Methodology for service life prediction of architectural concrete

Maria Inês Marques Serralheiro

Extended Abstract

Supervisor: Professor Doutor Jorge Manuel Caliço Lopes de Brito

Doutora Ana Filipa Ferreira da Silva Cigarro Matos

Lisbon, November 2016

1

1. Introduction This master thesis intends to develop a methodology to estimate the service life of architectural con-

crete applied as a cladding system in façades, following the research line of Gaspar (2002), Sousa

(2008), Gaspar (2009), Gaspar and Brito (2011), Silva et al. (2011a), Silva et al. (2011b), Chai et al.

(2014), Emídio et al. (2014), Chai et al. (2015), Ximenes et al. (2015) and Marques (2016), who stud-

ied the service life and durability of different types of coatings.

The methodology adopted is based on data collected by visual inspection of façades during the field-

work, including facades inspected by Silva (2015), including its degradation phenomena and all the

characteristics of architectural concrete. After this work, maintenance plans can be defined, in order to

enhance the service life of architectural concrete. By evaluating the environment impacts in buildings,

it is possible to extend their durability, since the degradation mechanisms are already understood and

their impacts can be reduced with regular inspections and rehabilitation actions.

2. Service life definition The end of service life is not an univocal concept, varying from author to author. For example, ASTM

E632-82 (1996) defines the service life of a building or an element as the period of time, after installation,

during which all its properties exceed the minimum acceptable requirements, assuming regular mainte-

nance procedures. The Architectural Institute of Japan (1993) refers that this concept can be defined as the

period of time, in years, until a building or its elements, equipment or parts reach a certain level of degrada-

tion, in regular circumstances of design, construction, using and exposure to environmental elements. The

service life can also be defined as the period of time in which a building, or its components, fulfils its func-

tion, without unpredictable maintenance costs and without any type of repair needs (PWGSC et al., 1997).

Therefore, in order to standardize this concept, ISO 15686-1: 2000 was developed and it is nowadays the

most important reference on service life and its prediction. This standard defines that the service life plan-

ning is a process developed during the design of a building, which tries to ensure that a building’s service life

equals or exceeds the designed service life, taking into account the service life costs of that same building.

Despite being a complex issue, predicting the service life of buildings is a very interesting task. Presently,

durability projects are proposed to ensure that the service life of a building is accomplished, based on the

materials performance to environmental actions (Ferreira, 2006). The buildings’ users expects that their

service life equals, at least, their own life, but when the construction is no longer new, the same users in-

quire about how many years the building will last (Branco and Brito, 1990). Thus, knowing how to quanti-

fy the buildings service life is quite important to answer these questions.

3. Architectural concrete description 3.1 Main characterisation

The architectural concrete characteristics are widely influenced by its design and production process,

namely: i) the choice of the elements applied in the concrete matrix; ii) the formwork adopted; iii) the

2

operations of concrete casting; and iv) the mould releasing process. The designer is able to choose the

final appearance of architectural concrete, for example, natural, polished, coloured, bush-hammered,

sandblasted, split relief moulded, flamed, photoengraved and translucent finishing. Thereby, this type

of coating material has an important aesthetical value.

3.2 Anomalies and its main causes

The anomalies of architectural concrete can be divided into three main groups, described in Table 1.

Brito (1987) and Silva (2015) defined a classification criterion based on a chronological system, estab-

lishing that design faults precede construction errors, that precede accidental and environmental ac-

tions, as well as aggressive agents. The design errors can be avoided by taking into account the tech-

nical viability of the proposed solutions, the aesthetical finishing desired, a maintenance planning of

concrete surfaces (Secil, 2011), an appropriate formwork and choice of release agents, and a fine de-

tailing of reinforcement and of expansion joints design. Construction errors are due to unskilled work-

ers, the violation of basic security rules, poor casting and compaction, excessive use of the formwork,

poor curing of concrete, as well as the storage of materials (Brito, 1987; Secil, 2011). Environmental

factors can be described by outside temperature, wind, solar exposure, moisture and freeze-thaw cy-

cles (Committee 305, 1999). Finally, the presence of chlorides and sulphates in marine environment

are synonymous of aggressive agents to architectural concrete (Hobbs, 2002). Table 1 - Description of the different groups of architectural concrete anomalies

