Frequency Spectrum Research Articles

Influences of blockage ratio and Reynolds number on the spatiotemporal dynamics around a rectangular prism

Particle image velocimetry is used to experimentally investigate the influence of blockage ratio (BR) and Reynolds number (Re) on the turbulent flow around a rectangular prism with depth-to thickness ratio of 3. The prism was selected because it falls within the intermediate regime where the turbulent dynamics is sensitive to the incoming boundary condition. The tested blockage ratios were 2.5%, 5%, and 10% at Reynold numbers of 3000 and 7500. The results are analyzed in terms of the mean flow, turbulent kinetic energy (TKE), frequency spectra, reverse flow area, as well as spectral proper orthogonal decomposition (SPOD). The results indicate that as blockage ratio and/or Reynolds number increase, the tendency of reattachment of the separated shear layer onto the surface of the prism increases while the location of maximum TKE over the prism shifts toward the leading edge, indicating earlier transition of the separated shear layer from laminar to turbulence. For the cases without mean reattachment over the side faces of the prisms, the separated bubble over and downstream of the prism exhibits strong tendency of synchronization in terms of the instantaneous areas of the flow reversal, suggesting a global instability mechanism encompassing the entire prism. In cases with mean flow reattachment, conversely, the low-frequency flapping motion manifests over the prism. SPOD analysis further shows that the relevant shedding dynamics are captured in the first mode and the von Kármán shedding structures have the highest energy.

Attitude motion classification of resident space objects using light curve spectral analysis

The characterization of Earth-orbiting objects in terms of attitude motion, material composition, and shape is crucial for Space Domain Awareness. In this respect, light curves, i.e., graphs showing the brightness variation of space objects over a specific time interval, can be used to infer both their dynamical and physical properties. However, such light curve inversion problem is challenging due to measurement noise, data gaps, and the intrinsic difficulty in separating the multiple effects impacting on the object’s brightness. Existing light curve inversion methods rely on estimation filters exploiting data fusion, Machine Learning approaches, or are based on the analysis of the light-curve frequency spectra. Many of these approaches make assumptions about a-priori knowledge of target object’s characteristics, such as shape, size, surface reflective properties, and/or observation parameters, e.g., target’s orbit and observation geometry. In this framework, this paper presents an innovative architecture for the classification of the attitude motion of space objects using only photometric light curve data, not requiring any a-priori assumption or knowledge. The proposed architecture exploits the Lomb-Scargle Periodogram algorithm to retrieve a frequency spectrum from light curve measurements, and then performs the classification by analyzing the spectrum characteristics testing different candidate rotation periods through the Phase Dispersion Minimization method. The proposed classification algorithm is first tested using a light curve simulator, in which any complex geometric model and different surface properties can be generated. Finally, the method is applied to real light curves retrieved from a publicly available database to assess the classification performance.

Optimising Sensor Placement for Tool Condition Monitoring: A Comparative Analysis of Acoustic Emission Data

In the monitoring of machining processes and in the context of tool condition monitoring, the position of acoustic emission sensors affects the quality of the resulting information. This drives this comparative study which presents a comparison of acoustic emission data recorded simultaneously by a sensor attached to the side of the milling table and another sensor near the spindle during a tool wear test on a CNC milling machine. The signal information is clearly influenced by the different positions. Whereas the signals near the spindle are dominated by vibrations of the spindle motor during machining, these strong contributions do not occur in the recorded data of the machining process detected by the sensor mounted to the table. However, the position of the sensor near the spindle has the advantage of maintaining a constant distance to the source of the acoustic emissions of the machining process, as the sensor moves with the tool. In contrast, the sensor attached to the milling table is affected from the fact that the distance to the milling tool is constantly changing. This results in different dominant frequencies, that are analysed in this study. To analyse both the entire frequency range and the higher frequencies, two distinct approaches are employed, one without and one with the use of a high-pass filter. Furthermore, the recorded signals were used to calculate the characteristic features, namely the Partial Powers, thereby enabling assessment of the condition of the tool. The results demonstrate that this single feature type is sufficient for training a machine learning model to predict the tool wear, focusing on the flank wear width. This study analyses the efficiency of wear prediction with respect to both sensors and frequency spectra, and compares the results. In this context, the most accurate predictions were achieved with Gaussian process regression models.

