Neutron interrogation of high-enriched uranium by a 4 MeV linac

For revealing unauthorized transport (illicit trafficking) of nuclear materials, a non-destructive method reported earlier, utilizing a 4 MeV linear accelerator for photoneutron interrogation, was further developed. The linac served as a pulsed neutron source for assay of highly enriched uranium. Produced in beryllium or heavy water by bremsstrahlung, neutrons subsequently induced fission in the samples. Delayed neutrons were detected by a newly designed neutron collar built up of 14 ³He counters embedded in a polyethylene moderator. A PC controlled multiscaler served as a time analyzer, triggering the detector startup by the beam pulse. Significant progress was achieved in enhancing the detector response, hence the sensitivity for revealing illicit material. A lower sensitivity limit of the order of 10 mg ²³⁵U was determined in a 20 s measurement time with a reasonable amount of beryllium (170 g) or of heavy water (100 g) and a mean electron current of 10 μA. Sensitivity can be further enhanced by increasing the measurement time.     

Calculation of the power peaking factor in a nuclear reactor using support vector regression models

Local power density (LPD) at the hottest part of a hot nuclear fuel rod should be estimated accurately to confirm that the rod does not melt. The power peaking factor (PPF) is defined as the highest LPD divided by the average power density in the reactor core. In this paper, the PPF is calculated by support vector regression (SVR) models using numerous measured signals from the reactor cooling system. SVR models are regression analysis models using a kernel function for artificial neural networks. Their neural network weights are found by solving a quadratic programming problem under linear constraints. SVR models are trained using a training data set and then verified against another test data set. The proposed SVR models were applied to the first fuel cycle of the Yonggwang nuclear power plant unit 3. The root mean square errors of the SVR model, with and without in-core neutron flux sensor signal inputs, were 0.1113% and 0.0968%, respectively. This level of errors is sufficiently low for use in LPD monitoring.     

Simulation of polymer removal from a powder injection molding compact by thermal debinding

Powder injection molding (PIM) is an important net-shape manufacturing process. Thermal debinding is a common methodology for the final removal of residual polymer from a PIM compact prior to sintering. This process is an intricate combination of evaporation, liquid and gas migration, pyrolysis of polymer, and heat transfer in porous media. A better understanding of thermal debinding could lead to optimization of the process to prevent the formation of defects. Simulation of the process based on an integrated mathematical model for mass and heat transfer in porous media is proposed. The mechanisms of mass transport, i.e., liquid flow, gas flow, vapor diffusion, and convection, as well as the phase transitions of polymer, and their interactions, are included in the model. The macroscopic partial differential equations are formulated by volume averaging of the microscopic conservation laws. The basic equations consist of mass conservation and energy conservation and are solved numerically. Polymer residue, pressure, and temperature distributions are predicted. The importance of the various mass transfer mechanisms is evaluated. The effects of key mass transfer parameters on thermal debinding are discussed. It is revealed from the results that the assumed binder front, which is supposed to recede into the powder compact as removal progresses, does not exist. The mass flux of polymer liquid is of the same order of the mass flux of polymer vapor in the gas phase, and the polymer vapor diffusion in the liquid phase is negligible.     

Measurement-based simulation model for TCP over ATM

Cell level analysis of ATM networks by means of simulation requires an accurate model for traffic sources. We present a simple model for TCP over ATM traffic sources in an ATM LAN, which captures the fundamental characteristics of the behaviour of tcp in this environment. The model was developed by extensive statistical analysis of numerous traffic traces recorded in an atm testbed. Simulated traffic generated by our model has roughly the same properties as observed in real traffic, even on the time scale of milliseconds. This makes it suitable for use by the analysis of various scheduling and congestion management algorithms.     

Clock generation and distribution for the first IA-64microprocessor

The clock design for the first implementation of the IA-64 microprocessor is presented. A clock distribution with an active distributed deskewing technique is used to achieve a low skew of 28 ps. This technique is capable of compensating skews caused by within-die process variations that are becoming a significant factor of the clock design. The global, regional and local clock distributions are described. A multilevel skew budget and local clock timing methodology are used to enable a high-performance design by providing support for intentional clock skew injection and time borrowing. By providing a test access port interface to the deskew architecture and the incorporation of the on-die-clock-shrink, this design is equipped with two very powerful post-silicon timing debug tools that are critical to high-performance microprocessor design and enabled quick time-to-market     

Estimation of directions of arrival of multipath signals in CDMAsystems

An algorithm is proposed for estimating the directions of arrival (DOAs) of multipath signals received from multiple users on the uplink of a code-division multiple-access system. The correlation matrices of the received signal before and after code-matched filtering are used to provide unique estimates even when the number of required DOAs exceeds the number of antenna array elements. This scenario is well known to cause conventional direction-finding algorithms (such as MUSIC) to fail. Both intersymbol interference (ISI) and multiple-access interference (MAI) are modeled exactly, and so the algorithm performs much better than those which model ISI and MAI as Gaussian noise     

Determinants of player acceptance of mobile social network games: An application of extended technology acceptance model

In recent years, mobile devices and social network games (SNGs) have gained wide popularity among the mainstream users. The present study aims to investigate the psychological elements that may contribute to user behaviors regarding mobile-social network games (M-SNGs). This study introduces an integrated model for M-SNGs. Statistical results from an online survey of players of M-SNGs indicate that the proposed research model effectively demonstrates and examines player acceptance of and attitudes toward M-SNGs. This research model is valid, and illustrates not only perceived enjoyment and usefulness as determinant variables of intention to use among players, but also perceived mobility together with perceived control and skill as motivational factors for players. The results also describe that satisfaction has a moderate role, which in turn has significant effects on multiple connections in the research model. Both theoretical and practical implications are provided based on the findings.