Group Description Examples Aesthetical anomalies

Affecting the visual appearance of architectural concrete, but not directly influencing its degradation

Dirt stains, moisture stains, efflorescence, biologi-cal growth, wear/erosion, bug holes and graffiti

Mechanical anomalies

Due to imposed displacements and/or static and dynamic actions, directly influencing the degradation of architectural concrete

Mapped cracking, orientated cracking, dis-aggregation and spalling

Constructive anomalies

Due to design faults or to constructive errors and/or inade-quate materials used in the concrete mixture

Flatness defects, honeycombing, fastening marks, dribbling, crusts and formwork incrustation

4. Fieldwork The aim of the fieldwork is to perform a survey of the anomalies of architectural concrete façades. To

understand how these anomalies influence the degradation of architectural concrete, it is necessary to

define levels of degradation of the façades.

4.1 Levels of degradation

Marteinsson and Jónsson (1999) proposed a degradation scale to concrete surfaces, with four levels of

performance, in which condition “A” means a surface with no damage. But this study follows a research

line developed by Gaspar (2002) and Gaspar and Brito (2005), who defined a numerical scale of degrada-

tion with five degradation levels, in which level 0 means no visible degradation and level 4 corresponds to

a generalised degradation. Therefore, in this work, degradation levels for each group anomalies were de-

veloped, where within each group the anomalies were classified according to their severity (Table 2 to 4).

During the fieldwork, 174 architectural concrete surfaces were visually inspected and all the data col-

lected were carefully processed, in order to study these façades’ degradation. It is necessary to identify

3

all the outliers, which in this work are represented by severe construction errors, corresponding to a

façade with 40% or more of its area affected by bug holes. Table 2 - Degradation levels for aesthetical anomalies

Degradation level Anomalies description Percentage of the area of archi-tectural concrete (AC) affected

Level 0 No degradation visible -

Level 1 Good

Dirt stains < 15% Moisture stains

Corrosion stains Wear/erosion

< 10% Bug holes Biological growth

Efflorescence

Level 2 Slight degradation

Dirt stains 15 to 40% Moisture stains

Corrosion stains Wear / erosion

10 to 30% Bug holes Biological growth

Efflorescence

Level 3 Moderate degradation

Dirt stains > 40% Moisture stains

Corrosion stains Wear/erosion

> 30% Bug holes Biological growth

Efflorescence

Table 3 - Degradation levels for mechanical anomalies

Degradation level Anomalies description Percentage of AC affected Level 0 No degradation visible -

Level 2 Slight degradation

Disaggregation < 10%

Spalling Oriented cracking (≤ 0,5 mm) < 5%

Level 3 Moderate degradation

Disaggregation 10 to 30%

Spalling Mapped cracking < 50%

Oriented cracking (> 0,5 mm and < 3mm) ≥ 5% Oriented cracking (≥ 3 mm) < 5%

Level 4 Generalised degradation

Disaggregation > 30%

Spalling Mapped cracking ≥ 50%

Oriented cracking (≥ 3 mm) ≥ 5%

Table 4 - Degradation levels for constructive anomalies

Degradation level Anomalies description Percentage of AC affected Level 0 No degradation visible - Level 1 Good

Flatness defects < 20% Dribbling ≤ 10%

Level 2 Slight degradation

Flatness defects 20 to 50% Dribbling > 10%

Fastening marks ≤ 5% Honeycombing

< 10% Crusts Formwork incrustation

Level 3 Moderate degradation

Flatness defects > 50% Fastening marks > 5% Honeycombing

≥ 10% Crusts Formwork incrustation

4

5. Methodology applied In this study, the model of Gaspar (2009) was adopted to study the degradation of architectural concrete.

This model leads to acceptable results to describe the degradation evolution of architectural concrete over

time. The Gaspar (2009) model defines the end of service life as level 3, which was also adopted in

this study. Consequently, all the architectural concrete façades with a degradation level of 3 or above

have already reached the end of their service life. After this condition, repairs and maintenance actions

are required to re-establish the necessary characteristics to fulfil the performance requirements.

5.1 Gaspar (2009) model

In order to improve his previous model, Gaspar (2009) proposed a numerical index, called severity of deg-

radation, which specifies the overall degradation level of a façade, normalized in relation to a benchmark

area (corresponding to a façade degraded to the maximum possible level of every degradation mechanism).

The severity of degradation is thus obtained by the ratio between the weighted area of architectural con-

crete and the maximum level of possible degradation (equation (1)), varying between 0 and 100%.

𝑆!,!" =𝐴! ∙ 𝑘! ∙ 𝑘!,! + 𝐴! ∙ 𝑘! ∙ 𝑘!,! + 𝐴! ∙ 𝑘! ∙ 𝑘!,!

𝐴 ∙ (𝑘!á!)=

𝐸!,!𝐸!,!á!

(1)

Where:

Sw,bv - severity of degradation of architectural concrete, in %;

Ae - cladding area affected by aesthetical anomalies, in m2;

Am - cladding area affected by mechanical anomalies, in m2;

Ac - cladding area affected by constructive anomalies, in m2;

kn - multiplication factor for n anomalies, as a function of their degradation level (k varies between 0 and 4);

ka,n - weighting coefficient according to relative weight of the anomaly detected (equal to 1 if no speci-

fication is referred);

A - total cladding area, in m2;

(𝑘!á!) - sum of the weighing constants, corresponding to the highest level of degradation (3+4+3,

aesthetical, mechanical and constructive anomalies, respectively);

Ew,p - architectural concrete’s weighted degradation level;

Ew,máx - architectural concrete’s maximum weighted degradation level.

As Gaspar (2009), this study evaluated two scenarios to determine the severity of degradation: i) in the first

scenario, it is assumed that all the different anomalies have the same relevance (ka,n = 1); and, ii) in the se-

cond one, it is assumed that the various anomalies are not all equally important for the degradation of the

architectural concrete. The second scenario, adopted for weighting the anomalies in architectural concrete

façades, is presented in Table 5. This scenario allows obtaining severity values closer to the observed reali-

ty, showing which anomalies have more influence on architectural concrete degradation. These weighting

factors were defined according to their repair costs and to their propensity to generate other anomalies,

knowing that disaggregation and spalling are more prominent than the others, because they are the main

5

anomalies that affect concrete durability, indicating a problem in the concrete composition, thus evolving

through the architectural concrete surface (Łowinska-Kluge and Błaszczynski, 2012; Guerrero et al., 2016). Table 5 - Weighting factors according to each type of anomalies

Aesthetical anomalies

Dirt stains Moisture

stains Corrosion

stains Efflorescence

Biological growth

Wear / erosion Bug holes Graffiti

0.15 0.15 0.50 0.20 0.60 2.00 0.10 0

Mechanical anomalies Mapped cracking Oriented cracking Disaggregation Spalling

0.15 1.00 5.00 4.00

Constructive anomalies

Flatness defects Honeycombing Fastening marks Dribbling Crusts Formwork

incrustation 0.10 0.30 0.10 0.10 0.10 0.10

In Table 6, the correspondence between degradation levels and severity of degradation is shown. As

mentioned above, level 3 or 20% of Sw,bv represents the end of architectural concrete service life. Thus,

a façade with a severity of degradation of 20% or more has reached the end of its service life. Table 6 - Correspondence between the degradation indicators

Degradation levels Sw,bv Level 0 Sw,bv ≤ 1% Level 1 1% < Sw,bv ≤ 10% Level 2 10% < Sw,bv ≤ 20% Level 3 20% < Sw,bv ≤ 40% Level 4 Sw,bv > 40%

By applying this method to estimate the degradation of the 174 façades inspected during the field-

work, a plot of the evolution of degradation over time can be obtained, as presented in Figure 1.

Figure 1 - Degradation severity for all the 174 architectural concrete inspected in fieldwork.

5.2 Degradation curves

The degradation curves shows the degradation evolution of architectural concrete over time or, in oth-

er words, the loss of performance of architectural concrete. This curve shows a ‘S’-shaped pattern that

means that anomalies at early ages induce an accelerated degradation, followed by a stabilization peri-

od, in which the degradation phenomena are cumulatively felt by the façade but in a slower way, and a

final period of senescence, corresponding to the end of the façades’ service life, where the degradation

occurs rapidly and there is an intensification of the degradation actions.

