To improve the corrosion-resistant properties of carbon steel cladding process is usually used. It is a process of depositing a thick layer of corrosion resistant material-over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long-term reliability and performance. By cladding, these properties can be achieved with minimum cost. The main problem faced in cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, contact tip to work distance, and pinch) to get optimum dilution in stainless steel cladding of low-carbon structural steel plates using gas metal arc welding (GMAW). Experiments were conducted based on central composite rotatable design with full-replication technique and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. Using particle swarm optimization (PSO) the parameters were optimized to get minimal dilution.
To improve the corrosion resistant properties of carbon steel, usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long-term reliability and performance. By cladding these properties can be achieved with minimum cost. The main problem faced on cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, and contact tip to work distance and pinch) to get optimum dilution in stainless steel cladding of low carbon structural steel plates using gas metal arc welding (GMAW). Experiments were conducted based on central composite rotatable design with full replication technique, and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. In this study, artificial neural network (ANN) and genetic algorithm (GA) techniques were integrated and labeled as integrated ANN-GA to estimate optimal process parameters in GMAW to get optimum dilution.
Smart materials are materials with properties that can be significantly altered in a controlled fashion by external stimuli, such as stress, temperature, pH, moisture, electric or magnetic fields. An elastomer comprising a matrix interspersed with micron sized ferromagnetic particles is known as a Magnetorheological Elastomer (MRE). The rheological properties of MREs are altered by the application of an external magnetic field. The characteristic response of MRE is influenced by many factors including; the elastomer matrix, the size, distribution, composition and percentage volume of the ferromagnetic particles, and whether the ferromagnetic particles are aligned in chains or randomly dispersed. During the past two decades the interest in intelligent material based solutions has shown a huge growth. Present work deals with the study of preparation method of Magnetorheological Elastomer mould and testing for its dynamic behaviour. Micron size iron particles are used for the preparation of MRE in order to increase number of iron particles in elastomer matrix. Two different types of MRE moulds are prepared and their dynamic response has been studied. Comparison has been done between MRE mould cured with magnetic field and without magnetic field by testing them with and without application of magnetic field. The results obtained are satisfactory and can be applied for automotive sector to reduce noise and vibrations.
Dynamic mechanical properties are the mechanical properties of materials as they are deformed under periodic forces. These properties can be expressed via dynamics modulus, the loss modulus and a mechanical damping or internal friction. This paper describes investigations on dynamic mechanical analysis of Magnetorheological Elastomer cured with and without magnetic field. Sylgard's 184 Silicone Elastomer has been used with 5 micron size iron particle. Viscoelastic properties such as storage modulus (E'), loss modulus (E"), damping, were compared for with and without magnetic field curing.
In the past several years, there has been increased market place awareness of noise, vibration, and harshness performance in automobiles. The differentiation between the quality and reliability levels of automobiles has become less pronounced and, as a result, manufacturers have had to demonstrate superiority by focusing on NVH concerns. The automotive industry is currently spending millions of dollars on NVH work to develop new materials and damping techniques so that the damping treatments are lighter, cheaper, and more effective. Some of the methods used to control noise, vibration, and harshness includes the use of different carpeting treatments, the addition of rubber or asphalt material to car panels, gap sealant, and the injection of expandable foam into body panels. The aim of this study is to explore the feasibility of smart damping materials such as magnet orheological elastomers (MRE), piezoelectric materials, with its basic properties, for augmenting and improving the performance benefits of damping materials. This study also evaluates the noise and vibration benefits of smart damping materials as compared to conventional damping treatments.
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