Search Results (3,268)

Cross-validation and open research on future electric grids, particularly in their stability modeling and dynamic performance, can greatly benefit from high-fidelity, publicly available test cases, since access to dynamic response models of actual grid models is often limited due to legitimate security concerns. This paper presents a methodology for designing and validating the dynamic performance of large, IBR-heavy synthetic grids, that is, realistic but fictitious test cases. The methodology offers a comprehensive framework for creating dynamic models for both synchronous generators (SGs) and inverter-based resources (IBRs), focusing on realism, controllability, and flexibility. For realistic dynamic performance, the parameters in each dynamic model are sampled based on statistical data from benchmark actual grids, considering power system dynamics such as frequency and voltage control, as well as oscillation response. The paper introduces system-wide governor design, which improves the controllability of parameters in dynamic models, resulting in a more realistic frequency response. As an example, multiple case studies on a 2000-bus Texas synthetic grid are shown; these represent realistic dynamic performance under different transmission conditions in terms of frequency, voltage control, and oscillation response. Full article

This study investigates the influence of rotation on wave propagation in a semiconducting nanostructure thermoelastic solid subjected to a ramp-type heat source within a two-temperature model. The thermoelastic interactions are modeled using the two-temperature theory, which distinguishes between conductive and thermodynamic temperatures, providing a more accurate description of thermal and mechanical responses in semiconductor materials. The effects of rotation, ramp-type heating, and semiconductor properties on elastic wave propagation are analyzed theoretically. Governing equations are formulated and solved analytically, with numerical simulations illustrating the variations in thermal and elastic wave behavior. The key findings highlight the significant impact of rotation, nonlocal parameters $e_{0}a$, and time derivative fractional order (FO) $\alpha$ on physical quantities, offering insights into the thermoelastic performance of semiconductor nanostructures under dynamic thermal loads. A comparison is made with the previous results to show the impact of the external parameters on the propagation phenomenon. The numerical results show that increasing the rotation rate $\mathsf{\Omega }=5$ causes a phase lag of approximately 22% in thermal and elastic wave peaks. When the thermoelectric coupling parameter ${\mathsf{\epsilon }}_3$ is increased from $-0.8\times {10}^{-42}$ to $1.2\times {10}^{-42}$. The temperature amplitude rises by 17%, while the carrier density peak increases by over 25%. For nonlocal parameter values $\mathsf{\epsilon }=0.3\to 0.6$, high-frequency stress oscillations are damped by more than 35%. The results contribute to the understanding of wave propagation in advanced semiconductor materials, with potential applications in microelectronics, optoelectronics, and nanoscale thermal management. Full article

After primary frequency regulation in large-scale wind farms is completed, the power dip phenomenon occurs during the rotor speed recovery phase. This phenomenon may induce a secondary frequency drop in power systems, which poses challenges to system frequency security. To address this issue, this paper proposes a frequency security-oriented optimal dispatch model for multi-regional power systems, taking into account the risks of secondary frequency drop. In the first stage, risk-averse day-ahead scheduling is conducted. It co-optimizes operational costs and risks under wind power uncertainty through stochastic programming. In the second stage, frequency security verification is carried out. The proposed dispatch scheme is validated against multi-regional frequency dynamic constraints under extreme wind scenarios. These two stages work in tandem to comprehensively address the frequency security issues related to wind power integration. The model innovatively decomposes system reserve power into three distinct components: wind fluctuation reserve, power dip reserve, and contingency reserve. This decomposition enables coordinated optimization between absorbing power oscillations during wind turbine speed recovery and satisfies multi-regional grid frequency security constraints. The column and constraint generation algorithm is employed to solve this two-stage optimization problem. Case studies demonstrate that the proposed model effectively mitigates frequency security risks caused by wind turbines’ operational state transitions after primary frequency regulation, while maintaining economic efficiency. The methodology provides theoretical support for the secure integration of high-penetration renewable energy in modern multi-regional power systems. Full article

An analog joint source-channel coding (AJSCC) based on Shannon–Kotel’nikov (S-K) mapping transmitting discrete-time encoded samples in orthogonal frequency division multiplexing (OFDM) systems over wireless channel has exhibited excellent performance. However, the phenomenon of carrier frequency offset (CFO) caused by the frequency mismatch between the transmitter’s and receiver’s local oscillators often exists in actual scenarios; thus, in this paper the performance of AJSCC-OFDM with CFO is analyzed and the S-K mapping is optimized. A joint optimization strategy is developed to maximize the signal-to-distortion ratio (SDR) subject to CFO constraints. Considering that the optimized AJSCC-OFDM strategies will change the amplitude distribution of encoded symbol, the peak-to-average power ratio (PAPR) characteristics under different AJSCC parameters are also analyzed. Full article

