Sintering behaviour of fluorapatite–silicate composites produced from natural fluorapatite and quartz

In this work, the sintering behaviour of fluorapatite (FAp)–silicate composites prepared by mixing variable amounts of natural quartz (2.5 wt% to 20 wt%) and FAp was studied. The composites were pressureless sintered in air at temperatures from 1000 °C to 1350 °C. The effects of temperatures on the densification, phase formation, chemical bonding and Vickers hardness of the composites were evaluated. All the samples exhibited mixed phase, comprising FAp and francolite as the major constituents along with some minor phases of cristobalite, wollastonite, dicalcium silicate and/or whitlockite dependent on the quartz content and sintering temperature. The composite containing 2.5 wt% quartz exhibited the best sintering properties. The highest bulk density of 3 g/cm³ and a Vickers hardness of >4.2 GPa were obtained for the 2.5 wt% quartz–FAp composite when sintered at 1100 °C. The addition of quartz was found to alter the microstructure of the composites, where it exhibited a rod-like morphology when sintered at 1000 °C and a regular rounded grain structure when sintered at 1350 °C. A wetted grain surface was observed for composites containing high quartz content and was believed to be associated with a transient liquid phase sintering.     

Honey-Bees Mating Optimization (HBMO) Algorithm: A New Heuristic Approach for Water Resources Optimization

Over the last decade, evolutionary and meta-heuristic algorithms have been extensively used as search and optimization tools in various problem domains, including science, commerce, and engineering. Their broad applicability, ease of use, and global perspective may be considered as the primary reason for their success. The honey-bees mating process may also be considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bees mating. In this paper, the honey-bees mating optimization algorithm (HBMO) is presented and tested with few benchmark examples consisting of highly non-linear constrained and/or unconstrained real-valued mathematical models. The performance of the algorithm is quite comparable with the results of the well-developed genetic algorithm. The HBMO algorithm is also applied to the operation of a single reservoir with 60 periods with the objective of minimizing the total square deviation from target demands. Results obtained are promising and compare well with the results of other well-known heuristic approaches.     

梓树果实中黄酮类化合物提取工艺研究

以梓树果实为原料,对黄酮类化合物提取工艺进行研究,采用单因素试验法对影响梓树果实中黄酮类化合物提取率的主要因素进行了分析,利用正交试验优化了提取总黄酮的最佳工艺条件.研究表明,梓树果实中提取黄酮类化合物的最佳条件为:乙醇浓度60%,提取温度70"C,料液比1:20,提取时间2.Oh,在最佳条件下总黄酮的提取率为4.83%.     

Effect of light intensity and frequency of flashing light from blue light emitting diodes on astaxanthin production by Haematococcus pluvialis

Flashing light from blue light emitting diodes is an effective method for the reduction of energy consumption in the bioproduction of astaxanthin by Haematococcus pluvialis. We investigated the effects of light intensity and frequency on the final astaxanthin concentration in bioproduction by H. pluvialis grown mixotrophically. The final astaxanthin concentration under illumination with flashing light, with frequencies ranging from 25 to 200 Hz, was dependent on the light intensity and on the duty cycle and was equivalent, or higher, in comparison with that under illumination with continuous light at the same incident intensity. The light intensity determined the maximum attainable concentration of astaxanthin under continuous illumination. Under illumination with flashing light, the ratio of the final astaxanthin concentration to the maximum concentration at a specific light intensity was correlated to the duty cycle in the frequency range from 25 to 200 Hz. The effect of lower frequencies on enhanced astaxanthin production under flashing light was also studied; at levels as low as 1 Hz, higher final astaxanthin concentrations were observed under flashing light compared to concentrations attained under continuous light.     

DELAYED COKING OF HYDROTREATED REDUCED CRUDE

ABSTRACT

A laboratory coking unit was designed and constructed for an experimental study of the delayed coking process of hydrotreated Kirkuk reduced crude. The yield and analysis of coke, gases and liquid products were obtained for each experiment. The gas < C₄. and gasoline yield decrease by increasing Liquid hourly space velocity (LHSV) while the yields of kerosene and gas oil increase and no effect of LHSV on petroleum coke yield was observed, The specific gravity of gasoline, kerosene and gas oil decreases by increasing LHSV. The increase in LHSV (decrease in residence time) decreases the olefinic hydrocarbons of produced gas oil and fraction 350-450^°C. Sulfur content of produced coke and coking residue increases by increasing residence time while it changes slightly for kerosene and gas oil. By increasing the recycle ratio (RR), the yield of gas decreases while the coke yield increases. Sulfur content of gas oil and coking residue increases with an increase in the recycle ratio while it decreases for coke. Metals content of coke decreases with an increase in the recycle ratio and coke with accepted properties for aluminum anode manufacture could be produced when a recycle ratio of 1.4 was used.     

