RE:Generation Master's Thesis

RE:GENERATION

VERONIKA KOVACH

Design

Tool In Reuse

Existing

Master Thesis | Wintersemester 19 | 20 Technische Universität München | Fakultät für Architektur Lehrstuhl für Architekturinformatik Prof. Dr.-Ing. Frank Petzold

Technische

Fakultät für Architektur

Lehrstuhl für Architekturinformatik Prof. Dr.-Ing. Frank Petzold

Master Arbeit

Planungsunterstützung bei der Wiederverwertung bestehender Gebäude

Master Thesis

Design

Veronika Kovach Matr. Nr. 03711405

Time

Supervisors:

Prof. Dr.-Ing. Frank Petzold Dipl.-Ing. Michael Mühlhaus

Chapter

Chapter

Chapter

Chapter

Chapter

Chapter

A usual consequence of contemporary ur ban development remains the city expansion. New buildings are fast to design and easy to construct, which makes it a comprehensible solution to growing housing demand.

But how feasible is it in a long run? New buildings require new infrastructure, service supply and functional diversity in order to function autonomously. So far, the majority of Russian cities are suffering from uncon trolled suburban growth, that is not being strategically overlooked of maintained.

One of the possible tactics to help overcom ing the need to extend the city borders is to work with existing structures. On the exam ple of Saint Petersburg, Russia, a typology of historical houses called Dohodny Dom was found and analyzed for a possibility of pro spective redevelopment by means of adapt ing them to new functions. The subsequent aim then was to ensure a systematic ap proach; in this regard another major topic of this study is the appliance of computer sup port in the early stages of building re-design.

For that, several measurable evaluation pa rameters were constructed, the outcome of which is set to help the architect make more informed decisions in less time.

On the example of the Case Study house the developed approach was executed.

Saint Petersburg is a city with estimated number of citizens of 5.38 million1. That makes it one of the largest cities in Europe, that is being rapidly urbanized. Annual number of new incomers spikes the demand for housing blocks, the realization of such is the quickest in periphery.

The dedication to provide the buyer with passable options and therefore sell as much property as possible, leads developers to postpone infrastructure supply. Moreover, the projects do not include any provision of job market, that results in low-density areas, highly dependent on city centre. There is also a fear of ruining natural landscape of St Petersburg northern border2 .

The problem of reviving periphery can be perceived as a goal on its own, but in the scope of this project, it is shown rather to illustrate the importance of maintaining a compact functioning city.

Fig.1 Map of St Petersburg. Dark areas - new development in periphery. Dotted line - borders of the city centre.

St Petersburg demographics over the years.

Fig.2 Illustration of statistical data (Petrostat).

New incomers

The demographical situation in the city has changed over the years; only in the last decade the population has grown from 5 million in 2013 to 5.4 million in 2019⁴. Naturally this implies the increasing demand on housing and new infrastructure. Unfortunately, in this time period there has been no effort made to efficiently distribute available space. On the contrary, the obvious direction of city’s development has been expansion in size by adding up surrounding territories.

As expected, the demand for housing in Saint Petersburg is increasing with time. Most popular among consumers are locations outside the city centre - they make up the

most affordable option⁵. Moreover, the around 20% of every building complex is being sold to incomers from outside the city⁶ .

Another important aspect of real estate market in Saint Petersburg is the fact, that a lot of people prefer buying their own dwelling to renting one; the number of tenants has dropped by 25% from 2010 to 2015⁷. One could argue this is consequent to general public desire to ensure stability by investing their capitals, rather than spending them on rental payments. As a result, however, suburban development continues to grow, as the demand for a cheap and fast-built housing is dominating the market.

4 Petrostat, “Demographics: Petrostat.”

5 Fontanka, “Demand for housing in St Petersburg has grown by a third,”

6 Delovoy Peterburg, “Higher than Moscow. Demand for real estate in St Petersburg is not slowing down.”

7 Novye Isvestya, “Renting instead of buying: why owning an apartment is a mistake.”

Fig.3 "Severnaya Dolina". (Varlamov 2016).

Periphery now

Said rapid development of the periphery results in vast mono-functional areas, that surround the city centre.

The housing complex pictured above (“Severnaya Dolina”) is planned to fit 80.000 residents on the building plot of 270 Ha8 . As all the blocks are high rises, the distance between them is proportionally increased. The outcome space would then be dedicated for parking; apart from it there is hardly any form of landscape design or recreational facilities (e.g. cafés, retail, workshops).

Buildings of this type are set to be as simple as possible construction-wise; that calls for respective design projects (typically, developing companies cut on architect studios service). Material quality remains law, so do the construction works.

All of the above make up for a highly profitable business and a strong competitor on the market.

Because of the reasons mentioned above, a sort of opposition movement has been formed towards how St Petersburg is being developed; it consists of architects, urbanists and journalists. Their main argument is that the affordable housing of such configuration has a total monopoly; for a regular consumer there is practically no other option left, than to invest in their own “private corner”.

Further concern revolves around sociological aspect – what neighborhoods are to be formed in such conditions? As of now, there is no clear answer: areas like that are still newly built and there is no corresponding examples of last years to make a feasible comparison9 .

8 Varlamov, “New districts of St Petersburg - would you like to live like that?,”

9 Varlamov, “Why highrise suburbs are bad (on the example of Parnas District in St Petersburg).”

INVISIBLE VOIDS IN THE CITY PERIPHERY EXPANSION

Urban voids disrupt city fabric and ruin network chain

...they provoke city expansion and periphery growth

FILLING OUT THE GAPSDETECTING THE VOIDS

Establishing new connections

...and creating sustainable poly-centres

Fig.5 Density comparison. Same scale. On the left - periphery (FAR = approx. 17%). On the rightSt Petersburg city centre (FAR = approx. 50%).

Invisible voids

As such a state of suburbs remains a known problem in many Russian cites, there has been some pilot projects, that aim towards improving the city fabric in those areas. One of them is called Dvoruliza and there the focus lies on densification of Moscow periphery by converting empty space into street fronts10 .

As proposed in Figure 4 on the left page, a way of competing with growing periphery is shifting the focus towards existing city and its compactness. However, as depicted in Figure 5 (right side), it becomes clear, that there are essentially little to no empty plots to proceed with densification.

That leaves us with the need of further investigation – as any other city, St Petersburg is a developing system; due to this fact, a lot of buildings inevitably go out of use. Such invisible voids remain a problem for urban fabric – they serve no purpose and steal valuable space. Yet they can also be seen as a potential – adapting them for new use.

Three major categories of invisible voids in St Petersburg can be highlighted – former industry, out-of-use infrastructure and abandoned historic houses (Figure 6).

URBAN VOIDS IN SAINT PETERSBURG REUSED SPACE

Industry Infrastructure Historic houses focus of this study

Public opinion

Saint Petersburg city centre is included into UNESCO heritage and is being protected by government policies of cultural heritage11. Accord ing to the Federal Law n.73, it is forbidden to demolish buildings built before 1917 in central area of St Petersburg12. Unfortunately, there are still many cases of breaking the restriction: illegal demolition remains a common case for the city.

One of the recent examples of that was the house on Ropshinskaya, 10, built in 1895. After performing an expertise, it was concluded that based on renovation works in 1947, the building does not any longer fall under protection and therefore has been demolished13 .

Due to the fact that malpractice like that became quite frequent in last decades, public movements and organisations against them have been established; there are nine major ones at the moment14. They would focus on trying to protect historical buildings either by collect ing petitions or attracting media sources. On the Figure 7, one can see a flash mob as a part of long-lasting process of attempting to save the houses from demolition15 .

11 Mihdan and Inforos, “Commission of the Russian Federation for UNESCO.”

12 Federal Law n.73, Appendix 2. regimes, KGIOP (2002).

13 Kanoner, “Historic house on Ropshinskaya was declared as soviet built and will be demolished,”

14 Protective Peterburg, “Organisations List.”

15 Protective Peterburg, “On Febuary 23 took place a protective action "Hug Telejnaya Street" against demolision.”

Fig.7 Locals on "Hug Telejnaya street" flash mob, Feb 2019 (Provective Peterburg 2019)

Fig.8 Construction works on Telejnaya street, Jan 2020. Photo: author.

