HYBRID FIBRE RUBBERIZED ECC OPTIMIZATION FOR MODULUS …€¦ · combination of fibers facilitated...

http://www.iaeme.com/IJCIET/index.asp 918 [email protected]

International Journal of Civil Engineering and Technology (IJCIET)

Volume 9, Issue 7, July 2018, pp. 918–928, Article ID: IJCIET_09_07_096

Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=9&IType=7

ISSN Print: 0976-6308 and ISSN Online: 0976-6316

© IAEME Publication Scopus Indexed

HYBRID FIBRE RUBBERIZED ECC

OPTIMIZATION FOR MODULUS OF

ELASTICITY

Veerendrakumar C Khed*, Bashar S Mohammed*, Mohd Shahir Liew,

Wesam S Alaloul, Musa Adamu

Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS,

32610 Bandar Seri Iskandar, Perak Darul Ridzuan, Malaysia

*Corresponding Author Email ID: [email protected] and

[email protected]

ABSTRACT

Optimization using the response surface methodology (RSM) for the modulus of

elasticity utilizing crumb rubber in partial replacement with the sand along with the

incorporation of hybrid fibers such as PVA and tirewire in engineered cementitious

composites (ECC). The crumb rubber in ECC ensured the homogeneous dispersion of

fibers and also restricted the fracture toughness of the matrix. An appropriate hybrid

combination of fibers facilitated in balancing the ultimate strength, strain capacity

and crack width with the proper volume of PVA and tirewire fibre. The modulus of

elasticity for hybrid combination was more than the ECC with only PVA fibers and in

meanwhile the tirewire fibers balanced the negative effect due to the crumb rubber

and PVA fibers on modulus of elasticity. RSM aided in optimizing the ingredients in

the ECC to achieve better performance of the ECC material. RSM optimized results

using ANOVA (Analysis of variance) was experimentally verified and it was found that

less than 5% of the difference in the results with the desirability of 1.

Key words: Crumb rubber, ECC, Hybrid fibers, Tirewire, PVA.

Cite this Article: Veerendrakumar C Khed, Bashar S Mohammed, Mohd Shahir

Liew, Wesam S Alaloul, Musa Adamu, Hybrid Fibre Rubberized ECC Optimization

for Modulus of Elasticity, International Journal of Civil Engineering and Technology,

9(7), 2018, pp. 918–928.

http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=9&IType=7

1. INTRODUCTION

Engineered cementitious composite (ECC) is a type of strain hardening behavior

supplemented by the multiple cracks leading towards high strength and better tensile ductility.

ECC is referred as a cement oriented composite which has an ultimate strength greater than

the first crack strength. ECC is known to have tensile strain capacity of about 2 to 5% and

have an average of 60 µm crack width develops when it is strained past 1%. These properties

could be attained by utilizing the high modulus fibers at an optimum volume fractions. ECC

Veerendrakumar C Khed, Bashar S Mohammed, Mohd Shahir Liew, Wesam S Alaloul, Musa Adamu


has industrial application in a broader range which there a need for higher load carrying

capacity, better deformability and good energy absorption capacity under reverse cyclic and

monotonic loadings. These kinds of high performance along with the moderate fibre

combination are achieved through the micromechanics based optimization theory.

The major components of the conventional ECC are cement, fly ash, fine aggregate,

fibers, water with high range water reducers (HRWR). Polyvinyl alcohol (PVA) fibers are the

most commonly used fibers in ECC. The mechanical properties of ECC depend on fibre type,

shape and volume fraction of fibers. The incorporation of fibers improves the strength and

strain abilities along with the energy absorption capabilities. The fibers such as

polypropylene, PVA (E≈40GPa), polyethylene (E≈66GPa) are the low modulus fibers when

compared to the steel fibre (E≈200GPa) which has a high modulus of elasticity. The low

modulus fibers increase the strain capacity along with the ductility of the ECC members

significantly where as high modulus fibers such as steel, carbon, glass fibers enhance the

toughness and the bulk strength of the ECC material, however, their inherent brittle property

does not permit for ductility and strain hardening [1]. PVA in ECC provides better ductility

property which aids in overcoming the brittle behavior of the conventional concrete [2]. It was

observed that the mechanical properties of the ECC can be enhanced by incorporating the

hybrid fibers in the form of the low and high modulus of elasticity with an appropriate volume

[3, 4]. The impact resistance can be increased by using hybrid fibers such as the low modulus

fibers with strain capacity for the energy absorption and high modulus fibre with the high

tensile strength for the penetration resistance, both together helps in improving the impact

resistance [5].

