Materials Algorithms Project
Program Library
Program MAP_NEURAL_WELDMETAL_T_27J
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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
Sree Harsha Lalam and Prof. H.K.D.H. Bhadeshia,
Phase Transformations Group,
Department of Materials Science and Metallurgy,
University of Cambridge,
Cambridge, CB2 3HU, 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: December 1999
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Purpose
To estimate the 27 J Charpy impact transistion temperature for ferritic steel welds as a function of the yield
strength, oxygen content, reheated material and percentage acicular
ferrite.
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Specification
Language: |
FORTRAN / C |
Product form: |
Source code / Executable files |
Operating System: |
Solaris 5.5.1, Linux & Windows 95/98 |
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Description
MAP_NEURAL_WELDMETAL_T_27J contains a suite of programs which enable the
user to estimate the 27 J Charpy toughness transistion temperature
( T27J ) of steel weldmetal , as a function of yield strength
, oxygen content, reheated material and percentage acicular ferrite
content in the weld metal.. 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 database of experimental results [1] . Thirteen
different committee models , 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 3]. 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 and Linux operating
system and on a PC under Windows 95/98. A distinct set of program and data
files are provided . The files for unix and Linux are separated into compressed
files called weldmetal_T_27J_solaris.tar and weldmetal_T_27J_linux.tar
; those for a PC : weldmetal_T_27J.zip. Each
directory or zip file 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. These shell files
compile and run 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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These executable programs for the PC correspond to the unix command files
model.gen. The source code is given in model.c
which are in subdirectory s.
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data_no.ex/data_no.exe
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This executable file reads the information of number of data from keyboard
input and creates no_of_rows.dat file, this file is used
by spec.ex/spec.exe to create spec.t1.
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spec.ex/spec.exe
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This executable file reads the information in no_of_rows.dat
and creates a file called spec.t1.
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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 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 selntems and generate55 on the PC. It reads
the normalised input data file, norm_test.in, and uses
the weight files in subdirectory c, to find a value for
temperature. 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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Fresult
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Contains the final un-normalised committee results for the predicted.
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SUBDIRECTORY s
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data_no.c
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The source code for program data_no.ex.
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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 as Fresult .
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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 [2]
for each model.
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_R*
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Files containing values for the noise, test error and log predictive error
[2] 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 during the building of 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 2.
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References
- French, I. E., 1999, Australaisan Welding Journal, 44, second quarter, 44-46.
- S. H. Lalam, H. K. D. H. Bhadeshia and D. J. C.
MacKay, Australasian Welding Journal, Vol. 45, 2000, pp. 33-37. [Download PDF file.]
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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.
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D.J.C MacKay's website at https://wol.inference.phy.cam.ac.uk/mackay/README.html#Source_code
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Parameters
Input parameters
The input variables for each module are listed in the README
file in the corresponding directory. The maximum and minimum values for
each variable are given in the file MINMAX.
Output parameters
These programs give the output in oC. The corresponding output
files are called Fresult . The format of the output file
is:
Prediction Error Prediction - Error Prediction + Error
(oC) (oC) (oC) (oC)
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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: Fresult
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Auxiliary Routines
None
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Keywords
neural network, weldmetal toughness, Charpy toughness
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Download
Download MAP information
files
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Solaris.5.5.1:
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Download Solaris module
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Linux:
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Download Linux module
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PC Software:
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Download PC Module
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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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