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
The exploration of under utilized plant seeds as sources of industrial oil was the main focus of the work. The research work was carried out to ascertain the viability of seeds of an African star apple as a source of oil for industrial use. Oils were extracted from dried seeds of African star apple using n-hexane by Soxhlet extraction method. A comprehensive range of physicochemical properties, namely: free fatty acid, peroxide value, saponification value, iodine value, and specific gravity were determined. The characterization of the oil was done according to the methods described by the Association of Official Analytical Chemist. The percentage yield of the oil was 2.5%, dark yellow in colour and liquid at room temperature. Saponification value of the oil was 51.45, Iodine value was 19.20, Peroxide value stood at 1.78, and Specific gravity was 0.91. The low yield and values of saponification and iodine show that, the oil is not viable for industrial use.
This paper deals with maximizing the power output from wind turbines over, all the expected wind conditions, while minimizing construction costs. The wind turbine construction is complex due to the design of turbine blades. As such, the authors focus on minimizing the amount of materials required to make the blade, while maximizing the power output. The considered disciplines include, aerodynamics, structures, and control. By considering a range of incoming wind velocities that represents the possible operating conditions of the turbine, the expected power output and extreme structural load over this range can be calculated. To Further limit the design space, the authors made a three-bladed design with PVC (Poly Vinyl Chloride) blades. The authors choose three blades, because, an initial Design of Experiments (DOE) test showed that, the three blades’ performance and efficiency is higher than the four and five-bladed designs in almost all cases. The traditional wind turbine’s cut in speed is 4 m/sec and so, the authors are trying to design a turbine that starts producing power even at a wind speed of 3 m/sec. Designed and fabricated wind turbine with a control system allows it to direct the blades against the wind flowing direction.
Traffic noise introduced by vehicles operating on highways is a major source of discomfort and concern for the population in the vicinity. A number of noise prediction models have been developed over the past 30 years that attempted to model the road condition under study. But, as traffic flow characteristics, road characteristics, geometric parameters etc. are different from what are prevailing in those developed countries, these models cannot be applied directly in its present form. There is a need to check its transferability in order to make it suitable for the prediction of traffic noise on Indian highways. In the present work, the traffic noise on NH – 06 passing through Chhattisgarh have been observed. The traffic noise prediction is done with the help of Federal Highway Administration Model (FHWA) using the traffic volume and speed data recorded at different sampling stations.
This paper tried to check the geographical transferability of the FHWA model on NH-06 passing through Chhattisgarh. In doing so, the study area of NH-06 has been divided into four locations, these locations are Supela (location 1), Power house (location 2), Bhilai III (location 3), and Charoda (location 4). Traffic noise is measured directly with the help of a sound level meter SL 4023SD. It is then compared with the noise level predicted using the FHWA model in terms of the percentage difference and absolute difference. Regression analysis is then performed to get modelled equations. Following are main points regarding the study undertaken for NH-06. The absolute difference between the observed and the predicted traffic noise level is observed in the range of 2.94-6.88 dB(A) for location 1, 0.266-4.47 dB(A) for location 2, 0.58-5.2 dB(A) for location 3, and 0.33-6.3 dB(A) for location 4. As the absolute difference obtained at all four locations are in an acceptable range and the Coefficient of Correlation (R2 ) obtains a value between 0.8 to 1.0, which depicts a good relationship, and therefore, the model can be geographically transferable. The validity of model is checked through statistical analysis using paired t test and also justifies the model developed for NH-06, as the calculated value of t obtained is less than the critical value for a given confidence interval.
Development of Stage-Discharge Rating Curve (SDRC) is of utmost importance for reliable planning, design and management of water resource projects. The SDRC is time dependent and very often exhibits a random phenomenon with fluctuation. For establishing the SDRC, Non-Linear Regression Approach (NLRA) is widely applied to many gauging sites worldwide for many decades. The SDRC is based on power equation that is used to establish a relationship between stage (i.e., water level) and discharge, whose variables can be determined by the method of least squares. In this paper, a study on development of SDRCs for Aamdabad, Nighoje and Wegre gauging sites located in the upper Bhima basin upto Ujjani reservoir is carried out. The performance of the NLRA used for developing the SDRCs is evaluated by correlation coefficient and the mean absolute percentage error. The paper presents the procedures adopted in the development of SDRCs using NLRA and the results obtained thereof.
The metallic wastes released by Industries mainly comprise of heavy metals like Copper, Cadmium, Zinc, Lead, Chromium and Nickel which cannot be degraded and thus contaminate the natural industrial wastewater. Copper is the third most widely used metal in industries next to aluminum and iron and has harmful effects on health and environment. There are numerous methods currently employed to remove and recover these heavy metals from industrial wastewater. Adsorption is one of the alternative methods which can be used for adsorption of heavy metals and is an effective separation technique. Considering the economics, there is an increasing research interest in using alternative low-cost adsorbents. In recent years, Spent Tea Extract (STE) is gaining ground due to its potential to adsorb heavy metals. In the present work, the potential of tea extract as an adsorbent for the adsorption of Cu (II) from synthetic waste industrial water is studied. The percentage adsorption of Cu (II) has been studied with three variables (adsorbent dosage, contact time and solution pH), keeping one constant at a time. Optimum percentage adsorption of Cu (II) is found to be 59.84 % at the adsorbent dosage of 0.5 g (in 50 ml solution), contact time of 60 minutes, pH of 5 and temperature of 30 °C. The result showed that the proposed adsorbent used in this study is very useful for removing Cu (II) from industrial wastewater.
Laser Beam Machining (LBM) is one of the most advanced machining processes that is used for shaping, cutting and machining the virtually whole varieties of engineering materials. In LBM, the surface roughness and kerf taper significant factors affects the product characteristics and quality of the product. During this analysis work, the impact of process parameters like cutting speed, frequency and Gas pressure surface roughness (Ra) of steel (AISI 321 stainless steel) material in laser cutting machining are studied. L9 orthogonal array was generated for fractional factorial design (Taguchi analysis) for better understanding of the interaction among the process parameters. The values of surface roughness for steel were calculated by Regression model equations, and Taguchi Analysis and Genetic Algorithm were employed to the parametric analysis of the experimental data. Taguchi analysis gives the optimum values of surface roughness and kerf taper, which are 2.2981 μm and 0.1637° respectively. Genetic algorithm was used for providing a set of optimum values for both outputs simultaneously.