Flame interactions in turbulent premixed twin V-flames

Multiple flame-flame interactions in premixed combustion are investigated using direct numerical simulations of twin turbulent V-flames for a range of turbulence intensities and length scales. Interactions are identified using a novel automatic feature extraction (AFE) technique, based on data registration using the dual-tree complex wavelet transform. Information on the time, position, and type of interactions, and their influence on the flame area is extracted using AFE. Characteristic length and time scales for the interactions are identified. The effect of interactions on the flame brush is quantified through a global stretch rate, defined as the sum of flamelet stretch and interaction stretch contributions. The effects of each interaction type are discussed. It is found that the magnitude of the fluctuations in flamelet and interaction stretch are comparable, and a qualitative sensitivity to turbulence length scale is found for one interaction type. Implications for modeling are discussed. © 2013 Copyright Taylor and Francis Group, LLC.

The roles of energy and material efficiency in meeting steel industry CO2 targets.

Identifying strategies for reducing greenhouse gas emissions from steel production requires a comprehensive model of the sector but previous work has either failed to consider the whole supply chain or considered only a subset of possible abatement options. In this work, a global mass flow analysis is combined with process emissions intensities to allow forecasts of future steel sector emissions under all abatement options. Scenario analysis shows that global capacity for primary steel production is already near to a peak and that if sectoral emissions are to be reduced by 50% by 2050, the last required blast furnace will be built by 2020. Emissions reduction targets cannot be met by energy and emissions efficiency alone, but deploying material efficiency provides sufficient extra abatement potential.

The price of pain and the value of suffering.

Estimating the financial value of pain informs issues as diverse as the market price of analgesics, the cost-effectiveness of clinical treatments, compensation for injury, and the response to public hazards. Such valuations are assumed to reflect a stable trade-off between relief of discomfort and money. Here, using an auction-based health-market experiment, we show that the price people pay for relief of pain is strongly determined by the local context of the market, that is, by recent intensities of pain or immediately disposable income (but not overall wealth). The absence of a stable valuation metric suggests that the dynamic behavior of health markets is not predictable from the static behavior of individuals. We conclude that the results follow the dynamics of habit-formation models of economic theory, and thus, this study provides the first scientific basis for this type of preference modeling.

Modulation of pain ratings by expectation and uncertainty: Behavioral characteristics and anticipatory neural correlates.

Expectations about the magnitude of impending pain exert a substantial effect on subsequent perception. However, the neural mechanisms that underlie the predictive processes that modulate pain are poorly understood. In a combined behavioral and high-density electrophysiological study we measured anticipatory neural responses to heat stimuli to determine how predictions of pain intensity, and certainty about those predictions, modulate brain activity and subjective pain ratings. Prior to receiving randomized laser heat stimuli at different intensities (low, medium or high) subjects (n=15) viewed cues that either accurately informed them of forthcoming intensity (certain expectation) or not (uncertain expectation). Pain ratings were biased towards prior expectations of either high or low intensity. Anticipatory neural responses increased with expectations of painful vs. non-painful heat intensity, suggesting the presence of neural responses that represent predicted heat stimulus intensity. These anticipatory responses also correlated with the amplitude of the Laser-Evoked Potential (LEP) response to painful stimuli when the intensity was predictable. Source analysis (LORETA) revealed that uncertainty about expected heat intensity involves an anticipatory cortical network commonly associated with attention (left dorsolateral prefrontal, posterior cingulate and bilateral inferior parietal cortices). Relative certainty, however, involves cortical areas previously associated with semantic and prospective memory (left inferior frontal and inferior temporal cortex, and right anterior prefrontal cortex). This suggests that biasing of pain reports and LEPs by expectation involves temporally precise activity in specific cortical networks.

