Application of statistical models in proportioning lightweight self-consolidating concrete with expanded clay aggregates

Construction and Building Materials 65 (2014) 450–469

Contents lists available at ScienceDirect

Construction and Building Materials journal homepage: www.elsevier.com/locate/conbuildmat

Application of statistical models in proportioning lightweight self-consolidating concrete with expanded clay aggregates Abdurrahmaan Lotfy a, Khandaker M.A. Hossain b,⇑, Mohamed Lachemi b a b

Lafarge Canada Inc., Toronto, Ontario, Canada Department of Civil Engineering, Ryerson University, 350 Victoria St., Toronto, Ontario M5B 2K3, Canada

h i g h l i g h t s  Developed statistical models for proportioning of expanded clay aggregate LWSCCs.  Evaluated the influence of mix design parameters on the properties of LWSCCs.  Mix design parameters are optimized for satisfactory LWSCC properties.  Robust LWSCC mixtures satisfying EFNARC criteria are proposed.  Proposed models are useful tools for designing LWSCCs for practical applications.

a r t i c l e

i n f o

Article history: Received 13 November 2013 Received in revised form 6 May 2014 Accepted 14 May 2014

Keywords: Lightweight self-consolidating concrete Expanded clay aggregates Multi-objective optimization Optimum mix proportions Statistical model

a b s t r a c t A response surface method based experimental study was carried out to model the influence of key parameters on the properties of Lightweight Self-Consolidating Concrete (LWSCC) mixtures developed with expanded clay (EC) aggregates. Three key mix design parameters were selected to derive mathematical models for evaluating fresh and hardened properties. Water to binder ratio of 0.30–0.40, high range water reducing admixture (HRWRA) of 0.3–1.2% (by total content of binder) and total binder content of 410–550 kg/m3 were used for the design of and testing of twenty LWSCC mixtures. Slump flow diameter, V-funnel flow time, J-ring flow diameter, J-ring height difference, L-box ratio, filling capacity, sieve segregation, fresh/28-day air/oven dry unit weights and 7- and 28-day compressive strengths were evaluated to analyze influence of mix design parameters and develop the models. Utilizing the developed models, three optimum expanded clay LWSCC (EC-LWSCC) mixtures with high statistical desirability were formulated and tested. It was possible to produce robust EC-LWSCC mixtures that satisfy the European EFNARC criteria for Self-Consolidating Concrete (SCC). The proposed mix design models are proved to be useful tools for understanding the interactions among mixture parameters that affect important characteristics of EC-LWSCCs. This understanding might simplify the mix design process and the required testing, as the model identifies the relative significance of each parameter, provides important information required to optimize mix design and consequently minimizes the effort needed to optimize LWSCC mixtures, and ensures balance among parameters affecting fresh and hardened properties. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mixture parameters on measured properties. LWSCCs with EC lightweight aggregates can reduce the construction pollution, increase the design solutions, extend the service life of the structure and hence, promote sustainability in construction industry. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Self-Consolidating Concrete (SCC) is capable of filling up the formwork and encapsulate reinforcement by its self-weight

⇑ Corresponding author. Tel.: +1 416 979 5000x7867. E-mail address: [email protected] (K.M.A. Hossain). http://dx.doi.org/10.1016/j.conbuildmat.2014.05.027 0950-0618/Ó 2014 Elsevier Ltd. All rights reserved.

without the need for additional compaction or external vibration. In addition it has excellent segregation resistance and high flowability and passing ability at fresh state. There are many other advantages of using SCC which include: reduction in the labor cost, better compaction and finish-ability in confined and restricted areas where compaction is difficult, and faster construction completion [1]. Due to these advantages, in recent years, SCC has been extensively used in many structural applications [1]. Lightweight

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469

aggregate concrete (LWC) has also been used successfully for the structural purposes for many years [2]. Lightweight SCC (LWSCC) combines the favorable properties of LWC and SCC. Using lightweight aggregates (such as expanded clay/shale, pumice, and blast furnace) in concrete has several advantages including increased strength-to-weight ratio, reduced modulus of elasticity, improved thermal and sound insulation and fire resistance properties [2]. Potential use of structural LWC involves situations when it is desirable to reduce a structure’s dead load particularly in earthquake zones [2,3]. In addition, substantially lighter LWC (compared to normal weight concrete) can also save on transportation, formwork and concrete placement related costs [2,3]. These LWC advantages can be greatly utilized by incorporating lightweight aggregates in SCC mix design. Provided that the strength, mechanical and durability characteristics are comparable to normal weight SCC, LWSCC can be prompted as a new generation of high performance concrete in construction. Although numerous investigations have been made on SCC and LWC, to the authors’ best knowledge little research has been conducted on the design procedures and statistical modeling of LWSCC [4–7]. Choi et al. [8] designed the mix proportion for LWSCC by adopting a modified method proposed by Su and Miao [9]. The slump flow, V-funnel and U-box tests were then used to evaluate the workability of LWSCC. Similarly, Shi and Wu [10] used the slump flow, V-funnel, and L-box tests, and the visual observation method to study the properties of LWSCC. Hwang and Hung [11] evaluated the performance of LWSCC mixtures containing sintered bottom ash, for varying water to cement ratio (w/c) and cement paste content. Thirteen mixes were designed with the densified mixture design algorithm method (DMDA). The main goal of this method was to obtain high strength along with a high flowing concrete. The approach taken during this investigation was to use fly ash to fill voids of aggregate instead of replacing part of the cement as in traditional mix design methods. Thus, fly ash physically filled the voids, densified the mixture and acted chemically as a pozzolanic material to strengthen the microstructure. Müller and Haist [12] proposed three mix proportions for LWSCC and assessed their self-compacting properties by the slump flow, J-ring, V-funnel, and L-box tests. No significant difference in the mix proportion design was found compared with SCC except for the aggregate used. Wu et al. [13] investigated workability of LWSCC and its mix proportion design using expanded shale aggregates at fixed fine and coarse aggregate contents using the volumetric method. The study demonstrated that fixed aggregate contents can be used effectively in volumetric method to design LWSCC mixtures. An increase in the paste content of the mix increased the flow velocity but reduced resistance to segregation. Lachemi et al. [14] developed three different classes of LWSCC mixtures with two different types of lightweight aggregates (blast furnace slag and expanded shale aggregates). The influence of the type of concrete (LWSCC vs. normal weight SCC), and the type of lightweight aggregates on the steel–concrete bond strength and failure modes were also studied. Kim et al. [15] studied the characteristics of SCC using two types of lightweight coarse aggregates with different densities, mostly semi-lightweight (2000–2300 kg/ m3). Nine mixes were evaluated in terms of flowability, segregation resistance and filling capacity of fresh concrete. The mechanical properties of hardened LWSCC, such as compressive strength, splitting tensile strength, elastic modulus and density were assessed. Due to the increasing interest in LWSCC construction in recent years, a comprehensive research program was developed by the authors to contribute to the existing knowledge. While design procedures and statistical modeling for self-consolidating normalweight concrete have been published [16–19], lacks in adequate research studies warrants investigations on LWSCC technology.

451

Authors research based on statistical experimental design approach to identify primary mix design parameters and their coupled effects on relevant properties of expanded clay (EC) lightweight SCC (EC-LWSCC) is a timely initiative. The knowledge of influence of mixture variables on fresh state and hardened characteristics (which is the objectives of the current study) is essential for successful development of EC-LWSCCs. This paper presents the outcomes of the research conducted in three phases and explains the relationships between mix design parameters/factors affecting EC-LWSCC important characteristics. In addition, the paper presents development and validation of statistical models for the design of EC-LWSCC mixtures with desired fresh and hardened properties. The statistical models developed in this study will simplify the test protocol needed to optimize EC-LWSCCs and can serve as a tool for practical production. In addition, simplification of the optimization process of EC-LWSCC mixtures also led to a balance between mix design parameters affecting workability and hardened properties. The recommendations of this research will be useful for engineers, designers and manufacturers involving in the development, production and use of EC-LWSCCs. 2. Research program This research was conducted in three phases. The Phase I focused on the experimental study of the fresh and hardened properties of mathematically derived EC-LWSCC mixes. Twenty concrete mixtures were designed. Three key mix design parameters namely water (w) to binder (b) ratio (w/b) (0.30–0.40), dosage of high range water reducing admixtures (HRWRA) (0.3–1.2% by total content of binder) and total binder content (b) (410–550 kg/m3) were selected to derive mathematical models for the design of EC-LWSCC mixtures. The tested EC-LWSCC properties were, slump flow, V-funnel flow time, J-ring flow diameter/height difference, Lbox ratio, filling capacity, segregation resistance, unit weight and compressive strength. Phase II focused on the model development. Based on the test results, the influences of various parameters (w/b, HRWRA% and binder content) on EC-LWSCC fresh and hardened properties were analyzed. The relative significance of these primary mixture design parameters and their coupled effects on relevant properties of ECLWSCCs were established. Afterward, statistical models were developed for prediction of these properties. In Phase III, the developed statistical models were used to derive optimized industrial class EC-LWSCCs. EC-LWSCC mixtures were mathematically optimized to satisfy three classes of EFNARC industrial classifications and their performance was experimentally validated through fresh and hardened properties. In addition, the relationship between theoretical and experimental results was further investigated, where validation of the statistical models were performed. 3. Investigation in Phase I 3.1. Materials ASTM Type I cement, Class F fly ash (FA) and silica fume (SF) were used. The physical and chemical properties of cement, FA and SF are presented in Table 1. FA and SF were incorporated into the mixture at a fixed percentage by mass of total binder at 12.5% and 7.5%, respectively. Nominal sizes of 4.75 mm and 12 mm lightweight expanded clay were used as fine and coarse aggregates, respectively. Table 1 presents the chemical properties of expanded clay aggregates, and Table 2 presents their grading and physical properties. The proposed EC-LWSCC mixtures contained no viscosity-modifying admixture (VMA). The use of VMA can ensure good flowability with lower paste volume. However, many successful LWSCC mixtures were developed without the use of VMA [14,15,20]. The silica fume is used to enhance the fresh properties as it helps to improve the cohesiveness and homogeneity of the LWSCCs; holding the lightweight

452

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469

Table 1 Characteristics of cement fly ash, silica fume and expanded clay.

