Estimation and optimization of shear strength for compacted iron powders by means of soft computing paradigms

Lotfi, Behnam; Sadeghian, Zohreh; Beiss, Paul

doi:10.1016/j.matdes.2012.08.076

Cited by 5 publications

(1 citation statement)

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“…Based on the realization on experimental findings, in the present work, we have adopted two data-driven based modeling approaches, so called GA-fuzzy approach as described in Section 2 to model the equivalent hardness of particle reinforced flexible mould materials. In the paradigm of materials design and prediction of equivalent properties of composite material, nowadays these techniques are effectively used by many researchers [31][32][33][34].…”

Section: Fuzzy Rule Based Modeling Of Equivalent Hardnessmentioning

confidence: 99%

GA-fuzzy based estimation of equivalent hardness of particle reinforced flexible mould material composites

Nandi

2014

Journal of Intelligent &Amp; Fuzzy Systems

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In the present work, an extensive experimental study on the equivalent hardness of various particle reinforced flexible mould materials is carried out. From the experimental study, it has been observed that the equivalent hardness of a composite mould material depend on many factors, such as filler content, morphology and type of filler particles, etc. Some of the factors may be correlated with each other and sometimes belong to uncertainty and ambiguity such as dispersion state of filler in the matrix, non-uniform filler particle size and shape. Moreover, the formation of physical bonding of filler particles with matrix polymer is highly complex and non-linear, because they are depending on such kind of parameters that are associated with uncertainty and ambiguity. By realizing it, an effort has been made to develop a model using a GA-fuzzy approach to estimate equivalent hardness of particle reinforced mould materials. An appropriate model is decided by carrying out a comparative analysis on the effectiveness of developed models based on different structures of TSK-type fuzzy rule-consequent function with the experimental measurements. It is found that better performance is envisaged by TSK-type fuzzy model which considers the variables namely hardness of polymer, hardness of filler material, volume fraction of filler particle as well as interactions among them in the ruleconsequent function. In addition, the developed model seems to possess a generic one which can be applicable to a wide range of two-phase particle-reinforced composite mould materials.

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Section: Fuzzy Rule Based Modeling Of Equivalent Hardnessmentioning

confidence: 99%