A comparative study of different reaction models for turbulent methane/hydrogen/air combustion

Reaction modelling of methane/hydrogen combustion has two important aspects. First, such mixtures may be used in future in combustion devices like gas turbines and gas engines in the frame of the demand for efficient energy storage systems, where the amount of hydrogen in natural gas delivering systems may vary according to varying hydrogen production from renewable energies. Second, this can be an important aspect for safety, as such mixtures may occur in disastrous situations and calculations may allow the prediction of safety issues. Modelling of such mixed fuel combustion processes is non-trivial due to the involved preferential diffusion effects, coming from the different diffusivities of methane and hydrogen. In turbulent flame modelling, this topic is of special interest, as also thermo-diffusive instabilities and local influence of the local burning velocity near leading edges of the flame seem to be of importance even for highly turbulent flames. This numerical work deals therefore with a comparative study of five different turbulent combustion models - Bray-Moss-Libby, Linstedt-Vaos (LV), a modified version LV, Turbulent Flamespeed Closure, and Algebraic Flame Surface Wrinkling model - to the situation of turbulent methane/hydrogen/air flames. Validation is done with extensive experimental data obtained by a low swirl burner in the group by Cheng. Besides a basic case with pure methane/air, special emphasis is laid on flames with 40 to 100 % hydrogen content by volume. It is shown that for such methane/hydrogen fuel mixtures common reaction rate models are not sufficient where the fuel effects are included only via a laminar flame speed. Instead, a recently proposed reaction model with the incorporation of an effective Lewis number of the fuel mixture is found to work rather well. This is of both, practical as well as theoretical importance, as for the latter it confirms controversially discussed assumptions of the influence of preferential diffusion

Survival and physiological responses of hatchling Blanding's turtles (Emydoidea blandingii) to submergence in normoxic and hypoxic water under simulated winter conditions.

Abstract Overwintering habits of hatchling Blanding’s turtles (Emydoidea blandingii) are unknown. To determine whether these turtles are able to survive winter in aquatic habitats, we submerged hatchlings in normoxic (155 mmHg Po2) and hypoxic (6 mmHg Po2) water at 4°C, recording survival times and measuring changes in key physiological variables. For comparison, we simultaneously studied hatchling softshell (Apalone spinifera) and snapping (Chelydra serpentina) turtles, which are known to overwinter in aquatic habitats. In normoxic water, C. serpentina and A. spinifera survived to the termination of the experiment (76 and 77 d, respectively). Approximately one‐third of the E. blandingii died during 75 d of normoxic submergence, but the cause of mortality was unclear. In hypoxic water, average survival times were 6 d for A. spinifera, 13 d for E. blandingii, and 19 d for C. serpentina. Mortality during hypoxic submergence was probably caused by metabolic acidosis, which resulted from accumulated lactate. Unlike the case with adult turtles, our hatchlings did not increase plasma calcium and magnesium, nor did they sequester lactate within the shell. Our results suggest that hatchling E. blandingii are not particularly well suited to hibernation in hypoxic aquatic habitats

Physiological Ecology of Overwintering in the Hatchling Painted Turtle: Multiple-Scale Variation in response to Environmental Stress

