Original approach to Service life prognostication developed for residential buildings Текст научной статьи по специальности «Строительство и архитектура»

ВЕСТНИК

УДК 69.059

A.A. Volkov, S.R. Muminova

MGSU

ORIGINAL APPROACH TO SERVICE LIFE PROGNOSTICATION DEVELOPED FOR RESIDENTIAL BUILDINGS

A novel integrated mathematical model for devaluation of residential buildings is presented. The devaluation model proposed by the authors is a useful tool employed to predict the residual life span of a building. Availability of information concerning the building behaviour in the course of time makes it possible to influence its properties by means of renovation or restructuring-related actions to resist the aging process. This approach can be regarded as a way to extend the service life span of residential buildings.

Key words: building devaluation, integrated mathematical model, life span, building behaviour, residential building.

Building valuation is an essential task, as any buildings are exposed to inevitable physical and chemical processes reducing their value in the course of time. The objective of a civil engineer is to limit building deterioration using timely and target-oriented renovation actions and to balance the resources needed for new construction, maintenance and renovation.

Development of a rational renovation policy requires a process model applicable to building devaluation and restoration. The authors present a quantitative method to simulate devaluation of individual building components as well as integral buildings. The method is regarded as part of a multi-component model used to identify the most appropriate time slots for renovation of groups of components and prognostication of accumulated initial and renovation costs in the course of the building life span [1]. An integrated model of building devaluation is developed in two stages. At the first stage, devaluation diagrams are developed for individual building components using the Schroeder method [2]. Normalized value v of the building component at age tc is ratio v of its value vc at age tc to its new value vc0. Normalized age t of the component is the ratio of its current age tc to age tc null at which its value becomes null:

v

v = , (1)

vc 0

t = . (2)

tc,null

Monitoring of buildings [2, 3] leads to development of a devaluation function expressing the normalized value of a component in terms of its normalized age and devaluation rate a depending on the type of component and its environment in terms of the building:

v(t) = 1 - Г (3)

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© Volkov A.A., Muminova S.R., 2013

Информационные системы и логистика в строительстве

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The smallest value v]ife of a component at which it can still be renovated is called its critical value. Normalized age tlife of a component having a critical value is called its normalized life span. Normalized life span is derived on the basis of expression (3):

tf = aj 1 - Vlife . (4)

As the process of devaluation of a new component can differ from the one during later periods within the life span, the two-phase devaluation diagram (Figure) is introduced. Phase 1 represents a special initial loss of value due to initial cracking, settlement and wear. Phase 2 represents gradual aging of a component due to chemical and physical processes as well as normal wear and tear.

^^rate a1

phase transit on poir t

vi

^^rate a2

v life ent of life span ! 'x

ti t life : \

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

normalized time t

phase 1-

phase 2

Two-phase Devaluation Diagram

The phase transition point is positioned on the diagonal of the diagram. During

Phase 1, devaluation rate a relates to normalized value v and time t as follows:

' = 1 -(1 - v)

( t V

v ti J

0 < t < ti,

1 - v

t = ti Ж- Vi < v < L

vi - V

(5)

(6)

During Phase 2, devaluation rate a2 relates to normalized value v and time t as follows:

V = V1 -( V1 - Vlife )

t = t1 +(tlife - t1 )"

i Ла2

' t - t1 A

v tlife - t1 J

V

ti < t < 1,

0 < v < V.

(7)

(8)

Normalized life span tlife for a given critical value is identified using expression (8) by taking v = 0 for t = 1.

At the second stage, devaluation diagram of a complete building is constructed. The building is defined as a set of building components decomposed into classified sets, each of which contains building components of exactly one class, for example, a window class. Two problems accompanying this approach are to be resolved:

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Normalized values of different components cannot be added because absolute values of these components differ.

Components, having the same normalized age, have different absolute ages, because their life spans differ. If two components having different life spans are to be considered at the same point in terms of the calendar time, they must be considered at different normalized times.

