Pavel Karban

Contemporary beam-forming antenna arrays often use a large number of individual elements, sometimes hundreds or more, to achieve high gain for advanced applications like radar, space communication, and next-gen cellular networks. These arrays are complex and costly due to the need for precise amplitude and phase adjustments across the elements. The feeding network complexity leads to signal losses, reduced efficiency, and higher noise. Current research aims to simplify arrays, reduce active elements needing frontends, and streamline the feeding network, considering non-uniform, sparse, parasitic, or reflective arrays. Challenges arise from element coupling and imperfect models of high-frequency materials and electronic components. Therefore, in addition to simulations, practical experimentation remains vital. This paper focuses on designing a novel $3 \times 3$ element antenna array with digital quantized control. We explore the impact of quantized control on beamforming and plan to validate simplified orthogonal optimization methods with limited quantization depth. The proposed antenna array is applicable to 2400 MHz band research, including arrays with parasitic elements and switchable polarization for individual elements.

Hysteresis loops constitute the source of important information for the designers of magnetic circuits in power transformers. The paper focused on the possibility to interpret the phenomenological T(x) model in terms of effective field vs. magnetization dependence. The interdependence of anhysteretic curve and hysteresis loops was emphasized. The concept of the anhysteretic plane introduced at the end of the last century by Sablik and Langman was subject to a tangible interpretation within the hyperbolic model framework. A novel geometric interpretation of the “effective field” related to the concept of affine transformation was introduced. It was shown in the paper that minor hysteresis loops of grain-oriented electrical steel may be described with the proposed formalism.

There is a great potential in small satellite technology for testing new sensors, processes, and technologies for space applications. Antennas need careful design when developing a small satellite to establish stable communication between the ground station and the satellite. This work is motivated by the design of an antenna array for a future rotatorless base station for the VZLUSAT group of Czech nano-satellites. The realized antenna array must cover a relatively broad range of elevation and azimuth angles, and the control must be fast enough to track the satellite in low Earth orbits. The paper deals with possibilities of synthesis of quantized control of the antenna array. It compares quantization influence for well-known deterministic synthesis methods. It shows the method for decreasing computational cost of synthesis using optimization approach and presents the multi-criteria optimization as a tool for reaching required radiation pattern shape and low sensitivity to quantization at the same time.

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.

Since large power transformers are custom-made, and their design process is a labor-intensive task, their design process is split into different parts. In tendering, the price calculation is based on the preliminary design of the transformer. Due to the complexity of this task, it belongs to the most general branch of discrete, non-linear mathematical optimization problems. Most of the published algorithms are using a copper filling factor based winding model to calculate the main dimensions of the transformer during this first, preliminary design step. Therefore, these cost optimization methods are not considering the detailed winding layout and the conductor dimensions. However, the knowledge of the exact conductor dimensions is essential to calculate the thermal behaviour of the windings and make a more accurate stray loss calculation. The paper presents a novel, evolutionary algorithm-based transformer optimization method which can determine the optimal conductor shape for the windings during this examined preliminary design stage. The accuracy of the presented FEM method was tested on an existing transformer design. Then the results of the proposed optimization method have been compared with a validated transformer design optimization algorithm.

Since large power transformers are custom-made, and their design process is a labor-intensive task, their design process is split into different parts. In tendering, the price calculation is based on the preliminary design of the transformer. Due to the complexity of this task, it belongs to the most general branch of discrete, non-linear mathematical optimization problems. Most of the published algorithms are using a copper filling factor based winding model to calculate the main dimensions of the transformer during this first, preliminary design step. Therefore, these cost optimization methods are not considering the detailed winding layout and the conductor dimensions. However, the knowledge of the exact conductor dimensions is essential to calculate the thermal behaviour of the windings and make a more accurate stray loss calculation. The paper presents a novel, evolutionary algorithm-based transformer optimization method which can determine the optimal conductor shape for the windings during this examined preliminary design stage. The accuracy of the presented FEM method was tested on an existing transformer design. Then the results of the proposed optimization method have been compared with a validated transformer design optimization algorithm.

The main goal of the Artap project is to provide an extensive infrastructure for robust design optimization, where usually many different numerical solvers have to be used together and the impact of the manufacturing uncertainties have to be minimized. Artap is an open-source software platform, developed jointly with the coupled numerical field solver, Agros Suite. Artap ensures interfaces for a broad collection of optimization algorithms (genetic and evolutionary algorithms, various interfaces to libraries such as Nlopt, Bayesopt, etc .), tools for machine learning (neural networks, Gaussian processes, etc. ), finite element solvers (Agros Suite, Comsol, Multiphysics, deal.II). The implemented tools offers an easy and straightforward solution not only for robust design optimization but parameter identification, model order reduction, and shape optimization, as well. Moreover, Artap provides automatic parallelization of the optimization process. The paper presents the structure of the framework and technologies powering the project. The main features of Artap are demonstrated on an induction brazing process design tasks.

A novel technique of optimizing selected models of electroheat processes (laser or induction-assisted laser welding, cladding, and so on) is presented, based on the calibration of temperature-dependent material properties. These properties often exhibit uncertainties that negatively influence the quality of the results. Their calibration starts from experimental investigation and evaluation of temperature profiles of welds or tracks, and the goal is to obtain the same profiles by solving the numerical models. The technique is illustrated with an example of induction-assisted laser welding.