Due to the high computing demand of whole-trip train dynamics simulations and the iterative nature of optimizations, whole-trip train dynamics optimizations using sequential computing schemes are practically impossible. This paper reports advancements in whole-trip train dynamics optimizations enabled by using the parallel computing technique. A parallel computing scheme for whole-trip train dynamics optimizations is presented and discussed. Two case studies using parallel multiobjective particle swarm optimization (pMOPSO) and parallel multiobjective genetic algorithm (pMOGA), respectively, were performed to optimize a friction draft gear design. Linear speed-up was achieved by using parallel computing to cut down the computing time from 18 months to just 11 days. Optimized results using pMOPSO and pMOGA were in agreement with each other; Pareto fronts were identified to provide technical evidence for railway manufacturers and operators.

References

References
1.
Sun
,
Y.
, and
Cole
,
C.
,
2008
, “
Vertical Dynamic Behavior of Three-Piece Bogie Suspensions With Two Types of Friction Wedge
,”
Multibody Syst. Dyn.
,
19
(
4
), pp.
365
382
.
2.
Spiryagin
,
M.
,
Polach
,
O.
, and
Cole
,
C.
,
2013
, “
Creep Force Modeling for Rail Traction Vehicles Based on the Fastsim Algorithm
,”
Veh. Syst. Dyn.
,
51
(
11
), pp.
1765
1783
.
3.
Evans
,
E.
, and
Berg
,
M.
,
2009
, “
Challenges in Simulation of Rail Vehicle Dynamics
,”
Veh. Syst. Dyn.
,
47
(
8
), pp.
1023
1048
.
4.
Negrut
,
D.
,
Serban
,
R.
,
Mazhar
,
H.
, and
Heyn
,
T.
,
2014
, “
Parallel Computing in Multibody System Dynamics: Why, When and How
,”
ASME J. Comput. Nonlinear Dyn.
,
9
(
4
), p.
041007
.
5.
Wu
,
Q.
, and
Cole
,
C.
,
2015
, “
Computing Schemes for Longitudinal Train Dynamics: Sequential, Parallel and Hybrid
,”
ASME J. Comput. Nonlinear Dyn.
,
10
(
6
), p.
064502
.
6.
Nedjah
,
N.
,
Alba
,
E.
, and
Mourelle
,
L.
,
2006
,
Parallel Evolutionary Computations
,
Springer
,
Berlin
.
7.
Hidalgo
,
A.
, and
de Jalon
,
J.
,
2015
, “
Real-Time Dynamic Simulations of Large Road Vehicles Using Dense, Sparse, and Parallelization Techniques
,”
ASME J. Comput. Nonlinear Dyn.
,
10
(
3
), p.
031005
.
8.
Kim
,
I.
, and
de Weck
,
O.
,
2006
, “
Adaptive Weighted Sum Method for Multiobjective Optimization
,”
Struct. Multidiscip. Optim.
,
31
(
2
), pp.
105
116
.
9.
Wu
,
Q.
,
Cole
,
C.
, and
Spiryagin
,
M.
,
2014
, “
Methodology for Optimization of Friction Draft Gear Design
,”
ASME
Paper No. DETC2014-34162.
10.
Cole
,
C.
, and
McLeod
,
T.
,
2004
, “
Optimising Train Operation Using Simulation, Fuzzy Logic Cruise Control and Evolutionary Algorithms
,”
Fifth Asia Pacific Industrial Engineering and Management Systems Conference
, Gold Coast, Australia, Paper No. 30.6.
11.
Wu
,
Q.
,
Cole
,
C.
,
Luo
,
S.
, and
Spiryagin
,
M.
,
2014
, “
A Review of Dynamics Modeling of Friction Draft Gear
,”
Veh. Syst. Dyn.
,
52
(
6
), pp.
733
758
.
12.
Wu
,
Q.
,
Spiryagin
,
M.
, and
Cole
,
C.
,
2015
, “
Advanced Dynamic Modeling for Friction Draft Gears
,”
Veh. Syst. Dyn.
,
53
(
4
), pp.
475
492
.
13.
Shabana
,
A.
,
Aboubakr
,
A.
, and
Ding
,
L.
,
2012
, “
Use of the Non-Inertial Coordinates in the Analysis of Train Longitudinal Forces
,”
ASME J. Comput. Nonlinear Dyn.
,
7
(
1
), p.
011001
.
14.
Balaji
,
P.
,
Bland
,
W.
,
Gropp
,
W.
,
Latham
,
R.
,
Lu
,
H.
,
Pena
,
A.
,
Raffenetti
,
K.
,
Thakur
,
R.
, and
Zhang
,
J.
,
2014
, “
MPICH User's Guide, Version 3.1.1
,” Mathematics and Computer Science Division Argonne National Laboratory, Argonne, IL, http://www.mpich.org/static/downloads/3.1.1/mpich-3.1.1-userguide.pdf
15.
Central Queensland University
,
2015
, “
High Performance Computing
,”
https://www.cqu.edu.au/hpc
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