Dynamic acoustic vowel distances within and across dialects.

Vowels vary in their acoustic similarity across regional dialects of American English, such that some vowels are more similar to one another in some dialects than others. Acoustic vowel distance measures typically evaluate vowel similarity at a discrete time point, resulting in distance estimates that may not fully capture vowel similarity in formant trajectory dynamics. In the current study, language and accent distance measures, which evaluate acoustic distances between talkers over time, were applied to the evaluation of vowel category similarity within talkers. These vowel category distances were then compared across dialects, and their utility in capturing predicted patterns of regional dialect variation in American English was examined. Dynamic time warping of mel-frequency cepstral coefficients was used to assess acoustic distance across the frequency spectrum and captured predicted Southern American English vowel similarity. Root-mean-square distance and generalized additive mixed models were used to assess acoustic distance for selected formant trajectories and captured predicted Southern, New England, and Northern American English vowel similarity. Generalized additive mixed models captured the most predicted variation, but, unlike the other measures, do not return a single acoustic distance value. All three measures are potentially useful for understanding variation in vowel category similarity across dialects.

Models of the Sea Surface Height Expression of the Internal-Wave Continuum

Abstract Several models are presented for the sea surface height (SSH) signature of the interior-ocean internal-wave continuum. Most are based on the Garrett–Munk internal-wave model. One is derived from the frequency spectrum of dynamic height from mooring observations. The different models are all plausibly consistent with accepted dynamical and semiempirical spectral descriptions of the climatological interval-wave field in the interior ocean, but they result in different proportionalities between interior and SSH spectral energy levels. The differences arise in part from differences in the treatment of near-surface stratification, and a major source of uncertainty for all the models comes from inadequately constrained assumptions about the energy in the low-vertical-mode internal-wave field. Most of these models suggest that the SSH signature of the internal-wave continuum will be visible in SSH measurements from the Surface Water and Ocean Topography (SWOT) wide-swath satellite altimeter. Temporal variability of internal-wave energy levels and the internal-wave directional spectrum are less well characterized but will also be consequential for the observability of internal-wave signals in SWOT data.

The use of pulsating jet impingement to minimize temperature oscillations caused by fluctuating heat-flux boundary conditions

Thermal cycling poses a significant challenge in modern applications employing semiconductor devices such as power electronics, owing to the dynamic heat dissipation encountered across diverse operational conditions. The oscillatory variation between peak and low temperatures can induce thermal fatigue, thereby compromising long-term reliability. To address this issue, an innovative approach involving intermittent pulsation of jets has emerged as a promising solution to mitigate peak temperatures and attenuate temperature fluctuations within acceptable limits. This paper presents a comprehensive numerical investigation into the efficacy of intermittent jet impingement in minimizing temperature fluctuations arising from transient heat-flux boundary conditions across a frequency spectrum ranging from 1 to 25 Hz. Comparative analysis against steady jets reveals that intermittent jet pulsation enables superior control over maximum temperature thresholds. An enhancement factor is introduced to quantitatively assess the effectiveness of intermittent jet pulsation, elucidating that up to 8.2 Hz, the reduction in temperature oscillation is notably enhanced compared to higher frequencies. A reduced model is developed to facilitate estimation of transient heat-transfer coefficients during the off period of the jet, shedding light on the underlying mechanisms driving enhanced heat transfer under intermittent jet conditions due to vorticity rings.

