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The purpose of this study is to investigate the application of non-destructive testing methods in measuring bearing oil film thickness to ensure that bearings are in a normal lubrication state. The oil film thickness is a crucial parameter reflecting the lubrication status of bearings, directly influencing the operational state of bearing transmission systems. However, it is challenging to accurately measure the oil film thickness under traditional disassembly conditions due to factors such as bearing structure and working conditions. Therefore, there is an urgent need for a nondestructive testing method to measure the oil film thickness and its status.

This paper introduces methods for optically, electrically and acoustically measuring the oil film thickness and status of bearings. It discusses the adaptability and measurement accuracy of different bearing oil film measurement methods and the impact of varying measurement conditions on accuracy. In addition, it compares the application scenarios of other techniques and the influence of the environment on detection results.

Ultrasonic measurement stands out due to its widespread adaptability, making it suitable for oil film thickness detection in various states and monitoring continuous changes in oil film thickness. Different methods can be selected depending on the measurement environment to compensate for measurement accuracy and enhance detection effectiveness.

This paper reviews the basic principles and latest applications of optical, electrical and acoustic measurement of oil film thickness and status. It analyzes applicable measurement methods for oil film under different conditions. It discusses the future trends of detection methods, providing possible solutions for bearing oil film thickness detection in complex engineering environments.

Although, numerous optimization algorithms have been devoted to construct an electrical ladder network model (ELNM), they suffer from some frail points such as insufficient accuracy as well as the majority of them are unconstrained, which result in optimal solutions that violate certain security operational constraints. For this purpose, this paper aims to propose a flexible-constraint coyote optimization algorithm; the novelty lies in these points: penalty function is introduced in the objective function to discard any unfeasible solution, an advanced constraint handling technique and empirical relationship between the physical estimated parameters and their natural frequencies.

Frequency response analysis (FRA) is very significant for transformer winding diagnosis. Interpreting results of a transformer winding FRA is quite challenging. This paper proposes a new methodology to synthesize a nearly unique ELNM physically and electrically coupled for power transformer winding, basing on K-means and metaheuristic algorithm. To this end, the K-means method is used to cluster the setting of control variables, including the self-mutual inductances/capacitances, and the resistances parameters. Afterward, metaheuristic algorithm is applied to determine the cluster centers with high precision and efficiency.

FRA is performed on a power transformer winding model. Basing on the proposed methodology, the prior knowledge in selecting the initial guess and search space is avoided and the global solution is ensured. The performance of the abovementioned methodology is compared using evaluation expressions to verify its feasibility and accuracy.

The proposed method could be generalized for diagnosis of faults in power transformer winding.

This paper aims to introduce a new numerical model that predicts the flashover voltage (FOV) value in the presence of polluted air surrounding a high-voltage insulator. The model focuses on simulating the propagation of arcs and aims to improve the accuracy and reliability of FOV predictions under these specific conditions.

This arc propagation method connecting the high voltage fitting and the grounded insulator cap involves a two-step process. First, the electric field distribution in the vicinity of the insulator is obtained using finite element method analysis software. Subsequently, critical areas with intense electric field strength are identified. Random points within these critical areas are then selected as initial points for simulating the growth of electric arcs.

by increasing the electric voltage applied to the insulator fittings, the arc path is, step by step, generated until a breakdown occurs on the polluted air surrounding the insulator surface, and thus a prediction of the FOV value.

The proposed model for the FOV prediction can be a very interesting alternative to dangerous and costly experimental tests requiring an investment in time and materials.

Some works were done trying to reproduce discharge propagation but it was always with simplified models such as propagation in one direction from a point to a plane. The difficulty and the originality of the present work is the geometry complexity of the insulator with arc propagation in three distinct directions that will require several proliferation conditions.

The utilisation of renewable energy sources for generating electricity and potable water is one of the most sustainable approaches in the current scenario. Therefore, the current research aims to design and develop a novel co-generation system to address the electricity and potable water needs of rural areas.

The cogeneration system mainly consists of a solar parabolic dish concentrator (SPDC) system with a concentrated photo-voltaic module at the receiver for electricity generation. It is further integrated with a low-temperature thermal desalination (LTTD) system for generating potable water. Also, a novel corn cob filtration system is introduced for the pre-treatment to reduce the salt content in seawater before circulating it into the receiver of the SPDC system. The designed novel co-generation system has been numerically and experimentally tested to analyse the performance at Karaikal, U.T. of Puducherry, India.

Because of the pre-treatment with a corn cob, the scale formation in the pipes of the SPDC system is significantly reduced, which enhances the efficiency of the system. It is observed that the conductivity, pH and TDS of seawater are reduced significantly after the pre-treatment by the corncob filtration system. Also, the integrated system is capable of generating 6–8 litres of potable water per day.