Governmental measures

In late 2019, city administration has awarded 35 million rubbles to a semi-private firm. The budget was planned to cover expenses of “analysing of improvement potential of existing buildings in historical centre of Saint Petersburg”16. All 1330 buildings had to be examined in time period of approx. 3 months. Set expertise had to be executed in order for the law “Restoration, Capital Renovation and Retrofitting of Historic Estate of St Petersburg” to come into effect.

The law project is currently put on hold, as it awaits further approval and support from higher governmental structures.

Another promising, but less financially supported program is called "Affordable housing for the Youth"17. Young families can either apply for 0% credit for new apartment or obtain a 40% discount when buying renovated apartment. For the latter, the city is performing a renovation of historic houses in the city centre. As of now, there are 12 houses in the list, including Dom Zelibeeva, which is also a Case Study building for this project18 .

16 Primechaniya, “Historic centre of St Petersburg is to be renovated by the unapproved law.”

17 St Petersburg City administration, “Affordable housing for the Youth.”

18 St Petersburg Center of Affordable Housing, “Objects of capital renovation. Affordable housing for the Youth.”

dohodny dom

Mansion - elite - permanent - central

TYPOLOGIES OF HISTORIC HOUSES

- 1917

Dohodny Dom - all classes - temporary - central

Dacha - elite - temporary - periphery

Since its foundation in early 1710-s, St Petersburg was being oriented towards European development. This was later reflected in adapting some special lifestyle traits, uncommon for other Russian cities. As around 70% of city’s population were men, who were coming for ad ministrative or military service, seasonal works and so on, residential market has adapted to temporary stays like that19. That would divide the available housing into two categories: temporary rent and perma nent ownership.

Simultaneously, society of that time was strictly classified (primarily by descent and later wards by income), what separated real estate into elite, regular and peasant housing. Naturally, residential housing can also be classified by their location: central (Mansion) and suburban (Dacha) 20 .

Temporary rental for long periods of time (weeks, months and years) first appeared in 1710-s, but gained their popularity in 1820-s. This has produced a new typology of housing – so-called “profitable house”, or Dohodny Dom. One of the essential traits of this type is multi-class inner structure: each social class could be accommodated there.

Fig.9

Fig.10

Fig.11

Dohodny Dom houses were built primarily for a long-term lease21. Every Dohodny Dom was built by a landlord to be rented out later. Lots of new incomers, attracted to the cap ital of Russian Empire, would spike the de mand in construction industry – the houses would be built fast and dense. Consequen tially, the number of landlords was increasing as well – the most adventurous would own not one, but several houses like that22 .

Generally, Dohodny Dom could house up to 500 people. As mentioned above, the class diversity was one of defining elements of the type – elites would prefer to rent big apart ments in the middle floors (sometimes the whole stories); with 2 staircases: one for ten ants and one for staff. Other social classes, such as students or

clerks, were renting apartments (or rooms) on higher stories, that would face the court yard23. The ground floor was occupied with store owners, similarly to modern-day stand ards.

According to a census performed in 1881, 1890 and 1900 years, the distribution of the profitable houses would differ, depending on the district. Generally, bigger houses with more apartments would be built towards the city centre and smaller houses would appear on the outskirts24

retail residential workshopsoffices

Fig.12 Dohodny Dom's Functionality (kleinwelt architekten)

21 Yuchneva E., Dohodny Dom's of Saint Petersburg. Notes from historic houshold.

22 Zemvopros, “Dohodny Dom in St Petersburg - Short Summary.”

23 Zemvopros, “Dohodny Dom in St Petersburg - Short Summary.”

24 Yuchneva E., Dohodny Dom's of Saint Petersburg. Notes from historic houshold.

In order to proceed with further analysis, existing Do hodny Dom’s should be first identified on the map. There is no such database in open access, so the map had to be constructed. The site called “Citywalls” was chosen as the most trustworthy source, as it is known for collecting in formation about majority of buildings in the city. The fol lowing step was to scrape ad dresses of all houses with tag “Dohodny Dom”25 .

Afterwards the Excel list of approx. 500 houses was constructed, that included in formation about name of the house, year of construction and its address.

In order to visualize this data, the combination of built-in geocoder by Google sheets and web-service ke pler.gl was implemented.

5

Small apartments with low ceilings, rented by peasants - students, low class workers. This was also the place for drying clothes. 26

4

The last floors were occupied by intellectuals. The room area was approx. 16-24 m² and windows were oriented to the yard.

3

Upper class were renting apartments with 10-15 rooms; there were also the first ones to benefit from electric pow er, that eliminated fire places.

Sometimes wealthy families would rent the whole story to themselves.

Ground floor was occupied by offices, stores and clinics.

In the rooms under the en trance lived the doorman. They were responsible for maintenance of the house, heating and cleaning.

26 Shumilov P., Anatomy of Peterburg.

Fig.14 Dohodny Dom typical section (Shumilov 2009)

TYPE I

Landlord: private person or a company27

Tenants: upper-class salesman, clerks, families with big income

Characteristics: street and courtyard façades would differ; many window openings; generally comfortable apartments;

TYPE II

Landlord: private person or a company

Tenants: upper-class salesman, clerks

Characteristics: street and courtyard façades would differ; many window openings; generally comfortable apartments;

cabinet cabinet

balcony boudoir boudoir

TYPE III

Landlord: private person; city administration

Tenants: poor families; clerks

Characteristics: minimal decoration; shared bathrooms and kitchens

hall hall

living room living room living room family subtype single subtype

dining room bedroom bedroom

stuff room stuff room

stairs stairs

Fig.15 Types of Dohodny Dom (kleinwelt architekten)

Century,”

Dohodny

Fig.16 Dohodny dom Lyshnevskogo. Built in 1913. Photo: Dobrodeev.

Fig.18 Dohodny dom Dyrenkova.Built in 1904. Photo: Dobrodeev.

Fig.17 Dohodny dom Banige. Built in 1864. Photo: Dobrodeev.

corridor

Urban yards

By the end of the 18th century and the beginning of the 19th, “Dohodny Dom” has been built along the street border, precisely put into a slot. Firewalls were shut and window-less, so that it was possible to connect another house to it28 .

Fig.19 Street organisation. (Yuchneva 2019)

When it comes to courtyards, the O-shape was considered the most efficient (2nd type on the illustration below). The other two (1st and 3rd) were rarer, although their geometry allowed to place two rows of rooms in the courtyard. Usually space inside the yards was dedicated for technical rooms and sheds, however in order to fit in more of liveable area, landlords would ask to relocate utility rooms in the basement or in ground floor29 .

1st Type 2nd Type

3rd Type

Courtyard Types. (Yuchneva 2019)

Dohodny

Saint

Notes from historic

Fig.21 Urban configuration according to plot size. (Yuchneva 2019)

Type A - if the width of the plot was less than 20 meters, than one street block and one yard block were built.

Type B - if the width of the plot was less than 20 meters and the length was sufficient enough, than one street block and two yard blocks were built.

Type C - if the width of the plot was more than 20 meters, than a closed street block was built.

Type D - if the width of the plot was more than 20 meters, and the length was sufficient enough, than a double-closed street block was built.

Type E - if the width of the plot was more than 20 meters, and the length was sufficient enough, than a double-closed street block was built.

Fig.22 Merged rooms and corridor system. (Yuchneva 2019)

Apartment layouts

20m 30m 30m 50m corridor corridor

At first, all apartments were designed in palace-like manner - corridors were absent, all rooms would be connected to each other instead. In the second half of 18th century some serious changes have taken place; rooms became separated and corridor system was intro duced.

corridor

Fig.23 Scheme of courtyard block. (Yuchneva 2019)

The corridors first started to occur in big bedrooms and cabinets, later wards the other rooms followed. In 1880-s there were only apartments with separated rooms.

