Skip to main content

Performative driven form finding in the early design stage


One of the most crucial factors architects should consider in building energy performance design is the energy consumption of residential buildings, particularly in megacities such as Cairo. Oxman classifies that a five-paradigmatic design model can help architects generate building forms. In this study, the authors aimed to develop a form-driven design framework based on a generative design model based on shape grammar that allows architects to generate building forms based on rules, which generate the building through variables that act as genes in the fitness function. The results indicate a significant framework that can help architects select the optimum building form that saves energy by enhancing daylight penetration and thermal and cooling loads on a building. Furthermore, after optimizing radiation and cooling load metrics, the form generated significant block and balcony arrangements, enhancing the shading in the eastern, western, and southern facades. In addition, the northern façade has been developed without block projections or balconies. Finally, the optimum window-to-wall ratio generated to balance spatial daylight autonomy (SDA) and annual sunlight exposure (ASE) lighting metrics for the north facade is 60% and for the southern, western, and eastern facades 10%.


Megacities all over the world consume resources and energy. Worldwide, building operations accounted for 27% of all energy sector emissions and 30% of the world’s energy consumption in 2021 [15]; Cairo has an estimated population of over ten million. Furthermore, its population continuously grows with the demand for energy and resources. In addition to climate change issues, these factors put much pressure on architects to design buildings with low-energy consumption [31]. In all parts of the world, the combined facilities and building construction sectors are responsible for 30% of total global energy consumption; moreover, they take the lead with approximately 25% of greenhouse emissions [32], according to the last report presented by the Egyptian Ministry of Electricity and Renewable Energy. Furthermore, the energy consumed by the residential sector was approximately 40% of the total energy consumption in 2019–2020 [7]. Therefore, energy-efficient residential buildings are highly recommended to meet this growing energy demand.

Adopting the design of building envelopes and generating their forms are two significant decisions that affect energy consumption [9]. Moreover, a well-designed building form provides an energy-saving and comfortable environment [32].

The design process for responsive building forms is frequently complicated due to their shape’s spatial and functional sensitivity [31]. However, a building’s design can allow or prevent the surrounding environment from affecting the energy balance of the building [8].

In addition, the rate of architectural change has been linked to rapid urbanization; however, additional achievements in energy savings remain to be achieved. Recently, most residents have been dissatisfied with their living environment because it lacks in natural aspects to meet human needs [33], especially in developed countries. However, the architectural design process has evolved because of the generation of new tools. The conventional design was based on users’ needs, preferences, and priorities; therefore, it was not necessarily adaptable to the surrounding environment. Generative design techniques and evolutionary methods enable architects to find more alternatives with different possible solutions by integrating many parameters and metrics, which may be environmental, social, or functional, to find the optimal solution [6].

During the first half of the twentieth century, a new generation of design tools was launched that helped architects simplify the complexity of architectural design, especially when combined with a performative design parameter among various variables. For example, shape grammar is a powerful tool for form generation, precisely the initial shapes provided by multiple previous researchers. For design development, findings are placed into a genetic algorithm allowing designers to optimize design alternatives through a list of environmental metrics achieving proper review [34].

Although establishing generative design through the use of shape grammar is a well-thought-out approach, it has been the subject of previous research to analyze and generate designs. Building forms that mimic environmental building performance are still difficult to create. Therefore, there is a gap in the generation of building structures that respond to the environment in the early design stages [45].

Therefore, this research aims to generate a methodology to develop performative residential building forms based on daylighting and thermal performance metrics. First, find the optimum solutions for these forms using shape grammar rules by addition and subtraction through an evolutionary genetic algorithm combined with computational tools to obtain multiple design explorations.

Literature review

Designing is complex and challenging, yet it is an ability that an architect must learn and develop. Meanwhile, the architecture form generation method has been modified to address this issue. The form has traditionally been regarded as a generation of trial-and-error geometrical transformation techniques based on the architect’s vision for meeting the requirements of users and contextual elements [22].

Engineers and architects have recently transformed the tools they use to develop buildings. Designers are now integrating the power of technology to explore the world beyond the limitations imposed by traditional design methodologies, influenced by advances in 3D modeling, material science, and automated production [2].

Oxman has divided digital design models into five paradigmatic classes, beginning with computer-aided design, the model element without generation memory, and then an approach that switches from form making to form finding called “formation design models.” The availability of computer mechanisms for structured generating processes distinguishes the third generative paradigm model of digital design. The fourth model is the performative design, which exists when a digital simulation of external forces drives a form based on environmental parameters. The last is the algorithmic form creation of an integrated compound model. Formation-based design can be considered performance based, incorporating performance simulation, generative, and formative methods [21]. Furthermore, this research will focus on the integrated model for the genetic generation of building forms with the integration of the design of environmental performance.

Computer-aided design

Computer-aided design programs are switched from form creation to form discovery, and architectural techniques are shifted from fixed design to process design. However, computer-aided design is considered the only graphical representation of a digital product, unlike the formation model that remembers the history of form creation, so this will move to the next design model that evolved from form making to form finding.