To meet the requirements for radar echo acquisition and feature extraction from stratified media and rough-surfaced targets, a vehicle was geometrically modelled in CAD. Monte Carlo techniques were applied to generate the rough interfaces at air–snow and snow–soil boundaries and over the vehicle surface. Soil complex permittivity was characterized with a four-component mixture model, while snow permittivity was described using a mixed-media dielectric model. The composite electromagnetic scattering from a rough-surfaced vehicle on snow-covered soil was then analyzed with the finite-difference time-domain (FDTD) method. Parametric studies examined how incident angle and frequency, vehicle orientation, vehicle surface root mean square (RMS) height, snow liquid water content and depth, and soil moisture influence the composite scattering coefficient. Results indicate that the coefficient oscillates with scattering angle, producing specular reflection lobes; it increases monotonically with larger incident angles, higher frequencies, greater vehicle RMS roughness, and higher snow liquid water content. By contrast, its dependence on snow thickness, vehicle orientation, and soil moisture is complex and shows no clear trend. Full article

We investigate how collisional interactions between the condensate and the thermal cloud influence the distinct dynamical regimes (Josephson plasma, phase-slip-induced dissipative regime, and macroscopic quantum self-trapping) emerging in ultracold atomic Josephson junctions at non-zero subcritical temperatures. Specifically, we discuss how the self-consistent dynamical inclusion of collisional processes facilitating the exchange of particles between the condensate and the thermal cloud impacts both the condensate and the thermal currents, demonstrating that their relative importance depends on the system’s dynamical regime. Our study is performed within the full context of the Zaremba–Nikuni–Griffin (ZNG) formalism, which couples a dissipative Gross–Pitaevskii equation for the condensate dynamics to a quantum Boltzmann equation with collisional terms for the thermal cloud. In the Josephson plasma oscillation and vortex-induced dissipative regimes, collisions markedly alter dynamics at intermediate-to-high temperatures, amplifying damping in the condensate imbalance mode and inducing measurable frequency shifts. In the self-trapping regime, collisions destabilize the system even at low temperatures, prompting a transition to Josephson-like dynamics on a temperature-dependent timescale. Our results show the interplay between coherence, dissipation, and thermal effects in a Bose–Einstein condensate at a finite temperature, providing a framework for tailoring Josephson junction dynamics in experimentally accessible regimes. Full article

Background/Objectives: The forced oscillation technique (FOT) is a non-invasive, effort-independent method for assessing respiratory mechanics and is particularly suited for young children who cannot reliably perform spirometry. This study aimed to evaluate the main anthropometric determinants of respiratory impedance parameters—resistance (Rrs) and reactance (Xrs)—in healthy Bulgarian children aged 2 to 8 years. Methods: A total of 100 healthy children were evaluated using a commercially available device at oscillation frequencies of 5, 11, and 19 Hz. Anthropometric data were collected, and FOT measurements were conducted following ATS/ERS guidelines. Stepwise multiple linear regression was applied to identify predictors of Rrs and Xrs. Results: Height (mean height of the children: 113.89 ± 8.46 cm) emerged as the most significant determinant of both Rrs and Xrs across all frequencies with a moderate inverse correlation observed between Rrs at 5 Hz and height (r = −0.446; p < 0.001). Weight additionally influenced reactance at 5 Hz. The mean R5–19 was 0.55, but no significant associations with height or weight were found. Stepwise regression confirmed height as the sole consistent predictor, while sex and age had no significant effect. Conclusions: This study is the first to present the determinants of key FOT parameters in a population of Bulgarian children. Height was identified as the strongest predictor of respiratory impedance and should be prioritized in the development of reference values for children under 8 years old. These findings reinforce the clinical utility of FOT in early childhood. Full article