Table 3 Limit and coded value of factors.

Chemical

Cement

Fly ash

Silica fume

Expanded clay

SiO2 (%) Al2O3 (%) Fe2O3 (%) TiO2 (%) CaO (%) MgO (%) SO3 (%) Alkalis as Na2O (%) LOI (%)

19.6 4.9 3.1 – 61.4 3 3.6 0.7 2.3

46.7 22.8 15.5 – 5.8 – 0.5 0.7 2.2

95.21 0.21 0.13 – 0.23 – 0.33 0.85 1.97

64.6 20.6 6.5 0.8 1.5 2.9 0.5 – 0.3

Physical Blaine (cm2/g) +45 lm (%) Density (g/cm3)

3870 3.00 3.15

3060 17 2.48

21,000 2.85 2.20

– – –

Factor

Range

Coded value

X1 = (w/b) X2 = (% of HRWRA) X3 = (B) kg/m3

0.30 to 0.40 0.3 to 1.2% 410–550

0.28 0.11 380

CCD portion

Mixture

X1

X2

X3

Factors Fractional factorial Center point Axial

1–8 15–20 9–14

±1 0 0, ±1.414

±1 0 0, ±1.414

±1 0 0, ±1.414

1.414

1 0.30 0.30 410

0

+1

+1.414

0.35 0.75 480

0.40 1.2 550

0.42 1.39 580

3.4. Testing procedures coarse aggregates in place, and preventing them from floating. Further, fly ash and silica fume also enhance the durability characteristics of the mixture. A polycarboxylate ether type HRWRA with a specific gravity of 1.05 and total solid content of 26% was used as superplasticizer (SP). 3.2. Mix design methodology and mixture proportions (Phase I) Twenty concrete mixtures were designed using the Box-Wilson central composite design (CCD) method [21]. Three input factors were used in the test program: X1 (water to binder ratio: w/b), X2 (percentage of HRWRA as a percentage of mass of total binder content), and X3 (total binder content: b). The ranges of the input factors were set at 0.30–0.40 for X1, 0.3–1.2% for X2, and 410–550 kg/m3 for X3. Table 3 presents the coded value and limits of each factor. The CCD method consists of three portions: the fraction factorial portion, the center portion, and the axial portion (Table 3). The mix design and statistical evaluation of the test results were performed using commercial software [22] at a 0.05 level of significance. Table 4 presents the mixture proportions for EC-LWSCCs developed by the software. 3.3. Casting of test specimens All concrete mixtures were prepared in 35 batches in a drum rotating mixer. Due to the high water absorption capacity, the expanded clay lightweight aggregates were pre-soaked for a minimum of 72 h and then drained using bucket with side holes (without losing the fine particles). Next the aggregates were wiped off with dry towels to make them saturated surface dry (SSD). The SSD aggregates were mixed for five minutes with 75% of the mixing water then added to the cementitious materials and mixed for an additional minute. Finally, the remaining water and HRWRA were added to the mixture, and mixed for another 15 min. Just after mixing, the slump flow, L-box, V-funnel, J-ring flow, filling capacity, sieve segregation, and unit weight tests were conducted. Ten 100  200 mm cylinders from each batch were cast for compressive strength determination. All EC-LWSCC specimens were cast without any compaction or mechanical vibration. After casting, all the specimens were covered with plastic sheets and water-saturated burlap and left at room temperature for 24 h. They were then demolded and transferred to the moist curing room, and maintained at 23 ± 2 °C and 100% relative humidity until testing. The cylinders for the oven dry unit weight test were stored in lime-saturated water for 28 days prior to transfer to the oven at 100 °C. The cylinders for the air dry unit weight test were stored in room temperature for 28 days.

All fresh tests were conducted as per EFNARC Self-Compacting Concrete Committee test procedures [23]. The slump flow test was conducted to assess the workability of concrete without obstructions to determine flow diameter. The deformability of EC-LWSCC was measured using the V-funnel test, where flow time under gravity was determined. The filling capacity, J-ring and L-box tests determined the passing ability of concrete. The sieve segregation resistance (SSR) test was conducted according to EFNARC test procedures: 5 kg of fresh concrete was poured over 5 mm mesh, and the mass of the mortar passing through the sieve was recorded. The fresh unit weight was tested according to per ASTM C 138 [24] and both air dry and oven dry densities were determined according to ASTM C 567 [25]. The compressive strength of EC-LWSCC mixtures was determined by using 100  200 mm cylinders, as per ASTM C 39 [26].

3.5. Phase I – Test results, analysis and discussion 3.5.1. Fresh and hardened properties of EC-LWSCC mixtures The fresh and hardened properties of EC-LWSCC mixtures are summarized in Table 5. Ranges of the test values for EC-LWSCC mixtures were between 345 and 760 mm for slump flow, 1.9 and 28.7 s for V-funnel flow time, 305 and 770 mm for J-ring flow, 0 and 19 mm for J-ring height difference, 0.28 and 0.95 for L-box ratio, 27% and 95% for filling capacity and 5% and 42%, for SSR. The compressive strength ranged from 17 to 36 MPa and 21 to 48 MPa at 7 and 28 days, respectively. The fresh unit weight ranged from 1563 to 1697 kg/m3 and the 28-day air dry density values were less than 1840 kg/m3 which classified all EC-LWSCC mixtures as lightweight concrete [27]. In order to qualify as SCC, the mixes should satisfy EFNARC industrial classifications, with 550–850 mm slump flow [28], less than 8 s of V-funnel time, 80–100% of filling capacity, greater than 0.8 of L-box ratio [29,30], and less than 20% of segregation resistance [23]. To be classified as LWSCC, a mix should satisfy EFNARCSCC industrial classifications as well as it should develop a minimum 28-day compressive strength of 17.2 MPa and attain an air dry unit weight of less than 1840 kg/ m3 [31,32]. Using basic knowledge of concrete technology, it is expected that fresh and hardened properties of LWSCC mixtures will be influenced by the same parameters and in same way as normal weight SCC mixtures, with exception to the V-funnel time. Theoretically speaking, when reducing the unit weight to less than 1840 kg/ m3, it might be expected that the velocity of flow can be affected; leading to lower V-funnel time values than the ones reported for normal weight SCC.

Table 2 Grading and physical properties of aggregates. Sieve size (mm)

% Passing ASTM C-330 specification

13.20 9.50 4.75 2.36 1.18 0.60 0.30 0.15 Bulk specific gravity (Dry) Bulk specific gravity (SSD) Dry loose bulk density (kg/m3) Absorption (%)

Expanded clay

Fine

Coarse

Fine

Coarse

100 80–100 5–40 0–20 0–10 – – – – – 1120 (Max) –

100 100 85–100 – 40–80 – 10–35 5–25 – – 880 (Max) –

100 100 87 63 40 18.5 10.6 5.5 1.22 1.51 760.9 17.6

100 83 19 2 1 0.7 0.2 0 1.21 1.41 621.5 16.2

453

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Table 4 Mixture proportions for EC-LWSCC (Phase I). Mix no.

X1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

X2

X3

Cement 3

FA

SF 3

w/b

HRWRA

b

kg/m

kg/m

kg/m

0.40 0.40 0.40 0.40 0.30 0.30 0.30 0.30 0.42 0.28 0.35 0.35 0.35 0.35 0.35 0.35 0.35 0.35 0.35 0.35

1.2 1.2 0.3 0.3 1.2 1.2 0.3 0.3 0.75 0.75 1.39 0.11 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75

550 410 550 410 550 410 550 410 480 480 480 480 580 380 480 480 480 480 480 480

440 328 440 328 440 328 440 328 384 384 384 384 464 304 384 384 384 384 384 384

69 51 69 51 69 51 69 51 60 60 60 60 73 48 60 60 60 60 60 60

41 31 41 31 41 31 41 31 36 36 36 36 44 29 36 36 36 36 36 36

The filling capacity test is more relevant for assessing the deformability of SCC among closely spaced obstacles. A filling capacity between 50% and 95% indicates moderate to excellent flowability among closely spaced obstacles [33]. For a desirable SCC mixture performance, different range of V-funnel time is suggested by researchers: between 3 and 7 s, between 2.2 and 5.4 s and between 2.1 and 4.2 s [33–35]. It is reported that the SCC with L-box ratio greater than 0.8 exhibited good performance without blocking, hence 0.8 is considered as the lower critical limit for a mix to be SCC [29,30]. According to several studies, the L-box and the filling capacity test results should be simultaneously considered to evaluate the concrete passing ability through heavily reinforced sections without the need of vibration. One of the most important requirements for any SCC is that the aggregates should not be segregated from the paste and the mix should remain homogeneous during the production and placement. It is also equally important that the particles move with the matrix as a cohesive fluid during the flow of SCC. A stable SCC should exhibit a segregation index less than 10% [16]. However it is expected that the allowable segregation index for LWSCC should be higher than normal weight SCC. Therefore, the limits for fresh state properties of LWSCC mixtures should be changed. For satisfactory LWSCC mixtures, the criteria can be as follows: slump flow diameter (550–850 mm), V-funnel time (0–25 s), L-box ratio (P0.80), sieve

