Flow visualization of Rayleigh–Bénard convection for cubical cavity

Natural convective flow of air inside the cubical cavity is investigated numerically. The temperature of the bottom wall is kept higher than that of top cold wall, and other four walls are assumed to be adiabatic. Attention has been paid to the convective discretization schemes, like upwind, QUICK, total variation diminishing, normalized variable diagram (NVD) schemes that are compared with respect to accuracy. The output is validated with respect to the results available in the literature. A parallel computing message passing interface code is adapted to run the simulations. From the results, it is observed that the NVD scheme gives better results among all the employed convective discretization schemes irrespective of the mesh structure. Thus, in this article, self filtered central differencing which is a family of NVD, is used. From the enormous output data, along with the streamlines, contours of isotherms, the new technique of energy pathlines, and field synergy are used to visualize the fluid flow and heat transfer mechanism arising in the system in the range of Ra from 10³ to 10⁶. Free energy streamlines are observed with small Ra, whereas trapped energy streamlines are observed with high Ra. When Ra increases, synergy angle increases and implies that the synergy between the velocity vector and temperature gradient gets reduced and leads to increasing values of average Nusselt number (Nu).     

Effect of Cryogenic Cooling on the Heat Transfer during Turning of AZ31C Magnesium Alloy

ABSTRACT

A combined analytical and experimental study was carried out to analyze the effects of cryogenic cooling on temperature during turning of AZ31C magnesium alloy. Finite element method was employed to model and simulating the cryogenic and dry turning. Results obtained from the model were found to be in good agreement with the experimental observations. For the maximum temperature at the turned surface, the difference in the experimental and predicted value observed during dry and cryogenic turning was only 4 and 8% respectively. A significant reduction in the maximum temperature on the chip surface (around 35%) and tool surface (around 29%) was observed during the cryogenic turning compared to dry turning. This reduction in temperature was an attribute of liquid nitrogen, which produces intense cooling effect around the vicinity cutting zone where heat generation takes place hence enhancing the heat transfer. The isothermal region belonging to the highest temperature on the tool surface was also reduced by about 42%. The reduction in temperature during cryogenic conditions were found to be beneficial for the machining of magnesium alloys under safe conditions, reducing the risk of ignition and explosions, and also increases the sustainability of the process.     

Carbon-based TiO2-x heterostructure nanocomposites for enhanced photocatalytic degradation of dye molecules

Application of brown titanium dioxide (TiO_2-x) and its modified composite forms in the photocatalytic decomposition of organic pollutants in the environment is a promising way to provide solutions for environmental redemption. Herein, we report the synthesis of effective and stable TiO_2-x nanoparticles with g-C₃N₄, RGO, and multiwalled carbon nanotubes (CNTs) using a simple hydrothermal method. Among all the as-synthesized samples, excellent photocatalytic degradation activity was observed for RGO-TiO_2-x nanocomposite with high rate constants of 0.075 min^?1_, 0.083 min^?1 and 0.093 min^?1 for methylene blue, rhodamine-B, and rosebengal dyes under UV–Visible light irradiation, respectively. The altered bandgap (1.8 eV) and the large surface area of RGO-TiO_2-x nanocomposite impacts on both absorption of visible light and efficiency of photogenerated charge electron (e^?)/hole (h⁺) pair separation. This resulted in enhanced photocatalytic property of carbon-based TiO_2-x nanocomposites. A systematic study on the influence of different carbon nanostructures on the photocatalytic activity of brown TiO_2-x is carried out.     

A novel hybrid hypervolume indicator and reference vector adaptation strategies based evolutionary algorithm for many-objective optimization

Engineering with Computers - A novel hybrid many-objective evolutionary algorithm called Reference Vector Guided Evolutionary Algorithm based on hypervolume indicator (H-RVEA) is proposed in this...     

Design and analysis of a sleep and wake-up CMOS low noise amplifier for 5G applications

Telecommunication Systems - This brief proposes a two-stage cascoded CMOS LNA with common drain envelope detection based power reduction method for the 5G applications of 28 GHz frequency....     