Formation model

In the architectural field, parametric design was first introduced in the early 1990s, parallel to the evolution of digital design software. Its ability to reconstruct and change models based on multiple factors distinguishes it. Compared to traditional design methods, parametric design uses mathematical variables to solve complicated geometrical problems and produce advanced design models in an automated process [22]. Additionally, changes to the architectural model based on user decisions and contextual design information are time- and effort-consuming in the traditional sense [31], as models frequently require a complete redesign or critical components are constantly edited. On the contrary, parametric design allows rapid iteration by changing parametric values related to aspects of the geometrical model built on mathematical sliders that automatically adjust model geometry properties such as height, width, and number of floors [16].

Generative design

In architecture, generative design is applied in various ways. According to Singh and Gu ([28]), five commonly used generative design techniques in architecture have been described: shape grammar (SG), L systems, cellular automata, genetic algorithms, and swarm intelligence. This research will focus on shape grammar and genetic algorithms as critical components of a new product analysis and design tool generation [26].

Shape grammar

Stiny and Gips invented the shape grammar design model in 1972, a powerful computational formalization for shape generation. They have been studied for more than 40 years in various areas of design generation, starting from product design, architecture, and engineering [14]. Recently, they have been used to generate forms based on computer design systems [25].

Shape grammar is used in many fields to generate or analyze forms. For example, in the early 1990s, it was used in architectural education to teach students how to apply grammar languages in form generation at MIT, Harvard, Lille, and UCLA universities. Moreover, during the 1980s and 1990s, shape grammar tools were supposed to analyze Wright’s work and the home design of Taiwanese and Japanese restaurants [13].

Multiple definitions are proposed for the shape grammar design model. For example, it was defined as a set of rules that transform the initial shape, generating new forms to help designers and decision-makers develop alternatives. A design generating or analysis tool for an existing design was also mentioned. Shape grammar has also been described as “a relation between elements,” since the proposed approach is based on addition, subtraction, or replacement via shape rules [28]. What distinguishes the shape grammar process is that it is based on algorithms that can be fitted to the engineering process to obtain the optimum form.

Analyses, explanations of design, and the creation of new thematically similar strategies have all been carried out with the help of shape grammar. This research focuses on applying shape grammar to the analysis of residential buildings and the production of forms. Therefore, all studies previously selected are residential and have been used to analyze or generate building forms (Fig. 1).

Fig. 1
figure 1

Shape grammar used in architecture

Many researchers have used shape grammar rules to analyze existing building designs. For example, Hasani has reread the form of courtyards in 100 houses in Kashan city, using shape grammar (SG) to develop a decision tree based on specific rules that guide the design process for building new homes. First, the study indicates the spatial relationships between the components of the residential houses, since the decision tree was started with a point at which it was converted to a court. Then, based on the number of rooms and the spatial relationships between them, many designs were generated using a specialized algorithm [13].

Additionally, applying shape grammar principles to 44 vernacular buildings in Mazandaran in northern Iran [42] invested in the characteristics of vernacular housing and devised an efficient procedure to generate vernacular houses at the exact location. The generation process began with placing the living room as the primary space in vernacular buildings. Then, it progressed to the additional rules of other rooms in the composition of the plan. Similarly, Wang, Zhao, Fan, Yang, and Zhao ([39]) provided a shape grammar-based method to analyze the design vocabularies of 56 villages in Shandong province, situated on the North China Plain, through a field survey and produce new solutions to a rural housing problem. They discovered that shape grammar could successfully address the issue of matching customized mass housing designs with various user demands, and AbdulRaheem and Abdul Wahab Rayis ([1]) used shape grammar. Furthermore, Tari and Abdolhoseini ([33]) designed a new model to develop the shape pattern of houses using shape grammar, which produced a decision tree based on the concept of existing houses of the Pahlavi era.

Additionally, Schnier and Gero ([26]) established an evolutionary approach with shape grammar rules after analyzing 11 prairie houses, so 34 rules were based on developing two-dimensional functional housing plan zones. Similarly Park and Economou ([23]) were used to investigate the shape grammar rules of the courthouse designed by Mies van der Rohe. The study indicates five types of functional spaces and generative shape rules to generate new shapes. Additionally, Toussi ([34]) used genetic algorithms and shape grammar to analyze the primary characteristics and spatial functional element relationships of 30 historical houses in Kashan, Iran, before beginning to generate new building forms based on shape grammar exploring rules and generative evolutionary design. This engagement provides an effective way to analyze and develop new techniques that respect the traditional method and evolve a new one.

Aydin and Lo ([5]) used this idea to apply a participatory approach through gamification techniques to generate new homes in Kashgar’s vernacular architecture. Gamification is a method of shaping grammar applications to create a master plan for single-family homes that meets the needs of the community and meets energy efficiency requirements. Form generation from scratch is another approach to applying shape grammar rules [18]. To do this, students can produce different alternatives utilizing the shape grammar design model model, which will then be assessed by rules viable with the requirements for tenability and energy efficiency. Furthermore, Upasani, Shekhawat, and Sachdeva [37] ideally suited an automated generation of rectangular dwelling floor plans based on dimensional constraints and room relationships in proportion, in which shape grammar rules occur.