HRWRA 3

l/m

Water

3

l/m

6.6 4.9 1.6 1.2 6.6 4.9 1.6 1.2 3.6 3.6 6.7 0.5 4.3 2.9 3.6 3.6 3.6 3.6 3.6 3.6

3

220 164 220 164 165 123 165 123 201 134 168 168 203 133 168 168 168 168 168 168

E-clay aggregate Coarse

Fine

375 445 379 447 412 472 415 474 405 450 426 429 382 473 427 427 427 427 427 427

450 534 455 537 495 567 498 570 486 540 511 516 458 568 514 514 514 514 514 514

segregation resistance (0–20%), 28-day air dry unit weight (<1840 kg/m3) and 28-day compressive strength (>17.2 MPa). From the results of the present study (Table 5), mixes 3–8 and 10–13 exhibited low flowability, poor workability and passing ability as the slump flow diameter, Vfunnel time and L-box ratio were below the acceptable EFNARC performance criteria for SCC [23]. On the other hand, mixes 2,4,6,9,11 and 14 are considered segregated mixes due to high segregation index beyond the prescribe limits. Mixes 1, 15, 16, 17, 18, 19 and 20 met all SCC fresh performance with no sign of segregation (Table 5). Out of 20 tested mixtures, only 7 mixtures satisfied the outlined criteria for structural LWSCC. This demonstrates the significant challenges associated with the development of LWSCC mixtures.

4. Phase II – Influence of mix design parameters and development of statistical models The fresh and hardened properties of twenty EC-LWSCC mixtures obtained in Phase I were used to analyze the influence of mix design parameters and development of statistical models.

Table 5 Test results on fresh and hardened properties. Mix no.

1 2a 3a 4a 5a 6a 7a 8a 9a 10a 11a 12a 13a 14a 15 16 17 18 19 20 a

Slump flow (mm)

760 755 490 500 580 595 345 385 730 395 740 370 540 720 650 645 630 655 620 630

V-funnel (s)

2.7 1.9 3.0 8.6 17.5 18.7 28.7 19.7 2.3 25.7 5.4 11.1 10.9 3.0 6.1 6.4 6.0 6.1 5.7 6.6

Mixture disqualified as LWSCC.

J-ring flow (mm)

770 765 460 470 550 585 305 340 745 345 765 330 505 735 650 635 655 585 645 625

J-ring height diff (mm)

0 0 5 7 5 5 19 13 0 12 0 16 6 0 3 3 2 3 1 3

L-box ratio

0.94 0.94 0.50 0.48 0.68 0.56 0.30 0.39 0.94 0.28 0.93 0.31 0.65 0.95 0.87 0.84 0.90 0.85 0.89 0.85

Filling capacity (%)

94 94 53 53 68 60 28 32 94 32 93 27 66 95 90 84 91 85 86 88

SSR (%)

19 42 8 28 12 24 5 6 36 7 29 9 8 35 14 16 15 17 18 15

Compressive strength (MPa)

28-day unit weight (kg/ m3)

7-d

28-d

Fresh

Air dry

Oven dry

22 18 24 20 30 29 34 31 17 36 24 28 29 20 27 28 27 27 29 30

29 23 29 27 38 39 42 41 21 48 34 39 38 27 36 37 37 38 39 40

1615 1639 1651 1660 1668 1675 1681 1571 1588 1622 1630 1597 1697 1563 1622 1605 1597 1599 1603 1615

1514 1525 1550 1561 1567 1574 1580 1445 1487 1496 1511 1482 1584 1462 1521 1504 1496 1498 1491 1503

1481 1476 1500 1517 1517 1532 1529 1405 1412 1456 1462 1439 1551 1437 1467 1439 1445 1448 1433 1458

454

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469

Slump Flow (mm)

Design-Expert® Software

550.00

Slump Flow (mm) Design Points 760 345

500

Actual Factor B: HRWRA = 0.75

A: w/b

Binder content (b) kg/m3

515.00

X1 = A: X2 = C: B

550

650

600

6

480.00

445.00

B: HRWRA 700

C: Binder content (b) 410.00 0.30

0.32

0.35

0.38

0.40

w/b Fig. 1. Contours of slump flow changes of EC-LWSCCs with w/b, total binder content and HRWRA at 0.75%.

4.1. Influence of mix design parameters on fresh and hardened properties 4.1.1. Effects on the slump flow Fig. 1 presents contour diagrams of the slump flow diameter changes of EC-LWSCC mixtures depending on the water to binder ratio and total binder content. According to Fig. 1, an increase in the w/b from 0.3 to 0.4 significantly increased the slump flow. However, at fixed HRWRA% the slump flow range was limited with the increase of binder content. For example, when the HRWRA% was fixed at 0.75% and the binder content was increased to 550 kg/m3, the maximum predicted slump flow was limited to 650 mm. This was due to the increased demand of HRWRA in order to maintain same slump flow diameter with higher binder content.

The combined effects of w/b and HRWRA have significant influence on the slump flow diameter as shown in Fig. 2. An increase in the HRWRA from 0.3% to 1.2% (by total content of binder) and w/b from 0.3 to 0.4 significantly increased the slump flow when high binder content (480 kg/m3) was used. Low effect of w/b and HRWRA in increasing the slump flow was observed for the EC-LWSCC mixtures. For example, when both parameters (w/b and HRWRA) were maximized at 1.2% and 0.40%, the maximum predicted slump flow for EC mixtures was 750 mm. This can be attributed to the aggregate shape/gradation and packing density because a high amount of fluidity is needed to achieve high workability for a low-packing density mixture, as in the case of EC aggregates. According to Assaad and Khayat [36], the w/b is closely related to flowability of concrete and an

Design-Expert® Software Slump Flow (mm) Design points above predicted value Design points below predicted value 760 345 X1 = A: X2 = B: HRWRA

790

Actual Factor C: B = 480.00

A: w/b B: HRWRA

Slump Flow (mm)

680

570

460

350

C: Binder content (b) 1.20

0.40 0.97

0.38 0.75

HRWRA (%)

0.35 0.53

0.32 0.30

w/b

0.30

Fig. 2. Effect of w/b, HRWRA and total binder content at 480 kg/m3 on the slump flow of EC-LWSCCs.

455

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Design-Expert® Software V-Funnel (s) Design points above predicted value Design points below predicted value 28.7 1.9 X1 = A: X2 = B: HRWRA

26.0

Actual Factor C: B = 480.00

V-Funnel (s)

19.8

A: w/b B: HRWRA

13.5 7.3 1.0

C: Binder content (b) 1.20

0.40 0.97

0.38 0.75

HRWRA (%)

0.35 0.53

w/b

0.32 0.30

0.30

Fig. 3. Effect of w/b, HRWRA and total binder content at 480 kg/m3 on the V-funnel time of EC-LWSCCs.

increase in w/b improves the flowability of the concrete. Sonebi [37] states that the SCC fresh properties are significantly influenced by the dosage of water and HRWRA. It is expected that LWSCC mixtures will exhibit similar behavior compared with normal weight SCC mixtures under the influence of HRWRA. 4.1.2. Effects on the V-funnel flow time An increase of the w/b from 0.3 to 0.4 significantly reduced the V-funnel flow time whereas an increase of HRWRA from 0.3% to 1.2% only slightly reduced the V-funnel flow time. However, combined maximum increase of both w/b and HRWRA parameters resulted in a substantial reduction of the V-funnel flow time (below 2 s) at given binder content. This observation is in agreement with the conclusion of previous SCC statistical workability study [37]. The V-funnel flow time is indicative of the viscosity of the LWSCC mixture – the higher the flow times the more viscous and less workable is the mix. Changes of V-funnel flow time with

w/b and HRWRA are depicted in Fig. 3. The effect of w/b and total binder content on the V-funnel flow time of EC-LWSCC mixtures is plotted in Fig. 4. It can be concluded that an increase of w/b from 0.3 to 0.4 significantly decreased the V-funnel flow time. However, the flow time increased with the increase of binder content at a given HRWRA%. 4.1.3. Effects on the L-box ratio The L-box ratio showed a similar trend of variation as slump flow. An increase of w/b from 0.3 to 0.4 and HRWRA from 0.3% to 1.2% significantly increased the L-box ratio when a high binder content of 480 kg/m3 was used. Fig. 5 presents the slump flow changes of EC-LWSCC mixtures depending on the w/b and HRWRA. According to Hwang et al. [38], a combination of the slump flow and the L-box ratio can be used to assess filling capacity of SCC for quality control and design of SCC for placement in restricted sections or congested elements.

Design-Expert® Software

V-Funnel (s)

V-Funnel (s) Design Points 28.7

550.00

1.9

20.0

Actual Factor B: HRWRA = 0.75

A: w/b B: HRWRA C: Binder content (b)

Binder content (b) kg/m3

X1 = A: X2 = C: B

515.00 18.0 2.0 16.0 14.0 12.0 10.0

480.00

8.0

6.0

4.0

6

445.00

410.00 0.30

0.32

0.35

0.38

0.40

w/b Fig. 4. Contours of V-funnel changes of EC-LWSCC mixes with w/b, total binder content and HRWRA at 0.75%.

456

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Design-Expert® Software L-Box Ratio (h2/h1) Design points above predicted value Design points below predicted value 0.95 0.28 X1 = A: X2 = B: HRWRA

1.03

Actual Factor C: B = 480.00

A: w/b B: HRWRA

L-Box Ratio (h2/h1)

0.8425 0.655 0.4675 0.28

1.20

C: Binder content (b)

0.40 0.38

0.97 0.35

0.75 0.32

0.53

HRWRA (%)

w/b

0.30

0.30

Fig. 5. Effect of w/b, HRWRA and total binder content at 480 kg/m3on the L-box of EC-LWSCCs.

Fig. 6 presents contour diagrams of the L-box ratio of EC-LWSCC mixtures depending on the w/b and total binder, respectively. It can be suggested that as the total binder content is increased, the L-box ratio is reduced for a given HRWRA%. Previous research demonstrated the relationship between w/b, HRWRA, volume of coarse aggregate and L-box ratio for normal weight SCC mixtures where all three parameters are found to significantly influence the L-box ratio [37].

4.1.4. Effects on the segregation resistance Fig. 7 shows that the increase of the binder content appeared to be very effective in increasing the segregation resistance. The increase in binder content enhanced the packing density of mixtures and resulted in a reduction in segregation. This is also attributed to the increased cohesiveness and viscosity of the concrete

mixture at high binder content. Similar conclusions were drawn in previous normal weight SCC statistical studies [17,39]. Fig. 8 illustrates the trade-off between variation of the w/b and HRWRA on the segregation resistance of EC-LWSCC mixtures at a given binder content (480 kg/m3). These contours show that increasing one or both parameters w/b and HRWRA (from 0.3 to 0.4 and from 0.3% to 1.2%, respectively), would significantly reduce the segregation resistance of EC-LWSCC mixtures. However, it would be better to increase HRWRA% rather than w/b.

4.1.5. Effects on other properties For all mixes, the filling capacity and J-ring flow/J-ring height difference were positively influenced by w/b and HRWRA. An increase of either or both parameters led to an increase in the measured responses/properties (Figs. 9–11). However, an increase in

Design-Expert® Software

L-Box Ratio (h2/h1)

L-Box Ratio (h2/h1) Design Points 0.95

550.00

0.85

X1 = A: X2 = C: B Actual Factor B: HRWRA = 0.75

A: w/b B: HRWRA

Binder content (b) kg/m3

0.28

515.00

0.85 0.6 0.65

0.7

0.75

0.8

0.9

6

480.00

445.00

C: Binder content (b) 410.00 0.30

0.32

0.35

0.38

w/b Fig. 6. Contours of L-box ratio changes of EC-LWSCCs with w/b, total binder content and HRWRA at 0.75%.

0.40

457

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469

Segregation Index (%)

Design-Expert® Software

550.00

Segregation Index (%) Design Points 42

8 10

X1 = A: W/B X2 = C: B Actual Factor B: HRWRA = 0.75

A: w/b

Binder content (b) kg/m3

5

12

515.00

14 16

618

480.00

20 22 24 26

B: HRWRA

445.00

28 30

C: Binder content (b)

32 34 36

410.00 0.30

0.32

0.35

0.38

0.40

w/b Fig. 7. Contours of segregation resistance changes of EC-LWSCC mixes with w/b, total binder content and HRWRA at 0.75%.

the binder content alone affects the results negatively – showing a decrease in the measured responses. The aggregate density played a major role in affecting the fresh unit weight of the mixes. As for the influence of the examined parameters on the response, the fresh unit weight was influenced mainly by the binder content – as the binder content increased the fresh unit weight increased and vice versa (Fig. 12). Only the total binder content affected the results of the 28-day air and oven dry unit weights of EC mixtures (Figs. 13 and 14). An increase in the total binder content increased both unit weights. This behavior might be attributed to the high absorption rate of aggregates (above 16%) that slowed the evaporation rate of water from the mixture. The HRWRA% did not have an effect on the results.

For all developed mixes, 7-day compressive strengths were affected by all three parameters (w/b, HRWRA and total binder content). As the binder increased, the 7-day strength increased. In contrast, as the either or both HRWRA (%) and w/b increased the 7-day strength decreased (Fig. 15). Nevertheless, it was expected that HRWRA% should not have any influence on the 7day strength. This is because HRWRA% effect is typically weakened away after 24–48 h. On the other hand, the 28-day compressive strengths were mainly affected by w/b and total binder content (Fig. 16). An increase in w/b decreased the 28-day strengths, while an increase in total binder content increased the compressive strength which is agreement with basic knowledge of concrete technology regardless of the concrete type.

Design-Expert® Software Segregation Index (%) Design points below predicted value 42 5 X1 = A: W/B X2 = B: HRWRA

36

A: w/b B: HRWRA C: Binder content (b)

Segregation Index (%)

Actual Factor C: B = 480.00

28

20

12

4

0.40

1.20 0.38

0.97 0.35

0.75

HRWRA (%)

0.32

0.53 0.30

w/b

0.30

Fig. 8. Effect of w/b, HRWRA and total binder content at 480 kg/m3 on the SSR of EC-LWSCCs.

458

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Design-Expert® Software J-Ring Flow (mm) Design points above predicted value Design points below predicted value 770 305 X1 = X2 = B: HRWRA

810

Actual Factor C: B = 480.00

J-Ring Flow (mm)

682.5

A: w/b

555

427.5

300

B: HRWRA 1.20

C: Binder content (B)

0.40 0.38

0.97 0.35

0.75

HRWRA (%)

0.32

0.53 0.30

w/b

0.30

Fig. 9. Effect of w/b, HRWRA and total binder content at 480 kg/m3 on J-ring EC-LWSCCs.

4.2. Statistical evaluation of test results

ities) of 0.05 6 it is accepted as a significant factor on the test result, as evidence indicates that the parameter is not zero; that is, the contribution of the proposed parameter has a highly significant influence on the measured response [17–19]. The contributions of the each parameters on the measured test results are presented in Table 6, where the effectiveness of the independent parameters on the measured response is calculated. The higher the contribution, the higher the effectiveness of the parameter on the response, equally, the lower the contributions the lower effect on the response. Analysis of the statistical parameters of the derived model, along with the relative significance, and the contribution % of each parameter on the results are given in Table 6. The R2 values of the EC-LWSCC response models for the slump flow, V-funnel flow, J-ring flow, J-ring height difference, L-box, filling capacity, sieve

A model analysis of the response was carried out to determine the effectiveness of test parameters in controlling the EC-LWSCC properties. Using GLM-ANOVA, the measured fresh and hardened properties of EC-LWSCCs such as slump flow, and V-funnel flow time, were given as the dependent variables while the experimental test parameters (‘‘w/b’’, ‘‘HRWRA%’’, and ‘‘B’’) were selected as the independent factors/variables. The general linear model analysis of variance was performed and the effective test parameters and their percent contributions on the above mentioned properties of EC-LWSCCs were determined. Table 6 summarized all the relevant data from statistical evaluation. The p-value in Table 6 shows the significance of the given test parameters on the test results. If a system has a p-value (Probabil-

Design-Expert® Software J-Ring Height Diff. (mm) Design points above predicted value Design points below predicted value 19 0 X1 = A: X2 = B: HRWRA

A: w/b B: HRWRA

17.0

J-Ring Height Diff. (mm)

Actual Factor C: B = 480.00

12.5 8.0 3.5 -1.0

1.20

0.40 0.97

C: Binder content (b)

0.38 0.75

HRWRA (%)

0.35 0.53

0.32 0.30

0.30

w/b

Fig. 10. Effect of w/b, HRWRA and total binder content at 480 kg/m3 on the J-ring height difference of EC-LWSCCs.

459

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Design-Expert® Software Filling Capacity (%) Design points above predicted value Design points below predicted value 95 27 X1 = X2 = B: HRWRA

102

Actual Factor C: B = 480.00

Filling Capacity (%)

83.25

64.5

45.75

27

A: w/b 1.20

B: HRWRA

0.40 0.97

0.38 0.75

C: Binder content (b)

HRWRA (%)

0.35 0.53

0.32 0.30

w/b

0.30

Fig. 11. Effect of w/b, HRWRA and total binder content at 480 kg/m3 on the filling capacity of EC-LWSCCs.

segregation resistance, 7-day compressive strength, 28-day compressive strength, fresh unit weight, 28-day air dry unit weight, and 28-day oven dry unit weight were found to be 0.96, 0.96, 0.94, 0.96, 0.93, 0.95, 0.93, 0.90, 0.93, 0.73, 0.56, and 0.75, respectively. Statistically significant models for EC-LWSCCs with a high correlation coefficient R2 > 0.90 were established for the slump flow, V-funnel, J-ring, J-ring height difference, L-box, filling capacity, sieve segregation resistance and 7-day/28-day compressive strength. A relatively lower R2 values of 0.73 and 0.75 were obtained for the fresh and 28-day oven dry unit weights, respectively. Low R2 of 0.56 was obtained for 28-day air dry unit weight (Table 6).

