Prediction of service life of building claddings using the factor method: A state of the art

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CIB World Building Congress 2019

Hong Kong SAR, China 17 – 21 June 2019

Prediction of service life of building claddings using the factor method: A state of the art

Ana Silva,

CERIS, Instituto Superior Técnico, University of Lisbon (email: [email protected])

Jorge de Brito,

CERIS, Instituto Superior Técnico, University of Lisbon (email: [email protected])

Pedro Lima Gaspar,

CERIS, Faculty of Architecture, University of Lisbon (email: [email protected])

Abstract

Service life prediction is an essential aspect of the contemporary construction sector, which intends to be more sustainable at an economic and environmental level. Knowledge of the service life and durability of buildings and components allows selecting the most suitable materials for a given use, while ensuring the compatibility of the buildings’ durability layers and optimizing maintenance schedules throughout the constructions’ life cycle. During the last decades, different methodologies have been proposed for the service life prediction of buildings and components. Among these methods, the factor method stands out since it combines simplicity and flexibility, being thus considered as a general framework for service life prediction, established in the international standard for durability, ISO 15686-1: 2011. This method allows calculating the estimated service life of a given building or component when subjected to a specific set of conditions, by multiplying a reference service life by a series of durability factors related with the quality of the materials and design, the execution level, the environmental exposure conditions, and the in-use and maintenance conditions. Currently, there are different studies addressing the application of the factor method for the service life prediction of building components. These studies present different procedures of quantification and expression of the durability factors, ranging from absolute values to probabilistic distributions. The models proposed in these studies propose different equations for the application of the factor method, which are adjusted to the specific conditions of each component under analysis.

This study provides an overview of the different models proposed in the literature, comparing the different results achieved for the estimated service life of different cladding solutions and discussing the physical meaning of these results. This study also discusses the adoption of new approaches to overcome the limitations of the factor method when applied as a purely deterministic tool.

Keywords: Service life prediction, factor method, durability, building claddings.

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1. Introduction

The concept of the “factor method” was initially proposed by the Architectural Institute of Japan (1993) and established the principles for the service life prediction of buildings and components. This method was further developed by Bourke and Davies (1997), in the absence of more precise, or even

‘scientific’ data (Davies and Wyatt, 2004), for the estimation of the service life of a given component subjected to specific conditions. Currently, the so-called “factor method” is seen as a general framework for the service life prediction of construction elements, combining simplicity and flexibility, thus becoming the main methodology for service life prediction (Silva et al., 2016), established in the international standard for service life planning of buildings (ISO 15686-1: 2011).

In the factor method, the estimated service life of a building component is obtained through the multiplication of a reference service life by a series of “modifying” factors related with the characteristics of the component under analysis (Lair, 2003), as shown in Equation (1).

ESL = RSL · A · B · C · D · E · F · G (1)

Where ESL is the estimated service life, RSL the reference service life, A the factor related to the quality of the materials, B the factor related to the design level, C the factor related to the execution level, D the factor related to the interior environmental conditions, E the factor related to the external environmental conditions, F the factor related to the in-use conditions, and G the factor related to the level of maintenance.

The reference service life is usually obtained based on previous experience, technical information from producers, laboratory tests and statistical analysis, regulations and building standards, scientific research or based on the knowledge of components’ performance when subjected to similar conditions (Teplý 1999; Nireki et al. 2002; Aktas and Bilec 2012). Several institutions, namely the Chartered Institution of Building Service Engineers (CIBSE, 2000), The Building Performance Group (BPG, 1999) and the HAPM Component Life Manual (Construction AuditLimited, 1992) present reference service life data, but this information is usually based on manufacturer’s warranties (Grant et al., 2014).

The application of the factor method requires the quantification of the “modifying” factors identified in ISO 15686-1 (2011), adjusted to the specific conditions of the element under analysis (Hovde, 1998). For the quantification of the durability factors, ISO 15686 (2011) suggests the use of standard values ranging normally from 0.8, for unfavourable situations, to 1.2, for favourable situations. This suggestion, although highly practical, is over-simplistic, since these values are usually incapable of portraying the inherent variability associated to the durability factors.

