Detailed design of242mAm breeding in pressurized water reactors

There is growing interest in the use of 242mAm as a nuclear fuel. Because of its very high thermal fission cross section and its large number of neutrons released per fission, it can be used for various unique applications, such as space propulsion, medical applications, and compact energy sources. Since the thermal absorption cross section of 242mAm is very high, the best way to obtain 242mAm is by the capture of fast or epithermal neutrons in 241Am. However, fast spectrum reactors are not readily available. In this paper, we explore the possibility of producing 242mAm in existing pressurized water reactors (PWRs) with minimal interference in reactor performance. As suggested in previous studies on the subject, the 242mAm breeding targets are shielded with strong thermal absorbers in order to suppress the thermal neutron flux that causes 242mAm destruction. Since 242mAm enrichment within the Am target mainly depends on the neutron energy distribution, which in turn depends on the Am target thickness and on the neutron filter cutoff energy (thermal absorber type), this unique Am target design was developed. In our study, Cd, Sm, and Gd were considered as thermal neutron filters, as suggested by Cesana et al. The most favorable results were obtained by irradiating Am targets covered either with Gd or Cd. In these cases, up to 8.65% enrichment of 242mAm is obtained after 4.5 yr (three successive PWR fuel cycles) of irradiation. It was also found that significant quantities [up to 1.3 kg/GW (electric)-yr] of 242mAm can be obtained in PWR reactors without notable interference with reactor performance. However, in order to maintain the original fuel cycle length, the enrichment of the driver (UO2) fuel must be increased by ∼1%, raised from the conventional 4.5 to 5.5%, depending on the thermal neutron filter used. The most important reactivity feedback coefficients for fuel assemblies containing the 242mAm breeding targets were evaluated and found to be close to those of a standard PWR. Another product of neutron capture in the 241Am reaction is 238Pu. It was found that in a typical 1000 MW (electric) PWR core with one-third of the fuel assemblies containing 241Am targets, up to 15.1 kg of 238Pu enriched to 80% can be produced per year.

The cross-entropy method for blind multiuser detection

We consider the problem of blind multiuser detection. We adopt a Bayesian approach where unknown parameters are considered random and integrated out. Computing the maximum a posteriori estimate of the input data sequence requires solving a combinatorial optimization problem. We propose here to apply the Cross-Entropy method recently introduced by Rubinstein. The performance of cross-entropy is compared to Markov chain Monte Carlo. For similar Bit Error Rate performance, we demonstrate that Cross-Entropy outperforms a generic Markov chain Monte Carlo method in terms of operation time.

Cross-sectional structure of tetrahedral amorphous carbon thin films

A cross-sectional transmission electron microscope study of the low density layers at the surface and at the substrate-film interface of tetrahedral amorphous carbon (ta-C) films grown on (001) silicon substrates is presented. Spatially resolved electron energy loss spectroscopy is used to determine the bonding and composition of a tetrahedral amorphous carbon film with nanometre spatial resolution. For a ta-C film grown with a substrate bias of -300 V, an interfacial region approximately 5 nm wide is present in which the carbon is sp2 bonded and is mixed with silicon and oxygen from the substrate. An sp2 bonded layer observed at the surface of the film is 1.3 ± 0.3 nm thick and contains no detectable impurities. It is argued that the sp2 bonded surface layer is intrinsic to the growth process, but that the sp2 bonding in the interfacial layer at the substrate may be related to the presence of oxygen from the substrate.

Language model cross adaptation for LVCSR system combination

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptation can be used as an alternative to direct hypothesis level combination schemes such as ROVER. In normal cross adaptation it is assumed that useful diversity among systems exists only at acoustic level. However, complimentary features among complex LVCSR systems also manifest themselves in other layers of modelling hierarchy, e.g., subword and word level. It is thus interesting to also cross adapt language models (LM) to capture them. In this paper cross adaptation of multi-level LMs modelling both syllable and word sequences was investigated to improve LVCSR system combination. Significant error rate gains up to 6.7% rel. were obtained over ROVER and acoustic model only cross adaptation when combining 13 Chinese LVCSR subsystems used in the 2010 DARPA GALE evaluation. © 2010 ISCA.