Materials Algorithms Project
Program Library
Program MAP_NEURAL_ADI_ELONGATION
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Provenance of code.
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Purpose of code.
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Specification.
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Description of subroutine's operation.
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References.
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Parameter descriptions.
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Error indicators.
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Accuracy estimate.
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Any additional information.
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Example of code
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Auxiliary subroutines required.
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Keywords.
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Download source code.
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Links.
Provenance of Source Code
Miguel Angel Yescas-Gonzalez and H.K.D.H. Bhadeshia,
Phase Transformations Group,
Department of Materials Science and Metallurgy,
University of Cambridge,
Cambridge, U.K.
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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Purpose
Estimation of the tensile yield strength in ADI as a function of
chemical composition
and heat treatment conditions (Austenitising temperature, austenitising
time, austempering
temperature and austempering time).
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Specification
Language: |
FORTRAN / C |
Product form: |
Source code / Executable files |
Operating Selntem: |
Solaris 5.5.1 & Windows 95/98 |
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Description
MAP_NEURAL_ADI_ELONGATION contains a suite of programs which
enable the user to estimate the tensile elongation in % for any austempered
ductile iron (ADI) as a function of chemical composition
and heat treatment conditions. 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].
12 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 [2]. 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 Solaris 5.5.1 unix operating system,
and on a PC under Windows 95/98. A set of program and data files
are provided for the model, which calculate the tensile elongation in % for ADI. The files for UNIX are included in a directory called
ADI. This directory contains the following files and subdirectories:
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README
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A text file containing step-by-step instructions for running the program,
including a list of input variables.
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MINMAX
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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.
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test.dat
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An input text file containing the input variables used for predictions.
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model.gen
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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.
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MODEL.exe
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This executable program for the PC correspond to the unix command file
model.gen.
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spec.t1
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A dynamic file, created by spec.ex/spec.exe, which contains
information about the module and the number of data items being supplied.
It is read by the program generate44/generate55.exe.
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norm_test.in
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This is a text file which contains the normalised input variables. It is
generated by the program normtest.for in subdirectory s.
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generate44 / generate55
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This is the executable file for the neural network program. generate44
runs on unix operating system and generate55 on the PC. 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.
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_ot, _out, _res, _sen
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These files are created by generate44 and can be deleted.
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Result
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Contains the final un-normalised committee results for the predicted hardness.
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SUBDIRECTORY s
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spec.c
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The source code for program spec.ex.
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normtest.for
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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.
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gencom.for
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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.
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treatout.for
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Program to un-normalise the committee results in com.dat
and write the output predictions to unnorm_com. This file
is then renamed Result.
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committee.dat
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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.
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SUBDIRECTORY c
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_w*f
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The weights files for the different models.
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*.lu
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Files containing information for calculating the size of the error bars
for the different models.
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_c*
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Files containing information about the perceived significance value [1]
for each model.
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_R*
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Files containing values for the noise, test error and log predictive error
[1]
for each model.
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SUBDIRECTORY d
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outran.x
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A normalised output file which was created when developing the model.
It is accessed by generate44 via spec.t1.
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SUBDIRECTORY outprdt
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out1, out2 etc.
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The normalised output files for each model.
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com.dat
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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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References
Miguel Angel Yescas-Gonzalez, Modelling the Microstructure and Mechanical Properties of Austempered Ductile Iron, Ph.D. Thesis, University of Cambridge, 2001.
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.
D.J.C MacKay's website at https://wol.ra.phy.cam.ac.uk/mackay/README.html#Source_code
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Parameters
Input parameters
The input variables for the model are listed in the README or 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 tensile elongation in '%' . The
corresponding output files is called
Model_RESULT.dat or Result.
The format of the output file is:
Prediction Error bar Lower-limit Upper-limit
(%) (%) (%)
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Error Indicators
None.
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Accuracy
A full calculation of the error bars is presented in reference 2.
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Further Comments
None.
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Example
1. Program text
Complete program.
2. Program data
See sample data file: test.dat.
3. Program results
See sample output file: Result or Model_RESULT.dat.
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Auxiliary Routines
None
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Keywords
neural network, tensile elongation, ADI, Austempered ductile cast
iron, bainite
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Download
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Solaris.5.5.1:
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Download ADI_ELONGATION
model (gzip tar file, 5.4 Mbytes)
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Linux:
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Download ADI_ELONGATION
model (gzip tar file, 5.4 Mbytes)
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PC Software:
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Download ADI_ELONGATION model (5.7Mbytes)
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MAP originated from a joint project of the National Physical
Laboratory and the University of Cambridge.
MAP Website administration / map@msm.cam.ac.uk
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