Modeling a rheological cement mixture suitable for 3D printing technology with Fuzzy Logic

Abstract

The material preferred in additive manufacturing technology 3D printing, which has advanced in current years and has been utilized in the construction sector, is a cement-based mixture. Considering the experimental studies for this mixture, which does not have a definite formulation, the success of the resulting products shows the rheological properties that enable the material to be built. Data on the constructability of the material can be obtained by defining the volume ratios of the resulting samples with the Fuzzy Logic method. For the constructability of the material, a Mamdani type fuzzy model was created and the "CENTROID center of gravity" method was stipulated as the clarification method. While the component material ratios of the cementitious mixture create the fuzzy inputs of the system, static and dynamic yield stresses are reached as fuzzy output values. 15 rules obtained from experimental studies that enable the system to work were defined and then the operation of the method was tested. In this study, it is aimed to develop a decision mechanism for intermediate values that are not encountered in the experimental results by blurring the mixture models supported with definite findings.

Energy Efficiency with Internet of Things Based Fuzzy Inference System for Room Temperature and Humidity Regulation

“…Fuzzy output is obtained through the execution of some fuzzy membership functions. There are several methods that can be used in the defuzzification process, namely (1) Weighted Average Method (58)(59)(60), a method that calculates the average value by assigning a certain weight or weight to each element in the data set aimed at reflecting the relative importance or contribution of each element to the final result, (2) Mean-Max Membership (61)(62)(63), a method that combines several overlapping membership rules by taking the maximum value of each set membership at a point, then calculate the average of those maximum values, (3) Centroid (Center of Gravity) Method (64,65), a method that calculates the center point (centroid) of a membership set using the weighted principle based on membership level. The membership value of each point on the set is multiplied by the position of that point, then added and divided by the total membership value, (4) Height Method (Max-Membership Principle) (66,67), a method that takes the maximum value of the membership level in a membership set as a representation of the membership value of the entire set, (5) Center of Sums (68-70), a method that calculates the center of input values by adding input points and dividing them by the total number of inputs, (6) First (or Last) of Maxima (66,71,72), a method that selects the first (or last) point at which the membership level reaches the maximum value of a membership set as a representation of the overall membership value of that set, and (7) Center of Largest Area (73,74), a method that calculates the center of the area of a membership set by taking the midpoint at the interval with the largest set area.…”