Additionally, Shekhawat, Upasani, Bisht, and Jain ([27]) developed a new software called GPLAN to optimize the floor plan dimensions design based on shape grammar rules, which can generate alternatives for boundary floor plan rectangular layout adjacencies through platforms used by designers.

Shape grammar was also introduced in applying energy performance-generated design to optimize the building envelope in the early design stage. It presented a study integrating shape grammar with energy simulation to support decision-making in the early-stage design phase of the building envelope within the guidance of energy performance simulations to obtain multiple alternatives through energy simulation (cooling/heating) calculations. The new tools generated in the last decade are Rhinoceros and Grasshopper programs, which are considered algorithm-based tools that can produce forms according to geometric rules. Andino and Chien ([4]) presents the role of the Grasshopper program in the shape of grammar applications.

A design tool that combines shape grammar with a genetic algorithm to produce multiple design solutions to a given problem and find the best one is one of the most significant applications of shape grammar in the design process [6]). Additionally, this tool generates alternatives to meet specific energy metrics. Using specific guidelines and metrics, this tool has been tested on residential buildings that are thought to improve shapes.

Previous research has shown that shape grammar is valuable for analyzing and producing two- and three-dimensional forms. Moreover, multiple alternatives are generated, particularly when combined with the evolutionary genetic algorithm technique, which speeds up the design process, generates conditions based on specific metrics, speeds up the design process, and causes conditions based on specific metrics. The most critical metrics that can be adopted in designing housing units are daylighting accessibility and enhancing building thermal loads. Therefore, this project will focus on producing residential building forms using shape grammar and genetic algorithms through specified daylighting metrics and thermal energy performance to create optimal building forms that are more comfortable for users while consuming less energy.

Table 1 investigates and compares the previous research projects that used shape grammar rules to analyze or generate house designs. The researchers used shape parameters and rules to establish the relation between the spatial position of rooms, room proportions (width, length, and height), courtyard position, and floor plan shape. The most practiced rules were addition and subtraction, and after analyses and obtaining the form rules, the process will be changed to develop new forms based on the analyzed one to be capable of the same context, especially in the vernacular context. Therefore, each study will generate a framework for architects to make a simple design decision when designing a new house following the rules of the existing one. The tools used ranged from mathematical calculations and computer support; researchers used programming languages such as MATLAB and Python to code the shape grammar rules to generate building forms with specific proportions of a room.

Table 1 Shape grammar investigation of previous studies
Performative design

One of the most critical roles in the performance design model is to generate the form of the building based on its energy performance in the early design stage [46]. Zhang’s works used a parametric performative approach to develop a Chinese residential building based on three primary components: the spatial relationship between residential building components, the energy simulation of the schematic design, and the generation and evaluation of new design ideas. The methods used in this work were to generate multiple alternatives for Chinese residents. Users first started to select the building orientation, room area, functions, etc. The second step was to determine the optimal building design using the simulation of energy consumption. Finally, the final building form and the schematic floor plan were automatically generated.

Furthermore, to minimize energy consumption, Feng, Luo, Gao, Abbas, Xu, and Pouramini ([11]) used different tools to optimize the form of residential buildings. The manta ray algorithm optimizer and energy simulator RIUSKA have been used to find the optimal building form through specific parameters such as floor area, window type, orientation, and building shape. The benchmark is the cost of the life cycle and the electrical energy used, and it was found that rectangular- and trapezoid-shaped buildings have the lowest life cycle costs.

Xia and Li ([40]) designed and evaluated the optimum residential urban morphology to improve access to sunlight and energy consumption. The main parameters used were the plot area ratio, building density, type, and height. Ladybug and honeybee simulated each iteration to optimize these variables to calculate solar radiation access and energy consumption. Similarly, Yi and Kim ([41]) introduced an agent-based geometric control system that helps designers find the optimal shape and position of the building to enhance the hours of solar access.

In addition, Amr and Youssef ([43]) applied the performative optimization process to increase the surfaces exposed to solar radiation to enhance the use of photovoltaic cells for energy generation. In this case, the shape grammar rules have been integrated to change the building form based on the addition and subtraction of the shapes. Each generation has been examined by the DOE-2 engine and compared with the base case to obtain better solar exposure for building integrated photovoltaic cells. In addition, some research is based on the performative optimization of the components of the building form to improve energy consumption and is supposed to find the optimum sustainable residential building design that balances energy consumption and daylight penetration. In this study, the parameters used were to change the construction materials of the building wall, the window material, and the depth and count. The Octopus plug-in engine chose the optimum spatial daylighting autonomy (SDA) and energy use intensity (EUI) metrics design.

