Additional Feedstock for Fluid Catalytic Cracking Unit

Fuel refineries are configured with Fluid Catalytic Cracking Unit (FCCU) to convert Vacuum Gas Oils (VGO) into higher value gasoline and middle distillates. But such refineries also generate 8-12% of heavy oils known either as decant oil or clarified oil (CLO), which has to be downgraded as furnace oil. The recycling of the decant oil into FCCU along with VGO feed is restricted to maintain the coke formation within design limits so that there is no decrease either in conversion or yield of liquid products from FCC operations. The condensed aromatic ring compounds present in CLO makes it undesirable feedstock for cracking, as it promotes heavy coke formation on the catalyst. Hence, CLO is disposed by absorbing in the residual fuel oils.

Of late, FCC units are being operated with higher severity to maximize gasoline, and this has resulted in much higher concentration of condensed aromatics in CLO. Hence, better utilization of CLO depends on separating its saturated hydrocarbon components as a good feedstock for recycling into FCCU with the simultaneous production of extract with enriched poly condensed aromatics as a value added product, namely Carbon Black Feed Stock (CBFS). This article describes several extraction studies carried out on CLO to obtain raffinate for which cracking studies were carried out in automated Micro Activity Test (MAT) unit. The quality of extract phase from each of the above studies was evaluated for its suitability as feedstock for carbon black.     

Optimization of microstructure development: application to hot metal extrusion

A new process design method for controlling microstructure development during hot metal deformation processes is presented. This approach is based on modern control theory and involves state- space models for describing the material behavior and the mechanics of the process. The challenge of effectively controlling the values and distribution of important microstructural features can now be systematically formulated and solved in terms of an optimal control problem. This method has been applied to the optimization of grain size and certain process parameters such as die geometry profile and ram velocity during extrusion of plain carbon steel. Various case studies have been investigated, and experimental results show good agreement with those predicted in the design stage.     

A finite element large displacement analysis of stiffened plates

A finite element analysis of the large deflection behaviour of stiffened plates using the isoparametric quadratic stiffened plate bending element is presented. The evaluation of fundamental equations of the stiffened plates is based on Mindlin's hypothesis. The large deflection equations are based on von Kármán's theory. The solution algmrithm for the assembled nonlinear equilibrium equations is based on the Newton-Raphson iteration technique. Numerical solutions are presented for rectangular plates and skew stiffened plates.     

Effect of porous lining on the MHD flow between two concentric rotating cylinders under the influence of a uniform magnetic field

Summary Bénard-Marangoni instabilities are theoretically discussed: emphasis is placed on the role of negative Rayleigh and Marangoni numbers. Marginal, supercritical and subcritical instabilities are respectively examined.The first part is concerned with the response of an unbounded fluid layer with respect to small disturbances. A variational principle describing marginal stability is proposed. Rayleigh-Ritz method is used to obtain approximate solutions for the critical Rayleigh and Marangoni numbers. In a second part, corrections to the linear theory, by including weak nonlinearities, are introduced. The amplitude of the supercritical temperature and velocity fields are calculated in the framework of Stuart's shape approximation. Finally, the possibility of subcritical instability with respect to disturbances of arbitrary amplitude is investigated by the method of energy.With 5 Figures     

Thermochemical studies on SrFe12O19(s)

The citrate-nitrate gel combustion route was used to prepare SrFe₁₂O₁₉(s) powder sample and the compound was characterized by X-ray diffraction analysis. A solid-state electrochemical cell of the type: (−)Pt, O₂(g)/{CaO(s) + CaF₂(s)}//CaF₂(s)//{SrFe₁₂O₁₉(s) + SrF₂(s) + Fe₂O₃(s)}/O₂(g), Pt(+) was used for the measurement of emf as a function of temperature from 984 to 1151 K. The standard molar Gibbs energy of formation of SrFe₁₂O₁₉(s) was calculated as a function of temperature from the emf data and is given by: (SrFe₁₂O₁₉, s, T)/kJ mol⁻¹ (±1.3) = −5453.5 + 1.5267 × (T/K). Standard molar heat capacity of SrFe₁₂O₁₉(s) was determined in two different temperature ranges 130-325 K and 310-820 K using a heat flux type differential scanning calorimeter (DSC). A heat capacity anomaly was observed at 732 K, which has been attributed to the magnetic order-disorder transition from ferrimagnetic state to paramagnetic state. The standard molar enthalpy of formation, (298.15 K) and the standard molar entropy, (298.15 K) of SrFe₁₂O₁₉(s) were calculated by second law method and the values are −5545.2 kJ mol⁻¹ and 633.1 J K⁻¹ mol⁻¹, respectively.     

