Startseite Behavior of non-reinforced and reinforced green mortar with fibers
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Behavior of non-reinforced and reinforced green mortar with fibers

  • Eethar Thanon Dawood EMAIL logo und Mafaz Hani Abdullah
Veröffentlicht/Copyright: 19. November 2020
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Abstract

The behavior of non-reinforced green mortar with fibers has been observed. Different green mortar mixes have been prepared using different percentages of waste glass powder (WGP), steel slag (SG) and silica fume (SF).The properties of flow, density, ultrasonic pulse velocity (UPV), compressive and flexural strengths have been tested for such green mortar in the first phase of the experimental work. The selected green mortar mix that gives good properties with the acceptable ranges of cement replacement by such cementitious materials has been utilized to achieve the second phase of the experimental work. Thus, the uses of human hair fibers, sisal fibers and stainless steel nails fibers in the form of individual and hybrid fibers system and testing for the same properties mentioned above have been performed. The third phase includes the cost estimation for the said mortar. Whereas, the last phase deals with analysis of the results using the integrated AHP and TOPSIS method for selection the best performance of the green mortar. The results of mono sisal fiber, human hair fiber and stainless nails fiber by 0.75, 0.75 and 2% of volume fraction respectively, exhibited the highest increase in compressive strength, flexural strength, UPV and density compared with other percentages.

1 Introduction

Cement is the one of the most produced materials in the world. Annual global cement production has been estimated at 4.15 billion tons in 2016, and is expected to increase to 4.25 billion tons per year in 2030 [1]. The production of this material requires the use of a huge amount of raw materials (limestone, clay and etc), energy (electricity and heat) and fossil fuels (natural gas, fuel oil, coak or some wastes) in addition to air and water [2, 3, 4]. The high quantity of pollutants generated and non-renewable resources consumed during cement industry make cement material has a negative impact on the environment [4]. Although this industry causes the formation of wastewater, solid waste, and noise, the main environmental issues are associated with air emissions and energy consumption. The high amounts of the carbon dioxide(CO2), nitrogen oxides (NOx), sulfur oxides (SOx) and dust emissions in addition to the other air pollutants are released from cement manufacturing [5, 6, 7, 8]. Approximately 8% of glodbal carbon dioxide (CO2) emission is released from cement industry [8]. Moreover, the production of one ton of cement releases 360 pounds of dust [9], requires about 1.597 metric ton of raw materials [9, 10] and consumes a high amounts of electricity and thermal energy. Another various industrial processes (silicon metal, ferrosilicon and steel) also have a significant role on the environment impact. The accumulation of solid wastes generated as a byproduct of these industry is one of the reasons which lead to deteriorate the environment. In 2016, the global crude steel, silicon and ferrosilicon production has estimated at 1630, 2.7 and 6.4 million tons respectively [11]. Production of one ton of the steel, silicon and ferrosilicon generates a high amount of solid waste like slag and silica fume dust respectively [12]. Besides the accumulation of the non-biodegradable solid waste like waste glass in the landfills is the one of phenomena which has negative impact on the environment. For reducing this environmental impact, reducing of raw materials and energy consumption during cement production, producing sustainable building material, saving in cementand recycling of waste products, many materials were blended with cement to make green building materials [13, 14, 15, 16]. Waste glass powder(WGP), steel slag(SG) and Silica fume(SF) are non-biodegradable materials and available as waste materials [17, 18, 19]. Utilization these materials with cement can improve mortar or/and concrete workability, early and long term strength and long term durability [20, 21, 22]. Physical properties and chemical composition of these materials have a significant roleon the properties of concrete. Many previous studies [23, 24, 25, 26] have concluded that the chemical composition and the particle size of WGP have governed its pozzolanic activity, smaller particles decrease alkali silica reaction and give higher strength.

Several researchers [22, 27] have focused on the use of SG with cement to improve the density ,durability and strength of concrete at later ages. Many researchers [28, 29, 30, 31, 32] have studied the properties of mortar or/and concrete prepared from blended cement with supplementary cementitious materials (SCMs). Silica fume is the one of SCMs which can contribute to improve the mechanical properties of mortar and concrete at identical water-binder ratio (W/b) and replacement level [33, 34, 35]. The high content of amorphous silicon dioxide and very fine particles of silica fume are responsible for its high pozzolanic activity [33, 36]. The amorphous silicon dioxide reacts with calcium hydroxide, which is resulted from hydration cement, and lead to produce calcium silicate hydrate (C-S-H). The fine particles size of silica fume can fill the gap between cement particles. Thus, silica fume have significant role on the densify of the interfacial transition zone between cement paste and fine aggregate which lead to enhance the microstructure of cement mortar and concrete [33]. Utilization of SF, SG and WGP as a supplementary cementitious materials in binary, ternary blends has been studied by many researchers [37, 38]. They are observed that the use of the mixture of SF and WGP or SG as a partial replacement of cement led to relieve the retardation effect of waste glass powder or steel slag on the early hydration of cement and improve the microstructure of hardened cement paste at later ages. Thus, the use of Waste glass powder, Steel slag and Silica fume with cement in combination form can contribute to produce green mortar and enhance its overall performance. Therefore, the utilize SCMs were considered in this study.

Generally, Concrete and mortar are brittle materials with low tensile strength and low deformation capacity [39]. The incorporation of the fibers in cementitious matrix mainly improves tensile, flexural, impact strength and flexural toughness [40, 41, 42]. Industrial and natural fibers have been studied by many researchers [43, 44, 45]. Utilization of natural ,renewable and low cost fibers instead of industrial and high cost fibers has resulted in many advantages such as reducing Carbon footprint of construction industry, reducing of raw materials consumption and economy [46]. Sisal fibers(SIF) is one of the natural/vegetable fibers which need a low degree of manufacturing for their processing in comparison with synthetic fibers [47, 48]. It can contribute to provide the same level of flexural strength as synthetic fibers such as polypropylene fibers and gain ductility and flexural toughness to concrete and mortar [49]. Recently, human hair has been also used as fibers for reinforcing concrete or mortar [50, 51]. Many researchers [52, 53, 54] have reported that the reinforcing of concrete with human hair fiber(HHF)can enhance mechanical properties. The use of micro fibers such as human hair fibers (HHF) can delay the formation of micro cracks by enhancing the pre peak mechanical properties [55, 56]. Moreover, utilization of Sisal fibers and Human hair fibers has a positive impact on environmental and economic aspects [57]. The incorporation of steel fibers in concrete and mortar has been documented by many researchers [58, 59]. Although, this type of fibers have characterized by high elastic modulus, tensile strength, flexural rigidity and gain good properties to mortar and concrete. It is expensive compared with other types of fibers. So, Stainless steel nails (SIF) have been used as fibers instead of steel fibers in this study. Stainless steel nails fibers are recognized by low cost and good properties. Utilization this type of fibers can contribute to increase the compressive strength, flexural strength and other properties of concrete [42].