In order to be able to compare devaluation diagrams of components having different life spans, devaluation functions (5) to (8) are transformed to the calendar time by substituting the normalized time specified in expression (2). Phase 1 equations are as follows:

■ = 1 -(1 - V: )

( t Ya

V tc1

0 < t < t1,

H - V

L = t_, <$1- v < v < 1.

11 - V

Phase 2 equations are as follows:

V = V1 -( V1 - Vlife ) tc = tc1 + (tc,life - tc

tc - tc1

V tc,life - tc1

V

tc1 < tc < 1c,null ,

0 < v < v1.

(9)

(10)

(11)

(12)

Devaluation of a building is regarded as devaluation of its components by considering the building as component set B decomposed into n classified component sets {SJ, ..., Sn}:

B = Sj u S2 u... u Sn,

i,k e {J,..., n\A i * k ^ SJ n Sk = 0 . (13)

As it is very difficult to determine the absolute value of building components, their value is derived indirectly. Initial value vc0(S.) of each classified set S . is expressed as a fraction of the total building value vc0(B). This fraction is called significance g. of the set, and it is estimated statistically. The sum of significances of classified sets of a building is J.

VcoS = g,vJBl (J4)

I gt = 1.

(15)

Let there be n. components within set S.. Weight w k is assigned to each component h ik of the set to represent its relative value. Initial value vc0(h .k) of the component is expressed as fraction z k of the building value. This fraction is called the participation factor of component h k:

Vjhh k) = z^l ' (J6)

Zn

k =1

П

k=1w k

1=1

Информационные системы и логистика в строительстве

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Normalized value vjk of component hk at age tc is computed using expression (9) or (11). Absolute value v(h.k) of the component is derived using expression (16):

vc (hkk ) = VikVc0 (hkk ) = VikZikVc0 (B). (17)

The model is based on the hypothesis that absolute value vc(B) of the building equals to the sum of absolute values of its components:

vc (B ) = j jj vc (hk ) vco ( B )j jj v^Zk. (18)

i=1 k =1 i=1 k =1

Normalized value v(B) of the building at time tc is derived using (18):

v (B ) = = j jj ^. (19)

vc0 (B) i=1 k=1

Our advanced approach to building devaluation modeling makes it possible to eliminate some drawbacks of probabilistic methods employed to predict residual life spans [4, 5], as it demonstrates its higher accuracy and objectivity. If used in combination with a mathematical model describing renovation actions applied to a building, it can be successfully implemented in the renovation strategy to optimize maintenance costs of residential buildings.

References

1. Muminova S.R., Pahl P. J. An Integrated Model of Planning Processes for Building Devaluation and Renovation. Vestnik MGSU [Proceedings of Moscow State University of Civil Engineering]. 2012, no. 10, pp. 297—304. Available at: http://vestnikmgsu.ru/index. php/en/archive. Date of access: 15.11.2012.

2. Schröder, Jules: Zustandsbewertung grosser Gebäudebestände. Schweizer Ingenieur und Architekt, no. 17, April 1989, pp. 449—459.

3. Schweizer Bundesamt für Konjunkturfragen: Impulsprogramm Bau (IP BAU). Alterungsverhalten von Bauteilen und Unterhaltskosten: Grundlagendaten für den Unterhalt und die Erneuerung von Wohnbauten. Bern, December 1994, 110 p.

4. Kirkham R.J., Alisa M., Pimenta da Silva A., Grindley T., Brondsted J. EUROLIFEFORM: an Integrated Probabilistic Whole Life Cycle Cost and Performance Model for Buildings and Civil Infrastructure. Proceedings of International Construction Research Conference of the Royal Institution of Chartered Surveyors (COBRA 2004), September 2004.

5. Cole I.S., Corrigan P.A (2009). Development of a Range of Methods for Estimating the Service Life of Buildings and Engineered Structures. In Anderssen R.S., Braddok R.D. and Newham L.T.H., editors. 18th World IMACS Congress and MODSIM09 International Congress on Modeling and Simulation. Modeling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation. July 2009, pp. 2377—2383.

Поступила в редакцию в феврале 2013 г.