Thermal Stability of Ge<Subscript>2</Subscript>Sb<Subscript>2</Subscript>Te<Subscript>5</Subscript> in Contact with Ti and TiN

The thermal stability of a Ge₂Sb₂Te₅ chalcogenide layer in contact with titanium and titanium nitride metallic thin films has been investigated mainly using x-ray diffraction and elastic nuclear backscattering techniques. Without breaking vacuum, Ti and TiN have been deposited on Ge₂Sb₂Te₅ material using magnetron sputtering. Thermal treatments have been performed in a 10⁻⁷ mbar vacuum furnace. On annealing up to 450°C, the TiN metallic film does not interact with the chalcogenide film, but at the same time adhesion problems and instabilities in contact resistance arise. To improve the adhesion and eventually stabilize the contact resistance, an interfacial Ti layer has been considered. At 300°C, a TiTe₂ compound is formed by interacting with Te segregated from the Ge₂Sb₂Te₅ layer. At higher temperatures, the Ti layer decomposes the chalcogenide film, forming several compounds tentatively identified as GeTe, Ge₃Ti₅, Ge₅Ti₆, TiTe_2,, and Sb₂Te₃. It has been found that the properties of the Ge₂Sb₂Te₅ film can be retained by controlling the decomposition rate of the chalcogenide layer, which is achieved by providing a limited supply of Ti and/or by depositing a Te-rich Ge₂Sb₂Te₅ film.     

Formation of As–As Interlayer Bonding in the cT Phase of EuFe<Subscript>2</Subscript>As<Subscript>2</Subscript> and CeFeAsO Under Pressure from First Principle

The electronic band structure and structural phase stability of EuFe₂As₂ and CeFeAsO compounds were studied using the full-potential linearized augmented plane wave (FP-LAPW) method implemented using WIEN2k. To calculate the structural stability and phase transition of these compounds, the total energies have been computed as a function of reduced volumes and fitted with the Birch–Murnaghan equation. The calculated lattice parameters are found to be in agreement with the available experimental data. The present results show that EuFe₂As₂ and CeFeAsO compounds undergo structural phase transition from body-centered tetragonal (BCT) into collapsed tetragonal (cT) and tetragonal (T) into cT phase under pressure. The calculated phase transition pressures are in agreement with recent experimental data. The calculated valence charge density of collapsed tetragonal phase reveals that As–As interactions found to be stronger under pressure.     

A Novel Deep Neural Network for Intracranial Haemorrhage Detection and Classification

Data fusion is one of the challenging issues, the healthcare sector is facing in the recent years. Proper diagnosis from digital imagery and treatment are deemed to be the right solution. Intracerebral Haemorrhage (ICH), a condition characterized by injury of blood vessels in brain tissues, is one of the important reasons for stroke. Images generated by X-rays and Computed Tomography (CT) are widely used for estimating the size and location of hemorrhages. Radiologists use manual planimetry, a time-consuming process for segmenting CT scan images. Deep Learning (DL) is the most preferred method to increase the efficiency of diagnosing ICH. In this paper, the researcher presents a unique multi-modal data fusion-based feature extraction technique with Deep Learning (DL) model, abbreviated as FFE-DL for Intracranial Haemorrhage Detection and Classification, also known as FFEDL-ICH. The proposed FFEDL-ICH model has four stages namely, preprocessing, image segmentation, feature extraction, and classification. The input image is first preprocessed using the Gaussian Filtering (GF) technique to remove noise. Secondly, the Density-based Fuzzy C-Means (DFCM) algorithm is used to segment the images. Furthermore, the Fusion-based Feature Extraction model is implemented with handcrafted feature (Local Binary Patterns) and deep features (Residual Network-152) to extract useful features. Finally, Deep Neural Network (DNN) is implemented as a classification technique to differentiate multiple classes of ICH. The researchers, in the current study, used benchmark Intracranial Haemorrhage dataset and simulated the FFEDL-ICH model to assess its diagnostic performance. The findings of the study revealed that the proposed FFEDL-ICH model has the ability to outperform existing models as there is a significant improvement in its performance. For future researches, the researcher recommends the performance improvement of FFEDL-ICH model using learning rate scheduling techniques for DNN.     

Acoustics and rheological studies of aqueous ethylene glycol blend copper oxide nanofluids

Experimental investigations have been performed to synthesize copper oxide nanoparticles by conventional chemical precipitation method and nanofluids were prepared by two-step method using CuO nanoparticles in different proportions of ethylene glycol–water mixtures (EG–water). Powder X-ray diffraction (PXRD), energy dispersive X-ray (EDX), scanning electron microscope (SEM), particle size, and zeta potential analysis have been studied to characterize both solid and fluid samples for their sizes, shapes, stability, and arrangement. Besides, acoustics and rheological properties such as ultrasonic velocity, density, and viscosity have been measured for all fluid samples at three different temperatures. Interpretations of all these parameters have been made on the basis of particle stability and dispersion capacity of nanoparticles in different proportions of base fluids. The variation of dynamic viscosity with shear rate shows the nanofluids to be behaved like non-Newtonian fluids at very less shear rate but shows Newtonian behavior as the shear rate increases.