Several researchers [60, 61] have worked to improve accurate building material properties and predict new models. Multiple regression analysis is the one of statistical techniques which have been utilized to analysis properties of concrete and mortar, predict the good relationship between concrete or mortar properties and produce generalized results for new concrete or mortar before test [62, 63, 64]. Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are one of these methods which were used to select the best reinforced green mortar based on its behavior and to rank the non-reinforced green mortars based on its cost.

Although, many literatures are available for combination silica fume and pozzolanic materials in the mortar or concrete, their utilization with three different types of the fibers (sisal fibers, human hair fibers and low cost stainless steel nails) to produce reinforced green mortar is still limited. The major objectives of this research can be summarized into three parts:

  1. The investigation of the green mortar behavior produced from waste glass powder, steel slag and silica fume and reinforced with natural and cheap fibers.

  2. Selecting and ranking the best green mortar based on its properties and cost.

2 Materials and Mix proportions

2.1 Materials

Ordinary Portland Cement (OPC) type (CEM I) of strength class 42.5N was used in this study. It is obtained from Sulaymaniyah cement factory, Bazian district, Kurdistan, Iraq. Clear waste glass powder and Steel slag powder (prepared by ball mill machine) were supplied from glass recycling plant andiron production factory, Mosul, Iraq respectively. The specific gravity and fineness of these materials were measured according to ASTM C188 [65] and ASTM C204 [66]. Chemical composition of both Clear waste glass powder(WGP) and steel slag (SG) powder were examined using a XRF-1800 Sequential X-ray fluorescence spectrometer. According to ASTM C618, (SiO2 + Al2O3 + Fe2O3) the minimum requirement for a standard pozzolana is 70% which is comparable with the results obtained for the clear waste glass and steel slag samples. As per ASTM standard mentioned above, the maximum limit of SO3, Loss on Ignition (LoI) and Moisture content is 4%, 10% and 3% respectively. As list in Table 1, the SO3 contents of clear waste glass powder and steel slag powder was less than the acceptable limit, Loss of ignition (LOI) and moisture content have been neglected. Minor compounds such as ZrO2, TiO2, CuO, Cr2O3, NiO, MnO, As2O3 are also found in clear waste glass and steel slag samples under consideration, the amount of individual component was not more than 0.5%. Densified Micro-silica (SF)was procured from MSASA-Construction Solutions for Africa, Pomona AH, South Africa.

Table 1

Physical properties and Chemical composition of the OPC, WGP, SG and SF.

Description OPC WGP SG SF
Physical properties
Specific gravity, gm/cm3 3.15 2.315 4.994 1.98
Blaine’s fineness, cm2/gm 4850 4094 8028 -
Chemical composition (% wt.)
Ferric oxide, Fe2O3 % 3.44 1.168 95.430 0.795
Calcium oxide, CaO % 61.46 11.940 0.646 1.436
Silicon dioxide, SiO2 % 19.53 72.71 4.027 93.29
Potassium oxide, SO3 % 2.25 0.323 0.837 0.851
Alkalies (K2O + Na2O) % 0.58 8.906 1.078 0.875
Manganese oxide, MnO % - 0.014 0.496 0.043
Magnesium oxide, MgO % 3.82 1.480 0.141 0.137
Aluminum oxide, Al2O3 % 4.92 1.487 0.523 0.264
Loss of ignition, % 3.11 - - -
C3S % 57.39 - - -
C2S % 13.53 - - -
C3A % 7.20 - - -
C4AF % 10.46 - - -

The chemical composition and physical properties of OPC, WGP, SG and SF are given in Table 1. The sand used for preparing of non-reinforced green mixes was prepared according to 20-30 sand requirements ASTM C778 [67]. Its specific gravity was measured according to ASTM C 128 [68] and was 2.590. Whereas, the sand used for preparing reinforced green mixes was prepared according to graded sand requirements ASTM C778 [67]. It was used to obtain a homogeneous mixture containing fibers, the specific gravity was 2.577. Superplasticizer obtained to enhance the workability of mixes was procured from Specialties construction chemicals factory, Jahra, Kuwait. Its commercial name is KUT PLAST PCE 600. The properties of superplasticizer are shown in Table 2. Tap water was utilized in all mixes.

Table 2

Properties of superplasticizer

Typical characteristics
Specific gravity Setting time Air entrainment Chloride content Calcium chloride Content
1.06 – 1.08@ No retardation at <1% additional Nil to Bs 5075 Nil
20C normal dosage airis entrained

Three different types of fibers used in this study were sisal fibers, human hair fibers and stainless steel nails in mono and hybrid fibers system. Sisal fibers (SIF) were brought in bundles form with length 1 meter approximately. They were separated and cut into (18 ± 2) mm before using them in the mixes. They were supplied from local markets, Mosul, Iraq. Human hair fibers (HHF) were obtained from local hair salons, Mosul, Iraq. They were washed, separated, combed and cut them into (18±2) mm before adding them to the mixes. Stainless steel nails (SNF) were procured from local markets, Mosul, Iraq (Figure 1). SIF and HHF were used in 0.5, 0.75 and 1% of volume fraction. (SNF) were used in 1, 1.5 and 2% of volume fraction. The properties of three different types of fibers are presented in Table 3.

Figure 1 Fibers utilized in this study
Figure 1

Fibers utilized in this study

Table 3

Fibers properties.

Properties SIF HHF SNF
Average diameter (mm) 0.225 0.20 0.92
Average length (mm) 18±2 18±2 18±2
Specific gravity (gm/cm3) 1.4 0.4 6.678

2.2 Mix proportions

In this research, total forty one [41] mixes were prepared; Ten [10] of them were prepared to measure pozzolanic activity for each of waste glass powder, steel slag and silica fume. Binder/sand ratio was 1:2.75, water/binder ratio (W/B) was 0.59, and the mix proportions of these mixes are shown in Table 4.

Table 4

Mortar mix proportions for measuring Pozzolanic activity.

Mix No. Cement mixes (%) OPC (kg/m3) WGP (kg/m3) SG (kg/m3) SF (kg/m3) Sand (kg/m3) W/B
1 100%OPC 508 0 0 0 1397 0.59
2 90%OPC+10%WGP 454 51 0 0 1389 0.59
3 85%OPC+15%WGP 428 75 0 0 1383 0.59
4 80%OPC+20%WGP 402 100 0 0 1381 0.59
5 90%OPC+10%SG 460 0 51 0 1405 0.59
6 85%OPC+15%SG 435 0 77 0 1408 0.59
7 80%OPC+20%SG 411 0 103 0 1414 0.59
8 94%OPC+6%SF 475 0 0 30 1389 0.59
9 92%OPC+8%SF 464 0 0 40 1386 0.59
10 90%OPC+10%SF 453 0 0 50 1383 0.59

Moreover, nineteen [19] mixes were prepared to produce non-reinforced green mortars, binder/sand ratio was 1:2.75, water + superplasticizer/binder ratio (W+SP/B) was 0.39, the mix proportions of these mixes are listed in Table 5.