In the past substantial research have been performed on the mechanical properties and

structural behavior of ECC, however most of the studies were carried out for the mono fibre

reinforced ECC material and very limited number of researchers have worked on hybridized

fibre reinforced ECC. The steel and PE fibers were used as hybrid fibers in ECC to study the

tensile strain hardening behavior and it was observed that hybrid ECC material shown better

tensile strength capacity in comparison to the ECC reinforced with the only PE fibers and in

the same study hybrid reinforced ECC shown higher tensile strain capacity than the ECC

reinforced with steel fibre alone [6]. The combination of PVA and shape memory alloy

(SMA) as hybrid fibers in ECC improved the tensile and flexural capacity of the ECC

significantly about 59 % and 97% respectively when compared with the ECC reinforced with

only PVA fibers [7]. The polypropylene and PVA hybridization in ECC enhanced the

toughness ratio and met the necessities of strain hardening with the multiple cracking and the

compressive strength was varied between 85 to 95 MPa [8]. The polypropylene and steel

hybridized fibers in ECC improved the compressive strength, flexural strength and splitting

tensile strength, modulus of elasticity, and reduced crack width [9]. The tirewire which also

called recycled fibers was used in concrete up to 1% had led to the reduction of pavement

thickness to 16% [10]. The recycled fibers in the form of tirewire had improved the

compressive strength and modulus of elasticity and energy absorption capacity for the fibre

reinforced rubberized concrete [11]. The concrete prepared with recycled fibers had shown

better improvement interms of shear behavior and toughness when compared with the

concrete reinforced with the industrial fibers [12]. A positive synergetic effect were improved

for the hybrid fibers in the form of recycled fibers and the manufactured steel fibre reinforced

concrete [13]. The nanosilica incorporated ECC was increased the modulus of elasticity by

maintaining the anticipated ductility due to the PVA [14]. Crumb rubber inclusion reduces the

modulus of elasticity however it helps in enhancing the workability [15]. The crumb rubber

reduced the modulus of elasticity in concrete however it aided in enhancing the deformable

capacity of concrete members [16]. Loss of modulus of elasticity in rubberized concrete can

Hybrid Fibre Rubberized ECC Optimization for Modulus of Elasticity


be mitigated by incorporating the nano-silica [17]. Rubberized concrete in hollow blocks

provides better resistance for acoustic, electrical and thermal conductivity [18]. The palm oil

clinker was used in concrete which produced a light weight concrete of strength 20 MPa [19,

20].

Many studies have been conducted using Response surface methodology (RSM)

technique for designing the experiments across various fields such as chemical industry,

concrete technology and in many other Engineering designs. In concrete experimental design

number of variables were interacted in order to influence the responses [21]. In geopolymer

concrete mixture was designed using RSM for the responses as slump flow and compressive

strength [22]. The concrete mix design for the inclusion of metakaolin was performed by

RSM regression analysis to obtain the optimum mix proportion in order to achieve the better

performance [23]. RSM experimental design was also extended to develop the pervious

concrete paste fort the accurate dosage of the admixtures [24]. RSM was also used to optimize

the hybrid fibre proportions appropriately for designing the self-compacting concrete mixtures

[25]. The strength reduction factors can also be incorporated as prescribed for the rubbercrete

mixtures [26].

In this research, the mix proportions for Hybrid fibre-reinforced rubberized engineered

cementitious composites (HFRECC) have been designed using RSM for the modulus of

elasticity as the response through the interaction of the variables mainly cement, fly ash, sand

replaced with the crumb rubber, PVA and tirewire fibers have been studied.

2. EXPERIMENTAL PROGRAM

2.1. Materials and Properties

Type I Ordinary Portland cement (OPC) conform to the ASTM C150 (Standard Specification

for Portland cement) has been incorporated for the preparation of HFRECC mixtures. The

specific gravity and surface area of cement are between 3.15 and 295 m2/kg correspondingly.