From free-form to a section

At the beginning all rooms in brick houses were built empty, with just plain bearing walls in side. Depending on the will and desire of the tenants the number of rooms could be adjusted by adding non-bearing walls. The same apartment could be rented as a single studio with two entrances; one for the guests and the other for the staff. The maximum number of the apart ments on one staircase was 4. The size of the apartment was defined by tenants as well.

Until the middle of 18th century the kitchens were placed randomly on each floor. With the introduction of sewage system and therefore toilets and kitchen sinks, the new arrangements took place: one block would be placed strictly one under the other. As the system developed, the regulations were becoming more and more strict.

kitchen kitchen

Fig.24 Comparison of free-form organisation with sectional one.

Houses built before 1850 Houses built after 1850

corridor corridor

corridor corridor

Fig.25 Apartment in Dohodny Dom (2019). Photo: Kosmin M.

Palaces to the working class

After break down of Russian Empire in 1917, the communist party took over the country and started the residential breakdown. There were two aspects, that predefined it: first, new government was in desperate need of supplying working class with living space, as people were moving to the big cities30. Sec ond, the communist party would emphasize the “loss” of middle class in Revolution, that they should pay off their residue31 .

With that, rapid measures were undertaken - Dohodny Dom’s were abolished and taken away from the landlords (nationalized). Work ers and their families could move into big apartments, but would be assigned with just one room; kitchen and bathroom had to be shared with others32. Those apartments later would be called Kommunalka's.

Practically the nationalization was per formed in the following way: all real estate was divided into equal parts, according to the newly established norm - 10 sq. Meters for adult and 5 sq. Meters for a child (2-12 years old). As of 1924, due to the rapidly growing number of citizens, the norm was reduced to 8 sq. m. per person, regarding the age33

For a short period of time in 1921, due to the disorganization of shared households, com munists tried to introduce a landlord system to Kommunalka’s back. That has improved the living conditions to some degree, but al ready in 1929 all the apartments were nation alized yet again34 .

1917

DOHODNY DOM

of Dohodny

KOMMUNALKA

apartment shown on the left is located in Moscow and can serve as a general example of communist reformations. Before the Revolution it was home of Ilya Pigit, where he lived together with his wife35 . Being the biggest apartment in the house with approx. 10 rooms, it was richly decorated and its windows would face the big street of Bolshaya Sadovaya

.

the early 1920-s the

was "tightened". In 1924 there were 14 neighbours registered, including nephews of Ilya Pigit himself).

1940 there were 35 neigh bours, in 1958 - 31 neigh bours

.

Classical communal apartment has lasted through the whole 20st century and pro ceeds to be an unfortunate reality in many Russian cities even today. A frequent com plaint for living in such an apartment is the lack of personal space38 .

Although there might seem to be some sim ilarities with other shared living concepts, e.g. German Wohngemeinshaft, the essen tial quality of Kommunalka is way they are owned: as a rule, each room belongs to the person who lives in it. That means, that in order to sell the whole apartment, all neigh bours have to cooperate, which is not always the case.

In 2017 there were about 76.600 Kommunal ka’s in Saint Petersburg. Since 2008, the city administration is taking measures in order to reform the apartments and offer the tenants a separate living space instead. So far, over the course of this program around 40000 apartments were successfully reorganized.

As the task remains rather challenging and requires a lot of investments, the city admin istration is planning to finish the program with a half of apartments reformed39 .

38 Kommersant, “Kommunars i Kommunarki”

39 Interfax, “In St Petersburg 245 thousand families are still living in Kommunalka's.”

Fig.31 Kommunalka in St Petersburg. Photo: Vesenin.

Fig.32 Celebration in Kommunalka, 1987. Photo: Lagranj.

Fig.33 Kommunalka in Moscow, 1992. Photo: Lagranj.

Fig.34 Kommunalka, 1992. Photo: Lagranj.

The history of market-based housing devel opment in Russia is relatively new; through out the 20st century the communist regime was predicating the human needs by esti mating areas, that would presumably suffice a regular person. Moreover, most of people were living in subsidized apartments, that they weren’t perceiving as their own40 .

However, as of 1992, the fall of the Soviet Union, the Russian Federation has adapted capitalist system, which meant a formation of a new real estate market. From this point, people could choose the most fitting apart ment for their own needs.

Regardless of this change, the buildings

technologies could not keep with rapid politi cal changes – many soviet norms and regula tions were still in use until 2000-s41 .

That being said, a brief analysis of last cen tury housing types was executed, as a lot of what is being built now, derives from the so viet household and regulations.

This period of real estate development could roughly be categorised by three typolo gies: Stalinka, Khrushchyovka and Brejnevka (each named after the Soviet party secretary of the time). The houses were pre-fabricat ed and their rapid construction was not least conditioned by demand of personal space from people living in Kommunalka's.

INDIVIDUAL HOUSES

"STALINKA"

"KHRUSHCHYOVKA" "BREJNEVKA" "NEW PANEL"

STALINKA

Apartments

1-room Apartments

rooms interconnected rooms

3m floor hight 2.5m floor hight

rooms

hight

Fig.39 A graph of real estate prices over the years in Saint Petersburg.

Market

The real estate market in St Petersburg is developing quite quickly.

The graph above demonstrates the growing prices throughout the last two years, that reflect the growing demand and purchasing capacity.

Naturally, there is a segregation based on the comfort class: in November 2017, around 80% of the constructed real estate were socalled “standard” and “comfort” class45. Those are characterized by rather small apartment size, with ranging planning features and material quality46 .

As the market grows, so does the diversity in apartment configurations. Some developers have shifted towards more personalised approach: person can choose the apartment according to his/her family status or occupation.

For instance, one could take the developer called "Legenda", that has made their

45 pwc.ru, “Marketing study of St Petersburg real estate.” (2018).

46 Gazeta.ru, “How to distinguish between real estate classes.”

47 LEGENDA, “English summary / LEGENDA Intelligent Development,”

48 LEGENDA Smart, “Layout catalog.”

apartment portfolio, based on approximate needs of social groups (e.g. single parent with one child, elderly couple and so on). It is claimed to be reflected in unit lay-out organization and room sizes47 .

In order to obtain an overview of current trends in contemporary Russian real estate development incl. the logic behind special organisation, the dataset of approx. 80 apartment layouts was analysed in the following Chapter . The focus of the study was to estimate the area values of each apartment and its rooms; connection occurrences inside the layout. The following data was then put into Excel list and categorised. Results of the study were afterwards illustrated in next Chapter48 (note: the figures in it were based on the source mentioned above; all illustrations were made by the author of the thesis).

M L

1-Bedroom

22.4 - 29.4 m2

Since 2000-s this configuration is quite popular on the market, although it is still being considered a rather uncomfortable option, due to the lack of privacy.

Advantages: - low price - functional usage of space - low maintenance costs

Downsides: - high noise levels - quick smell distribution - lack of privacy

* J-graph (Justified G) is a way to represent depth of a space as a node scheme. A chosen room is placed at the bottom,the others are arranged sequentially, based on the direct connections between them49 .

of space and its integration are both terms of Space Syntax Methodology,that would be later described in Chapter 7 ("Concept Tool")

Storage

Hall 3.4 - 4.7 m2

Washer

Hall is the main circulation centre of the apartment and it is usually equipped with a storage closet.

Number of direct connections: 3

Living room 100% Kitchen 25%

Bathroom 3.3 - 3.9 m2

Bathroom 100% Hall 100%

There is only one bathroom; the room is always connected to the hall

Number of direct connections: 1

Living room 10.1 - 21.3 m2

Number of direct connections: 2

Hall 100%

Kitchen (merged) 100%

In all cases, kitchen is merged with living room

Kitchen 5 - 5.6 m2

Living room (merged) 100%

Number of direct connections: 2

Hall 25%

MArea 32.9 - 52.7 m2

Relatively new option on the market, that first made an appearance in 2000-s. Living room and kitchen are combined, one bedroom is separated.

