Seismic Earth Pressure Development in Sheet Pile Retaining Walls: A Numerical Study

The design of retaining walls requires the complete knowledge of the earth pressure distribution behind the wall. Due to the complex soil-structure effect, the estimation of earth pressure is not an easy task; even in the static case. The problem becomes even more complex for the dynamic (i.e., seismic) analysis and design of retaining walls. Several earth pressure models have been developed over the years to integrate the dynamic earth pressure with the static earth pressure and to improve the design of retaining wall in seismic regions. Among all the models, MononobeOkabe (M-O) method is commonly used to estimate the magnitude of seismic earth pressures in retaining walls and is adopted in design practices around the world (e.g., EuroCode and Australian Standards). However, the M-O method has several drawbacks and does not provide reliable estimate of the earth pressure in many instances. This study investigates the accuracy of the M-O method to predict the dynamic earth pressure in sheet pile wall. A 2D plane strain finite element model of the wall-soil system was developed in DIANA. The backfill soil was modelled with Mohr-Coulomb failure criterion while the wall was assumed behave elastically. The numerically predicted dynamic earth pressure was compared with the M-O model prediction. Further, the point of application of total dynamic force was determined and compared with the static case. Finally, the applicability of M-O methods to compute the seismic earth pressure was discussed

A note on the gaps between consecutive zeros of the Riemann zeta-function

Assuming the Riemann Hypothesis, we show that infinitely often consecutive non-trivial zeros of the Riemann zeta-function differ by at most 0.5155 times the average spacing and infinitely often they differ by at least 2.69 times the average spacing.Comment: 7 pages. Submitted for publicatio

How Far Removed Are You? Scalable Privacy-Preserving Estimation of Social Path Length with Social PaL

Social relationships are a natural basis on which humans make trust decisions. Online Social Networks (OSNs) are increasingly often used to let users base trust decisions on the existence and the strength of social relationships. While most OSNs allow users to discover the length of the social path to other users, they do so in a centralized way, thus requiring them to rely on the service provider and reveal their interest in each other. This paper presents Social PaL, a system supporting the privacy-preserving discovery of arbitrary-length social paths between any two social network users. We overcome the bootstrapping problem encountered in all related prior work, demonstrating that Social PaL allows its users to find all paths of length two and to discover a significant fraction of longer paths, even when only a small fraction of OSN users is in the Social PaL system - e.g., discovering 70% of all paths with only 40% of the users. We implement Social PaL using a scalable server-side architecture and a modular Android client library, allowing developers to seamlessly integrate it into their apps.Comment: A preliminary version of this paper appears in ACM WiSec 2015. This is the full versio