0%

10%

20%

30%

40%

50%

60%

0 10 20 30 40 50

Sw,bv (%)

Age (years)

Level 1

Level 2

Level 3

Level 4

6

Figure 2 shows the degradation curve obtained from the 174 façades analysed in fieldwork, while Figure

3 shows the degradation curve obtained from the average degradation of all the buildings analysed, lead-

ing to acceptable results, with a good correlation between the observed and the predicted values.

Figure 2 - Degradation curve obtained from the 174

cases analysed in the fieldwork. Figure 3 - Degradation curve obtained from the average

degradation of the buildings analysed.

In order to understand the influence of different factors to the architectural concrete degradation, dif-

ferent degradation curves were established, according to the facades’ characteristics (Figures 4 to 10).

The majority of the degradation curves present a good correlation coefficient, showing that this meth-

odology can accurately describe the real degradation of architectural concrete. In some situations,

when the correlation between the predicted and the observed values do not allow obtaining unequivo-

cal conclusions, the results must be carefully analysed, since the small sample size according to some

characteristics can explain the poor correlation obtained.

Figure 4 - Degradation curves according to the surfaces colour. Figure 5 - Degradation curves according to the surfaces colour.

Figure 6 - Degradation curves according to type of protection.

y = 3E-06x3 - 0.0001x2 + 0.0036x R² = 0.7504

0%

5%

10%

15%

20%

25%

30%

0 10 20 30 40 50

Sw,bv (%)

Age (years)

y = 3E-06x3 - 0.0001x2 + 0.0035x R² = 0.8706

0%

5%

10%

15%

20%

25%

30%

0 10 20 30 40 50

Sw,bv (%)

Age (years)

y = 5E-06x3 - 0.0002x2 + 0.0042x R² = 0.8492

y = 5E-06x3 - 0.0002x2 + 0.0053x R² = 0.7974

0%

5%

10%

15%

20%

25%

30%

0 10 20 30 40 50

Sw,bv (%)

Age (years)

Grey Dark grey White Blue Pink

y = 5E-06x3 - 0.0003x2 + 0.0048x R² = 0.7815

y = 4E-06x3 - 0.0002x2 + 0.005x R² = 0.8096

0%

5%

10%

15%

20%

25%

30%

35%

0 10 20 30 40 50

Sw,bv (%)

Age (years)

Clara Escura Dark Light

y = 0.0001x2 + 0.0015x

y = 1E-05x3 - 0.0004x2 + + 0.0066x

y = 0.0001x2 + 0.0002x

y = 0.0001x2 + 0.0001x

R² = 0.5609

0%

5%

10%

15%

20%

25%

30%

0 10 20 30 40 50 60 70

Sw,bv (%)

Age (years)

Sem protecção

Hidrófugo

Tinta

Tinta+ Hidrófugo

Verniz y = 0.0029x

R2 = 0.7608 R2 = 0.6175

R2 = 0.6972

R² = 0.8859

No protection

Paint

Water repellent

Varnish

Paint + water repellent

7

Figure 7 - Degradation curves according the façades orientation. Figure 8 - Degradation curves according to

the distance from the sea.

Figure 9 - Degradation curves according to wind-

rain exposure and façades orientation Figure 10 - Degradation curves according to exposure to damp.

6. Results and conclusions

In this work, the service life of architectural concrete is evaluated, analysing the influence of its char-

acteristics on its degradation phenomena. By studying the architectural concrete degradation and its

service life, maintenance plans and strategies can be defined, in order to reduce the repair costs.

Gaspar (2009) obtained a correlation coefficient of 0.9 applying the service life prediction model to

rendered façades, concluding that the proposed model properly describes the real degradation of fa-

çades. In this study, the correlation coefficient obtained is 0.75, showing that this model reasonably

depicts the real degradation of architectural concrete.

The expected service life (ESL) of architectural concrete façades according to their different character-

istics is shown in Table 7. This type of coating has an ESL of 44.4 years, which is aligned with struc-

tural concrete (NP EN 1992-1, 2000) and architectural concrete (Takahashi et al., 2008) service life,

both of 50 years. Also the Australian standard AS 3600: 2009 refers that concrete in maritime envi-

ronment has an expected service life between 40 and 60 years.

The values of the ESL presented in this table show that architectural concrete is very susceptible to dif-

ferent protection types, which is the characteristic that most influences its ESL, varying between 38 and

52 years. For all the other characteristics, the values of service life are in the range of 42 to 47 years,

closer to 44.4 years evaluated as the average estimated service life for architectural concrete.