Table 5

Mix proportions of non-reinforced green mortar.

Mix No. Cement mixes (%) OPC (Kg/m3) WGP (Kg/m3) SG (Kg/m3) SF (Kg/m3) Sand (Kg/m3) SP % W+SP / B
U1 100%OPC 565 0 0 0 1554 2 0.39
U2 90%OPC+10%WGP 506 56 0 0 1546 2 0.39
U3 85%OPC+15%WGP 476 84 0 0 1540 2 0.39
U4 80%OPC+20%WGP 446 112 0 0 1535 2 0.39
U5 90%OPC+10%SG 512 0 57 0 1565 2 0.39
U6 85%OPC+15%SG 485 0 86 0 1570 2 0.39
U7 80%OPC+20%SG 458 0 115 0 1576 2 0.39
U8 94%OPC+6%SF 528 0 0 34 1546 2 0.39
U9 92%OPC+8%SF 515 0 0 45 1540 2 0.39
U10 90%OPC+10%SF 503 0 0 56 1537 2 0.39
U11 80%OPC+8%WGP+12%SG 454 45 68 0 1559 2 0.39
U12 80%OPC+10%WGP+10%SG 452 45 68 0 1554 2 0.39
U13 80%OPC+5%WGP+15%SG 455 29 85 0 1565 2 0.39
U14 78%OPC+10%WGP+12%SG 441 57 68 0 1557 2 0.39
U15 75%OPC+12.5%WGP+12.5%SG 423 71 71 0 1554 2 0.39
U16 75%OPC+10%WGP+15%SG 425 57 85 0 1559 2 0.39
U17 74%OPC+8%WGP+12%SG+6%SF 417 45 68 34 1551 2 0.39
U18 72%OPC+8%WGP+12%SG+8%SF 405 45 67 45 1546 2 0.39
U19 70%OPC+8%WGP+12%SG+10%SF 393 45 67 56 1543 2 0.39

Another twelve [12] mixes were prepared by substituting 8%, 12% and 10% of cement by WGP, SG and SF respectively and using three different types of fibers (sisal fibers, human hair fibers and stainless steel nails) with different percentages of volume fraction to produce reinforced green mortars, binder/sand ratio was 1:2.75, maximum superplasticizer dosage (2%) by weight of cement was also used in these mixes as listed in Table 6.

Table 6

Mix proportions of reinforced green mortar used superplasticizer

Index OPC (kg/m3) Sand (kg/m3) WGP (kg/m3) SG (kg/m3) SF (kg/m3) Sp. (%) W+SP./B SIF (%) HHF (%) SNF (%)
M0 358 1405 41 61 51 2 0.56 - - -
M1 358 1405 41 61 51 2 0.56 0.5 - -
M2 358 1405 41 61 51 2 0.56 0.75 - -
M3 358 1405 41 61 51 2 0.56 1 - -
M4 358 1405 41 61 51 2 0.56 - 0.5 -
M5 358 1405 41 61 51 2 0.56 - 0.75 -
M6 358 1405 41 61 51 2 0.56 - 1 -
M7 358 1405 41 61 51 2 0.56 - - 1
M8 358 1405 41 61 51 2 0.56 - - 1.5
M9 358 1405 41 61 51 2 0.56 - - 2
M10 358 1405 41 61 51 2 0.58 0.5 0.5 1.5
M11 358 1405 41 61 51 2 0.58 0.75 0.5 1

3 Methodology

3.1 Experimental method

Ten [10] mixes were prepared to measure the pozolanic activity of solid waste materials (waste glass powder, steel slag and silica fume) by following steps: a) Cement and solid waste material were mixed for 1 to 2 minutes. b) Then, the sand was added and mixed with the mixture for 1 to 2 minutes. c) Tap water was added to the mixture and mixed for 2 to 3 minutes. Non-reinforced green mixes were prepared by the same steps mentioned above, except that the superplasticizer was mixed with tap water before adding into the mixture. Reinforced green mixes were prepared by the same steps mentioned above. Then, the fibers were added gradually in to the mixture.

At least three [3] specimens were cast for all mixes. These specimens were prepared at room temperature (25±2C). After 24 hour of molding and humidity not less than 75%, the specimens were demolded, immersed in tap water and treated up to 7 and 28 days.

Flow test was conducted for each mix according to ASTM C1437 [69]. Dry density test was conducted for 70.7×70.7×70.7mm specimens at 28 day according to ASTM C642 [70]. Ultrasonic pulse velocity (UPV) was performed through 70.7×70.7×70.7 mm specimens at 28 day as per to ASTM C642 [70] after thirty minutes of taking them out of water. The compressive and flextural strength tests were applied on 50×50×50 mm cubes and 40×40×160 mm prisms at different ages (7 and 28 days) by using ASTM C109 [71] and ASTM C348 [72] respectively.

Motorized Cement flow table was used for measuring flowability of mixes. Laboratory oven was used to determine the mass of oven-dried sample and the mass of surface dry sample after boiling for 5 hours. Specific gravity apparatus was used to calculate apparent mass of the sample in water. Ultrasonic tester was utilized for measuring the propagation time of ultrasound pulses with a precision of 0.1 μs through 70.7×70.7×70.7 mm specimen. Hydraulic compression testing machine (300 kN capacity) was utilized to measure compressive strength and flexural strength for 50×50×50mmand 40×40×160mmsamples, respectively, at age 7 and 28 days.

3.2 AHP and TOPSIS methodology

3.2.1 Analytic Hierarchy Process (AHP)

The Analytic Hierarchy Process (AHP) is a multi-criteria decision making approach which organizes and analyzes complex decisions [73]. It was developed by Thomas Saaty in the 1970, 1980 and 1990 [74]. The decision problem in this approach is arranged in hierarchic structure [74]. The arrangement is in the descending form from an overall goal to criteria, sub-criteria and alternatives in successive levels [75]. In this paper, AHP was used to evaluate the weight of the thirteen [13] criteria of reinforced green mortars and non-reinforced green mortars. Five [5] of them were compressive strength, flexural strength,UPVand cost of reinforced green mortars and another eight [8] were raw materials, electricity energy, thermal energy, CO2, dust, waste glass, steel slag and silica fume of non-reinforced green mortars. The criteria weight of reinforced green mortars and non-reinforced green mortars were computed using the following general steps:

Step 1

Conduct the comparison for two criteria at the same time with respect their impact on the mortar prepared. The comparison conducts based on the one common scale (adapted from Satty [75] that is displayed in Table 7 to build the Pair-wise comparison matrix (F).

