Search

Histochemical staining and DNA manipulations help target an enhancer trap of the p element alleles vg(lacZ1) to the S-1 region of the vestigial gene (vg+) that is essential for the formation of wings. The allele has high mutant phenotypic characteristics and contains high level haltere expression of beta-galactosidase in the dorsal wing surface. This targeting process of the p elements is applicable to genes that have low primary p element insertion rates.

A principal component analysis (PCA) and artificial neural network (ANN) based chemistry tabulation approach is presented. ANNs are used to map the thermochemical state onto a low-dimensional manifold consisting of five control variables that have been identified using PCA. Three canonical configurations are considered to train the PCA-ANN model: a series of homogeneous reactors, a nonpremixed flamelet, and a two-dimensional lifted flame. The performance of the model in predicting the thermochemical manifold of a spatially-developing turbulent jet flame in diesel engine thermochemical conditions is a priori evaluated using direct numerical simulation (DNS) data. The PCA-ANN approach is compared with a conventional tabulation approach (tabulation using ad hoc defined control variables and linear interpolation). The PCA-ANN model provides higher accuracy and requires several orders of magnitude less memory. These observations indicate that the PCA-ANN model is superior for chemistry tabulation, especially for modelling complex chemistries that present multiple combustion modes as observed in diesel combustion. The performance of the PCA-ANN model is then compared to the optimal estimator, i.e. the conditional mean from the DNS. The results indicate that the PCA-ANN model gives high prediction accuracy, comparable to the optimal estimator, especially for major species and the thermophysical properties. Higher errors are observed for the minor species and reaction rate predictions when compared to the optimal estimator. It is shown that the prediction of minor species and reaction rates can be improved by using training data that exhibits a variation of parameters as observed in the turbulent flame. The output of the ANN is analysed to assess mass conservation. It is observed that the ANN incurs a mean absolute error of 0.05% in mass conservation. Furthermore, it is demonstrated that this error can be reduced by modifying the cost function of the ANN to penalise for deviation from mass conservation. [ABSTRACT FROM AUTHOR]

Abstract We investigate the influence of inflow velocity (V in) and scalar dissipation rate (χ) on the flame structure and stabilisation mechanism of steady, laminar partially premixed n -dodecane edge flames stabilised on a convective mixing layer. Numerical simulations were performed for three different χ profiles and several V in (V in = 0.2 to 2.5m/s). The ambient thermochemical conditions were the same as the Engine Combustion Network's (ECN) Spray A flame, which in turn represents conditions in a typical heavy duty diesel engine. The results of a combustion mode analysis of the simulations indicate that the flame structure and stabilisation mechanism depend on V in and χ. For low V in the flame is attached. Increasing V in causes the high-temperature chemistry (HTC) flame to lift-off, while the low-temperature chemistry (LTC) flame is still attached. A unique speed S R associated with this transition is defined as the velocity at which the lifted height has the maximum sensitivity to changes in V in. This transition velocity is negatively correlated with χ. Near V i n = S R a tetrabrachial flame structure is observed consisting of a triple flame, stabilised by flame propagation into the products of an upstream LTC branch. Further increasing the inlet velocity changes the flame structure to a pentabrachial one, where an additional HTC ignition branch is observed upstream of the triple flame and ignition begins to contribute to the flame stabilisation. At large V in , the LTC is eventually lifted, and the speed at which this transition occurs is insensitive to χ. Further increasing V in increases the contribution of ignition to flame stabilisation until the flame is completely ignition stabilised. Flow divergence caused by the LTC branch reduces the χ at the HTC branches making the HTC more resilient to χ. The results are discussed in the context of identification of possible stabilisation modes in turbulent flames. [ABSTRACT FROM AUTHOR]

Abstract: We examine the combustion of mixed H2-CH4-air fuels using two-dimensional simulations that incorporate detailed kinetics and a mixture-averaged model for differential species transport. The mixtures range from lean H2-air at to lean CH4-air at . For each mixture, we compute the quasi-steady propagation of a flame into flow with superimposed low-level turbulent fluctuations, so that the resulting flames are in the laminar flamelet regime. We examine the resulting global flame characteristics, and quantify how the chemistry depends on local flame curvature. We then examine in more detail how the methane chemistry is modulated by the presence of hydrogen. In particular, we find that the local methane burning speed shows a strong positive correlation with local flame curvature when sufficient hydrogen is added to the mixture. Moreover, for higher hydrogen concentrations, the mixtures exhibit cellular burning patterns that are traditionally associated with thermodiffusively unstable fuel mixtures. Various pathways for the oxidation of methane are identified and are shown to be amplified considerably in the presence of H2 combustion, which varies considerably along the flame surface. [ABSTRACT FROM AUTHOR]

