PSI - Issue 73

Sushant Chaudhary et al. / Procedia Structural Integrity 73 (2025) 19–26 Pratanu Ghosh / Structural Integrity Procedia 00 (2025) 000–000

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methods—in estimating the strength of zeolite-based concrete mixtures. • To determine the optimal datum temperature and activation energy values for zeolite-based concrete mixes to enhance the precision of strength predictions. • To evaluate strength prediction models, including exponential, hyperbolic, and logarithmic functions, for estimating strength gain in zeolite-based concrete. • To analyze the relationship between zeolite content and the accuracy of maturity-based strength predictions in binary and ternary mixtures blended with zeolite. 3. Materials and Methods 3.1. Materials This research focuses on ten different binary and ternary concrete mixtures with a w/c ratio of 0.4 and incorporating natural zeolite (Z) in varying proportion along with various SCMs including metakaolin (M), silica fume (SF), pumice (P), and GGBS slag of grade 120 (G120S), as listed in Table (1). Each mixture contained 335 kg/m 3 of cementitious materials and included preparing 17 cylindrical specimens (100 mm × 200 mm) in two batches and curing them in a lime water tank at room temperature (22-24 0 C). The nomenclature of the mixtures was chosen based on the percentage contribution by mass of each cementitious material, e.g., 80 TII-V/ 20 Z means 80% of type II-V Ordinary Portland Cement (OPC) and 20% zeolite. The selection of proportions of different SCMs for mixtures was conducted based on previous research, which provided the most optimal performance-based output [Tran (2015), Ganesan (2017)]. Table 1 shows all mixture compositions. A high-range water reducer and an air entraining admixture were used to obtain better fresh concrete properties. Compressive strength development was monitored by destructive testing of three cylinders for each mixture using a Universal Testing Machine (UTM) at 1, 3, 7, 14, and 28 days. At the same time, maturity measurements were conducted using multi-channel maturity meters and SmartRock sensors. Two sensors were utilized for each concrete mixture- one for each batch, and the maturity index was calculated using the average temperature from both sensors for each mixture.

(a)

(b) (c) Figure 1: (a) Maturity meter; (b) Universal Testing; (c) Machine (UTM)

Table 1: Concrete mixtures composition

Percentage by weight of total cementitious materials (%)

Mixture ID

Mixtures

Type II-V OPC (TII-V)

Metakaolin (M)

Silica Fume (SF)

Slag (G120S)

Zeolite (Z)

Pumice (P)

1 2 3 4 5 6 7 8

100 TII-V

100

-

- - - - - -

- - - - - - -

- - - - - - - -

- - - - - - - -

90 TII-V/ 10 Z 85 TII-V/ 15 Z 80 TII-V/ 20 Z 75 TII-V/ 25 Z 70 TII-V/ 30 Z

90 85 80 75 70 70 78

10 15 20 25 30 20 20

70 TII-V/ 20 Z/ 10 M 78 TII-V/ 20 Z/ 7 SF

10

-

7