A Comparative Thermodynamic Analysis of Organic Rankine Cycles (ORC) and Kalina Cycle for Low-Grade Energy Resources
Exergy Efficiency and Exergy Destruction Assessment of Heat Transfer and Fluid Flow through Spiral Passages using Source-Sink Model
Innovative Approach: Empowering Contextual Consulting in Industry 4.0 through a Hybrid Data Analytics Framework
Study of Corrosion and its Preventive Measures
Green Hydrogen Feasibility in Oman
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
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
Development and Performance Evaluation of Magnetic Abrasive Finishing Setup for Thick Cylinders
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 main sources of lead in the environment are effluent industries such as electroplating, alloying, smelting, mining, refining, pigmenting, plastic manufacture, and metallurgical industries. A batch experiment as well as an Artificial Neural Network (ANN) coupled with a Genetic Algorithm model for the extraction of lead from wastewater was conducted. In the development of the ANN model, a tan sigmoid transfer function for input and a purelin for output layers have been employed. A feed-forward back propagation with a single layer was used with thirteen neurons in the hidden layer. The optimized process parameters, viz., pH, adsorbent dosage, and initial concentration of lead, have been obtained. Based on the regression coefficient value of R2 of 0.998, it was confirmed that the ANN model predicted data and the experimental value data were a perfect match. The maximum percentage removal of lead was obtained at optimum conditions by means of a pattern search algorithm in GA.
The present paper examines the performance of a resistance heating furnace by measuring the resistance of two different heating elements, namely, Silicon Carbide (SiC) heating rods and Molybdenum Di-Silicide (MoSi2) heating elements, to raise the working chamber temperature to 1600ᴼC for heating the charge materials. SiC rods are used to raise the working chamber temperature, starting from the beginning (ambience) temperature of 35ᴼC up to 1300ᴼC. Then MoSi2 heating elements will be used to raise the chamber temperature from 1300ᴼC to the set temperature at 1600ᴼC. Transition from SiC to MoSi2, heating system is uninterrupted, and swift in heating element effected by inter-locking system (an electronic device or an electro-magnetic system) without any drop in effect. Use of two different heating elements has been tested to achieve many objectives, like saving amperage (current consumption), long life of the heating elements, and optimization of thermal efficiency for high working temperature at 1600ᴼC for long hours. This is achieved by creating resistance to the flow of electrons through an element (a good conductor for electricity as well as heat). Thus, due to high friction, a temperature is developed and heats the charged materials, up to a temperature as high as 1600ᴼC. This method is applied in an environment of air, inert gas, vacuum, etc. with no pollution, for programmable and also for non-programmable types of cycles of operations set before starting the furnace within a maximum working temperature of 1600ᴼC to achieve the objectives of a Compound Heating Resistance (CHR) furnace satisfactorily.
In the last couple of years, the footprints of humankind on the greenhouse effect have been a highlighted and debated topic. There are many contributing factors to the negative impacts on the environment, one of them being the automobile sector. Today, most cars are driven on fossil fuel, which produces toxic emissions. The search for replaceable alternative fuels were considered mainly and the keys to demand are renewable energy and energy-friendly resources. Hydrogen as a fuel, in particular hydrogen gas, is one of the options considering the only residues to be water and hot air, provided that the energy used in the hydrogen production comes from renewable sources. In the storage tanks of cars fueled by hydrogen gas, a high pressure is set due to its advantages of more storage opportunities and thus increased mileage of the tank. A decompression process is necessary to supply the fuel cell with hydrogen gas at the right pressure and thus achieve the highest possible degree of efficiency. The concept offers a wide set of application opportunities in industrial situations, and understanding the valve is important for characterizing the performance of the device. In other words, high performance could be achieved with correct and optimal geometry on the Tesla valve. In this work, the geometric parameters were investigated in order to determine their ideal value for optimizing the performance. The parameters of interest were the optimum operating conditions of the valve. A numerical observation was conducted using simulations in a Computational Fluid Dynamics program, ANSYS Fluent, in order to obtain the results.
Corrosion is a universal natural phenomenon that causes degradation in metal and alloy properties by chemical or electrochemical interaction with their environment. In the United States, the total direct cost of corrosion is estimated at about 300 billion dollars per year, which is about 3.2 percent of the domestic product. This means corrosion has a huge economic loss on national infrastructure, such as bridges, chemical processing, buildings, and waste water treatment. In addition, corrosion not only increases the costs of components, but it is also responsible for life losses or injuries to people, and it reduces the value of goods owing to deterioration of appearance as well as safety hazards. Thus, by retarding either the cathodic or anodic reactions, the rate of corrosion can be reduced by coating, addition of chemical additives (corrosion inhibitors) etc. Hence, the aim of this research paper is to provide an overview of corrosion, its history, importance, classification, and preventive measures.
The need for orthopedic implants is increasing due to the rise in the number of accidents. As people begin to age, they begin to experience pain in their joints, bones, and wrists. If it is not managed with medication, an orthopedic implant may be deemed as the best solution. As per the Bureau of Indian Standard Research, the global market for orthopedic products in 2016 in US dollars was 4.20 billion. Industries seem to have an annual growth rate of 6.1 percent when compared with the previous year, which means the market is expected to reach 61.02 billion dollars by 2023. Therefore, the demand for orthopedic devices is significant and the quality of implants manufactured should be strictly controlled and checked for human health safety worldwide. Nowadays, the regulatory agencies also focus on every medical device manufacturing industry with highly stringent needs. Therefore, the knowledge of standards, validation, and differences between Good Manufacturing Practice (GMP) and Current Good Manufacturing Practice (CGMP) is highly important. Therefore, this paper focuses on the importance of validation in detail for the safety of patients.