Abstract: Lean premixed hydrogen flames are thermodiffusively unstable and burn in cellular structures. Within these cellular structures the flame is locally enriched by preferential diffusion of hydrogen, leading to local hotspots that burn more intensely than an idealized flat steady flame at comparable inlet conditions. We investigate the impact of this local enrichment on the formation of nitrogen oxides. We consider a two dimensional configuration in which lean premixed hydrogen–air flames interact with a weakly turbulent velocity field for a range of equivalence ratios. The simulations show that although peak temperatures remain well below 1800K (where thermal NO x traditionally is thought to become significant), these localized hot spots lead to significant production of nitric oxides, and the relative enhancement becomes increasingly significant with lower fuel equivalence ratios. A detailed examination of the reaction chemistry in these unsteady flames shows that at richer conditions the predominant path taken to convert nitrogen gas to nitric oxide is via NNH. For leaner flames a path through nitrous oxide becomes increasingly important. [ABSTRACT FROM AUTHOR]

Abstract: Simulations are routinely used to study the process of carbon dioxide (CO2) sequestration in saline aquifers. In this paper, we describe the modeling and simulation of the dissolution–diffusion–convection process based on a total velocity splitting formulation for a variable-density incompressible single-phase model. A second-order accurate sequential algorithm, implemented within a block-structured adaptive mesh refinement (AMR) framework, is used to perform high-resolution studies of the process. We study both the short-term and long-term behaviors of the process. It is found that the onset time of convection follows closely the prediction of linear stability analysis. In addition, the CO2 flux at the top boundary, which gives the rate at which CO2 gas dissolves into a negatively buoyant aqueous phase, will reach a stabilized state at the space and time scales we are interested in. This flux is found to be proportional to permeability, and independent of porosity and effective diffusivity, indicative of a convection-dominated flow. A 3D simulation further shows that the added degrees of freedom shorten the onset time and increase the magnitude of the stabilized CO2 flux by about 25%. Finally, our results are found to be comparable to results obtained from TOUGH2-MP. [Copyright &y& Elsevier]

Abstract: Comparatively little attention has been given to multicomponent diffusion effects in lean hydrogen–air flames, in spite of the importance of these flames in safety and their potential importance to future energy technologies. Prior direct numerical simulations either have considered only the mixture-averaged transport model, or have been limited to stabilized flames that do not exhibit the thermo-diffusive instability. The so-called full, multicomponent transport model with cross-diffusion is found to predict hotter, significantly faster flames with much faster extinction and division of cellular structures. [Copyright &y& Elsevier]

Abstract: A dominant factor in determining the burning rate of a premixed turbulent flame is the degree to which the flame front is wrinkled by turbulence. Higher turbulent intensities lead to greater wrinkling of the flame front and an increase in the turbulent burning rate. This picture of turbulent flame dynamics must be modified, however, to accommodate the affects of variations in the local propagation speed of the flame front. Classical flame analysis characterizes these local variations in propagation speed by the Markstein number which represents the response of the flame front to curvature and strain. In this paper, we consider lean premixed flames for three different fuels having widely varying fuel Lewis numbers corresponding to widely varying Markstein numbers. In particular, we present numerical simulations of premixed turbulent flames for lean hydrogen, propane and methane mixtures in two dimensions. Each simulation is performed at turbulence conditions similar to those found in laboratory-scale experiments and is performed using detailed chemical kinetics and transport properties. We discuss the effect of Lewis number on the overall flame morphology and explore the dependence of local flame propagation speed on flame curvature. We also explore the relationship between local flame speed and experimentally accessible variables such as OH concentration. Finally, we focus on the low Lewis number case, hydrogen, in which the flame front is broken indicating local extinction. [Copyright &y& Elsevier]

