Energetic performance of urban forms Julia Tschetwertak Bauhaus University Weimar, Germany Junior Professorship Computational Architecture: Prof. Dr. Reinhard Kรถnig & Professorship Informatics in Architecture: Dipl. Ing. Sven Schneider E-mail: julia_tschetwertak@gmx.de
This research paper introduces a computational tool which was designed to automatically generate basic urban form models which vary in their size, orientation, height plus in the density of the urban structure. Followed by an automated performance evaluation, ranges of energy performance values are delivered. Aiming to compare different urban forms in terms of their heating energy demand, several diagrams display the calculated results and design conclusions for city planners are made. Keywords: urban morphology, automated model generation, variation of urban forms, automated performance evaluation, heating energy performance, compare urban forms
Introduction Urban morphology in conjunction with building energy performance is a major topic in architectural research. Various factors including urban morphology, architectural typology, construction technologies, energy systems and the behaviour of the inhabitants are significant factors for the energy demand of a city fabric. Resulting from the combined multiplicative effect of these factors, the energetic performance can vary greatly. According to studies of the CSTB Urban Morphology Laboratory which confirm previous studies conducted by the MIT in London, Berlin and
Climate
Urban morphology Factor: 1.8
Toulouse, it was found that the factor for urban morphology is 1.8. That is the same factor as for energy systems. Only building physics (2.5) and occupants` behaviour (2.6) have a higher effect on the energy demand (Figure 1) (Ratti et al., 2005; Salat, 2009). These numbers confirm that the shape of an urban form has a considerable impact on the energetic performance. In his study, Salat (2009) showed that 77% of the energy consumption in Parisian housing accounts to heating. In reference to that, this paper takes the heating energy demand as the comparative value for different urban forms.
Building physics (architecture & materials) Factor: 2.5
Systems (heating & cooling) Factor: 1.8
Occupants` behaviour Factor: 2.6
Figure 1 Factors affecting the energy performance of Paris as calculated by the CSTB Urban Morphology Laboratory
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Basic urban forms are subject of the study. Through transformative operations the shapes vary in size, orientation, height plus in the density of the urban structure. The thermal models for the energy analysis are generated automatically by marking grid cells with line objects. Custom settings like the scaling factor of the form, the number of floors, orientation angles, building distance and many more enable the designer to produce countless variations in a short time. On the other hand generating and analysing these models manually is very time consuming. This paper introduces a framework for accelerating the production of form variations and their performance analysis. The tool can be helpful to city planners and architects in the early design stages for identifying the most effective urban forms and their sizing in terms of energy demand. During a case study four urban forms are transformed, each in five different ways and every single variation analysed in regard to its annual heating consumption. The results are displayed through diagrams.
Base models The shape of an urban form has a significant impact on its energetic behaviour. As mentioned above, it has the same factor of 1.8 as building systems which control heating and cooling. That means that it can be compared to the energy consumption difference between electrical, gas and heating oil systems (Salat, 2009). Regarding that resemblance, it is of economic and environmental interest to planners to be aware of the importance of building shape and the attendant urban form. Urban form can be described by the shape factor C = A/V where A is the external surface exposed to the environment and V is the form volume. The higher the value of C, the less compact is the form (Ratti et al., 2005). In relation to the energy performance, it can be said that, the more external surfaces are exposed to climatic conditions (high C-value), the higher is the value of heat loss during cold weather
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and the higher the heat gain during warm weather. That leads to higher heating energy demand in winter and to higher cooling energy consumption in summer time. However, a higher C-value can be beneficial in cold weather when the solar gain through exterior surfaces and windows cause heat gain within the form and reduces therefore the heating energy demand. In summer a higher C-value can have a positive effect on the cooling at night time since there is more external surface area to emit the heat from the forms inside to the environment which reduces the cooling energy demand. These opposing dependencies require a balance between high and low C-value for an optimised building energy performance. Certainly further factors need to be taken into consideration when looking for this balance. One important factor is the sizing of the window area since that causes solar heat gain as well as heat loss due to the insulation properties of the glass material. Furthermore natural daylight is required in working and living areas. An adequate window area can reduce the demand for artificial lighting energy significantly. However an oversized window area can cause unnecessary heat loss during winter and solar heat gain in summer time. This leads to the same conclusion as for the C-value, that a balance between a high and low window surface area is relevant to the form energy performance. In addition to the window area, the shading from surrounding forms needs to be considered since that can reduce the solar gain as well as the amount of daylight accessing the form.
