927 research outputs found
Application of hybrid binomial Langevin-multiple mapping conditioning method to reacting jet flow
The hybrid binomial Langevin-MMC (Multiple Mapping Conditioning) method combines the advantages of the binomial Langevin and MMC models in a consistent manner to overcome difficulties in each. The binomial Langevin method provides joint velocity-scalar statistics, but the treatment of scalars is complex since specification of the bounds is not trivial. The MMC method is capable of dealing with the mixing of any number of scalars, but it can be difficult to specify coefficients involving averages of the scalars and the introduced reference space. The difficulties are overcome by using the velocity statistics from the binomial Langevin model to obtain the reference variable for MMC and, subsequently, the mixing of MMC scalars is performed in a manner that minimises the difference between the mixture fractions for each submodel. The current work expands past studies of NO conversion in a mixing layer to include a study of the Sandia D Flame in preparation for the application to more complex combustion phenomena. Results compare favourably with experimental data and other models
Hybrid binomial Langevin-multiple mapping conditioning modeling of a reacting mixing layer
A novel, stochastic, hybrid binomial Langevin-multiple mapping conditioning (MMC) modelâthat utilizes the strengths of each componentâhas been developed for inhomogeneous flows. The implementation has the advantage of naturally incorporating velocity-scalar interactions through the binomial Langevin model and using this joint probability density function (PDF) to define a reference variable for the MMC part of the model. The approach has the advantage that the difficulties encountered with the binomial Langevin model in modeling scalars with nonelementary bounds are removed. The formulation of the closure leads to locality in scalar space and permits the use of simple approaches (e.g., the modified Curlâs model) for transport in the reference space. The overall closure was evaluated through application to a chemically reacting mixing layer. The results show encouraging comparisons with experimental data for the first two moments of the PDF and plausible results for higher moments at a relatively modest computational cost
Mixture-fraction based hybrid binomial-langevinâMMC modelling applied to auto-ignition in vitiated flow
A new hybrid binomial LangevinâMMC (Multiple Mapping Conditioning) modelling approach is proposed. The mixture fraction derived from the binomial Langevin model is used to specify the reference variable for MMC. The modified Curlâs model is used to close the stochastic MMC mixing term. The new model is applied to a jet burner with a vitiated co-flow (the 'Cabra burner') with methane as the fuel. The first- and second-order statistics show good agreement with experimental data
The NILE Project â Advances in the Conversion of Lignocellulosic Materials into Ethanol
NILE ("New Improvements for Lignocellulosic Ethanol") was an integrated European project (2005-2010) devoted to the conversion of lignocellulosic raw materials to ethanol. The main objectives were to design novel enzymes suitable for the hydrolysis of cellulose to glucose and new yeast strains able to efficiently converting all the sugars present in lignocellulose into ethanol. The project also included testing these new developments in an integrated pilot plant and evaluating the environmental and socio-economic impacts of implementing lignocellulosic ethanol on a large scale. Two model raw materials â spruce and wheat straw â both preconditioned with similar pretreatments, were used. Several approaches were explored to improve the saccharification of these pretreated raw materials such as searching for new efficient enzymes and enzyme engineering. Various genetic engineering methods were applied to obtain stable xylose- and arabinose-fermenting Saccharomyces cerevisiae strains that tolerate the toxic compounds present in lignocellulosic hydrolysates. The pilot plant was able to treat 2 tons of dry matter per day, and hydrolysis and fermentation could be run successively or simultaneously. A global model integrating the supply chain was used to assess the performance of lignocellulosic ethanol from an economical and environmental perspective. It was found that directed evolution of a specific enzyme of the cellulolytic cocktail produced by the