A discrete element method representation of an anisotropic elastic continuum

A method for modeling cubically anisotropic elasticity within the discrete element method is presented. The discrete element method (DEM) is an approach originally intended for modeling granular materials (sand, soil, and powders); however, recent developments have usefully extended it to model stochastic mechanical processes in monolithic solids which, to date, have been assumed to be elastically isotropic. The method presented here for efficiently capturing cubic elasticity in DEM is an important prerequisite for further extending DEM to capture the influence of elastic anisotropy on the mechanical response of polycrystals, composites, etc. The system demonstrated here uses a directionally assigned stiffness in the bonds between adjacent elements and includes separate schemes for achieving anisotropy with Zener ratios greater and smaller than one. The model framework is presented along with an analysis of the accessible space of elastic properties that can be modeled and an artificial neural network interpolation scheme for mapping input parameters to model elastic behavior

A social spider algorithm for global optimization

The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Metaheuristics based on evolutionary computation and swarm intelligence are outstanding examples of nature-inspired solution techniques. Inspired by the social spiders, we propose a novel social spider algorithm to solve global optimization problems. This algorithm is mainly based on the foraging strategy of social spiders, utilizing the vibrations on the spider web to determine the positions of preys. Different from the previously proposed swarm intelligence algorithms, we introduce a new social animal foraging strategy model to solve optimization problems. In addition, we perform preliminary parameter sensitivity analysis for our proposed algorithm, developing guidelines for choosing the parameter values. The social spider algorithm is evaluated by a series of widely used benchmark functions, and our proposed algorithm has superior performance compared with other state-of-the-art metaheuristics.postprin

Coordinated Autonomous Vehicle Parking for Vehicle-to-Grid Services: Formulation and Distributed Algorithm

Autonomous vehicles (AVs) will revolutionarize ground transport and take a substantial role in the future transportation system. Most AVs are likely to be electric vehicles (EVs) and they can participate in the vehicle-to-grid (V2G) system to support various V2G services. Although it is generally infeasible for EVs to dictate their routes, we can design AV travel plans to fulfill certain system-wide objectives. In this paper, we focus on the AVs looking for parking and study how they can be led to appropriate parking facilities to support V2G services. We formulate the Coordinated Parking Problem (CPP), which can be solved by a standard integer linear program solver but requires long computational time. To make it more practical, we develop a distributed algorithm to address CPP based on dual decomposition. We carry out a series of simulations to evaluate the proposed solution methods. Our results show that the distributed algorithm can produce nearly optimal solutions with substantially less computational time. A coarser time scale can improve computational time but degrade the solution quality resulting in possible infeasible solution. Even with communication loss, the distributed algorithm can still perform well and converge with only little degradation in speed.postprin

Delay Aware Intelligent Transient Stability Assessment System

Transient stability assessment is a critical tool for power system design and operation. With the emerging advanced synchrophasor measurement techniques, machine learning methods are playing an increasingly important role in power system stability assessment. However, most existing research makes a strong assumption that the measurement data transmission delay is negligible. In this paper, we focus on investigating the influence of communication delay on synchrophasor-based transient stability assessment. In particular, we develop a delay aware intelligent system to address this issue. By utilizing an ensemble of multiple long short-term memory networks, the proposed system can make early assessments to achieve a much shorter response time by utilizing incomplete system variable measurements. Compared with existing work, our system is able to make accurate assessments with a significantly improved efficiency. We perform numerous case studies to demonstrate the superiority of the proposed intelligent system, in which accurate assessments can be developed with time one third less than state-of-the-art methodologies. Moreover, the simulations indicate that noise in the measurements has trivial impact on the assessment performance, demonstrating the robustness of the proposed system.published_or_final_versio

Coordinated autonomous vehicle parking for vehicle-to-grid services

postprin

Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization

Image-based camera relocalization is an important problem in computer vision and robotics. Recent works utilize convolutional neural networks (CNNs) to regress for pixels in a query image their corresponding 3D world coordinates in the scene. The final pose is then solved via a RANSAC-based optimization scheme using the predicted coordinates. Usually, the CNN is trained with ground truth scene coordinates, but it has also been shown that the network can discover 3D scene geometry automatically by minimizing single-view reprojection loss. However, due to the deficiencies of the reprojection loss, the network needs to be carefully initialized. In this paper, we present a new angle-based reprojection loss, which resolves the issues of the original reprojection loss. With this new loss function, the network can be trained without careful initialization, and the system achieves more accurate results. The new loss also enables us to utilize available multi-view constraints, which further improve performance.Comment: ECCV 2018 Workshop (Geometry Meets Deep Learning

Magnetic ordering at the edges of graphitic fragments: Magnetic tail interactions between the edge-localized states

To understand the formation mechanism of magnetic moments at the edges of graphitic fragments, we carry out first-principles density-functional calculations for the electronic and magnetic structures of graphitic fragments with various spin and geometric configurations. We find that interedge and interlayer interactions between the localized moments can be explained in terms of interactions between the magnetic tails of the edge-localized states. In addition, the dihydrogenated edge states as well as Fe ad-atoms at the edge are studied in regard to the magnetic order and proximity effects.open28621

Energetics of large carbon clusters: Crossover from fullerenes to nanotubes

The energetics of large-sized fullerenes and carbon nanotubes is investigated through first-principles pseudopotential calculations for the carbon cluster of CN (60???N???540). The strain energy due to the presence of pentagons, in addition to the curvature effect, makes an important contribution to the energetics of the fullerenes and nanotubes and accurately describes the N dependence of the energy of the spherical fullerenes. Our model predicts that a nanotube of ??? 13 A in diameter [for example, a (9,9) or (10,10) tube] is energetically most stable among various single-walled nanotubes and fullerenes, consistent with many experimental observations.open252

Individuals with knee impairments identify items in need of clarification in the Patient Reported Outcomes Measurement Information System (PROMIS®) pain interference and physical function item banks - a qualitative study

Background: The content and wording of the Patient Reported Outcome Measurement Information System (PROMIS) Physical Function and Pain Interference item banks have not been qualitatively assessed by individuals with knee joint impairments. The purpose of this investigation was to identify items in the PROMIS Physical Function and Pain Interference Item Banks that are irrelevant, unclear, or otherwise difficult to respond to for individuals with impairment of the knee and to suggest modifications based on cognitive interviews. Methods: Twenty-nine individuals with knee joint impairments qualitatively assessed items in the Pain Interference and Physical Function Item Banks in a mixed-methods cognitive interview. Field notes were analyzed to identify themes and frequency counts were calculated to identify items not relevant to individuals with knee joint impairments. Results: Issues with clarity were identified in 23 items in the Physical Function Item Bank, resulting in the creation of 43 new or modified items, typically changing words within the item to be clearer. Interpretation issues included whether or not the knee joint played a significant role in overall health and age/gender differences in items. One quarter of the original items (31 of 124) in the Physical Function Item Bank were identified as irrelevant to the knee joint. All 41 items in the Pain Interference Item Bank were identified as clear, although individuals without significant pain substituted other symptoms which interfered with their life. Conclusions: The Physical Function Item Bank would benefit from additional items that are relevant to individuals with knee joint impairments and, by extension, to other lower extremity impairments. Several issues in clarity were identified that are likely to be present in other patient cohorts as well