Table 7

One common scale (adapted from Saaty) used in this study.

Definition Equal importance Somewhat more important Much more important Very much more important Absolutely more important Intermediate Values
Intensity of importance 1 3 5 7 9 2, 4, 6, 8

The Pair-wise comparison matrix (F) builds by asking questions to experts or decision makers like, which criterion is more important with regards to the decision goal. The answers to these questions will construct the matrix (F) as shown below:

F = ( f i j ) m × m = C 1 C 2 C m C 1 C 2 C m f 11 f 12 f 1 m f 21 f 22 f 2 m f m 1 f m 2 f m m

where fij represents a quantified judgment on Ci/Cj with fii = 1 and fij = 1/fji for i, j = 1, · · · , m

Step 2

Compute the sum ( i = 1 4 f i j for each column in matrix (F). Then, divide (Fij) to computed sum according to Eq. 1, the result will be matrix (X):

(1) x i j = F i j i = 1 m F i j ( i = 1 , 2 4 , j = 1 , 2 4 )
X = C 1 C 2 C m C 1 C 2 C m x 11 x 12 x 1 m x 21 x 22 x 2 m x m 1 x m 2 x m m

Step 3

Calculate the average of each raw in the matrix (X) to obtain the weight (w) of each criterion.

Step 4

Check the consistency of the pairwise comparison matrix (F) by using the following steps:

  1. Construct matrix (Y) by multiplying the criterion weight (w) withpairwise comparison matrix (F).

Y = C 1 C 2 C m C 1 C 2 C m Y 11 Y 12 Y 1 m Y 21 Y 22 Y 2 m Y m 1 Y m 2 Y m m

Where Yij represents the result of the multiplying fi j by wj, i = 1, … , m; j = 1, … , m.

  1. Calculate the sum of each raw j = 1 4 Y i j ) in the matrix (Y). The result will be (S).

S = S 1 S 2 S m

  1. Divide the calculated sum of each raw(S) to criterion weight (wi). The result will be (S/W)

S / W = S 1 / w 1 S 2 / w 2 S m / w m

Compute the consistency index (CI) according to Eq. 2.

(2) C I = i = 1 m ( S / w ) i j m m m 1

(where, m is number of compared criteria)

The random consistency index (RCI) is obtained using Table 8. Based on the number of the criteria used in AHP method, the random consistency index is determined. The consistency ratio (CR) is computed by dividing (CI) to (RC). If the consistency ratio (CR) is ≤ 0.1 ,the pair wise comparison matrix (F) is considered to have an acceptable trust worthy and consistency; otherwise, it required to be revised [76].

Table 8

Values of the Random Consistency Index (RCI) for small problems.

Number of criteria
2 3 4 5 6 7 8 9 10
Random Consistency Index 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.51

3.3 Technique for Order Performance by Similarity to Ideal Solution (TOPSIS)

TOPSIS is a simple and useful approach which is used to deal with the complex system related to making a best choice among several alternatives [77]. It was developed by Ching-Lai Hwang and Yoon in 1981. The concept of this technique is based on the selecting the ideal alternative which has the shortest distance from the positive ideal solution and the farthest distance from the negative ideal solution [62]. In this research, TOPSIS was used to select and rank the best of reinforced green mortar based on its properties. In addition this technique was also used to determine and rank the best and worst non-reinforced green mortar based on its impact on the environment. The ranking and determining of reinforced and non-reinforced green mortars was achieved using the following steps:

Step 1

Construct the decision matrix (N) for ranking of the alternatives, the structure of matrix can be expressed as follow:

N = A 1 A 2 A m C 1 C 2 C n Z 11 Z 12 Z 1 m Z 21 Z 22 Z 2 m Z m 1 Z m 2 Z m m

Where Ai represents the alternatives i , i = 1, … , m; Cj represents the criteria that are required on which the alternative is judged, j = 1, … , n; Zij represents j th attribute, j = 1, … , n related to i, the alternative; and Zij is the obtained value representing the performance rating of each alternative Ai with respect to each requirement C j.

Step 2

Calculate the normalized decision matrix (V): The raw data can be normalized by utilizing Eq. 3. to produce the matrix (V).

(3) V i j = n i j i = 1 m n i j 2

Where i = 1, 2, 3, …… , m and j = 1, 2, 3, …… , n

Step 3

Compute the weighted normalized decision matrix (B) by multiplying the weights of criteria (w) with the normalized decision matrix (V). In this paper, the weights of criteria (w) were previously calculated based on AHP method.

Step 4

Determine the positive ideal reference point (A+) and negative ideal reference point (A) respectively.

A + = { a 1 + , a 2 + a n + } = { ( max bij | j C b ) , ( mini bij | j C P ) }
A = { a 1 , a 2 a n } = { ( mini bij | j C b ) , ( max bij | j C P ) }

Where Cb is benefit-type attributes (the higher value is the better) and Cp is benefit -type attribute (the lower value is the better).

Step 5

Compute the distance of all alternatives to the positive and negative ideal reference point (D+ and D) by using Eq. 4 and Eq. 5, respectively.

(4) D i + = j = 1 n ( b i j a j + ) 2
(5) D i = j = 1 n ( b i j a j ) 2

Step 6

Calculate the relative closeness coefficient (R) of each alternative to the ideal reference point by using Eq. 6. Then, conduct the outranking of the alternatives in descending order. The larger value of Ri indicates to the better performance of the alternative.

(6) R i = D i D i + + D i

4 Results and discussion

4.0.1 Pozzolanic activity index (PAI)

The average of three values of compressive strength of mortar prepared for measuring the pozzolanic activity of waste glass powder, steel slag or silica fume are shown in (Figure 2). The ratio between compressive strength of mortar containing supplementary cementitious material (waste glass powder, steel slag or silica fume) and compressive strength of control mortar at the same age is called activity index which assesses the pozzolanic activity of the supplementary cementitious materials as displayed in (Figure 2). The results indicate that the compressive strength of mortar containing waste glass powder or steel slag decreases with increases cement. The reduction of the strength can be attributed to the reduction of the amount of cement and the pozzolanic activity variation of these materials and cement.Moreover, the presence of these materials in cement past lead to delay of C3S and C3A hydration at early age and the activity of the compounds (SiO2 + Al2O3 + Fe2O3) of waste glass powder or steel slag is less than the activity of the same compounds of cement [23, 78].