Advantages: - rational usage of space - lower cost, compared with standard multi-room apartments

Downsides: - smell distribution from the kitchen to the living room

Living room 7.2 - 27.9 m2

Hall 3.3 - 9.5 m2

Number of direct connections: 7

Toilet 27%

Bathroom 100% Hall 100%

Living room 100% Kitchen 54% Kitchen 100%

Bedroom 75% Bedroom 18%

Storage room 6% Cabinet 3%

Number of direct connections: 3

Hall

Living room

Private storage room 12%

Bedroom 8.4 - 17.5 m2

Number of direct connections: 4

Storage rooms can either be with public access or "private" (attached to the bedroom)

Storage room 1.8 - 4.8 m2

Bathroom 3%

Bathroom 2.8 - 5.3 m2

Hall 4.4 - 14.7 m2

Living room

10.6 - 31.6 m2

Number of direct connections: 7

Number of direct connections: 4

Toilet 51%

Living room 100% Kitchen 28%

Master bedroom 96%

Bathroom 100% Hall 100%

Storage room 27%

Kitchen 100%

Master bedroom 17%

Secondary bedroom 78% Secondary bedroom 13%

Master Bedroom

9 - 16.4 m2

Secondary Bedroom

8.9 - 15.8 m2

Hall 100%

Storage room 12% Private Bathroom 30%

Number of direct connections: 3

Hall 75% Living room 13% Private Bathroom 11% Storage room 6%

Number of direct connections: 4

in 50% of the apartments there is an additional WC (public or private)

Bathroom

8.9 - 15.8 m2

Number of direct connections: 3

Hall 100% Bedroom 1 30% Bedroom 2 11%

Room Proportions

Aside from room functionality and size, another considerable aspect of room configuration is its proportions. The list below shows approximate ratios of all rooms in the dataset (regarding the usage).

law regulations

The legislation system of Russian Federation in the area of building production is controlled land-wise by (ordered by legal influence): international laws, ratified by Russian Federation; Constitution on Russian Federation; Codes ; Federal laws

The federal law n. 384 "Technical Regulation of safety in buildings and structures” is giv ing outlines of general technical and safety requirements to be followed across the country. Based on that, Ministry of Construction is then responsible to assemble documents of de tailed technical regulations, called “SP” or “SNiP”

.

The process of building and renovation of residential dwellings lower than 75 meters is reg ulated through the SP 54.13330.2011

. This set of regulations includes the information about the regulations concerning inner floor plan organisation, such as minimal length of fire es capes; elevator equipment; minimal areas of rooms in the apartments (next page).

Fire escape corridors

width of a corridor should be no less than 1.4 m.

to the estimated fire-resistance class of historical buildings, the distance for fire escapes equals 25 meters, if it leads to firewall (Fig.); 40 meters, if it leads to a staircase (Fig.).

Elevators

building

than 5 stories

be equipped with an

m

1-room apartment and studios

kitchen: kitchen: kitchen as part of a dining room:

living room: living room: bedroom:

≥ 6 sq.m. ≥ 8 sq.m. ≥ 6 sq.m.

≥ 14 sq.m. ≥ 16 sq.m. ≥ 9 sq.m.

2-room apartment and upwards

*Room proportions are set according to the needs and furniture arrangement.

Sunlight Supply

Federal Law n.52 “Sanitary and epidemiological wellbeing of the population” sets the guide lines for technical regulations in the field of healthcare.

The document that regulates sunlight supply is called SANPIN 2.2.1/2.1.1.1076-01 “Hygienic requirements for sunlight supply and solar protection of public and residential buildings”53 . The sunlight requirement in Russia is estimated by how many sunlit hours a liveable room obtains per day (e.g. living room, bedroom). This document provides estimations land-wise, differentiating by latitude of the area.

St. Petersburg’s position on a latitude of ca. 60° N, what puts it into the following category of sunlight regulation:

- no less than 2.5 hours of sunlight supply per day in a time period from 22 April to 22 August. - a break (no longer than 1 hour) in a sunlight period is allowed; in that case additional 0.5 hour is requested from all sunlight periods.

rooms

more

Cultural heritage

Cultural heritage in St Petersburg is regulated through Federal Law N.73 “Objects of cultural heritage (monuments of history and culture) of Russian Federation”. It requires a division of the city into zones with various level of heritage protection. The zones and regulations, ap plied for each zone are then provided by Local Law of Saint Petersburg N.82054 .

In order to proceed with renovation design of the building, the zone has to be identified.

Additionally, the house can belong to the list of protected buildings in Saint Petersburg55 .

In that case, the renovation proposal has to undergo an independent expertise, that would conclude the correspondence of the project with law regulations. Therefore, only general outlines can be illustrated in this Chapter. As mentioned before, each house and legislation categories that it falls into, have to be investigated individually. Based on the sources above, some general traits could be identified:

1. Historic look of street façade, changes of inner structure (e.g. bearing walls), windows openings in firewalls – in most cases have to be approved by an expertise.

2. Non bearing walls, restoration works of engineering communications can be accom plished without an expertise.

Usually require expertise:

street facade bearing walls windows openings

Usually do not require expertise:

non-bearing walls engineering

SPACE REFILLED

dohodny dom

demolish reuse

+ new buildings can be built, that would meet modern efficiency standards

+ construction process can be controlled more precisely

+ less energy waste then new construction

+ economically advantageous

+ keeping cultural value

+ improving urban fabric and empowering community

Future trend

Re-adapting historic buildings is somewhat of a paradox, as it cares for the timeless, while trying to adjust to today's needs. It’s inevitable that structures will age and outgrow their original functions.

With changes in technology and lifestyle, construction and de sign are constantly updated to meet modern demands, and older structures are left in the wake of change. An alternate concept is “adaptive reuse” a process transforming heritage buildings into accessible and usable places as well as provide the added bene fit of regenerating an area in a sustainable manner56 .

Potential Candidate

Dohodny Dom, due to its influential, yet poorly maintained presence in Saint Petersburg can serve as a "playground" for new development strategies. Different areas of the city request dif ferent solutions, therefore it is implied that the reuse concept would contain various usage possibilities. However in the scope of this paper, the residential function would be a main redevel opment focus.

hybrid dom

56 P.A. Bullen and P.E.D. Love, Adaptive reuse of heritage buildings: Sustaining an icon or eyesore.

Loss of innocence

In his highly influential book “Notes on the Synthesis of Form”, C. Alexander compares the ability of an individual to design with their ability to resolve mathematical problems57. There is a cer tain limit to what can be figured in mind; as the difficulty of a problem arises, so does the need of a human in supporting tools. On the other hand, design problems of different scales are still being considered as something that a human mind can solve un supported. Reaching to more holistic approach, where design tasks could be examined analytically and decisions made are based on logical arguments, is the way dealing with modern era problematic.

"The use of logical structures to represent design problems has an important consequence . It brings with it the loss of innocence. A logical picture is easier to criticize than a vague picture since the assumptions it is based on are brought out into the open. "

- "Notes on the Synthesis of Form", C. Alexander

Wicked problem

Among many duties of an architect, floor plan design in its ear ly stages is a dive into the unknown. There are many aspects to consider at the same time (e.g. sunlight, area distribution, law regulations and so on), which raise the complexity of a task. Such problems that don't have clear goal definitions, have no stopping rule and therefore can not be solved linearly (true or false result) are defined as wicked58 .

One of the way to deal with such problems would be a rather homogeneous approach of considering many options at once and interfering into problem model itself59. With introduction of computational "processing efficiency and tirelessness"60, those methods could be executed with a help of a machine.

Alexander C, Notes on the Synthesis of From.

Rittel H.W., “Planning Problems

Arvin S.A., “Making Designs

Kalay,

media.

Problems,”

Physically

Applying automation to reuse

When it comes to the specific case of reusing Dohodny Dom in St Petersburg, the advan tages of automation and computer support could play a big role it the process of general revitalisation of a historical core. The analysis would be performed more objectively and out come data can be stored, compared and evaluated. The overall time consumption of design process could be reduced, making it more sustainable, as it would require less energy and money investments.