Multi-reservoir Operation Rules: Multi-swarm PSO-based Optimization Approach

Reservoir operation rules are intended to help an operator so that water releases and storage capacities are in the best interests of the system objectives. In multi-reservoir systems, a large number of feasible operation policies may exist. System engineering and optimization techniques can assist in identifying the most desirable of those feasible operation policies. This paper presents and tests a set of operation rules for a multi-reservoir system, employing a multi-swarm version of particle swarm optimization (MSPSO) in connection with the well-known HEC-ResPRM simulation model in a parameterization–simulation–optimization (parameterization SO) approach. To improve the performance of the standard particle swarm optimization algorithm, this paper incorporates a new strategic mechanism called multi-swarm into the algorithm. Parameters of the rule are estimated by employing a parameterization–simulation–optimization approach, in which a full-scale simulation model evaluates the objective function value for each trial set of parameter values proposed with an efficient version of the particle swarm optimization algorithm. The usefulness of the MSPSO in developing reservoir operation policies is examined by using the existing three-reservoir system of Mica, Libby, and Grand Coulee as part of the Columbia River Basin development. Results of the rule-based reservoir operation are compared with those of HEC-ResPRM. It is shown that the real-time operation of the three reservoir system with the proposed approach may significantly outperform the common implicit stochastic optimization approach.     

Modeling of conjugated heat transfer in a thick walled enclosure filled with nanofluid

The objective of this paper is to investigate the conjugated heat transfer in a thick walled cavity filled with copper-water nanofluid. The analysis uses a two-dimensional rectangular enclosure under conjugated convective-conductive heat transfer conditions and considers a range of Rayleigh numbers. The enclosure was subjected to a constant and uniform heat flux at the left thick wall generating a natural convection flow. The thicknesses of the other boundaries are assumed to be zero. The right wall is kept at a low constant temperature while the horizontal walls are assumed to be adiabatic. A moveable divider is located at the bottom wall of the cavity. The governing equations are derived based on the conceptual model in the Cartesian coordinate system. The study has been carried out for the Rayleigh number in the range of 10⁵ ≤ Ra ≤ 10⁸, and for the solid volume fraction at 0 ≤ ? ≤ 0.05. Results are presented in the form of streamlines, isotherms, average Nusselt number and input heat absorption by the nanofluid. The effects of solid volume fraction of nanofluids, the location of the divider and also the value of the ambient convective heat transfer coefficient on the hydrodynamic and thermal characteristics of flow have been analyzed. An increase in the average Nusselt number was found with the solid concentration for the whole range of Rayleigh number. In addition, results show that the position of the divider and the ambient convective heat transfer coefficient have a considerable effect on the heat transfer enhancement.     

Three Dimensional Conceptualisation of Hydrogeological Environment to Underpin Groundwater Management in Irrigation Area

Australian irrigated agriculture utilises about 70?% of all water used in the country, 21?% of which is derived from groundwater. Sustainability for irrigated agriculture also depends on keeping the watertables at a safe level below the rootzone to avoid salinisation and reduction in crop yields. There is a vital need to understand groundwater and aquifer systems and their roles in the sustainability of irrigated agriculture in order to manage groundwater properly. This study builds on the previous hydrogeological and groundwater investigations of the Coleambally Irrigation Area (CIA) in New South Wales of Australia. It presents a new approach which systematically characterises regional hydrogeological environment using a three-dimensional (3-D) conceptual framework developed in ArcGIS. The 3-D hydrological conceptualisation of the CIA has integrated disparate sources of data into a coherent knowledge base for a better visualisation of hydrogeological characteristics and a comprehensive analysis of groundwater flow and aquifers. As an application example, the model was used to develop cross-sectional models of the area and to estimate regional-scale net recharge. The results have provided a basis for the numerical modelling and added values to procedures which underpin irrigation system management investment decisions through improving the understanding of hydrogeology underlying the area and creating an action-oriented dialogue among stakeholders.     

Predicting Dew Point Pressure: Using a Hybrid Intelligent Network

This article presents a new model in predicting dew point pressure, which is reduced the complexities of the prior fuzzy model by implementing genetic algorithm as a feature recognition tool. Feature recognition is a tool that makes the problem less complex and create the opportunity to have a better model. In this study, 15 parameters decreased to six by using the feature recognition tool. This tool discovered if fuzzy model inputs include reservoir temperature and mole fractions of H2S, N2, C3, iC5, and C6, the proposed model captures the physical trend better than previous models. The recommended model has an average relative deviation of 1.16% and average absolute deviation of 3.08% for testing data points.     

A stochastic security approach to energy and spinning reserve scheduling considering demand response program

In this paper a new algorithm for allocating energy and determining the optimum amount of network active power reserve capacity and the share of generating units and demand side contribution in providing reserve capacity requirements for day-ahead market is presented. In the proposed method, the optimum amount of reserve requirement is determined based on network security set by operator. In this regard, Expected Load Not Supplied (ELNS) is used to evaluate system security in each hour. The proposed method has been implemented over the IEEE 24-bus test system and the results are compared with a deterministic security approach, which considers certain and fixed amount of reserve capacity in each hour. This comparison is done from economic and technical points of view. The promising results show the effectiveness of the proposed model which is formulated as mixed integer linear programming (MILP) and solved by GAMS software.