The Urban Form & Energy Tool created with the software Grasshopper for Rhino 3D aims to generate urban forms parametrically, rapidly and with least effort. Therefore the shapes are based on a grid which is variable in its size and its numbers in x- and y-direction. In the following example the grid size is 8 m x 8 m and has 6 cells in x- and y-direction. The advantage of this method is that the shapes are easy to generate by filling in the marked cells. Additionally they have the same shape structure
which facilitates the comparison between them. A disadvantage is that this structure is limited to the shape of homogeneous rectangles/squares which doesn`t necessarily correspond with real site conditions. However, the aim of this tool is not to analyse real building stocks but to provide an understanding of how different shapes of urban forms and their transformations affect the energetic performance. For creating a shape the user needs to draw at least one line into the grid cells which activates the marked cells and the basic shape footprint is generated. The tool takes automatically all grid cells as the site area (figure 2).
Figure 2 Draw lines into the grid (6 x 6 cells, each 8m x 8m), generate footprint, generate site
The form volume is defined by the floor height multiplied by the floor number (e.g. 2,7 m x 2 floors). Only the initial form is divided by slabs, the other surrounding forms are solid volumes without windows. This reduces the calculation time (figure 4).
Figure 4 Generate floors and volume (2,7 m x 2 floors)
The windows of the initial form are generated by moving the outline of the shape footprint to the parapet height of each floor and extruding that according to the window height (e.g. 1,0 m parapet height, 1,2 m window height). This simplification of the window layout allows a better comparison between the different forms because it depends primarily on the length of the shape footprint outline (figure 5).
In addition to that, the tool generates the ground which is the sum of the site area placed eight times around the site. On each of these eight fragments of the ground is placed a copy of the shape. These are the surrounding shape footprints (figure 3).
Figure 3 Generate ground area, generate surrounding shape footprints
Figure 5 Generate windows on the initial form (parapet 1,0 m, windows 1,2 m)
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Another action to make the forms more comparable is scaling them up or down to the same footprint area (e.g. 800 m²) which indicates that they have the same volume as well (figure 6).
Output parameters The base models as well as the thermal models deliver a range of output values which are necessary for the comparison of the forms. Such are for example the grid size, the footprint area, the site area, the density, the FAR (figure 7), the shape factor C and the window area. This case study focuses on the yearly heating energy consumption per m² of the four different urban forms and their transformations.
100% coverage
50% coverage
25% coverage of the site
Figure 7 FAR = 1 (floor area ratio = site area/ built form area) Figure 6 Scale footprint area to the set up value
Thermal Models Energy analysis requires thermal models. Therefore the volume of the initial form gets divided into thermal zones by walls, floors and ceilings. In this example the zones are defined by floors and ceilings only without additional walls in-between (figure 8). Windows are treated as holes in the envelope covered with the chosen material (e.g. double clear glazing). Shading is created by the surrounding forms. Materials of the form components can be defined manually but for the matter of comparison of different forms in this case study, the same materials will be applied to all forms according to their function (slab, roof, facade, window). Several other settings can influence the energy analysis, for example the heating/ cooling point (e.g. 20°C/ 26°C) or the infiltration rate (e.g. 0,5 ACH). Before starting the analysis process the output needs to be chosen (e.g. monthly heating energy demand). Figure 8 Thermal model with two thermal zones, windows, ground surface and surrounding forms
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Case study: four urban forms There is a high number of urban forms in existence and all of them have their own characteristics. In his case study four of the most basic forms are generated and analysed. One form can consist of one single building or a group of buildings which are freestanding or directly attached to each other. The first is the pavilion/ tower form (Martin & March, 1972). It is defined by a solitary standing form with one or multiple floors (figure 9).
Pavilion/ Tower
The next urban form is the perimeter block which has characteristic inner courtyards (figure 9).
Perimeter block
The third urban form to analyse are the blocks. They have an elongated rectangular shape. On one site two identical blocks are located (figure 9).
Blocks
The last of the four forms is the court form. Here all forms are connected to each other through eight connection walls (Martin & March, 1972). This emerging network creates equally sized courts (figure 9). Through five transformative operations, a range of variations of these four urban forms is created and their energy analysis results compared.