Abstract: We present three-dimensional, time-dependent simulations of the flowfield of a laboratory-scale slot burner. The simulations are performed using an adaptive time-dependent low-Mach-number combustion algorithm based on a second-order projection formulation that conserves both species mass and total enthalpy. The methodology incorporates detailed chemical kinetics and a mixture model for differential species diffusion. Methane chemistry and transport are modeled using the DRM-19 (20-species, 84-reaction) mechanism derived from the GRI-Mech 1.2 mechanism along with its associated thermodynamics and transport databases. Adaptive mesh refinement dynamically resolves the flame and turbulent structures. Detailed comparisons with experimental measurements show that the computational results provide a good prediction of the flame height, the shape of the time-averaged parabolic flame surface area, and the global consumption speed (the volume per second of reactants consumed divided by the area of the time-averaged flame). The thickness of the computed flame brush increases in the streamwise direction, and the flame surface density profiles display the same general shapes as the experiment. The structure of the simulated flame also matches the experiment; reaction layers are thin (typically thinner than 1mm) and the wavelengths of large wrinkles are 5–10mm. Wrinkles amplify to become long fingers of reactants which burn through at a neck region, forming isolated pockets of reactants. Thus both the simulated flame and the experiment are in the “corrugated flamelet regime.” The overall turbulent burning velocities of the simulation and experiment were, respectively, 2.45 and 2.55 times the laminar flame speed. [Copyright &y& Elsevier]

Abstract: Ammonia often occurs in combustion gases as a product of fuel-nitrogen. Since either NO or N2 may predominate as the product of ammonia oxidation, there is considerable interest in understanding the factors responsible for selecting the final products. In flames, the selectivity is known to depend on whether the reaction zones are premixed or nonpremixed. This paper reports on a combined experimental and modeling investigation of ammonia chemistry in a hot combustion environment that is below flame temperatures, such as in post-combustion gases. Experiments that mix highly diluted ammonia–methane and oxygen–water streams are interpreted in terms of a plug-flow model, a simplified mixing reactor model, and a two-dimensional direct numerical simulation. The study finds that the final products of ammonia oxidation remain sensitive to mixing even at temperatures below those of self-sustaining flames. At low temperatures, ammonia oxidation occurs in a premixed reaction zone, but at sufficiently high temperatures a nonpremixed reaction zone may develop that produces significantly less NO than the equivalent premixed system. A direct numerical simulation is required to predict the behavior over the full range of conditions investigated experimentally, while a simplified mixing reactor model captures the essential features as long as the radial gradients are not too steep. [Copyright &y& Elsevier]

The Drosophila homologue of the human TEF-1 gene, scalloped (sd), is required for wing development. The SD protein forms part of a transcriptional activation complex with the protein encoded by vestigial (vg) that, in turn, activates target genes important for wing formation. One sd function involves a regulatory feedback loop with vg and wingless (wg) that is essential in this process. The dorsal–ventral (D/V) margin-specific expression of wg is lost in sd mutant wing discs while the hinge-specific expression appears normal. In the context of wing development, a vg::sdTEA domain fusion produces a protein that mimics the wild-type SD/VG complex and restores the D/V boundary-specific expression of wg in a sd mutant background. Further, targeted expression of wg at the D/V boundary in the wing disc was able to partially rescue the sd mutant phenotype. This infers that sd could function in either the maintenance or induction of wg at the D/V border. Another functional role for sd is the establishment of sensory organ precursors (SOP) of the peripheral nervous system at the wing margin. Thus, the relationship between sd and senseless (sens) in the development of these cells is also examined, and it appears that sd must be functional for proper sens expression, and ultimately, for sensory organ precursor development. [Copyright &y& Elsevier]

A new algorithm is developed to tackle the issue of sampling non-Gaussian model parameter posterior probability distributions that arise from solutions to Bayesian inverse problems. The algorithm aims to mitigate some of the hurdles faced by traditional Markov Chain Monte Carlo (MCMC) samplers, through constructing proposal probability densities that are both, easy to sample and that provide a better approximation to the target density than a simple Gaussian proposal distribution would. To achieve that, a Gaussian proposal distribution is augmented with a Gaussian Process (GP) surface that helps capture non-linearities in the log-likelihood function. In order to train the GP surface, an iterative approach is adopted for the optimal selection of points in parameter space. Optimality is sought by maximizing the information gain of the GP surface using a minimum number of forward model simulation runs. The accuracy of the GP-augmented surface approximation is assessed in two ways. The first consists of comparing predictions obtained from the approximate surface with those obtained through running the actual simulation model at hold-out points in parameter space. The second consists of a measure based on the relative variance of sample weights obtained from sampling the approximate posterior probability distribution of the model parameters. The efficacy of this new algorithm is tested on inferring reaction rate parameters in a 3-node and 6-node network toy problems, which imitate idealized reaction networks in combustion applications. • An adaptive emulator is built using Gaussian process regression. • An acquisition function is derived for optimal training of the emulator. • MCMC sampler is used to optimize the acquisition function. • Emulator is used to reduce computational cost of a Bayesian inverse problem. [ABSTRACT FROM AUTHOR]