industrial fungus, Trichoderma reesei, and modification of the composition of this cocktail led to improvements of the enzymatic hydrolysis of pretreated raw material. These results, however, were difficult to reproduce at a large scale. A substantial increase in the ethanol conversion yield and in specific ethanol productivity was obtained through a combination of metabolic engineering of yeast strains and fermentation process development. Pilot trials confirmed the good behaviour of the yeast strains in industrial conditions as well as the suitability of lignin residues as fuels. The ethanol cost and the greenhouse gas emissions were highly dependent on the supply chain but the best performing supply chains showed environmental and economic benefits. From a global standpoint, the results showed the necessity for an optimal integration of the process to co-develop all the steps of the process and to test the improvements in a flexible pilot plant, thus allowing the comparison of various configurations and their economic and environmental impacts to be determined. <br> Le projet NILE, acronyme de "New Improvements for Lignocellulosic Ethanol", Ă©tait un projet europĂ©en (2005-2010) consacrĂ© Ă la conversion des matiĂšres premiĂšres lignocellulosiques en Ă©thanol. Ses principaux objectifs Ă©taient de concevoir de nouvelles enzymes adaptĂ©es Ă lâhydrolyse de la cellulose en glucose et de nouvelles souches de levure capables de convertir efficacement tous les sucres prĂ©sents dans la lignocellulose en Ă©thanol. Une autre partie du projet consistait Ă tester ces nouveaux systĂšmes dans une installation pilote et Ă Ă©valuer les impacts environnementaux et socio-Ă©conomiques de la production et utilisation Ă grande Ă©chelle dâĂ©thanol lignocellulosique. Deux matiĂšres premiĂšres modĂšles (lâĂ©picĂ©a et la paille de blĂ©) prĂ©traitĂ©es de façon semblable, ont Ă©tĂ© Ă©tudiĂ©es. DiffĂ©rentes approches ont Ă©tĂ© tentĂ©es pour amĂ©liorer la saccharification de ces matiĂšres premiĂšres, par exemple, la recherche de nouvelles enzymes efficaces ou lâingĂ©nierie dâenzymes. Plusieurs stratĂ©gies dâingĂ©nierie gĂ©nĂ©tique ont Ă©tĂ© utilisĂ©es pour obtenir des souches stables de Saccharomyces cerevisiae capables de fermenter le xylose et lâarabinose, et de tolĂ©rer les composĂ©s toxiques prĂ©sents dans les hydrolysats lignocellulosiques. Lâinstallation pilote pouvait traiter 2 tonnes de matiĂšres sĂšches par jour, et lâhydrolyse et la fermentation pouvaient ĂȘtre menĂ©es successivement ou simultanĂ©ment. Un modĂšle global intĂ©grant la chaĂźne dâapprovisionnement en matiĂšre premiĂšre a servi Ă Ă©valuer les performances Ă©conomiques et environnementales de la production dâĂ©thanol lignocellulosique. LâĂ©volution dirigĂ©e dâune enzyme du cocktail cellulolytique produit par le champignon Trichoderma reesei, et la modification de la composition de ce cocktail amĂ©liorent lâhydrolyse enzymatique des matiĂšres premiĂšres prĂ©traitĂ©es. Cependant, ces rĂ©sultats nâont pu ĂȘtre reproduits Ă grande Ă©chelle. Le rendement de conversion et la productivitĂ© spĂ©cifique en Ă©thanol ont Ă©tĂ© sensiblement augmentĂ©s grĂące Ă lâingĂ©nierie mĂ©tabolique des souches de levure et au dĂ©veloppement dâun procĂ©dĂ© optimal de fermentation. Les essais en pilote ont confirmĂ© le bon comportement de ces souches de levure en conditions industrielles ainsi que la possibilitĂ© dâutiliser les rĂ©sidus riches en lignine comme combustible. Le coĂ»t de production de lâĂ©thanol et le bilan des Ă©missions de gaz Ă effet de serre Ă©taient trĂšs dĂ©pendants des sources dâĂ©nergie utilisĂ©es. Dâun point de vue plus global, les rĂ©sultats ont montrĂ© que lâoptimisation du procĂ©dĂ© nĂ©cessite de codĂ©velopper toutes les Ă©tapes de façon intĂ©grĂ©e et de valider les amĂ©liorations dans une installation pilote, afin notamment de pouvoir comparer diffĂ©rentes configurations et dâen dĂ©terminer les effets sur lâĂ©conomie du procĂ©dĂ© et ses impacts environnementaux
A mixture-fraction-based hybrid binomial Langevin-multiple mapping conditioning model
