Heat and mass transport impact on MHD second-grade fluid: A comparative analysis of fractional operators

The effect of the magnetic flux plays a major role in convective flow. The process of heat transfer is accompanied by a mass transfer process; for instance, condensation, evaporation, and chemical process. Due to the applications of the heat and mass transfer combined effects in different fields, the main aim of this paper is to do a comprehensive analysis of heat and mass transfer of magnetohydrodynamic (MHD) unsteady second-grade fluid in the presence of ramped conditions. The new governing equations of MHD second-grade fluid have been fractionalized by means of singular and nonsingular differentiable operators. To have an accurate physical significance of imposed conditions on the geometry of second-grade fluid, the constant concentration with ramped temperature and ramped velocity is considered. The fractional solutions of temperature, concentration, and velocity have been investigated by means of integral transform and inversion algorithm. The influence of physical parameters and flow is analyzed graphically via computational software (MATHCAD-15). The velocity profile decreases by increasing the Prandtl number. The existence of a Prandtl number may reflect the control of the thickness and enlargement of the thermal effect.     

Intelligent computing for the dynamics of fluidic system of electrically conducting Ag/Cu nanoparticles with mixed convection for hydrogen possessions

The present study aims to provide an innovative stochastic numerical solver's application by the use of neural networks with Levenberg-Marquardt backpropagation to examine the dynamics of hydrogen possessions and variable viscosity in the fluidic system of electrically conducting copper and silver nanoparticles with mixed convection. The system of PDEs obtained by mathematical modeling of the physical phenomena are reduced into non-linear ODEs by utilizing suitable transformations. The ODEs dataset is constructed through Adams numerical solver and target parameters for input and output parameter of neural networks. The testing, validation and training processes are exploited in neural network models with learning based on backpropagation of LM method to calculate the solution for different scenarios created on variation of physical parameters of the proposed flow of Reynolds and Vogel models. Validation and verification of neural network model to find the solution of fluid flow problem is endorsed on the assessment of achieved accuracy through mean squared error, error histograms and regression studies.     

Influence of van der waals heterostructures of 2D materials on catalytic performance of ZnO and its applications in energy: A review

Recently, photocatalysis has received huge attention in order to overcome energy crisis worldwide. Many semiconductors, potential schemes and hierarchies have come to light during past few decades to fabricate efficient catalysts however, among all these methods heterostructures have taken the world by surprise. With the advancement in post-graphene 2D materials, van der Waals heterostructures have come to light exploring enhancement in photocatalysis. During a very short period a number of ZnO-based van der Waal heterostructures have taken the limelight in the field of photocatalysis. First principles calculations and DFT approach towards the heterostructures of GeC, GaN, WSe₂, WS₂ and other layered 2D materials unleased a series of properties and facts for the provision of enhanced catalysis. Reduction in bandgap of ZnO has also been observed which widens the pathways towards visible light irradiation. However, energy applications of zinc oxide are also fascinating feature as it can serve as a photoanode to replace TiO₂. Whereas the famous hydrogen production, batteries and solar cells have also been fabricated by the use of this semiconductor.     

Development of optimized triaxially electrospun titania nanofiber-in-nanotube core-shell structure

One dimensional (1D) nanostructures and its derivatives can be manipulated to serve special functions like hollow structure, and higher surface area. 1D TiO₂ nanotube-in-nanofibers (NF@NT) are developed through triaxial electrospinning followed by a calcination process. A blended solution of polyvinyl pyrrolidone and tetra-butyl titanate is used in outer and inner layers of nanofibers, respectively, while paraffin oil is used in the middle layer. The optimized triaxial nanofibers of 669.4 ± 52.43 nm are developed at 7.5 w/w% concentration, 28 kV applied voltage, and 24 cm spinning distance. TiO₂ NF@NT structure is obtained through calcination of optimized triaxial nanofibers at 550°C. Subsequently, the morphology of TiO₂ NF@NT and its uniform diameter distribution is confirmed through scanning electron microscopy. Fourier-transform infrared spectroscopy results indicates the formation of TiO₂ NF@NT. X-Rays diffraction pattern peaks also reveals the presence of both anatase and rutile crystalline phases. The presence of only titanium (Ti) and oxygen (O) elements in the TiO₂ NF@NT is confirmed through energy dispersive X-ray spectroscopy. Brunauer–Emmett–Teller analysis indicates that TiO₂ NF@NT has a higher specific surface area of ~141.68 m²/g compared with the solid TiO₂ nanofiber (~75.31 m²/g). This study can be adopted to develop TiO₂ NF@NT for wide range of application.     

Evaluation of domestic solar water heating system in Jordan using analytic hierarchy process

In addition to the solar water heating (SWH) system, other domestic water heating systems used in Jordan were considered in terms of benefits and costs using the Analytic Hierarchy Process. In terms of cost, the SWH system was the least expensive. On a percentage basis, the SWH cost about 13% compared to the most expensive heating system, LPG, of about 28%. In terms of benefits, the SWH was also the most beneficial. Approximately, the SWH benefits were about 31%, while the least benefits were obtained from the kerosene water heating system, which is about 9%. By considering both cost and benefit (i.e. cost-to-benefit ratio), solar was also the least expensive, about 7%, with kerosene being the most expensive, over 30%.     

