Techno-economic evaluation of coal-to-liquids (CTL) plants with carbon capture and sequestration

Coal-to-liquids (CTL) processes that generate synthetic liquid fuels from coal are of increasing interest in light of the substantial rise in world oil prices in recent years. A major concern, however, is the large emissions of CO₂ from the process, which would add to the burden of atmospheric greenhouse gases. To assess the options, impacts and costs of controlling CO₂ emissions from a CTL plant, a comprehensive techno-economic assessment model of CTL plants has been developed, capable of incorporating technology options for carbon capture and storage (CCS). The model was used to study the performance and cost of a liquids-only plant as well as a co-production plant, which produces both liquids and electricity. The effect of uncertainty and variability of key parameters on the cost of liquids production was quantified, as were the effects of alternative carbon constraints such as choice of CCS technology and the effective price (or tax) on CO₂ emissions imposed by a climate regulatory policy. The efficiency and CO₂ emissions from a co-production plant also were compared to the separate production of liquid fuels and electricity. The results for a 50,000 barrels/day case study plant are presented.     

Multi-resolution boosting for classification and regression problems

Various forms of additive modeling techniques have been successfully used in many data mining and machine learning–related applications. In spite of their great success, boosting algorithms still suffer from a few open-ended problems that require closer investigation. The efficiency of any additive modeling technique relies significantly on the choice of the weak learners and the form of the loss function. In this paper, we propose a novel multi-resolution approach for choosing the weak learners during additive modeling. Our method applies insights from multi-resolution analysis and chooses the optimal learners at multiple resolutions during different iterations of the boosting algorithms, which are simple yet powerful additive modeling methods. We demonstrate the advantages of this novel framework in both classification and regression problems and show results on both synthetic and real-world datasets taken from the UCI machine learning repository. Though demonstrated specifically in the context of boosting algorithms, our framework can be easily accommodated in general additive modeling techniques. Similarities and distinctions of the proposed algorithm with the popularly used methods like radial basis function networks are also discussed.     

Energy efficient task allocation and consolidation in multicast cloud network

Wireless Networks - Information Technology is now a revolution due to its user dependence for various services available over Internet through cloud computing (CC). The usability is now reached to...     

Green etherification of bioglycerol with 1-phenyl ethanol over supported heteropolyacid

Escalating demand for biodiesel production has generated surplus glycerol. Therefore, the consumption of glycerol for valuable conversions has become a global challenge. In an effort to convert glycerol, we have etherified it to make a biologically active component, 3-(1-phenylethoxy) propane-1,2-diol. Etherification of glycerol with 1-phenyl ethanol was carried out by using heterogeneous acid catalysts. The process is green and clean. Different types of heteropolyacids (HPAs) supported on hexagonal mesoporous silica (HMS) and K-10 clay were prepared by incipient-wetness technique and screened to get high selectivity towards monoether of glycerol. 20% w/w dodeca-tungstophosphoric acid (DTP)/HMS was found to be the best. The effects of various reaction parameters such as speed of agitation, catalyst loading, mole ratio of reactants and temperature were evaluated systematically to prove that the reaction obeys Langmuir–Hinshelwood–Hougen–Watson (LHHW) type of mechanism. It was also observed that the reaction was free from any external mass transfer as well as intra-particle diffusion limitations and was intrinsically kinetically controlled. An overall second order kinetic equation was used to fit the experimental data, under the assumption that all the species are weakly adsorbed on the catalytic sites. Apparent activation energy was estimated as 27.0 kcal/mol. Solvent-free condition for this reaction has also added the green chemistry perception to the reaction.     

Evolution of Texture,Grain Boundary Constitution,Strain, and Corrosion Behavior of Electrodeposited Ni–P Coatings as a Function of Deposition Current Density

Metallurgical and Materials Transactions A - Ni–P coatings with low P content (P wt pct < 1.0) were fabricated at different applied current densities of electrodeposition...     

Multi-objective optimization of oil well drilling using elitist non-dominated sorting genetic algorithm

A multi-objective optimization of oil well drilling has been carried out using a binary coded elitist non-dominated sorting genetic algorithm.A Louisiana offshore field with abnormal formation pressure is considered for optimization.Several multi-objective optimization problems involving twoand three-objective functions were formulated and solved to fix optimal drilling variables.The important objectives are：（i） maximizing drilling depth,（ii） minimizing drilling time and （iii） minimizing drilling cost with fractional drill bit tooth wear as a constraint.Important time dependent decision variables are：（i） equivalent circulation mud density,（ii） drill bit rotation,（iii） weight on bit and （iv） Reynolds number function of circulating mud through drill bit nozzles.A set of non-dominated optimal Pareto frontier is obtained for the two-objective optimization problem whereas a non-dominated optimal Pareto surface is obtained for the three-objective optimization problem.Depending on the trade-offs involved,decision makers may select any point from the optimal Pareto frontier or optimal Pareto surface and hence corresponding values of the decision variables that may be selected for optimal drilling operation.For minimizing drilling time and drilling cost,the optimum values of the decision variables are needed to be kept at the higher values whereas the optimum values of decision variables are at the lower values for the maximization of drilling depth.     

Substrate temperature and hydrogen dilution: parameters for amorphous to microcrystalline phase transition in silicon thin films

Amorphous to microcrystalline phase transition in hydrogenated silicon (Si:H) is realized separately with the variations of substrate temperature and hydrogen dilution. The Raman spectroscopy reveals structural transformations and marks the transition. It occurs at 450°C with 10% silane concentration, whereas that is noted at 250°C with a silane concentration of 4.5%. The material evolved in the transition region is a well-developed amorphous matrix containing a small fraction (12%) of crystallites. A uniform distribution of small (100 Å) crystallites in the films is observed by transmission electron microscopy. The transition material is photosensitive.     

Nutritional and healthful aspects of cultured and culture-containing dairy foods

Nutritional and therapeutic qualities of fermented dairy products are reviewed. Partial hydrolysis of milk constituents (proteins, fats, and lactose) in yogurt, cheese, and other cultured dary foods appears to contribute to their increased digestibility. Lactase and other constituent enzymes of various culturing organisms should contribute to assimilation of lactose by lactose intolerant individuals. Several lactic cultures synthesize certain B-vitamins in fermented dairy products. In contrast, directly acidified dairy products do not exhibit such enhancement in B-vitamins. The hypocholestremic effect of milk is enhanced by fermentation or inclusion of lactic cultures. Lactobacillus acidophilus, Lactobacillus bulgaricus and other lactic organisms produce antimicrobial agents and natural antibiotics. However, production of natural antibacterial substances by different strains of the same species vary widely. These metabolites in cultured dairy products may be responsible for increased shelf life of the foods by inhibiting a wide spectrum of food spoilage organisms. Also, consumption of cultured products containing such natural antibacterial substances may provide the consumer with protection against disease organisms. Unfermented milk containing a specific culture or strain may be consumed to invest organisms for projected beneficial effects.