Asymmetric instability of flow-induced vibration for elastically mounted cube at moderate Reynolds numbers

The asymmetric instability in two streamwise orthogonal planes for three-dimensional flow-induced vibration (FIV) of an elastically mounted cube at a moderate Reynolds number of 300 is numerically investigated in this paper. The full-order computational fluid dynamics method, data-driven stability analysis via the eigensystem realization algorithm and the selective frequency damping method and total dynamic mode decomposition (TDMD) are applied here to explore this problem. Due to the unsteady non-axisymmetric wakefield formed for flow passing a stationary cube, the FIV response was found to exhibit separate structural stability and oscillations (including lock-in and galloping behaviour) in the two different streamwise orthogonal planes while the body is released. The initial kinetic energy accompanying the release of the cube could destabilize the above-mentioned structural stability. The observed FIV asymmetric instability is verified by the root trajectory of the structural mode obtained via data-driven stability analysis. The stability of the structural modes dominates regardless of whether the structural response oscillates significantly in various (reduced) velocity ranges. Further TDMD analysis on the wake structure, accompanied by the time–frequency spectrum of time-history structural displacements, suggested that the present FIV unit with galloping behaviour is dominated by the combination of the shifted base-flow mode, structure modes and several harmonics of the wake mode.

An ultra-broadband low profile modified chessboard metasurface with improved backscattering reduction

Building upon the concepts of polarization conversion and the mechanism of destructive interference, a single-layered ultra-broadband metasurface for radar cross-section (RCS) or backscattering reduction is proposed in this work. A diffusion-assisted checkerboard metasurface with re-tailored unit cells at the center leads to a significant improvement in the stealth characteristics. For this, a low profile and less complex unit cell is proposed, comprising a long metallic strip along the diagonal and two thin horizontal stubs at the edges. This unique arrangement exhibits more than 90% polarization conversion efficiency from 13.2 to 38.2 GHz. Modifying the geometry of central elements in a conventional checkerboard metasurface achieves a minimum of 15 dB RCS reduction from 10 to 38 GHz. Also, as we ascend the frequency spectrum, the beams are scattered in unintended directions with reduced signal strength. Notably, there is no beam in the boresight direction, as opposed to the conventional chessboard configurations. For off-normal incidences, the metasurface exhibits good angular stability, and a minimum of 10 dB backscattering reduction is maintained up to an incidence angle variation of 60°. The final optimized fabricated prototype exhibits measurement results that agree with the simulation results for normal and wide-angle incidences.

Unsteady numerical study on the effects of inlet distortion parameters on the aerodynamic instability of the centrifugal compressor

Total pressure inlet distortion significantly impairs the aerodynamic performance and flow stability of centrifugal compressors. This paper presents a full annulus unsteady numerical simulation to investigate the flow mechanisms under varying inlet distortion parameters. First, the flow characteristics of a uniform inflow is studied as a baseline for comparison with distorted inlet conditions. Results indicate that the interaction between shock waves and tip leakage flow is a primary factor leading to aerodynamic instability. The instability signal in this region is detected through fast Fourier transform and frequency slice wavelet transform (FSWT). Under near stall condition, different distortion parameters are set to research the effects on aerodynamic performance, flow mechanisms, and instability characteristics. The results reveal that distortion intensity has the most significant impact, causing a maximum stall margin loss of 55.43%, followed by distortion angle with a maximum stall margin loss of 43.02%. Total pressure inlet distortion leads to a deterioration in aerodynamic performance, primarily due to premature occurrences of unstable flow phenomena such as leading-edge spillage and trailing-edge backflow. The onset key features triggering aerodynamic instability are identified as leading-edge spillage vortex, tip leakage vortex, and passage vortex. The continuous disintegration of the tip leakage vortex results in low-frequency fluctuating energy exhibiting multipeak characteristics, with pulsation peaks centered around 0.5 BPF, related to the spike stall of the compressor. The high-energy frequency band dissipates over time in the time–frequency spectrum, as shown by FSWT results, indicating the characteristics of instability in the flow.