As for the significance of the parameters on the responses, for example for the slump flow; the order of influence of the test variables is: the dosage of HRWRA, w/b, and the binder content. The dosage of HRWRA had the greatest effect on the slump flow. The effect of binder content was insignificant to the response. This can be attributed to the fact that flowability is driven by HRWRA dose and w/b rather than the binder content. In fact, to secure the same slump flow with more binder content, an increase of both HRWRA and w/b is necessary. As for the V-funnel time, the order of influence of the test variables on the response is: w/b, the dosage of HRWRA and then binder content. Whereas the dosage of HRWRA, w/b, and the binder content in this order of influence, are contributing to the responses

Design-Expert® Software Fresh Unit Weight (kg/m3) Design points above predicted value Design points below predicted value 1697 1563 X1 = X2 = C: B

1700

Fresh Unit Weight (kg/m3)

Actual Factor B: HRWRA = 0.75

A: w/b

1665

1630

1595

1560

550.00

B: HRWRA

0.40 0.38

515.00

C: Binder content (b)

0.35

480.00

b (kg/m3)

0.32

445.00 410.00

0.30

Fig. 12. Effect of w/b, b and HRWRA at 0.75% on fresh unit weight of EC-LWSCCs.

w/b

460

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Design-Expert® Software Air Dry Unit Weight (kg/m3) Design points above predicted value Design points below predicted value 1584 1445 X1 = C: B X2 = A: W/B

A: w/b

Air Dry Unit Weight (kg/m3)

1590

Actual Factor B: HRWRA = 0.75

1557.5 1525 1492.5 1460

0.40

550.00 0.38

B: HRWRA

515.00 0.35

C: Binder content (b)

480.00 0.32

w/b

445.00 0.30

410.00

Binder content (B) kg/m3

Fig. 13. Effect of w/b, b and HRWRA at 0.75% on the 28d air dry unit weight of EC-LWSCCs.

of J-ring flow, J-ring height different, L-box and filling capacity. The sieve segregation resistance response is greatly influenced by the total binder content, followed by w/b and then the dosage of HRWRA. The contribution% of each parameter on the rest of the results is given in Table 6. The high correlation coefficient of responses demonstrates excellent correlation, where it can be considered that at least 95% of the measured values can be accounted for with the proposed models [17,40,41]. 4.3. Mathematical formulation of EC-LWSCC properties The mathematical relationship between the independent variables and the responses can be estimated using the model. Linear or quadratic relationships are simplified by using a backward step-

wise technique. Evaluating the contribution of each parameter and its significant influence on the response is a key tool used in accepting certain contribution [42,43]. When determining the model for each response, a regression analysis is performed on the basis of a partial model containing only the terms which are statistically significant at a 0.05 level of significance. Then, t-statistics are calculated and the terms that are statistically insignificant are eliminated. This process is repeated until the partial model contains only the significant terms. The experimental data are fed to a mathematical model through multiple linear regression analysis which consisted of the terms which are statistically significant at a 0.05 level. R2 statistic, which gives a correlation between the experimental data and the predicted response, should be high enough for a particular model to be significant [44].

Design-Expert® Software Oven Dry Unit Weight (kg/m3) Design points above predicted value Design points below predicted value 1551 1405 X1 = A: W/B X2 = C: B

A: w/b B: HRWRA

Oven Dry Unit Weight (kg/m3)

1560

Actual Factor B: HRWRA = 0.75

1522.5

1485

1447.5

1410

550.00

0.40 515.00

0.38 480.00

C: Binder content (b)

b (kg/m3)

0.35 445.00

0.32 410.00

w/b

0.30

Fig. 14. Effect of w/b, b and HRWRA at 0.75% on the 28d oven dry unit weight of EC-LWSCCs.

461

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Design-Expert® Software 7d Compressive Strength (MPa) Design points above predicted value 36 17

Actual Factor B: HRWRA = 0.75

A: w/b B: HRWRA

7d Compressive Strength (MPa)

X1 = C: B X2 = A: W/B

36 31.25 26.5 21.75 17 0.40

550.00 0.38

515.00 0.35

C: Binder content (b) w/b

480.00 0.32

445.00 0.30

b (kg/m3)

410.00

Fig. 15. Effect of w/b, b and HRWRA at 0.75% on the 7d compressive strength of EC-LWSCCs.

The derived equations of the modeled responses are summarized in Table 7 for EC-LWSCC mixtures. In this Table, mixture variables expressed in actual factored values present a comparison of various parameters as well as the interactions of the modeled responses. The model constants are determined by multi-regression analysis and are assumed to be normally distributed. A negative estimate signifies that an increase of the given parameter results in a reduction of the measured response. For any given response, the presence of parameters with coupled terms, such as (w/b)2 and (w/b)3 indicates that the influence of this parameter (w/b) is quadratic and cubic, respectively.

4.4. Repeatability of the test parameters The repeatability of test parameters at central points is given in Table 8. EC-LWSCC mixtures 15–20 (Center point mixes) are found to satisfy LWSCC performance criteria. This table shows the mean results, standard deviation and coefficient of variance (COV), as well as the standard errors and the relative errors, with 95% confidence limit of measured response of the six repeated mixes. The relative errors at the 95% confidence limit for slump flow, V-funnel flow time, J-ring flow, L-box, filling capacity, sieve segregation resistance test, fresh unit weight, 28-day air dry unit weight,

Design-Expert® Software 28d Compressive Strength (MPa) Design points above predicted value Design points below predicted value 48 21

Actual Factor B: HRWRA = 0.75

A: w/b B: HRWRA C: Binder content (b)

28d Compressive Strength (MPa)

X1 = C: B X2 = A: W/B

48 41.25 34.5 27.75 21 0.40

550.00 515.00

0.38 480.00

0.35

w/b

445.00

0.32 0.30

b (kg/m3)

410.00

Fig. 16. Effect of w/b, b and HRWRA at 0.75% on the 28d compressive strength of EC-LWSCCs.

462

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469

Table 6 Analysis of GLM-ANOVA model. Dependent variable

Source of variation

Statistical parameters

Significant

Contribution (%)

DOF

Sum of square

Mean square

F

p-Value

Slump flow

w/b HRWRA b

1 1 1

95869.21 1.859E+05 8325.00

95869.21 1.859E+05 8325.00

65.03 126.07 5.65

0.0001 0.0001 0.0388

Y Y Y

33.1 64.1 2.9

V-funnel

w/b HRWRA B

1 1 1

858.50 61.90 16.89

858.50 61.90 16.89

162.56 11.72 3.20

0.0001 0.0065 0.1040

Y Y N

91.6 6.6 1.8

J-ring flow

w/b HRWRA b

1 1 1

1.300E+05 2.438E+05 13480.79

1.300E+05 2.438E+05 13480.79

49.16 92.17 5.10

0.0001 0.0001 0.0476

Y Y Y

33.6 62.9 3.5

J-ring height

w/b HRWRA b

1 1 1

183.74 267.42 13.08

183.74 267.42 13.08

74.34 108.19 5.29

0.0001 0.0001 0.0442

Y Y Y

39.6 57.6 2.8

L-box

w/b HRWRA b

1 1 1

0.29 0.45 0.012

0.29 0.45 0.012

34.03 53.26 1.40

0.0002 0.0001 0.2641

Y Y N

38.4 60.1 1.6

Filling capacity

w/b HRWRA b

1 1 1

3118.44 4937.22 115.95

3118.44 4937.22 115.95

49.17 77.86 1.83

0.0001 0.0001 0.2061

Y Y N

38.2 60.4 1.4

Sieve segregation resistance

w/b HRWRA b

1 1 1

688.62 510.86 740.28

688.62 510.86 740.28

56.02 41.56 60.23

0.0001 0.0001 0.0001

Y Y Y

35.5 26.3 38.2

7-day compressive strength

w/b HRWRA b

1 1 1

372.11 20.43 51.14

372.11 20.43 51.14

116.03 6.37 15.95

0.0001 0.0225 0.0010

Y Y Y

83.9 4.6 11.5

28-day compressive strength

w/b HRWRA b

1 1 1

676.51 24.31 46.55

676.51 24.31 46.55

104.52 3.76 7.19

0.0001 0.0814 0.0230

Y N Y

90.5 3.3 6.2

Fresh unit weight

w/b HRWRA b

1 1 1

505.18 543.79 5656.93

505.1 543.79 5656.93

0.71 0.76 7.91

0.4202 0.4036 0.0184

N N Y

7.6 8.1 84.3

28-day air dry unit weight

w/b HRWRA b

1 1 1

68.62 603.27 6502.44

68.62 603.27 6502.44

0.068 0.60 6.48

0.7978 0.4520 0.0244

N N Y

1.0 8.4 90.7

28-day oven dry unit weight

w/b HRWRA b

1 1 1

418.15 638.69 5589.12

418.15 638.69 5589.12

0.50 0.76 6.69

0.4954 0.4024 0.0271

N N Y

6.3 9.6 84.2

DOF: degree of freedom, F: statistic test, p-value: probabilities, significant: p < 0.050 (Y: Yes), p > 0.050 (N: NO).