Figure 2 Activity index at 7 and 28 days
Figure 2

Activity index at 7 and 28 days

Although, The use of waste glass powder and steel slag led to slightly decrease in the strength, these materials are considered in this study due to its pozzolanic activity. As per ASTMC 618 [79], the minimum requirement of strength activity index for a standard pozzolana is 75% at age 7 and 28 days. Therefore, Waste glass powder and steel slag are considered as pozzolanic materials due to the strength activity index of waste glass powder and steel slag, at replacement level 20%, was 87 and 86% at age 7 days and 80 and 79% at age 28 days respectively.

Also, the strength activity index of silica fume was examined according to ASTM C1240 [80]. The results indicate that the strength activity index of silica fume, at replacement level 10%, is 112 and 104% at age 7 and 28 days respectively. As per ASTM C standard mentioned above, the minimum requirement of accelerated pozzolanic activity index of silica fume is 85% at age 7 days. Therefore, this material is considered as pozzolanic material in this research. Moreover, the results indicate that the compressive strength of mortar containing replacement ratio of cement by 10% of silica fume show the highest compressive strength in comparison with other mortars. Indeed, the high fineness, high content of amorphous silicon dioxide of silica fume and sufficient content of calcium hydroxide acquired by hydration of cement play a significant role on improvement production of calcium silicate hydrate (C-SH) supplying additional compressive strength [19].

4.0.2 Workability

Table 9 exhibits the flowability of non-reinforced green mixes. This table indicates that the flowability of the mix decreases with increases the replacement ratio of cement by silica fume or/and steel slag. The high specific surface of silica fume leads to more quantity demand of water for hydration and for flowability [21, 33, 81]. In contrast, waste glass powder content in mix does slightly increase of flow mix by increasing replacement ratio of cement. It might be the effect of glass material which is cleaner in nature. This result is supported by recently studies which conducted by other researchers [33, 82].

Table 9

Non-reinforced green mortar test results.

Mix Name Cement mixes (%) Flow (%) Compressive strength (MPa) Flexural strength (MPa) UPV. (Km/sec) Dry density (Kg/m3)

7day 28day 7day 28day 28day 28day
U1 100%OPC 113 36.465 40.331 6.821 7.823 4.521 2266
U2 90%OPC+10%WGP 113 26.691 31.722 6.012 6.782 4.046 2210
U3 85%OPC+15%WGP 115 33.879 40.017 6.681 7.800 4.402 2256
U4 80%OPC+20%WGP 109 30.373 36.340 6.594 7.497 4.287 2250
U5 90%OPC+10%SG 113 27.892 31.080 6.013 6.691 4.001 2212
U6 85%OPC+15%SG 110 29.608 33.016 6.303 7.142 4.131 2242
U7 80%OPC+20%SG 105 22.989 26.610 5.032 6.209 3.527 2165
U8 94%OPC+6%SF 105 36.948 42.836 6.701 7.482 4.556 2270
U9 92%OPC+8%SF 100 41.533 43.394 6.821 7.563 4.582 2283
U10 90%OPC+10%SF 82 43.372 48.866 7.021 8.032 4.713 2369
U11 80%OPC+8%WGP+12%SG 108 29.269 31.896 6.213 6.679 4.024 2220
U12 80%OPC+10%WGP+10%SG 115 28.059 33.927 5.861 7.380 4.356 2248
U13 80%OPC+5%WGP+15%SG 105 24.799 32.344 5.758 6.977 4.207 2229
U14 78%OPC+10%WGP+12%SG 110 26.887 31.908 5.823 6.782 4.092 2222
U15 75%OPC+12.5%WGP+12.5%SG 113 24.805 32.569 5.523 7.146 4.227 2235
U16 75%OPC+10%WGP+15%SG 109 23.271 30.331 5.227 6.094 4.032 2206
U17 74%OPC+8%WGP+12%SG+6%SF 113 23.204 29.323 5.321 6.502 3.901 2197
U18 72%OPC+8%WGP+12%SG+8%SF 110 25.178 30.088 5.921 6.821 4.021 2210
U19 70%OPC+8%WGP+12%SG+10%SF 108 29.572 32.068 6.221 7.321 4.107 2225

On the other side, the results in Table.10 indicate that the folwability of green mix reduces due to the addition of the sisal fibers. This can be attributed to the amount of cellulose which forms (43-56)% by weight of sisal fibers [83]. The large quantity of hydrophilic hydroxyl groups which containing cellulose make sisal fibers are water-absorbent [84]. The same trend at adding human hair fibers to the mix.

Table 10

Reinforced green mortar test results.

Index Flow (%) Compressive Strength (MPa) Flexural Strength (MPa) UPV. (Km/sec) Dry density (Kg/m3)

7day 28-day 7-day 28-day 28-day 28-day
M0 135 20.480 28.088 4.452 4.831 3.645 2100
M1 128 20.661 28.206 4.686 5.166 3.667 2165
M2 118 21.657 30.170 4.968 5.562 3.919 2173
M3 105 20.773 28.265 4.858 5.202 3.668 2169
M4 132 20.547 29.021 4.621 5.021 3.887 2173
M5 128.6 20.809 30.733 4.829 5.342 3.989 2191
M6 126 20.490 28.675 4.612 5.088 3.701 2137
M7 138.6 21.677 29.012 6.092 6.285 3.901 2234
M8 142 21.930 29.597 6.560 6.767 3.951 2278
M9 144 22.912 32.408 7.005 8.177 3.991 2323
M10 80 23.555 28.578 5.661 5.787 3.698 2260
M11 60 22.130 28.098 5.295 5.638 3.655 2174

Indeed, the chemical composition of cortex and cuticle, which consisted of human hair fiber, rich of keratin peptide bonds as well as to hydrophilic side chains (phenolic, carboxyl, amino, hydroxyl, guanidine, etc.) which contribute to absorption of water [85]. Therefore, addition human hair fibers to the mix led to reduce its flowability. But, the inclusion of stainless steel nails in the mix increases the flowability of mortar as shown in Table 10. This is may be attributed to low porosity and softness of the surface of this type of fibers as well as shape of roller tapered of stainless steel nails.

In hybridization case, it is observed that the flowability of reinforced green mixes with hybrid fibers M10 and M11 was decreased obviously. Therefore, water-binder ratio was increased to 0.58 for obtaining flowability 80% and 60% for M10 and M11 respectively as shown in Table 10. The reduction of flowability of M11 was higher than M10. This can be attributed to the amount of sisal fibers and stainless steel nails which was used in the both mixes. The increment of sisal fiber volume fractions and reduction of stainless steel nails volume fraction in M11 led to decrease its flowability compared with M10.

