year recurrent floods, which is more stable, safe,
beautiful and sustainable than other design forms.
226 J. Song and S. Sun
Table 3. The relevant data values of every phase simulation
Total building
area
/m2
Building
footprint
/m2
Building
length
/m
Building
width
/m
Building
length-width
ratio
Building
height
/m
Maximum
pressure
/pa
Average
pressure
/pa
Maximum
velocity
m/s
Average
velocity
m/s
External
surface area
/m2
Volume
/m3
Shape
coefficient
115364.21 5121.41 138.48 55.29 2.50 13.50 2.80 5.76 3.86 1.94 16752.72 69138.96 0.2423
215638.91 5212.97 140.05 66.65 2.10 13.50 2.59 4.62 3.56 1.79 17066.57 70375.05 0.2425
314785.31 5026.07 140.05 62.04 2.26 15.80 3.00 3.65 3.44 1.72 14760.49 61889.81 0.2385
414584.16 5614.31 145.11 58.95 2.46 16.50 2.81 3.35 3.38 1.69 15286.39 60671.71 0.2519
516146.12 5939.09 150.31 65.85 2.28 15.20 2.53 4.49 3.82 1.92 16350.24 68579.62 0.2384
616010.76 5003.09 144.73 67.21 2.15 15.20 2.79 3.85 3.39 1.71 15234.88 70464.66 0.2162
716253.28 5006.14 150.09 63.44 2.37 15.20 2.52 3.59 3.29 1.65 15403.99 73286.18 0.2102
815424.21 4784.01 149.24 60.54 2.47 15.20 2.63 3.33 3.09 1.55 15464.31 73301.31 0.2109
916336.52 5446.21 150.04 60.34 2.47 16.50 2.16 3.71 3.54 1.79 15452.59 71568.99 0.2087
10 15416.87 4632.56 150.21 53.13 2.83 15.20 2.02 2.85 3.09 1.59 15747.32 75449.96 0.2005
11 15270.15 4574.28 157.79 48.61 3.25 15.20 1.83 3.42 3.08 1.60 13930.61 68302.12 0.2039
12 15124.29 4528.12 154.69 48.37 3.19 15.20 2.43 3.00 3.15 1.59 13688.67 67853.43 0.2017
13 15675.26 4757.42 155.57 52.79 2.95 15.30 1.93 2.23 3.09 1.59 13973.08 69873.07 0.2001
14 15326.79 4643.76 164.39 52.77 3.12 15.30 1.82 2.50 3.11 1.64 13872.24 68051.48 0.2038
15 15348.49 4670.62 169.73 54.21 3.13 15.30 2.05 2.66 3.09 1.65 13997.35 67943.66 0.2060
16 15744.41 4665.43 142.27 67.46 2.11 15.30 2.10 2.69 3.15 1.64 13950.96 71148.68 0.1961
17 14954.44 4531.41 124.44 74.63 1.67 15.30 2.08 2.95 3.27 1.68 13050.84 66743.06 0.1955
18 15429.91 4515.17 128.60 69.83 1.84 15.30 2.27 3.02 3.23 1.62 13455.92 69264.66 0.1943
Research on Architectural Form Optimization Method 227
Fig. 10. The broken line diagram of
relationship among mean pressure value,
mean velocity value and shape coefficient
Fig. 11. A rendering of the final building
scheme
6 Conclusion
In the context of contemporary environment and society, to develop sustainable energy
and to protect environmental ecosystem urgently need to develop the new architectural
design strategy.
Only passively seeking design inspiration from nature, and the bionic design of
existing mode can no longer meet the demand of sustainable building development.
Under the influence of various complex environmental factors, it is necessary to apply
the performance-driven design thought to find the optimal value of the architectural form
optimization design that responds to the environment. Performance-driven design gives
full play to the advantages of digital technology, making the selection of its results more
proactive and avoiding being limited to the design of local optimization. In short, the
performance-driven design method can truly combine design with nature to drive the
development of energy-efficient buildings and sustainable buildings [12].
In addition, the architectural design of riverside area is a research subject to be
further developed and utilized. There are many uncontrollable environmental factors
in the riverside area, which will affect the architectural form, the construction process,
Use process and maintenance process of building. In the design process, it advocates
environmental factors as the driving factors rather than the confrontational factors, so
as to improve the energy efficiency of the building environment. The design practice
explores the optimization strategy of architectural form in riverside area influenced by the
performance-driven design thought. The results of simulation and optimization show that
the architectural form is not only satisfied with other design conditions, but also affected
least by the specific water flow factors of this area. The final optimized architectural
form combines the urban space, embankment features and surrounding landscape to
form a building of the modern design feature (Fig. 11). More importantly, this provides
strategic guidance for further development of programs, that can be modelled, simulated,
evaluated, optimized and generated simultaneously.
At present, we are gradually realizing the transformation from computer-aided design
to computer-decided design. The latter will focus more on the global optimal study of
architectural design problems at the level of the self-organization generation and adaptive
optimization. This will be a new exploration of architectural design thinking, methods
and technical tools in the context of artificial intelligence technology. It is bound to
228 J. Song and S. Sun
integrate more vigorous vitality into the sustainable design concept of environmental
performance.
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