Class F fly ash (FA) which has the total oxide content of 82.12% i.e. Aluminum (Al2O3), iron

(Fe2O3), and silicon (SiO2). FA has less than 6% of the loss on ignition according to the

ASTMC 618 (Standard Specification for Coal Fly Ash and Raw or Calcined Natural Pozzolan

for Use in Concrete). The cleaned river sand of sieve size ranging from 300 µm to 1.18 mm

having the specific gravity of 2.65. Crumb rubber was used in partial replacement with the

fine aggregate ranged from zero to 30% of size 30 mesh and 1 to 3 mm in the appropriate

mixed proportion of 60% and 40%. The particle size distributions of the crumb rubber and

sand are shown in Figure 1. Cleaned tap water for mixing the composite was utilized in

accordance with the ASTM C1602 along with the polycarboxylic induced superplastisizer

“Sika Viscocrete 2044”. The hybrid fibre reinforcement was used in the ECC mix in the form

of PVA and tirewires (steel wires from waste tyres). The fibre mechanical properties are

mentioned in Table 1.

Table 1. The chemical arrangement of the cementitious materials

Type Specific

gravity

Length

of

fibre

(mm)

Diameter

of fibre

(µm)

Aspect

ratio (l/d)

Tensile

strength

(MPa)

Modulus

of

Elasticity

(GPa)

PVA 1.3 12 40 462 1600 41

Tirewire 7.85 10 to 35 11 to 43 600(Average) >1200 200



Figure 1 Particle size distributions

2.2. Design of Experiments

The experimental design was carried out through the response surface methodology (RSM) of

central design composite (CCD). RSM is a statistical method which involves the statistical

analysis where the response is interrelated with the variables to estimate the interaction,

relationship, and their effects. The analysis of RSM consists of designing the experimental

runs thereby collecting the results in the form of response, then validating the response

surface models in order to optimize the responses [25]. The statistical model provides better

mix design tool for the concrete containing wood chipping which is partially replaced with the

fine aggregate [27]. The statistical model delivers useful and appropriate models to predict the

responses [28]. In the present study the Design expert software version 10 has been used to

optimize the modulus of elasticity for HFRECC for the five variables such as cement, fly ash,

crumb rubber, PVA, and tirewire. CCD is the most normally used design method in the RSM

which comprises of factorial design, where central points are enlarged by the star points and

thereby enhancing the variable space to estimate the quadratic terms [29, 30].

The variables cement, fly ash, crumb rubber partial volume replacement to the sand, PVA

and tirewire fibres in the ranges are shown in the Table 2. These five variables were

incorporated and developed 50 mix proportions in the CCD interacted in order to optimize the

response as modulus of elasticity. The CCD produced the 50 experimental runs by using the

five variables as prescribed in Table 3. The CCD should be rotatable with second-order

response surfaces as recommended by BOX and Hunter in 1957. The CCD can be made

rotatable by choosing the axial run α from design centre model [31]. The description of the

CCD is shown in Figure 2.

Figure 2 CCD Design Model

0.010.020.030.040.050.060.070.080.090.0

100.0

0.01 0.1 1 10 100

Per

cen

t p

assi

ng

%

Sieve size (mm)

1-3mm

30 mesh

Sand



The optimum conditions were determined by selecting an appropriate model which

explains the response surface. Thus, in this case, the quadratic equation models were selected

[14], which is as shown in the equation (1).

∑ ∑

∑ ∑

(1)

Where, y is the response which is the modulus of elasticity, are the coded values for

the variables, be the linear co-efficient, indicates the quadratic co-efficient, represents

regression co-efficient, represents number of factors and indicates the random error. An

appropriate model was chosen, so that the response surface can be well defined. The

responses were analysed thus, a fitting model (linear, quadratic or cubic) was selected.

Table 2. Mix proportions

Objectives Factors Unit Low level (-1) High level (+1)

Mix

proportions

Cement kg/m3 350 650

Fly ash kg/m3 500 850

Crumb rubber % 0 30

Tirewire % 0 0.5

PVA % 0 1.5

3. RESULTS AND DISCUSSION

3.1. Experimental Results

Structural application of the concrete largely depends on the on compressive strength, intern

which is influenced by the constituent material used. In the current study the compressive

strength test was carried out according to the requirements of BS EN 12390-3:2009 (Testing

hardened concrete. Compressive strength of test specimens). The inclusion of CR particles

has led to the presence of voids in the rubbercrete microstructure due to its hydrophobicity

and thus CR replacement adversely affecting the compressive strength. Modulus of elasticity

is the quantity used to measure the deformation resisting capacity of the concrete which is

defined as the ratio between stress and strain within the elastic limit. Modulus of elasticity for

the concrete is an important parameter which is influenced by a number of factors, among

them are compatibility of concrete, size, shape and type of aggregate, binding material,

aggregate modulus and the interfacial transition zone [32]. The elastic modulus test was

conducted according to the requirements of ASTM C 469 (Standard Test Method for Static