Table 7 Mathematical formulation of EC-LWSCC properties. Parameters

Slump flow

V-funnel

J-ring flow

J-ring height

L-box

Filling capacity

SSR

Constant w/b HRWRA b w/b * HRWRA w/b*b HRWRA * b (w/b)2 (HRWRA)2 (b)2 R2

1839.4 +11,715 +356.44 0.1373 +444.44 +1.7857 +0.1587 15,874 208.10 1.0E 3 0.96

+236.178 1187.73 17.8770 +0.04963 +28.8888 0.45000 0.01507 +1731.9 +6.6442 +1.4E 4 0.96

2395.804 +13809.4 +395.621 +0.39625 +638.888 +2.32143 +0.05952 19019.90 221.1035 1.802E 3 0.94

+82.955 438.26 41.316 +0.1079 +55.555 0.2857 0.0158 +650.31 +12.680 +1.9E 5 0.96

7.36312 +36.9090 +0.25145 +4.48E 3 +1.94444 3.57E 4 +7.53E 4 50.1217 0.57582 5.59E 6 0.93

761.4993 +3613.42 +90.0893 +0.49793 +77.7777 0.14286 +0.04761 4685.275 63.45234 5.499E 4 0.95

192.232 +666.299 +41.1386 +0.30484 +9.7E 14 1.07143 0.05555 – – – 0.93

Comp strength

Constant w/b HRWRA b w/b * HRWRA w/b * b HRWRA * b (w/b)2 (HRWRA)2 (b)2 R2

7-day

28-day

+53.673 111.74 2.894 +0.029 – – – – – – 0.90

55.3521 +122.71 7.40755 +0.39672 +11.1111 +0.28571 +7.93E 3 598.373 2.29842 4.9E 4 0.93

Fresh unit weight

28-day air dry weight

28-day oven dry weight

+1512.550 +888.769 +474.8730 1.25033 822.2222 4.85714 0.52381 +2755.89 +52.8429 +3.80E 03 0.73

13.5544 +651.758 +2.62904 1044.4 5.3571 0.5634 – – – 0.56

+1794.931 +2030.68 +503.7415 3.9773 972.2222 4.32143 0.46429 +934.732 +50.3832 +6.401E 3 0.75

463

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Table 8 Repeatability of test parameters for EC-LWSCC mixtures. Test method

Mean (n = 6)

Standard deviation

C.O.V. (%)

Estimated error (95% CI)

Relative error (%)

Slump flow (mm) V-funnel (s) J-ring flow (mm) J-ring height (mm) L-box (Ratio) Filling capacity (%) Sieve segregation resistance (%) 7-day comp strength (MPa) 28-day comp strength (MPa) Fresh unit weight (kg/m3) 28-day air dry unit (kg/m3) 28-day oven dry unit (kg/m3)

638.33 6.15 632.50 2.50 0.87 87.33 15.83 28.00 37.83 1606.83 1502.17 1448.33

13.66 0.31 25.64 0.84 0.02 2.80 1.47 1.26 1.47 9.72 10.38 12.45

2.1 5.1 4.1 33.5 2.8 3.2 9.3 4.5 3.9 0.6 0.7 0.9

13.35 0.31 25.06 0.82 0.02 2.74 1.44 1.24 1.44 9.50 10.14 12.17

2.1 5.0 4.0 32.7 2.7 3.1 9.1 4.4 3.8 0.6 0.7 0.8

Table 9 Mixture proportions for EC-LWSCC. Mix no.

EC1 EC2 EC3 EC4 EC5 EC6 EC7 EC8 EC9 EC10

X1

X2

X3

Cement 3

FA

SF 3

HRWRA 3

w/b

HRWRA

b

kg/m

kg/m

kg/m

l/m

0.4 0.36 0.32 0.37 0.33 0.35 0.35 0.35 0.35 0.35

0.60 0.88 0.94 0.30 1.00 0.75 0.75 0.75 0.75 0.75

520 430 550 420 450 480 480 480 480 480

416 344 440 336 360 384 384 384 384 384

78 64 82 63 67 72 72 72 72 72

26 21 27 21 22 24 24 24 24 24

2.9 3.6 4.9 1.2 4.2 3.6 3.6 3.6 3.6 3.6

3

EC aggregate kg/m3

Water l/m

3

208 155 176 155 148 168 168 168 168 168

Coarse

Fine

390 445 405 450 445 427 427 427 427 427

470 538 487 540 535 514 514 514 514 514

Table 10 Test results of EC-LWSCC mixes used to validate statistical models. Mix no.

Slump flow (mm)

V-funnel (s)

J-ring flow (mm)

J-ring height diff (mm)

L-box ratio

Filling capacity (%)

SSR (%)

EC1 EC2 EC3 EC4 EC5 EC6 EC7 EC8 EC9 EC10

628 698 578 519 661 645 630 655 620 630

2.6 3.8 14.4 6.3 8.6 6.4 6.0 6.1 5.7 6.6

619 704 554 496 661 635 655 585 645 625

2.0 0.5 5.0 7.0 2.0 3.0 2.0 3.0 1.0 3.0

0.77 0.94 0.73 0.61 0.85 0.84 0.90 0.85 0.89 0.85

80 95 74 60 86 84 91 85 86 88

17 28 10 21 22 16 15 17 18 15

Unit weight (kg/m3)

Comp strength (MPa)

EC1 EC2 EC3 EC4 EC5 EC6 EC7 EC8 EC9 EC10

7-day

28-day

Fresh

28-day air dry

28-day oven dry

23 24 31 24 27 28 27 27 29 30

30 33 40 32 38 37 37 38 39 40

1620 1603 1662 1600 1613 1605 1597 1599 1603 1615

1526 1507 1555 1490 1519 1504 1496 1498 1491 1503

1462 1449 1514 1451 1456 1439 1445 1448 1433 1458

28-day oven dry unit weight, and 7- and 28-day compressive strength in EC-LWSCC model are found to be limited to 0.6–9.1%. On the other hand, the relative error for J-ring height difference is found 32.7%. The relative error was defined as the value of the error with 95% confidence limit divided by the mean value.

formed to develop mixtures that satisfy EFNARC industrial classifications for SCC [23]. Moreover, this phase also presents the results of additional experimental study to validate whether the theoretically proposed optimum mix design parameters such as w/b, HRWRA%, and total binder (B) can yield the desired fresh and hardened properties for EC-LWSCCs.

5. Phase III: Optimization-validation of the statistical models and development of industrial EC-LWSCC

5.1. Verification of statistical models

This phase included the validation of the statistical model and mix proportion optimization process. The optimization was per-

The accuracy of the proposed model was determined by comparing predicted-to-measured values obtained with mixes

464

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469

Fig. 17. Predicted vs. measured fresh state properties of EC-LWSCC.

prepared at the centre of the experimental domain and five other random mixes. Mixes 1–5 were randomly selected to cover a wide range of mixture proportioning within the modeled region, while mixes 6–10 were the centre points of the models. Mixture proportioning and measured responses of these EC-LWSCC mixtures are presented in Tables 9 and 10, respectively. Comparisons between predicted and measured values for various EC-LWSCC responses are illustrated in Figs. 17 and 18 where the dashed lines present the upper and lower estimated error at 95% confidence limit. Points found above the 1:1 diagonal line indi-

cates that the statistical model overestimates the measured response. On average, the predicated-to-measured ratios of slump flow, Jring flow, L-box ratio, V-funnel flow time, J-ring height difference, filling capacity%, SSR index%, fresh unit weight, 28-day air-dry unit weight, 28-day oven dry unit weight, and 7- and 28-day compressive strengths were 0.99, 1.0, 1.01, 0.97, 0.98, 1.0, 1.02, 1.0, 1.0, 1.0, 1.03 and 1.01, respectively, indicating an accurate prediction of measured responses within the modeled region. The majority of the data for the measured responses lie close to the 1:1 diagonal

465

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469

Fig. 18. Predicted vs. measured hardened properties of EC-LWSCC.

Table 11 EFNARC SCC classification. EFNARC SCC classification Slump flow

Slump flow (mm)

SF1 SF2 SF3

550–650 660–750 760–850

Viscosity

T500 (s)

V-funnel (s)

VS1/VF1 VS2/V2

62 >2

68 9 to 25

Passing ability (L-box)

Passing ability ratio (h2/h1)

PA1 PA2 Sieve segregation resistance

P0.80 with 2 rebars P0.80 with 3 rebars Segregation resistance (%)

SR1 SR1

620 615

line, resulting in the mean value of ratio between predicated-tomeasured responses to be 1.00 ± 0.03. This indicates a high accuracy of the derived model to predicate the response. On the other hand, the majority of the predicated slump flow, Jring flow, L-box ratio, V-funnel flow time, J-ring height difference, filling capacity, SSR index, fresh unit weight, 28-day air-dry unit weight, 28-day oven dry unit weight, and 7- and 28-day compressive strengths values (Figs. 17 and 18) are within the acceptable limit of ±13.35 mm, ±25.06 mm, ±0.02, ±0.31 s, ±0.82 mm, ±2.74%, ±1.44%, ±9.50 kg/m3, ±10.14 kg/m3, ±12.17 kg/m3, ±1.24 MPa and ±1.44 MPa, respectively. These limits constitute experimental errors for responses determined from the repeatability tests. As can be seen from the validation investigation, the derived model offers adequate predication of workability, unit weight and compressive strength response within the experimental domain of the modeled mixture parameters. It is important to note that the absolute values of the predicated values are expected to change with the changes in raw material characteristics. However,

Table 12 Classification of responses goal and limits. Name of responses

Slump flow (mm) V-funnel (S) J-RING FLOW (mm) J-ring height (mm) L-box ratio (h2/h1) Filling capacity (%) Sieve segregation (%) 7-day comp strength (MPa) 28-day comp strength (MPa) Fresh unit weight (MPa) 28-day air dry unit (kg/m3) 28-day oven dry unit (kg/m3)

Goal

In range In range In range Minimize In range In range In range In range In range Minimize In range In range

EC-LWSCC-1

EC-LWSCC-2

EC-LWSCC-3

Lower limit

Upper limit

Lower limit

Upper limit

Lower limit

Upper limit

550 4 550 0.0 0.8 80 0.0 17 21 1563 1445 1405

650 8 650 19.0 1.0 100 15 36 48 1697 1584 1551

660 4 660 0.0 0.8 80 0.0 17 21 1563 1445 1405

750 8 750 19.0 1.0 100 15 36 48 1697 1584 1551

760 0.0 760 0.0 0.8 80 0.0 17 21 1563 1445 1405

850 8 850 19.0 1.0 100 20 36 48 1697 1584 1551

466

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Design-Expert® Software

High Desirability Area

Desirability 1 0 X1 = A: W/B X2 = B: HRWRA

0.810

Actual Factor C: B = 526.18

B: HRWRA C: Binder content (B)

Desirability

0.608

A: w/b

0.405 0.203 0.000

1.20

0.40 0.38

0.97 0.35

0.75 0.32

0.53

HRWRA (%)

0.30

w/b

0.30

Fig. 19. Effect of w/b, HRWRA and total binder content at 526 kg/m3on the desirability function of EC-LWSCC-1 mixture (EFNARC SCC class 1).