Courts Figure 9 Four basic urban forms
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Transformation: Orientation The orientation of an urban form has an impact on the solar gains of the interior and therefore on the heat gain. It is of great significance which exterior surfaces are facing which cardinal direction. Surfaces exposed to the south receive more sunlight than the ones oriented towards the north. In the morning hours the surfaces facing the east get most solar radiation. About midday the surfaces oriented towards the south and in the evening the west directed facades experience most sunlight. The reason for this phenomenon is the position of the sun during the different seasons and times of the day (figure 10).
40° Rotation
Figure 10 Sun positions of the seasons and day times
To analyse how the orientation of the urban form affects the energy performance, the tool rotates the initial form with its site plus the surrounding forms accordingly to the number of calculations aimed or to the custom rotation angles which can be set up manually. In this case study, the 360 degrees got divided by 9 calculations which resulted in a rotation angle of 40 degrees. Starting with 0 degrees up to 320 degrees the tool generates 9 thermal models of each urban form for the analysis (figure 11). The results are presented in the following diagram (figure 12). As mentioned above, the different sizes of the models come from the scaling which provides each layout with an identical form footprint area (e.g. 800 m²) to make them more comparable. Figure 11 Rotations of the initial model, its site plus the surrounding forms
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Pavilion/ Tower
Perimeter block
Block
Court
8,16 m
10,00 m
6,32 m
Floors
2
Form height
5,4 m
Grid size
14,14 m
Footprint area
800 m²
Density
0,19
0,59
0,39
0,98
FAR
0,22
0,66
0,44
1,11
C = A/V
0,32
0,43
0,44
0,50
Figure 12 Heating Energy - Orientation diagram of four basic urban forms
The first result of the four urban forms is calculated without any rotation of the model (0°) which gives an indication of how their energy performance is compared to each other. With approximately 31,2 kWh/m², the pavilion form is more energy efficient than the others. One explanation for that is its shape factor C of only 0,32 which is the smallest of all. The court with the biggest envelope area has a much higher shape factor of 0,50. This value influences the heating energy demand of the court which is 58,6 kWh/m². Regarding the perimeter block and the block form, the shape factor is almost the same but the energy performance is different. The most likely reason for that is the shape of the urban forms.
While the perimeter block has four identical sides, the block has two different pairs of identical sides. In context with the sun positions this circumstance influences the solar heat gain and causes a higher heating energy demand for the block. As for the variations of orientation angles, the heating energy performance of the forms does not change significantly (≈ 1 kWh/m²). Although a closer look at the results reveals that considering the orientation during the planning process of an urban form can be beneficial for the energy performance. Since these numbers are showing the value per m², the energy that can be saved in the overall form is worth paying attention to.
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Transformation: Scaling The aim of the scaling transformation is to investigate the correlation between the size of the urban form and the heating energy demand per m². As the grid size gets scaled, the dimensions of the footprint change (figure 14). In contrast, the number of floors remains the same as well as the form height (e.g. 2 floors, 5,4 m form height). According to the conventional planning guidelines, the natural daylight illuminates the interior of the form approximately up to a depth of 2H (figure 13). That is the length of the parapet height plus the window height, multiplied by two (Brandi, 2005).
1.4
0.5
Figure 13 Natural daylight illumination of a room
That means that the area which is lit by daylight is limited to this illumination depth. Now, regarding the scaled forms, their grid size increases and so does the depth of their form. With rising scaling the proportion of the areas which get lit by daylight decreases and the proportion of the areas which don`t get accessed by daylight increases. That has a negative impact on the significance of the solar heat gains of the form. Another important parameter which changes is the form volume. The bigger the volume the more heat can be retained on the inside and the longer the form needs to cool down. Furthermore, the shape factor C changes because of the two dimensional scaling instead of three dimensional, since the form height remains the same. Proportionally to the form and the surrounding forms, the ground gets scaled so that the FAR as well as the density remain constant.