Modulus of Elasticity and Poisson’s Ratio of Concrete in Compression). Modulus of elasticity

of concrete has strong correlation with the compressive strength. In past researchers have

suggested several equations for various types of concrete to denote the correlation. These

equations were developed on the basis of experimental study [33]. The equation to estimate

the modulus of elasticity was developed for the rubberized concrete for different w/c ratio

[16]. The results of compressive strength and modulus of elasticity for the fifty experimental

runs are depicted in Figure 3. The correlation between the compressive strength and modulus

of elasticity has been found with an R-squared approaching to unity (co-efficient of

determination value of 0.93) which is shown in the Figure 4. It indicates that the modulus of

elasticity is well agreement with the compressive strength. In this case the modulus of

elasticity inversely proportional to the crumb rubber, fly ash and directly proportional to the

cement, tirewire and PVA fibers. This is due the ability of fibers to confine the internal

microstructure of HFRECC matrix which improve the toughness and consequently leads to

the enhancement of modulus of elasticity.



Figure 3 Experimental results for Compressive strength and Modulus of Elasticity

Figure 4 Correlation between Compressive strength and Modulus of Elasticity

3.2. RSM Analysis

RSM analysis contributed the model for response surface which replicates the consequence of

factors. The obtained model is of second order which is more precise than the first order

model because of the capability to determine the optimum number of individual factor

accurately [25]. Therefore, the second-order model has been established to correlate between

the variables cement, fly ash, crumb rubber, tirewire and PVA using the ANOVA (Analysis

of variance) and it is found to be the best fit according to the output of modulus of elasticity

and which can be predicted. The ANOVA model equation is as shown in Eq (2).

Modulus of Elasticity (GPa) = 41.232 + 0.00434768 * A - 0.055748 * B - 0.13586 * C +

2.3668 * D + 0.66577 * E + 0.00000254163 * A * B + 0.000104093 * A * C - 0.00511165 *

A * D + 0.00045975 * A * E - 0.000104494 * B * C - 0.000444825 * B * D - 0.000929125

* B * E + 0.01249 * C * D + 0.00467017 * C * E + 0.27113 * D * E + 0.00000400217 * A *

A + 0.0000377 * B * B + 0.00145659 * C * C + 1.03416 * D * D - 0.18516 * E * E… (2)

Terms in the ANOVA equation indicates that A = Cement in kg/m3, B = Fly ash in kg/m

3,

C = Crumb rubber in %, D = Tirewire in %, E = PVA in %.

The results of modulus elasticity are graphically shown in the Figures 5. The 3D surface

diagrams indicate the variation of response modulus of elasticity for the different variables, it

can be observed that the crumb rubber has a negative effect on the modulus of elasticity,

contrarily the cement and tirewire fibers have contributed positively toward the enhancement

of modulus of elasticity.

0

20

40

60

80

100

M1

M3

M5

M7

M9

M1

1

M1

3

M1

5

M1

7

M1

9

M2

1

M2

3

M2

5

M2

7

M2

9

M3

1

M3

3

M3

5

M3

7

M3

9

M4

1

M4

3

M4

5

M4

7

M4

9

Compressive strength Modulus of Elasticity

y = -0.0004x2 + 0.2655x + 12.183 R² = 0.9394

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

40 50 60 70 80 90 100

MO

DU

LUS

OF

ELA

STIC

ITY

COMPRESSIVE STRENGTH



Design-Expert® SoftwareFactor Coding: ActualYoungs Modulus (MPa)

Design points above predicted valueDesign points below predicted value27.4135

19.2

X1 = C: Crumb rubberX2 = D: Tirewire

Actual FactorsA: Cement = 500B: Fly ash = 750E: PVA = 0.75

0

0.1

0.2

0.3

0.4

0.5

0 6

12 18

24 30

18

20

22

24

26

28

Yo

un

gs M

od

ulu

s (

MP

a)

C: Crumb rubber (%)

D: Tirewire (%)

Design-Expert® SoftwareFactor Coding: ActualYoungs Modulus (MPa)

