Oak Ridge National Laboratory

About: Oak Ridge National Laboratory is a facility organization based out in Oak Ridge, Tennessee, United States. It is known for research contribution in the topics: Neutron & Ion. The organization has 31868 authors who have published 73724 publications receiving 2633689 citations. The organization is also known as: ORNL.

ALLIANCE: an architecture for fault tolerant multirobot cooperation

Abstract: ALLIANCE is a software architecture that facilitates the fault tolerant cooperative control of teams of heterogeneous mobile robots performing missions composed of loosely coupled subtasks that may have ordering dependencies. ALLIANCE allows teams of robots, each of which possesses a variety of high-level functions that it can perform during a mission, to individually select appropriate actions throughout the mission based on the requirements of the mission, the activities of other robots, the current environmental conditions, and the robot's own internal states. ALLIANCE is a fully distributed, behaviour-based architecture that incorporates the use of mathematically-modeled motivations (such as impatience and acquiescence) within each robot to achieve adaptive action selection. Since cooperative robotic teams usually work in dynamic and unpredictable environments, this software architecture allows the robot team members to respond robustly, reliably, flexibly, and coherently to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. The feasibility of this architecture is demonstrated in an implementation on a team of mobile robots performing a laboratory version of hazardous waste cleanup.

Multilevel converters for large electric drives

Abstract: This paper presents transformerless multilevel power converters as an application for high-power and/or high-voltage electric motor drives. Multilevel converters: (1) can generate near-sinusoidal voltages with only fundamental frequency switching; (2) have almost no electromagnetic interference or common-mode voltage; and (3) are suitable for large voltampere-rated motor drives and high voltages. The cascade inverter is a natural fit for large automotive all-electric drives because it uses several levels of DC voltage sources, which would be available from batteries or fuel cells. The back-to-back diode-clamped converter is ideal where a source of AC voltage is available, such as in a hybrid electric vehicle. Simulation and experimental results show the superiority of these two converters over two-level pulsewidth-modulation-based drives.

Computer simulation of atomic-displacement cascades in solids in the binary-collision approximation

Abstract: A comprehensive computer program has been developed for the simulation of atomic-displacement cascades in a variety of crystalline solids, using the binary-collision approximation to contruct the projectile trajectories. The atomic scattering is governed by the Moli\'ere potential.Impact-parameter-dependent inelastic losses are included using Firsov's theory. Thermal vibrations of the target atoms and crystal surfaces may be included. Permanent displacement of lattice atoms may be based on either an energy-threshold criterion or a Frenkel-pair-separation criterion. An extensive series of calculations has been made for cascades in the simple metals Cu, Fe, and Au, to test the effects on the results of many of the model parameters. When a displacement-threshold energy is used, the number of Frenkel pairs is found to be a linear function of that part of the primary recoil energy which remains as the kinetic energy of atoms. This result is independent of target temperature, of the presence or absence of inelastic energy losses, and of various details of the model. In contrast, when a separation criterion is used, the number of defects increases less rapidly than linearly. This effect is caused by increased recombination in the highly disturbed tracks of the energetic recoils. Agreement between theoretical and experimental estimates of the radiation damage produced by neutron irradiation of Cu is substantially improved in the latter model.

Bayesian Variable Selection in Linear Regression

Abstract: This article is concerned with the selection of subsets of predictor variables in a linear regression model for the prediction of a dependent variable. It is based on a Bayesian approach, intended to be as objective as possible. A probability distribution is first assigned to the dependent variable through the specification of a family of prior distributions for the unknown parameters in the regression model. The method is not fully Bayesian, however, because the ultimate choice of prior distribution from this family is affected by the data. It is assumed that the predictors represent distinct observables; the corresponding regression coefficients are assigned independent prior distributions. For each regression coefficient subject to deletion from the model, the prior distribution is a mixture of a point mass at 0 and a diffuse uniform distribution elsewhere, that is, a “spike and slab” distribution. The random error component is assigned a normal distribution with mean 0 and standard deviation ...