Influence of momentum ratio on heat release rate and noise of co/counter-swirl non-premixed diluted CO/H2 flames

Understanding co/counter-swirl or twin-swirl flames remains challenging due to the complex interaction of two swirling streams. In the present study, we investigate the heat release features of non-premixed co/counter-swirl syngas/air flames and their’ influence on combustor noise in a ∼20 kW combustor using simultaneous high-speed OH*-chemiluminescence (5 kHz) and microphone measurement (50 kHz) by varying the momentum ratio (M) from 0.4 to 0.95. Furthermore, the velocity field is examined using a low-speed two-dimensional particle image velocimetry (2D-PIV, frequency = 7 Hz). For all studied momentum ratios, the frequency spectra of noise measurements for both co/counter-swirl flames consistently exhibit a dominant frequency (∼285 Hz), close to the fundamental axial mode of the combustor. A further analysis using spectrograms, phase spaces, and recurrence plots reveals intermittent patterns in noise measurements, featuring periodic (P) and aperiodic regions (A). In periodic regions (P), noise synchronizes with the global fluctuation of the heat release rate as observed in chemiluminescence. Along with global fluctuation, the chemiluminescence also reveals a rotational component of heat release rate with distinct frequencies for co and counter-swirl configurations. This rotational motion possibly originated from a precessing vortex core (PVC) as indicated by the zig-zag arrangements of vortices in the inner shear layer. Furthermore, the impact of M on global fluctuation and rotational motion has been investigated using the frequency spectrum of OH*-intensity and the distribution of peaks in noise measurement. The global fluctuation is found to be suppressed when M increases while the rotational component becomes prominent at higher M. Therefore, the study elucidates the co-existence of global fluctuation and rotational motion and how these motions evolve with the varying momentum ratio (M), thus enhancing the understanding of combustion characteristics of the complex twin-swirl (co/counter-swirl) flames.

Enhanced breast tumor localization with DRA antenna backscattering and GPR algorithm in microwave imaging

With the rapid rate of increasing breast cancer cases across the globe and restrictions of existing early stage detection techniques, microwave imaging based cancer and malignant cell diagnosing methodology is finding its way. Microwave imaging technology has higher accuracy of detection in the variation of tissue properties. In this article, a dielectric resonator based wide band antenna is designed and investigated for microwave imaging (MWI) of early breast cancer detection due to its improved accuracy. The designed antenna has compact size, broad frequency spectrum, high gain and broadside radiation characteristics. To attain the wider bandwidth from (6.5 GHz–12.5 GHz), two rectangular shaped dielectric slabs are used. Wide band microwave frequency band supports the high resolution images. A C-shaped defected ground structure is used to tune the impedance matching. Dielectric resonator based antenna has higher gain and reduces the squints in antenna impedance. Two-asymmetrical dielectric slabs contribute in the excitation of different resonating modes which in turn enhance the bandwidth. It also contributes to excite multiple resonance mode that in turn enhance the bandwidth. Antenna performance is first numerically and experimentally verified in free space. Then, simulation based performance is examined for the microwave imaging. Numerical phantom with equivalent tissue properties is designed with and without the tumor. Unhealthy cells have higher water percentage and larger dielectric constant as compared to healthy cells. It causes the different in the back scattered signal of antenna, which is analyzed to diagnose the tumor or cancer. Here, a maximum deviation of 16 dB is observed in the backscattered signal. Furthermore, surface of the breast tissue is scanned along the x-axis and y-axis at different angels. The collected signals are used to reconstruct the microwave image of the interior. Mean value data of backscattered signals is used to locate the existence of unhealthy cells and GPR algorithm is used to calculate the depth of a 4 mm tumor in breast tissue. Proposed structure has shown efficient performance for microwave imaging.