Last but not least, automation of tedious, time consuming processes (e.g. sunlight analysis) would enable architects to focus on more challenging tasks. As the architect is presented with additional information, he/she can make more weighted choices, overcoming a cocalled "design fixation" - a state when a designer is set on one thought or approach and is not able to see past his/her initial assumptions.

Computer support

Architect

Objectivity

AdjustabilityTime efficiency

Entering the competition

All of the above can make an impact in the competitive world of city's development. Un doubtedly, reuse projects would remain highly complicated task of many aspects (e.g. actual building works, often times affected by discovering structural problems in the building).

It is also reasonable to believe, that this field of building industry might never be able to keep up with economical profit or revenue speed of cheap construction of high-rise blocks in the periphery. That being said, even small steps towards speeding up the early stages of design could attract potential investors. An abandoned building could be seen as a potential, rather than a obstacle.

Overview of Supportive Generation

Over the last decades, a lot of progress has been made towards supporting floor plan design process. One of the first examples would be attempts to program more efficient production facilities. In that case, the space allocation is performed in order to fulfill objectively mea sured criteria (e.g. cost minimization)

those steps, architects started trying to further develop methods, that would work with automated space organisation. For over the 50 years of development, several ap proaches could be highlighted:

Grammar (Stiny, Gips)

Shape grammar is a set of rules, that is applied recursively to a geometrical form with a help of geometrical transformations. The objects can vary in types (e.g. points, lines or polygons). The list of transformations is diverse as well: the object can be mirrored, subtracted, added or rotated.

(Kalay 2004)

Expert Systems (Flemming, Coyne) 1988

This method introduces systematic exploration of alternative solutions for a design prob lem, by changing a given layout. Essentially it operates through situation rules, or if - then conditions. Expert system is a collection of possible scenarios, through applying which new combinations can be produced.

Constraint-Based (Li, Frazer, Tang) 2000

method focuses on a constraint based system: non-linear way of programming, that opts to satisfy as many pre-set constraints as possible. Design constrains are divided into dimensional constrains

of each block or room; their placement is de fined by room’s

Genetic Engeneering Approach (Gero, Kazakov) 1999

method is based on Genetic Algorithm

that was introducing evolutionary inheritance of genes. This idea implies creation of complex genes (or evolved genes) from basic input genes. Afterwards, the process of evaluating the resulting genes is performed, according to the fitness function. This function is aimed to reward individuals, based on their correspondence to desired outcome.

Dense packing and subdivision (Koenig, Knecht, Schneider), 2012

of the

the

is a KREMLAS project

. There various

The first one operates

that allows to divide rectan gular

generated division would then be optimized with multi-criteria

smaller

The aim of dense packing is to organize

plan with pre-set room program, without over lapping/leaving empty holes. This method makes it possible to change/swap room programs.

Parcelling (Kaisersrot) 2000

'Kaisersrot' is a project aimed at incorporating the capabilities of computer programming into the design of urban plans. The aim was to create a bottom-up generation of urban lay outs, formed by wishes and demands of citizens allowing them to interact with a result. Start ing with the point distribution (assigned to plots), after user approval they would be trans formed into mesh, creating streets outlines by manipulating their borders.

Metis (Eisenstadt V., Langenhan C., Althoff K., Petzold F., Bukhari S., Dengel), 2016

This approach is dealing with early stages of design, where architect is being supported with a “knowledge base” of similar building models. The database is first analysed and then inter preted as various retrievable cases (either rule-based of case-based reasoning can be ap plied). Architect inputs his/her query in a form of semantic fingerprint – a way of representing floor plan meta data.

Braach,

Eisenstadt

Langenhan

Althoff K., Petzold F., Bukhari S., Dengel A., “Thinking With

Retrieval Approach for the Case-

Semantic Search of Architectural Designs” (2016).

tool

The concept toolbox is considered to be made as an extension to Grasshopper 3D (plug-in to Rhinoserous 6.0).

The software offers various advantages:

- general familiarity of designers with Rhinoserous and its simple interface;

- open source plug-ins base (FoodForRhino); - capability of integration with other software;

Preparation

When considering a building for adaptive reuse it is essential to examine the following issues69:

- building’s structural layout and its capacity to accommodate required spaces and functions;

- energy efficiency of the building’s walls, windows and roof;

- building’s potential for meeting building, heath, safety and accessibility requirements;

- condition of mechanical, plumbing and electrical systems and their capacity for modification;

- the presence of hazardous materials;

- ability of the building and site to provide a safe and secure environment;

- convenience and safety of the building’s location.

In this project it is implied that the steps above have been considered beforehand; the tool operates solely on the early stages of design.

Rhinoserous 6.0 Grasshopper 3D

69 Love P.E.D. Bullen P.A., “Adaptive reuse of heritage buildings: Sustaining an icon or eyesore” (2011).

In order to obtain meaningful results, it is necessary to sample a large number of cases and to consider as many criteria as possible. The latter is motivated by the fact that one cannot know in advance which criteria are most important for certain research ques tions as well as an awareness that the com plexity of the environment and the human cognitive process is such that the majority of phenomena we are examining is the result of multiple variables acting simultaneously70 .

Lobos separates design criteria into two main categories: rational and general. While rational criteria are measurable, general cri teria are more abstract and unmeasurable71 .

Further categorisation is introduced in this project: similarly, the division into measur able (law and architect's criteria group) and unmeasurable (subjective perception crite ria group). As one can hardly object law reg ulations, their nature is more linear; on the other hand, goals set by architect are often interchangeable and can be ordered by mat ter of influence on the design. Strictly speak ing, they are prone to be iterative and can be optimized towards one of multiple criteria of choice. Subjective perception is different for every individual and can not be put into any kind of measurement systems, therefore can not be programmed.

Tool structure

The tool is designed to perform support ive analysis on 4 different scales: city, floor plan, area of planning and apartment. For each step the evaluation criteria of either Law or Architect group is being executed. That means, every criteria of both groups is a separate case, that has to be implemented according to the task. The set of cases was chosen by the author and is arbitrary.

Additional criteria could be considered on every scale, such as: connections to the pub lic transport, local supply of retail and com merce on the city level; section width and glazing percentage on the floor plan level; corridor length and low-mobility access on the section level; outside views and heat ing/cooling demand on the apartment level; moreover, some criteria are interchangeable and could be applied to several levels at once.

On the following pages the description of proposed evaluation criteria is presented, alongside with potential script definitions for an analysis.

house in urban context

// Evaluation: -context based sunlight supply calculations

FLOOR PLAN

story

house

// Evaluation: -elevators request -fire escape distance

// Evaluation: - number of apartments to fit into planning area

// Evaluation - room daylight factor - room connectivity - room integration - room area - room proportionsm²

Sunlight supply is an important step in a process of residential development, as it is being strictly regulated by law.

This is an analysis step executed in urban scale, with regard to the surrounding context. It would estimate parts of a building, that are performing well according to the Russian law (Chapter 5, "Law Regulations"). That way, areas that are not suitable for dwellings, would be marked as red (less than 1.5 hours of sunlight supply); areas with reduced supply would be marked yellow (more than 1.5 hours, but less than 2.5 hours of sunlight supply); areas, suitable for the design, would be marked green.

Evaluation example:

Urban context sunlight analysis

Floor plan adjustment

Fire escapes. As mentioned in the Chapter 5 ("Law Regulations"), fire escapes are measured through the distance between fire-proof staircase and firewall. If the distance exceeds the length set by law, then the area is not suitable for planning dwellings inside it.

distance ≤ 25m

distance ≥ 25m

Similarly, elevators are to be put in every floor plan, where the height of the building exceeds 5 stories. Dimensions of elevator cabins can vary and are listed below:

hight ≤ 5 stories

m 1.9 m

m 2.2 m

≥ 5 stories

Fig.58 Fig.59

number is understood as the number of dwellings of desired size would be able to fit into selected section of a floor plan, the borders of which have to be defined by the user.

