Experiments and zero D modeling studies using specific Wiebe coefficients for producer gas as fuel in spark-ignited engines

The paper addresses experiments and modeling studies on the use of producer gas, a bio-derived low energy content fuel in a spark-ignited engine. Producer gas, generated in situ, has thermo-physical properties different from those of fossil fuel(s). Experiments on naturally aspirated and turbo-charged engine operation and subsequent analysis of the cylinder pressure traces reveal significant differences in the heat release pattern within the cylinder compared with a typical fossil fuel. The heat release patterns for gasoline and producer gas compare well in the initial 50% but beyond this, producer gas combustion tends to be sluggish leading to an overall increase in the combustion duration. This is rather unexpected considering that producer gas with nearly 20% hydrogen has higher flame speeds than gasoline. The influence of hydrogen on the initial flame kernel development period and the combustion duration and hence on the overall heat release pattern is addressed. The significant deviations in the heat release profiles between conventional fuels and producer gas necessitates the estimation of producer gas-specific Wiebe coefficients. The experimental heat release profiles are used for estimating the Wiebe coefficients. Experimental evidence of lower fuel conversion efficiency based on the chemical and thermal analysis of the engine exhaust gas is used to arrive at the Wiebe coefficients. The efficiency factor a is found to be 2.4 while the shape factor m is estimated at 0.7 for 2% to 90% burn duration. The standard Wiebe coefficients for conventional fuels and fuel-specific coefficients for producer gas are used in a zero D model to predict the performance of a 6-cylinder gas engine under naturally aspirated and turbo-charged conditions. While simulation results with standard Wiebe coefficients result in excessive deviations from the experimental results, excellent match is observed when producer gas-specific coefficients are used. Predictions using the same coefficients on a 3-cylinder gas engine having different geometry and compression ratio(s) indicate close match with the experimental traces highlighting the versatility of the coefficients.

Comprehensive investigations on DNa center dot center dot center dot A (D = H/F) complexes show why `sodium bonding' is not commonly observed

A comprehensive study of D-Na center dot center dot center dot A (D = H/F) complexes has been done using advanced ab initio and atoms in molecule (AIM) theoretical analyses. The correlation between electron density at bond critical point and binding energy gives a distinguishing feature for hydrogen bonding, different from the `electrostatic complexes' formed by LiD and NaD. Moreover, the LiD/NaD dimers have both linear and anti-parallel minima, as expected for electrostatic dipole-dipole interactions. The HF dimer has a quasi-linear minimum and the anti-parallel structure is a saddle point. Clearly, characterizing hydrogen bonding as `nothing but electrostatic interaction between two dipoles' is grossly in error.

A multichannel sampling method for 2-D finite-rate-of-innovation signals

We address the problem of sampling and reconstruction of two-dimensional (2-D) finite-rate-of-innovation (FRI) signals. We propose a three-channel sampling method for efficiently solving the problem. We consider the sampling of a stream of 2-D Dirac impulses and a sum of 2-D unit-step functions. We propose a 2-D causal exponential function as the sampling kernel. By causality in 2-D, we mean that the function has its support restricted to the first quadrant. The advantage of using a multichannel sampling method with causal exponential sampling kernel is that standard annihilating filter or root-finding algorithms are not required. Further, the proposed method has inexpensive hardware implementation and is numerically stable as the number of Dirac impulses increases.

Investigating thermal stability of structural defects and its effect on d(0) ferromagnetism in undoped SnO2

The effect of annealing on structural defects and d(0) ferromagnetism in SnO2 nanoparticles prepared by solution combustion method is investigated. The as-synthesized SnO2 nanoparticles were annealed at 400-800 degrees C for 2 h, in ambient conditions. The crystallinity, size, and morphology of the samples were studied using x-ray diffraction and transmission electron microscopy studies. The annealing results in grain growth due to coarsening as well as reduction in oxygen vacancies as confirmed by Raman spectroscopy, photoluminescence spectroscopy, and x-ray photoelectron spectroscopy. All the as synthesized and annealed samples exhibit room temperature ferromagnetism (RTFM) with distinct hysteresis loops and the saturation magnetization as high as similar to 0.02 emu/g in as-synthesized samples. However, the saturation magnetization is drastically reduced with increasing annealing temperature. Further the presence of singly charged oxygen vacancies (V-o(-) signal at g-value 1.99) is confirmed by electron paramagnetic resonance studies, which also diminish with increasing annealing temperature. The observed diminishing RTFM and simultaneous evidences of diminishing O vacancies clearly indicate that RTFM is driven by defects in oxide lattice and confirms primary role of oxygen vacancies in inducing ferromagnetic ordering in metal oxide semiconductors. The study also provides improved fundamental understanding regarding the ambiguity in the origin of intrinsic RTFM in semiconducting metal oxides and projects their technological application in the field of spintronics. (C) 2013 AIP Publishing LLC.