Design points above predicted valueDesign points below predicted value27.4135

19.2

X1 = A: CementX2 = C: Crumb rubber

Actual FactorsB: Fly ash = 750D: Tirewire = 0.25E: PVA = 0.75

0 6

12 18

24 30

350

410

470

530

590

650

18

20

22

24

26

28

Yo

un

gs M

od

ulu

s (

MP

a)

A: Cement (kg/m3)

C: Crumb rubber (%)

Figure 5 3D Surface diagram for variables crumb rubber, cement , tirewire

3.3. ANOVA Model Validation

The model has been statistically validated. It has been witnessed that the ANOVA model is

significant and most of the terms are also significant and are valid since the values of

“Probability > F” is less than 5% (i.e. α = 0.05, 1-α = 0.95, which means 95% of interval

confidence) thus it explains that greater than 95% of confidence level. The term lack of fit is

not significant, that indicates that the model is fit for the analysis.

From Table 3, it is noticed that the standard deviation less than 1%, thus it indicates that

less than 1% of variation from the mean value. The regression value of R-squared is 0.9796,

which is almost approaching to unity, which indicates data are fitted to the regression line.

The difference between the predicted R-squared and adjustable R-squared is less than 0.2 i.e.

Difference of less than 20%, which indicates the model has a reasonable agreement for the

prediction of the results

Table 3. Validation of model terms

Response/Model Terms Values

Std. Dev. 0.41

Mean 23.36

C.V. % 1.74

PRESS 10.06

-2 Log Likelihood 24.55

R-Squared 0.9796

Adj R-Squared 0.9656

Pred R-Squared 0.9572

Adeq Precision 29.66

BIC 106.7

AICc 99.55

Graphically from Figure 6 shows that points are normally distributed on 450

straight line,

this evaluates that the points are normally distributed and there is less chance of varying the

actual results with the results predicted. Figure 6 shows the residual versus predicted, which

indicates that the predicted response by the model is accurate as the points within the upper

and lower limits.



…

Figure 6 Normal distribution diagrams

The drifts in the model are tested using the “Run order” residual plots which is a special

type of plot where the residuals indicate the composition of the data as described in Figure 7.

This plot is helpful, however, only if data have been collected in a randomized run order, or

some other order that is not increasing or decreasing in any of the predictor variables used in

the model. The even spread of the residual across the range of the data indicates that there is

no apparent drift in this process.

Figure 7 Run order Residuals

4. OPTIMIZATION AND EXPERIMENTAL VALIDATION

The optimization technique is a study of finding the best solution by analyzing the multiple

objectives simultaneously through the incorporation of RSM. A common response surface

experimental scheme which is used for setting the optimal solution for the variables is the

CCD method. In different regions, the optimal values are localized it could be challenging to

find the situation that concurrently satisfies the response. The level of difficulty increases as

the optimum region widens from each other and will not intersect. It is not occasional for the

case where all surfaces found. The desirability function is one of the most significant multi

criteria methodology. The scale of the individual desirability function ranges from zero to 1,

where zero indicates the fully adverse response and as it moves towards 1, it said to be

desirable. The optimization for the multiple variables have been performed by selecting the

target strength for the preferred ranges of variables. The RSM optimized results have been

validated by performing the experiments in the laboratory. The specimens were casted for the

three optimized mixes and it was found that a less than 5% of the variation between the RSM

optimized results and experimentally obtained results as tabulated in Table 4.

Design-Expert® SoftwareYoungs Modulus

Color points by value ofYoungs Modulus:

27.4135

19.2

Predicted

Inte

rnal

ly S

tude

ntiz

ed R

esid

uals

Residuals vs. Predicted

-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

18 20 22 24 26 28

3

-3

0

Design-Expert® SoftwareYoungs Modulus

Color points by value ofYoungs Modulus:

27.4135

19.2

Run Number

Inte

rnal

ly S

tude

ntiz

ed R

esid

uals

Residuals vs. Run

-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

1 8 15 22 29 36 43 50

3

-3

0



Table 4. Experimental Validation

Type Validation

Ceme

nt

kg/m3

Fly

ash

in

kg/m3

Crumb

rubber

in %

PV

A in

%

Tirew

ire in

%

Compressi

ve strength

in MPa

Modulus of

Elasticity

in GPa

Desirabilit

y

HFRE

CC

Optimizati

on

650 662 30 0.5 1.5

60 24.02

1 Experiment

al 58 23.2

Variation

% 3.45 3.53

Optimizati

on

350 650 0 0.5 1.5

63.5 23.95

1 Experiment

al 60.6 23

Variation

% 4.78 4.13

Optimizati

on

470 652 30 0 0

49.8 20.26

1 Experiment

al 48 19.5

Variation

% 3.75 3.89

5. CONCLUSIONS

The higher modulus of elasticity can be attained by using hybridized fibers, where the tirewire

