Optimization of Batch Conditions for COD and Ammonia Nitrogen Removal Using cockle shells Through Response Surface Methodology

Abstract

NH 3-N (Y NH3-N) by using response surface methodology (RSM) via central composite design (CCD). RSM

Enhancing drilling mud performance through CMITS-modified formulations: rheological insights and performance optimization

“…29 where β is the regression coefficient, i and j are the linear and quadratic coefficients, respectively, k represents the number of examined factors optimized by the experiment while e represents the random error. 30…”

“…where b is the regression coefficient, i and j are the linear and quadratic coefficients, respectively, k represents the number of examined factors optimized by the experiment while e represents the random error. 30 Design expert was used for empirical model development, optimization, and conrmation of the models. The optimization module searches for a combination of factor levels that simultaneously satisfy the criteria placed on each of the responses and factors.…”