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

Provenance of Source Code

Carlos Capdevila, Francisca G. Caballero and Carlos Garcia de Andres,
Phase TRansformation group (GITFES),
Department of Physical Metallurgy,
National Center for Metallurgical Research (CENIM),
Madrid, Spain.

The neural network program was produced by:

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

Added to MAP: August 2000

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Estimation of the Ms temeprature in steels as a function of chemical composition and previous austenite grain size (PAGS).

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Language: FORTRAN / C
Product form: Source code / Executable files
Operating Selntem: Windows 95/98/2000 

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MAP_STEEL_MS-TEMPERATURE  contains a suite of programs which enable the user to estimate the Ms temperature as a function of chemical composition and previous austenite grain size. It makes use of a neural network program called generate44, which was developed by David MacKay and is part of the bigback5 program. The network was trained using a large database of experimental results [1].  16 different models are provided, which differ from each other by the number of hidden units and by the value of the seed used when training the network. It was found that a more accurate result could be obtained by averaging the results from all the models [1]. This suite of programs calculates the results of each model and then combines them, by averaging, to produce a committee result and error estimate, as described by MacKay [page 387 of reference 2]. The source code for the neural network program can be downloaded from David MacKay's website; the executable files only are available from MAP. Also provided are FORTRAN programs (as source code) for normalising the input data, averaging the results from the neural network program and unnormalising the final output file, along with other files necessary for running the program.

Programs are available which run on a PC under Windows 95/98/2000. A set of program and data files are provided for the model, which calculate the Ms temperature in steels. The files for PC are included in a directory called MS_files. This directory contains the following files and subdirectories:

A text file containing step-by-step instructions for running the program, including a list of input variables.
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.
An input text file containing the input variables used for predictions.
This executable program for the PC.
This is a text file which contains the normalised input variables. It is generated by the program MS.exe.
This is the executable file for the neural network program.
It reads the normalised input data file and uses the weight files in subdirectory c. The results are written to the temporary output file _out.
Contains the final un-normalised committee results for the predicted percentage retained austenite.
A text file containing the number of models to be used to form the committee result and the number of input variables.
A text file containing information about number of input variables and weight file for committee models.
The weights files for the different models.
Files containing information for calculating the size of the error bars for the different models.
Files containing information about the perceived significance value [1] for each model.
Files containing values for the noise, test error and log predictive error [1] for each model.
A normalised output file which was created during the building of the model. It is accessed by generate44.
out1, out2 etc.
The normalised output files for each model.
The normalised output file containing the committee results. It is generated by gencom.for.

Detailed instructions on the use of the program are given in the README files. Further information about this suite of programs can be obtained from reference 1.

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  1. C. Capdevila, F.G. Caballero and C. Garcia de Andres, Prediction of Ms Temperature in Steels Submitted to Materials Science and Technology, 2002.
  2. D.J.C. MacKay, 1997, Mathematical Modelling of Weld Phenomena 3, eds. H. Cerjak & H.K.D.H. Bhadeshia, Inst. of Materials, London, pp 359.
  3. D.J.C MacKay's website at http://wol.ra.phy.cam.ac.uk/mackay/README.html#Source_code
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Input parameters

The input variables for the model are listed in the README.DOC  file in the corresponding directory. The maximum and minimum values for each variable are given in the file MINMAX.

Output parameters

These program gives the Ms temperature in 'K'. The corresponding output files is called Result.dat or Result. The format of the output file is:
Prediction     Error-Bar      Upper-limit      Lower-limit    
    (K)           (K)             (K)             (K)
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Error Indicators


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A full calculation of the error bars is presented in reference 1.

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Further Comments


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1. Program text

       Complete program.

2. Program data

See sample data file: test.dat.

3. Program results

See sample output file: Result or Result.dat.

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Auxiliary Routines


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neural network, Ms temperature, Steels

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Download Ms temperature Model

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MAP originated from a joint project of the National Physical Laboratory and the University of Cambridge.


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