2021
DOI: 10.1016/j.jclepro.2021.128208
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Less is more: Optimising the biocementation of coastal sands by reducing influent urea through response surface method

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Cited by 17 publications
(8 citation statements)
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“…One limitation of MICP is ammonia production, as it is a by-product of the process of urea hydrolysis which may contaminate drinking water and affect health if it seeps into groundwater. However, this can be handled by treating the effluent to remove ammonia, such as by using the response surface method (RSM) [5] or using it as a fertilizer for plants [6].…”
Section: Introductionmentioning
confidence: 99%
“…One limitation of MICP is ammonia production, as it is a by-product of the process of urea hydrolysis which may contaminate drinking water and affect health if it seeps into groundwater. However, this can be handled by treating the effluent to remove ammonia, such as by using the response surface method (RSM) [5] or using it as a fertilizer for plants [6].…”
Section: Introductionmentioning
confidence: 99%
“…Consequently, the contour's red zone indicates the ideal operational parameters. The circular orbits observed in the 2D contour remain consistent across all regions of color variation, with no individual circular orbit deviating or appearing anomalous [ 79 ]. Each element examined demonstrates a noteworthy influence on the targeted response.…”
Section: Resultsmentioning
confidence: 99%
“…The R 2 was 0.9926, which indicated that the model was a good fit for the data points. 38 However, adding more data points can change the R 2 value because of model overfitting, and adjusted (0.9937) and predicted (0.9902) R 2 values can be used to prevent overfitting. In the current study, the difference between the adjusted and predicted R 2 values was less than 0.2, which demonstrated that the selected quadratic model had high accuracy.…”
Section: Resultsmentioning
confidence: 99%
“…The standard deviation was 1.04, and the coefficient of variance was 1.50%. The R 2 was 0.9926, which indicated that the model was a good fit for the data points . However, adding more data points can change the R 2 value because of model overfitting, and adjusted (0.9937) and predicted (0.9902) R 2 values can be used to prevent overfitting.…”
Section: Resultsmentioning
confidence: 99%