The factor method has been the subject of several criticisms, mainly when applied as a purely deterministic tool. Various authors (Moser and Edvardsen 2002; Re Cecconi and Iacono, 2005; Mc Duling et al. 2008) refer that: i) the factor method is incapable of addressing the variability of the degradation phenomenon; ii) the quantification of the durability factors is rather subjective and strongly influences the values of the estimated service life; iii) the output of the model is an absolute value for the estimated service life of a given element, thus not providing any information regarding the accuracy of the result obtained. Nevertheless, this method presents a balance between accuracy, low cost and ease of application, and therefore, its practical application has been adopted in the construction sector in the international community (Silva et al., 2016).

2. Studies on the application of the factor method (FM) to the service life prediction of building’s components

In the last decades, several studies have been put forward addressing the application of the factor method

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to the service life prediction of buildings and their elements. Much work has been done within international organizations, such as the Council for Research and Innovation in Building and Construction (CIB) (Hovde, 1998). Marteinsson (2003) adopted the factor method to evaluate the durability and service life of 220 wooden windows in Reykjavik, Iceland. In that study, the author discusses the different degradation agents and factors that affect the degradation and service life of wooden windows and points out some problems for a general user in using the factor method, mainly because the model to produce accurate results requires knowledge that is rarely available. Hans et al. (2008) propose the establishment of a French National Service Life Information Platform, to provide essential information regarding the factors conditioning the buildings’ durability, allowing estimating the buildings’ service life. Brischke et al. (2006) analysed the applicability of the factor method to the service life prediction of wood facades and wood- based products. In this study, the modifying factors are understood as mathematical variables, describing the most important decay factors. The authors refer that the classification proposed by ISO 15686 (2011) is partially suitable, but some important decay factors are inadequately considered, while the weighting of other factors is disproportionately low. Ortega-Madrigal et al. (2015) proposed the application of the factor method to estimate the service life of building envelopes, with a special focus on outer walls and roofs. In this study, the proposed model and the durability factors were adjusted to the specificity of the elements under analysis and to the Spanish context. Recently, Re Cecconi (2016) proposed the application of the factor method to the service life prediction of aluminium windows and curtain walls, intending to create a specific factor method for each family of components under analysis. In this approach, the estimated service life may be computed by combining the multiplication and function level for groups of different factor categories.

3. Application of the factor method to the service prediction of building claddings

This study discusses the application of the factor method in different contexts, with a special focus on the service life prediction of building claddings. In the last decade, the authors applied the factor method to different types of external claddings. These studies were always based on the definition of a reference service life and the modifying factors that affect the durability of these claddings, based on an extensive fieldwork survey, in order to reflect the Portuguese building context (Gaspar and de Brito, 2008). In this sense, the different models proposed by the authors are presented in the next sections.

3.1 Rendered facades

The application of the factor method to the service life prediction of rendered facades, based on an in situ evaluation of the deterioration condition of the case studies analysed, was initially proposed by Gaspar and de Brito (2008). Recently, Silva et al. (2016) adopted the same methodology for the service life prediction of 100 rendered façades, located in Portugal, proposing the adoption of Equation (2) for the estimation of the service life of rendered façades.

ESL = RSL · A1 · B1 · B2 · B3· B4· B5 · E1 · E2 · E3 · E4 · E5 · F1 · G1 (2) Where ESL represents the estimated service life, RSL the reference service life (equal to 16 years), A1 the render type, B1 façade colour, B2 building geometry, B3 eaves’ protection, B4 protection of parapets in roofs and terraces, B5 protection of balcony parapets, B6 ground floor protection (socle), B7 detailing/design level, E1 façade orientation, E2 distance from the sea, E3 exposure to damp, E4 distance from pollution sources, E5 façade protection level, F1 in-use conditions, and G1 ease of inspection of the façade. For the application of the factor method to the service life prediction of the rendered facades, the durability factors considered must be replaced by the numerical values shown in Table 1.

The application of the factor method to 100 renderings led to an average estimated service life of 18.8 years, with a median ESL of 15.7 years and a standard deviation of 9 years. The ESL obtained is in

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accordance with the empirical knowledge and with other related studies; e.g. Shohet and Paciuk (2004) obtained an average ESL of 15 years (with estimated service lives ranging from 12 to 19 years), for situations where the cladding must have a high level of performance.