Furthermore, Vukadinović, Radosavljević, Đorđević, Protić, and Petrović ([38]) tried to find the most passive solar component that affects heating, cooling, and energy consumption through the parameters of the WWR architecture, window material, wall construction, and shading. Moreover, NSGA-II examined this idea, a nondominant genetic algorithm tool. The results indicate that the WWR has the most significant influence on energy consumption among all parameters of the building elements.

Table 2 demonstrates the popularity of the genetic algorithm optimization method, as it generates genes to find the best solution to fit the objective function, which was based on building performance metrics such as energy consumption, energy use intensity (EUI), daylighting, and spatial daylighting autonomy (SDA), which parametric programs can provide in the simulation process.

Table 2 Investigate the performance design of previous studies

The research projects presented merged parameters such as shape length, width, and height and add parameters that affect energy consumption, such as building orientation, location, azimuth, degree, and construction materials (U-value & window types).

Most of the programs used in the previous studies are Rhinoceros and Grasshoppers, which can integrate plugins in different areas. Moreover, most of these software programs are open sources of energy, ladybug, and honeybee programs. They are based on verified engine OpenStudio, which is based on EnergyPlus for energy simulation and radiance for lighting simulation. Therefore, these programs can merge the parameters for geometrical building form generation, and the objective metrics and the optimal solution can be found through optimization.


In various Egyptian cities, the government promotes Sakan Masr middle-class prototypes with the same shape. Therefore, the researchers were interested in creating these buildings in various regions with less energy consumption. This method can offer a flexible housing unit in shape for mass production housing, which can be used with government programs to produce homes for the middle class and save energy. The case study will focus on the prototype housing project Sakan Masr in Cairo, as shown in Figs. 2, 3, and 4, which illustrate the typical form of the building, the spatial relation between rooms, and a geographical map of the site.

Fig. 2
figure 2

Sakan Masr architecture plan

Fig. 3
figure 3

Sakan Masr’s perspective

Fig. 4
figure 4

Sakan Masr layout (Google Earth)

The average area is 115 m2 per unit. Either single-family or multifamily housing unit design is a highly restricted process. The nature of such limitations varies, from concerns such as the area of each space to adjacency relations [25]. Although the architectural design is a challenging process that progresses from purely conceptual ideas to practical methods, spatial space arrangements, organization, and expected human implications are solved through problem-solving [20]. Based on the configurational theory of space, invisible features of space are deciphered using space syntax to find the accessibility between different house activities, such as living areas, bedrooms, kitchens, and spacious gardens [29]. This theory provides a methodology that investigates a framework for spatial relations [20].

The house design has been generated by adding specific parameters based on the Egyptian housing code, as shown in Table 3, which represents the minimum requirements for the spatial relation and the range of the used parameters that act as genes for the optimization process.

Table 3 Representing the minimum requirements for the proportional room ratio of the Egyptian housing code

The design starts with the idea generation process. Then, it transforms these concepts into actual spatial structures, illustrating a link between each space activity and indicating the required space adjacencies between functional house spaces [19]; then, performance metrics will be added to set the fitness function for the simulation.

Building performance metrics

According to the literature review, this study adopts the most reliable and accurate energy, daylighting, and thermal metrics to determine the optimal form of the building based on the benchmarks of these metrics. Energy use intensity, or EUI, is one of the primary metrics used as a benchmark for calculating energy usage. EUI is expressed as energy per square foot per year. The total energy consumed by the building in 1 year (measured in kWh) is divided by the total gross floor area. According to standards [10] for multifamily housing, the required EUI is 118.1 kBtu/ft2.

Daylighting design is critical to building rating systems, such as leadership in energy and environmental design, BREEAM, and certification. For assessment, BREEAM uses daylighting metrics such as spatial daylight autonomy (SDA 300 lx/50% of the annual occupied hours) for at least 55% of the floor area and annual sun exposure (ASE), which measures the percentage of floor area that receives at least 1000 lx for at least 250 occupied hours per year [8]. However, metrics such as ASE and SDA, which do not have an upper illuminance threshold, may be better suited to determine whether a place is well lit for a particular activity.

Then, to examine the generative component of evolutionary algorithms, evolutionary approaches were adopted to acquire the ideal building form through fitness objectives. Individuals’ ability to explain sample designs is measured via genetic optimization, as gene inputs and actuators (building form variables) are operated, and a physics engine simulates them based on predefined evaluations [34] as shown in Table 4.

Table 4 Selected metrics with their benchmarks


The modeling program “Rhinoceros” and its associated parametric scripting tool “Grasshopper,” which has many free, open-source plugins and the use of floating sliders and functioning controls for the geometrical shape form and proportional rules, can generate shape grammar geometry. Therefore, it may produce forms based on shape grammar principles, which this work aims to do.

For building performance simulation, lighting performance can be simulated by applying the ladybug-Grasshopper plug-in based on Python scripting and verified by the most well-known radiance lighting engine. In addition, the incident solar facade can determine solar radiation calculations. Moreover, the honeybee plug-in simulates energy based on EnergyPlus by installing an open studio program.

After adding the building parameters as a floating slider, a fitness function is added to generate the performative-driven optimization that maximizes the SDA metric and minimizes the metrics of total radiation, ASE, and EUI.

