Materials Algorithms Project
Program Library

Subroutine MAP_STEEL_FLANGEABILITY

Provenance of code.
Purpose of code.
Specification.
Description of subroutine's operation.
References.
Parameter descriptions.
Error indicators.
Accuracy estimate.
Any additional information.
Example of code
Auxiliary subroutines required.
Keywords.
Download source code.
Links.

Provenance of Source Code

S Chatterjee, December 2006, sc446@cam.ac.uk
Phase Transformations and Complex Properties Research Group,
Materials Science and Metallurgy,
University of Cambridge,
U.K.

The neural network program was produced by:

David MacKay,
Cavendish Laboratory,
University of Cambridge,
Madingley Road,
Cambridge, CB3 0HE, U.K.

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Purpose

There are a number of programs included.

To predict the hole expansion ratio of steel as a function of yield strength (YS), ultimate tensile strength (UTS), yield ratio (YR), uniform elongation (UEL) and product of UTS and UEL (UTS-UEL).
To predict the hole expansion ratio as a function of UTS and UEL.
To predict the hole expansion ratio of steel as a function of YS and UEL.
To predict the hole expansion ratio of steel as a function of YS, UTS, YR, total elongation (TEL) and product of UTS and TEL (UTS-TEL).
To predict the hole expansion ratio of steel as a function of UTS and TEL.
To predict the hole expansion ratio of steel as a function of UTS and UTS-TEL.
To predict the hole expansion ratio of steel as a function of UTS-TEL.

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Specification

Language:	executables, C
Product form:	executables

Stretch-flangeability measures the ability of a material to be formed into a complex shape. A hole is initally punched on a steel blank. The hole is then allowed to expand under load until cracks develop at the surface. The ratio of the increase in diameter to the original diameter of the hole, referred to as hole expansion ratio, is used to determine the flangeability. An attempt is made here to represent the flangeability in terms of tensile test data.

Data used to create the model were collected from references [1-5]. The actual research is described in [6].

The training of the model makes use of a neural network program called generate44, which was developed by David MacKay and is part of the bigback5 program. The model is trained using an interface developed by Sourmail. The source code for the neural network program can be downloaded from David MacKay's website; the executable files only are available from MAP. The downloadable package contains the following files and subdirectories (details may differ between LINUX and PC versions):

MINMAX: A text file containing the minimum and maximum limits of each input and output variable. This file is used to normalise and unnormalise the input and output data.
test.dat: An input text file containing the input variables used for predictions.
model.gen or model.exe: This is a unix shell file containing the command steps required to run the module. It can be executed by typing csh model.gen at the command prompt. This shell file compiles and runs all the programs necessary for normalising the input data, executing the network for each model, unnormalising the output data and combining the results of each model to produce the final committee result.
spec.t1: A dynamic file, created by spec.ex, which contains information about the module and the number of data items being supplied. It is read by the program generate44.
norm_test.in: This is a text file which contains the normalised input variables. It is generated by the program normtest.for in subdirectory s.
generate44: This is the executable file for the neural network program. It reads the normalised input data file, norm_test.in, and uses the weight files in subdirectory c. The results are written to the temporary output file _out.
_ot, _out, _res, _sen: These files are created by generate44 and can be deleted.
Result: Contains the final un-normalised committee results for the predicted hardness.
SUBDIRECTORY s
spec.c: The source code for program spec.ex.
normtest.for: Program to normalise the data in test.dat and produce the normalised input file norm_test.in. It makes use of information read in from no_of_rows.dat and committee.dat.
gencom.for: This program uses the information in committee.dat and combines the predictions from the individual models, in subdirectory outprdt, to obtain an averaged value (committee prediction). The output (in normalised form) is written to com.dat.
treatout.for: Program to un-normalise the committee results in com.dat and write the output predictions to unnorm_com. This file is then renamed Result.
committee.dat: A text file containing the number of models to be used to form the committee result and the number of input variables. It is read by gencom.for, normtest.for and treatout.for.
SUBDIRECTORY c
_w_*f: The weights files for the different models.
_*.lu: Files containing information for calculating the size of the error bars for the different models.
_c_*: Files containing information about the perceived significance value [1] for each model.
_R_*: Files containing values for the noise, test error and log predictive error [1] for each model.
SUBDIRECTORY d
outran.x: A normalised output file which was created when developing the model. It is accessed by generate44 via spec.t1.
SUBDIRECTORY outprdt
out1, out2 etc.: The normalised output files for each model.
com.dat: The normalised output file containing the committee results. It is generated by gencom.for.

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References

Sudo, M., Tsukatani, I. and Shibata, Z., Effect of microstructure on the plastic anisotropy and mechanical properties of triphase sheet steel, Metallurgy of Continuous Annealed Sheet Steel, AIME (1982), 310-319
Sugimoto, K-I., Nagasaka, A., Kobayashi, M. and Hashimoto, S. I., Effects of retained austenite parameters on warm stretch-flangeability in TRIP-aided dual phase sheet steels, ISIJ International 39 (1999) 56-63
Hasegawa, K., Kawamura, K., Urabe, T. and Hosoya, Y., Effects of microstructure on stretch-flange-formability of 980 MPa grade cold-rolled ultra high strength steel sheets, ISIJ International 44 (2004) 603-609
Fang, X., Fan, Z., Ralph, B., Evans, P. and Underhill, R., Effects of tempering temperature on tensile and hole expansion properties of a C-Mn steel, Journal of Materials Processing Technology 132 (2003) 215-218
Fang, X., Fan, Z., Ralph, B., Evans, P. and Underhill, R., The relationships between tensile properties and hole expansion property of C-Mn steels, Journal of Materials Science 38 (2003) 3877-3882
S. Chatterjee and H. K. D. H. Bhadeshia, Materials Science and Technology, 23 (2007) 819-827.

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Parameters

Program number 1, inputs

Inputs in sequence YS (MPa), UTS (MPa), UEL (%), YR, UTS-UEL (MPa-%). The following example has three sets of inputs.

    
472    736    27    0.64    19872 
418    720    27    0.58    19440 
518    834    32    0.62    26688