fibre helps in producing higher modulus of elasticity and PVA fibre along with crumb assists

in maintaining the strain capacity of the HFRECC material. The relation between the

compressive strength and the modulus of elasticity have been developed using the regression

model with the R-squared value of 0.9394. RSM models to predict modulus of elasticity of

rubberized hybrid reinforced ECC based on the amount of five variable have been developed

with ANOVA of more than 95% significance level. The difference between Adjusted R2 and

Predicted R2 is less than 0.2. From model’s validation, the difference between findings in the

optimized RSM and the experimental results is less than 5% with desirability function 1

REFERENCES

[1] K. T. Soe, Y. Zhang, and L. Zhang, Material properties of a new hybrid fibre-reinforced

engineered cementitious composite, Construction and Building Materials, 43, 2013, pp.

399-407.

[2] B. S. Mohammed, M. Aswin, W. H. Beatty, and M. Hafiz, "Longitudinal shear resistance

of PVA-ECC composite slabs," in Structures, 2016, vol. 5, pp. 247-257: Elsevier.

[3] J. Zhang, M. Maalej, and S. T. Quek, Performance of hybrid-fiber ECC blast/shelter

panels subjected to drop weight impact, Journal of Materials in Civil Engineering, 19,

2007, 10, pp. 855-863.

[4] M. Maalej, S. T. Quek, and J. Zhang, Behavior of hybrid-fiber engineered cementitious

composites subjected to dynamic tensile loading and projectile impact, Journal of

Materials in Civil Engineering, 17, 2005, 2, pp. 143-152.

[5] L. Zhang, "Impact resistance of high strength fiber reinforced concrete," University of

British Columbia, 2008.



[6] S. Ahmed and M. Maalej, Tensile strain hardening behaviour of hybrid steel-polyethylene

fibre reinforced cementitious composites, Construction and Building Materials, 23, 2009,

1, pp. 96-106.

[7] M. Ali and M. Nehdi, Innovative crack-healing hybrid fiber reinforced engineered

cementitious composite, Construction and Building Materials, 150, 2017, pp. 689-702.

[8] H. R. Pakravan, M. Jamshidi, and M. Latifi, Study on fiber hybridization effect of

engineered cementitious composites with low-and high-modulus polymeric fibers,

Construction and Building Materials, 112, 2016, pp. 739-746.

[9] N. G. Manvi and A. A. Kumar, Evaluation of Mechanical Properties of Hybrid Engineered

Cementitious Composite (HECC), Materials Today: Proceedings, 4, 2017, 9, pp. 9856-

9859.

[10] M. Ahmadi, S. Farzin, A. Hassani, and M. Motamedi, Mechanical properties of the

concrete containing recycled fibers and aggregates, Construction and Building Materials,

144, 2017, pp. 392-398.

[11] Y.-c. Guo, J.-h. Zhang, G.-m. Chen, and Z.-h. Xie, Compressive behaviour of concrete

structures incorporating recycled concrete aggregates, rubber crumb and reinforced with

steel fibre, subjected to elevated temperatures, Journal of cleaner production, 72, 2014,

pp. 193-203.

[12] M. Leone, G. Centonze, D. Colonna, F. Micelli, and M. Aiello, Fiber-reinforced concrete

with low content of recycled steel fiber: Shear behaviour, Construction and Building

Materials, 161, 2018, pp. 141-155.

[13] H. Hu, P. Papastergiou, H. Angelakopoulos, M. Guadagnini, and K. Pilakoutas,

Mechanical properties of SFRC using blended manufactured and recycled tyre steel fibres,


[14] B. S. Mohammed, B. E. Achara, M. F. Nuruddin, M. Yaw, and M. Z. Zulkefli, Properties

of nano-silica-modified self-compacting engineered cementitious composites, Journal of

cleaner production, 162, 2017, pp. 1225-1238.

[15] B. S. Mohammed and M. Adamu, Mechanical performance of roller compacted concrete

pavement containing crumb rubber and nano silica, Construction and Building Materials,

159, 2018, pp. 234-251.