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Figure 14 Scaling of the base model, its site plus the surrounding forms
0,5
0,6
0,7
Pavilion/ Tower
0,8
0,9
1,0
1,1
1,2
1,3
1,4 Scaling factor
Perimeter block
Block
Court
4,08 m to 11,43 m
5,00 m to 14,00 m
3,16 m to 8,85 m
Floors
2
Form height
5,4 m
Grid sizes
7,07 m to 19,79 m
Footprint areas
200 m²; 288 m²; 392 m²; 512 m²; 648 m²; 800 m²; 968 m²; 1152 m²; 1352 m²; 1568 m²
Density
0,19
0,59
0,39
0,98
FAR
0,22
0,66
0,44
1,11
C = A/V
0,46 to 0,28
0,67 to 0,36
0,68 to 0,37
0,81 to 0,41
Figure 15 Heating Energy - Scaling diagram of four basic urban forms
As described in the previous chapter, the four urban forms have different heating energy demands mainly because of their shape factor C and their footprint shape. When the forms get scaled down from 1,0 until the factor 0,5, the heating energy demand increases (figure 15). One explanation is that the form volume decreases and less heat can be retained on the inside. The form cools down faster and more heating energy is needed to maintain the desired inside temperature. Another reason may be the high window area in proportion of the envelope area. Glass has worse insulation properties than insulated facade walls what in this case, increases the heat loss through the window
surfaces. On the other hand the heating energy demand decreases because of the proportionally high solar gain. Despite that, the heating energy consumption remains considerably high what leads to the assumption that the volume is a significant parameter. Up scaling the form from 1,0 to the factor 1,4 improves the heating energy performance of the building. Although the difference between the heating energy values gets less with every up scaling step. The reason for that lies most likely in the influence of the decreasing shape factor C which means that the form gets more compact and less heat can be emitted through the surface of the envelope.
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Transformation: Thickness Another transformative process is the change of the form size by homogeneously adding area all around the form in relation to a thickness value (e.g. 0,3 m). For the most part, that transformation can be compared to the scaling in the previous chapter. There is but a difference in the forms which have a gap in their shape like the perimeter block and the courts form. Then the gap gets smaller with the increasing thickness value. Furthermore, the site maintains its area plus the position of the surrounding forms doesn`t change (figure 17). Resulting from this is that the distance between the forms decreases with the rising of the thickness value and the density increases. The number of floors as well as the form height remain the same.
0.3 m
When the distance between the urban form and the surrounding forms gets smaller, possible shading comes into focus. That is dependent on the form height (H) and the form distance (A) (figure 16). In this example the form height is a fixed value of 5,4 m but the form distance is variable through the thickness value.
Figure 16 Shading from surrounding forms
Depending on the level of shading, the solar heat gain can get restricted leading to a higher heating energy demand. To all four urban forms the rising thickness value is beneficial in terms of the annual heating energy demand per m² (figure 18). Although the reduction rate is mostly different for all forms. The pavilion/ tower records the least change of the heating energy consumption. This may be because, the added volume to the pavilion/tower it too small
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Figure 17 Thickness alteration of the base model plus the surrounding forms
2.7 m
0,0
0,3
Pavilion/ Tower
0,6
0,9
1,2
1,5
1,8
2,1
2,4 2,7 Thickness addition [m]
Perimeter block
Block
Court
Floors
2
Form height
5,4 m
Starting grid sizes
14,14 m
8,16 m
10,00 m
6,32 m
Footprint areas
800 m² to 1134 m²
800 m² to 1329 m²
800 m² to 1398 m²
800 m² to 1229 m²
Density
0,19 to 0,28
0,59 to 0,98
0,39 to 0,69
0,98 to 1,51
FAR
0,22 to 0,31
0,66 to 1,10
0,44 to 0,77
1,11 to 1,70
C = A/V
0,32 to 0,30
0,43 to 0,33
0,44 to 0,35
0,50 to 0,35
Figure 18 Heating Energy - Thickness diagram of four basic urban forms
in comparison to the forms whole volume. Represented through the low shape factor difference of 0,02 from 0,32 to 0,30 the form doesn`t change much of its compactness as well. Additionally, the shading has no significant impact on the energy performance since the distance remains high between the forms. In contrast, the other three forms reveal a bigger difference within their own heating energy demand, especially with the perimeter block. Furthermore, the court demonstrates the impact of the increasing volume because proportionally, they gain more volume through their gaps in the shape than the forms which represent solids. That indicates why the block and the pavilion/
tower form have a smaller difference within their own heating consumption. It can be supposed that the shading affects the perimeter block and the court form more than the others because of their higher density, which leads to a higher energy demand. In the first calculation the difference of the heating energy demand of the four forms is approximately 26 KWh/m² which drops with rising thickness addition to about 10 kWh/m². That can be seen in comparison with the shape factor C which has a difference of 0,18 in the beginning and of only 0,05 in the end. This leads to the assumption that the shape factor C is an important indicator for the heating energy performance of an urban form.