Shape formation

The initial unit dimension was defined as 4 × 4 × 3 m, which fit with the minimum requirements for the Egyptian housing design code. The case study is a five-story building divided mainly into four apartments per floor. Therefore, the form will be divided into four main parts. Each part consists of a 9-module 4 × 4 grid for each story, and the following rule is to subtract two modules to ensure that each unit has access to sunlight through the addition and subtraction of the other blocks when the form has been generated. See Figs. 5 and 6, which illustrates the form generation rules and script.

Fig. 5
figure 5

Rules for form development and shape language

Fig. 6
figure 6

Introduced Grasshopper script for the shape rules

The shape grammar rules used can be determined as follows:

  • • Rule 1: A rectangle with dimensions 12 × 12 generates the building boundary that was divided into nine rectangles, each 4 × 4.

  • • Rule 2: The rectangles have been moved to generate four floors.

  • • Rule 3: Rectangular boxes have been extruded so block 1 contains five floors with nine blocks and to ensure daylight penetration and to achieve the area of Sakan Masr units.

  • • Rule 4: Subtract two blocks from each floor to let the apartment size = 112 m2 (7 boxes with area 4 × 4 each).

  • • Rule 5: Add the staircase between the four apartments.

  • • Rule 6: Add a point in the connection between every two apartments, as the attachment generates blocks without sunlight access. These points develop a void to allow sunlight to enter these parts.

  • • Rule 7: The blocks have been duplicated to form the whole building.

  • • Rule 8: The blocks of the fifth floor have been generated with the twisted box to let the roof inclination flexible to add photovoltaic cells.

  • • Rules 9, 10, and 11 are used to solve the adjacencies between blocks and construct windows in the exposed faces.

Simulation methodology

The first iteration is a random simulation for the base case, the applied weather file of Cairo International Airport (EGY_QH_Cairo.Intl.AP.623660_TMYx.2004-2018.epw).

As examined first, the goal of the optimization is to set a fitness function that merges the optimization of the objective metrics decided to maximize SDA, minimize ASE for daylighting, and minimize the cooling load and total incident radiation.

A powerful PC unit is recommended, as the current hardware did not comply with the standard processing time, which delayed the required results and could delay the entire project. Additionally, each simulation took approximately 5 to 6 days to see the results of the optimization process, and the methodology was changed step by step, as shown in Fig. 7.

Fig. 7
figure 7

The simulation methodology

First, the base-case simulation has a random form but with the selected area for the mentioned metrics. Second, an optimization process was performed on the building unit’s arrangements and the balconies’ positions to minimize the total incident radiation.

Another simulation for the entire cooling load and daylighting metrics was generated to compare the base case with the first iteration.

Third, optimizing the window-to-wall ratio allows the fitness function to balance spatial daylighting autonomy and annual sunlight exposure. Then, the simulation for the cooling load and the energy intensity was used to compare the results.

Results and discussion

The results of this research suggest a framework for architects to generate forms through multiple simulations based on the previous one.

Due to too many different parameters and simulation metrics to balance daylighting and thermal performance, the simulation process took approximately 2 weeks, and there was no output. Therefore, at first, the research suggests optimizing the form through block arrangement and balcony location to reduce the thermal and cooling loads on the building; then, the second phase is optimizing the output form from phase 1 to obtain the best window-to-wall ratio for each orientation. After the optimization process, the results for the building block arrangements are sorted to reduce the total incident radiation upon the building, which has been noticed in the output design. For example, the northern direction has no recess or extrusion in its shape and no balconies, as it has no direct sunlight exposure according to the sun path of Cairo. Instead, the other facades, mainly their shape design for the building blocks, are arranged to increase the shadow on the building surfaces. For example, the western façade block arrangement appears to have more vertically staggered elements to act as vertical shading blocks, and for the southern façade, the balconies’ location, and the sorted block form as horizontal shading.

Furthermore, the terraces are rearranged in the eastern, western, and southern exposures to enhance shading on the building blocks, especially when the top block surface is exposed to sunlight, unlike Amr’s research project used to increase the surfaces that have high sunlight exposure to add solar panels to produce energy [43]. Therefore, the parameters and selected metrics will change as the target changes. However, this research suggests that shading is improved first, and then, the exposed face to sunlight can be optimized.

Although the arrangement of building blocks and balconies is essential in designing the form of the building to prevent fewer kWh incident radiation upon the building, the energy savings after optimization are approximately 6% in the whole building per year. However, the building form significantly changes, as shown in Table 5.

Table 5 Base case results

Vukadinović, Radosavljević, Đorđević, Protić, and Petrović [38] investigates that WWR has the most significant influence on energy consumption among all parameters of the building element. In this research, the authors added the optimum WWR for each side of the elevation, as in the north direction, the war was recommended to be 60%, and in the rest of the elevations, it was recommended to be 10% to achieve a balance between the SDA and ASE lighting metrics to save energy and penetrate the useful daylight.

Additionally, the results can introduce design guidelines for the design of residential buildings in hot arid climates such as Cairo.