Dark fermentative biohydrogen production by Acinetobacter junii-AH4 utilizing various industry wastewaters

Hydrogen (H₂) is one of the most promising renewable energy sources, anaerobic bacterial H₂ fermentation is considered as one of the most environmentally sustainable alternatives to meet the potential fossil fuel demand. Bio-H₂ is the cleanest and most effective source of energy provided by the dark fermentation utilizing organic substrates and different wastewaters. In this study, the bio-H₂ production was achieved by using the bacteria Acinetobacter junii-AH4. Further, optimization was carried out at different pH (5.0–8.0) in the presence of wastewaters as substrates (Rice mill wastewater (RMWW), Food wastewater (FWW) and Sugar wastewater (SWW). In this way, the optimized experiments excelled with the maximum cumulative H₂ production of 566.44 ± 3.5 mL/L (100% FWW at pH 7.5) in the presence of Acinetobacter junii-AH4. To achieve this, a bioreactor (3 L) was employed for the effective production of H₂ and Acinetobacter junii-AH4 has shown the highest cumulative H₂ of 613.2 ± 3.0 mL/L, HPR of 8.5 ± 0.4 mL/L/h, HY of 1.8 ± 0.09 mol H₂/mol glucose. Altogether, the present study showed a COD removal efficiency of 79.9 ± 3.5% by utilizing 100% food wastewater at pH 7.5. The modeled data established a batch fermentation system for sustainable H₂ production. This study has aided to achieve an ecofriendly approach using specific wastewaters for the production of bio-H₂.     

Speed–density functional relationship for heterogeneous traffic data: a statistical and theoretical investigation

This study is an attempt to establish a suitable speed–density functional relationship for heterogeneous traffic on urban arterials. The model must reproduce the traffic behaviour on traffic stream and satisfy all static and dynamic properties of speed–flow–density relationships. As a first attempt for Indian traffic condition, two behavioural parameters, namely the kinematic wave speed at jam (C_j) and a proposed saturation flow (λ), are estimated using empirical observations. The parameter C_j is estimated by developing a relationship between driver reaction time and vehicle position in the queue at the signalised intersection. Functional parameters are estimated using Levenberg–Marquardt algorithm implemented in the R statistical software. Numerical measures such as root mean squared error, average relative error and cumulative residual plots are used for assessing models fitness. We set out several static and dynamic properties of the flow–speed–density relationships to evaluate the models, and these properties equally hold good for both homogenous and heterogeneous traffic states. From the numerical analysis, it is found that very few models replicate empirical speed–density data traffic behaviour. However, none of the existing functional forms satisfy all the properties. To overcome the shortcomings, we proposed two new speed–density functional forms. The uniqueness of these models is that they satisfy both numerical accuracy and the properties of fundamental diagram. These new forms would certainly improve the modelling accuracy, especially in dynamic traffic studies when coupling with dynamic speed equations.

     

Targeting Casein Kinase 1 (CK1) in Hematological Cancers

The casein kinase 1 enzymes (CK1) form a family of serine/threonine kinases with seven CK1 isoforms identified in humans. The most important substrates of CK1 kinases are proteins that act in the regulatory nodes essential for tumorigenesis of hematological malignancies. Among those, the most important are the functions of CK1s in the regulation of Wnt pathways, cell proliferation, apoptosis and autophagy. In this review we summarize the recent developments in the understanding of biology and therapeutic potential of the inhibition of CK1 isoforms in the pathogenesis of chronic lymphocytic leukemia (CLL), other non-Hodgkin lymphomas (NHL), myelodysplastic syndrome (MDS), acute myeloid leukemia (AML) and multiple myeloma (MM). CK1δ/ε inhibitors block CLL development in preclinical models via inhibition of WNT-5A/ROR1-driven non-canonical Wnt pathway. While no selective CK1 inhibitors have reached clinical stage to date, one dual PI3Kδ and CK1ε inhibitor, umbralisib, is currently in clinical trials for CLL and NHL patients. In MDS, AML and MM, inhibition of CK1α, acting via activation of p53 pathway, showed promising preclinical activities and the first CK1α inhibitor has now entered the clinical trials.