About the authors: Volkov Andrey Anatol'evich — Doctor of Technical Sciences, Professor, Vice-Rector for Research, Chair, Department of Information Systems, Technology and Automation in Civil Engineering, Moscow State University of Civil Engineering (MGSU), 26 Yaroslavskoe shosse, Moscow, 129337, Russian Federation; [email protected];

Muminova Svetlana Rashidovna — Research Assistant, Scientific and Educational Centre for Information Systems and Intelligent Automatics in Civil Engineering, Moscow State University of Civil Engineering (MGSU), 26 Yaroslavskoe shosse, Moscow, 129337, Russian Federation; [email protected].

ВЕСТНИК

For citation: VolkovA.A.,Muminova S.R. Original Approach to Service Life Prognostication Developed for Residential Buildings. Vestnik MGSU [Proceedings of Moscow State University of Civil Engineering]. 2013, no. 3, pp. 244—248.

А.А. Волков, С.Р. Муминова

ФГБОУ ВПО «МГСУ»

НОВЫЙ ПОДХОД К ПРОГНОЗИРОВАНИЮ СРОКА СЛУЖБЫ ЖИЛЫХ ЗДАНИЙ

Представлена новая интегрированная математическая модель износа жилых зданий, действующая на основании данных об изменении состояния зданий с течением времени. Данная модель представляет собой незаменимое средство прогнозирования срока службы жилых зданий. Наличие информации об изменении технического состояния жилого дома, или его износе с течением времени, позволяет воздействовать на его свойства путем проведения таких мероприятий, как ремонт или реконструкция, направленных на сокращение скорости износа здания. Данный подход может рассматриваться как способ продления общего срока службы жилых зданий.

Ключевые слова: износ зданий, интегрированная математическая модель.

Библиографический список

1. Muminova S.R., Pahl P.J. An Integrated Model of Planning Processes for Building Devaluation and Renovation // Вестник МГСУ. 2012. № 10. С. 297—304. Электронный ресурс: http://vestnikmgsu.ru/index.php/en/archive. Дата просмотра: 15.11.2012.

2. Schröder, Jules: Zustandsbewertung grosser Gebäudebestände. Schweizer Ingenieur und Architekt, Nr. 17, April 1989. P. 449—459.

3. Schweizer Bundesamt für Konjunkturfragen: Impulsprogramm Bau (IP BAU). Alterungsverhalten von Bauteilen und Unterhaltskosten: Grundlagendaten für den Unterhalt und die Erneuerung von Wohnbauten. Bern, Dezember 1994. 110 p.

4. Kirkham R.J., Alisa M., Pimenta da Silva A., Grindley T, Brondsted J. EUROLIFEFORM: an Integrated Probabilistic Whole Life Cycle Cost and Performance Model for Buildings and Civil Infrastructure. Proceedings of International Construction Research Conference of the Royal Institution of Chartered Surveyors (COBRA 2004), September 2004.

5. Cole I.S., Corrigan P.A. Development of a Range of Methods for Estimating the Service Life of Buildings and Engineered Structures. In Anderssen R.S., Braddok R.D. and Newham L.T.H., editors. 18th World IMACS Congress and MODSIM09 International Congress on Modeling and Simulation. Modeling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation. July 2009, pp. 2377—2383.

Об авторах: Волков Андрей Анатольевич — доктор технических наук, профессор, проректор по научной работе, заведующий кафедрой информационных систем, технологий и автоматизации в строительстве, ФГБОУ ВПО «Московский государственный строительный университет» (ФГБОУ ВПО «МГСУ»), 129337, г Москва, Ярославское шоссе, д. 26, [email protected];

Муминова Светлана Рашидовна — научный сотрудник научно-образовательного центра информационных систем и интеллектуальной автоматики в строительстве, ФГБОУ ВПО «Московский государственный строительный университет» (ФГБОУ ВПО «МГСУ»), 129337, г. Москва, Ярославское шоссе, д. 26, [email protected].

Для цитирования: Volkov A.A., Muminova S.R. An Approach to Service Life Prediction for Residential Buildings // Вестник МГСУ. 2013. № 3. С. 244—248.