Numerical study on combustion of H2—O2 in a supersonic reactive expansion in a nozzle

A study on expansion flow inside a nozzle considering full mechanism chemistry of hydrogen and oxygen was carried out. In this study, a full implicit scheme for turbulent reactive flow was obtained by combining the second order TVD scheme of Yee and Harten (1987, Implicit TVD schemes for hyperbolic conservation laws in curvilinear coordinates. American Institute of Aeronautics and Astronautics Journal, 25(2), 266–274) with the efficient implicit lower-upper scheme of Shuen and Yoon (1989, Numerical study of chemically reacting flows using a lower-upper symmetric successive overrelaxation scheme. American Institute of Aeronautics and Astronautics Journal, 27(12), 1752–1756). The species equations, Navier–Stokes equations and turbulence model were implemented in the numerical scheme and solved in conjunction with full detailed finite rate chemistry. The numerical scheme is verified by comparison with experimental results of a converging–diverging nozzle. Effects of inlet pressure, temperature and fuel-oxidant mass ratio on nozzle flow field were studied. Variation of chemical species under different conditions was investigated by considering a chemical mechanism. Results show that increasing inlet pressure increases the rate of reactions due to increasing the concentration of reactants. For lower inlet pressure the radical H increases slightly in the diverging part of the nozzle, while for higher pressures it decreases along the nozzle. Inlet fuel–oxidant mass ratio affects the variation of all species with a greater effect for a near stoichiometric ratio. It was also shown that a higher inlet temperature provides a more enhanced reaction zone in the diverging part of the nozzle.     

Application of Sol–Gel Based Poly(ethylene glycol)/Multiwalled Carbon Nanotubes Coated Fiber for SPME of Methyl tert-Butyl Ether in Environmental Water Samples

In this research, the sol–gel technology was applied for the preparation of solid-phase microextraction fibers for extracting of methyl tert-butyl ether (MTBE) from environmental water samples. For this purpose, two different polymers such as poly(ethylene glycol) (PEG) and combination of PEG and multiwall carbon nanotubes (MWCNTs) were prepared using sol–gel technology as coating procedure for the fibers. The pre-concentration process followed by GC–FID determination was used and the results evidenced that pre-concentration factor for PEG/CNTs fiber was approximately five times higher than PEG. Parameters affecting the extraction efficiency such as temperature, extraction time, stirring speed and salt effect for each fiber were investigated and optimized. On the optimal conditions, the linear range for MTBE with PEG and PEG/CNT fibers were 10–3,000 and 1–1,000 ng mL^?1 and the detection limits (S/N = 3) were 1.0 and 0.3 ng mL^?1, respectively. The sol–gel PEG/CNTs fiber has good performance and therefore relatively better figures of merit and experimental results such as thermal stability (up to 320 °C), average of life time (over 150 times) and repeatability (RSD < 4) in comparison to conventional PDMS/Carboxen fiber, which was already reported for determination of MTBE.     

An ultra-fast all-optical RS flip-flop based on nonlinear photonic crystal structures

In this paper, an all-optical RS flip-flop was proposed using nonlinear Kerr effect in photonic crystals. The proposed structure is composed of a core section and two optical switches. The core section consists of two cross-connected resonant cavities whose resonant mode are at wavelengths 1586 and 1620 nm. The cavities were designed such that the resonance of one cavity prevents the signal coupling through the other one. For designing the switch sections, a bias port was used to keep data when there is no input for the flip-flop. Therefore, when both input ports are inactive, the previous state of the flip-flop will be kept. Total footprint and maximum frequency of the proposed structure are obtained 361 μm² and 320 GHz, respectively.     

Synthesis and Simulation Study of Right Silver Bipyramids via Seed-Mediated Growth cum Selective Oxidative Etching Approach

In this study, a simple method to synthesize right silver bipyramid (AgBP) nanostructures via the seed-mediated growth cum oxidative etching approach in aqueous solution is developed. The key strategy of this method is to control the growth and etching process by careful adjustment of the reactants concentration. Ascorbic acid (AA) is used to reduce silver precursor while cetyltrimethylammonium bromide stabilizer is used to direct the preferential growth of (100) facets. The presence of Cu²⁺ and AA in the reaction mixture also enable in-situ generation of H₂O₂, leading to selective etching of (111) facets, which is crucial to the formation of anisotropic AgBPs. The structure-properties of AgBPs is systematically investigated through a series of experiments and theoretical simulations. Transmission electron microscope images and X-ray diffraction patterns of the as-synthesized AgBPs show the formation of single crystalline twined nanostructures with a relatively high yield. These results suggest the important role of the excitation of electric dipole in enhancing the electric field at the six sharp corners of AgBPs, making them especially promising for a wide range of technological applications including surface-enhanced Raman scattering with a significant enhancement factor of 1.50 × 10⁵ as demonstrated herein.     

