Environmental Engineering Reference
In-Depth Information
making building construction element. The Response Surface Methodology
model was employed to optimize the process for maximizing products quality
using classic mixture approach. To verify, the model was fit to data using
analysis of variance (ANOVA) and least squares techniques, validated and
interpreted graphically using contour plot, trace plots and 3D graph. Numerical
optimization using desirability functions was done to find the optimum
mixture proportions. Statistical analysis for the response compressive strength,
water absorption capacity, shrinkage, density and leachate of lead and
cadmium in the jarosite waste composite bricks were performed. The details
are summarized in the following sections.
1.1. Response Surface Methodology
Response Surface Methodology (RSM) was employed (Myers and
Montgomery, 1995) in optimizing the experimental data for achieving the
most desired results where several factors including quantity of individual
component such as jarosite waste, CCRs and clay as well as their chemical
constitutions concentration influence the quality of s/s sintered composites.
The steps involves in RSM are:
1.
Experimental design
2.
Modelling, and
3.
Optimization
1.2. Experiment Design
Consider a brick consisting of q component materials (where q is the
number of component materials namely jarosite waste, CCRs and clay). For
this, two experimental design approaches can be applied to optimize brick
propertiesie. (i) the classic mixture approach, in which the q mixture
components are the variables, (Cornell, 1990) and (ii) the mathematically
independent variable (MIV) approach, in which q mixture components are
transformed into q-1 independent mixture-related variables (Piepel and
Cornell, 1994). In this study, the classic mixture approach was used to
optimize the brick characteristics. As the sum of the proportions must be 1 in
the classic mixture approach, the variables are not all independent. Hence, the
experimental region of interest can be defined more naturally. The MIV
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