Modeling of Tensile Test Results for Low Alloy Steels by Linear Regression and Genetic Programming Taking into Account the Non-Metallic Inclusions
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{Kovacic:2022:Metals,
-
author = "Miha Kovacic and Uros Zuperl",
-
title = "Modeling of Tensile Test Results for Low Alloy Steels
by Linear Regression and Genetic Programming Taking
into Account the Non-Metallic Inclusions",
-
journal = "Metals",
-
year = "2022",
-
volume = "12",
-
number = "8",
-
article-number = "1343",
-
keywords = "genetic algorithms, genetic programming, mechanical
properties, tensile test, tensile strength, yield
strength, percentage elongation, percentage reduction
area, low alloy steel, modeling, linear regression,
industrial study, steel making, optimization",
-
ISSN = "2075-4701",
-
URL = "https://www.mdpi.com/2075-4701/12/8/1343",
-
URL = "https://www.mdpi.com/metals-12-01343.pdf",
-
DOI = "doi:10.3390/met12081343",
-
size = "17 pages",
-
abstract = "Store Steel Ltd. is one of the biggest flat spring
steel producers in Europe. The main motive for this
study was to study the influences of non-metallic
inclusions on mechanical properties obtained by tensile
testing. From January 2016 to December 2021, all
available tensile strength data (472 cases 472 test
pieces) of 17 low alloy steel grades, which were
ordered and used by the final user in rolled condition,
were gathered. Based on the geometry of rolled bars,
selected chemical composition, and average size of
worst fields non-metallic inclusions (sulfur, silicate,
aluminium and globular oxides), determined based on
ASTM E45, several models for tensile strength, yield
strength, percentage elongation, and percentage
reduction area were obtained using linear regression
and genetic programming. Based on modeling results in
the period from January 2022 to April 2022, five
successively cast batches of 30MnVS6 were produced with
a statistically significant reduction of content of
silicon (t-test, p < 0.05). The content of silicate
type of inclusions, yield, and tensile strength also
changed statistically significantly (t-test, p < 0.05).
The average yield and tensile strength increased from
458.5 MPa to 525.4 MPa and from 672.7 MPa to 754.0 MPa,
respectively. It is necessary to emphasize that there
were no statistically significant changes in other
monitored parameters.",
-
notes = "Messphysik Beta 300 tensile test machine
STORE STEEL, d.o.o., Research and Development, 3220
Store, Slovenia",
- }
Genetic Programming entries for
Miha Kovacic
Uros Zuperl
Citations