Parallelization Strategies for Computational Fluid Dynamics Software: State of the Art Review

Computational fluid dynamics (CFD) is one of the most emerging fields of fluid mechanics used to analyze fluid flow situation. This analysis is based on simulations carried out on computing machines. For complex configurations, the grid points are so large that the computational time required to obtain the results are very high. Parallel computing is adopted to reduce the computational time of CFD by utilizing the available resource of computing. Parallel computing tools like OpenMP, MPI, CUDA, combination of these and few others are used to achieve parallelization of CFD software. This article provides a comprehensive state of the art review of important CFD areas and parallelization strategies for the related software. Issues related to the computational time complexities and parallelization of CFD software are highlighted. Benefits and issues of using various parallel computing tools for parallelization of CFD software are briefed. Open areas of CFD where parallelization is not much attempted are identified and parallel computing tools which can be useful for parallelization of CFD software are spotlighted. Few suggestions for future work in parallel computing of CFD software are also provided.     

Cobalt–Iron nanoparticles encapsulated in mesoporous carbon nanosheets: A one-pot synthesis of highly stable electrocatalysts for overall water splitting

Advancement of cost-effective, highly efficient and non-noble metal-based bifunctional electrocatalysts is considered an attractive approach to overcome the energy defect and environmental pollution challenges. Herein, this study presents a simple one-pot approach to synthesize cobalt-Iron nanoparticles encapsulated in mesoporous carbon nanosheets (Co₃Fe₇@CNSs) by the pyrolysis method. The Co₃Fe₇@CNSs-750/4h electrocatalyst exhibits a notable performance, low overpotential of 181 and 301 mV at a current density of 10 mA cm^?2 and small Tafel slope of 124.8 and 38.59 mV dec^?1, large active surface area 18.20 and 21.18 mF cm^?2, and low charge transfer resistance 4.92 and 9.42 Ω for hydrogen and oxygen evolution reactions, respectively, in 1.0 M KOH. Overall water splitting, with the set-up of two-electrode cells acquires the 10 mA cm^?2 of current density at 1.610 V in 1.0 M KOH. The combined structure of cobalt-iron nanoparticles encapsulated in carbon nanosheets; it could enhance the surface area and, provide more active sites that improve the overall catalytic activity. Not only this but also the synergistic effect due to different temperature treatments which significantly influenced the structural formation. However, the major involvement of this study is concerned with the production of economical non-noble metal-based electrocatalysts at an industrial scale for renewable energy to sustainability.     

Effect of Ho3+ ions on microwave losses and high-temperature electrical behavior of Li-based magnetic oxides

We investigate here the effect of holmium on Li–Co nano-ferrites to elaborate the surface morphology, dynamic magnetic and electrical transport properties. The transmission electron microscopy (TEM) technique was employed to examine the microstructure and grain size distribution. TEM analysis confirmed the nanocrystalline nature (~50 nm) of the prepared materials. X-ray photoelectron spectroscopy (XPS) experiment results verify the presence of all metal ions with the required valences. Ferromagnetic resonance (FMR) analysis revealed the need for a dense microstructure to cut down the microwave losses. FMR line width was observed to reduce from 2757 -to 1676 Oe except for x = 0.12 by the substitution of Ho ions which correspond to low microwave losses. The dc resistivity results show that high resistivity values are associated with smaller grains of the samples and vice versa. Resistivity values are found to increase from 3.66 × 10⁸ -to 5.31 × 10⁸ Ω-cm by increasing the Ho addition. Seebeck experiment revealed n-type conduction. Together with showing the nature of charge carriers, a decrease in the Seebeck coefficient with increasing Ho ensured the replacement of Fe ions by Ho ions on B-sites.     

Composite description based on color vector quantization and visual primary features for CBIR tasks

Multimedia Tools and Applications - This paper presents a novel method for content-based color image retrieval that combines color vector quantization and visual primary features into a compact...     

A facile supramolecular aggregation of trithiocyanuric acid with PCN for high photocatalytic hydrogen evolution from water splitting

Polymeric carbon nitride (PCN) is a promising hotspot metal‐free material for artificial photosynthesis, solar energy conversion, and photo degradation of pollutant, hence predicting unsatisfactory photocatalytic efficiency due to fast charge recombination. Here, we implemented a remediation approach to fuel its catalytic performance by interpretation of a sulfur rich‐material, ie, trithiocyanuric acid (TTCA) in the framework of PCN by traditional one facile protocol called copolymerization (molecular assembled) under nitrogen at 550°C. Results demonstrate that the integration of TTCA comonomer into the triazine oligomers of PCN widens the specific surface area, extends the lifetime of photoexcited charge carriers, speeds up the rate of photogenerated electrons optimized from lower energy state toward high energy state, lowers the rate of charge recombination and band gap, and modulates its electronic structure and optical properties in a regular fashion as compared with pristine PCN. Ultimately, due to aforementioned modification, the copolymerized PCN semiconductor predicts superior photocatalytic properties of hydrogen energy production about 7 times higher than that of pristine PCN from the water splitting system.     

