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•Synthetic bio-oil produced by mixing model compounds featuring light fractions.•Design of experiments techniques applied to represent wide range of compositions.•Iron oxide with ...additives reduced by vaporized synthetic bio-oils.•Oxidation of metallic iron releases high purity hydrogen.•Effect of composition of liquid, reduction temperature and number of cycles.
High purity hydrogen has been obtained by “steam-iron” process from lighter fractions of synthetic bio-oils of different compositions in a single fixed bed reactor operating cyclically. This process in closely related to chemical looping producing and purifying hydrogen in a single reactor. The feedstock consisted of a blend of four model compounds representing the lighter fractions of a bio-oil. Acetic acid has been chosen as representative of the acidic fraction, hydroxyacetone of the ketonic/aldehydic, methanol of the alcoholic and finally water of the aqueous one. Content of each model compound in the mixture has been fixed by design of experiments techniques according to composition of real bio-oils found in literature. First step involves the reduction of an iron oxide at several temperatures (650–850°C) by the action of a synthetic bio-oil, which catalytically decomposes into gaseous reductive species (mainly hydrogen and carbon monoxide). Solid carbon was also produced and deposited on the surface of the solid. Once the iron oxide is completely reduced, a second step consists in the oxidation of the metallic iron with steam releasing pure hydrogen. Along this reaction, and due to the low oxidation temperature (550°C), carbon deposited in the previous step was not appreciably gasified, letting the released hydrogen be virtually free of carbon monoxide (CO<20ppm). Low proportions of water in the reductive gases have proved to exert a positive effect in the process, diminishing the residual carbon deposited on the solid bed, although decreasing reduction rates. The solid tested along this study, based on an iron oxide with small amounts of alumina and ceria, can produce pure hydrogen following a cyclic process, but exhibits a progressive loss of redox capacity of ca. 3wt% after each cycle.
General relativistic force-free electrodynamics is one possible plasma-limit employed to analyze energetic outflows in which strong magnetic fields are dominant over all inertial phenomena. The ...amazing images of black hole (BH) shadows from the Galactic Center and the M87 galaxy provide a first direct glimpse into the physics of accretion flows in the most extreme environments of the universe. The efficient extraction of energy in the form of collimated outflows or jets from a rotating BH is directly linked to the topology of the surrounding magnetic field. We aim at providing a tool to numerically model the dynamics of such fields in magnetospheres around compact objects, such as BHs and neutron stars. To do so, we probe their role in the formation of high energy phenomena such as magnetar flares and the highly variable teraelectronvolt emission of some active galactic nuclei. In this work, we present numerical strategies capable of modeling fully dynamical force-free magnetospheres of compact astrophysical objects. We provide implementation details and extensive testing of our implementation of general relativistic force-free electrodynamics in Cartesian and spherical coordinates using the infrastructure of the E
INSTEIN
T
OOLKIT
. The employed hyperbolic/parabolic cleaning of numerical errors with full general relativistic compatibility allows for fast advection of numerical errors in dynamical spacetimes. Such fast advection of divergence errors significantly improves the stability of the general relativistic force-free electrodynamics modeling of BH magnetospheres.
Methanation of the CO2 contained in a biogas stream has been experimentally analyzed in a fixed bed reactor with a Ni-Mn catalyst, evaluating the effect of feeding reactants distributed throughout ...the bed. The performance of different feeding configurations (conventional cofeeding and others implying a lateral distribution of one of the reactive streams) has been analyzed for different nominal temperatures T (250–400 ºC) and weight-related space velocities WHSV (47.71–6.63 gCO2 gcat-1 h-1), always keeping a H2: CO2 ratio of 4:1, and a CH4:CO2 ratio of 7:3. For identical WHSV, the lateral biogas distribution (Poly-Biogas feeding configuration) always showed the best results in terms of activity (higher conversion at the same temperature) and selectivity (lower selectivity to CO in iso-conversion). These better results agree with what was observed in a previous work in methanation of CO2 (i.e., without methane in the feed). In that work, CO2 was distributed along the catalytic bed by several lateral feeds (Poly-CO2). When T was kept constant and WHSV was varied, the reactor fed with distributed biogas (Poly-Biogas), again confirmed its higher efficiency and better selectivity for biogas upgrading (i.e., higher CH4 content). Furthermore, by adopting a Poly-Biogas (or poly-CO2) feeding configuration, a more homogeneous temperature profile was achieved along the bed avoiding the severity of hot spots appearance. In contrast, the lateral distribution of hydrogen (Poly-H2) always led to similar or worse results than those for the conventional co-feeding configuration.