The integration of the corncob filtration system reduced the scaling formation compared to the general circulation of water in the hoses. Also, the integrated SPDC and LTTD systems are comparatively economical to generate higher yields of clean water than solar stills.

The aim of this study is to investigate the usability of horsetail, sunflower stalk, wheat stalk and corn stalk ashes as additives in paints and their performance against corrosion resistance when used.

The ashes of horsetail, sunflower stalk, wheat stalk and corn stalk were investigated in this study in single, binary and ternary combinations with three different percentages as additives in paints. Samples of concrete with any combinations of ashes resisted against the corrosion of steel reinforcements, but horsetail ash proved to be the most effective.

It can be said that these research results show that the paint containing horsetail ash is an excellent coating material that can be used in paints for the corrosion resistance of steel in reinforced concrete. The corrosion rate decreased with the increase in the amount of reactive SiO₂. There was less mass loss with the formation of resistance against corrosion in the horsetail ash added concretes. That is why horsetail ash is one of the most effective options for the aforementioned purpose.

Being cheap and easily obtainable, the materials used for coating in this study are perfect candidates for industrial use.

The purpose of the paper is to showcase the significant achievements of Egypt's scientists in the 20th century across various fields of study such as medicine, physics, chemistry, biology, math, geology, astronomy and engineering. The paper highlights the struggles and successes of these scientists, as well as the cultural, social and political factors that influenced their lives and work. The aim is to inspire young people to pursue careers in science and make their own contributions to society by presenting these scientists as role models for hard work and dedication. Ultimately, the paper seeks to promote the importance of science and its impact on society.

The purpose of this review is to present the scientific biographies of Egypt's most distinguished scientists, primarily in the field of Natural Sciences, in a balanced and comprehensive manner. The work is objective, honest and abstract, avoiding any bias or exaggeration. The author provides a clear and concise methodology, including a brief introduction to the scientist and their field of study, an explanation of their major contributions, the impact of their work on society, any challenges or obstacles faced during their career and their lasting legacy. The aim is to showcase the important achievements of these scientists, their impact on their respective fields and to inspire future generations to pursue scientific careers.

The group of outstanding scientists in 20th century Egypt were shaped by various factors, including familial upbringing, education, society, political and cultural atmosphere and state support for scientific research. These scientists made significant contributions to various academic disciplines, including medicine, physics, chemistry, biology, mathematics and engineering. Their impact on their communities and cultures has received international acclaim, making them role models for future generations of scientists and researchers. The history of these scientists highlights the importance of educational investments and supporting scientific research to foster innovation and social progress. The encyclopedia serves as a useful tool for students, instructors and education professionals, preserving Egypt's scientific heritage and honouring the scientists' outstanding accomplishments.

The encyclopedia preserves Egypt's scientific heritage, which has been overlooked for political or other reasons. It is a useful tool for a variety of readers, including students, instructors and education professionals, and it offers insights into universally relevant scientific success factors as well as scientific research methodologies. The encyclopedia honours the outstanding scientific accomplishments of Egyptian researchers and their contributions to the world's scientific community.

The practical implications of this paper are several. First, it highlights the importance of education, family upbringing and societal support for scientific research in fostering innovation and social progress. Second, it underscores the need for continued funding and support for scientific research to maintain and build upon the accomplishments of past generations of scientists. Third, it encourages young people to pursue scientific careers and make their own contributions to society. Fourth, it preserves the scientific heritage of Egypt and honors the contributions of its outstanding scientists. Finally, it serves as a useful tool for students, instructors and education professionals seeking to understand the factors underlying scientific success and research methodologies.

The social implications of the paper include promoting national pride and cultural identity, raising awareness of the importance of education and scientific research in driving social progress, inspiring future generations of scientists and researchers, reducing socioeconomic disparities and emphasizing the role of society, politics and culture in shaping scientific researchers' personalities and interests.

The paper's originality/value lies in its comprehensive documentation of the scientific biographies of Egypt's most prominent scientists in the 20th century, providing unique insights into the factors that contributed to their development and their impact across various academic disciplines. It preserves Egypt's scientific heritage and inspires future generations of scientists and researchers through the promotion of educational investments and scientific research. The encyclopedia serves as a useful tool for education professionals seeking to understand scientific success factors and research methodologies, emphasizing the importance of supportive and inclusive environments for scientific development.

To prevent the coil from burning or getting damaged, it is necessary to estimate the duration of its operation as long as its temperature does not exceed the permissible limit. This paper aims to investigate the effect of switching on the thermal behavior of impregnated and nonimpregnated windings. Also, the safe operating time for each winding is determined.