Crystal growth and nonlinear optical properties of sodium D-isoascorbate monohydrate

Optical quality single crystals of sodium D-isoascorbate monohydrate were grown by a slow cooling technique. The crystal possesses a bulky prismatic morphology. Thermal analyses indicate that the crystals are stable up to 125 degrees C. The optical transmission window ranges from 307 nm to 1450 nm. The principal refractive indices have been measured employing Brewster's angle method. The crystallographic and the principal dielectric axes coincide with each other such that a lies along Z, b along X and c along Y. The optic axis is oriented 58 degrees (at 532 nm) to the crystallographic a axis in the XZ plane and the crystal is negative biaxial. Type 1 and type 2 phase matching curves are generated and experimentally verified. No polarization dependence of the light absorption was observed confirming the validity of Kleinman's symmetry conjecture, leading to a single nonvanishing nonlinear tensor component. According to Hobden's classification the crystal belongs to class 3. The crystal also exhibits second order noncollinear conic sections. The single shot and multiple shot surface laser damage thresholds are determined to be 32.7 GW cm(-2) and 6.5 GW cm(-2) respectively for 1064 nm radiation.

Growth mechanism of ZnO nanostructures for ultra-high piezoelectric d(33) coefficient

A comparative morphological study of different ZnO nanostructures was carried out with different varying process parameters for energy harvesting. Molarity, temperature, growth duration and seed layer were such fundamental controlling parameters. The study brings out an outstanding piezoelectric coefficient (d(33)) of 44.33 pm/V for vertically aligned ZnO nanorod structures, considered as the highest reported d(33) value for any kind of ZnO nanostructures. XRD analysis confirms wurtzite nature of this nanorod structure with 0001] as preferential growth direction. Semiconducting characteristic of nanorods was determined with temperature induced I/V characterization.

Constraining complex aquifer geometry with geophysics (2-D ERT and MRS measurements) for stochastic modelling of groundwater flow

Stochastic modelling is a useful way of simulating complex hard-rock aquifers as hydrological properties (permeability, porosity etc.) can be described using random variables with known statistics. However, very few studies have assessed the influence of topological uncertainty (i.e. the variability of thickness of conductive zones in the aquifer), probably because it is not easy to retrieve accurate statistics of the aquifer geometry, especially in hard rock context. In this paper, we assessed the potential of using geophysical surveys to describe the geometry of a hard rock-aquifer in a stochastic modelling framework. The study site was a small experimental watershed in South India, where the aquifer consisted of a clayey to loamy-sandy zone (regolith) underlain by a conductive fissured rock layer (protolith) and the unweathered gneiss (bedrock) at the bottom. The spatial variability of the thickness of the regolith and fissured layers was estimated by electrical resistivity tomography (ERT) profiles, which were performed along a few cross sections in the watershed. For stochastic analysis using Monte Carlo simulation, the generated random layer thickness was made conditional to the available data from the geophysics. In order to simulate steady state flow in the irregular domain with variable geometry, we used an isoparametric finite element method to discretize the flow equation over an unstructured grid with irregular hexahedral elements. The results indicated that the spatial variability of the layer thickness had a significant effect on reducing the simulated effective steady seepage flux and that using the conditional simulations reduced the uncertainty of the simulated seepage flux. As a conclusion, combining information on the aquifer geometry obtained from geophysical surveys with stochastic modelling is a promising methodology to improve the simulation of groundwater flow in complex hard-rock aquifers. (C) 2013 Elsevier B.V. All rights reserved.