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Transformation: Density The density value describes the ratio of the total form area plus the surrounding form area divided by the total ground area. Since the form area as well as the volume remain the same, the distance between the forms becomes variable in this transformation method. The tool generates models with a defined form distance using a step size (e.g. 2 m) (figure 20). A phenomenon which is influenced by the density of forms is the urban microclimate. Several factors change when urban forms act as a group with high density in comparison to low density appearances. Like figure 19 shows, the sunrays get captured between the forms as they get reflected by the envelopes. This causes higher air temperatures between the forms and heats up the facades. This additionally decreases the heat loss of the forms. In conclusion the heating energy demand decreases.
2m
Figure 19 Urban microclimate
Furthermore, the wind speed reduces between the forms causing a decrease in the warm air evacuation from these spaces. The warm air remains longer in the in-between spaces and reduces therefore the cool down of the envelopes. This is beneficial for the energy performance of the urban forms (Dorer, 2012). Additionally the shading which is explained in the previous chapter can influence the solar heat gains.
Figure 20 Density alteration of the base model plus the surrounding forms
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20 m
Pavilion/ Tower
Perimeter block
Block
Court
8,16 m
10,00 m
6,32 m
Floors
2
Form height
5,4 m
Grid size
14,14 m
Footprint area
800 m²
Density
0,60 to 0,38
0,91 to 0,53
0,61 to 0,39
0,92 to 0,54
C = A/V
0,32
0,43
0,44
0,50
Figure 21 Heating Energy - Density diagram of four basic urban forms
As the volume and the shape factor C of the forms remain the same during the transformation, the density and the shading are the two influential parameters to the annual heating energy demand per m². The difference of the heating energy performance within each form transformation is comparably low in regard to the other transformative operations. A difference of approximately 1,3 kWh/ m² of the perimeter block form shows that the microclimate phenomenon reduces the heating energy demand with increasing density. On the contrary, the shading increases with higher density and lowers the solar heat gain what increases the heating energy demand. In
conclusion, it can be assumed that these two parameters density and shading have an opposing effect on the energy performance of the urban forms. This can be a reason for the low difference between the heating energy demand values. The least heating energy consumption difference of approximately 0,5 kWh/m² has the court form. Because it has almost the same density values as the perimeter block, the most likely explanation for that is its shape. The same applies to the block which has a difference of about 1,25 kWh/m² and the pavilion/ tower with its 1,0 kWh/m² heating energy consumption difference.
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Transformation: Height The last transformation is the change of form height (figure 23). Here the step size is the number of floors (e.g. 2 floors starting with one floor). The previous transformative operations show that the volume and the shape factor C of a form have significant impact on its heating energy performance. Every additional floor gets the same window surfaces what in total increases the solar heat gain within the forms. This has a positive effect on the annual heating energy consumption of the form, although higher forms cause more shadows which can lead to less solar heat gain (see chapter Transformation: Thickness, figure 16).
11. floor
3. floor 1. floor
high shape factor C (low compactness)
low shape factor C (high compactness)
Figure 22 Increasing number of floors according to the step size of 2 floors
As a result of the form area increase effected by additional floors, the FAR value increases. The shape factor C decreases which means that the form gets more compact (figure 22). Regarding the shape factor C of the forms with only one floor (figure 24), the perimeter block has the highest value of 0,61 and in relation to that it has the highest heating energy demand of about 117 kWh/m². In comparison, the block form has the lowest shape factor of 0,44 and in proportion to that the lowest heating energy consumption of about 51 kWh/m².
