Near-complete transuranic waste incineration in a thorium fuelled pressurised water reactor

The production of long-lived transuranic (TRU) waste is a major disadvantage of fission-based nuclear power. Incineration, and virtual elimination, of waste stockpiles is possible in a thorium (Th) fuelled critical or subcritical fast reactor. Fuel cycles producing a net decrease in TRUs are possible in conventional pressurised water reactors (PWRs). However, minor actinides (MAs) have a detrimental effect on reactivity and stability, ultimately limiting the quality and quantity of waste that can be incinerated. In this paper, we propose using a thorium-retained-actinides fuel cycle in PWRs, where the reactor is fuelled with a mixture of thorium and TRU waste, and after discharge all actinides are reprocessed and returned to the reactor. To investigate the feasibility and performance of this fuel cycle an assembly-level analysis for a one-batch reloading strategy was completed over 125 years of operation using WIMS 9. This one-batch analysis was performed for simplicity, but allowed an indicative assessment of the performance of a four-batch fuel management strategy. The build-up of 233U in the reactor allowed continued reactive and stable operation, until all significant actinide populations had reached pseudo-equilibrium in the reactor. It was therefore possible to achieve near-complete transuranic waste incineration, even for fuels with significant MA content. The average incineration rate was initially around 330 kg per GW th year and tended towards 250 kg per GW th year over several decades: a performance comparable to that achieved in a fast reactor. Using multiple batch fuel management, competitive or improved end-of-cycle burn-up appears achievable. The void coefficient (VC), moderator temperature coefficient (MTC) and Doppler coefficient remained negative. The quantity of soluble boron required for a fixed fuel cycle length was comparable to that for enriched uranium fuel, and acceptable amounts can be added without causing a positive VC or MTC. This analysis is limited by the consideration of a single fuel assembly, and it will be necessary to perform a full core coupled neutronic-thermal-hydraulic analysis to determine if the design in its current form is feasible. In particular, the potential for positive VCs if the core is highly or locally voided is a cause for concern. However, these results provide a compelling case for further work on concept feasibility and fuel management, which is in progress. © 2011 Elsevier Ltd. All rights reserved.

Low partial pressure chemical vapor deposition of graphene on copper

A systematic study of the Cu-catalyzed chemical vapor deposition of graphene under extremely low partial pressure is carried out. A carbon precursor supply of just P CH4∼ 0.009 mbar during the deposition favors the formation of large-area uniform monolayer graphene verified by Raman spectra. A diluted HNO 3 solution is used to remove Cu before transferring graphene onto SiO 2/Si substrates or carbon grids. The graphene can be made suspended over a ∼12 μm distance, indicating its good mechanical properties. Electron transport measurements show the graphene sheet resistance of ∼0.6 kΩ/□ at zero gate voltage. The mobilities of electrons and holes are ∼1800 cm 2/Vs at 4.2 K and ∼1200 cm 2/Vs at room temperature. © 2011 IEEE.

200-V lateral superjunction LIGBT on partial SOI

This letter presents a novel lateral superjunction lateral insulated-gate bipolar transistor (LIGBT) in partial silicon-on-insulator (SOI) technology in 0.18-μm partial-SOI (PSOI) high-voltage (HV) process. For an n-type superjunction LIGBT, the p-layer in the superjunction drift region not only helps in achieving uniform electric field distribution but also contributes to the on-state current. The superjunction LIGBT successfully achieves a breakdown voltage (BV) of 210 V with an R dson of 765 mΩ ̇ mm 2. It exhibits half the value of specific on-state resistance R dson and three times higher saturation current (I dsat) for the same BV, compared to a comparable lateral superjunction laterally diffused metal-oxide-semiconductor fabricated in the same technology. It also performs well in higher temperature dc operation with 38.8% increase in R dson at 175°C, compared to the room temperature without any degradation in latch-up performance. To realize this device, it only requires one additional mask layer into X-FAB 0.18-μm PSOI HV process. © 2012 IEEE.

