Multiphase CFD modeling to evaluate and to improve mixing in Chinese dome digester

Household or domestic biogas plants constitute a growing sub-sector of the anaerobic digestion industry worldwide, but had received low research attention for improvements. The Chinese dome digester (CDD), a major type of domestic biogas plant, is a naturally mixed, unheated and low tech system that is mainly used in rural areas. In this study, a multiphase computational fluid dynamics (CFD) model was applied to evaluate and subsequently improve mixing in a lab scale Chinese dome digester. The normal Chinese dome digester (CDD1) and two baffle configurations were investigated to improve the hydraulic mixing in the digester (CDD2 and CDD3 respectively) . 2-D time dependent numerical simulations were done with the three-phase, phase field model in COMSOL Multiphysics in a CDD geometry. Residence time distribution (RTD) curves were derived for all the configurations to evaluate and compare performances. In addition, three hydraulic indicators were also studied to evaluate mixing improvement. The Anaerobic digestion model No. 1 (ADM1) was used to evaluate biogas production. The effects of the addition of baffles to the CDDs did not significantly improve mixing, however about 16 % of dead zones was reduced in the two-baffle configuration

Diffusion due to the Beam-Beam Interaction and Fluctuating Fields in Hadron Colliders

Random fluctuations in the tune, beam offsets and beam size in the presence of the beam-beam interaction are shown to lead to significant particle diffusion and emittance growth in hadron colliders. We find that far from resonances high frequency noise causes the most diffusion while near resonances low frequency noise is responsible for the large emittance growth observed. Comparison of different fluctuations shows that offset fluctuations between the beams causes the largest diffusion for particles in the beam core.Comment: 5 pages, 3 postscript figure

Applying Rule Ensembles to the Search for Super-Symmetry at the Large Hadron Collider

In this note we give an example application of a recently presented predictive learning method called Rule Ensembles. The application we present is the search for super-symmetric particles at the Large Hadron Collider. In particular, we consider the problem of separating the background coming from top quark production from the signal of super-symmetric particles. The method is based on an expansion of base learners, each learner being a rule, i.e. a combination of cuts in the variable space describing signal and background. These rules are generated from an ensemble of decision trees. One of the results of the method is a set of rules (cuts) ordered according to their importance, which gives useful tools for diagnosis of the model. We also compare the method to a number of other multivariate methods, in particular Artificial Neural Networks, the likelihood method and the recently presented boosted decision tree method. We find better performance of Rule Ensembles in all cases. For example for a given significance the amount of data needed to claim SUSY discovery could be reduced by 15 % using Rule Ensembles as compared to using a likelihood method.Comment: 24 pages, 7 figures, replaced to match version accepted for publication in JHE

Planning the Future of U.S. Particle Physics (Snowmass 2013): Chapter 6: Accelerator Capabilities

These reports present the results of the 2013 Community Summer Study of the APS Division of Particles and Fields ("Snowmass 2013") on the future program of particle physics in the U.S. Chapter 6, on Accelerator Capabilities, discusses the future progress of accelerator technology, including issues for high-energy hadron and lepton colliders, high-intensity beams, electron-ion colliders, and necessary R&D for future accelerator technologies.Comment: 26 page

θ13\theta_{13}, δ\delta and the neutrino mass hierarchy at a γ=350\gamma=350 double baseline Li/B β\beta-Beam

We consider a $\beta$-Beam facility where $^8$Li and $^8$B ions are accelerated at $\gamma = 350$, accumulated in a 10 Km storage ring and let decay, so as to produce intense $\bar \nu_e$ and $\nu_e$ beams. These beams illuminate two iron detectors located at $L \simeq 2000$ Km and $L \simeq 7000$ Km, respectively. The physics potential of this setup is analysed in full detail as a function of the flux. We find that, for the highest flux ($10 \times 10^{18}$ ion decays per year per baseline), the sensitivity to $\theta_{13}$ reaches $\sin^2 2 \theta_{13} \geq 2 \times10^{-4}$; the sign of the atmospheric mass difference can be identified, regardless of the true hierarchy, for $\sin^2 2 \theta_{13} \geq 4\times10^{-4}$; and, CP-violation can be discovered in 70% of the $\delta$-parameter space for $\sin^2 2 \theta_{13} \geq 10^{-3}$, having some sensitivity to CP-violation down to $\sin^2 2 \theta_{13} \geq 10^{-4}$ for $|\delta| \sim 90^\circ$.Comment: 35 pages, 20 figures. Minor changes, matches the published versio

Comparison of phenotypic and genotypic diagnosis of acute human bocavirus 1 infection in children

Background: Diagnosis of human bocavirus 1 (HBoV1) has been based on qualitative PCRs detecting HBoV1 DNA or detection of HBoV1 mRNA. Objective: This study aims to assess whether a rapid and automated HBoV1 antigen test is suitable for diagnosis of acute HBoV1 infection. Study design: HBoV1 antigen detection has been compared with quantitative HBoV1 DNA PCR and HBoV1 mRNA RT-PCR. Results and conclusion: We conclude that HBoV1 antigen detection has higher clinical specificity and positive predictive value than HBoV1 DNA qualitative PCRs, yet a lower sensitivity than HBoV1 mRNA detection. Additionally, HBoV1 antigen detection is beneficial in its rapidity and availability as a point-of-care test.Peer reviewe