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Figure 23 Increasing the height of the base model plus the surrounding forms
Pavilion/ Tower
Perimeter block
Block
Court
10,00 m
6,32 m
Floors
1; 3; 5; 7; 9; 11
Form height
2,7 m; 8,1 m; 13,5 m; 18,9 m; 24,3 m; 29,7 m
Grid size
14,14 m
Footprint area
800 m²
Form areas
800 m²; 2400 m²; 4000 m²; 5600 m²; 7200 m²; 8800 m²
Density
0,09 to 1,08
0,29 to 3,25
0,39 to 1,38
0,98 to 3,45
FAR
0,11 to 1,22
0,33 to 3,66
0,44 to 1,55
1,11 to 3,88
C = A/V
0,51 to 0,17
0,61 to 0,27
0,44 to 0,30
0,50 to 0,36
8,16 m
Figure 24 Heating Energy - Height diagram of four basic urban forms
The big difference of 0,34 in the shape factor C of the pavilion/ tower and of the perimeter block gets reflected proportionally in their heating energy performances. The difference in the heating energy demand of the pavilion/ tower is 94 kWh/m² and of the perimeter block it is 99 kWh/m². On the contrary, the low shape factor difference of 0,14 of the block and the court form goes along with lower differences in the heating energy demand of these two urban forms. The heating energy performance difference of the block form is 38 kWh/m² and of the court form it`s 41 kWh/ m². That plus previous examples lead to the
conclusion that the shape factor C influences the heating energy consumption proportionally. The density increases with the number of floors added. That can have a beneficial effect on the microclimate between the buildings and reduce heat loss through the envelope which can be one reason for the comparably low heating energy demand. Nevertheless, the shading can increase the heating energy consumption by reducing the solar heat gains.
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Conclusion & outlook The energy performance of urban forms is dependent on the combination of several factors. Some of these factors describe the form itself (e.g. the shape factor) and others are environmental influences like solar radiation. Through different transformational methods, the form attributes can be altered which then affects the impact of the environmental influences on the form. The case study shows that the conducted transformations can change the heating energy demand of the forms significantly. Least impact on the difference of the heating energy demand have the orientation and the density of the urban form. Nevertheless finding an optimised solution for these can save a decent amount of energy. Scaling, the thickness alteration and the increase of the form height lead to the biggest difference of the heating energy demand. These transformations change the volume and the shape factor of the forms. The calculation results of the case study confirm that the form volume and the shape factor are the most influential form attributes in regard to the heating energy performance. Regarding the four investigated basic urban forms, the shape has direct impact on the shape factor and therefore on the heating energy consumption. By paying attention to these factors during the design process, an enormous amount of heating energy can be saved. Awareness of the influence of environmental factors like solar radiation, shading and the urban microclimate phenomenon can additionally help with optimizing the energetic performance of urban forms. Further research could provide a wider range of transformation methods and generate more detailed form models (e.g. different window layouts). That would expand the tools possibilities of model generation and conclude in more accurate simulations. Additional energy output parameters (e.g. the cooling energy consumption, the artificial lighting demand) can offer a closer look at the influence of form attributes and environmental factors on the energy performance.
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References Dorer, V. 2012 ‘Urban Physics für die Planung von Gebäuden ’ Novatlantis Bauforum, Zürich Martin, L. and March, M. 1972 ‘Urban Space and Structures‘ Cambridge Urban & Architectural Studies, Cambridge, pp. 35, 36 Ratti, C., Baker, N. and Steemers, K. 2005 ‘Energy consumption and urban texture ’ Energy and Buildings, 37(7), 762-776 Salat, S. 2009 ‘Energy loads, CO2 emissions and building stocks: morphologies, typologies, energy systems and behaviour’, Urban Morphology Laboratory, Building Research & Information, Paris, pp. 599-602
Images Figure 1: Salat, S. 2009 ‘Energy loads, CO2 emissions and building stocks: morphologies, typologies, energy systems and behaviour’, Urban Morphology Laboratory, Building Research & Information, Paris, p. 599 Figure 7: Cheng, V., Steemers, K., Montavon, M., Compagnon, R. 2006 ‘Urban Form, Density and Solar Potential‘ PLEA2006- The 23rd Conference on Passive and Low Energy Architecture, Geneva, p. 3 Figure 10: http://www.big.dk/#projects-bhs, 27.03.2016 Figure 13: Brandi, Ulrike: Tageslicht, Kunstlicht. Grundlagen, Ausführung, Beispiele. WeselKommunikation, München 2005, S. 20, 22 Figure 16: http://p221522.typo3server.info/ uploads/RTEmagicC_Skizze_Verschattung_02. png.png, 28.03.2016 Figure 19: Dorer, V. 2012 ‘Urban Physics für die Planung von Gebäuden ’ Novatlantis Bauforum, Zürich, p. 7 All images are produced by the author of this paper excluding the stated above.