Multifracture response to supercritical CO2‐EGS and water‐EGS based on thermo‐hydro‐mechanical coupling method

Hydraulic‐fracturing treatments have become an essential technology for the development of deep hot dry rocks (HDRs). The deep rock formation often contains natural fractures (NFs) at micro and macroscales. In the presence of the NF, the hydraulic‐fracturing process may form a complex fracture network caused by the interaction between hydraulic fractures and NF. In this study, analysis of carbon dioxide (CO₂)‐based enhanced geothermal system (EGS) and water‐based EGS in complex fracture network was performed based on the thermo‐hydro‐mechanical (THM) coupling method, with various rock constitutive models. The complexity of the fracture geometry influences the fluid flow path and heat transfer efficiency of the thermal reservoir. Compared with CO₂‐based EGS, water‐based EGS had an earlier thermal breakthrough with a rapid decline in production temperature. CO₂ can easily gain heat rising its temperature thus reducing the effect of a premature thermal breakthrough. Both CO₂‐based EGS and water‐based EGS are affected by in‐situ stress; the increase in stress ratio improved the fracture permeability but resulted in an early cold thermal breakthrough. When the same injection rate is applied to water‐based EGS and CO₂‐based EGS, water‐based EGS displayed higher injection pressure buildup. Water‐based EGS had higher reservoir deformation area than CO₂‐based EGS, and thermoelastic constitutive model for water‐based EGS showed larger deformed area ratio than thermo‐poroelastic rock model. Furthermore, higher values of rock modulus accelerated the reservoir deformation for water‐based EGS. This study established a novel discussion investigating the performance of CO₂‐based EGS and water‐based EGS in a complex fractured reservoir. The findings from this study will help in deepening the understanding of the mechanisms involved when using CO₂ or water as a working fluid in EGS.     

Soft‐template synthesis of high surface area mesoporous titanium dioxide for dye‐sensitized solar cells

In the present work, 10 to 14 nm titania nanoparticles with high‐packing density are synthesized by the soft‐template method using a range of cationic surfactants including cetyl trimethylammonium bromide (CTAB), Sodium dodecyl sulfate (SDS), and dodecyl trimethylammonium bromide (DTAB). The synthesized nanoparticles are used as a photoanode material in dye solar cells. Density functional theory (DFT) simulations reproduce our experimental results of charge transfer and strong interaction between the TiO₂ and N719. N719‐TiO₂ complex establishes strong electrostatic bonding through H of the dye with the O of TiO₂ surface. Solar cell efficiency of 6.08% with 12.63 mA/cm², 793 mV, and 48.5% for short circuit current density, open circuit voltage, and fill factor, respectively, are obtained under 1 sun illumination for the dye‐sensitized solar cell (DSSC) using a film of mesoporous TiO₂ synthesized from the SDS surfactant. On the other hand, the 21 nm commercial TiO₂ powder (P25) device results in 4.60% efficiency under similar conditions. Electrochemical impedance spectroscopic studies show that the SDS device has lesser charge transport resistance than the other devices because of its higher surface area, packing density, and dye loading capacity. Our results show that employing high packing density‐based TiO₂ nanoparticles represents a commercially viable approach for highly beneficial photoanode development for future DSSC applications.     

Bio-inspired computational heuristics for parameter estimation of nonlinear Hammerstein controlled autoregressive system

In this study, strength of evolutionary computational intelligence based on genetic algorithms (GAs) is exploited for parameter identification of nonlinear Hammerstein controlled autoregressive (NHCAR) systems. The fitness function is constructed for the NHCAR system by defining an error function in the mean square sense. Unknown adjustable weights of the system are optimized with GAs, used as an effective tool for effective global search. Comparative analysis of the proposed scheme is made from true parameters of the systems for a number of scenarios based on different levels of signal-to-noise ratios. The validation of the performance is made through statistics based on sufficiently large number of runs using indices of mean absolute error, variance account for, and Thiel’s inequality coefficient as well as their global versions.