Abstract: In the classical buckling analysis of rectangular plates
subjected to the concurrent action of shear and uniaxial forces, the
Euler shear buckling stress is generally evaluated separately, so that
no influence on the shear buckling coefficient, due to the in-plane
tensile or compressive forces, is taken into account.
In this paper the buckling problem of simply supported rectangular
plates, under the combined action of shear and uniaxial forces, is
discussed from the beginning, in order to obtain new project formulas
for the shear buckling coefficient that take into account the presence
of uniaxial forces.
Furthermore, as the classical expression of the shear buckling
coefficient for simply supported rectangular plates is considered only
a “rough" approximation, as the exact one is defined by a system of
intersecting curves, the convergence and the goodness of the classical
solution are analyzed, too.
Finally, as the problem of the Euler shear buckling stress
evaluation is a very important topic for a variety of structures, (e.g.
ship ones), two numerical applications are carried out, in order to
highlight the role of the uniaxial stresses on the plating scantling
procedures and the goodness of the proposed formulas.
Abstract: Fair share objective has been included into the goaloriented
parallel computer job scheduling policy recently. However,
the previous work only presented the overall scheduling performance.
Thus, the per-user performance of the policy is still lacking. In this
work, the details of per-user fair share performance under the
Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair
share priority backfill policy namely RelShare(1d) is also studied.
The performance of all policies is collected using an event-driven
simulator with three real job traces as input. The experimental results
show that the high demand users are usually benefited under most
policies because their jobs are large or they have a lot of jobs. In the
large job case, one job executed may result in over-share during that
period. In the other case, the jobs may be backfilled for
performances. However, the users with a mixture of jobs may suffer
because if the smaller jobs are executing the priority of the remaining
jobs from the same user will be lower. Further analysis does not show
any significant impact of users with a lot of jobs or users with a large
runtime approximation error.