4.0.3 Compressive strength

Table 9 lists the results of the compressive strength of non-reinforced green mortar. The results indicated that the compressive strength of mortars containing replacement ratio of cement by waste glass powder and steel slag was decreased in comparison with control mortar (U1) at 7 and 28 days. The decreasing rate was by 21.345, 0.778 and 9.895% at age 28 days for U2, U3 and U4, respectively. And by 22.937, 18.137 and 34.020% at age 28 days for U5, U6 and U7, respectively, in comparison with control mortar. So, the replacement 15% of cement by waste glass powder or steel slag boosts the best performance in comparison with 10 and 20% replacement ratio of cement.

Moreover, the results of mortar using of the mixture of waste glass powder and steel slag as partial replacement of cement indicated that the compressive strength was reduced in comparison with control mortar at 7 and 28 days. The reduction was by 20.914, 15.878, 19.803, 20.884, 19.245 and 24.794% at age 28 days for U11, U12, U13, U14, U15 and U16, respectively. And, the reduction of compressive strength was by 27.294, 25.397 and 20.487% at age of 28 days for the mixes U17, U18 and U19, respectively, compared to control mortar.

The reduction of mortar strength containing waste glass powder or /and steel slag can be attributed to the decreasing of the amount of cement in the mix and the contribution of the hydration or the pozzolanic reactivity of waste glass powder or steel slag did not compensate for the reduction of the cement content [86]. Moreover, the presence of slag in cement mortar leads to slightly delay the hydration of C3S at early age where slag acts as retarder to the hydration of compound C3A [87].

Although, the results show that the presence of waste glass powder and steel slag led to decrease the strength, the reduction of the strength of mortar containing waste glass powder was lower than mortar containing slag. This is attributed to the high content of amorphous of silicon dioxide (72.71%) and the sufficient content of Na2O in waste glass powder. Indeed, the presence of Na2O in acceptable level led to act as a catalysts in forming calcium silicate hydrate in early age [78, 86].

While, the results of the mortar containing replacement ratio of cement by silica fume indicate that the compressive strength increases with increase silica fume content in the mortar compared with control mortar. The increments were by 6.211, 7.594 and 21.162% at age 28 days for U8, U9 and U10, respectively.

The increases in the compressive strength can be attributed to the decreased volume of large pores in the cement mortar and the spaces between fine aggregate and cement past due to its high fineness [63, 78]. Moreover, silica fume have significant role on the reducing of Ca(OH)2 resulted from cement hydration by reacting with it to form C3S2H3 [63, 78]. Thus, the presence of silica fume was enhanced the strength of mortar in this study.

On the other side, the drop in compressive strength of mortar containing silica fume, waste glass powder and steel slag blended cement can be attributed to the reasons mentioned above regarding to the presence of waste glass powder and steel slag. Although, the silica fume contributes to increase the strength of mortar the agglomeration of silica fume, which cannot be broken down by normal mixing, lead to decrease the strength. The core of agglomeration does not take part in hydration. Thus, it cause the weakness in binder paste [29].

Table 10 shows the results of reinforced green mortar with mono and hybrid fibers. This Table shows that the compressive strength of M1, M2 and M3 was increased by 0.420%, 7.412% and 0.630%, respectively, at age 28 days compared with control mortar M0. The higher increase was observed at M2 then the compressive strength of M3 was demonstrated the reductions by 4.081 and 6.314% at 7days and 28 days respectively. The increase in compressive strength may be attributed to identical SIF percent and bond strength between the surface of sisal fibers and composites of mortar which led to diminish of porosity of hardened mortar [59].

While, reinforced mix by 0.5, 0.75 and 1% of human hair volume fractions led to increase the compressive strength of mortar by 3.321, 9.416 and 2.089% at 28 days respectively. This enhancement in compressive strength come back to the proper amount of HHF which did not lead to cause balling and lumping of HHF during the mixing process as well as high modulus, high tensile strength of HHF and its ability to reduce the micro-fractures or cracks of hardened mortar [54]. Also, it can be seen that the inclusion 1% of HHF in the mix led to decrease the compressive strength by 1.532 and 2.089% at age 7 and 28 days respectively in comparison with M5 as listed in Table 10. This reduction can be attributed to the agglomeration of HHF during blending with composites of mortar which has resulted in non-homogeneity mix as noted by [50].

Moreover, the results in Table 14, indicates that the compressive strength of M7, M8 and M9 increased by 3.290%, 5.372% and % 15.380, respectively at age 28 days in comparison with control mortar (M0). The increasing of compressive strength can be ascribed to the good mechanical bond strength between the stainless steel nails and mortar.

Table 11

Estimated cost of material used

Materials Quantity Cost in USD ($)
OPC 1000 Kg 67$
WGP 1000 Kg 55$1
SG 1000 Kg 55$1
SF 1000 Kg 850$
Local River Sand 1000 Kg 17$
Superplasticizer 1000 Liter 1000$
SIF 1000 Kg 150$
HHF 1000 Kg 100$2
SNF 1000 Kg 800$
  1. 1: Grinding cost, 2: Collecting and Washing cost

Table 12

Estimated cost of reinforced green mortar

Index OPC (Kg/m3) Sand (Kg/m3) WGP (Kg/m3) SG (Kg/m3) SF (Kg/m3) SIF (Kg/m3) HHF (Kg/m3) SNF (Kg/m3) Sp. (L/m3) Cost in USD
M0 358 1405 41 61 51 - - - 10 106.831
M1 358 1405 41 61 51 7 - - 10 107.881
M2 358 1405 41 61 51 10.5 - - 10 108.406
M3 358 1405 41 61 51 14 - - 10 108.931
M4 358 1405 41 61 51 - 2 - 10 107.031
M5 358 1405 41 61 51 - 3 - 10 107.131
M6 358 1405 41 61 51 - 4 - 10 107.231
M7 358 1405 41 61 51 - - 66.8 10 160.271
M8 358 1405 41 61 51 - - 100 10 186.831
M9 358 1405 41 61 51 - - 134.6 10 214.511
M10 358 1405 41 61 51 7 2 100 10 188.081
M11 358 1405 41 61 51 10.5 2 66.8 10 162.046
Table 13

The pair-wise comparison matrix (F) of reinforced green mortars (AHP method).

Compressive strength Flexural strength UPV Cost in USD
Compressive 1 1 2 1/3
strength
Flexural 1 1 2 1/3
strength
UPV 1/2 1/2 1 1/3
Cost in USD 3 3 3 1
Table 14

Matrix X calculated and weights of criteria of reinforced green mortars (AHP method).

Compressive strength Flexural strength UPV Cost in USD
Compressive strength 0.181818 0.181818 0.25 0.166667
Flexural strength 0.181818 0.181818 0.25 0.166667
UPV 0.090909 0.090909 0.195076 0.118371
Cost in USD 0.545455 0.545455 0.375 0.5
Weight 0.195076 0.195076 0.118371 0.491478

For hybrid fiber reinforced mortar, the compressive strength of M10 and M11 has shown increment by 1.744 and 0.035%, respectively, at age of 28 days, compared with control mortar.