OUTSIDE GENERATION PROCESS

INSIDE GENERATION PROCESS

Using the dataset in Chapter 4 ("Apartment Story"), we retrieve approximate area domains of the dwellings - S, N or L. For a chosen section, staircases, bearing walls and window openings need to be excluded from calculation. After making sure, that the fire escape corridor (min. 1.4 m wide) is placed into the planning area, one can proceed with the analysis.

AREA

value for

area

1. Daylight factor describes the ratio of outside illuminance over inside illuminance, ex pressed in percent72. The higher the DF, the more natural light is available in the room. The outcome measurements are compared with architect's ranking. In this project the sun light request of each room is ordered as following:

Sunlight requirements by room

Rooms with an average DF of 2% are considered day-lit. However, a room is only perceived as well day-lit when the DF is above 5%. Daylight factors are always measured under an over cast sky or in an artificial sky which simulates a standard CIE overcast sky.

Evaluation example:

DF values of each room are calculated;

Values are compared to architect's requirement (listed above);

Comparison is summed and put into scale;

DF = 0.1%

= 1%

= 10%

DF>2% = 0%

outcome value

deviation from preferred domain

DF>2% = 40%

Smaller deviation from preferred domain

Connectivity is a measure, used in Space Syntax method73, that indicates the amount of direct connections to a specific room. The room analysis operates on so-called "convex spac es" - no line between any of its points crosses the perimeter of the space.

First, number of points between rooms are counted. If there is only one point of the border of two spaces, they are considered to be connected (resulting as true values); if there is two of more - they are not (resulting as false values). Each room now has a number of direct connec tions, that can then be compared with a dataset of desired connections in Chapter 4 ("Apart ment Story").

Apartment

hall - living room = 1 (true) hall - bathroom = 1 (true)

example: hall - living room = 1 (true) hall - bathroom = 0 (false)- no connection

Number of direct connections: 2

living room

B

Number of direct connections: 1

bathroom

roomhall

hall

deviation from

domain

3. Room integration, alongside with connectivity, is another Space Syntax term. This meas ure, however, is called "global", as it represents how central each room is inside an apart ment74. Rooms can then be ranked as most integrated and most segregated. The outcome can be compared with desired integration ranks. Those can be obtained through analysis in Chapter 4 ("Apartment Story"), or assigned manually.

First, Mean Depth (MDepth) is estimated by assigning a depth value to each space according to how many spaces it is away from the original space, summing these values and dividing by the number of spaces in the system less one (the original space). Then, by putting the values into the formula of relative asymmetry, one can measure integration75: where k is the number of nodes (rooms) in a system. The values would be in a range from 0 to 1, where 0 is most integrated and 1 is least integrated room.

Evaluation example:

B

R asymmetry = 2*(MDepth-1) k-2

D

d a = 1+1+1 = 3 db = 1+2+2 = 5 d c = 1+2+2 = 5 dd = 1+2+2 = 5

MDeptha = 3/(4-1) = 1 MDepthb = 5/(4-1) = 1.6 MDepthc = 5/(4-1) = 1.6 MDepthd = 5/(4-1) = 1.6

Int a = 2*(2*0)/4-2 = 0 - the most integrated Intb = 2*(1.6*-1)/4-2 = 0.6 Int c = 2*(1.6*-1)/4-2 = 0.6 Intd = 2*(1.6*-1)/4-2 = 0.6

4.

are represented in a

approximate

that

Story") as well. For each room there is

is to be measured and

5. Proportions are understood as a relation of the longest side of the room to a shortest one.

is to be meas ured

study

ZAGORODNIY PROSPEKT

House: Dom Zelibeeva Year built: 1904 Address: Serpuhovskaya st.2 Height: 5 stories

The house was built in 1847 in a part of the city called Sementzy76. Back then it was an area where the soldiers would complete their seasonal military service. Later wards the area became more marginalized and crime levels went up. In 1904 the house was purchased by Nicolay Zelibeev (hence the new name) and rebuilt in art deco style.

After being rented out as Dohodny Dom for a few years, it was transformed into first Polytechnical school for women in the city with around 800 students. There were several faculties: architectural, engineering, chemical and electro-mechanical. After the Resolution the School continued to function

for some time, but in 1924 it was eventually closed. The house has served as a student dormitory for some time, with consequential reformation into Kommunalka's (with 30 apartments in total).

Today

From 2000-s the building was in the center of public's eye, as it was falsely considered "unrepairable" and were planned to be demolished. After many petitions and new historical expertise, the status was dismissed. At the moment the house is being a part of government sponsored program "Affordable housing for the Youth”.

DOHODNY DOM ZELiBEEVA built: 1847; rebuilt:1904 (arch. Shirshov)

76 Protective Peterburg, “Dom Zelibeeva: from from schoolgirls to young mothers.”

Evaluation Criteria, described in the Chapter 7 (“Concept Tool”) are forming a theoretical basis for a prototype toolbox, showcased in this Chapter. As mentioned before, each criteria represents a separate Case.

Design Pattern methodology77 proposes that one solution pattern can be utilized for solving countless problems of the same type. Similarly, the Cases in the toolbox are offering analysis execution for a specific task in a script form.

Following the logic of the Evaluation Circle (p. 65), Cases are first organized according to evaluation group (either Law or Architect); that are then sequentially ordered in a scale system, introduced on page 66.

The inner structure of the tool builds up as follows: each Case is assigned with a card (p.82-99), that provides a short information about the result of script performance, inputs from the architect and the eventual outputs. Additionally, the cards shortly describe the evaluation criteria it is set to execute, alongside with a depiction of a working script.

Cases are thought to provide supportive expertise for architects, working on the early design stages in the field of re-use. Currently, Cases are not connected with each other; however, there is a potential to extend the prototype into generative tool, that would focus on optimizing one or multiple criteria from the list.

77 Alexander, Ishikawa, and Silverstein, A pattern language, vol.2.

As mentioned on p. 63, the tool in this project is made in Grasshopper 3D and operates within its terminology. Essentially, Grasshopper is a node-based visual program language, where a user can navigate through different operators; by connecting them to each other, a script sequence is built. Each operator requires specific input data in order to produce desired outputs. Below are some basic inputs, needed for the concept toolbox.

Represents a referenced open Rhino surface.

surface (srf)

Represents a referenced closed Rhino surface - an object made from open surfaces.

closed poly-surface (brep) curve (crv)

List Domain

Represents a referenced Rhino polyline. In this tool all the curves must be kept planar(XY)

Represents a list of numeric values, ratios, domains.

Represents minimum and maximum numeric boundaries of values (e.g. room area ratios)

Additional plug-ins, used in the tool: Human, Human UI, DeCodingSpaces Toolbox, Heterop tera, Pufferfish, Treesloth, Chingree, SYNTACTIC, LadyBug, HoneyBee.

SCRIPT RESULT

CRITERIA

INPUTS

OF

GROUP

EVALUATION DESCRIPTION SCRIPT

SUNLIGHT SUPPLY

selected building envelope (srf)

surrounding buildings - incl. selected house, closed poly srf(brep)

location (latitude)

LAW CRITERIA

size of the analysed cells (value)

LUCIOLA Grasshopper plug-in (A. Anishchenko).

The extension was made specifically for calculating sunlight supply according to the Russian law. The user picks house to analyse, surrounding buildings, picks a latitude, sets the size of analysis cells; the script then calculates number of hours each cell is being exposed to direct solar rays in one day.

Note:"Human" and "Human UI" plug-ins have to be installed in order for script to run.

Surfaces of building envelope with overlaid calculated cells.

to Russian law, residential dwellings can only be planned in green/yellow zone of the building.

LAW CRITERIA

ELEVATOR REQUEST staircases (crv)

number of stories in a building (value)

Custom-made Grasshopper definition that places elevators on each staircase,if the building is higher that 5 stories; user can control the position and size of the elevators.