Modelling and control of nonlinear systems using Gaussian processes with partial model information

Gaussian processes are gaining increasing popularity among the control community, in particular for the modelling of discrete time state space systems. However, it has not been clear how to incorporate model information, in the form of known state relationships, when using a Gaussian process as a predictive model. An obvious example of known prior information is position and velocity related states. Incorporation of such information would be beneficial both computationally and for faster dynamics learning. This paper introduces a method of achieving this, yielding faster dynamics learning and a reduction in computational effort from O(Dn2) to O((D - F)n2) in the prediction stage for a system with D states, F known state relationships and n observations. The effectiveness of the method is demonstrated through its inclusion in the PILCO learning algorithm with application to the swing-up and balance of a torque-limited pendulum and the balancing of a robotic unicycle in simulation. © 2012 IEEE.

Linear regression under fixed-rank constraints: A Riemannian approach

In this paper, we tackle the problem of learning a linear regression model whose parameter is a fixed-rank matrix. We study the Riemannian manifold geometry of the set of fixed-rank matrices and develop efficient line-search algorithms. The proposed algorithms have many applications, scale to high-dimensional problems, enjoy local convergence properties and confer a geometric basis to recent contributions on learning fixed-rank matrices. Numerical experiments on benchmarks suggest that the proposed algorithms compete with the state-of-the-art, and that manifold optimization offers a versatile framework for the design of rank-constrained machine learning algorithms. Copyright 2011 by the author(s)/owner(s).

Regression on fixed-rank positive semidefinite matrices: A Riemannian approach

The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space and on scalability to high-dimensional problems. The mathematical developments rely on the theory of gradient descent algorithms adapted to the Riemannian geometry that underlies the set of fixedrank positive semidefinite matrices. In contrast with previous contributions in the literature, no restrictions are imposed on the range space of the learned matrix. The resulting algorithms maintain a linear complexity in the problem size and enjoy important invariance properties. We apply the proposed algorithms to the problem of learning a distance function parameterized by a positive semidefinite matrix. Good performance is observed on classical benchmarks. © 2011 Gilles Meyer, Silvere Bonnabel and Rodolphe Sepulchre.

Riemannian metric and geometric mean for positive semidefinite matrices of fixed rank

This paper introduces a new metric and mean on the set of positive semidefinite matrices of fixed-rank. The proposed metric is derived from a well-chosen Riemannian quotient geometry that generalizes the reductive geometry of the positive cone and the associated natural metric. The resulting Riemannian space has strong geometrical properties: it is geodesically complete, and the metric is invariant with respect to all transformations that preserve angles (orthogonal transformations, scalings, and pseudoinversion). A meaningful approximation of the associated Riemannian distance is proposed, that can be efficiently numerically computed via a simple algorithm based on SVD. The induced mean preserves the rank, possesses the most desirable characteristics of a geometric mean, and is easy to compute. © 2009 Society for Industrial and Applied Mathematics.

Synchronization with partial state feedback on SO(n)

In this paper we consider the problem of constructing a distributed feedback law to achieve synchronization for a group of k agents whose states evolve on SO(n) and which exchange only partial state information along communication links. The partial state information is given by the action of the state on reference vectors in ℝn. We propose a gradient based control law which achieves exponential local convergence to a synchronization configuration under a rank condition on a generalized Laplacian matrix. Furthermore, we discuss the case of time-varying reference vectors and provide a convergence result for this case. The latter helps reach synchronization, requiring less communication links and weaker conditions on the instantaneous reference vectors. Our methods are illustrated on an attitude synchronization problem where agents exchange only their relative positions observed in the respective body frames. ©2009 IEEE.

200V superjunction lateral IGBT fabricated on partial SOI

A 200V lateral insulated gate bipolar transistor (LIGBT) was successfully developed using lateral superjunction (SJ) in 0.18μm partial silicon on insulator (SOI) HV process. The results presented are based on extensive experimental measurements and numerical simulations. For an n-type lateral SJ LIGBT, the p layer in the SJ drift region helps in achieving uniform electric field distribution. Furthermore, the p-pillar contributes to the on-state current. Furthermore, the p-pillar contributes to sweep out holes during the turn-off process, thus leading to faster removal of plasma. To realize this device, one additional mask layer is required in the X-FAB 0.18μm partial SOI HV process. © 2013 IEEE.