Instability and ultra-high frequency spectrum pulse train in passively Q-switched Yb:LuAG ceramic laser

Instability and ultra-high frequency spectrum pulse train in passively Q-switched Yb:LuAG ceramic laser

Influence of back pressure adjustment of porous media on cavity flow noise control

Control of self-sustained oscillation and noise reduction poses a significant challenge. The present study employs Implicit Large Eddy Simulation at a Mach number of 0.85 to investigate the influence of a porous cavity floor on flow dynamics. By substituting the solid floor with porous media, the fundamental pressure–velocity relationship within the medium is established according to Darcy's law. Findings reveal marked suppression of wall pulsations, accompanied by a 10 dB decrease in sound pressure levels. The porous medium induces blowing and suction effects, effectively modulating large-scale re-circulation and mitigating shear layer instability, thereby approximating free mixing layer characteristics and suppressing cavity flow oscillations. At an optimized porosity for maximum noise reduction, altering back pressure at the cavity floor induces a transition in the local flow regime from suction-dominated to blowing-dominated state. Excessive reduction of back pressure promotes suction; conversely, increased pressure intensifies blowing, further attenuating feedback mechanisms and enhancing noise reduction. To explore noise reduction mechanisms, mode decomposition analyses demonstrate the efficacy of porous media in disrupting large-scale coherence structures within shear layer and redistributing energy from dominant modes to a broader frequency spectrum that engages smaller flow structures. This energy reallocation mechanism contributes to the mitigation of cavity flow noise and deepens insights into the role of porous media in flow modulation and noise control.

Mathematical modeling of sound propagation through the respiratory tract in a modified gas environment

The aim of the work was to develop a mathematical model of sound propagation through the human respiratory tract when breathing certain respiratory gas mixtures. We based the model on an assembler model of branching of the respiratory tract. For calculations, we presented the human tracheobronchial tree in the form of an equivalent T-shaped cut section diagram, which includes parameters of the walls of the respiratory tract. We carried the simulation out in two main stages. At the first stage, we calculated the impedance of the flow from the small airways to the larger airways. At the second stage, we calculated the sound pressure caused by breathing. As a result, we obtained the curves of the impedance dependence on the frequency spectrum, as well as the sound power from the respiratory flow. We noted that when breathing air, the impedance value remains constant with increasing frequency. Moreover, we also noted that when exposed to a heavier gas than air, the impedance value constantly increases, and when exposed to lighter gases, after reaching a maximum, the impedance value decreases. We found that the highest sound pressure is typical for the oxygen-krypton mixture, and the lowest for the oxygen–helium mixture. We also found that in the case of modeling the laminar flow regime (with a critical Reynolds number equal to 1800), sound affects how many generations of bronchi more than in the case of modeling the transient flow regime (with a critical Reynolds number equal to 2700). Thus, we drew conclusions about the influence of the physical properties of gaseous media on the amount of sound pressure and the propagation of sound through the human respiratory tract.

Image quality improvement in single plane-wave imaging using deep learning

In ultrasound image diagnosis, single plane-wave imaging (SPWI), which can acquire ultrasound images at more than 1000 fps, has been used to observe detailed tissue and evaluate blood flow. SPWI achieves high temporal resolution by sacrificing the spatial resolution and contrast of ultrasound images. To improve spatial resolution and contrast in SPWI, coherent plane-wave compounding (CPWC) is used to obtain high-quality ultrasound images, i.e., compound images, by coherent addition of radio frequency (RF) signals acquired by transmitting plane waves in different directions. Although CPWC produces high-quality ultrasound images, their temporal resolution is lower than that of SPWI. To address this problem, some methods have been proposed to reconstruct a ultrasound image comparable to a compound image from RF signals obtained by transmitting a small number of plane waves in different directions. These methods do not fully consider the properties of RF signals, resulting in lower image quality compared to a compound image. In this paper, we propose methods to reconstruct high-quality ultrasound images in SPWI by considering the characteristics of RF signal of a single plane wave to obtain ultrasound images with image quality comparable to CPWC. The proposed methods employ encoder–decoder models of 1D U-Net, 2D U-Net, and their combination to generate the high-quality ultrasound images by minimizing the loss that considers the point spread effect of plane waves and frequency spectrum of RF signals in training. We also create a public large-scale SPWI/CPWC dataset for developing and evaluating deep-learning methods. Through a set of experiments using the public dataset and our dataset, we demonstrate that the proposed methods can reconstruct higher-quality ultrasound images from RF signals in SPWI than conventional method.