Floor plan with installed elevators.

hight

CRITERIA

hight

stories

LAW CRITERIA

ESCAPES

staircases (crv)

sections (crv) sections'longest sides(crv)

Custom-made Grasshopper definition that calculates distances between each firewall and staircase (fire exit) by creating a centreline of the section; their positions can be manipulated by the user. Distances, that meet the regulations are marked as green, the areas that surpass required distance are marked as red.

lengths between fire escapes and firewalls.

LAW CRITERIA

ARCHITECT CRITERIA

APARTMENT NUMBER

staircases (crv) bearing walls(crv) windows (crv) area ratios (domain) section (crv)

Custom-made Grasshopper definition that estimates possible apartment placement in a specified section. User inputs desired apartment area ratios (S,M and L), then an evolutionary algorithm (Galapagos) optimises their placement inside an adjustable grid. For achieving better results, sub-goals can be added: reduction of unused space and direct connection of apartments to the corridors.

Section divided into apartments via input ratios.

S S S S M

MML

bath bath 0% hall hall 0% kitchen kitchen 0%

living room

living room 14.7%

ARCHITECT CRITERIA weather file .epw rooms (3D-volume) windows (surfaces)

DF preferences for each room (list)

Customized Honey Bee Definition (based on "Honeybee Grid-based Daylight Simulation Example I"; hydrashare.github.io); the script operates with 3d volumes, calculating DF values for each room. Then the values are to be compared with preferred ones for each room.

Measured % of DF for each room; deviation from desired dataset. Fig.84

ARCHITECT CRITERIA

Example Sunlight requirements by room

Room with more than 2% Daylight Factor can be considered day-lit.

Larger deviation from preferred values

outcome value MAX MIN

Smaller deviation from preferred values

Fig.85

ARCHITECT CRITERIA

bathhall kitchen

Connectivity:

Hall - 2 connections Bathroom - 2 connections (Deviation:1)

Living room - 3 connections (Deviation:1)

Kitchen - 1 connectionliving room

preferred connections (list) apartment outline (crv) rooms (crv)

Custom-made Grasshopper definition that calculates the number of connections for each room in selected apartment (S,M or L) and then compares them to the dataset from the user (either based on the data in "Apartment Story" or his/her own preferences).

Measured number of connections for each room; deviation from preferred dataset.

ARCHITECT CRITERIA

Example room domain: 2 -

connections Result: 0 deviation

Number of connections: 2

Larger deviation from preferred values

outcome value MAX MIN

Smaller deviation from preferred values

INTEGRATION

bathhall kitchen

living room

ARCHITECT CRITERIA

Integration: Hall: 0 - the most integrated Bath: 0.6

Living room: 0 - the most integrated Kitchen: 0.6

preferred integration for each room (list) apartment outline(crv) rooms (crv)

Custom-made Grasshopper definition, that utilizes SYNTACTIC extension for Grasshopper (created by Pirouz Nourian) for the calculation of integration values of each room. The values are then compared with preferred integration order from the user (e.g. hall might be the most integrated, whereas bathroom can be the most segregated).

Measured integrations for each room; deviation from preferred values.

bathhall kitchen

Room areas: Hall: 2.85 m Bath: 3.42 m

ARCHITECT CRITERIA

living room

Living room: 17.1 m Kitchen: 5.1 m

area ratios (domain) apartment outline(crv) rooms (crv)

Custom-made Grasshopper definition that calculates the areas of each room and compares it to a dataset of desired area range, returning the absolute difference (deviation).

Area values for each room in an apartment and their deviation from the dataset.

ARCHITECT CRITERIA

area domain {from x to y}

larger deviation smaller deviation

outcome value

Larger deviation from preferred domain

MAX MIN

Smaller deviation from preferred domain

ROOM PROPORTIONS

bathhall kitchen

living room

ARCHITECT CRITERIA proportions ratios (domain) apartment outline(crv) rooms (crv)

Room proportions: Hall: 2.12 Bath: 1.7 Living room: 0.79 Kitchen: 1.17

Custom-made Grasshopper definition that calculates proportions of each room and compares it to a dataset of desired proportions range, returning the absolute difference (deviation).

Proportion ratio values for each room in an apartment and their deviation from the dataset.

ARCHITECT CRITERIA

proportion domain {from x to y}

larger deviation smaller deviation

outcome value

Larger deviation from preferred domain

MAX MIN

Smaller deviation from preferred domain

The concept, studied in this thesis sets a general direction for systematic approach to adaptive reuse. The goal was to illustrate the need of technological advancement in the field, that could be valuable in foreseeable future.

That being said, computer support in solving complicated tasks like building renovation is essential.

The prototype, presented in thesis offers an analysis of several aspects of Dohodny Dom, that were considered important by the author of the thesis; the selection of evaluation parameters is therefore arbitrary. It is reasonable to believe, that each following design outcome, made with said tool, is directly correlated to the program definition.

The evaluation process is also highly influenced by a dataset, gathered in the study. It applies to some cases more, than to the others – e.g. law regulations usually form a direct set of measured constraints. The dataset in Chapter 4 “Apartment Story” is more arbitrary, as it offers constraints, that are not finite and could be discussed (or neglected) by other architects. On the other hand, said data is not built-in directly into the tool; user can input his/ her own preferred variables. Concerning the tool itself, there is definitely room for improvement in terms of scripts’ efficiency – however, they mainly serve an illustrational purpose. It is implied, that

programming assistance for the future development could help expanding the functionality of the prototype. Other aspect, observed in the process of creation of the prototype, was the degree of automation, that is required for floor plan creation. Should computer involvement go as far as performing fully automated generation of potential options to choose from, or should it remain a supportive analytical feature for manual design?78

In the case of Dohodny Dom, automated generation might be applicable in some cases, but rather as an option, than a necessary requirement. Every house is very different from the other, what amplifies the importance of architect involvement and expertise.

Summing up, the experience of working on this thesis was therefore valuable, as it allowed to observe a complex process of space planning through a lens of computer logic. Transferring components of design process to a machine helps to break down one’s unconscious or intuitive decisions. It is reasonable to believe, that future holds further technological advancements, varying in approaches. Testing and tailoring them to support the design process can bring new opportunities and insights for the architects;that way they could embrace their creativity and focus on problematics, unsolvable in the past.

Daniel Davis,”

Note: Sources' names in Russian language have been translated into English by the author.

Figure 1: Map of St Petersburg. (MLA+, “Undiscovered St. Petersburg.”), edited by the author. 9

Figure 2: Illustration of statistical data (Petrostat, “Demographics: Petrostat). 10

Figure 3: "Severnaya Dolina". (Varlamov, “New districts of St Petersburg - would you like to live like that?,”) 11

Figure 4: Illustration by the author. 12

Figure 5: Density comparison between city centre and periphery. Illustration and calculations by the author.13

Figure 6: Illustration by the author. 14

Figure 7: Locals on "Hug Telejnaya street" flash mob, Feb 2019 (Protective Peterburg) 15

Figure 8: Construction works on Telejnaya street, Jan 2020 (Photo taken by the author) 16

Figure 9: Otkritiy Gorod. URL: https://xn--c1acndtdamdoc1ib.xn--p1ai/ 18

Figure 10: Citywalls.URL: http://www.citywalls.ru/house901.html?highlight=%E1%E0 18

Figure 11: Kanoner 2019. URL:http://kanoner.com/2019/12/20/164775/ 18

Figure 12: kleinwelt architekten, “Architecture of Dohodny Dom in Moscow at the beginning of 20st Century,”URL: http://kleinewelt.ru/dohodny_dom 19

Figure 13: Illustration by the author. 20

Figure 14: Dohodny Dom typical section. Shumilov P. Anatomy of Peterburg. 2009. 22

Figure 15: kleinwelt architekten, “Architecture of Dohodny Dom in Moscow at the beginning of 20st Century,” URL: http://kleinewelt.ru/dohodny_dom 23