4.0.4 Ultrasonic pulse velocity (UPV)

Table 9 illustrates the results of ultrasonic pulse velocity test (UPV) of non-reinforced green mortar. The results indicate that the UPV of mortar containing waste glass powder and steel slag was decreased compared to control mortar. The decreasing recorded rate ranged from 2.632 to 10.506% due to partial replacement of cement by WGP. Also, there were remarkable decreases of UPV due to the partial replacement of cement by SG. Such decreases ranged from 8.626 to 21.986% by such replacement. In contrast, the mortar containing replacement ratio of cement by the silica fume exhibited slight increases of UPV. The increasing rate ranged from 0.774 to and 4.246% by partial replacement of cement with SF. The grain size and high quantity of hydration products (C-S-H and CH) of silica fume in comparison with WGP and SG led to reduction in porosity and void ratio of hardened mortar [86]. Thus, UPV of mortar containing silica fume higher than UPV of mortar containing waste glass powder or/and steel slag.

The similar trend for mortar containing WGP, SG and SF blended cement. UPV results revealed mild to moderate decreases by the inclusions of different percentages of such cementitious materials.

However, the highest reduction of UPV has been obtained due to replacement of cement by to WGP and SG which has less efficiency compared with silica fume resulting in porosity and void ratio increases in the hardened mortar which cause decreasing in UPV [87].

The results in Table 10 indicate that the UPV of sisal fiber reinforced mortar, Human hair fiber reinforced mortar and stainless steel nail reinforced mortar showed higher values of UPV than that of control mortar. The increases in such values ranged from 0.603 to 9.492% for mixes (M1-M9). Moreover, the results of mortar containing hybrid fibers showed that the UVP of M10 and M11 increased by 1.454 and 0.274%, respectively, compared with control mortar. This can be attributed to good mechanical bond between the fibers and cementitious matrix and the ability of fibers to arrest cracks at the micro and macro levels which leads to densify of the microstructure and decrease the cracks and porosity in hardened mortar.

4.0.5 Flexural strength

The results of flexural strength of non-reinforced green mortar are given in Table 9. The results indicate that the flexural strengths of mortar containing waste glass powder or/and steel slag were decreased in comparison with control mortar (100%OPC). This can be attributed to the same reasons mentioned in compressive strength. However, a slight increase in flexural strength of mortar prepared by 90% OPC+10% SF has been recorded.

While, the results indicate that the flexural strength of mortar containing mono or hybrid fibers was higher than control mortar as listed in Table 10. The highest increases were 15.131, 10.577 and 69.261%at age 28days for individual fibers form 0.75% SIF, 0.75% HHF and 2% SNF. The developing of the flexural strength can be attributed to the good mechanical bond between the fibers and cementitious matrix. The presence of fibers, on the other hand, had a beneficial effect on the post-crack behavior, promote the flexural strength and ductility and hence toughness of the mortar [43]. The increasing of flexural strength was mainly observed in the reinforced mortar containing higher volume fraction of stainless steel nails due to the high elastic modulus of stainless steel nails compare to other fibers.

In hybridization case, It is observed that the flexural strength of M10 and M11 was higher than of control mortar. The increases were by 19.788 and 16.704% respectively, at age 28 days. Moreover, the increment of the flexural strength of M9 was higher than that of M10 and M11. The increments were by 41.299 and 45.034% at age 28days, respectively. The use of mono stainless steel fibers shows a significant increment of flexural strength for mortar. While, the use of this type of the fiber with sisal fibers and human hair fibers in hybrid form led to decrease the flexural strength in comparison with mortar containing stainless steel nails in mono form. This can be attributed to clearly decrease the flowability of reinforced mortar with hybrid fibers. Besides of that, some of sisal fibers and human hair fibers were agglomerated leading to cause non-homogeneous mix.

4.0.6 Dry density

Table 9 depicts the results of oven dry density of non-reinforced green mortars. The obtained results indicate that the dry density of control mortar (100% OPC) was higher than mortar containing waste glass powder or/and steel slag. The decreasing of the density can be ascribed to the greater variation between pozzolanic reactivity of cement and supplementary cementitious materials (waste glass powder and steel slag) which led to increase the voids ratio and the porosity in hardened mortar. In contrast, the density of mortar containing silica fume. The results indicates that the density of mortar U8, U9 and U10 was higher than of control mortar (100%OPC). The increasing was by 0.176, 0.750 and 4.545% respectively. This is because of high amount of amorphous silicon dioxide made by silica fume to reduce Ca(OH)2 provided by cement hydration to form calcium silicate hydrate gel [39, 54]. Moreover, the high fineness of silica fume made it acts as filler material and because of which fits the spaces between cement past matrix and the aggregate cement paste interfacial zone leading to improve the density of hardened mortar [20]. Also, it is observed that the dry density of M1, M2 and M3was higher than Control mortar(M0). The increasing was by 3.095, 3.476 and 3.285% respectively as shown in Table 10. The same trend for M4, M5 and M6, there was little increasing by 3.476, 4.333 and 1.761% respectively. The reason can be attributed to good mechanical bond between cementitious matrix and fibers. Moreover, the use of sisal fibers and human hair fibers can contribute to fill the micro space in cementitious matrix leading to improve the density. Moreover, the inclusion of 1, 1.5 and 2% volumetric fraction of stainless steel nails led to increase the oven dry density. The increasing was by 6.380, 8.476 and 10.619%for M7 ,M8 and M9 in comparison with control mortar (M0). This is because of high specific gravity of stainless steel nails and ability of this type of fibers to improve inter-facial bond characteristics between the matrix and fibers.

For hybridization mixes, the results Indicate that the dry density of M10 and M11was increased by 7.619 and 3.523, respectively, in comparison with control mortar (M0).This enhancements are attributed to appropriate ratio uses of sisal fiber, human fiber and stainless steel nails volume fraction which led to improve the microstructure of matrix [48, 54].

4.1 Estimation of green mortar cost

The estimated cost of reinforced green mortar was evaluated on the basis of the different materials which were used to prepare green mortar as listed in Table 11-12. The estimated cost of each material was depended on the existing market cost.