Table 1: Weighting of the durability factors considered for the application of the factor method to the service life prediction of rendered facades

Durability factors Quantification

A1 Render type

Lime-cement renderings Current cement renderings Renderings with crushed marble

Single-layer renderings

0.875 1.025 1.325 1.425

B1 Colour

White Light colours Dark colours

0.700 1.025 1.125

B2 Building geometry Compact

Irregular

1.025 0.975

B3 Eaves’ protection Without protection

With protection

1.000 1.125

B4 Platbands copings Without copings

With copings 0.850

1.200

B5 Balcony copings Without copings

With copings

1.000 1.200

B6 Ground floor

protection (socle)

Without protection With protection

1.000 1.050 B7 Detailing/design

level

Inferior Medium Superior

0.800 1.000 1.150 E1 Façade orientation

East/SE North/NE West/NW South/SW

1.050 0.825 1.050 1.250 E2 Distance from the

sea Less than 5 km

More than 5 km 0.950

1.050 E3 Exposure to damp

Unfavourable Normal Favourable

1.000 1.100 1.125

E4 Distance from

pollution sources

Unfavourable Normal Favourable

0.800 0.800 1.500 E5 Façade protection

level

Without protection Normal situation

With protection

1.000 1.000 1.000

F1 Type of property Private

Public sector Commerce and services

0.800 1.075 1.075

G1 Ease of inspection Normal

Unfavourable 1.225

1.000

3.2 Painted surfaces

Magos et al. (2016) adopted the same methodology to predict the service life of external paint finishes, concluding that the factor method can be an efficient tool to evaluate the service life of these claddings. Silva et al. (2016) analysed a sample of 220 case studies and established Equation (3) for the application of the factor method to the service life prediction of painted surfaces.

ESL = RSL · A1 · B1 · B2 · B3 · E1 · E2 · E3 · E4 · E5 · F1 · G1 (3) Where ESL represents the estimated service life, RSL the reference service life (equal to 9.7 years), A the type of paint, B1 the façade colour, B2 the type of finishing, B3 the building geometry, E1 the façade orientation, E2 the wind-rain action, E3 the distance to the sea, E4 the exposure to damp, E5 the distance to pollution sources, F1 the in-use conditions, and G1 the ease of inspection of the façade.

The durability factors considered must be replaced by the numerical values shown in Table 2.

The application of the factor method, as proposed by Silva et al. (2016), to a sample of 220 surfaces,

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led to an average ESL of 10 years, with a median value of 9.9 years and a standard deviation around 1 year. This result is in accordance with previous studies, which suggested an average service life of ten years for painted surfaces (Hed 1999; Keoleian et al. 2001; Chai et al., 2014).

Table 2: Weighting of the durability factors considered for the application of the factor method to the service life prediction of painted surfaces

A1 Type of paint

Plain paints Elastic membranes Silicate and silicone paints

Textured paint

1.025 1.015 1.000 1.025

B1 Colour

White Light colours Dark colours

1.075 1.000 0.975

B2 Type of finishing Smooth

Rough

1.000 1.150

B3 Building geometry Compact

Irregular

1.000 0.975 E1 Façade orientation

1.000 1.050 0.950 0.925 E2 Wind-rain action

Severe Moderate

Low

0.950 0.975 1.000 E3 Distance from the

sea

Less than 5 km More than 5 km

0.975 1.000

E4 Exposure to damp High

Low

1.000 1.050

E5 Distance from

pollution sources

Unfavourable Normal

0.950 1.000

F1 Type of use Commerce and services

Housing 1.000

1.000

G1 Ease of inspection Unfavourable

Normal

0.985 1.000

3.3 Natural stone claddings

Emídio et al. (2014) and Silva et al. (2016) evaluated the applicability of the factor method to the service life prediction of natural stone claddings. Equation (4) presents the model proposed (Silva et al., 2016), considering the durability factors that influence the degradation condition of 203 natural stone claddings.

ESL = RSL · A1 · B1 · B2 · B3 · B4 · B5 · E1 · E2 · E3 · E4 · F1 · G1 (4) Where ESL represents the estimated service life, RSL the reference service life (equal to 68 years), A1 the type of stone, B1 the colour, B2 the type of finishing, B3 the size of stone plates, B4 the thickness of stone plates, B5 the location of the cladding, E1 the façades orientation, E2 the distance from the sea, E3 the exposure to wind-rain action, E4 the exposure to damp, F1 the type of property, G1 the ease of inspection. The durability factors should be quantified by the values shown in Table 3.