In a future research, it will be interesting to increase the number of older case studies away from the

y = 7E-06x3 - 0.0003x2 + +0.0055x

y = 2E-06x3 - 4E-05x2 + +0,0027x

y = 4E-06x3 - 0.0002x2 + +0,0039x

y = 2E-06x3 - 5E-05x2 + +0.0026x

0%

5%

10%

15%

20%

25%

30%

0 10 20 30 40 50

Sw,bv (%)

Age (years)

N

NE / E / SE

O / NO

S / SO

R2 = 0.8355

R2 = 0.5782

R2 = 0.8223

R2 = 0.8030

W / NW

S / SW y = 2E-06x3 - 5E-05x2 + 0.0024x R² = 0.8207

y = 0.0027x

0%

5%

10%

15%

20%

25%

30%

0 10 20 30 40 50

Sw,bv (%)

Age (years)

< 5km ≥ 5km

y = 7E-05x2 + 0.001x R² = 0.8005

y = 4E-06x3 - 0.0001x2 + 0.0039x R² = 0.7374

0%

5%

10%

15%

20%

25%

30%

0 10 20 30 40 50

Sw,bv (%)

Age (years)

Protegido Corrente Protected Current

y = 6E-06x3 - 0.0003x2 + 0.0052x R² = 0.8424

y = 3E-06x3 - 6E-05x2 + 0.0028x R² = 0.7278

0%

5%

10%

15%

20%

25%

30%

0 10 20 30 40 50

Sw,bv (%)

Age (years))

Corrente Desfavorável Current Adverse

8

sea (at more than 5 km), in order to obtain a more homogeneously sample, intending to obtain a better

correlation between the degradation curves and the real degradation (observed during fieldwork). The

results obtained in this study can also be applied with the factor method, which allows validating the

work developed in this study. Other proposal for future work is to evaluate the perception related with

the severity of degradation, through surveys among owners of the buildings inspected, to understand

whether the severity defined in this work to establish the end of the architectural concrete service life

is in accordance with the owners’ perception and demands.

Table 7 - Expected service life (ESL) of architectural concrete façades

Façades characterisation ESL (years) Façades characterisation ESL

(years) Alignment N 43 Distance to the sea < 5 km 45

NE / E / SE 45 ≥ 5 km - W / NW 46 Wind-rain expo-

sure Protected 46

S / SW 44 Current 45 Protection type

Without protection 46 Colour Light 47

Water repellent 41 Dark 42

Paint 38 Exposure to damp

Current 46 Paint + Water re-pellent 52 Adverse 42

Varnish -

Bibliography Architectural Institute of Japan (1993), The English edition of principal guide for service life planning of

buildings, AIJ, Tokyo.

AS 3600 (2009), Concrete structures, Committee BD-002, Australia.

ASTM E632-82 (1996), Standard practice for developing accelerated tests to aid prediction of the service

life of building components and materials, American Society for Testing and Materials, Pennsylvania.

Branco, F.; Brito, J. de (1990), The service life of concrete structures - Considerations for their characteri-

zation (in Portuguese), Portuguese Journal of Structural Engineering, No. 30, Lisbon, pp. 29-34.

Brito, J. de (1987), Pathology of concrete structures - degradation, evaluation and service life prediction

(in Portuguese), Master's Thesis in Structural Engineering, Instituto Superior Técnico , Technical Universi-

ty of Lisbon, Lisbon.

Chai, C.; Brito, J. de; Gaspar, P. L.; Silva, A. (2014), Predicting the service life of exterior wall paint-

ing: techno-economic analysis of alternative maintenance strategies, Journal of Construction Engi-

neering and Management, V. 140, No. 3, CD-ROM.

Chai, C.; Brito, J. de; Gaspar, P. L.; Silva, A. (2015), Statistical modelling of the service life prediction of

painted surfaces, International Journal of Strategic Property Management, V. 19, No. 2, pp. 173-185.

Committee 305 (1999), Hot weather concreting, ACI 305R-99, American Concrete Institute, Michigan.

Emídio, F.; Brito, J. de; Gaspar, P.; Silva, A. (2014), Application of the factor method to the estimation of

the service life of natural stone cladding, Construction and Building Materials, V. 66, pp. 484-493.

