Materials Algorithms Project Program Library

Program MAP__STEEL_WEAR_VOLUME_LOSS

1. Provenance of code.
2. Purpose of code.
3. Specification.
4. Description of program's operation.
5. References.
6. Parameter descriptions.
7. Error indicators.
8. Accuracy estimate.
9. Any additional information.
10. Example of code
11. Auxiliary routines required.
12. Keywords.
13. Download source code.
14. Links.

Provenance of Source Code

Suruj Protim Neog,
Steel Metallurgy Group,
Department of Metallurgical and Materials Engineering,
Indian Institute of Technology Roorkee,
Roorkee 24766, India.

E-mail: surujprotimneog@gmail.com.

Added to MAP: May 2021.

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Purpose

A program for the estimation of wear volume loss during dry sliding wear of steel against steel contact in a pin-on-disc wear testing machine as a function of a wide number of input variables like chemical composition (C, and rest of the elements as C_eq-C; C_eq: Carbon equivalent), volume fraction of different microstructural phases like bainite, martensite and retained austenite, pin hardness, the Hollomon Jaffe parameter, disc hardness, working temperature, speed, force and distance slid [1].

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Specification

Complete program.

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Description

MAP_STEEL_WEAR_VOLUME_LOSS contains the executable, using which the user can predict the wear volume loss during the dry sliding wear of steel-to-steel contact in a pin-on-disc tribometer. The model has been trained to predict the output, which is nothing but the wear volume loss in mm³, considering a wide number of input variables.

The term C_eq represents carbon equivalent and has been used here to consider the effect of elements like Mn, Si, Cr, Mo, V, Cu and Ni. The effect of carbon (C) was considered separately. One can calculate C_eq using the expression given below, where all elements are in wt.% [2].

Also, the Hollomon Jaffe parameter (hj) was considered to account for any thermal treatment the material might have been subjected to prior to wear testing and can be expressed by following Eq.

Where T = temperature in Kelvin; t = time in hour; C₁ = Material constant. If no information related to the `T' and `t' are provided, then T = 298 K and t = 10 h were considered in training the model. Also, the value of material constant C₁ was considered to be 20 for steel [3].

After opening the executable file, one has to give the inputs for each variable with units as specified below.

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References

1. S.P. Neog, A.R. Kumar, S. Das Bakshi, and S. Das, Materials Science and Technology. (2021)
2. S. Talas, Materials and Design. (2010): 31(5), pp.2649-2653.
3. L.C. Canale, X. Yao, J. Gu and G.E. Totten, International Journal of Microstructure and Materials Properties. (2008): 3(4-5), pp.474-525.

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Parameters

Input parameters

C

(wt.%).

Ceq-C

(wt.%).

bainite

(vol.%).

martensite

(vol.%).

austenite

(vol.%).

pin hardness

(HV).

hollomon Jaffe parameter

disc hardness

(HV).

working temperature

(^oC).

speed

(m/s).

force

(N).

distance slid

(m).

Output parameters

volume loss

(mm³).

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Error Indicators

None.

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Accuracy

No information supplied.

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Further Comments

None.

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Example

1. Program text

Complete program.

2. Program data

'C' 'Ceq-C' 'bainite' 'martensite' 'pin_h' 'hj' 'austenite' 'disc_h' 'w_temp' 'speed' 'force' 'dis_slid'
'0.34' '0.735' '75' '5' '462' '6.3' '20' '740' '26' '1' '30' '7200'
 

3. Program results

'C' 'Ceq-C' 'bainite' 'martensite' 'pin_h' 'hj' 'austenite' 'disc_h' 'w_temp' 'speed' 'force' 'dis_slid' 'vol_loss' 'error'
'0.34' '0.735' '75' '5' '462' '6.3' '20' '740' '26' '1' '30' '7200' '5.551829' '1.11566'

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Auxiliary Routines

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Keywords

Sliding wear, steel-on-steel, ANN modelling, effect of different parameters

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Download

Download source code for Unix

Download Microsoft Windows Executable

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