Results
The Optimization Cost vs. Iteration Plot
The plot below shows the decrease in the cost function as the optimizer changes the design to minimize the error. Note that the ordinate is plotted on a log scale to show the lower values. The optimizer required 17 iterations. The initial error in the RMS2 metric was64.707. At convergence the RMS2 error was 3.11e-03.
Camber vs. Ride Height
Optimization Summary Log File
OPTIMIZATION HISTORY FILE
Version 0.1
************************************************************************
** COPYRIGHT (C) 2004-2016 Altair Engineering, Inc. **
** All Rights Reserved. Copyright notice does not imply publication. **
** Contains trade secrets of Altair Engineering, Inc. **
** Decompilation or disassembly of this software strictly prohibited. **
************************************************************************
Date : 23/01/2017
Time : 12:57:16
Python Version : 2.7.6 | 64-bit | (default, Jun 4 2014, 16:42:26)
[GCC 4.2.1 (Apple Inc. build 5666) (dot 3)]
Input File : /Users/rajivr/Desktop/test/mv3010.py
Output Directory : /Users/rajivr/Desktop/test/test-mv3010_125716
Summary File : /Users/rajivr/Desktop/test/test-mv3010_125716/summary.log
Design Log File : /Users/rajivr/Desktop/test/test-mv3010_125716/design.log
Optimizer Settings
------------------
Algorithm : FMIN_SLSQP
Max. # iterations: 50
Accuracy : 1.000e-04
Simulation Settings
-------------------
Analysis : STATICS
End Time : 4.0
DTout : 0.04
DSA : AUTO
Iteration # Cost # Objective Mag(Slope)
--------------------------------------------------
1 1 6.4707e+01 2.0447e+01
2 3 2.2143e+01 1.4041e+00
3 4 1.9742e+01 1.5573e+00
4 5 8.5020e+00 1.7302e+00
5 6 9.7136e-01 4.0295e-01
6 7 8.3504e-01 2.3386e-01
7 8 4.4158e-01 5.9849e-01
8 9 3.9598e-01 2.3927e-01
9 10 3.9180e-01 1.7912e-02
10 11 3.9123e-01 1.2616e-02
11 12 3.8803e-01 1.1790e-02
12 13 3.7223e-01 1.2267e-02
13 14 3.0082e-01 1.1340e-02
14 15 8.8214e-02 3.0133e-02
15 16 1.1937e-02 3.9872e-02
16 17 3.8547e-03 8.3153e-03
17 18 3.1055e-03 3.0780e-03
Optimization terminated successfully.
Results from Optimization
-------------------------
Initial Cost = 64.707
Final Cost = 0.003
Cost reduction = 99.995
Individual Responses
--------------------
Weight = 1.00 Final cost of objective Area Error = 0.003
Final Design Table
------------------
DV Lower Bound Upper Bound Initial Value Optimized Value
------------------------------------------------------------------------------------------
OTB-left-y -6.5115e+02 -5.5115e+02 -5.6515e+02 -6.3601e+02
OTB-left-z +1.9092e+02 +2.5092e+02 +2.4892e+02 +1.9695e+02
ITB-left-y -2.9890e+02 -2.0990e+02 -2.1590e+02 -2.9391e+02
ITB-left-z +2.3086e+02 +2.7886e+02 +2.7686e+02 +2.3161e+02
Elapsed Time for job = 27.09 seconds
Time in Cost function = 12.35 seconds
Time in Sensitivity function = 14.14 seconds
Optimization process completed.
Design Summary Log File
Design History
Input File : /Users/rajivr/Desktop/test/mv3010.py
Output Directory: /Users/rajivr/Desktop/test/test-mv3010_125716
Iteration # Design
--------------------------------------------------------------------------------
1 [-565.15, 248.92, -215.90, 276.86]
2 [-564.34, 244.19, -216.66, 277.51]
3 [-563.34, 243.34, -217.68, 276.65]
4 [-557.69, 239.37, -223.43, 271.53]
5 [-551.15, 234.71, -230.78, 264.99]
6 [-551.15, 234.44, -231.28, 264.60]
7 [-551.15, 232.75, -234.09, 262.49]
8 [-551.15, 232.21, -234.84, 261.95]
9 [-551.15, 232.11, -234.95, 261.89]
10 [-551.21, 232.08, -235.00, 261.86]
11 [-551.52, 231.95, -235.22, 261.74]
12 [-553.09, 231.29, -236.33, 261.17]
13 [-560.71, 228.08, -241.71, 258.39]
14 [-594.17, 214.02, -265.27, 246.22]
15 [-624.31, 201.55, -286.19, 235.48]
16 [-633.27, 198.0, -292.14, 232.49]
17 [-636.01, 196.95, -293.91, 231.61]