Pore-resolving Simulation of Char Particle Gasification Using Micro-CT

Understanding the interaction between transport, reaction and morphology at the scale of individual char particles is important for optimizing solid fuel gasification and combustion processes. However, most particle-scale models treat porous char particles as an effective porous continuum, even though the presence of large, irregular macropores, voids and fractures render such upscaled treatments mathematically invalid, and the models non-predictive. A new modeling framework is therefore proposed to elucidate the impact of morphology on char particle gasification and combustion. A pore-resolving, transient, three-dimensional simulation for gasification of a realistic coal char particle is developed based on X-ray micro-computed tomography (micro-CT). The large macropores and voids resolved by micro-CT are explicitly represented in the particle’s geometry and conservation equations based on first principles are solved in those regions. Upscaled, effective-continuum equations are applied only within the micro- and meso-porous grains surrounding the voids, where such equations are mathematically appropriate. To assess the impact of the realistic particle morphology, a second model which employs effective-continuum equations everywhere and assumes spherical symmetry is also developed for a particle having the same initial mass, volume, porosity, surface area and equivalent diameter as the pore-resolving model. The results indicate that large, irregular voids enhance mass transport throughout the particle and affect its overall conversion behavior when reactions occur under intra-particle diffusion control

Zero-Shot Learning by Convex Combination of Semantic Embeddings

Several recent publications have proposed methods for mapping images into continuous semantic embedding spaces. In some cases the embedding space is trained jointly with the image transformation. In other cases the semantic embedding space is established by an independent natural language processing task, and then the image transformation into that space is learned in a second stage. Proponents of these image embedding systems have stressed their advantages over the traditional \nway{} classification framing of image understanding, particularly in terms of the promise for zero-shot learning -- the ability to correctly annotate images of previously unseen object categories. In this paper, we propose a simple method for constructing an image embedding system from any existing \nway{} image classifier and a semantic word embedding model, which contains the \n class labels in its vocabulary. Our method maps images into the semantic embedding space via convex combination of the class label embedding vectors, and requires no additional training. We show that this simple and direct method confers many of the advantages associated with more complex image embedding schemes, and indeed outperforms state of the art methods on the ImageNet zero-shot learning task

Factors associated with hepatitis B vaccine series completion in a randomized trial for injection drug users reached through syringe exchange programs in three US cities

juillet 19311931/07 (T8,A1931)-1931/12.Appartient à l’ensemble documentaire : PACA

Constructions of Generalized Sidon Sets

We give explicit constructions of sets S with the property that for each integer k, there are at most g solutions to k=s_1+s_2, s_i\in S; such sets are called Sidon sets if g=2 and generalized Sidon sets if g\ge 3. We extend to generalized Sidon sets the Sidon-set constructions of Singer, Bose, and Ruzsa. We also further optimize Koulantzakis' idea of interleaving several copies of a Sidon set, extending the improvements of Cilleruelo & Ruzsa & Trujillo, Jia, and Habsieger & Plagne. The resulting constructions yield the largest known generalized Sidon sets in virtually all cases.Comment: 15 pages, 1 figure (revision fixes typos, adds a few details, and adjusts notation

No Free Lunch for Avoiding Clustering Vulnerabilities in Distributed Systems

Emergent design failures are ubiquitous in complex systems, and often arise when system elements cluster. Approaches to systematically reduce clustering could improve a design's resilience, but reducing clustering is difficult if it is driven by collective interactions among design elements. Here, we use techniques from statistical physics to identify mechanisms by which spatial clusters of design elements emerge in complex systems modelled by heterogeneous networks. We find that, in addition to naive, attraction-driven clustering, heterogeneous networks can exhibit emergent, repulsion-driven clustering. We draw quantitative connections between our results on a model system in naval engineering to entropy-driven phenomena in nanoscale self-assembly, and give a general argument that the clustering phenomena we observe should arise in many distributed systems. We identify circumstances under which generic design problems will exhibit trade-offs between clustering and uncertainty in design objectives, and we present a framework to identify and quantify trade-offs to manage clustering vulnerabilities.Comment: 20 pages, 5 figure

Challenges in Monitoring Regional Trail

This study reports traffic monitoring results at 30 locations on a 972-mi shared-use trail network across the east-central United States. We illustrate challenges in adapting the principles in the Federal Highway Administration’s Traffic Monitoring Guide to a regional trail network. We make four contributions: 1) we use factor analysis and k-means clustering to implement a stratified random process for selecting monitoring sites; 2) we illustrate quality assurance procedures and the challenges of obtaining valid results from a multi-state monitoring system; 3) we describe variation in trail traffic volumes across five land use classes in response to daily weather and seasons; and 4) we report two performance measures for the network: annual average daily trail traffic and trail miles traveled. The Rails to Trails Conservancy deployed passive infrared traffic monitors in 2015 through 2017. Site-specific regression models were used to impute missing daily traffic volumes. The effects of weather were consistent across land use classes but the effects of temporal variables, including weekend and season of year, varied. A plan for short-duration monitoring is presented. Results confirm the FHWA monitoring principles and the difficulties of implementing them regionally

Cockpit control system conceptual design

The purpose of this project was to provide a means for operating the ailerons, elevator, elevator trim, rudder, nosewheel steering, and brakes in the Triton primary flight trainer. The main design goals under consideration were to illustrate system and subsystem integration, control function ability, and producibility. Weight and maintenance goals were addressed