Post-earthquake behaviour of footings employing densification to mitigate liquefaction

In situ densification is a popular technique to protect shallow foundations from the effects of earthquake-induced liquefaction, current design being based on semiempirical rules. Poor understanding of the mechanisms governing the performance of soil-structure systems during and after earthquakes inhibits the use of narrow densified zones, which could contribute to optimise the use of densification if the increase in post-earthquake settlement is restrained. Therefore this paper investigates the long-term behaviour of a footing built on densified ground and surrounded by liquefiable ground, centrifuge experiments being used to identify the mechanisms occurring in the ground during and after a seismic simulation. The differential excess pore pressure generated in the ground during the shaking and the processes of vertical stress concentration and subsequent redistribution observed under the footing dominate the system behaviour. The results enlighten the complex mechanisms determining the post-earthquake settlement when densification is carried out to mitigate liquefaction effects. The improvement in performance resulting from widening the zone of densification is rationally explained which encourages the development of new design concepts that may enhance the future use of densification as a liquefaction resistance measure. © 2007 Thomas Telford Ltd.

The design of an agent for modelling supply chain network dynamics

A useful insight into managerial decision making can be found from simulation of business systems, but existing work on simulation of supply chain behaviour has largely considered non-competitive chains. Where competitive agents have been examined, they have generally had a simple structure and been used for fundamental examination of stability and equilibria rather than providing practical guidance to managers. In this paper, a new agent for the study of competitive supply chain network dynamics is proposed. The novel features of the agent include the ability to select between competing vendors, distribute orders preferentially among many customers, manage production and inventory, and determine price based on competitive behaviour. The structure of the agent is related to existing business models and sufficient details are provided to allow implementation. The agent is tested to demonstrate that it recreates the main results of the existing modelling and management literature on supply chain dynamics. A brief exploration of competitive dynamics is given to confirm that the proposed agent can respond to competition. The results demonstrate that overall profitability for a supply chain network is maximised when businesses operate collectively. It is possible for an individual business to achieve higher profits by adopting a more competitive stance, but the consequence of this is that the overall profitability of the network is reduced. The agent will be of use for a broad range of studies on the long-run effect of management decisions on their network of suppliers and customers.

Asymptotic behaviour of approximate Bayesian estimators

Although approximate Bayesian computation (ABC) has become a popular technique for performing parameter estimation when the likelihood functions are analytically intractable there has not as yet been a complete investigation of the theoretical properties of the resulting estimators. In this paper we give a theoretical analysis of the asymptotic properties of ABC based parameter estimators for hidden Markov models and show that ABC based estimators satisfy asymptotically biased versions of the standard results in the statistical literature.