Outage Probability Analysis of Multi-relay Cooperative Decode-and-Forward System Over Generalized η–μ and κ–μ Fading Channels

In present scenario of wireless sensor networks and communications, efficient sensed data transmission among nodes is being a great confrontation because of the impulsive and volatile nature of sensors in the network. For providing that and enhancing network lifetime, there are several approaches are developed, specifically using clustering techniques. Still, there are requirements for energy based efficient routing in WSN. With that note, this paper develops anEnergy Aware Efficient Data Aggregation (EAEDAR) and Data Re-Schedulingwith the incorporation of clustering techniques. Moreover, the model used energy based cluster formation and cluster head selection for increasing the network stability and data delivery rate. The model comprises four main phases, namely, Energy factor based cluster formation, Aggregator_SN (Sensor Node) Selection, Efficient Data Aggregation (EDA) and Data Re-Scheduling based on delay and processing time. Furthermore, the model is updated with respect to the status of the nodes and links, for providing consistent network with improved reliable data transmissions. The simulation results portrays the effectiveness of the proposed model over other compared works in terms of the performance factors such as, throughput, packet delivery ratio, network lifetime, transmission delay and packet drop.

     

Catalytic gasification of oil sludge with calcined dolomite

Abstract

Gasification of carbon-based residues for synthesis gas production is one of the most important strategies for clean energy production and environmental management. Currently, China is the world's largest net oil importer which is a result of China's added refinery capacity. In this article, a simulation model of oil sludge gasification with a combination of air and steam was developed using Aspen Plus software. Effect of dolomite as an active catalyst on gas composition was studied at various operating conditions. Results showed that H₂ and CO increased with reaction temperature, while CH₄ decreased from 9.1 to 4.71?vol% because of increased steam reforming of CH₄. By adding steam to the gasifier, H₂ content increased significantly, while CO content showed an opposite trend.     

Analytical Simulation of the Cloud Combustion of Corn Starch Microparticles

Knowledge of the fundamentals of dust combustion is necessary for designing safety technologies such as flame arrestors. The structure of flame propagation in a uniformly distributed cloud of volatile fuel particles was simulated. A model based on energy and mass conservation laws was generated. The obtained system of equations was nondimensionalized and solved according to the introduced boundary conditions. Comparison of the results with the existing experimental data in the literature showed remarkable agreement. Finally, the effect of parameters such as particle size and Lewis number on the characteristics of the cloud combustion of biomass microparticles under both lean and rich conditions was studied.     

Knudsen diffusion through ZIF-8 membranes synthesized by secondary seeded growth

Herein we demonstrate the synthesis of ZIF-8 membranes via secondary seeded growth on tubular stainless steel porous supports. The membranes were characterized and evaluated for the separation of CO₂/N₂ and N₂/CH₄ gas mixtures. The adsorbate polarizability correlated with the adsorption capacity on ZIF-8, and the amounts of gases adsorbed were in the order: CO₂ > CH₄ > N₂. The CO₂/N₂ separation selectivity’s for the ZIF-8 membranes were close to the Knudsen selectivity, suggesting that Knudsen diffusion through non-ZIF pores dominated the separation. On the other hand, the separation selectivity’s for N₂/CH₄ were slightly higher than the Knudsen selectivity, indicating that the flow contribution from the ZIF pores favored the transport of N₂ over CH₄.     

Self-assembly hydrothermal assisted synthesis of mesoporous anatase in the presence of ethylene glycol

Mesoporous nanocrystalline anatase was prepared hydrothermally employing P123 as structure-directing agent. Ethylene glycol was used as a key synthesis parameter to fine tune the morphology, crystal size and pore size of the resultant mesophases. The incorporation of EG in the synthesis gel resulted in the formation of 1–2 μm sphere-like shapes and led to an increase in the specific surface area from 95 to 170 m²/g, decrease in the average pore size from 11 to 4.8 nm, and decrease in the average crystallite size from 17 to 12 nm. These mesophases were used as photocatalysts for the UV degradation of methylene blue and methyl orange. The mesoporous anatase phases photodegraded MB 1.5–3× faster than commercially available P25 and showed limited photocatalytic behavior for methyl orange.     