We integrates field and laboratory studies in an investigation of water balance, energy use, and mechanisms of cold-hardiness in hatchling painted turtles (Chrysemys picta) indigenous to west-central Nebraska (Chrysemys picta bellii) and northern Indiana (Chrysemys picta marginata) during the winters of 1999-2000 and 2000-2001. We examined 184 nests, 80 of which provided the hatchlings (n=580) and or samples of soil used in laboratory analysis. Whereas winter 1999-2000 was relatively dry and mild, the following winter was wet and cold; serendipitously, the contrast illuminated a marked plasticity in physiological response to environmental stress. Physiological and cold‐hardiness responses of turtles also varied between study locales, largely owing to differences in precipitation and edaphics and the lower prevailing and minimum nest temperatures (to −13.2°C) encountered by Nebraska turtles. In Nebraska, winter mortality occurred within 12.5% (1999–2000) and 42.3% (2000–2001) of the sampled nests; no turtles died in the Indiana nests. Laboratory studies of the mechanisms of cold‐hardiness used by hatchling C. picta showed that resistance to inoculative freezing and capacity for freeze tolerance increased as winter approached. However, the level of inoculation resistance strongly depended on the physical characteristics of nest soil, as well as its moisture content, which varied seasonally. Risk of inoculative freezing (and mortality) was greatest in midwinter when nest temperatures were lowest and soil moisture and activity of constituent organic ice nuclei were highest. Water balance in overwintering hatchlings was closely linked to dynamics of precipitation and soil moisture, whereas energy use and the size of the energy reserve available to hatchlings in spring depended on the winter thermal regime. Acute chilling resulted in hyperglycemia and hyperlactemia, which persisted throughout winter; this response may be cryoprotective. Some physiological characteristics and cold‐hardiness attributes varied between years, between study sites, among nests at the same site, and among siblings sharing nests. Such variation may reflect adaptive phenotypic plasticity, maternal or paternal influence on an individual’s response to environmental challenge, or a combination of these factors. Some evidence suggests that life‐history traits, such as clutch size and body size, have been shaped by constraints imposed by the harsh winter environment

DI Diesel Engine Combustion Visualized by Combined Laser Techniques

In this work we demonstrate that the progress of the combustionccycle in a four-cylinder (in-line) 1.9 1 direct injection Diesel engine can be studied effectively using different laser visualization techniques. Direct optical access to the piston bowl was facilitated by inserting quartz windows in one of the pistons. The flow field at the time of injection was characterized by seeding the flow and illuminating the piston bowl with a laser light sheet. Fuel spray development, auto-ignition and flame propagation in a Diesel cycle were followed by laser shadowgraphy and high speed cinematography while simultaneous laser induced fluorescence (LIF) and Mie scattering images were taken to distinguish the fuel distribution in the liquid and vapor phase. In addition, two dimensional distributions of OH and NO, formed during n-heptane/air combustion in the same engine, were recorded in the pressure range 5 to 50 bar by LIF following narrowband excitation using tunable excimer lasers. Finally, further work, designed to obtain quantitative images and hence data for comparison with model calculations, is outlined.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86790/1/Sick50.pd

Changes in PM2.5 concentrations and their sources in the US from 1990 to 2010

Significant reductions in emissions of SO2, NOx, volatile organic compounds (VOCs), and primary particulate matter (PM) took place in the US from 1990 to 2010. We evaluate here our understanding of the links between these emissions changes and corresponding changes in concentrations and health outcomes using a chemical transport model, the Particulate Matter Comprehensive Air Quality Model with Extensions (PMCAMx), for 1990, 2001, and 2010. The use of the Particle Source Apportionment Algorithm (PSAT) allows us to link the concentration reductions to the sources of the corresponding primary and secondary PM. The reductions in SO2 emissions (64 %, mainly from electric-generating units) during these 20 years have dominated the reductions in PM2.5, leading to a 45 % reduction in sulfate levels. The predicted sulfate reductions are in excellent agreement with the available measurements. Also, the reductions in elemental carbon (EC) emissions (mainly from transportation) have led to a 30 % reduction in EC concentrations. The most important source of organic aerosol (OA) through the years according to PMCAMx is biomass burning, followed by biogenic secondary organic aerosol (SOA). OA from on-road transport has been reduced by more than a factor of 3. On the other hand, changes in biomass burning OA and biogenic SOA have been modest. In 1990, about half of the US population was exposed to annual average PM2.5 concentrations above 20 µg m−3, but by 2010 this fraction had dropped to practically zero. The predicted changes in concentrations are evaluated against the observed changes for 1990, 2001, and 2010 in order to understand whether the model represents reasonably well the corresponding processes caused by the changes in emissions.This work was supported by the Center for Air, Climate, and Energy Solutions (CACES), which was supported under assistance agreement no. R835873 awarded by the U.S. Environmental Protection Agency and the Horizon-2020 Project REMEDIA of the European Union under grant agreement no. 874753.Peer ReviewedPostprint (published version