Based on the application of this model to 203 natural stone claddings, an average ESL of 70.5 years was obtained, with a median value of 68 years and a standard deviation around 17 years. This value is in accordance with previous studies, e.g. Shohet and Paciuk (2004) estimated an average ESL ranging between 59 and 70 years, for claddings subjected to normal conditions.

3.4 Ceramic tiling systems

Concerning ceramic tiling systems, Galbusera et al. (2014) and Silva et al. (2016) proposed the

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application of the factor method to a sample of 196 ceramic claddings, based on in situ visual inspections to claddings located in Portugal. Based on the sample analysed, Silva et al. (2016) proposed the application of the factor method to the ceramic claddings, adopting Equation (5).

ESL = RSL · A1 · B1 · B2 · B3 · B4 · B5 · E1 · E2 · E3 · E4 · G1 (5) Where ESL represents the estimated service life, RSL the reference service life (equal to 51 years), A the type of surface, B1 the façade colour, B2 the tiles size, B3 the substrate type, B4 the presence of peripheral joints, B5 the presence of peripheral protection, E1 the façade orientation, E2 the distance to the sea, E3 the wind-rain action, E4 the exposure to damp and G1 the ease of inspection of the façade. Table 4 presents the numerical quantification of the durability factors considered.

Table 3: Weighting of the durability factors considered for the application of the factor method to the service life prediction of natural stone claddings

A1 Type of stone

Limestone Granite Marble

1.000 1.100 0.950

B1 Colour Light colours

Dark colours

1.025 1.000

B2 Type of

finishing Smooth

Rough 1.100

1.000 B3 Size of stone

plates

Medium Large

1.000 0.900 B4 Thickness of

stone plates

Less than 2.5 cm

≥ 2.5 cm

1.000 1.100 B5 Location of the

cladding Partial and integral elevated cladding

Bottom wall cladding 0.950

1.000

E1 Façade

orientation

North NE/E/SE West/NW South/SW

0.900 0.950 0.900 1.000 E2 Distance from

the sea Less than 5 km

More than 5 km 1.000

1.150

E3 Exposure to

wind-rain action

Moderate Severe

1.000 1.000

E4 Exposure to

damp Low

High 1.000

0.900

F1 Type of

property

Housing Commerce and services

1.000 1.000

G1 Ease of

inspection

Current Unfavourable

1.000 0.900

Table 4: Weighting of the durability factors considered for the application of the factor method to the service life prediction of ceramic claddings

A1 Type of surface Glazed

Not glazed

1.000 0.950

B1 Colour Light colours

Dark colours

1.000 1.050

B2 Size of tiles L ≤ 20 cm

L > 20 cm 1.000

0.825

B3 Substrate type Masonry

Concrete

1.000 1.050

B4 Peripheral joints Without

With

1.000 1.150

B5 Peripheral

protection

Without With

1.000 1.125 E1 Façade orientation

1.125 1.125 0.945 1.045

E2 Distance to the sea Less than 5 km

More than 5 km

0.850 1.000

E3 Wind-rain action Severe 0.900

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Moderate Low

0.995 1.000

E4 Exposure to damp High

Low 0.900

1.000

G1 Ease of inspection Unfavourable

Normal

0.925 1.050

The application of the factor method to 196 ceramic claddings led to an average ESL of 54.5 years, with a median value of 50 years and a standard deviation of 18 years. This value is in accordance with the value suggested by BCIS (2001), which suggests an average service life of 35 years with a range between 20 and 50 years for external ceramic claddings. Recently, Souza et al. (2018) applied the factor method to the service life prediction of ceramic tiling systems in Brasília, obtaining similar results.

3.5 External Thermal Insulation Systems (ETICS)

Marques et al. (2018) proposed the application of the factor method to the service life prediction of ETICS, evaluating the degradation condition of 274 claddings in Portugal - Equation (5).

ESL = RSL · A1 · A2 ·B1 · B2 · C1 · E1 · E2 · E3 · E4 · E5 · G1 (5) Where ESL represents the estimated service life; RSL the reference service life (equal to 21 years, according to the values obtained in this study), A1 the type of cladding system, A2 the colour; B1 the type of finishing, B2 the protection level, C1 the execution level, E1 the façades orientation, E2 the distance from the sea, E3 the exposure to damp, E4 the wind/rain action, E5 the exposure to pollution sources and G1 the ease of inspection. The durability factors should be quantified by the values shown in Table 5.

