Advances in Design by Metallic Materials: Synthesis, Characterization, Simulation and Applications

Very recently, a great deal of attention has been paid by researchers and technologists to trying to eliminate metal materials in the design of products and processes in favor of plastics and composites. After a few years, it is possible to state that metal materials are even more present in our lives and this is especially thanks to their ability to evolve. This Special Issue is focused on the recent evolution of metals and alloys with the scope of presenting the state of the art of solutions where metallic materials have become established, without a doubt, as a successful design solution thanks to their unique properties

Maximum power point tracking using P&O control optimized by a neural network approach: a good compromise between accuracy and complexity

In the field of power optimization of photovoltaic panels (PV), there exist many maximum power point tracking (MPPT) control algorithms, such as: the perturb and observe (P&O) one, the algorithms based on fuzzy logic and the ones using a neural network approaches. Among these MPPT control algorithms, P&O is one of the most widely used due to its simplicity of implementation. However, the major drawback of this kind of algorithm is the lack of accuracy due to oscillations around the PPM. Conversely, MPPT control using neural networks have shown to be a very efficient solution in term of accuracy. However, this approach remains complex. In this paper we propose an original optimization of the P&O MPPT control with a neural network algorithm leading to a significant reduction of the computational cost required to train it, ensuring a good compromise between accuracy and complexity. The algorithm has been applied to the models of two different types of solar panels, which have been experimentally validated

Maximum power point tracking using P&O control optimized by a neural network approach: a good compromise between accuracy and complexity

In the field of power optimization of photovoltaic panels (PV), there exist many maximum power point tracking (MPPT) control algorithms, such as: the perturb and observe (P&O) one, the algorithms based on fuzzy logic and the ones using a neural network approaches. Among these MPPT control algorithms, P&O is one of the most widely used due to its simplicity of implementation. However, the major drawback of this kind of algorithm is the lack of accuracy due to oscillations around the PPM. Conversely, MPPT control using neural networks have shown to be a very efficient solution in term of accuracy. However, this approach remains complex. In this paper we propose an original optimization of the P&O MPPT control with a neural network algorithm leading to a significant reduction of the computational cost required to train it, ensuring a good compromise between accuracy and complexity. The algorithm has been applied to the models of two different types of solar panels, which have been experimentally validated

Thermomechanical processing of 34CrNiMo6 steel for Large Scale Forging

This work simulated the thermo-mechanical processing of large-scale forging product made of 34CrNiMo6 steel to evaluate the effect of different processing condition parameters and cooling rates on the variation of microstructure and the final mechanical properties. Through this investigation we tried to achieve the required mechanical properties for deep sea applications, which were a minimum Charpy impact value of 38J at temperature of -20 °C according to ABS specifications and a minimum surface hardness of 302 HB according to First Subsea specification design. Initially, a series of single and multi-hit plane strain compression tests were performed to evaluate the hot-deformed microstructure in thermo-mechanical processing, with particular attention paid to the effect of austenitising temperature and deformation conditions of temperature, strain and strain rate. The exponential law, power law and hyperbolic sine law types of Zener–Hollomon equations were utilised to calculate the hot activation energy of deformation (Qdef). In addition the constitutive equations were used for modelling and generalising the DRV and DRX flow curves of 34CrNiMo6 steel, using the method proposed by Avrami. Secondly, a heat treatment process using different austenitising temperatures and different cooling rates was also investigated to achieve the required aims, in which many tests were performed through controlling the temperatures, soaking times, and cooling rates to study the effect of the heat treatment parameters on the grain size and transformation behaviour of austenite. Additionally, to attempt to refine the austenite grain size and to increase the austenite phase percentage within the microstructure, multiple heat treatment paths were also used. A double normalizing, double quenching, and single tempered process were used in all possible combinations to investigate their influence on the final microstructure in an attempt to identify the most effective heat treatment cycle with an effective sequence for the heat treatment operations

Advances in Plastic Forming of Metals

The forming of metals through plastic deformation comprises a family of methods that produce components through the re-shaping of input stock, oftentimes with little waste. Therefore, forming is one of the most efficient and economical manufacturing process families available. A myriad of forming processes exist in this family. In conjunction with their countless existing successful applications and their relatively low energy requirements, these processes are an indispensable part of our future. However, despite the vast accumulated know-how, research challenges remain, be they related to the forming of new materials (e.g., for light-weight transportation applications), pushing the boundaries of what is doable, reducing the intermediate steps and/or scrap, or further enhancing the environmental friendliness. The purpose of this book is to collect expert views and contributions on the current state-of-the-art of plastic forming, thus highlighting contemporary challenges and offering ideas and solutions

Microstructure and Corrosion Behavior of Advanced Alloys

In many industrial applications, metallic materials are exposed to harsh operating conditions. Due to a combination of chemical and thermal stresses, the constructional and functional materials are degraded, and their utility properties are lost. These undesirable events are of a physicochemical nature and are commonly known as ‘corrosion’. In this Special Issue Book, 3 reviews and 18 original research papers focused on the complex relationships between the microstructure, phase constitution, and corrosion behavior of metallic materials are collected. Both high temperature and low temperature corrosion studies are included as they investigate the physicochemical processes at the material interfaces. Furthermore, possibilities for increasing the corrosion resistance of metallic materials are studied by means of surface modification and application of protective layers. This Special Issue Book, Microstructure and Corrosion Behavior of Advanced Alloys, displays the diversity and complexity of modern corrosion research. It is hoped that it will become a valuable source of reference for corrosion scientists