Oceanic mesoscale activity influences the atmosphere in the southwestern and southern sectors of the Atlantic Ocean. However, the influence of high latitudes, specifically sea ice, on mid-latitudes and a better understanding of mesoscale ocean–atmosphere thermodynamic interactions still require further study. To quantify the effects of oceanic mesoscale activity during the periods of maximum and minimum Antarctic sea ice extent (September 2019 and February 2020), numerical experiments were conducted using a coupled regional model and an online two-dimensional spatial filter to remove high-frequency sea surface temperature (SST) oscillations. The largest SST anomalies were observed in the Brazil–Malvinas Confluence and along oceanic fronts in September, with maximum SST anomalies reaching 4.23 °C and −3.71 °C. In February, the anomalies were 2.18 °C and −3.06 °C. The influence of oceanic mesoscale activity was evident in surface atmospheric variables, with larger anomalies also observed in September. This influence led to changes in the vertical structure of the atmosphere, affecting the development of the marine atmospheric boundary layer (MABL) and influencing the free atmosphere above the MABL. Modulations in precipitation patterns were observed, not only in oceanic regions, but also in adjacent continental areas. This research provides a novel perspective on ocean–atmosphere thermodynamic coupling, highlighting the mesoscale role and importance of its representation in the study region. Full article

Background: Electroencephalography (EEG) systems based on textile electrodes are increasingly being developed to address the need for more wearable sensor systems for brain function monitoring. Blink-related oscillations (BROs) are a new measure of brain function that corresponds to brainwave responses occurring after spontaneous blinking, and indexes neural processes as the brain evaluates new visual information appearing after eye re-opening. Prior studies have reported BRO utility as both a clinical and non-clinical biomarker of cognition, but no study has demonstrated BRO measurement using textile-based EEG devices that facilitate user comfort for real-world applications. Methods: We investigated BRO measurement using a four-channel EEG system with textile electrodes by extracting BRO responses using existing, publicly available EEG data (n = 9). We compared BRO effects derived from textile-based electrodes with those from standard dry Ag/Ag-Cl electrodes collected at the same locations (i.e., Fp1, Fp2, F7, F8) and using the same EEG amplifier. Results: Results showed that BRO effects measured using textile electrodes exhibited similar features in both time and frequency domains compared to dry Ag/Ag-Cl electrodes. Data from both technologies also showed similar performance in artifact removal and signal capture. Conclusions: These findings provide the first demonstration of successful BRO signal capture using four-channel EEG with textile electrodes, providing compelling evidence toward the development of a comfortable and user-friendly EEG technology that uses the simple activity of blinking for objective brain function assessment in a variety of settings. Full article

After the interruption of the timing service, the increase in clock offset is a critical issue for the global navigation satellite system (GNSS)-disciplined oven-controlled crystal oscillator (OCXO). Current timekeeping methods for GNSS-disciplined OCXO have some drawbacks, such as high computational complexity, inadequate consideration of temperature effects, and insufficient separation of the impacts of temperature and aging. To address this issue, this study proposes a timekeeping method using a dual iterative algorithm. First, the external iteration separates the clock offset caused by temperature and aging. Then, the internal Gauss–Seidel iterative algorithm estimates the temperature and aging coefficients. During the timing service interruption phase, the model estimates and compensates for the frequency offset in real time using the coefficients. The proposed method demonstrates improved performance compared with OCXO in the free state and compensated by a second-order polynomial model, with better accuracy, drift rate, and long-term stability. The time offset is better than 4 μs over 24 h, representing an improvement of over 95% compared with the OCXO in the free state. Full article

The increasing incorporation of renewable energy into power grids has significantly reduced system inertia and damping, posing challenges to frequency stability and power quality. To address this issue, an adaptive virtual synchronous generator (VSG) control strategy is proposed, which dynamically adjusts virtual inertia and damping in response to real-time frequency variations. Virtual inertia is modulated by an exponential function according to the frequency variation rate, while damping is regulated via a hyperbolic tangent function, enabling minor support during small disturbances and robust compensation during severe events. Control parameters are optimized using an enhanced particle swarm optimization (PSO) algorithm based on a composite performance index that accounts for frequency deviation, overshoot, settling time, and power tracking error. Simulation results in MATLAB/Simulink under step changes, load fluctuations, and single-phase faults demonstrate that the proposed method reduces the frequency deviation by over 26.15% compared to fixed-parameter and threshold-based adaptive VSG methods, effectively suppresses power overshoot, and eliminates secondary oscillations. The proposed approach significantly enhances grid transient stability and demonstrates strong potential for application in power systems with high levels of renewable energy integration. Full article

