Response Surface Methodology to optimize the cement paste mix design: Time-dependent contribution of fly ash and nano-iron oxide as admixtures

Soto-Pérez, Linoshka; López, Valerie; Hwang, Sangchul

doi:10.1016/j.matdes.2015.07.049

Cited by 41 publications

(6 citation statements)

References 18 publications

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“…There are some methods dealing the effect of several features on laboratory-based target variable (Köken and Lawal, 2021). One of them is to use response surface methodology (RSM) which uses the multivariate nonlinear regression method and strive for the optimal experimental conditions (Oraon et al, 2006;Palanikumar, 2007;Soto-Pérez et al, 2015). Being one of the most entirely used experimental design ways, RSM uses central composite design (CCD) for appraising the link between autonomous factors and responses (Zhu et al, 2021a).…”

Section: Introductionmentioning

confidence: 99%

Strength Analysis and Optimization of Alkali Activated Slag Backfills Through Response Surface Methodology

Dai

Ren

et al. 2022

Front. Mater.

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The significant difference in water-to-binder ratio, activator type and concentration between alkali-activated slag (AAS) paste/mortar/concrete and AAS-based cemented paste backfill (AAS-CPB) means that previous results related to the properties and mix optimization of AAS materials cannot be directly translated to AAS-CPB. This study statistically identifies the effect of key influential variables such as silicate modulus, slag fineness and activator concentration on 3- and 28 day unconfined compressive strength (UCS) of AAS-CPB by central composite design (CCD) established in response surface methodology (RSM). In this study, the prominence of independent variables and their relations are investigated by using ANOVA (analysis of variance) having a significant level of 0.05. ANOVA results certify that there is a strong link between the level of variable contribution on UCS performance of AAS-CPB and curing age. Obviously, silicate modulus and activator concentration are the most major variables influencing UCS at 3 and 28 days, respectively. Increased fineness of slag and higher pH of pore solution enhance 3 day UCS, but restrain the further hydration of unreacted slag and subsequent the gain in strength at advanced curing ages. The combination of independent variables of silicate modulus (0.295), slag fineness (12630.2), activator concentration (0.45) gives the optimum responses.

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Section: Introductionmentioning

confidence: 99%

Strength Analysis and Optimization of Alkali Activated Slag Backfills Through Response Surface Methodology

Dai

Ren

et al. 2022

Front. Mater.

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“…Existing studies on the optimization of cementitious composites have used classic response surface designs, such as central composite design (CCD) [ 29 , 30 ] and Box–Behnken design (BBD) [ 29 , 31 ]. Aside from these classic response surface designs, computer-aided designs, such as the I-optimal and D-optimal designs, are also increasing in popularity.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the Compressive Strength and Time of Setting of Low-Calcium Fly Ash Geopolymer Paste Using Response Surface Methodology

et al. 2021

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Approximately 2.78 Mt of coal fly ash is produced in the Philippines, with a low utilization rate. Using fly ash-based geopolymer for construction will lessen the load sent to landfills and will result in lower GHG emissions compared to OPC. It is necessary to characterize the fly ash and optimize the geopolymer components to determine if it can replace OPC for in situ applications. The activator-to-precursor ratio, the water-to-solids ratio, and the sodium hydroxide-to-sodium silicate ratio were optimized using a randomized I-optimal design from the experimental results of 21 runs with five replicates, for a total of 105 specimens of 50 mm × 50 mm × 50 mm paste cubes. The engineering properties chosen as the optimization responses were the unconfined compressive strength (UCS), the initial setting time, and the final setting time. The samples were also ambient-cured with the outdoor temperature ranging from 30 °C to 35 °C and relative humidity of 50% ± 10% to simulate the on-site environment. Runs with high unconfined compressive strength (UCS) and short setting times were observed to have a low water-to-solids (W/S) ratio. All runs with a UCS greater than 20 MPa had a W/S ratio of 0.2, and the runs with the lowest UCS had a W/S of 0.4. The initial setting time for design mixes with a W/S ratio of 0.2 ranged from 8 to 105 min. Meanwhile, five out of seven design mixes with a W/S ratio of 0.4 took longer than 1440 min to set. Specimens with an alkali activator ratio (NaOH/WG) of 0.5 (1:2) and 0.4 (1:2.5) also had significantly lower setting times than those with an alkali activator ratio of 1. The RSM model was verified through confirmatory tests. The results of the confirmatory tests are agreeable, with deviations from the expected UCS ranging from 0 to 38.12%. The generated model is a reliable reference to estimate the UCS and setting time of low-calcium FA geopolymer paste for in situ applications.

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“…Studies on cement production optimisation have been carried out on clinker simulation using AspenTech [36], cement raw materials blending using a general nonlinear time-varying model [37], cement grinding using population balance model [6], clinker chemistry and kiln energy efficiency using metaheuristic optimization techniques [38], numerical and computational fluid dynamics study of cement calciner [16]. RSM has been efficient and accurate in studies on cement and concrete technology [39][40][41][42][43]. This study focused on the simulation of an integrated wet cement process flow sheet using Aspen HYSYS and optimisation of the cement production rate at minimum raw material feed using CCD of response surface methodology.…”

Section: Introductionmentioning

confidence: 99%

Simulation and Optimization of an Integrated Process Flow Sheet for Cement Production

Fadayini¹,

Obisanya²,

Ajiboye³

et al. 2021

Cement Industry - Optimization, Characterization and Sustainable Application

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In this study the process flow diagram for the cement production was simulated using Aspen HYSYS 8.8 software to achieve high energy optimization and optimum cement flow rate by varying the flow rate of calcium oxide and silica in the clinker feed. Central composite Design (C.C.D) of Response Surface Methodology was used to design the ten experiments for the simulation using Design Expert 10.0.3. Energy efficiency optimization is also carried out using Aspen Energy Analyser. The optimum cement flow rate is found from the contour plot and 3D surface plot to be 47.239 tonnes/day at CaO flow rate of 152.346 tonnes/day and the SiO2 flow rate of 56.8241 tonnes/day. The R2 value of 0.9356 determined from the statistical analysis shows a good significance of the model. The overall utilities in terms of energy are found to be optimised by 81.4% from 6.511 x 107 kcal/h actual value of 1.211 x 107 kcal/h with 297.4 tonnes/day the carbon emission savings.

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Response Surface Methodology to optimize the cement paste mix design: Time-dependent contribution of fly ash and nano-iron oxide as admixtures

Cited by 41 publications

References 18 publications

Strength Analysis and Optimization of Alkali Activated Slag Backfills Through Response Surface Methodology

Strength Analysis and Optimization of Alkali Activated Slag Backfills Through Response Surface Methodology

Investigation on the Compressive Strength and Time of Setting of Low-Calcium Fly Ash Geopolymer Paste Using Response Surface Methodology

Simulation and Optimization of an Integrated Process Flow Sheet for Cement Production

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