Evaluation of high-resolution predictions of fine particulate matter and its composition in an urban area using PMCAMx-v2.0

Accurately predicting urban PM2.5 concentrations and composition has proved challenging in the past, partially due to the resolution limitations of computationally intensive chemical transport models (CTMs). Increasing the resolution of PM2.5 predictions is desired to support emissions control policy development and address issues related to environmental justice. A nested grid approach using the CTM PMCAMx-v2.0 was used to predict PM2.5 at increasing resolutions of 36 km × 36 km, 12 km × 12 km, 4 km × 4 km, and 1 km × 1 km for a domain largely consisting of Allegheny County and the city of Pittsburgh in southwestern Pennsylvania, US, during February and July 2017. Performance of the model in reproducing PM2.5 concentrations and composition was evaluated at the finest scale using measurements from regulatory sites as well as a network of low-cost monitors. Novel surrogates were developed to allocate emissions from cooking and on-road traffic sources to the 1 km × 1 km resolution grid. Total PM2.5 mass is reproduced well by the model during the winter period with low fractional error (0.3) and fractional bias (+0.05) when compared to regulatory measurements. Comparison with speciated measurements during this period identified small underpredictions of PM2.5 sulfate, elemental carbon (EC), and organic aerosol (OA) offset by a larger overprediction of PM2.5 nitrate. In the summer period, total PM2.5 mass is underpredicted due to a large underprediction of OA (bias = −1.9 µg m−3, fractional bias = −0.41). In the winter period, the model performs well in reproducing the variability between urban measurements and rural measurements of local pollutants such as EC and OA. This effect is less consistent in the summer period due to a larger fraction of long-range-transported OA. Comparison with total PM2.5 concentration measurements from low-cost sensors showed improvements in performance with increasing resolution. Inconsistencies in PM2.5 nitrate predictions in both periods are believed to be due to errors in partitioning between PM2.5 and PM10 modes and motivate improvements to the treatment of dust particles within the model. The underprediction of summer OA would likely be improved by updates to biogenic secondary organic aerosol (SOA) chemistry within the model, which would result in an increase of long-range transport SOA seen in the inner modeling domain. These improvements are obvious topics for future work towards model improvement. Comparison with regulatory monitors showed that increasing resolution from 36 to 1 km improved both fractional error and fractional bias in both modeling periods. Improvements at all types of measurement locations indicated an improved ability of the model to reproduce urban–rural PM2.5 gradients at higher resolutions.</p

Static Friction Phenomena in Granular Materials: Coulomb Law vs. Particle Geometry

The static as well as the dynamic behaviour of granular material are determined by dynamic {\it and} static friction. There are well known methods to include static friction in molecular dynamics simulations using scarcely understood forces. We propose an Ansatz based on the geometrical shape of nonspherical particles which does not involve an explicit expression for static friction. It is shown that the simulations based on this model are close to experimental results.Comment: 11 pages, Revtex, HLRZ-33/9

Typing and Species Identification of Clinical Klebsiella Isolates by Fourier Transform Infrared Spectroscopy and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