Secure IoT solution for wearable health care applications,case study Electric Imp development platform

Internet expansion affects currently diverse entities on the physical world and daily life. The democratization of the technology called Internet of Things (IoT) brings back many problems associated with the security of the transmitted data, autonomy, and ease of use, with the central constraint of gathering momentum. The use of an embedded development platform for IoT operating through Wi‐Fi and cloud technology is in our case the solution that fits the internet model objects for wearable health care application. This work involves the study and implementation of wearable IoT secure solution dedicated to health care devoted to old and dependent people. The proposed hardware, powered by solar cells, operate through smart sleep and wake up events. The relevant part of the developed IoT operating software exploits the multiagent behavior. Case study, based on the exploitation of the Electric Imp platform, is proposed.     

The role of graphene and europium on TiO2 performance for photocatalytic hydrogen evolution

Highly efficient Eu-TiO₂/graphene composites were synthesized by a two-step method such as sol-gel and hydrothermal process. The synthesized photocatalysts were characterized by XRD, TEM, XPS, UV–vis diffuse reflectance spectroscopy and photoluminescence (PL) spectroscopy. The results confirmed that anatase Eu-TiO₂ nanoparticles with average 10 nm sizes were successfully deposited on two-dimensional graphene sheets. The UV–visible spectroscopy showed a red shift in the absorption edge of TiO₂ due to Eu doping and graphene incorporation. Moreover, effective charge separation in Eu-TiO₂/graphene composites was confirmed by PL emission spectroscopy compared to TiO₂/graphene, Eu-TiO₂ and pure TiO₂. The photocatalytic activity for H₂ evolution over prepared composites was studied under visible light irradiation (λ ≥ 400 nm). The results demonstrate that photocatalytic performance of the photocatalysts for hydrogen production increases with increasing doping concentration of Eu upto 2 at%. However, further increase in doping content above this optimum level has decreased the performance of photocatalyst. The enhanced photocatalytic performance for H₂ evolution is attributed to extended visible light absorption, suppressed recombination of electron-hole pairs due to synergistic effects of Eu and graphene.     

Engineering the smart factory

The fourth industrial revolution promises to create what has been called the smart factory. The vision is that within such modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralised decisions. This paper provides a view of this initiative from an automation systems perspective. In this context it considers how future automation systems might be effectively configured and supported through their lifecycles and how integration, application modelling, visualisation and reuse of such systems might be best achieved. The paper briefly describes limitations in current engineering methods, and new emerging approaches including the cyber physical systems (CPS) engineering tools being developed by the automation systems group (ASG) at Warwick Manufacturing Group, University of Warwick, UK.     

A cumulative belief degree approach for group decision‐making problems with heterogeneous information

In some complex group decision‐making (GDM) problems, the information needing to be processed may be heterogeneous. This may involve consideration of objective and subjective criteria by experts who have their own particular set of criteria, their own preference format for assessing alternatives under these criteria, and who may themselves be assigned differing importance weights as experts. This paper presents a cumulative belief degree approach to cope with heterogeneous information in multiple attribute GDM problems. The proposed approach focuses to aggregate subjective expert assessments and objective criteria that are presented in various representation formats and scales. The methodology employs transformation formulae for several preference representation scales to belief structure, including 2‐tuple representation, classical fuzzy sets, hesitant fuzzy sets, and intuitionistic fuzzy sets. Aggregation formulae are proposed to combine expert criteria evaluations and find a collective preference. A consensus degree is calculated for measuring the agreement between the experts. An illustrative example is presented to clarify the steps of the methodology, and validity of the approach is assured through comparative analysis with the existing methods.     

Nanoparticles shape effects on peristaltic transport of nanofluids in presence of magnetohydrodynamics

Magnetohydrodynamics plays important role to manipulate the physiological fluids due to magnetic nature of physiological fluids. Magnetohydrodynamics pumps are a robust technology which provide more elegant and sustainable performance compared with conventional medical pumps. To study the effects of suspension of the nanoparticles (drugs) in physiological fluids (blood) flow are important in biomedical science and engineering. Motivated by such applications, an analytical approach is presented to study the nanoparticle shape effects on peristaltic transport of nanofluids in presence of magnetohydrodynamics in the present article. A two dimensional continuity, momentum and energy equations are considered to govern the present biophysical model. The governing equations are also linearized using lubrication theory where we consider the low Reynolds number and long wavelength approximations. Closed form solutions are obtained for axial velocity, axial pressure gradient, temperature, pressure rise, wall shear stress and stream function. The effects of three different type of shapes (bricks, cylinders, and platelets) of nanoparticles on peristaltic pumping characteristics and thermal characteristics are computed with the help of graphical illustrations. The interesting outcomes of this study are relevant to more realistic designs for ocular peristaltic pumps in drug delivery systems.