  • ▪ There is no need to add balconies to the northern facade except for the aesthetics of the architect’s view or the user’s need.

  • ▪ The western façade design can be consistent with more vertical elements.

  • ▪ The southern façade needs the projection to be more horizontal.

  • ▪ Block arrangement and balconies distribution on buildings reduce solar radiation.

  • ▪ The window-to-wall ratio percentage differs for each facade to balance daylighting penetration and glare. The optimum percentage is 10% for the western, southern, and eastern facades, which is more like the Egyptian energy efficiency in residential buildings, and 60% for the northern direction.

However, the proposed framework aims to close the knowledge gap between students and architects about analytical techniques. It is to mention that the framework can help decision-makers produce modular housing with less energy consumption. It should be noted that the generated floor plans have some limitations that affect the functionality of the architecture space compared to the Sakan Masr architecture plan; some of them can be solved in the design development stage.

  • ▪ The first issue, the blocks’ random arrangement, was carried out as a rule to generate different 3D forms to test the optimum building form with optimization of thermal and daylighting performance metrics. This makes it a challenge for the early-stage design to design the architecture plan, which can be modified in the next stage of design development, such as if some iteration of generating blocks far from each other’s corridors can be added.

  • ▪ The second issue is the bathroom’s plumbing location. Again, it differs that not all the units can be distributed vertically, but two ducts can collect the plumbing and the reservations; screens to hide the plumbing can be added in the design development stage.

  • ▪ The third issue is the quality of architecture space function; it should be noted that the generated units are in the same area provided by the government, but the footprint is different. As there is a generation of in-between spaces due to the difference in floor outline, this can be developed in the design development stage; its access can be from an apartment or can be shared between every two apartments. Moreover, there is an option to use these spaces as vertical outdoor spaces for users, which was recommended after quarantine.

  • ▪ The fourth issue, the space syntax, differs from Sakan Masr. Still, most of the spaces are achieved, so the recommended further research will investigate the space syntax with the performative and generative design.


The residential building sector in Egypt consumes approximately 60% of the total energy consumption [3], allowing architects to be responsible for reducing these cooling loads. Therefore, architects should enhance their tools and design methods to generate building forms that consume less energy. Considering these issues, this research aimed to develop a design methodology to improve building energy consumption through form finding. By integrating Oxman design models, one of the generative design models is shape grammar, which depends on rules to generate forms [21]. Research used the characteristics of rules to generate forms based on sliders to act as genes in the fitness function, such as the arrangements of the building blocks and the location of the balconies. As a result, the fitness function optimizes radiation, cooling loads, and daylighting metrics for performance design.

It should be noted that the methodology at first was to optimize the thermal daylighting and cooling metrics simultaneously by applying it at this building scale due to the multiple variables. Nevertheless, no results appeared due to the numerous variables with various metrics simultaneously.

Therefore, the research methodology has been changed step by step. First, the building block arrangement and balconies’ locations are optimized to reduce thermal and cooling loads through total radiation metrics. Then, the percentage of WWR is optimized using ASE and SDA daylighting metrics, and the results indicate that in the north façade, the WWR is 60%, and for the southern, western, and eastern facades, the WWR is 10%.

The results present a valuable block arrangement to improve shading, especially in the eastern, western, and southern façades, which is one of the most critical aspects in reducing the cooling load. Additionally, the balconies’ arrangement is directed to the southern, eastern, and western facades, not the northern ones.

Finally, the output architecture plan zones can be distributed and furnished with multiple solutions, for example, all wet areas attached to the side elevation or court to be served with infrastructure plumbing fixtures. In addition, a simple modification can be added, such as the highlighted space, to ensure the circulation performance of residences, as shown in Fig. 8. Also, it should be noted that the produced plans have limitations in their designs, as there are generated spaces due to the different outline of each floor; this spaces can be suggested by authors to be used for vertical outdoor spaces for the residence which can be planted, as after the pandemic period the architect should design flexible housing units to be resilient for crisis times and outdoor spaces can be added to the housing prototype standards.

Fig. 8
figure 8

Illustrates the output architecture plan for level one with zone distributions

The introduced framework provides a decision-making tool for architects to design buildings with high-energy performance to save energy in residential buildings. Research recommends that the next step is to add renewable energy to produce energy targeting net zero energy. Additionally, as the government demonstrates Sakan Masr in different cities in Egypt, another study can be applied to compare the produced forms with different weather files according to the suggested cities and buildings.

Additionally, this framework can be introduced to students and merged into the educational programs/curriculums to make them aware of building performance simulation methods to save energy and decide the optimum building form that saves energy in early-stage design.

Availability of data and materials

Not applicable



Computer-aided design


Spatial daylighting autonomy

Annual ASE:

Annual sunlight exposure


Energy use intensity


Shape grammar


Window-to-wall ratio


  1. AbdulRaheem OB, Abdulwahab Rayis O (2016) Design of generative model for the language of traditional suakin using parametric shape grammar. International Journal of Computer-Aided Technologies 3(2/3):01–18.