4.2 Selection of the best green mortar

The integrated AHP and TOPSIS method was also used to rank and select the best reinforced green mortar. In this stage, there were twelve [12] alternatives and four [4] criteria of reinforced green mortars. The alternatives were represented the reinforced green mortars. The criteria were represented the properties of the reinforced green mortar which were Compressive strength, Flexural strength, UPV and Cost. Based on AHP method, the weight for each criterion was calculated. The matrices and results, which were obtained through applying of AHP method to evaluate the criterion weight,were illustrated in Table 13-14. The checking of pair-wise matrix (F) was achieved according to the step 4 which was previously mentioned in the general steps of AHP method. The results were listed in Table 15. The consistency index (CI) obtained was 0.020 and the random consistency obtained from Table 8 was 0.9. Thus, the pair-wise comparison matrix was considered in this study due to the consistency ratio was 0.022. Then, TOPSIS method was applied to rank the reinforced green mortars. The raw data used in the TOPSIS technique, were listed in Table 16. The matrices and the results obtained from this technique were show in Table 17-18. Table 19 showed that the second mix of the reinforced green mortar is the best as it got the rank 1 and the ninth mix is the worst mix as it got the rank 11.

Table 15

Matrix Y for checking the pair-wise comparison matrix evaluated in AHP method.

Compressive strength Flexural strength UPV Cost in USD Si Si/wi
Compressive strength 0.195076 0.195076 0.236742 0.163826 0.79072 4.053395
Flexural strength 0.195076 0.195076 0.236742 0.163826 0.79072 4.053395
UPV 0.097538 0.097538 0.118371 0.163826 0.477273 4.03201
Cost in USD 0.585228 0.585228 0.355113 0.491478 2.017047 4.104043
Table 16

The alternatives and criteria used in TOPSIS method for ranking of reinforced green mortars.

Index Compressive Strength (MPa) Flexural Strength (MPa) UPV (Km/sec) Cost in USD

28 days 28 days 28 days
A1 28.206 5.166 3.667 107.881
A2 30.170 5.562 3.919 108.406
A3 28.265 5.202 3.668 108.931
A4 29.021 5.021 3.887 107.031
A5 30.733 5.342 3.989 107.131
A6 28.675 5.088 3.701 107.231
A7 29.012 6.285 3.901 160.271
A8 29.597 6.767 3.951 186.831
A9 32.408 8.177 3.991 214.511
A10 28.578 5.787 3.698 188.081
A11 28.098 5.638 3.655 162.046
Table 17

Normalized decision matrix (V) obtained from TOPSIS method for reinforced green mortars.

Compressive strength Flexural strength UPV Cost in USD
A1 0.289572 0.264401 0.289208 0.221168
A2 0.309736 0.284669 0.309083 0.222244
A3 0.290178 0.266244 0.289287 0.22332
A4 0.29794 0.25698 0.306559 0.219425
A5 0.315515 0.273409 0.314604 0.21963
A6 0.294387 0.260409 0.29189 0.219835
A7 0.297847 0.321673 0.307663 0.328573
A8 0.303853 0.346342 0.311607 0.383024
A9 0.332712 0.418507 0.314761 0.439771
A10 0.293392 0.296185 0.291653 0.385587
A11 0.288464 0.288559 0.288262 0.332212
Table 18

The weight normalized decision matrix (B) and the positive and negative ideal reference point obtained from TOPSIS method.

Compressive strength Flexural strength UPV Cost in USD
A1 0.056489 0.051578 0.034234 0.108699
A2 0.060422 0.055532 0.036586 0.109228
A3 0.056607 0.051938 0.034243 0.109757
A4 0.058121 0.050131 0.036288 0.107842
A5 0.061549 0.053336 0.03724 0.107943
A6 0.057428 0.0508 0.034551 0.108044
A7 0.058103 0.062751 0.036418 0.161486
A8 0.059274 0.067563 0.036885 0.188247
A9 0.064904 0.081641 0.037259 0.216137
A10 0.057234 0.057779 0.034523 0.189507
A11 0.056272 0.056291 0.034122 0.163275
a i + 0.064904 0.081641 0.037259 0.107842
a i - 0.056272 0.050131 0.034122 0.216137
Table 19

The distance to the positive and negative ideal reference point (Di+ and Di), Relative closeness coefficient (Ri) to the ideal reference point and the ranking for each alternative.

Number of mix Alternative Di+ Di Ri Ranking of the alternative
1 A1 0.031376 0.107448 0.773987 4
2 A2 0.026535 0.107155 0.801518 1
3 A3 0.031046 0.106396 0.774116 3
4 A4 0.032247 0.108332 0.770613 6
5 A5 0.028503 0.108415 0.791824 2
6 A6 0.03185 0.108102 0.772422 5
7 A7 0.057284 0.056166 0.495073 7
8 A8 0.081823 0.033142 0.288279 9
9 A9 0.108295 0.032821 0.232582 11
10 A10 0.085468 0.027726 0.244942 10
11 A11 0.061642 0.05322 0.463339 8

5 Conclusions

Some conclusions are revealed for this study which deals with the production of green mortar as follows:

  1. Replacement of OPC by 10, 15 and 20% of WGP or SG with or without using superplasticizer leads to decrease the compressive strength of mortar. The replacement ratio of 15% from WGP shows the best performance of mortar compared with another replacement ratio. Thus, the percentage of compressive strength decrease is 0.778% compared with control mortar mix.

  2. Incorporation of 10% SF as replacement of OPC with or without utilizing superplasticizer, gives the highest increase in the compressive strength strength by about 21% compared to control mix. Also the UPV and density for such mortar mix shows increases from 4.512 to 4.713 Km/sec and 2226 to 2369 Kg/m3 compared to control mortar mix.

  3. Inclusion of mono fibers into the green mortar shows significant increases in flexural strength compared with control mortar. Using mono sisal fiber, human hair fiber and stainless nails fiber by 0.75, 0.75 and 2% of volume fraction, respectively, gives the highest increases compared with control mortar in compressive strength, by about 7.4, 9.4 and 15.4%, respectively. And in flexural strengths are increased by about 15.1, 10.6 and 69.3%, respectively. UPV values are increased by 3.47, 4.33 and 10.6%, respectively.

  4. The hybridization of sisal fibers, human hair fibers and stainless steel fibers gives remarkable increases in the compressive strength, flexural strength and UPV compared with control mortar. The highest increases of compressive strength, flexural strength and UPV are 1.7, 19.7 and 1.45, respectively, for the mortar mix with 0.5% SIF + 0.5% HHF + 1.5% SNF compared with control mortar mix.

  5. The use of integrated AHP and TOPSIS method shows good strategy for the selection of best mortar mixes weather they are reinforced or non-reinforced green mortar. Such methods help the researchers for selecting the best green mortars which are economic and ecofriendly mortars that possess positive impacts on the environment.

Acknowledgement

The work described in this paper has been conducted in the laboratory of the technical engineering college of Mosul-Northern Technical University.

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Received: 2020-08-03
Accepted: 2020-10-06
Published Online: 2020-11-19

© 2021 E. Thanon Dawood and M. Hani Abdullah, published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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Heruntergeladen am 20.11.2025 von https://www.degruyterbrill.com/document/doi/10.1515/eng-2021-0006/html
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