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Yayın Inductor saturation compensation in three-phase three-wire voltage-source converters via inverse system dynamics(Institute of Electrical and Electronics Engineers Inc., 2022-05-01) Özkan, Ziya; Hava, Ahmet MasumIn three-phase three-wire (3P3W) voltage-source converter (VSC) systems, utilization of filter inductors with deep saturation characteristics is often advantageous due to the improved size, cost, and efficiency. However, with the use of conventional synchronous frame current control methods, the inductor saturation results in significant dynamic performance loss and poor steady-state current waveform quality. This article proposes an inverse dynamic model-based compensation (IDMBC) method to overcome these performance issues. For this purpose, two-phase exact modeling of the 3P3W VSC control system is obtained. Based on the modeling, the inverse system dynamic model of the nonlinear system is obtained and employed such that the nonlinear plant is converted to a virtual linear inductor system for linear current regulators to perform satisfactorily. Further, to control phase currents in the synchronous frame, a two-phase coordinate transformation is proposed. The IDMBC method is tested via dynamic command response and waveform quality simulations and experiments that employ saturable inductors reaching down from full inductance at zero current to 1/9th inductance at full current. The results obtained demonstrate the suitability of the method for 3P3W VSCs employing saturable inductors.Yayın Image recovery of inaccessible rough surfaces profiles having impedance boundary condition(IEEE, 2022) Sefer, Ahmet; Yapar, AliThis letter addresses a reconstruction algorithm of locally rough inaccessible surface profiles via the knowledge of the scattered field data under the consideration of the impedance boundary condition (IBC). To this aim, first, the synthetic scattered field data are obtained through the solution of the conventional surface integral equation (SIE) written on the rough surface. Then, the same SIE together with the data equation is solved iteratively via Newton's method to obtain the image of the rough surface profile. In the numerical implementation, the nonlinear ill-posed inverse problem is linearized in an iterative fashion via the Newton method and regularized by Tikhonov in the least-squares sense. The feasibility of the algorithm is provided via numerical examples, which shows that the method is effective and promising.Yayın On the identification of microstretch elastic moduli of materials by using vibration data of plates(Pergamon-Elsevier Science LTD, 2008-06) Kırış, Ahmet; İnan, EsinIn the present work, the vibration problems of rectangular plates modeled by Eringen's microstretch theory are investigated for the identification of the upper bounds of the microstretch moduli of the plate material. The calculated frequencies of the plates are obtained by extending the Ritz method to the microstretch plates. The three dimensional (3D) vibration analysis of the plates shows that some additional frequencies occur among the classical frequencies as characterizing the microstretch effects. Then it is also observed that these additional frequencies disappear and only the classical frequencies remain with the increasing values of microstretch constants. The inverse problem is established for the identification of the upper bounds of the microstretch elastic constants as an optimization problem where an error function is minimized.Yayın CNN-Based deep learning architecture for electromagnetic imaging of rough surface profiles(IEEE, 2022-10) Aydın, İzde; Budak, Güven; Sefer, Ahmet; Yapar, AliA convolutional neural network (CNN) based deep learning (DL) technique for electromagnetic imaging of rough surfaces separating two dielectric media is presented. The direct scattering problem is formulated through the conventional integral equations and the synthetic scattered field data is produced by a fast numerical solution technique which is based on Method of Moments (MoM). Two different special CNN architectures are designed and implemented for the solution of the inverse rough surface imaging problem wherein both random and deterministic rough surface profiles can be imaged. It is shown by a comprehensive numerical analysis that the proposed deep-learning (DL) inversion scheme is very effective and robust.Yayın Imaging of rough surfaces by RTM method(IEEE, 2024) Sefer, Ahmet; Yapar, Ali; Yelkenci, TanjuAn electromagnetic imaging framework is implemented utilizing a single frequency reverse time migration (RTM) technique to accurately reconstruct inaccessible two-dimensional (2D) rough surface profiles from the knowledge of scattered field data. The unknown surface profile, which is expressed as a 1D height function, is either perfectly electric conducting (PEC) or an interface between two penetrable