D-A-D-structured conducting polymer-modified electrodes for detection of lead(II) ions in water

Donor-acceptor-donor-structured thiophene derivative-based conducting polymer poly(7,9-dithiophene-2yl-8H-cyclopentaa]acenaphthalene-8-one) was chemically synthesized. This polymer was used to modify both glassy-carbon and carbon-paste electrode, which was used to detect lead(II) ions present in water in the range of 1 mM to 0.1 mu M. Cyclic voltammetry confirms the formation of the co-ordination complex between the soft segment of polymer and the dissolved lead ion. Anodic stripping voltammetry was carried out by the modified electrode to determine the lower limit of detection of dissolved lead(II) species in the solution. Differential adsorptive stripping and impedance measurements were also conducted to find the lowest possible response of the as-synthesized polymer to lead(II) ion in water. The electrochemical performance of the modified electrodes at different pH (4, 7 and 9) environments was carried out by stripping voltammetry, to get optimum sensitivity and stability under these conditions. Finally, interference analysis was carried out to detect the modified electrode's sensitivity towards lead ion affinity in water.

Differential evolution based 3-D guidance law for a realistic interceptor model

This paper presents a novel, soft computing based solution to a complex optimal control or dynamic optimization problem that requires the solution to be available in real-time. The complexities in this problem of optimal guidance of interceptors launched with high initial heading errors include the more involved physics of a three dimensional missile-target engagement, and those posed by the assumption of a realistic dynamic model such as time-varying missile speed, thrust, drag and mass, besides gravity, and upper bound on the lateral acceleration. The classic, pure proportional navigation law is augmented with a polynomial function of the heading error, and the values of the coefficients of the polynomial are determined using differential evolution (DE). The performance of the proposed DE enhanced guidance law is compared against the existing conventional laws in the literature, on the criteria of time and energy optimality, peak lateral acceleration demanded, terminal speed and robustness to unanticipated target maneuvers, to illustrate the superiority of the proposed law. (C) 2013 Elsevier B. V. All rights reserved.

On 2-D Non-Adjacent-Error Channel Models

In this work, we consider two-dimensional (2-D) binary channels in which the 2-D error patterns are constrained so that errors cannot occur in adjacent horizontal or vertical positions. We consider probabilistic and combinatorial models for such channels. A probabilistic model is obtained from a 2-D random field defined by Roth, Siegel and Wolf (2001). Based on the conjectured ergodicity of this random field, we obtain an expression for the capacity of the 2-D non-adjacent-errors channel. We also derive an upper bound for the asymptotic coding rate in the combinatorial model.

Influence of exhaust gas heating and L/D ratios on the discharge efficiencies for an activated carbon natural gas storage system

A transient 2D axi-symmetric and lumped parameter (LP) model with constant outflow conditions have been developed to study the discharge capacity of an activated carbon bed. The predicted discharge times and variations in bed pressure and temperature are in good agreement with experimental results obtained from a 1.82 l adsorbed natural gas (ANG) storage system. Under ambient air conditions, a maximum temperature drop of 29.5 K and 45.5 K are predicted at the bed center for discharge rates of 1.0 l min(-1) and 5.0 l min(-1) respectively. The corresponding discharge efficiencies are 77% and 71.5% respectively with discharge efficiencies improving with decreasing outflow rates. Increasing the LID ratio from 1.9 to 7.8 had only a marginal increase in the discharge efficiency. Forced convection (exhaust gas) heating had a significant effect on the discharge efficiency, leading to efficiencies as high as 92.8% at a discharge of 1.0 l min(-1) and 88.7% at 5 l min(-1). Our study shows that the LP model can be reliably used to obtain discharge times due to the uniform pressure distributions in the bed. Temperature predictions with the LP model were more accurate at ambient conditions and higher discharge rates, due to greater uniformity in bed temperatures. For the low thermal conductivity carbon porous beds, our study shows that exhaust gas heating can be used as an effective and convenient strategy to improve the discharge characteristics and performance of an ANG system. (C) 2013 Elsevier Ltd. All rights reserved.

Germanane: a Low Effective Mass and High Bandgap 2-D Channel Material for Future FETs

We investigate the electronic properties of Germanane and analyze its importance as 2-D channel material in switching devices. Considering two types of morphologies, namely, chair and boat, we study the real band structure, the effective mass variation, and the complex band structure of unstrained Germanane by density-functional theory. The chair morphology turns out to be a more effective channel material for switching devices than the boat morphology. Furthermore, we study the effect of elastic strain, van der Waals force, and vertical electric field on these band structure properties. Due to its very low effective mass with relatively high-energy bandgap, in comparison with the other 2-D materials, Germanane appears to provide superior performance in switching device applications.