Quantifying the uncertainties in life cycle greenhouse gas emissions for UK wheat ethanol

Biofuels are increasingly promoted worldwide as a means for reducing greenhouse gas (GHG) emissions from transport. However, current regulatory frameworks and most academic life cycle analyses adopt a deterministic approach in determining the GHG intensities of biofuels and thus ignore the inherent risk associated with biofuel production. This study aims to develop a transparent stochastic method for evaluating UK biofuels that determines both the magnitude and uncertainty of GHG intensity on the basis of current industry practices. Using wheat ethanol as a case study, we show that the GHG intensity could span a range of 40-110 gCO2e MJ-1 when land use change (LUC) emissions and various sources of uncertainty are taken into account, as compared with a regulatory default value of 44 gCO2e MJ-1. This suggests that the current deterministic regulatory framework underestimates wheat ethanol GHG intensity and thus may not be effective in evaluating transport fuels. Uncertainties in determining the GHG intensity of UK wheat ethanol include limitations of available data at a localized scale, and significant scientific uncertainty of parameters such as soil N2O and LUC emissions. Biofuel polices should be robust enough to incorporate the currently irreducible uncertainties and flexible enough to be readily revised when better science is available. © 2013 IOP Publishing Ltd.

Liquid fuel visualization using laser-induced fluoresence during cold start

The presence of liquid fuel inside the engine cylinder is believed to be a strong contributor to the high levels of hydrocarbon emissions from spark ignition (SI) engines during the warm-up period. Quantifying and determining the fate of the liquid fuel that enters the cylinder is the first step in understanding the process of emissions formation. This work uses planar laser induced fluorescence (PLIF) to visualize the liquid fuel present in the cylinder. The fluorescing compounds in indolene, and mixtures of iso-octane with dopants of different boiling points (acetone and 3-pentanone) were used to trace the behavior of different volatility components. Images were taken of three different planes through the engine intersecting the intake valve region. A closed valve fuel injection strategy was used, as this is the strategy most commonly used in practice. Background subtraction and masking were both performed to reduce the effect of any spurious fluorescence. The images were analyzed on both a time and crank angle (CA) basis, showing the time of maximum liquid fuel present in the cylinder and the effect of engine events on the inflow of liquid fuel. The results show details of the liquid fuel distribution as it enters the engine as a function of crankangle degree, volatility and location in the cylinder. A. semi-quantitative analysis based on the integration of the image intensities provides additional information on the temporal distribution of the liquid fuel flow. © 1998 Society of Automotive Engineers, Inc.

Statistics of reaction progress variable and mixture fraction gradients from DNS of turbulent partially premixed flames

Statistically planar turbulent partially premixed flames for different initial intensities of decaying turbulence have been simulated for global equivalence ratios = 0.7 and 1.0 using three-dimensional, simplified chemistry-based direct numerical simulations (DNS). The simulation parameters are chosen such that the flames represent the thin reaction zones regime combustion. A random bimodal distribution of equivalence ratio is introduced in the unburned gas ahead of the flame to account for the mixture inhomogeneity. The results suggest that the probability density functions (PDFs) of the mixture fraction gradient magnitude |Δξ| (i.e., P(|Δξ|)) can be reasonably approximated using a log-normal distribution. However, this presumed PDF distribution captures only the qualitative nature of the PDF of the reaction progress variable gradient magnitude |Δc| (i.e., P(|Δc|)). It has been found that a bivariate log-normal distribution does not sufficiently capture the quantitative behavior of the joint PDF of |Δξ| and |Δc| (i.e., P(|Δξ|, |Δc|)), and the agreement with the DNS data has been found to be poor in certain regions of the flame brush, particularly toward the burned gas side of the flame brush. Moreover, the variables |Δξ| and |Δc| show appreciable correlation toward the burned gas side of the flame brush. These findings are corroborated further using a DNS data of a lifted jet flame to study the flame geometry dependence of these statistics. © 2013 Copyright Taylor and Francis Group, LLC.

Dicke superradiance in GaN quantum wells

We numerically modeled the spatio-temporal dynamics of Dicke superradiance in GaN/InGaN heterostructure quantum wells in a ridge waveguide cavity. Model predictions envisage ultrashort pulses of intensities superior to what can be obtained in mode-locked lasers. ©2010 IEEE.

Electron-beam-induced direct etching of graphene

We present electron-beam-induced oxidation of single- and bilayer graphene devices in a low-voltage scanning electron microscope. We show that the injection of oxygen leads to targeted etching at the focal point, enabling us to pattern graphene with a resolution of better than 20 nm. Voltage-contrast imaging, in conjunction with finite-element simulations, explain the secondary-electron intensities and correlate them to the etch profile. © 2013 Elsevier Ltd. All rights reserved.

