This chapter discusses leading problems linked to energy that the world is now confronting and to propose some ideas concerning possible solutions. Oil deserves special attention among all energy sources. Since the beginning of 1981, it has merely been continuing and enhancing the downward movement in consumption and prices caused by excessive rises, especially for light crudes such as those from Africa, and the slowing down of worldwide economic growth. Densely-populated oil-producing countries need to produce to live, to pay for their food and their equipment. If the economic growth of the industrialized countries were to be 4%, even if investment in the rational use of energy were pushed to the limit and the development of nonpetroleum energy sources were also pursued actively, it would be extremely difficult to prevent a sharp rise in prices. It is evident that it is absolutely necessary to pursue actively the development of coal, natural gas, and nuclear power if a physical shortage of energy is not to block economic growth.

World energy outlook

System Identification I

Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories Alternative teaching approaches are more inductive Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

The author details the reactions of various concretes on steel reinforcement. Although portland cements, slag cements and high alumina cements are all hydraulic binders, each possess special properties which are examined. The discussion of causes and methods of preventing the corrosion of steel reinforcement covers such aspects as galvanised steel reinforcement, effects of concrete composition, corrosion of steel reinforcments in concrete and prestressed reinforcement. It is concluded that the most significant influences on the corrosion of prestressing wire in concrete are: the presence of chloride; the presence of nitrates; the composition of the concrete; the degree of carbonation of the concrete; concrete compaction and, chlorides and sulphates should be used as far as possible when steel is embedded. (TRRL)

Corrosion of steel by concrete

Encyclopedia of Life Support Systems (EOLSS)

The bio-inspired algorithms are novel, modern, and efficient tools for the design of electrical machines. However, from the mathematical point of view, these problems belong to the most general branch of non-linear optimization problems, where these tools cannot guarantee that a global minimum is found. The numerical cost and the accuracy of these algorithms depend on the initialization of their internal parameters, which may themselves be the subject of parameter tuning according to the application. In practice, these optimization problems are even more challenging, because engineers are looking for robust designs, which are not sensitive to the tolerances and the manufacturing uncertainties. These criteria further increase these computationally expensive problems due to the additional evaluations of the goal function. The goal of this paper is to give an overview of the widely used optimization techniques in electrical machinery and to summarize the challenges and open problems in the applications of the robust design optimization and the prospects in the case of the newly emerging technologies.

Robust Design Optimization and Emerging Technologies for Electrical Machines: Challenges and Open Problems

A review of the fault diagnostic techniques based on machine is presented in this paper. As the world is moving towards industry 4.0 standards, the problems of limited computational power and available memory are decreasing day by day. A significant amount of data with a variety of faulty conditions of electrical machines working under different environments can be handled remotely using cloud computation. Moreover, the mathematical models of electrical machines can be utilized for the training of AI algorithms. This is true because the collection of big data is a challenging task for the industry and laboratory because of related limited resources. In this paper, some promising machine learning-based diagnostic techniques are presented in the perspective of their attributes.

Trends and Challenges in Intelligent Condition Monitoring of Electrical Machines Using Machine Learning

Recent studies show that synchronous reluctance motors (SynRMs) present promising technologies. As a result, research on trending SynRMs drive systems has expanded. This work disseminates the recent developments of design, modeling, and more specifically, control of these motors. Firstly, a brief study of the dominant motor technologies compared to SynRMs is carried out. Secondly, the most prominent motor control methods are studied and classified, which can come in handy for researchers and industries to opt for a proper control method for motor drive systems. Finally, the control strategies for different speed regions of SynRM are studied and the transitions between trajectories are analyzed.

https://www.mdpi.com/2071-1050/13/2/729/pdf

A Review of Synchronous Reluctance Motor-Drive Advancements

Since electrical machines are the largest consumer of electricity worldwide, their fault diagnostic at the incipient stage and condition monitoring is essential for better reliability, economy, and safety of operation. Out of several condition monitoring techniques, motor current signature analysis is gaining heightened popularity because of its non-invasive nature, the least number of sensors required and versatility of compatible algorithms. In this study, the best characteristics of infinite impulse response (IIR) filter are exploited to observe the broken rotor bar (BRB) frequencies with good legibility in current and voltage spectrum of the grid and inverter-fed motor, respectively. The causes of various harmonics in the stator current spectrum are first investigated for better understanding. The results are taken based on simulation and measurements taken from the laboratory setup. It is observed that a better tuning of IIR filters can make diagnostic algorithms capable of detecting the frequencies of interest by effectively attenuating the fundamental component and reducing its spectral leakage. Moreover, in case of direct torque control-based industrial inverter-fed motors, the current cannot be a good candidate for fault diagnostics rather the phase voltage can be effectively used for the detection of BRBs.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-epa.2019.0350

Broken rotor bar fault detection of the grid and inverter-fed induction motor by effective attenuation of the fundamental component

This paper presents current research trends and prospects of utilizing additive manufacturing (AM) techniques to manufacture electrical machines. Modern-day machine applications require extraordinary performance parameters such as high power-density, integrated functionalities, improved thermal, mechanical & electromagnetic properties. AM offers a higher degree of design flexibility to achieve these performance parameters, which is impossible to realize through conventional manufacturing techniques. AM has a lot to offer in every aspect of machine fabrication, such that from size/weight reduction to the realization of complex geometric designs. However, some practical limitations of existing AM techniques restrict their utilization in large scale production industry. The introduction of three-dimensional asymmetry in machine design is an aspect that can be exploited most with the prevalent level of research in AM. In order to take one step further towards the enablement of large-scale production of AM-built electrical machines, this paper also discusses some machine types which can best utilize existing developments in the field of AM.

Anton Rassolkin

Papers

Robust Design Optimization and Emerging Technologies for Electrical Machines: Challenges and Open Problems

Trends and Challenges in Intelligent Condition Monitoring of Electrical Machines Using Machine Learning

A Review of Synchronous Reluctance Motor-Drive Advancements

Broken rotor bar fault detection of the grid and inverter-fed induction motor by effective attenuation of the fundamental component

A Review on Additive Manufacturing Possibilities for Electrical Machines