Kinematic Analysis of the Vibration Harvesting Process of Lycium barbarum L. Fruit

The traditional shrub fruits harvesting method is manual picking, while the efficiency is low, which seriously restricts the development of Lycium barbarum L. industry. In order to mechanize the harvesting process of Lycium barbarum L. and improve the correct picking rate while reducing the damage rate of Lycium barbarum L. harvesting, it is very important to analyze the kinematic model of the fruit-bearing branch during vibration harvesting. Through the measurement and analysis of the natural characteristics and physical parameters of the branches, a simplified model of Lycium barbarum L. shrub fruit-bearing branch was built by Solidworks 2023 software, and the appropriate material properties were selected. Through modal analysis and harmonious response analysis, the response characteristics data of fruit-bearing branches of Lycium barbarum L. shrub were obtained. In Qinghai Nuomuhong Farm, the field vibration harvesting kinematic model feature analysis test was carried out, and the acceleration data of the vibration harvesting process were collected by using the acceleration sensor, and through the analysis of the frequency spectrum characteristics of the data, it was concluded that when the excitation frequency was maintained between 8 and 14 Hz, the Lycium barbarum L. fell off well and the picking rate can reach 97.56%, the efficiency can reach 6.88 pieces of fruit per second, and the branch damage was acceptable, which theoretically met the needs of harvesting.

Tuning ferroelectric domains and polarization properties of flexible BiFeO3 thin films by phase transition engineering

In the present investigation, thin films of flexible (Bi1-xSmx)(Fe0.95Mn0.05)O3 (denoted as BSFM0, BSFM4, BSFM8, and BSFM12 for x=0 %, 4 %, 8 %, and 12 %, respectively) were synthesized on metallic Ni-Cr substrates via the sol-gel technique. A comprehensive examination was conducted to elucidate the influence of varying concentrations of Sm3+ substitution on the phase constitution, oxygen vacancy concentration, and leakage behavior of the (Bi1-xSmx)(Fe0.95Mn0.05)O3 films. Utilizing X-ray diffraction (XRD) and Raman spectrometry, it was ascertained that all films exhibited a composite structure comprising orthorhombic (Pnma) and rhombohedral (R3c) phases. An augmentation in Sm3+ doping led to a non-monotonic variation in the R3c phase content, initially increasing and subsequently decreasing, while the nonpolar Pnma phase demonstrated a progressive enhancement. The distorted R3c phase was found to promote the flipping of the domain architecture, thereby augmenting the polarization attributes. Notably, at a Sm doping level of 4 %, the maximum polarization (Pmax) attained was 95 μC/cm2, with a remnant polarization (Pr) of 78 μC/cm2. The incorporation of a judicious amount of Sm was observed to curtail film leakage and decelerate the aging phenomenon. The compositional stability of this doping level was evaluated across a frequency spectrum of 0.1–12 kHz and a temperature gradient of 25–200 °C, revealing no propensity for degradation under conditions of polarization, a holding duration of 104 s, or fatigue scenarios involving a curvature of 5 mm and 108 switching cycles subjected to 103 instances of bending. These findings provide innovative insights for the development of next-generation lead-free transducer apparatus and flexible information storage mediums.