    Article  Google Scholar 

  2. Al-Azzawi T, Al-Majidi Z (2021) Parametric architecture: the second international style. IOP Conf Ser: Mater Sci Eng 1067(1)

  3. Alsaadani S (2022) A statistical review of a decade of residential energy research in Egypt. Energy Reports 8:95–102.

    Article  Google Scholar 

  4. Andino, D., & Chien, S.-F (2014) Embedding garifuna shape grammars in a parametric design software. 202–206.

  5. Aydin, S., Lo, T. T., & Schnabel, M. A (2014) Gamification of shape grammars collaborative and participatory mass-housing design for Kashgar Old Town. ECAADe 32 - Digital Heritage 1, 1(September), 603–612

  6. Chouchoulas O, Day AK (2007) Design exploration using a shape grammar with a genetic algorithm. Open House International 32(2):26–35

    Article  Google Scholar 

  7. Egyptian Electricity Holding Company (2020) Annual Report of the Egyptian Electricity Holding Company2019/2020

  8. Elghazi, Y., Wagdy, A., & Abdalwahab, S (2015) Simulation driven design for kinetic system; optimize kaleidocycle façade configuration for daylighting adequacy in hot arid climates. 14th International Conference of IBPSA - Building Simulation 2015, BS 2015, Conference Proceedings, 182–189

  9. Elsheikh A, Motawa I, Diab E (2021) Multi-objective genetic algorithm optimization model for energy efficiency of residential building envelope under different climatic conditions in Egypt. Int J Constr Manag 0:1–10.

    Article  Google Scholar 

  10. ENERGY STAR (2021) Canadian energy use intensity by property type technical reference. April, 1–6.

  11. Feng J, Luo X, Gao M, Abbas A, Xu YP, Pouramini S (2021) Minimization of energy consumption by building shape optimization using an improved Manta-Ray foraging optimization algorithm. Energy Reports 7:1068–1078.

    Article  Google Scholar 

  12. Granadeiro V, Duarte JP, Correia JR, Leal VMS (2013) Building envelope shape design in early stages of the design process: integrating architectural design systems and energy simulation. Automation in Construction 32(September):196–209.

    Article  Google Scholar 

  13. Hasani K, Borazjani VN, Salami MN (2017) Re-read of court’s form and related spaces with shape grammar case study: 100 houses of Qajar dynasty in kashan city. Bagh-E Nazar 13(44):71–80

    Google Scholar 

  14. Hong, T., & Economou, A (2021) Five criteria for shape grammar interpreters Five Criteria for Shape Grammar Interpreters. March, 189–208

  15. IEA (2022), Buildings, IEA, Paris, License: CC BY 4.0

  16. Jayathissa P, Luzzatto M, Schmidli J, Hofer J, Nagy Z, Schlueter A (2017) Optimising building net energy demand with dynamic BIPV shading. Applied Energy 202:726–735.

    Article  Google Scholar 

  17. Lee JH, Ostwald MJ, Gu N (2021) A statistical shape grammar approach to analysing and generating design instances of Murcutt’s domestic architecture. Environment and Planning B: Urban Analytics and City Science 48(4):929–944.

    Article  Google Scholar 

  18. Mandow L, Pérez-de-la-Cruz JL, Rodríguez-Gavilán AB, Ruiz-Montiel M (2020) Architectural planning with shape grammars and reinforcement learning: habitability and energy efficiency. Eng Appl Artif Intell 96:103909

    Article  Google Scholar 

  19. Nourian P (2016) Configraphics: graph theoretical methods for design and analysis of spatial configurations. A+BE Architecture and the Built Environment 14:1–348

    Google Scholar 

  20. Nourian, P., Rezvani, S., & Sariyildiz, S. (2013). Designing with space syntax: a configurative approach to architectural layout, proposing a computational methodology. 1, 357–365.,%0A

  21. Oxman R (2006) Theory and design in the first digital age. Design Studies 27(3):229–265.

    Article  Google Scholar 

  22. Panya DS, Kim T, Choo S (2020) A methodology of interactive motion facades design through parametric strategies. Applied Sciences (Switzerland) 10(4):1218.

    Article  Google Scholar 

  23. Park, J., & Economou, A (2015) The Dirksen variations towards a generative description of Mies’s courthouse language. 1, 453–462.

  24. Prakash A, Shekhawat H, Goyal G, Prof A, University, Knm (2008) Visual calculation through shape grammar in architecture. Int Res J Eng Technol, 9001, 293–301.

  25. Ruiz-Montiel M, Boned J, Gavilanes J, Jiménez E, Mandow L, Pérez-De-La-Cruz JL (2013) Design with shape grammars and reinforcement learning. Advanced Engineering Informatics 27(2):230–245.

    Article  Google Scholar 

  26. Schnier T, Gero JS (1996) Learning genetic representations as alternative to hand-coded shape grammars. Artif Intell Eng Des 96(1989):39–57.