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•An alternate way, besides catalysts, to boost performance of CO2 methanation reactors•Proven beneficial influence of side distributed feed on biogas upgrading process•Side feeding of biogas results in enhanced CO2 conversions and selectivities to CH4•Thermal gradients along the bed length can be reduced by distributed feeding
Elliptic partial differential equations (ePDEs) appear in a wide variety of areas of mathematics, physics and engineering. Typically, ePDEs must be solved numerically, which sets an ever growing ...demand for efficient and highly parallel algorithms to tackle their computational solution. The Scheduled Relaxation Jacobi (SRJ) is a promising class of methods, atypical for combining simplicity and efficiency, that has been recently introduced for solving linear Poisson-like ePDEs. The SRJ methodology relies on computing the appropriate parameters of a multilevel approach with the goal of minimizing the number of iterations needed to cut down the residuals below specified tolerances. The efficiency in the reduction of the residual increases with the number of levels employed in the algorithm. Applying the original methodology to compute the algorithm parameters with more than 5 levels notably hinders obtaining optimal SRJ schemes, as the mixed (non-linear) algebraic-differential system of equations from which they result becomes notably stiff. Here we present a new methodology for obtaining the parameters of SRJ schemes that overcomes the limitations of the original algorithm and provide parameters for SRJ schemes with up to 15 levels and resolutions of up to 215 points per dimension, allowing for acceleration factors larger than several hundreds with respect to the Jacobi method for typical resolutions and, in some high resolution cases, close to 1000. Most of the success in finding SRJ optimal schemes with more than 10 levels is based on an analytic reduction of the complexity of the previously mentioned system of equations. Furthermore, we extend the original algorithm to apply it to certain systems of non-linear ePDEs.
•We compute new optimal parameters of the Scheduled Relaxation Jacobi method.•The new parameters are calculated for SRJ schemes with P=6 to P=15 levels.•We reduce the stiffness in the computation of optimal SRJ parameters analytically.•We provide a grid of optimal parameters for different P and numerical resolutions.•We benchmark SRJ methods against other algorithms to solve linear systems.
Production of high purity hydrogen (<50 ppm CO) by steam–iron process (SIP) from a synthetic sweetened biogas has been investigated making use of a natural iron ore containing up to 81 wt% of ...hematite (Fe2O3) as oxygen carrier. The presence of a lab-made catalyst (NiAl2O4 with NiO excess above its stoichiometric composition) was required to carry out the significant transformation of mixtures of methane and carbon dioxide in hydrogen and carbon monoxide by methane dry reforming reaction. Three consecutive sub-stages have been identified along the reduction stage that comprise A) the combustion of CH4 by lattice oxygen of NiO and Fe2O3, B) catalyzed methane dry reforming and C) G–G equilibrium described by the Water-Gas-Shift reaction. Oxidation stages were carried out with steam completing the cycle. Oxidation temperature was always kept constant at 500 °C regardless of the temperature used in the previous reduction to minimize the gasification of eventual carbon deposits formed along the previous reduction stage. The presence of other oxides different from hematite in minor proportions (SiO2, Al2O3, CaO and MgO to name the most significant) confers it an increased thermal resistance against sintering respecting pure hematite at the expense of slowing down the reduction and oxidation rates. A “tailor made” hematite with additives (Al2O3 and CeO2) in minor proportions (2 wt%) has been used to stablish comparisons in performance between natural and synthetic iron oxides. It has been investigated the effect of the reduction temperature, the proportion of methane to carbon dioxide in the feed (CH4:CO2 ratio) and the number of repetitive redox cycles.
•Natural iron ores used as oxygen carriers in steam–iron process.•Steam–iron process (SIP) checked out as way to produce high purity H2 from biogas.•Synthetic biogas simulated with mixtures of different CH4:CO2 ratios.•Reduction model comprises up to three stages according to equilibria between gaseous and solid species.•Minimization of Gibbs free energy and Baur–Glaessner diagrams allow good interpretation for reductions.