Figure 16: Dohodny dom Lyshnevskogo. URL: http://dohodnyedoma.ru/dohodnyj-dom-lishnevskogo-2/ 24

Figure 17: Dohodny dom Banige. http://dohodnyedoma.ru/dohodnyj-dom-banige/ 24

Figure 18: Dohodny dom Dyrenkova. http://dohodnyedoma.ru/dohodnyj-dom-dyrenkova/ 24

Figure 19: Yuchneva E., Dohodny Dom's of Saint Petersburg. Notes from historic houshold.Edited by the author25

Figure 20: Yuchneva E., Dohodny Dom's of Saint Petersburg. Notes from historic houshold.Edited by the author 25

Figure 21: Urban configuration according to plot size. Yuchneva E., Dohodny Dom's of Saint Petersburg. Notes from historic houshold. Edited by the author 25

Figure 22: Merged rooms and corridor system. Yuchneva E., Dohodny Dom's of Saint Petersburg. Notes from histor ic houshold. Edited by the author 25

Figure 23: Scheme of courtyard block. Merged rooms and corridor system. Yuchneva E., Dohodny Dom's of Saint Petersburg. Notes from historic houshold. Edited by the author 26

Figure 24: Yuchneva E., Dohodny Dom's of Saint Petersburg. Notes from historic houshold. Edited by the author. Illustration by the author. 26

Figure 25: Apartment in Dohodny Dom (2019). URL: https://www.instagram.com/maax_sf/ 27

Figure 26: Apartment in Dohodny Dom (2019). URL: https://www.instagram.com/maax_sf/ 28

Figure 27: Apartment in Dohodny Dom (2019). URL: https://www.instagram.com/maax_sf/ 28

Figure 28: Transformation of Dohodny Dom into Kommunalka's after the Revolution of 1917. Illustration by the author. 28

Figure 29: Plan of the apartment N.5 on Bolshaya Sadovaya str. (Moscow) before Revolution. Bulgakov Musem. URL: http://dom10.bulgakovmuseum.ru/photo/akvarelnye-risunki-intererov-kvartiry-5/ 29

Figure 30: Plan of the apartment N.5 on Bolshaya Sadovaya str. (Moscow) in 1950-60s. Arzamas. URL: https://arzamas.academy/materials/597 30

Figure 31: Kommunalka in St Petersburg. Photo: Vesenin 2015. URL: https://vezenin.livejournal. com/344551.html 30

Figure 32: Celebration in Kommunalka, 1987. Photo: Lagranj. Arzamas. URL: https://arzamas.academy/ materials/594 31

Figure 33: Kommunalka in Moscow, 1992 . Photo: Lagranj. Arzamas. URL: https://arzamas.academy/ materials/594 32

Figure 34: Celebration in Kommunalka, 1987. Photo: Lagranj. Arzamas. URL: https://arzamas.academy/ materials/594 32

Figure 35: Serial Housing by type (proportionate illustration of houses built); edited by author. Delovoy Peterburg 2017. URL: https://www.dp.ru/a/2017/04/07/Kak_zastraivalsja_Peterburg 32

Figure 36: Stalinka; Type II-03. Edited by author. URL: http://advancerealty.ru/stalinskie/sacb/ 34

Figure 37: Khrushchyovka;Type 1-464. Edited by author. URL: http://a-h.by/s153/archives/Hruwevki._Opisanie_i_ti povye_planirovki.html 35

Figure 38: Brejnevka;Type II-18; URL: https://www.tipdoc.ru/catalog/24784/1577272/ 35

Figure 39: Real estate prices over the years in Saint Petersburg. BN. URL: https://www.bn.ru/analytics/ 35

Figure 40: A graph of real estate prices over the years in Saint Petersburg. 36

Figure

Figure

Figure

Figure

Figure

Figure

Illustration by the author.

Illustration by the author.

Illustration by the author.

Illustration by the author.

Illustration by the author.

Illustration by the author.

Transformation rules, initial shapes and transformations that can be used to generate floor plan ele ments. Edited by the author. Kalay, Architecture's new media.

Figure

Figure 48: LOOS program. Alterations on the room shape results in different arrangement of fixtures according to situation rules. Edited by the author. Kalay, Architecture's new media.

Figure 49: Optimisation of a geometrical constraint. Edited by the author. Li S., Frazer J.H., Tang M., “A Constraint Based Generative System for Floor Layouts”. 59

Figure 50: Illustration by the author, based on: Gero J., Kazakov V. "Design knowledge acquisition and re-use using genetic engineering-based genetic algorithms" 2001.

Figure 51: Koenig R., Knecht K., Schneider S. KREMLAS. Illustration edited by the author.

Figure 52: Koenig R., Knecht K., Schneider S. KREMLAS. Illustration edited by the author. 60

Figure 53: Parcelling layout. Screenshots from URL: https://youtu.be/Zw7_JFHi5hk 61

Figure 54: Rhinoserous 6.0 and Grasshopper 3D logos. 61

Figure 55: Evaluation circle. Illustration by the author. 63

Figure 56: Scala of evaluation. Illustration by the author. 65

Figure 57: Sun supply evaluation. Illustration by the author. 66

Figure 58: Fire exit distance evaluation. Illustration by the author. 67

Figure 59: Elevator request evaluation. ISO 4190-1:2010. Illustration edited by the author. URL: http://docs.cntd.ru/ document/1200135770 68

Figure 60: Generation constrains for estimating Apartment number. Illustration by the author. 68

Figure 61: Apartment number evaluation. Illustration by the author. 69

Figure 62: Sunlight requirements by room. Ordered and illustrated by author. 69

Figure 63: Daylight evaluation. Illustration edited by the author. Mardaljevic J., "Daylight, Indoor Illumination, and Human Behavior" 2012. 70

Figure 64: Connectivity evaluation. Illustration by the author. 70

Figure 65: Integration evaluation. Illustration by the author. 71

Figure 66: Room areas evaluation. Illustration by the author. 72

Figure 67: Room proportions evaluation. Illustration by the author. 73

Figure 68: Schematic site layout of Case Study house surroundings. Illustration by the author. 74

Figure 69: Dohodny Dom Zelibeeva. Photo taken by the author. January 2020 75

Figure 70: Dohodny Dom Zelibeeva. Photo taken by the author. January 2020 76

Figure 71: Dohodny Dom Zelibeeva. Photo taken by the author. January 2020 76

Figure 72: Dohodny Dom Zelibeeva. Photo taken by the author. January 2020 76

Figure 73: Dohodny Dom Zelibeeva. Photo taken by the author. January 2020 77

Figure 74: Inputs glossar. Illustration by the author. 79

Figure 75: Schematic layout of concept tool. Illustration by the author. 80

Figure 76: Sunlight supply case. Illustration by the author. 82

Figure 77: Screenshot of the script interface. ( LUCIOLA) 83

Figure 78: Elevator request case. Illustration by the author. 84

Figure 79: Screenshot of the script interface. 85

Figure 80: Fire Escapes Case. Illustration by the author. 86

Figure 81: Screenshot of the script interface. 87

Figure 82: Apartment Number Case. Illustration by the author. 88

Figure 83: Screenshot of the script interface. 89

Figure 84: Daylight Factor Case. Illustration by the author. 90

Figure 85: Screenshot of the script interface (based on "Honeybee Grid-based Dylight Simulation Example I")

Figure 86: Connectivity Case. Illustration by the author.

Figure 87: Screenshot of the script interface.

Figure 88: Integration Case. Illustration by the author.

Figure 89: Screenshot of the script interface.

Figure 90: Room Area Case. Illustration by the author.

Figure 91: Screenshot of the script interface.

Figure 92: Room Proportion Case. Illustration by the author.

Figure 93: Screenshot of the script interface.

Figure 94: Distributed apartments in a section. S-apartments

Figure 95: Distributed apartments in a section. M-apartments

Figure 96: Distributed apartments in a section. L-apartments

Figure 97: Distributed apartments in a section. S-,M- and L-apartments

92 93 94 95 96 97 98 99 100 100 101 101

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