Novel Design Changes in DES Not Necessarily Better until Proven So

2012 ◽  
Vol 12 (8) ◽  
pp. 24-24
Author(s):  
R. Buckley ◽  
M. W. Krucoff
Keyword(s):  
ACTA IMEKO ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 204
Author(s):  
Christiaan Smith Veldman

This paper describes novel design changes to the accelerometer mounting support of a commercial pneumatic shock exciter, with the aim of reducing the transverse motion the accelerometer is subjected to during shock excitation. The author describes the mounting support supplied by the manufacturer, the design changes made and the measurement data to compare the transfer motions recorded using two different mounting designs.


2011 ◽  
Vol 39 (3) ◽  
pp. 193-209 ◽  
Author(s):  
H. Surendranath ◽  
M. Dunbar

Abstract Over the last few decades, finite element analysis has become an integral part of the overall tire design process. Engineers need to perform a number of different simulations to evaluate new designs and study the effect of proposed design changes. However, tires pose formidable simulation challenges due to the presence of highly nonlinear rubber compounds, embedded reinforcements, complex tread geometries, rolling contact, and large deformations. Accurate simulation requires careful consideration of these factors, resulting in the extensive turnaround time, often times prolonging the design cycle. Therefore, it is extremely critical to explore means to reduce the turnaround time while producing reliable results. Compute clusters have recently become a cost effective means to perform high performance computing (HPC). Distributed memory parallel solvers designed to take advantage of compute clusters have become increasingly popular. In this paper, we examine the use of HPC for various tire simulations and demonstrate how it can significantly reduce simulation turnaround time. Abaqus/Standard is used for routine tire simulations like footprint and steady state rolling. Abaqus/Explicit is used for transient rolling and hydroplaning simulations. The run times and scaling data corresponding to models of various sizes and complexity are presented.


Author(s):  
D. T. Chen ◽  
J. Y. Lin ◽  
Y. K. Chuah ◽  
L. J. Fang

2010 ◽  
Vol 4 (2) ◽  
pp. 1-6
Author(s):  
S. Sankar ◽  
◽  
G. Gokula Krishnan ◽  

Author(s):  
B.KH. AKHALAYA ◽  
◽  
YU.KH SHOGENOV ◽  
S.I. STAROVOITOV ◽  
◽  
...  

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