The Scheduled Relaxation Jacobi (SRJ) method is an extension of the classical Jacobi iterative method to solve linear systems of equations (Au=b) associated with elliptic problems. It inherits its ...robustness and accelerates its convergence rate computing a set of P relaxation factors that result from a minimization problem. In a typical SRJ scheme, the former set of factors is employed in cycles of M consecutive iterations until a prescribed tolerance is reached. We present the analytic form for the optimal set of relaxation factors for the case in which all of them are strictly different, and find that the resulting algorithm is equivalent to a non-stationary generalized Richardson's method where the matrix of the system of equations is preconditioned multiplying it by D=diag(A). Our method to estimate the weights has the advantage that the explicit computation of the maximum and minimum eigenvalues of the matrix A (or the corresponding iteration matrix of the underlying weighted Jacobi scheme) is replaced by the (much easier) calculation of the maximum and minimum frequencies derived from a von Neumann analysis of the continuous elliptic operator. This set of weights is also the optimal one for the general problem, resulting in the fastest convergence of all possible SRJ schemes for a given grid structure. The amplification factor of the method can be found analytically and allows for the exact estimation of the number of iterations needed to achieve a desired tolerance. We also show that with the set of weights computed for the optimal SRJ scheme for a fixed cycle size it is possible to estimate numerically the optimal value of the parameter ω in the Successive Overrelaxation (SOR) method in some cases. Finally, we demonstrate with practical examples that our method also works very well for Poisson-like problems in which a high-order discretization of the Laplacian operator is employed (e.g., a 9- or 17-points discretization). This is of interest since the former discretizations do not yield consistently ordered A matrices and, hence, the theory of Young cannot be used to predict the optimal value of the SOR parameter. Furthermore, the optimal SRJ schemes deduced here are advantageous over existing SOR implementations for high-order discretizations of the Laplacian operator in as much as they do not need to resort to multi-coloring schemes for their parallel implementation.
In an age of species declines, delineating and discovering biodiversity is critical for both taxonomic accuracy and conservation. In recent years, there has been a movement away from using ...exclusively morphological characters to delineate and describe taxa and an increase in the use of molecular markers to describe diversity or through integrative taxonomy, which employs traditional morphological characters, as well as genetic or other data. Tiger beetles are charismatic, of conservation concern, and much work has been done on the morphological delineation of species and subspecies, but few of these taxa have been tested with genetic analyses. In this study, we tested morphologically based taxonomic hypotheses of polymorphic tiger beetles in the Eunota circumpicta (LaFerté-Sénectère, 1841) species complex using multilocus genomic and mtDNA analyses. We find multiple cryptic species within the previous taxonomic concept of Eunota circumpicta, some of which were historically recognized as subspecies. We found that the mtDNA and genomic datasets did not identify the same taxonomic units and that the mtDNA was most at odds with all other genetic and morphological patterns. Overall, we describe new cryptic diversity, which raises important conservation concerns, and provide a working example for testing species and subspecies validity despite discordant data.
Abstract
Estrus detection in water buffalo is affected by the high incidence of poor manifestation inherent in this animal species. This affected the success rate of Artificial Insemination (AI) and ...Embryo Transfer (ET) due to the failure of perfect timing in AI and embryo-recipient synchrony in ET. While various ways of estrus detection were reported, the accuracy was interfered with by other symptoms that signify the health condition rather than the reproductive status of the animal. This results in a low conception rate and long calving intervals in AI and ET programs. Vaginal Cytology is a simple clinical tool of estrus detection that can also detect the pathological status of the reproductive tract and the perfect time for AI. While this is greatly used in canines, application in large animals was limited. The need to collect the swab from animals in the field and bring the smeared sample for analysis to the laboratory hindered its use and application. Our study, however, showed that by adopting this tool in estrus detection, increase in conception rate and calf production were achieved. A >60.0% cornification with the presence of >10 mm Graafian follicle is enough indicators of the perfect time for AI resulting in 80-100% conception. The development of a water buffalo vaginal chart helped determine the time of estrus. Strategies to adopt this tool for improved livestock reproduction are warranted.
Abstract
Low conception rate, long calving interval, and poor calf production limits the profitability of livestock production keeping food security a concern. In the ASEAN region, artificial ...insemination (AI) remains the most common reproductive biotechnology used for livestock breeding to produce up-graded and genetically superior animals that could address the need for food and income to the rural farming communities. Field technicians play a crucial role in carrying out AI to enhance reproduction especially in the remote areas. While ultrasonography emerged as an efficient tool to check the reproductive organ of animals for efficient reproduction, the cost of the machine hinders its availability and access by Field technicians. Skills on palpation per rectum of the ovarian dynamics and tonicity of the uterus are important assets. This paper discusses the importance of Female Reproductive Organ Monitoring or FROM in the economical and efficient application of AI in the field and enhance livestock reproduction. Strategies to develop the skills of AI practitioners are outlined to come out to skilled technicians who could execute an accurately check the reproductive status of the animals and determine the perfect time to carry out an effective and efficient AI. This method is helpful in determining the timing of AI making the resources, time and efforts of the technicians maximized and livestock production more efficient.
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