[16] B. Mohammed and N. J. Azmi, Failure mode and modulus elasticity of concrete

containing recycled tire rubber, The Journal of Solid Waste Technology and Management,

37, 2011, 1, pp. 16-24.

[17] B. S. Mohammed, A. B. Awang, S. San Wong, and C. P. Nhavene, Properties of nano

silica modified rubbercrete, Journal of cleaner production, 119, 2016, pp. 66-75.

[18] B. S. Mohammed, K. M. A. Hossain, J. T. E. Swee, G. Wong, and M. Abdullahi,

Properties of crumb rubber hollow concrete block, Journal of Cleaner Production, 23,

2012, 1, pp. 57-67.

[19] B. S. Mohammed, W. Foo, K. Hossain, and M. Abdullahi, Shear strength of palm oil

clinker concrete beams, Materials & Design, 46, 2013, pp. 270-276.

[20] M. Abdullahi, H. Al-Mattarneh, A. A. Hassan, M. H. Hassan, and B. Mohammed, "Trial

mix design methodology for Palm Oil Clinker (POC) concrete," in The International

Conference on Construction and Building Technology in Kuala Lumpur, 2008.

[21] D. C. Montgomery, Response surface methods and other approaches to process

optimization, Design and analysis of experiment, 1997, pp. 427-510.



[22] M. Jo, L. Soto, M. Arocho, J. St John, and S. Hwang, Optimum mix design of fly ash

geopolymer paste and its use in pervious concrete for removal of fecal coliforms and

phosphorus in water, Construction and Building Materials, 93, 2015, pp. 1097-1104.

[23] H. S. Al-alaily and A. A. Hassan, Refined statistical modeling for chloride permeability

and strength of concrete containing metakaolin, Construction and Building Materials,

114, 2016, pp. 564-579.

[24] B. E. Jimma and P. R. Rangaraju, Chemical admixtures dose optimization in pervious

concrete paste selection–A statistical approach, Construction and Building Materials,

101, 2015, pp. 1047-1058.

[25] E. Ghafari, H. Costa, and E. Júlio, RSM-based model to predict the performance of self-

compacting UHPC reinforced with hybrid steel micro-fibers, Construction and Building

Materials, 66, 2014, pp. 375-383.

[26] B. S. Mohammed and N. Azmi, Strength reduction factors for structural rubbercrete,

Frontiers of Structural and Civil Engineering, 8, 2014, 3, pp. 270-281.

[27] B. S. Mohammed, M. Abdullahi, and C. Hoong, Statistical models for concrete containing

wood chipping as partial replacement to fine aggregate, Construction and building

materials, 55, 2014, pp. 13-19.

[28] B. S. Mohammed, O. C. Fang, K. M. A. Hossain, and M. Lachemi, Mix proportioning of

concrete containing paper mill residuals using response surface methodology,


[29] B. S. Mohammed, V. C. Khed, and M. F. Nuruddin, Rubbercrete mixture optimization

using response surface methodology, Journal of Cleaner Production, 171, 2018, pp.

1605-1621.

[30] V. C. Khed, B. S. Mohammed, and M. F. Nuruddin, "Effects of different crumb rubber

sizes on the flowability and compressive strength of hybrid fibre reinforced ECC," in IOP

Conference Series: Earth and Environmental Science, 2018, vol. 140, no. 1, p. 012137:

IOP Publishing.

[31] B. S. Mohammed, Z. I. Syed, V. Khed, and M. S. Qasim, Evaluation of Nano-Silica

Modified ECC Based on Ultrasonic Pulse Velocity and Rebound Hammer, The Open Civil

Engineering Journal, 11, 2017, 1.

[32] R. V. Silva, J. de Brito, and R. K. Dhir, Establishing a relationship between modulus of

elasticity and compressive strength of recycled aggregate concrete, Journal of cleaner

production, 112, 2016, pp. 2171-2186.

[33] A. Alsalman, C. N. Dang, G. S. Prinz, and W. M. Hale, Evaluation of modulus of

elasticity of ultra-high performance concrete, Construction and Building Materials, 153,

2017, pp. 918-928.

HYBRID FIBRE RUBBERIZED ECC OPTIMIZATION FOR MODULUS …€¦ · combination of fibers facilitated...

Documents

Transcript of HYBRID FIBRE RUBBERIZED ECC OPTIMIZATION FOR MODULUS …€¦ · combination of fibers facilitated...