A Fully Bayesian Approach for Combining Multilevel Failure Information in Fault Tree Quantification and Corresponding Optimal Resource Allocation

This paper presents a fully Bayesian approach that simultaneously combines basic event and statistically independent higher event-level failure data in fault tree quantification. Such higher-level data could correspond to train, sub-system or system failure events. The full Bayesian approach also allows the highest-level data that are usually available for existing facilities to be automatically propagated to lower levels. A simple example illustrates the proposed approach. The optimal allocation of resources for collecting additional data from a choice of different level events is also presented. The optimization is achieved using a genetic algorithm.

Characterization of harmonic tremor at Santiaguito volcano and its implications for eruption mechanisms

We observed Santiaguito volcano in southwestern Guatemala from March 2008 - March 2010. Seismic and infrasound data collected between January and March of 2009 contain records of many diverse processes occurring at the dacitic dome complex, including the recurrence of short lived (30-200 seconds in duration) harmonic tremor concurrent with ash poor gas emissions from the volcano. We employ several different analytical techniques to examine different portions of the tremor and source mechanisms. We use the parameters derived by this analysis to compare the feasibility of several suggested models of eruption mechanisms, and determine that this type of harmonic tremor is most justifiably generated by the flow of gas through crack networks generated by shear fracture along the magma conduit margin.

Farmer land allocation for maize, groundnut and cotton production in Chipata District, Eastern Province, Zambia

Small-scale farmers in the Chipata District of Zambia rely on their farm fields to grow maize and groundnuts for food security. Cotton production and surplus food security crops are used to generate income to provide for their families. With increasing population pressure, available land has decreased and farmers struggle to provide the necessary food requirements and income to meet their family’s needs. The purpose of the study was to determine how a farmer can best allocate his land to produce maize, groundnuts and cotton when constrained by labor and capital resources to generate the highest potential for food security and financial gains. Data from the 2008-2009 growing season was compiled and analyzed using a linear programming model. The study determined that farmers make the most profit by allocating all additional land and resources to cotton after meeting their minimum food security requirements. The study suggests growing cotton is a beneficial practice for small-scale subsistence farmers to generate income when restricted by limited resources.