Sound Source Identification of Vehicle Noise Based on a Microphone Array With a Modified Multiple Signal Classification Algorithm

In this paper, a modified multiple signal classification (MUSIC) algorithm tailored for sound source identification (SSI) of vehicle noise is introduced and experimentally validated. A uniform planar microphone array (UPMA) is formulated for mathematical modeling, with its SSI-oriented parameters selected based on the primary frequency spectrum of vehicle noise. Simulations are conducted to compare the SSI accuracy of two conventional spatial spectra estimation (SSE) algorithms: the Capon algorithm and the MUSIC algorithm. The results demonstrate that the MUSIC algorithm, which relies on the eigenvalues of a covariance matrix to estimate signal direction, exhibits superior SSI resolution under low signal-to-noise ratio (SNR) conditions. However, it faces challenges in distinguishing between coherent or closely spaced signals. To address this, a modified MUSIC algorithm is proposed by reconstructing the covariance matrix of received signals and the SSE function. Simulation outcomes indicate that the modified MUSIC significantly outperforms the conventional version, owing to its enhanced SSI resolution. The accuracy of the SSI system, incorporating the UPMA and the modified MUSIC, is verified using a low-frequency volume source. Ultimately, the devised SSI system is successfully deployed to identify noise sources in a vehicle at different operational conditions, further validating the efficacy of the modified MUSIC. The UPMA and the modified MUSIC presented in this study have direct applicability in vehicle noise source identification and may be extended to other sound-related engineering fields for SSI purposes.

Microwave diagnostics of flare plasma by the direct fitting method based on data from the Siberian Radioheliograph

In this paper, we analyze images and the frequency spectrum of microwave emission in the maximum of brightness distribution in the January 20, 2022 and July 16, 2023 flares recorded by the Siberian Radioheliograph in the 3–6 GHz and 6–12 GHz ranges. We use the obtained spectrum data for radio diagnostics of magnetic field strength and orientation, plasma density, and parameters of accelerated particles in a radio source. The radio diagnostics is carried out by a method based on minimizing the functional containing the intensities of theoretically calculated and observed frequency spectra of left-polarized and right-polarized emission. Since the form of such a multidimensional functional is quite complex, and it is not possible to minimize it by standard approaches, we employ a genetic minimization method. The radio diagnostics allows us to determine features of the dynamics of the magnetic field intensity and orientation, as well as the density and the energy spectral index of non-thermal electrons in the region of maximum brightness of the radio source. We have found that during the growth phase of the main radiation peaks the magnetic field decreases, whereas during the decay phase, on the contrary, it increases. The rate of these changes varies from a few G/s to 11 G/s for the January 20, 2022 flare and is about 1 G/s for the July 16, 2023 flare.

Микроволновая диагностика вспышечной плазмы методом фитирования по данным Cибирского радиогелиографа

In this paper, we analyze images and the frequency spectrum of microwave emission in the maximum of brightness distribution in the January 20, 2022 and July 16, 2023 flares recorded by the Siberian Radioheliograph in the 3–6 GHz and 6–12 GHz ranges. We use the obtained spectrum data for radio diagnostics of magnetic field strength and orientation, plasma density, and parameters of accelerated particles in a radio source. The radio diagnostics is carried out by a method based on minimizing the functional containing the intensities of theoretically calculated and observed frequency spectra of left-polarized and right-polarized emission. Since the form of such a multidimensional functional is quite complex, and it is not possible to minimize it by standard approaches, we employ a genetic minimization method. The radio diagnostics allows us to determine features of the dynamics of the magnetic field intensity and orientation, as well as the density and the energy spectral index of non-thermal electrons in the region of maximum brightness of the radio source. We have found that during the growth phase of the main radiation peaks the magnetic field decreases, whereas during the decay phase, on the contrary, it increases. The rate of these changes varies from a few G/s to 11 G/s for the January 20, 2022 flare and is about 1 G/s for the July 16, 2023 flare.