Strength analysis of lamellar graphite cast iron in the «carbon (C) – carbon equivalent (Ceq)» factor space in the range of C = (3,425-3,563) % and Ceq = (4,214-4,372) %
DOI:
https://doi.org/10.15587/2312-8372.2017.93178Keywords:
lamellar graphite cast iron, induction crucible furnace, regression equation, canonical transformation of the response surfaceAbstract
The object of research is the structural lamellar graphite cast iron, where the carbon equivalent (Ceq) is in the range of (4,214-4,372) % and the carbon content (C) is in the range of (3,425-3,563) %.
The aim of research is to describe the distribution of values of tensile strength of cast iron series in the factor space C–Ceq at a fixed level of Cr-Ni-Cu-Ti alloyed complex in narrow ranges.
To achieve this aim, there are the next objectives.
1. Build a workable analytical description of the impact of the selected input variables on the tensile strength of cast iron.
2. Study the response surface and identify the most informative point of the factor space for further detailed investigation of the microstructure in these points.
It is shown that polynomial regression equation provides forecast accuracy, exceeding the accuracy using a linear regression equation in 1,23 times. An existence of a saddle point is revealed on the basis of the canonical transformation of response surface. It is an informative indicator, which suggests that the respective values of the input variables C = 3,492 %, Ceq = 4,28 % when the content of alloying elements , form a microstructure that guarantees the value of cast iron tensile strength TS = 203 MPa. In view of the resulting confidence interval, this value with a probability of 95 % is in the range of TS = (193-213) MPa. Metallographic microstructure description in the saddle point is important and can be obtained by the development of modeling results.
It is noted that there is a fundamental opportunity to improve accuracy and obtaining more precise description of the response surface – due to numerical building of D-optimal plan or artificial orthogonalization of full factorial experiment, inside the considered in this work
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