Generalized Multiple Mapping Conditioning (MMC) allows for the use of any physical quantity to represent the required reference variable provided that it delivers the desired behavior. The binomial Langevin model (BLM) has been shown to predict higher statistical moments with good accuracy. However, joint-scalar modeling for many scalars becomes problematic because scalar bounds must be specified as conditional on other scalars to preserve elemental balances. The resulting volumes in state space become exceptionally complex for realistic problem sizes. In the current work, this central difficulty is avoided by using only velocity and mixture fraction statistics from the BLM with the latter used as the MMC reference variable. The principal advantage of this method is that the implementation of the binomial Langevin mixture fraction is relatively straightforward and provides a direct physical link to MMC. The MMC model is closed using an augmented modified Curl's model where the selection of particle pairs for (turbulent) mixing ensures proximity in reference space and a corresponding closeness in physical space. The method is evaluated for a lifted methane jet flame undergoing auto-ignition in a vitiated coflow. Most of the major features of the flow are well reproduced and found to generally outperform other modeling approaches, including Large Eddy Simulations using simplified treatments of turbulence--chemistry interactions such as unsteady flamelet/progress variable descriptions
Rich methane laminar flames doped with light unsaturated hydrocarbons. Part II: 1,3butadiene
In line with the study presented in the part I of this paper, the structure
of a laminar rich premixed methane flame doped with 1,3-butadiene has been
investigated. The flame contains 20.7% (molar) of methane, 31.4% of oxygen and
3.3% of 1,3-butadiene, corresponding to an equivalence ratio of 1.8, and a
ratio C4H6 / CH4 of 16 %. The flame has been stabilized on a burner at a
pressure of 6.7 kPa using argon as dilutant, with a gas velocity at the burner
of 36 cm/s at 333 K. The temperature ranged from 600 K close to the burner up
to 2150 K. Quantified species included usual methane C0-C2 combustion products
and 1,3-butadiene, but also propyne, allene, propene, propane, 1,2-butadiene,
butynes, vinylacetylene, diacetylene, 1,3-pentadiene, 2-methyl-1,3-butadiene
(isoprene), 1-pentene, 3-methyl-1-butene, benzene and toluene. In order to
model these new results, some improvements have been made to a mechanism
previously developed in our laboratory for the reactions of C3-C4 unsaturated
hydrocarbons. The main reaction pathways of consumption of 1,3-butadiene and of
formation of C6 aromatic species have been derived from flow rate analyses. In
this case, the C4 route to benzene formation plays an important role in
comparison to the C3 pathway
MLVA polymorphism of Salmonella enterica subspecies isolated from humans, animals, and food in Cambodia
<p>Abstract</p> <p>Background</p> <p><it>Salmonella </it>(<it>S</it>.) <it>enterica </it>is the main cause of salmonellosis in humans and animals. The epidemiology of this infection involves large geographical distances, and strains related to an episode of salmonellosis therefore need to be reliably discriminated. Due to the limitations of serotyping, molecular genotyping methods have been developed, including multiple loci variable number of tandem repeats (VNTR) analysis (MLVA). In our study, 11 variable number tandem-repeats markers were selected from the <it>S. enterica </it>Typhimurium LT2 genome to evaluate the genetic diversity of 206 <it>S. enterica </it>strains collected in Cambodia between 2001 and 2007.</p> <p>Findings</p> <p>Thirty one serovars were identified from three sources: humans, animals and food. The markers were able to discriminate all strains from 2 to 17 alleles. Using the genotype phylogeny repartition, MLVA distinguished 107 genotypes clustered into two main groups: <it>S. enterica </it>Typhi and other serovars. Four serovars (Derby, Schwarzengrund, Stanley, and Weltevreden) were dispersed in 2 to 5 phylogenic branches. Allelic variations within <it>S. enterica </it>serovars was represented using the minimum spanning tree. For several genotypes, we identified clonal complexes within the serovars. This finding supports the notion of endemo-epidemic diffusion within animals, food, or humans. Furthermore, a clonal transmission from one source to another was reported. Four markers (STTR3, STTR5, STTR8, and Sal20) presented a high diversity index (DI > 0.80).</p> <p>Conclusions</p> <p>In summary, MLVA can be used in the typing and genetic profiling of a large diversity of <it>S. enterica </it>serovars, as well as determining the epidemiological relationships of the strains with the geography of the area.</p
Variational Transition State Theory-Based Surface Chemistry for the C2H6/H2/O2/Pt System
- âŠ