Materials Algorithms Project
Program Library
MAP_NICKEL_UTS
- Provenance of code.
- Purpose of code.
- Specification.
- Description of program's operation.
- References.
- Parameter descriptions.
- Error indicators.
- Accuracy estimate.
- Any additional information.
- Example of code
- Auxiliary routines required.
- Keywords.
- Download source code.
- Links.
F. Tancret and H.K.D.H. Bhadeshia,
Phase Transformations and Complex Properties Group,
Department of Materials Science and Metallurgy,
University of Cambridge,
Cambridge CB2 3QZ, U.K.
Added to MAP: August 2000.
Top |
Next
A program for the estimation of the ultimate tensile stress (UTS) of nickel-base superalloys. This prediction is made as a function of elemental composition, heat and mechanical treatments, and test temperature.
Top |
Next |
Prev
Language: | FORTRAN / C
|
Product form: | Source code / Executable files
|
Operating System: |
Solaris 5.5.1 & Windows 95/98 |
Top |
Next |
Prev
The modelling procedure is a purely empirical one, and is based on a neural network program called generate44, which was developed by David MacKay and is part of the bigback5 program. The model is constituted of a committee of several individual neural networks. It was trained on a set of experimental data for which the "outputs" are known, and creates a kind of non-linear, multi-parameter "regression" of the outputs versus the inputs. This "regression" has already been produced and the model is delivered ready to perform predictions for nickel-base alloys of any desired composition (within certain specified limits). 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 distinct set of program and data
files are provided . The files for unix are separated into compressed
files called niUTS.tar ; those for a PC : niUTS.zip. Each
directory or zip file contains the following files and subdirectories:
-
README
-
A manual containing step-by-step instructions for running the program,
including a list of input variables.
-
-
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
-
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.
-
-
model.exe
-
These executable programs for the PC correspond to the unix command files
model.gen. The source code is given in subdirectory s.
-
-
spec.ex
-
This executable file reads the information in no_of_rows.dat
and creates a file called spec.t1 (UNIX only).
-
-
spec.t1
-
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/generate44.exe.
-
-
norm_test.in
-
This a text file which contains the normalised input variables. It is generated
by the program normtest.for in subdirectory s.
-
-
generate44 / generate44.exe
-
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, to find a value for
the output. The results are written to the temporary output file _out.
-
-
Result, or model_result.dat
-
Contains the final un-normalised committee results for the predicted output.
-
-
-
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 as Result or model_result.dat.
-
-
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 for each model.
-
-
_R*
-
Files containing values for the noise, test error and log predictive error
for each model.
-
-
-
SUBDIRECTORY d
-
-
outran.x
-
A normalised output file which was created during the building of the model.
It is accessed by generate44 via spec.t1.
-
-
-
SUBDIRECTORY outprdt
-
-
-
com.dat
-
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 file.
Top |
Next |
Prev
- F. Tancret et al., a series of three papers on Design of Nickel Superalloys, 2003
- F. Tancret, Processing for China, Sterling Publications, London, 2000, pp. 56-58. [Download postscript, PDF, Word, html files.]
- F. Tancret, H. K. D. H. Bhadeshia, Key Engineering Materials, Vols. 171-174, 2000, pp. 529-536. [Download postscript, PDF, Word, html files.]
- F. Tancret, H. K. D. H. Bhadeshia, ISIJ International, 39 (1999) 1020-1026.
Top |
Next |
Prev
Input parameters
- Cr (wt.%)
- Co (wt.%)
- Mo (wt.%)
- W (wt.%)
- Ta (wt.%)
- Nb (wt.%)
- Al (wt.%)
- Ti (wt.%)
- Fe (wt.%)
- Mn (wt.%)
- Si (wt.%)
- C (wt.%)
- B (wt.%)
- Zr (wt.%)
- Cu (wt.%)
- N (wt.%)
- S (wt.%)
- P (wt.%)
- V (wt.%)
- Hot working (binary)
- 1st high temperature heat treatment: duration (h) and temperature (oC)
- 2nd high temperature heat treatment: duration (h) and temperature (oC)
- 1st low temperature heat treatment: duration (h) and temperature (oC)
- 2nd low temperature heat treatment: duration (h) and temperature (oC)
- Test temperature (oC)
Output parameters
- predicted UTS (MPa)
- error bar on UTS
- UTS - error bar
- UTS + error bar
A more detailed description is presented in the README file.
Top |
Next |
Prev
None.
Top |
Next |
Prev
An estimated predictive error bar is provided by the model.
Top |
Next |
Prev
None.
Top |
Next |
Prev
1. Download the model
Uncompress the "niUTS.tar" or "niUTS.zip" file in a dedicated directory (for example: "neural").
On UNIX systems, this is done by:
tar -xvf niUTS.tar
On PC systems, this is done by extracting the archive using standard unzipping software.
2. Program data
Create an input file "test.dat" in the "neural" directory, containing the information on your alloy and test conditions (see README file for details).
Example: to predict the UTS at 20, 200, 400, 600, and 800oC, of the following wrought alloy: Ni-20Cr-10Co-2Al-2Ti-0.03C wt.%, heat-treated 1 h at 1175oC and 8 h at 800oC:
20 10 0 0 0 0 2 2 0 0 0 0.03 0 0 0 0 0 0 0 1 1 1175 0 0 8 800 0 0 20
20 10 0 0 0 0 2 2 0 0 0 0.03 0 0 0 0 0 0 0 1 1 1175 0 0 8 800 0 0 200
20 10 0 0 0 0 2 2 0 0 0 0.03 0 0 0 0 0 0 0 1 1 1175 0 0 8 800 0 0 400
20 10 0 0 0 0 2 2 0 0 0 0.03 0 0 0 0 0 0 0 1 1 1175 0 0 8 800 0 0 600
20 10 0 0 0 0 2 2 0 0 0 0.03 0 0 0 0 0 0 0 1 1 1175 0 0 8 800 0 0 800
3. Running the program (making predictions)
For Solaris 5.5.1, just type:
csh model.gen
For PC software, just double-click on:
model.exe
4. Results of the program (predictions)
The results are written in the "Result" or "model_result.dat" file, as described in the README file. In the present case:
Predicted Error Predicted-Error Predicted+Error
1034.4292055 139.5674280 894.8617775 1173.9967820
969.4975805 113.5693845 855.9281960 1083.0671135
915.5980205 107.4632130 808.1348075 1023.0612335
874.5150500 130.7988000 743.7162500 1005.3138500
593.1599705 135.9483345 457.2117845 729.1083050
Top |
Next |
Prev
Top |
Next |
Prev
neural networks, ultimate tensile stress, UTS, Ni-base, superalloy
Top |
Next |
Prev
Download source code (Solaris 5.5.1)
Download source code (PC software)
Top |
Prev