A rather novel approach for delivery of inertia-like grid services through energy storage devices is described and validated by physical experiments and on-site measurements. In this approach, denoted “amplified inertia response”, an actual inertial response from a grid-connected synchronous machine is amplified. This inertia emulation approach is contrasted by what is called synthetic inertia, which uses a frequency-locked loop in order to extract the grid frequency. The synthetic inertia faces the usual input signal filtering challenges if the signal-to-noise ratio is low. The amplified inertia controller avoids the input filtering since it only amplifies the natural inertial response from a synchronous machine. However, rotor angle oscillations lead to filtering requirements of the amplified version as well, but on the output signal of the controller. Experimental comparisons are conducted both on the measurement output from the physical experiments in a microgrid and on analysis based on input from on-site measurements from a 55 MVA hydropower generator connected to the Nordic grid. In the specific cases compared, we observe that the amplified inertia version is the better method for smaller power systems, with large frequency fluctuations. On the other hand, the synthetic inertia method is the better in larger power systems as compared to the amplification of the inertial response from a real production unit. Full article

It is well known that aqueous solutions can emit electromagnetic waves in the radio frequency range. However, the physical nature of this process is not yet fully understood. In this work, the possible role of gas nanobubbles formed in the bulk liquid is considered. We develop a theoretical model based on the concept of gas bubbles stabilized by ions, or “bubstons”. The role of bicarbonate and hydronium ions in the formation and stabilization of bubstons is explained through the use of quantum chemical simulations. A new model of oscillating bubstons, which takes into account the double electric layer formed around their gas core, is proposed. Theoretical estimates of the frequencies and intensities of oscillations of such compound species are obtained. It was determined that oscillations of negatively charged bubstons can occur in the GHz frequency range, and should be accompanied by the emission of electromagnetic waves. To validate the theoretical assumptions, we used dynamic light scattering (DLS) and showed that, after subjecting aqueous solutions to vigorous shaking with a force of 4 or 8 N (kg·m/s²) and a frequency of 4–5 Hz, the volume number density of bubstons increased by about two orders of magnitude. Radiometric measurements in the frequency range of 50 MHz to 3.5 GHz revealed an increase in the intensity of radiation emitted by water samples upon the vibrational treatment. It is argued that, according to our new theoretical model, this radiation can be caused by oscillating bubstons. Full article

The balance between cortical excitation and inhibition (E/I balance) in the cerebral cortex is critical for cognitive processing and neuroplasticity. Modulation of this balance has been linked to a wide range of neuropsychiatric and neurodegenerative disorders. The human visual system has well-differentiated magnocellular (M) and parvocellular (P) pathways, which provide a useful model to study cortical excitability using non-invasive visual flicker stimulation. We present an Arduino-driven non-image forming system to deliver controlled flickering light stimuli at different frequencies and wavelengths. By triggering the critical flicker fusion (CFF) frequency, we attempt to modulate the M-pathway activity and attenuate P-pathway responses, in parallel with induced optical scattering. EEG recordings were used to monitor cortical excitability and oscillatory dynamics during visual stimulation. Visual stimulation in the CFF, combined with induced optical scattering, selectively enhanced magnocellular activity and suppressed parvocellular input. EEG analysis showed a modulation of cortical oscillations, especially in the high frequency beta and gamma range. Our results support the hypothesis that visual flicker in the CFF, in addition to spatial degradation, initiates detectable neuroplasticity and regulates cortical excitation and inhibition. These findings suggest new avenues for therapeutic manipulation through visual pathways in diseases such as Alzheimer’s disease, epilepsy, severe depression, and schizophrenia. Full article

This article proposes a new Flower Patch Nectar Sensor to address the problem of detecting and measuring nectar in artificial flowers used in experiments on pollinator behavior. Traditional methods have focused mainly on recording the visits of pollinators to the flowers, without addressing the dynamic variations in nectar in terms of volume and concentration. The proposed approach provides more detailed information about the nectar consumption by bees and allows for the determination of the optimal time to refill the flowers. This study introduces an innovative method that uses electrodes and an oscillator circuit to measure the volume of nectar present in the flower. The system correlates the concentration of nectar with a frequency signal that can be processed by a microcontroller. It was evaluated using initial volumes ranging from 1 $\mathsf{\mu }$L to 4 $\mathsf{\mu }$L, demonstrating its ability to accurately detect variations in nectar, even up to the point where the frequency approaches zero. The results confirm that this method allows us to identify how the reward offered to pollinators (represented by nectar) varies over time, in terms of concentration, under both controlled and natural conditions. Additionally, graphs are presented that show the relationship between an initial volume of 4 $\mathsf{\mu }$L and variations in the frequency signal over a period of 25 min, highlighting the influence of these factors on nectar dynamics. This work not only introduces an innovative approach for the dynamic monitoring of nectar in artificial flowers but also lays the groundwork for future studies on the physical and chemical modeling of nectar in response to environmental conditions. Full article