Design-Expert® Software

High Desirability Area

Desirability 1 0 X1 = A: W/B X2 = B: HRWRA

0.840

Actual Factor C: B = 544.00

0.630

B: HRWRA C: Binder content (b)

Desirability

A: w/b 0.420

0.210

0.000

1.20

0.40 0.38

0.97 0.35

0.75

HRWRA (%)

0.32

0.53 0.30

w/b

0.30

Fig. 20. Effect of w/b, HRWRA and total binder content at 544 kg/m3on the desirability function of EC-LWSCC-2 mixture (EFNARC SCC class 2).

the relative contributions of the various parameters are expected to be the same, thus facilitating the mix design protocol.

5.2. EC-LWSCC mixture optimization Based on the developed statistical model and the outlined relationships between mix design variables and the responses as shown in Table 9, all independent variables are varied simultaneously and independently in order to optimize the response. The objective of the optimization process is to obtain the ‘‘best fit’’ for particular response, considering alternating multiple responses concurrently. In this study, optimization was performed to develop mixtures that satisfy EFNARC industrial classifications for SCC [23]. The fresh properties of SCC as per EFNARC are presented in Table 11.

The mix proportions (independent variables) were optimized to yield three EC-LWSCC mixtures with the following fresh properties/classes: 1. SF1 + VF1 + PA2 + SR2 (casting by a pump injection system e.g. tunnel linings) – EC-LWSCC1. 2. SF2 + VF1 + PA2 + SR2 (suitable for many normal applications e.g. walls, columns) – EC-LWSCC2. 3. SF3 + VF1 + PA2 + SR1 (suitable for vertical applications in very congested structures, structures with complex shapes, or for filling under formwork) – EC-LWSCC3. VF1 limits were constrained tighter as 4–8 s for EC-LWSCC 1 & 2 to ensure density stability during application and placement. A numerical optimization technique, using desirability functions (dj) defined for each target response, was utilized to optimize the

467

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 Table 13 Theoretically optimum mix proportions and experimental results. Mix no.

EC-LWSCC-1

Mix parameters and responses

Opt values and expected response

Experimental results for Opt mix proportions

Opt values and expected response

Experimental results for Opt mix proportions

Opt values and expected response

Experimental results for Opt mix proportions

w/b HRWRA b

0.37 0.75 526

0.37 0.75 526

0.37 0.99 543

0.37 0.99 543

0.40 1.17 543

0.40 1.17 543

Slump flow (mm) V-funnel (s) J-ring flow (mm) J-ring height (mm) L-box (%) Filling capacity (%) Sieve segregation (%) 7-day comp strength (MPa) 28-day comp strength (MPa) Fresh unit weight (kg/m3) 28-day air dry unit (kg/m3) 28-day oven dry unit (kg/m3)

650 4.2 644 1.75 0.87 88 12

630 4.6 625 2 0.85 85 11

695 4 693 0.426 0.938 94 13

670 3.8 660 0 0.9 89 12

760 1.3 770 0 0.98 97 20

770 2.3 765 0 0.99 98 19

25.65

26.35

25.91

26.5

21.5

22.75

35

37.2

34.56

35.3

28.11

30.25

1619

1635

1627

1670

1607

1652

1527

1539

1524

1570

1488

1528

1465

1476

1479

1505

1454

1438

0.81

–

0.83

–

0.90

–

Desirability

EC-LWSCC-2

responses [42,43,45]. Desirability is an objective function that ranges from 0 to 1, where 0 indicates it is outside the range and 1 indicates the goal is fully achieved. The numerical optimization finds a point that maximizes the desirability function. The characteristics of a goal may be altered by adjusting the weight or importance [45]. In this research, target responses were assigned equal weight and importance. All target responses were combined into a desirability function and the numerical optimization software was used to maximize this function [45,46]. The goals seeking begin at a random starting point and proceeds up the steepest slope to a maximum. To perform the optimization process, goals, upper and lower limits for the factors and responses were defined as in Table 12. In order to have an equal importance, five predefined responses (slump flow, J-ring flow, V-funnel, L-box and SSR index) in addition to the goal to minimize both J-ring height difference and fresh unit weight response were considered and optimized simultaneously. Furthermore, filling capacity, 28-day air dry unit weight, 28-day oven dry unit weight, and 7- and 28-day compressive strengths were defined as in the experimental study range. After running the numerical optimization process for ECLWSCC-1 mixture, 28 solutions were obtained, satisfying the set limits and constrains. The desirability of the proposed solutions ranged from 0.750 to 0.811. As for EC-LWSCC-2 & 3 mixtures, 28 and 8 solutions were obtained, with desirability ranging from 0.787 to 0.835 and 0.900 to 0.905, respectively. The highest desirability functions value 0.811, 0.835 and 0.905 for achieving the set, goals and limits are given in Table 12. The desirability function changed based on the optimization process and is graphically presented in Figs. 19 and 20. For ECLWSCC mixes of classes 1 and 2 (when keeping the binder content constant at 526, 544 kg/m3, respectively), it was found that the desirability function increased only for very limited area (highlighted in the figures), and when the w/b and HRWRA% are between certain values. However, desirability value decreased drastically to zero outside this limited area indicating that very specific parameter range is needed to achieve high desirability above 0.8 for EC-LWSCC mixtures. High desirability only can be

EC-LWSCC-3

achieved for EC-LWSCC mixes of class 3 when the w/b is kept at 0.4 and for binder content above 500 kg/m3. 5.3. Verification experiment for an optimum mix design Utilizing the established high statistical confidence of the developed models, an experimental study was used to validate whether the theoretically proposed optimum mix design parameters, w/b, HRWRA%, and total binder could yield the desired responses. The test was carried out with the same materials and under the same testing conditions. The results are presented in Table 13. As it can be seen from the optimization/validation process, the model satisfactorily derived the three desired EFNARC-SCC industrial class mixtures. Optimum HRWRA% is found to be ranging between 0.64% and 0.95%. The optimized mixes satisfy the ranges for slump flow, V-funnel time, L-box ratio and segregation resistance percentage. The derived statistical models can therefore be used as useful and reliable tools in understanding the effect of various mixture constituents and their interactions on the fresh properties of LWSCC. The analysis of the derived models enables the identification of major trends and predicts the most promising direction for future mixture optimization. This can reduce the cost, time, and effort associated with the selection of trial batches. 6. Conclusions The properties of Lightweight Self-Consolidating Concrete (LWSCC), developed with expanded clay (EC) lightweight aggregates (EC-LWSCC) were investigated. This research included comprehensive laboratory investigations leading to the development of statistical design model for EC-LWSCC mixtures accompanied by fresh and hardened performance evaluation of the developed EC-LWSCC mixtures having varying water to binder ratio (w/b), high range water reducing admixture (HRWRA%) and total binder content (B). This research involved statistical modeling, mix design development, performance evaluation of EC-LWSCCs, development/validation of statistical models and development of indus-

468

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469

trial class EC-LWSCCs. The following conclusions were derived from the results of the comprehensive series of investigations: 1. The w/b has significant influence on the overall performance of EC-LWSCCs, including fresh and hardened properties. In terms of fresh properties, the w/b has high influence on workability and HRWRA demand. The passing ability and filling capacity increase with the increases of w/b. The segregation resistance decreases with increase in w/b. EC-LWSCCs with low w/b (0.35) required high dosage of HRWRA for flowability. It is noted that EC-LWSCC mixtures proportioned with w/b of less than 0.33 (regardless of HRWRA% or the total binder content), produced unsatisfactory fresh properties, and disqualified to be a LWSCC. On the other hand a balanced LWSCC mixture with w/b of around 0.35 made with EC lightweight aggregates exhibited satisfactory workability, passing ability, filling capacity and segregation resistance. 2. Similar to normal weight SCC, the w/b has significant influence on the compressive strength of EC-LWSCC mixtures – mixes with w/b of 0.35 developed higher compressive strength than those with w/b of 0.40. 3. In terms of fresh properties, the total binder content had influence on workability and static stability (segregation resistance) of EC-LWSCCs. For a given w/b, the HRWRA demand decreased with the increase of total binder content. On the other hand, segregation resistance increased with the increase of total binder content. In contrast, at fixed HRWRA% and w/b, the workability/passing ability/filling capacity decreased and segregation resistance increased with the increase of total binder content. 4. The HRWRA% had significant influence on the workability and static stability of EC-LWSCC mixtures. For a given w/b and total binder content, the workability/passing ability/filling capacity increased significantly and segregation resistance decreased with the increase of HRWRA%. 5. The established relation between the slump flow and the segregation index confirmed the commonly held notion that EC-LWSCCs with less than 500 mm slump flow should not exhibit segregation. The chances of EC-LWSCC segregation are very high beyond a slump flow of 750 mm as the segregation index tends to be more than 20%. It is always desirable to keep the slump flow between 550 and 750 mm for a stable and homogenous EC-LWSCC mixture. 6. Generally, use of fine and coarse EC lightweight aggregates in mix proportioning yielded concretes with a 28-day air dry unit weight of less than 1840 kg/m3, classifying them as LWSCC. 7. From ANOVA statistical analysis, it was found that w/b, HRWRA% and total binder content had significant impact on the fresh properties of EC-LWSCC mixtures. The effect of the total binder content on the segregation resistance and compressive strength of all EC-LWSCC mixtures was classified as statistically significant. 8. The established model using the fractional factorial design approach are valid for EC-LWSCC mixtures with w/b ranging between 0.30 and 0.40, total binder content between 410 and 550 kg/m3 and HRWRA dosages between 0.3% and 1.2% by mass of total binder content. 9. It was possible to produce robust EC-LWSCC mixtures that satisfy the EFNARC criteria for SCC. Three industrial classes of EC-LWSCC mixtures with wide range of workability performance were successfully developed. These mixtures can cover various ranges of applications, such as tunnel linings, walls, columns, vertical applications in very congested structures, and structures with complex shapes.