Phycobilisome-Deficient Strains of Synechocystis sp. PCC 6803 Have Reduced Size and Require Carbon-Limiting Conditions to Exhibit Enhanced Productivity.

Reducing excessive light harvesting in photosynthetic organisms may increase biomass yields by limiting photoinhibition and increasing light penetration in dense cultures. The cyanobacterium Synechocystis sp. PCC 6803 harvests light via the phycobilisome, which consists of an allophycocyanin core and six radiating rods, each with three phycocyanin (PC) discs. Via targeted gene disruption and alterations to the promoter region, three mutants with two (pcpcT→C) and one (ΔCpcC1C2:pcpcT→C) PC discs per rod or lacking PC (olive) were generated. Photoinhibition and chlorophyll levels decreased upon phycobilisome reduction, although greater penetration of white light was observed only in the PC-deficient mutant. In all strains cultured at high cell densities, most light was absorbed by the first 2 cm of the culture. Photosynthesis and respiration rates were also reduced in the ΔCpcC1C2:pcpcT→C and olive mutants. Cell size was smaller in the pcpcT→C and olive strains. Growth and biomass accumulation were similar between the wild-type and pcpcT→C under a variety of conditions. Growth and biomass accumulation of the olive mutant were poorer in carbon-saturated cultures but improved in carbon-limited cultures at higher light intensities, as they did in the ΔCpcC1C2:pcpcT→C mutant. This study shows that one PC disc per rod is sufficient for maximal light harvesting and biomass accumulation, except under conditions of high light and carbon limitation, and two or more are sufficient for maximal oxygen evolution. To our knowledge, this study is the first to measure light penetration in bulk cultures of cyanobacteria and offers important insights into photobioreactor design.

Obtaining the shape of a moving object with a specular surface

This paper addresses the basic problem of recovering the 3D surface of an object that is observed in motion by a single camera and under a static but unknown lighting condition. We propose a method to establish pixelwise correspondence between input images by way of depth search by investigating optimal subsets of intensities rather than employing all the relevant pixel values. The thrust of our algorithm is that it is capable of dealing with specularities which appear on the top of shading variance that is caused due to object motion. This is in terms of both stages of finding sparse point correspondence and dense depth search. We also propose that a linearised image basis can be directly computed by the procudure of finding the correspondence. We illustrate the performance of the theoretical propositions using images of real objects. © 2009. The copyright of this document resides with its authors.

Polarization dependence of double resonant Raman scattering band in bilayer graphene

The polarization dependence of the double resonant Raman scattering (2D) band in bilayer graphene (BLG) is studied as a function of the excitation laser energy. It has been known that the complex shape of the 2D band of BLG can be decomposed into four Lorentzian peaks with different Raman frequency shifts attributable to four individual scattering paths in the energy-momentum space. From our polarization dependence study, however, we reveal that each of the four different peaks is actually doubly degenerate in its scattering channels, i.e., two different scattering paths with similar Raman frequency shifts for each peak. We find theoretically that one of these two paths, ignored for a long time, has a small contribution to their scattering intensities but are critical in understanding their polarization dependences. Because of this, the maximum-to-minimum intensity ratios of the four peaks show a strong dependence on the excitation energy, unlike the case of single-layer graphene (SLG). Our findings thus reveal another interesting aspect of electron-phonon interactions in graphitic systems. © 2014 Elsevier Ltd. All rights reserved.

Doping dependence of the Raman spectrum of defected graphene.

We investigate the evolution of the Raman spectrum of defected graphene as a function of doping. Polymer electrolyte gating allows us to move the Fermi level up to 0.7 eV, as directly monitored by in situ Hall-effect measurements. For a given number of defects, we find that the intensities of the D and D' peaks decrease with increasing doping. We assign this to an increased total scattering rate of the photoexcited electrons and holes, due to the doping-dependent strength of electron-electron scattering. We present a general relation between D peak intensity and defects valid for any doping level.