    Article  Google Scholar 

  27. Shekhawat K, Upasani N, Bisht S, Jain RN (2021) A tool for computer-generated dimensioned floorplans based on given adjacencies. Autom Construct 127:103718.

  28. Singh V, Gu N (2012) Towards an integrated generative design framework. Design Studies 33(2):185–207.

    Article  Google Scholar 

  29. Sisman, M., & Çebi, P. D (2017) Using space syntax as a tool for architectural design. Proceedings - 11th International Space Syntax Symposium, SSS 2017, 28.1-28.12.

  30. Smyth M, Edmonds E (2000) Supporting design through the strategic use of shape grammars. Knowledge-Based Systems 13(6):385–393.

    Article  Google Scholar 

  31. Sushant, V., & Pradeep, D (2013) Adaptive [skins]: responsive building skin systems based on tensegrity principles. Future Traditions [1st ECAADe Regional International Workshop Proceedings, p.155-170.

  32. Svetozarevic B, Begle M, Jayathissa P, Caranovic S, Shepherd RF, Nagy Z, Hischier I, Hofer J, Schlueter A (2019) Dynamic photovoltaic building envelopes for adaptive energy and comfort management. Nature Energy 4(8):671–682.

    Article  Google Scholar 

  33. Tari, M., & Abdolhoseini, M (2019) A study on residential houses using shape grammar (case study: Houses of Pahlavi era in Tehran Province). Religación. Revista De Ciencias Sociales Y Humanidades, 4(21), 65-71. Retrieved from

  34. Toussi, H. E (2020) The application of evolutionary, generative, and hybrid approaches in architecture design optimization. NEU Journal of Faculty of Architecture (NEU-JFA), 2(2), 1–20.

  35. Toutou A, Fikry M, Mohamed W (2018) The parametric based optimization framework daylighting and energy performance in residential buildings in hot arid zone. Alexandria Engineering Journal 57(4):3595–3608.

    Article  Google Scholar 

  36. Trescak T, Esteva M, Rodriguez I (2012) A shape grammar interpreter for rectilinear forms. CAD Computer Aided Design 44(7):657–670.

    Article  Google Scholar 

  37. Upasani N, Shekhawat K, Sachdeva G (2020) Automated generation of dimensioned rectangular floorplans. Autom Construct 113:103149

    Article  Google Scholar 

  38. Vukadinović, A., Radosavljević, J., Đorđević, A., Protić, M., & Petrović, N (2021) Multi-objective optimization of energy performance for a detached residential building with a sunspace using the NSGA-II genetic algorithm. In Solar Energy (Vol. 224, pp. 1426–1444).

  39. Wang, J., Zhao, B., Fan, W., Yang, Y., & Zhao, J (2021) A combined shape grammar and housing-space demand approach: customized mass housing design in rural areas of the North China Plain. Nexus Network Journal, 0123456789.

  40. Xia, B., & Li, Z (2021) Optimized methods for morphological design of mesoscale cities based on performance analysis: taking the residential urban blocks as examples. Sustainable Cities and Society, 64(March 2020), 102489.

  41. Yi, Y. K., & Kim, H (2015) Agent-based geometry optimization with genetic algorithm (GA) for tall apartment’s solar right. In Solar Energy (Vol. 113, pp. 236–250).

  42. Yousefniapasha M, Teeling C, Rollo J, Bunt D (2021) Shape grammar, culture, and generation of vernacular houses (a practice on the villages adjacent to rice fields of Mazandaran, in the north of Iran). Environment and Planning B: Urban Analytics and City Science 48(1):94–114.

    Article  Google Scholar 

  43. Youssef, A. M. A., Zhai, Z. (John), & Reffat, R. M (2018) Generating proper building envelopes for photovoltaics integration with shape grammar theory. In Energy and Buildings (Vol. 158, pp. 326–341).

  44. Youssef AMA, Zhai ZJ, Reffat RM (2015) Design of optimal building envelopes with integrated photovoltaics. Building Simulation 8(3):353–366.

    Article  Google Scholar 

  45. Zboinska, M. A., Cudzik, J., Juchnevic, R., & Radziszewski, K (2015) A design framework and a digital toolset supporting the early-stage explorations of responsive kinetic building skin concepts. The Architectural Convertibles View project Artificial Intelligence View project. December 2017.

  46. Zhang J, Liu N, Wang S (2020) A parametric approach for performance optimization of residential building design in Beijing. Building Simulation 13(2):223–235.

    Article  Google Scholar 

Download references


The authors thank my professors and colleagues at Cairo University’s Faculty of Engineering Architecture Department for their support and recognition.


Not applicable

Author information

Authors and Affiliations



SG analyzed the results and discussion section. AA performed the methods section. RM interpreted the introduction section. Finally, all authors read and approved the final manuscript.

Corresponding author

Correspondence to Soha Mohamed Elgohary.

Ethics declarations

Competing interests

The authors declare that they have no competing interests.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Elgohary, S.M., Abdin, A.R. & Mohamed, R.M. Performative driven form finding in the early design stage. J. Eng. Appl. Sci. 70, 73 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: