The use of Th in HTR: State of the art and implementation in Th/Pu fuel cycles

Nowadays nuclear is the only greenhouse-free source that can appreciably respond to the increasing worldwide energy demand. The use of Thorium in the nuclear energy production may offer some advantages to accomplish this task. Extensive R&D on the thorium fuel cycle has been conducted in many countries around the world. Starting from the current nuclear waste policy, the EU-PUMA project focuses on the potential benefits of using the HTR core as a Pu/MA transmuter. In this paper the following aspects have been analysed: (1) the state-of-the-art of the studies on the use of Th in different reactors, (2) the use of Th in HTRs, with a particular emphasis on Th-Pu fuel cycles, (3) an original assessment of Th-Pu fuel cycles in HTR. Some aspects related to Thorium exploitation were outlined, particularly its suitability for working in pebble-bed HTR in a Th-Pu fuel cycle. The influence of the Th/Pu weight fraction at BOC in a typical HTR pebble was analysed as far as the reactivity trend versus burn-up, the energy produced per Pu mass, and the Pu isotopic composition at EOC are concerned. Although deeper investigations need to be performed in order to draw final conclusions, it is possible to state that some optimized Th percentage in the initial Pu/Th fuel could be suggested on the basis of the aim we are trying to reach. Copyright © 2009 Guido Mazzini et al.

Experimental and theoretical comparison between static and dynamic torsional soil tests

The dynamic properties of dry Leighton Buzzard sand have been investigated using a resonant column test apparatus. These data are compared with very low frequency cyclic tests on identical specimens of sand. The comparison indicates that the properties of dry sand are independent of frequency. A simple one-dimensional model of kinematic hardening plasticity is used to predict the dynamic behaviour of the sand. The input parameters for this model are based on the results of static tests. These may be conducted on standard laboratory equipment with only minor modifications. The predictions are in good agreement with the measured data.

Neuro-Fuzzy genetic system for selection of construction project managers

Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions