Towards finding the best-fit distribution for OSN data

The Journal of Supercomputing - Currently, all online social networks (OSNs) are considered to follow a power-law distribution. In this paper, the degree distribution for multiple OSNs has been...     

A simulation study of reduction kinetics for sponge iron production in a rotary hearth furnace

ABSTRACT

A mathematical model has been developed by coupling genetic algorithm (GA) with heat and material balance equations to estimate rate parameters and solid-phase evolution related to the reduction of iron ore-coal composite pellets in a multi-layer bed Rotary hearth Furnace (RHF). The present process involves treating iron ore-coal composite pellets in a crucible over the hearth in RHF. The various solid phases evolved at the end of the process are estimated experimentally, and are used in conjunction with the model to estimate rate parameters. The predicted apparent activation energy for the wustite reduction step is found to be lower than those of the reduction of higher oxides. The thermal efficiency is found to decrease significantly with an increase in the carbon content of the pellet. Thermal efficiency was also found to increase mildly up to three layers. Multilayer bed remains as a potential design parameter to increase thermal efficiency.     

Review on zirconate-cerate-based electrolytes for proton-conducting solid oxide fuel cell

The performance of low-to-intermediate temperature (400–800?°C) solid oxide fuel cells (SOFCs) depends on the properties of electrolyte used. SOFC performance can be enhanced by replacing electrolyte materials from conventional oxide ion (O^2-) conductors with proton (H⁺) conductors because H⁺ conductors have higher ionic conductivity and theoretical electrical efficiency than O^2- conductors within the target temperature range. Electrolytes based on cerate and/or zirconate have been proposed as potential H⁺ conductors. Cerate-based electrolytes have the highest H⁺ conductivity, but they are chemically and thermally unstable during redox cycles, whereas zirconate-based electrolytes exhibit the opposite properties. Thus, tailoring the properties of cerate and/or zirconate electrolytes by doping with rare-earth metals has become a main concern for many researchers to further improve the ionic conductivity and stability of electrolytes. This article provides an overview on the properties of four types of cerate and/or zirconate electrolytes including cerate-based, zirconate-based, single-doped cerate–zirconate and hybrid-doped cerate–zirconate. The properties of the proton electrolytes such as ionic conductivity, chemical stability and sinterability are also systematically discussed. This review further provides a summary of the performance of SOFCs operated with cerate and/or zirconate proton conductors and the actual potential of these materials as alternative electrolytes for proton-conducting SOFC application.     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

A metaheuristic analysis of heat transfer rates through porous fins of tapered and step profiles: a comparative study

Neural Computing and Applications - The advanced high-end gadgets and sophisticated machines require effective mechanism of transferring heat away from the sources. In a large number of...     

Synthesis of Self-Healing Bio-Based Tannic Acid-Based Methacrylates By Thermoreversible Diels–Alder Reaction

This investigation reports the effective use of the Diels–Alder (DA) click reaction in the preparation of self-healing bio-based dendritic methacrylates having reactive furfuryl functionality. Bio-based methacrylates were synthesized by modifying tannic acid with glycidyl methacrylate and furfuryl functionality was introduced by atom transfer radical polymerization with varied amount of furfuryl methacrylate monomer. The thermoreversible network was successfully achieved by DA and retro-DA reaction between the furfuryl groups and a bifunctional maleimide crosslinker, bismaleimide. This process was studied by nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis, and solvent exposure tests. Differential scanning calorimetry analysis was used to determine the endothermic retro-DA reaction in the DA adduct. The self-healing property of the above crosslinked material was demonstrated by monitoring the repair of a scratch in the polymer film upon heating and cooling. This was analyzed by scanning electron microscopy. POLYM. ENG. SCI., 60:140–150, 2020. © 2019 Society of Plastics Engineers