Dense network of O-H ... O and C-H ... O interactions in the solid state structure of n-pentyl-2-chloro-2-deoxy-alpha-D-manno-sept 3-uloside

Single crystal X-ray structural analysis of a septanoside, namely, n-pentyl-2-chloro-2-deoxy sept-3-uloside (1) provides many finer details of the molecular structure, in addition to its preferred twist-chair conformation, namely, (TC3,4)-T-5,6 conformation. Structural analysis reveals a dense network of O-H...O, C-H...O and van der Waals interactions that stabilize interdigitized, planar bi-layer structure of the crystal lattice. (C) 2014 Elsevier Ltd. All rights reserved.

A Stochastic Chemical Dynamic Approach to Correlate Autoimmunity and Optimal Vitamin-D Range

Motivated by several recent experimental observations that vitamin-D could interact with antigen presenting cells (APCs) and T-lymphocyte cells (T-cells) to promote and to regulate different stages of immune response, we developed a coarse grained but general kinetic model in an attempt to capture the role of vitamin-D in immunomodulatory responses. Our kinetic model, developed using the ideas of chemical network theory, leads to a system of nine coupled equations that we solve both by direct and by stochastic (Gillespie) methods. Both the analyses consistently provide detail information on the dependence of immune response to the variation of critical rate parameters. We find that although vitamin-D plays a negligible role in the initial immune response, it exerts a profound influence in the long term, especially in helping the system to achieve a new, stable steady state. The study explores the role of vitamin-D in preserving an observed bistability in the phase diagram (spanned by system parameters) of immune regulation, thus allowing the response to tolerate a wide range of pathogenic stimulation which could help in resisting autoimmune diseases. We also study how vitamin-D affects the time dependent population of dendritic cells that connect between innate and adaptive immune responses. Variations in dose dependent response of anti-inflammatory and pro-inflammatory T-cell populations to vitamin-D correlate well with recent experimental results. Our kinetic model allows for an estimation of the range of optimum level of vitamin-D required for smooth functioning of the immune system and for control of both hyper-regulation and inflammation. Most importantly, the present study reveals that an overdose or toxic level of vitamin-D or any steroid analogue could give rise to too large a tolerant response, leading to an inefficacy in adaptive immune function.

Subexponential Algorithm for d-Cluster Edge Deletion: Exception or Rule?

The correlation clustering problem is a fundamental problem in both theory and practice, and it involves identifying clusters of objects in a data set based on their similarity. A traditional modeling of this question as a graph theoretic problem involves associating vertices with data points and indicating similarity by adjacency. Clusters then correspond to cliques in the graph. The resulting optimization problem, Cluster Editing (and several variants) are very well-studied algorithmically. In many situations, however, translating clusters to cliques can be somewhat restrictive. A more flexible notion would be that of a structure where the vertices are mutually ``not too far apart'', without necessarily being adjacent. One such generalization is realized by structures called s-clubs, which are graphs of diameter at most s. In this work, we study the question of finding a set of at most k edges whose removal leaves us with a graph whose components are s-clubs. Recently, it has been shown that unless Exponential Time Hypothesis fail (ETH) fails Cluster Editing (whose components are 1-clubs) does not admit sub-exponential time algorithm STACS, 2013]. That is, there is no algorithm solving the problem in time 2 degrees((k))n(O(1)). However, surprisingly they show that when the number of cliques in the output graph is restricted to d, then the problem can be solved in time O(2(O(root dk)) + m + n). We show that this sub-exponential time algorithm for the fixed number of cliques is rather an exception than a rule. Our first result shows that assuming the ETH, there is no algorithm solving the s-Club Cluster Edge Deletion problem in time 2 degrees((k))n(O(1)). We show, further, that even the problem of deleting edges to obtain a graph with d s-clubs cannot be solved in time 2 degrees((k))n(O)(1) for any fixed s, d >= 2. This is a radical contrast from the situation established for cliques, where sub-exponential algorithms are known.