10. The statistical analysis and validation results of the derived statistical models indicate that this model can be used to design EC-LWSCCs and to facilitate the protocol for optimization of EC-LWSCCs. The theoretical optimum mix proportions can be used to derive desirable fresh properties and compressive strength of EC-LWSCCs. The developed models and guidelines will ensure a speedy mix design process and reduce the number of trials needed to achieve LWSCC mix specifications. Overall, this research established a technology for the production of LWSCCs which will guide engineers, researchers and manufacturers to develop future high performance LWSCC mixtures with different types of lightweight aggregates. Users can implement statistical models as tools for determining mix design parameters to develop EC-LWSCC mixtures with desired properties and then verify the properties through tests before construction application. However, additional research is needed to validate the applicability of the model to LWSCC with varying gradation and shapes of aggregates.

References [1] Okamura H, Ouchi M. Self-compacting concrete. J Adv Concr Technol 2003;1(1):5–15. [2] Hossain KMA. Properties of volcanic pumice based cement and lightweight concrete. Cem Concr Res 2004;34(2):283–91. [3] Mor A. Steel-concrete bond in high-strength lightweight concrete. ACI Mater J 1992;89(1):76–82. [4] Chao-Lung H, Le ATB, Kae-Long L, Chun-Ting L. Manufacture and performance of lightweight aggregate from municipal solid waste incinerator fly ash and reservoir sediment for self-consolidating lightweight concrete. Cem Concr Compos 2012;34(10):1159–66. [5] Bogas JA, Gomes A, Pereira MFC. Self-compacting lightweight concrete produced with expanded clay aggregate. Constr Build Mater 2012;35:1013–22. [6] Topçu IB, Uygunog˘lu T. Effect of aggregate type on properties of hardened SelfConsolidating Lightweight Concrete (SCLC). Constr Build Mater 2010;24(7):1286–95. [7] Andiç-Çakır Ö, Hızal S. Influence of elevated temperatures on the mechanical properties and microstructure of self-consolidating lightweight aggregate concrete. Constr Build Mater 2012;34:575–83. [8] Choi YW, Kim YJ, Shin HC, Moon HY. An experimental research on the fluidity and mechanical proprieties of high-strength lightweight self-compacting concrete. Cem Concr Res 2006;36(9):1595–602. [9] Su N, Miao B. A new method for the mix design of medium strength flowing concrete with low cement content. Cem Concr Compos 2003;25(2):215–22. [10] Shi CJ, Wu YZ. Mixture proportioning and properties of self-consolidating lightweight concrete containing glass powder. ACI Mater J 2005;102(5): 355–63. [11] Hwang CL, Hung MF. Durability design and performance of self-consolidating lightweight concrete. Constr Build Mater 2005;19(8):619–26. [12] Müller HS, Haist M. Self-compacting lightweight concrete – technology and use. Concr Plant Precast Technol 2002;71(2):29–37. [13] Wu Z, Zhang Y, Zheng J, Ding Y. An experimental study on the workability of self-compacting lightweight concrete. Constr Build Mater 2009;23(5): 2087–92. [14] Lachemi M, Bae S, Hossain KMA, Sahmaran M. Steel–concrete bond strength of lightweight self-consolidating concrete. Mater Struct 2009;42(7):1015–23. [15] Kim YJ, Choi YW, Lachemi M. Characteristics of self-consolidating concrete using two types of lightweight coarse aggregates. Constr Build Mater 2010;24(1):11–6. [16] Khayat KH, Ghezal A, Hadriche MS. Development of factorial design models for proportioning self-consolidating concrete. In: Malhotra VM, editor. Nagataki symposium on vision of concrete: 21st Century, June 1998. p. 173–97. [17] Patel R, Hossain KMA, Shehata M, Bouzoubaâ N, Lachemi M. Development of statistical models for mixture design of high-volume fly ash self-consolidating concrete. ACI Mater J 2004;101(4):294–302. [18] Sonebi M. Medium strength self-compacting concrete containing fly ash: modelling using factorial experimental plans. Cem Concr Res Mater J 2004;34(4):1199–208. [19] Sonebi M. Applications of statistical models in proportioning mediumstrength self-consolidating concrete. ACI Mater J 2004;101(5):339–46. [20] Karahan O, Hossain KMA, Ozbay E, Lachemi M, Sancak E. Effect of metakaolin content on the properties self-consolidating lightweight concrete. Constr Build Mater 2012;31(6):320–5. [21] Schmidt SR, Launsby RG. In: Kiemele MJ, editor. Understanding industrial designed experiments. Colo: Air Academic Press, Colorado Springs; 1994. 1– 48.

A. Lotfy et al. / Construction and Building Materials 65 (2014) 450–469 [22] Stat-Ease Corporation, Minneapolis, Design-Expert 8.0 Software for Design of Experiments. Stat-Ease, Statistics Made Easy, USA; 2009. [23] EFNARC. The European guidelines for self compacting concrete: specification, production and use, The Self-Compacting Concrete European Project Group; 2005. [24] ASTM C173. Standard test method for air content of freshly mixed concrete by the volumetric method. American Society for Testing and Materials, West Conshohocken 2002; 04. [25] ASTM C403. Standard test method for time of setting of concrete mixtures by penetration resistance. American Society for Testing and Materials, West Conshohocken 2002; 04. [26] ASTM C39. Standard test method for compressive strength of cylindrical concrete specimens. American Society for Testing and Materials, West Conshohocken 2002; 04. [27] Mehta PK, Monteiro PJM. Concrete—structure, properties, and materials. second ed. Englewood Cliffs, NJ: Prentice Hall; 1993. p. 548. [28] Nagataki S, Fujiwara H. In: Malhotra VM, editor. Self-compacting property of highly flowable concrete. Farmington Hills, Mich: ACI SP, American Concrete Institute; 1995 (SP-154), p. 301–314. [29] Sonebi M, Bartos PJM, Zhu W, Gibbs, J, Tamimi A. Final report task 4, hardened properties of SCC. Brite-EuRam, Contract No. BRPRTC96-0366, Hardened Properties of SCC. Advanced Concrete Masonry Center, University of Paisley, Scotland, UK; 2000. 75p. [30] Petersson Ö, Skarendahl Å. Self-Compacting Concrete. In: Proceedings of the first international RILEM-Symposium, Stockholm, Sweden; 1999. p. 786. [31] ACI Committee 213R. Guide for structural lightweight-aggregate concrete. American Concrete Institute Farmington Hills, Michigan, USA; 2003. p. 38. [32] ACI Committee 318. Building code requirements for structural concrete. American Concrete Institute, Farmington Hills, Michigan, USA; 2011. p. 151. [33] Khayat KH, Lovric D, Obla K, Hill R. Stability optimization and performance of self-consolidating concrete made with fly ash. In: First north American conference on the design and use of self-consolidating concrete, November 12–13, ACI, Chicago, Illinois; 2002. p. 215–23. [34] Bouzoubaa N, Lachemi M. Self-compacting concrete incorporating high volumes of class f fly ash preliminary results. Cem Concr Res 2001;31(2):413–20.

469

[35] Ghezal A, Khayat KH. Optimizing self-consolidating concrete with limestone filler by using statistical factorial design methods. ACI Mater J 2002;99(3):264–72. [36] Assaad JJ, Khayat KH. Effect of viscosity-enhancing admixtures on formwork pressure and thixotropy of self-consolidating concrete. ACI Mater J 2006;103(4):280–7. [37] Sonebi M, Grünewald S, Walraven J. Filling ability and passing ability of selfconsolidating concrete. ACI Mater J 2007;104(2):162–70. [38] Hwang S, Khayat K, Bonneau O. Performance-based specifications of selfconsolidating concrete used in structural applications. ACI Mater J 2006;103(2):121–9. [39] Khayat KH, Ghezal A, Hadriche MS. Utility of statistical models in proportioning self-consolidating concrete. In: Proceedings of the first international RILEM symposium on self-compacting concrete, Stockholm, Sweden; 2000. p. 345–59. [40] Sonebi M. Medium strength self-compacting concrete containing fly ash: modelling using factorial experimental plans. Cem Concr Res 2004;34(7):1199–208. [41] Sonebi M. Applications of statistical models in proportioning medium strength self-compacting concrete. ACI Mater J 2004;34(5):339–46. [42] Whitcomb PJ, Anderson MJ. RSM simplified: optimizing processes using response surface methods for design of experiments. NY: Productivity Press; 2004. p. 292. [43] Pradeep G. Response surface method. Saarbrücken Germany: VDM Verlag Publishing; 2008. 76p. [44] Muthukumar M, Mohan D. Optimization of mechanical properties of polymer concrete and mix design recommendation based on design of experiments. J Appl Polym Sci 2004;94(3):1107–16. [45] Ozbay E, Gesoglu M, Guneyisi E. Transport properties based multi-objective mix proportioning optimization of high performance concretes. J Mater Struct 2011;44(1):139–54. [46] Nehdi ML, Summer J. Optimization of ternary cementitious mortar blends using factorial experimental plans. Mater Struct J 2002;35(8):495–503.