Modelling effects of axial load on behaviour of pile groups in laterally-spreading soil

Previous research into the behaviour of piled foundations in laterally-spreading soil deposits has concentrated on pile groups that carry small or negligible axial loads. This paper presents dynamic centrifuge test results for 2 x 2 pile groups with bending and geometric properties similar to real 0.5 m diameter tubular steel and solid circular reinforced-concrete field piles. Axial loads applied represented upper-bounds on typical working loads. The simultaneous scaling of the relevant properties controlling both lateral and axial behaviour allows comparisons to be drawn regarding the particular mechanisms of failure that would dominate for each type of pile. Flexible reinforced-concrete piles which tend to carry lower loads were found to be dominated by lateral effects, while steel piles, which are much stiffer and usually carry greater loads are dominated by settlement considerations. © 2006 Taylor & Francis Group.

Modelling effects of axial load on behaviour of pile groups in laterally-spreading soil

Previous research into the behaviour of piled foundations in laterally-spreading soil deposits has concentrated on pile groups that carry small or negligible axial loads. This paper presents dynamic centrifuge test results for 2×2 pile groups with bending and geometric properties similar to real 0.5m diameter tubular steel and solid circular reinforced-concrete field piles. Axial loads applied represented upper-bounds on typical working loads. The simultaneous scaling of the relevant properties controlling both lateral and axial behaviour allows comparisons to be drawn regarding the particular mechanisms of failure that would dominate for each type of pile. Flexible reinforced-concrete piles which tend to carry lower loads were found to be dominated by lateral effects, while steel piles, which are much stiffer and usually carry greater loads are dominated by settlement considerations. © 2006 Taylor & Francis Group, London.

Minimum sensor duty cycle with guaranteed estimator performance

In this paper, we consider Kalman filtering over a network and construct the optimal sensor data scheduling schemes which minimize the sensor duty cycle and guarantee a bounded error or a bounded average error at the remote estimator. Depending on the computation capability of the sensor, we can either give a closed-form expression of the minimum sensor duty cycle or provide tight lower and upper bounds of it. Examples are provided throughout the paper to demonstrate the results. © 2012 IEEE.

Closely correlating lower and upper bound plastic analysis of real slabs

An engineer assessing the load-carrying capacity of an existing reinforced concrete slab is likely to use elastic analysis to check the load at which the structure might be expected to fail in flexure or in shear. In practice, many reinforced concrete slabs are highly ductile in flexure, so an elastic analysis greatly underestimates the loads at which they fail in this mode. The use of conservative elastic analysis has led engineers to incorrectly condemn many slabs and therefore to specify unnecessary and wasteful flexural strengthening or replacement. The lower bound theorem is based on the same principles as the upper bound theorem used in yield line analysis, but any solution that rigorously satisfies the lower bound theorem is guaranteed to be a safe underestimate of the collapse load. Jackson presented a rigorous lower bound method that obtains very accurate results for complex real slabs.

Improved bounds for subband-adaptive iterative shrinkage/thresholding algorithms.

This paper presents new methods for computing the step sizes of the subband-adaptive iterative shrinkage-thresholding algorithms proposed by Bayram & Selesnick and Vonesch & Unser. The method yields tighter wavelet-domain bounds of the system matrix, thus leading to improved convergence speeds. It is directly applicable to non-redundant wavelet bases, and we also adapt it for cases of redundant frames. It turns out that the simplest and most intuitive setting for the step sizes that ignores subband aliasing is often satisfactory in practice. We show that our methods can be used to advantage with reweighted least squares penalty functions as well as L1 penalties. We emphasize that the algorithms presented here are suitable for performing inverse filtering on very large datasets, including 3D data, since inversions are applied only to diagonal matrices and fast transforms are used to achieve all matrix-vector products.