media. For both cases, it is assumed that the surface is illuminated by a number of line sources located in the upper medium. The scattered fields, which should be collected by real measurements in practical applications, are obtained synthetically by solving the associated direct scattering problem through the surface integral equations. RTM is subsequently applied to generate a cross-correlation imaging functional which is evaluated numerically and provides a 2D image of the region of interest. A high correlation is observed by the functional in the regions where the transitions between two media occur. Hence, it results in the acquisition of the unknown surface profile at the sites where the functional attains its highest values. The efficiency of the proposed method is comprehensively tested by numerical examples covering various types of scattering scenarios.Yayın Recovery of impenetrable rough surface profiles via CNN-based deep learning architecture(Taylor and Francis Ltd., 2022-08-18) Aydın, İzde; Budak, Güven; Sefer, Ahmet; Yapar, AliIn this paper, a convolutional neural network (CNN)-based deep learning (DL) architecture for the solution of an electromagnetic inverse problem related to imaging of the shape of the perfectly electric conducting (PEC) rough surfaces is addressed. The rough surface is illuminated by a plane wave and scattered field data is obtained synthetically through the numerical solution of surface integral equations. An effective CNN-DL architecture is implemented through the modelling of the rough surface variation in terms of convenient spline type base functions. The algorithm is numerically tested with various scenarios including amplitude only data and shown that it is very effective and useful.Yayın Inverse scattering by perfectly electric conducting (PEC) rough surfaces: an equivalent model with line sources(Institute of Electrical and Electronics Engineers Inc., 2022) Sefer, Ahmet; Yapar, AliThis paper presents a new method for the reconstruction of the perfectly electric conducting (PEC) rough surface profiles by utilizing electromagnetic waves. The inaccessible rough surface is illuminated by a tapered plane electromagnetic wave and the scattered field data are measured on a certain number of points above the surface under test. The method for the inverse electromagnetic imaging problem is based on a special representation of the scattered field in terms of a finite number of fictitious discrete line sources located along a plane below the rough surface. The current densities of these fictitious sources are obtained through the regularized solution of an ill-posed problem. Then, it is shown that the image of the rough surface can be directly retrieved by seeking the points in the space where the tangential component of the total electric field vanishes. Alternatively, a much more rigorous iterative method based on a regularized Newton algorithm is also presented. A comprehensive numerical analysis is provided to demonstrate the feasibility of the presented approach. In this context, the quantitative successes of both approaches are interpreted by considering a very sensitive ?2-norm based error function between the actual and the reconstructed surface profiles. Regarding different scattering scenarios taken into account, the error values obtained for satisfactory reconstructions are generally in the range of 10% - 30% for both methods. It is also shown that the presented algorithms are capable of reconstructing the rough surfaces which oscillate for every ? horizontally and have a peak to peak variation 0.5? at most.Yayın A multi-frequency iterative method for reconstruction of rough surfaces separating two penetrable media(Institute of Electrical and Electronics Engineers Inc., 2024-12-18) Sefer, Ahmet; Yapar, Ali; Bağcı, HakanA numerical scheme that uses multi-frequency Newton iterations to reconstruct a rough surface profile between two dielectric media is proposed. At each frequency sample, the scheme employs Newton iterations to solve the nonlinear inverse scattering problem. At every iteration, the Newton step is computed by solving a linear system that involves the Frechet derivative of the integral operator, which represents the scattered fields, and the difference between these fields and the measurements. This linear system is regularized using the Tikhonov method. The multi-frequency data is accounted for in a recursive manner. More specifically, the profile reconstructed at a given frequency is used as an initial guess for the iterations at the next frequency. The effectiveness of the proposed method is validated through numerical examples, which demonstrate its ability to accurately reconstruct surface profiles even in the presence of measurement noise. The results also show the superiority of the multi-frequency approach over single-frequency reconstructions, particularly in terms of handling surfaces with sharp variations.
