Biomaterial Strategies for Immune System Enhancement and Tissue Healing
Qualitative and Quantitative Performance Optimization of Simple Gas Turbine Power Plant using Three Different Types of Fuel
Efficient Shopping: RFID-Powered Cart with Automated Billing System
Medical Drone System for Automated External Defibrillator Shock Delivery for Cardiac Arrest Patients
A Critical Review on Biodiesel Production, Process Parameters, Properties, Comparison and Challenges
Review on Deep Learning Based Image Segmentation for Brain Tumor Detection
Chemistry and Chemical Engineering: Approaches, Observations, and Outlooks
Integration of PMS Software and Decision Matrix Tool Based on Data Acquired from Latest IT Advanced Sensors and 3D CAD Models in Marine Operations Field
A Series of Tool-Life Studies on Aluminium Matrix Hybrid Composites
Dynamic Changes in Mangrove Forest and Lu/Lc Variation Analysis over Indian Sundarban Delta in West Bengal (India) Using Multi-Temporal Satellite Data
The Impacts of Climate Change on Water Resources in Hilly Areas of Nepal
An Analysis of Machining Forces On Graphite/Epoxy, Glass/Epoxy and Kevlar/Epoxy Composites Using a Neural Network Approach
Deformation Behaviour of Fe-0.8%C-1.0%Si-0.8%Cu Sintered P/M Steel during Powder Preform Forging
A Series of Tool-Life Studies on Aluminium Matrix Hybrid Composites
Achieving Manufacturing Excelence by Applying LSSF Model – A Lean Six Sigma Framework
Design and Analysis of Piezo- Driven Valve-Less Micropump
It is the provision of energy that meets the demands of the present generation without compromising the ability of the future generations to meet their needs. It includes all renewable energy sources such as hydroelectricity, wind energy, solar energy, wave power, geothermal, bio energy and tidal energy. It also includes technologies that are designed to improve energy efficiency. The renewable energy technologies are mainly grouped into three sectors as first, second and third generation technologies. Green energy and energy conservation techniques comes under the category of sustainable energy development. Many European countries employ these techniques in the local level (Canadell, 2007). These techniques are implemented right from energy carriers such as hydrogen and liquid nitrogen carriers. The recent statistic figures show that these green sustainable energies of rapid importance as the planet earth is suffering from global warming. This sustainable energy development has got links with all the sectors of energy such as energy production, conservation, and decrease of pollution and to implement techniques that are eco friendly.
In this paper, an artificial neural network (ANN) model was developed to predict the removal efficiency of Cu (II) from aqueous solution using a custard apple peel powder as adsorbent. The effect of operational parameters such as pH, adsorbent dosage, and initial Cu (II) concentration are studied to optimize the conditions for the maximum removal of Cu (II) ions. Experimentally it was found that adsorption equilibrium is obtained in 60 minutes. The ANN model was developed using 40 experimental data points for training and 14 data points for testing by a single layer feed forward back propagation network with 10 neurons to obtain minimum mean squared error (MSE). A tansigmoid was used as transfer function for input and purelin for output layers. The high correlation coefficient (R2average-ANN =0.989) between the model and the experimental data showed that the model was able to predict the removal of Cu (II) from aqueous solution using custard apple peel powder efficiently. Pattern search method in genetic algorithm was applied to get optimum values of input parameters for the maximum removal of Cu (II).
This paper presents an optimization algorithm called Plant Growth Optimization (PGO) and it is applied for different test functions to evaluate its performance. The PGO is based on the plant growth characteristics in which an artificial plant growth model is built including leaf growth, branching, phototropism, and spatial occupancy. The plant growth process is that a plant grows a trunk from its root; some branches will grow from the nodes on the trunk; and then some new branches will grow from the nodes on the branches. Such process is repeated, until a plant is formed. This process is simulated in this algorithm by producing new points (branch points) from initial points (roots). After producing the new points (branch points), the algorithm searches the optimum solution around these points through the operation called leaf growth (for local search). This is used to ensure the accuracy of the solution. It is one of the evolutionary algorithms like the Genetic algorithm. A MATLAB code for the plant growth optimization algorithm is developed and it is tested for three classical test functions. The results are tabulated and plotted.
Chordwise bending vibration characteristics of rotating double tapered beam have been investigated. Considering the assumed modes method, potential energy and kinetic energy expressions are derived from a set of hybrid deformation variables. The system of equations of motion are derived by using the Lagrange’s approach based on Euler–Bernoulli beam theory. Numerical examples are considered to investigate the effect of taper ratio, hub radius ratio and rotational speed on chordwise bending natural frequencies of the rotating taper beam. To establish the validity of the formulation, initially the results were compared with those of the earlier reported works. It has been observed that the results are in conformity with those reported in the literature.
In this paper, the study of the steady two-dimensional flow of an incompressible viscous fluid with heat and mass transfer and MHD heat generation past a moving vertical plate with suction in the presence of viscous dissipation and chemical reaction is investigated. Using similarity variables, the governing partial differential equations are transformed into non-linear ordinary differential equations. These equations are then solved numerically using fourth order Runge-Kutta method with shooting technique. The flow variables are presented graphically. The graphs showed that velocity rises for increasing Grashof number, mass Grashof numer, suction, heat generation and Eckert number while reducing with increasing magnetic parameter, Schmidt number, and chemical reaction parameter and Prandtl number. Comparisons with previously published work are performed and are found to be in an excellent agreement.