Synthesis of nano-TiC powder using titanium gel precursor and carbon particles

The paper presents a novel process for synthesis of nano-size titanium carbide by reaction between titanium bearing precursor gel and nano carbon particles derived from soot at different temperatures in the range of 1300-1580 °C for 2 h under argon cover. The HRTEM studies of TiC powder synthesized by heating at 1580 °C show the presence of cube shaped particles (~ 60-140 nm) and hollow rods (diameter ~ 30-185 nm). The average particle size of crystallites, calculated by Scherer equation is observed to be ~ 35 nm while the surface area-density measurements indicate it to be ~ 113 nm. The surface area decreases with increase in reaction temperature.     

Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing,GIS and MCDM Techniques

Remote sensing (RS) and geographic information system (GIS) are promising tools for efficient planning and management of vital groundwater resources, especially in data-scarce developing nations. In this study, a standard methodology is proposed to delineate groundwater potential zones using integrated RS, GIS and multi-criteria decision making (MCDM) techniques. The developed methodology is demonstrated by a case study in Udaipur district of Rajasthan, western India. Initially, ten thematic layers, viz., topographic elevation, land slope, geomorphology, geology, soil, pre- and post-monsoon groundwater depths, annual net recharge, annual rainfall, and proximity to surface water bodies were considered in this study. These thematic layers were scrutinized by principal component analysis technique to select influential layers for groundwater prospecting. Selected seven thematic layers and their features were assigned suitable weights on the Saaty’s scale according to their relative importance in groundwater occurrence. The assigned weights of the thematic layers and their features were then normalized by using AHP (analytic hierarchy process) MCDM technique and eigenvector method. Finally, the selected thematic maps were integrated by weighted linear combination method in a GIS environment to generate a groundwater potential map. Thus, four groundwater potential zones were identified and demarcated in the study area, viz., ‘good’, ‘moderate’, ‘poor’ and ‘very poor’ based on groundwater potential index values. The area falling in the ‘good’ zone is about 2,113 km² (17% of the total study area), which encompasses major portions of Sarada, Salumber, Girwa, Dhariawad, and Mavli blocks of the study area. The northeast and southwest portions along with some scattered patches fall in the ‘moderate’ zone, which encompasses an area of 3,710 km² (about 29%). The ‘poor’ zone is dominant in the study area which covers an area of 4,599 km² (36% of the total area). The western portion and parts of eastern and southeast portions of the study area are characterized as having ‘very poor’ groundwater potential, and this zone covers an area of 2,273 km² (18%). Moreover, in the ‘good’ zone, the mean annually exploitable groundwater reserve is estimated at 0.026 million cubic metres per km² (MCM/km²), whereas it is 0.024 MCM/km² in the ‘moderate’ zone, 0.018 MCM/km² in the ‘poor’ zone, and 0.013 MCM/km² in the ‘very poor’ zone. The groundwater potential map was finally verified using the well yield data of 39 pumping wells, and the result was found satisfactory.     

Machine Learning Based Resource Allocation of Cloud Computing in Auction

Resource allocation in auctions is a challenging problem for cloud computing. However, the resource allocation problem is NP-hard and cannot be solved in polynomial time. The existing studies mainly use approximate algorithms such as PTAS or heuristic algorithms to determine a feasible solution; however, these algorithms have the disadvantages of low computational efficiency or low allocate accuracy. In this paper, we use the classification of machine learning to model and analyze the multi-dimensional cloud resource allocation problem and propose two resource allocation prediction algorithms based on linear and logistic regressions. By learning a small-scale training set, the prediction model can guarantee that the social welfare, allocation accuracy, and resource utilization in the feasible solution are very close to those of the optimal allocation solution. The experimental results show that the proposed scheme has good effect on resource allocation in cloud computing.     

Entropy generation analysis of free convection radiative MHD Eyring–Powell fluid flow between porous parallel plates with Soret and Dufour effects

In this present study, we have investigated the entropy generation analysis and Dufour and Soret impacts on unsteady incompressible free convective radiative MHD Eyring–Powell fluid flow between parallel plates with periodic injection and suction. The governing PDEs are converted into nondimensional coupled nonlinear ordinary differential equations by using similarity variables then numerically solved by Runge–Kutta fourth-order scheme with shooting technique. The results are discussed in detail for different flow, mass, and heat transfer profiles corresponding to various active parameters and presented in tables and graphs. Also, it is noticed that the temperature profiles are enhanced with the fluid parameter, whereas the concentration profiles are decreased with the Prandtl number. The validations of present results with the existing outcomes for the viscous case of skin friction are included and have found to be in good agreement. The present numerical study is useful for the enhancement of heat transfer in various industrial and chemical processes.     

A study on the local behaviour of steel-concrete interfaces at and around large openings in the PSC inner containment dome

A finite element (FEM) study has been made to know the overall structural behaviour of a PSC inner containment (IC) dome having large steam generator (SG) openings with emphasis on the local behaviour of the steel-concrete interfaces near SG openings, under initial prestress transfer. The primary thrust of the work has been in the objective of predicting the possibilities of separation at the steel-concrete interface zones adjacent to the embedded plates of the SG openings. For the FEM analysis, the interface zone has been modeled using gap elements, the properties of which are derived from the results of the past experiments conducted on steel plate-concrete interface specimens. Important observations have been made regarding dome deformation and the stresses with special emphasis on the local behaviour of steel-concrete interfaces at and around SG openings.