Klebsiella pneumoniae and related species are frequent causes of nosocomial infections and outbreaks. Therefore, quick and reliable strain typing is crucial for the detection of transmission routes in the hospital. The aim of this study was to evaluate Fourier transform infrared spectroscopy (FTIR) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) as rapid methods for typing clinical Klebsiella isolates in comparison to whole-genome sequencing (WGS), which was considered the gold standard for typing and identification. Here, 68 clinical Klebsiella strains were analyzed by WGS, FTIR, and MALDI-TOF MS. FTIR showed high discriminatory power in comparison to the WGS reference, whereas MALDI-TOF MS exhibited a low ability to type the isolates. MALDI-TOF mass spectra were further analyzed for peaks that showed high specificity for different Klebsiella species. Phylogenetic analysis revealed that the Klebsiella isolates comprised three different species: K. pneumoniae, K. variicola, and K. quasipneumoniae. Genome analysis showed that MALDI-TOF MS can be used to distinguish K. pneumoniae from K. variicola due to shifts of certain mass peaks. The peaks were tentatively identified as three ribosomal proteins (S15p, L28p, L31p) and one stress response protein (YjbJ), which exhibit amino acid differences between the two species. Overall, FTIR has high discriminatory power to recognize the clonal relationship of isolates, thus representing a valuable tool for rapid outbreak analysis and for the detection of transmission events due to fast turnaround times and low costs per sample. Furthermore, specific amino acid substitutions allow the discrimination of K. pneumoniae and K. variicola by MALDI-TOF MS

Safety of Levetiracetam in paediatrics: a systematic review

Objective To identify adverse events (AEs) associated with Levetiracetam (LEV) in children. Methods Databases EMBASE (1974-February 2015) and Medline (1946-February 2015) were searched for articles in which paediatric patients (≤18 years) received LEV treatment for epilepsy. All studies with reports on safety were included. Studies involving adults, mixed age population (i.e. children and adults) in which the paediatric subpopulation was not sufficiently described, were excluded. A meta-analysis of the RCTs was carried out and association between the commonly reported AEs or treatment discontinuation and the type of regimen (polytherapy or monotherapy) was determined using Chi2 analysis. Results Sixty seven articles involving 3,174 paediatric patients were identified. A total of 1,913 AEs were reported across studies. The most common AEs were behavioural problems and somnolence, which accounted for 10.9% and 8.4% of all AEs in prospective studies. 21 prospective studies involving 1120 children stated the number of children experiencing AEs. 47% of these children experienced AEs. Significantly more children experienced AEs with polytherapy (64%) than monotherapy (22%) (p<0.001). Levetiracetam was discontinued in 4.5% of all children on polytherapy and 0.9% on monotherapy (p<0.001), the majority were due to behavioural problems. Conclusion Behavioural problems and somnolence were the most prevalent adverse events to LEV and the most common causes of treatment discontinuation. Children on polytherapy have a greater risk of adverse events than those receiving monotherapy

Deficits in Long-Term Recognition Memory Reveal Dissociated Subtypes in Congenital Prosopagnosia

The study investigates long-term recognition memory in congenital prosopagnosia (CP), a lifelong impairment in face identification that is present from birth. Previous investigations of processing deficits in CP have mostly relied on short-term recognition tests to estimate the scope and severity of individual deficits. We firstly report on a controlled test of long-term (one year) recognition memory for faces and objects conducted with a large group of participants with CP. Long-term recognition memory is significantly impaired in eight CP participants (CPs). In all but one case, this deficit was selective to faces and didn't extend to intra-class recognition of object stimuli. In a test of famous face recognition, long-term recognition deficits were less pronounced, even after accounting for differences in media consumption between controls and CPs. Secondly, we combined test results on long-term and short-term recognition of faces and objects, and found a large heterogeneity in severity and scope of individual deficits. Analysis of the observed heterogeneity revealed a dissociation of CP into subtypes with a homogeneous phenotypical profile. Thirdly, we found that among CPs self-assessment of real-life difficulties, based on a standardized questionnaire, and experimentally assessed face recognition deficits are strongly correlated. Our results demonstrate that controlled tests of long-term recognition memory are needed to fully assess face recognition deficits in CP. Based on controlled and comprehensive experimental testing, CP can be dissociated into subtypes with a homogeneous phenotypical profile. The CP subtypes identified align with those found in prosopagnosia caused by cortical lesions; they can be interpreted with respect to a hierarchical neural system for face perception