A new integrated DEA model for finding most BCC-efficient DMU

In many applications of widely recognized technique, DEA, finding the most efficient DMU is desirable for decision maker. Using basic DEA models, decision maker is not able to identify most efficient DMU. Amin and Toloo [Gholam R. Amin, M. Toloo, Finding the most efficient DMUs in DEA: an improved integrated model. Comput. Ind. Eng. 52 (2007) 71–77] introduced an integrated DEA model for finding most CCR-efficient DMU. In this paper, we propose a new integrated model for determining most BCC-efficient DMU by solving only one linear programming (LP). This model is useful for situations in which return to scale is variable, so has wider range of application than other models which find most CCR-efficient DMU. The applicability of the proposed integrated model is illustrated, using a real data set of a case study, which consists of 19 facility layout alternatives.     

Sparse fusion frames: existence and construction

Fusion frame theory is an emerging mathematical theory that provides a natural framework for performing hierarchical data processing. A fusion frame can be regarded as a frame-like collection of subspaces in a Hilbert space, and thereby generalizes the concept of a frame for signal representation. However, when the signal and/or subspace dimensions are large, the decomposition of the signal into its fusion frame measurements through subspace projections typically requires a large number of additions and multiplications, and this makes the decomposition intractable in applications with limited computing budget. To address this problem, in this paper, we introduce the notion of a sparse fusion frame, that is, a fusion frame whose subspaces are generated by orthonormal basis vectors that are sparse in a ‘uniform basis’ over all subspaces, thereby enabling low-complexity fusion frame decompositions. We study the existence and construction of sparse fusion frames, but our focus is on developing simple algorithmic constructions that can easily be adopted in practice to produce sparse fusion frames with desired (given) operators. By a desired (or given) operator we simply mean one that has a desired (or given) set of eigenvalues for the fusion frame operator. We start by presenting a complete characterization of Parseval fusion frames in terms of the existence of special isometries defined on an encompassing Hilbert space. We then introduce two general methodologies to generate new fusion frames from existing ones, namely the Spatial Complement Method and the Naimark Complement Method, and analyze the relationship between the parameters of the original and the new fusion frame. We proceed by establishing existence conditions for 2-sparse fusion frames for any given fusion frame operator, for which the eigenvalues are greater than or equal to two. We then provide an easily implementable algorithm for computing such 2-sparse fusion frames.     

Enhanced Non-enzymatic amperometric sensing of glucose using Co(OH)<Subscript>2</Subscript> nanorods deposited on a three dimensional graphene network as an electrode material

We report on the synthesis of cobalt dihydroxide [Co(OH)₂] nanorods and their deposition on a 3-dimensional graphene network via chemical bath deposition. The structural characterization reveals deposited Co(OH)₂ to consist of flower-like nanorods on a 3-dimensional graphene foam. The nanocomposite was used for glucose sensing by electrocatalytic oxidation of glucose in 1 M KOH solution. Cyclic voltammetry and amperometric studies revealed a high sensitivity for glucose (3.69 mA mM^?1 cm^?2) and a 16 nM detection limit. The nanocomposite offers a large effective surface (11.4 cm²) and is very selective for glucose over potentially interfering materials such as dopamine, ascorbic acid, lactose, fructose and urea, not the least due to a relatively low working potential of 0.6 V (vs. Ag/AgCl). The high sensitivity, low detection limit and very good selectivity of free-standing nanocomposite electrodes are attributed to the synergistic effect of (a) the good electrocatalytic activity of the NRs, and (b) the large surface area with high conductivity offered by the 3D graphene foam.

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Graphical Abstract Cobalt hydroxide [Co(OH)₂] nanorods were deposited on three dimensional graphene (3DG) by a chemical bath deposition method, and the resulting material was used as an electrode for non-enzymatic and specific sensing of glucose in 1 M KOH solution.

     

A rewarding-punishing coordination mechanism based on Trust in a divergent supply chain

Coordination of decentralized supply chains using contract design is a problem that has been widely addressed in the literature. We consider a divergent supply chain including a supplier and several retailers producing fashion products with short sale seasons. The retailers cooperate with the supplier as sales agents; i.e., they work in the framework of revenue sharing contracts. Because of their proximity to the market, retailers can provide more accurate demand forecasts to the supplier that is used to decide on issues such as capacity building and market prices with regard to retailers stiff due dates, different lead times and different price-dependent demand functions. To ensure abundant supply and cope with the demand variability, the retailers have an incentive to exaggerate their private forecast information. In this study, we propose a new rewarding-punishing coordination mechanism based on trust between supply chain tiers, considered as a differentiation factor between honest and deceptive partners. An optimization model is developed as a building block of this mechanism. An approximation method is used to simplify and solve the problem. The model is then implemented using Monte-Carlo simulation in four different situations, according to 10 different strategies for forecast information sharing. The findings from the tests show that the mechanism including trust as a decisional factor performs better than ‘No Trust’ mechanism in all situations. These results suggest that taking into account Trust in designing coordination mechanism may have significant influence on the financial performance of the supply chain.