We present results from a three-dimensional (3D) direct numerical simulation (DNS) of a spatially developing n -dodecane round jet flame. The thermochemical conditions (i.e. pressure, temperature and oxidiser composition) correspond to those of Spray A, an experimental target flame of the Engine Combustion Network (ECN). To make the DNS computationally tractable, we consider a gas jet with a reduced Reynolds number of 17,000 and a shorter lifted length of 11 times the jet diameter. The flame structure and stabilisation mechanism of the statistically steady jet flame are discussed. Overall the flame structure is similar to that identified from experimental observations, i.e. a region of high formaldehyde (CH 2 O) concentration, which marks the low-temperature chemistry (LTC), is present upstream of the main flame and persists downstream in the central region of the jet where the mixture is rich. A high-temperature (HTC) nonpremixed flame marked by OH radicals shrouds the jet. Ignition kernels are observed upstream of the flame base, some of which are convected downstream and join with the main flame. At the flame base, a three-branch structure is observed, namely an LTC branch upstream of the flame, a rich HTC branch attached to the flame base and a trailing nonpremixed flame anchored at the stoichiometric mixture fraction. A detailed analysis of the flame stabilisation mechanism is reported, employing structural comparisons to two-dimensional (2D) reference cases, transport budgets, and flame speeds. It is concluded from these analyses that the flame is stabilised principally by flame propagation. The role of autoignition kernels is also analysed and found to be secondary. [ABSTRACT FROM AUTHOR]

• MFIX-Exa is a modern, massively parallel, CFD-DEM code. • MFIX-Exa aids the design of new carbon capture and storage technologies. • MFIX-Exa to be performant on current and next generation supercomputers. • MFIX-Exa solves thermodynamics and chemical reactions for gas–solid multiphase flows. • MFIX-Exa's CFD-DEM approach is accurate and cost-efficient. MFIX-Exa is a CFD-DEM code for the numerical solution of chemically reacting multiphase flows (fluid and solids phases), specifically targeted for flows in complex reactor geometries. The fluid is modeled using a low Mach number formulation with a multicomponent ideal gas equation of state, which is imposed as a constraint of the velocity field. The fluid equations are discretized using an embedded boundary (EB) aware Godunov scheme with an approximate projection. The particles (that constitute the solids phase) are represented by a soft-sphere spring-dashpot model and evolved using a forward Euler method with subcycling. The fluid and particles models are coupled through a volume fraction field in addition to interphase mass, momentum, and energy transfer. The mathematical model and numerical approach are benchmarked against three different verification tests and validated with two separate tests. Also, a scaling analysis is provided. This manuscript represents the current state-of-the-art of MFIX-Exa and describes the major extensions to the previous work presented in Musser et al. (2021) , including the Godunov time integration algorithm for the fluid phase and the inclusion of thermodynamics and chemistry modeling to both the fluid and solids phases. [ABSTRACT FROM AUTHOR]

This paper reports on a combined experimental and modeling investigation of NOx formation in laminar, ammonia-seeded, nitrogen-diluted, methane diffusion flames. The methane-ammonia mixture is a surrogate for biomass fuels, which contain significant fuel-bound nitrogen. The experiments use flue-gas sampling to measure the concentration of stable species in the exhaust gas. The computations use adaptive mesh refinement (AMR) to capture fine-scale features of the flame. The model includes a detailed chemical mechanism, differential diffusion, buoyancy, and radiative losses. The model shows good agreement with the measurements over the full range of experimental NH3 seeding amounts. As more NH3 is added, a greater percentage is converted to N2 rather than to NO. The simulation results are analyzed to trace the changes in NO formation mechanisms with increasing amounts of ammonia in the fuel. [Copyright &y& Elsevier]