The power loss of the winding is expressed as a function of the winding specifications. Using homogenization techniques, the equivalent thermal properties for the homogenized winding are calculated and used in a proposed thermal equivalent circuit for winding modeling and analysis. The validity and accuracy of the proposed model are determined by comparing its analysis results and simulation and measurement results.

The results show that copper windings have better thermal behavior and lower temperature compared to aluminum windings. On the other hand, by impregnating or increasing the packing factor of the winding, the thermal behavior is improved. Also, by choosing the right duty cycle for the winding current source, it is possible to prevent the burning or damage of the winding and increase its lifespan. Comparing the measurement results with the analysis results shows that the proposed equivalent circuit has an error of less than 4% in the calculation of the winding center temperature.

In this paper, the effect of temperature on the electrical resistance of the coil is ignored. Also, rectangular wires were not investigated. Research in these topics are considered as future work.

By calculating the thermal time constant of the winding, its safe operation time can be calculated so that its temperature does not exceed the tolerable value (150 °C). The proposed method analyzes both impregnated and nonimpregnated windings with various schemes. It investigates the effects of switching on their thermal behavior. Additionally, it determines the safe operating time for each type of winding.

As one of the tomographic imaging techniques, electrical capacitance tomography (ECT) is widely used in many industrial applications. While most ECT sensors have electrodes placed around a cylindrical chamber, the planar ECT sensor has been investigated for depth and defect detection. However, the planar ECT sensor has limited height and depth sensing capability due to its single-sided assessment with the use of only a single-plane design. The purpose of this paper is to investigate a dual-plane miniature planar 3D ECT sensor design using the 3 × 3 matrix electrode array.

The sensitivity map of dual-plane miniature planar 3D ECT sensor was analysed using 3D visualisation, the singular value decomposition and the axial resolution analysis. Then, the sensor was fabricated for performance analysis based on 3D imaging experiments.

The sensitivity map analysis showed that the dual-plane miniature planar 3D ECT sensor has enhanced the height sensing capability, and it is less ill-posed in 3D image reconstruction. The dual-plane miniature planar 3D ECT sensor showed a 28% improvement in reconstructed 3D image quality as compared to the single-plane sensor set-up.

The 3 × 3 matrix electrode array has been proposed to use only the necessary electrode pair combinations for image reconstruction. Besides, the increase in number of electrodes from the dual-plane sensor setup improved the height reconstruction of the test sample.

Nonlinear solution approaches for inverse problems require fast simulation techniques for the underlying sensing problem. In this work, the authors investigate finite element (FE) based sensor simulations for the inverse problem of electrical capacitance tomography. Two known computational bottlenecks are the assembly of the FE equation system as well as the computation of the Jacobian. Here, existing computation techniques like adjoint field approaches require additional simulations. This paper aims to present fast numerical techniques for the sensor simulation and computations with the Jacobian matrix.

For the FE equation system, a solution strategy based on Green’s functions is derived. Its relation to the solution of a standard FE formulation is discussed. A fast stiffness matrix assembly based on an eigenvector decomposition is shown. Based on the properties of the Green’s functions, Jacobian operations are derived, which allow the computation of matrix vector products with the Jacobian for free, i.e. no additional solves are required. This is demonstrated by a Broyden–Fletcher–Goldfarb–Shanno-based image reconstruction algorithm.

MATLAB-based time measurements of the new methods show a significant acceleration for all calculation steps compared to reference implementations with standard methods. E.g. for the Jacobian operations, improvement factors of well over 100 could be found.

The paper shows new methods for solving known computational tasks for solving inverse problems. A particular advantage is the coherent derivation and elaboration of the results. The approaches can also be applicable to other inverse problems.

The purpose of this paper is to develop an appropriate machine learning model for predicting soil compaction degree while also examining the contribution rates of three influential factors: moisture content, electrical conductivity and temperature, towards the prediction of soil compaction degree.

Taking fine-grained soil A and B as the research object, this paper utilized the laboratory test data, including compaction parameter (moisture content), electrical parameter (electrical conductivity) and temperature, to predict soil degree of compaction based on five types of commonly used machine learning models (19 models in total). According to the prediction results, these models were preliminarily compared and further evaluated.

The Gaussian process regression model has a good effect on the prediction of degree of compaction of the two kinds of soils: the error rates of the prediction of degree of compaction for fine-grained soil A and B are within 6 and 8%, respectively. As per the order, the contribution rates manifest as: moisture content > electrical conductivity >> temperature.

By using moisture content, electrical conductivity, temperature to predict the compaction degree directly, the predicted value of the compaction degree can be obtained with higher accuracy and the detection efficiency of the compaction degree can be improved.