Porous g-C3N4-encapsulated TiO2 hollow sphere as a high-performance Z-scheme hybrid for solar-induced photocatalytic abatement of environmentally toxic pharmaceuticals

Herein,we rationally constructed a hybrid heterostructure comprising porous g-C3N4(CN)-encapsulated anatase TiO2 hollow spheres(TOHS)via a synthesis method that involves hydrothermal and calcination treatments.The fabricated hybrid,termed CN/TOHS,demonstrated extraordinary activity toward the degradation of environmentally toxic pharmaceutical substances(acetaminophen and ciprofloxacin)in aqueous solutions under simulated sunlight irradiation;the activity of CN/TOHS was superior to that attained for individual TOHS and CN counterparts.In particular,the CN/TOHS hybrid containing 13.3 wt.％of CN on TOHS displayed the optimum degradation activity among the tested catalysts used in this study,and it also possessed exceptional recyclability and stability during consecutive degradation tests.The remarkable photocatalytic activity and stability of the hybrid were predominantly ascribed to the large solid interfacial contact between constituents,TOHS and CN,induced by effective hybrid structure,which boosted the interfacial charge transfer and impeded with the direct recombination of photo-induced charges.Notably,the results of the liquid chromatography-mass spectrometry analysis corroborated the effective mineralization of model pharmaceutical pollutants in the presence of the CN/TOHS hybrid.The simple interfacial engineering strategy presented in this study offers a potential route for the rational design of novel catalysts for application in environmental remediation and solar energy conversion.     

Biohydrogen synthesis from catalytic steam gasification of furniture waste using nickel catalysts supported on modified CeO2

Present study evaluated the catalytic steam gasification of furniture waste to enhance the biohydrogen production. To do this, 10 wt% nickel loaded catalysts on the variety of supports (Al₂O₃, CeO₂, CeO₂-La₂O₃, and CeO₂–ZrO₂) were prepared by the novel solvent deficient method. The hydrogen selectivity (vol%) order of the catalysts was achieved as Ni/CeO₂–ZrO₂>Ni/CeO₂>Ni/Al₂O₃?Ni/CeO₂-La₂O₃. The best catalytic activity of Ni/CeO₂–ZrO₂ catalyst (~82 vol % H₂ at 800 °C) was ascribed to the smaller size of nickel crystals, finely dispersed Ni on the catalyst surface, and Ce_1-xZr_xO_2-δ solid solution. The role of Ce_1-xZr_xO_2-δ solid solution in Ni/CeO₂–ZrO₂ catalyst was observed as bi-functional; acceleration of water-gas-shift and oxidation of carbon reaction. The high resistance of Ni/CeO₂–ZrO₂ towards the coke formation showed its potential to establish a cost-effective commercial-scale biomass steam gasification process. This study is expected to provide a promising solution for the disposal of furniture wastes for production of clean energy (biohydrogen).     

Fuel oil characteristics and applications: economic and technological aspects

This review explains some of the most important properties of heavy oils compared to other fuels. Although there is numerous heavy oil upgrading methods, this study was focused on the production of synthesis gas. Alongside advantages, some of the limitations of using heavy oil are also explained, including high heavy oil upgrading costs. In this regard, some of the most important heavy oil upgrading methods were selected and their economic characteristics were compared.     

A novel intelligent approach to simulate the blast-induced flyrock based on RFNN combined with PSO

This research focuses to propose a new hybrid approach which combined the recurrent fuzzy neural network (RFNN) with particle swarm optimization (PSO) algorithm to simulate the flyrock distance induced by mine blasting. Here, this combination is abbreviated using RFNN–PSO. To evaluate the acceptability of RFNN–PSO model, adaptive neuro-fuzzy inference system (ANFIS) and non-linear regression models were also used. To achieve the objective of this research, 72 sets of data were collected from Shur river dam region, in Iran. Maximum charge per delay, stemming, burden, and spacing were considered as input parameters in the models. Then, the performance of the RFNN–PSO model was evaluated against ANFIS and non-linear regression models. Correlation coefficient (R2), Nash and Sutcliffe (NS), mean absolute bias error (MABE), and root-mean-squared error (RMSE) were used as comparing statistical indicators for the assessment of the developed approach’s performance. Results show a satisfactory achievement between the actual and predicted flyrcok values by RFNN–PSO with R2, NS, MABE, and RMSE being 0.933, 0.921, 13.86, and 15.79, respectively.     

Implications of the file names and user requested queries on Gnutella performance

The Gnutella file sharing system allows a large number of peers to share their local files. However, it does not coordinate the way by which these shared objects are named or how they are searched by other users; such decisions are made independently by each peer. In this work, we investigate the practical performance implications of this design. We collected the shared filenames and user generated queries over a three-year period. We show the mismatch between these naming mechanisms. We show the fundamental limitations of Gnutella performance that cannot be addressed by improvements in overlays or by varying the search mechanisms alone. Based on our observations, we describe two practical approaches to improve Gnutella performance. We describe a mechanism to build the file term synopsis using the observed popularity of queries routed through the ultrapeer. We also describe a query transformation mechanism that improves the success rates for failed queries.