9

Ferreira, R. (2006), Optimizing the service life of reinforced concrete structures (in Portuguese), 4th

Portuguese Journeys of Structural Engineering, Lisbon, pp. 1-16.

Gaspar, P. (2002), Methodology to determine the durability of current exterior renders (in Portu-

guese). Masters Dissertation in Construction. Instituto Superior Técnico, Technical University of Lis-

bon, Lisbon.

Gaspar, P.; Brito, J. de (2005), Assessment of the overall degradation level of an element, based on

field data, 10th DBMC International Conference on Durability of Building Materials and Components,

Lyon, pp. 1043-1050.

Gaspar, P. (2009), Service life of buildings: methodology for service life prediction of building compo-

nents. Application to external cement-renders (in Portuguese). Doctoral Dissertation in Engineering Sci-

ences. Instituto Superior Técnico, Technical University of Lisbon, Lisbon.

Gaspar, P.; Brito, J. de (2011), Limit states and service life of cement renders on façades, Journal of Ma-

terials in Civil Engineering, V. 23, n.º 10, pp. 1393-1404.

Guerrero, A.; Gutiérrez, R.; Correia, M. (2016), Corrosion performance of blended concretes exposed to

different aggressive environments, Construction and Building Materials, V. 121, pp. 704-716.

Hobbs, D. W. (2002), The durability of concrete, in Hewlett, P.; Oldham, P.; Nixon, P.; Taylor, G.; Perkis,

L., The institute of concrete technology. Yearbook: 2002-2003, Engineering Council, Crowthorne.

ISO 15686-1 (2011), Buildings and constructed assets. Service life planning. Part 1: General principles

and framework, International Organization for Standardization, Switzerland.

Łowinska-Kluge, A.; Błaszczynski, T. (2012), The influence of internal corrosion on the durability of

concrete, Archives of Civil and Mechanical Engineering, V. 12, pp. 219 - 227.

Marques, C. (2016), Application of the factor method to the service life prediction of ETICS (in Portu-

guese). Masters Dissertation in Civil Engineering. Instituto Superior Técnico, Technical University of

Lisbon, Lisbon.

Marteinsson, B.; Jónsson, B. (1999), Overall survey of buildings - performance and maintenance, 8th

DBMC, pp. 1634-1654.

NP EN 206-1 (2007), Concrete - Part 1: Specification, performance, production and conformity (in

Portuguese), IPQ - Portuguese Institute of Quality, Caparica, Portugal.

PWGSC RPS, Technology & Environment (1997), Durability guidelines for building wall envelopes,

Public Works and Government Services Canada, Real Property Services, Technology and Environmen-

tal Services, Canada, 202 p.

Secil (2011), White concrete. Elements for the preparation of technical clauses of works contract doc-

uments in white concrete (in Portuguese), available on: http://issuu.com/globept/docs/cl-usulas-t-

cnicasbook/ 2, (consulted on12th November of 2015).

Silva, A.; Brito, J. de; Gaspar, P. L. (2011a); Service life prediction model applied to natural stone wall

10

claddings (directly adhered to the substrate), Construction and Building Materials, V. 25, pp. 3674-3684.

Silva, A.; Dias, J.; Gaspar, P.; Brito, J. de (2011b), Service life prediction models for exterior stone

cladding, Building Research and Information, V. 39, No. 6, pp. 637-653.

Silva, C. (2015), System of inspection and diagnostic of anomalies on architectural concrete’s facades (in

Portuguese), Masters Dissertation in Civil Engineering, Instituto Superior Técnico, Technical University

of Lisbon, Lisbon.

Sousa, R. (2008), Prediction of the service life of external ceramic wall tiling laid on mortar or adhesive

(in Portuguese), Masters Dissertation in Civil Engineering, Instituto Superior Técnico, Technical Univer-

sity of Lisbon, Lisbon.

Takahashi, T.; Sekine, E.; Horiike, T.; Matsuoka, S.; Hoshiro, H. (2008), Study on the applicability of

short fiber reinforced concrete to precast concrete slabs for slab track, Quality Report of RTRI, V.

39, No. 1, pp. 40-46.

Ximenes, S.; Brito, J. de; Gaspar, P.; Silva, A. (2015), Modelling the degradation and service life of

ETICS in external walls, Materials and Structures, V. 48, No. 7, pp. 2235-2249.