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Physical Properties of Steel
Published in Vladimir B. Ginzburg, Metallurgical Design of Flat Rolled Steels, 2020
One of the most common tests that is used for determining hardenability is the end-quench test, also known as the Jominy test [7]. During this test, a cylindrical specimen with a 1 in. diameter is cooled at one end by a column of water; thus the entire specimen experiences a range of cooling rates between those associated with water and air cooling. After quenching, opposite ends of the specimen are grounded to be parallel to each other and hardness readings are taken every 1/16 in. from the quenched end as shown in Fig. 3.12.
Non-Equilibrium Diagrams and Microconstituents
Published in Joseph Datsko, Materials Selection for Design and Manufacturing, 2020
Hardenability is a measure of how slow a cooling rate can be used for a given steel to achieve all martensite. It is frequently referred to as the ease with which martensite can be formed. Hardenability should not be confused with hardness, which is discussed in Chapter 6. At this point it is sufficient to realize that hardness is a measure of a material’s compressive strength (after a certain amount of deformation imparted by the indenter), whereas hardenability is a measure of a steel’s ability to achieve a high hardness due to the presence of martensite in the center of a large bar or thick section. Consider two steels, A having 02% C and Β having 0.6% C, where 2” diameter bars are austenitized and water quenched. Bar A has a surface hardness of 45 R and a center hardness of 44 Rc, while bar Β has a surface hardness of 65 Rc and a center hardness of 50 Rc. In this case steel A has a higher hardenability than steel B, even though its actual hardness is lower. The hardness of a 0.2 C steel containing all martensite is 45 Rc and that of a 0.6% C steel is 65 Rc. Thus steel A transforms to martensite at the center but steel Β does not. In summary, the hardness of steel is determined by the carbon content, whereas the hardenability is determined by the amount of alloys present.
Common Heat Treatment Practices
Published in Bankim Chandra Ray, Rajesh Kumar Prusty, Deepak Nayak, Phase Transformations and Heat Treatments of Steels, 2020
Bankim Chandra Ray, Rajesh Kumar Prusty, Deepak Nayak
Hardenability is a measure of the amount of martensite present in the structure. Hence, steel is said to have high hardenability if it is completely transformed to martensite. The factors that promote the formation of martensite are those who shift the nose of the TTT curve to the right. Alloying elements, carbon content, and austenitic grain size affect hardenability. All alloying elements, except cobalt, have a tendency to shift the nose of the TTT curve to the right. This ensures a more hardenable steel as the probability that the cooling curve will not touch the nose of CCT curve is higher. However, undissolved inclusions, such as carbides or nitrides, nonmetallic inclusions, and inhomogeneity of austenite, which may happen due to the presence of alloying elements, decrease the hardenability of the steel. Carbon content dramatically influences the hardenability. The size of austenite also plays a vital role in determining the hardenability. The finer the austenite grain size, the lower the hardenability. It may be attributed to the fact that with a decrease in grain size, more sites become available for pearlite nucleation. Once pearlite formation occurs, martensite transformation is suppressed, and hence, hardenability decreases. Although coarse-grained steel increases the hardenability, it is not always recommended to use the same to increase hardenability because it may lead to specific other undesirable properties such as poor impact properties, decrease in ductility, and quench crack susceptibility.
Predicting hardness profile of steel specimens subjected to Jominy test using an artificial neural network and electromagnetic nondestructive techniques
Published in Nondestructive Testing and Evaluation, 2021
Iman Ahadi Akhlaghi, Saeed Kahrobaee, Amir Akbarzadeh, Mehrdad Kashefi, Thomas W. Krause
In materials science, hardenability is one of the most important features of steel parts and is defined as a measure of the capacity of steel to be hardened in depth when quenched from its austenitizing temperature. This characteristic indicates the potential of a specific steel to avoid diffusional transformation of austenite to equilibrium phases (ferrite/pearlite) [1], which greatly influences its mechanical properties. The well-known Jominy end-quench test is considered the most common experimental method to assess hardenability of carbon and alloy steels [2]. In recent years, a variety of Jominy end-quench testing machines have designed and fabricated to determine the Hardenability of steels [3–5]. In all the machines, the experimental results are presented as a curve of hardness values versus distance from the quenched end of the Jominy specimen. The method is indeed time-consuming and expensive since a ground flat surface should be first prepared in a longitudinal direction and then hardness tests should be performed at 1.6 mm intervals. Therefore, it is highly desirable to introduce a method in order to speed up the test process. To this end, several predictive models have been explored to predict the hardenability of various steel grades using their hardness profiles. Yazdi et al. [6] have simulated the Jominy test of AISI 4130 steel based on the quench factor analysis (QFA) method. They have determined hardness at different points of the samples by correlating cooling curves and their corresponding microstructural responses. Vermeulen et al. [7] have shown the application of an artificial neural network to predict hardness profiles of steels with various chemical composition and austenitizing temperatures subjected to the Jominy test. Song et al. [8] have presented an improved model using nonlinear equations for predicting the hardness curves of multi-alloying carbon steel after Jominy test. One main disadvantage of using these methods is that the techniques need precise information concerning the chemical composition of steel, austenitizing temperature/time and cooling rates. Moreover, the verification of these models requires hardness measurements for each grade of steel. Therefore, it is of great interest that an alternative non-destructive, adaptive and rapid method could be used for this purpose. This can make it possible to determine the hardness profile of any steel grade subjected to Jominy test without having to know any information about the chemical composition, austenitizing temperature/time and cooling rates.