Table 5: Weighting of the durability factors considered for the application of the factor method to the service life prediction of ETICS

A1 Type of

system

Traditional 1.000

Strengthened 1.100

Ceramic 1.250

A2 Colour

White 1.100

Light colours 1.000

Dark colours 1.400

Other 1.400

B1 Type of

finishing

Rough 0.900

Smooth 1.000

Other 1.100

B2 Protection

level

Peripheral profile 1.115

Wainscot 1.100

Other 0.775

C1 Execution

level

Adequate 1.000

Inadequate 0.800

E1 Façade

orientation

North 0.800

South 1.000

East 1.000

West 1.000

E2 Distance

from the sea

< 1 km 0.800

Between 1 and 5 km 1.000

> 5 km 1.100

E3 Exposure to damp

High 1.000

Low 1.150

E4

Exposure to wind/rain

action

Severe 0.800

Moderate 0.900

Mild 0.950

E5 Exposure to

pollutants

High 0.950

Low 1.100

G1 Ease of

inspection

Yes 1.100

No 1.000

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The application of the factor method to the 274 ETICS analysed, led to an average ESL of 21 years, with a median value of 20 years and a standard deviation of 4.5 years. This result is in accordance with previous studies, namely Künzel et al. (2006) refer that, after 20 years, ETICS systems should be subjected to maintenance actions in order to restore an adequate performance level.

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4. New approaches to overcome the limitations of the FM

In the last decades, different approaches have been proposed, in order to optimize the determination of the estimated service life through the application of the factor method. According to ISO 15686-8 (2008), the factor method can be applied at different levels of sophistication, from working as a simple checklist to complex calculations (Re Cecconi et al., 2016). In this sense, the main innovation proposed for the application of the factor method lies on the improvement of the quantification of the durability factors.

Various authors (Aarseth and Hovde, 1999; Moser, 1999; van Nunen, 2010) proposed the adoption of stochastic functions to quantify the durability factors, in order to encompass the variability associated with the durability of the building components. Re Cecconi (2004) proposed the adoption of Monte Carlo simulation, applying triangular probability distribution functions, in the quantification of the durability factors. Daniotti and Spagnolo (2008) refer that using random variables in the quantification of the durability factors allows describing with higher reliability and accuracy the complexity of the degradation phenomena, providing an ESL with precise probabilistic information.

McDuling et al. (2008) proposed a neuro-fuzzy artificial intelligence model for the quantification of the durability factors, intending to translate expert knowledge into probability values to describe the durability factors. Silva et al. (2016) and Souza et al. (2018) adopted a stochastic approach to the factor method, multiplying a deterministic RSL by durability factors given by probabilistic distribution functions. In the stochastic approaches to the factor method, the estimated service life is given by a probability distribution function. Therefore, these approaches provide an extremely relevant information in the service life prediction context, supporting more rational decisions in the maintenance sector, since they allow estimating the ESL with the highest probability of being achieved based on the characteristics of the building component under analysis.

5. Conclusions

This study provides an overview of the application of the “factor method” to the service life prediction of building components. This method is a simple tool, easily implemented by practitioners, in the absence of more scientific data related with the components’ performance under real exposure conditions. Different studies addressing the application of the factor method to the service life prediction of building components are briefly described in this study. It is mainly focused on the service life prediction of buildings’ envelope elements, applying the factor method. In the last decades, the authors proposed different approaches for the application of the factor method to the service life prediction of external claddings. These models are defined based on extensive fieldwork surveys, performing a detailed evaluation of the degradation agents and mechanisms that affect the cladding under analysis.

The different models led to coherent results, in accordance with empirical knowledge and with related studies, ensuring the applicability of the factor method to the service life prediction of these elements.

Finally, this study discusses new trends and approaches to overcome the limitations of the factor method when applied as a purely deterministic tool. Essentially, these approaches suggest the application of the durability factors as random variables, in order to encompass the variability associated with the degradation mechanisms, thus obtaining an estimated service life given by a probabilistic function, which allow obtaining more useful and reliable information regarding the risk of failure of the element under analysis.

Acknowledgements

The authors gratefully acknowledge the support of the CERIS Research Institute, IST, University of Lisbon and the FCT (Foundation for Science and Technology) through the projects SLPforBMS (PTDC/ECM-COM/5772/2014) and BestMaintenance-LowerRisks (PTDC/ECI-CON/29286/2017).

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