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Hall thrusters are electric propulsion devices widely used on spacecraft. The stability of Hall thrusters is often disturbed by low-frequency oscillations (LFOs) around 5–100 kHz, known as the 'breathing mode', typically observed through fluctuations in channel discharge current and plasma parameters. Experimental studies on Hall thrusters with a wide range of sizes show that LFOs exhibit distinct characteristics depending on the channel structures. The size of the channel can modify the particle-wall interactions, electric potential distribution, and electron temperature, thereby influencing the performance of LFOs. Furthermore, the long-term operation of thrusters can cause significant wall erosion, altering the geometry of the discharge channel, which further impacts LFOs. In this work, a one-dimensional fluid model is established to explore the influences of structure sizes and wall erosion of the channel on the LFO characteristics. Both the thruster channel and the plume region are included in the model, and a modified and more precise approach to calculating the electron energy loss at the wall is proposed, which takes into account the influences of secondary electron emission and the channel cross-sectional area. The simulation results indicate that choosing a narrower or longer channel structure has a significantly suppressing effect on LFOs. An erosion model is established according to the cited experimental data to construct the eroded channel structure and to investigate the effect of channel erosion on the breathing mode, which shows that wall erosion can exacerbate LFOs and impact the performance of the thruster. [ABSTRACT FROM AUTHOR]

The incorporation of converter-based generating sources in utility-scale microgrids causes frequency instability and low-frequency oscillations (LFOs), which is also a reason for degeneration in system stability. Damping frequency control is an essential part of alternating current (AC) microgrid system operation and control. Sudden changes in load, variations in renewable power outputs due to changes in solar insolation or wind speed, and so on factors cause the system frequency to deviate from the nominal value. Therefore, the role of a frequency controller is to maintain the dynamic stability in an AC microgrid by retaining the system frequency at the nominal value. Again, AC microgrids with high renewable power penetration face even more difficulty in maintaining frequency stability because of their poor inertial response. The research presented here proposes a novel approach for grid-connected AC microgrid oscillation damping and frequency control that simultaneously takes into consideration time delay and noise. To improve the frequency response and dampen LFOs by providing the voltage and frequency within the specified range, a coordinated technique-based control approach is adopted. In the developed hybrid control, the frequency controller relies on active power modulation, while the power oscillation damping controller is dependent on reactive power modulation. To improve stability and reduce communication consequences such as noise and signal latency (time delay), the developed power oscillation damping controller and frequency controller are coordinated along with the robust linear quadratic Gaussian controller. The comparative investigation of the effectiveness of the coordinated control technique is employed in the software of MATLAB/Simulink for grid-connected AC microgrid. The outcome of the simulation illustrates the superior effectiveness of the suggested controller over the traditional droop controller for huge power flows under disturbance with various operating conditions, under/overfrequency events, time delay, and noise. This grid encouragement capability for AC microgrids is anticipated to lead to novel possibilities for generating revenue. [ABSTRACT FROM AUTHOR]

This paper presents a detailed model of low-frequency oscillations and their damping within the Electric Power System (EPS) of Bosnia and Herzegovina (B&H). The system is modeled using MATLAB software, analysing the steady state and dynamic responses. This research highlights the challenges and impacts of integrating renewable energy sources, such as wind farms, on grid stability and oscillation damping. The paper utilizes eigenvalue analysis to investigate the dynamic characteristics of the system, emphasizing the need for efficient damping strategies to maintain system stability. The methodology includes a comprehensive review of existing literature, the creation of a detailed EPS model of B&H, and the application of eigenvalue and oscillation amplitude analysis to determine damping ratios. The dynamic responses of hydro power plants, HPP Mostar and HPP Jablanica, to transient disturbances are analysed to validate the model and refine damping strategies. The results indicate that the B&H EPS is well-damped, with all eigenvalues possessing negative real parts, and demonstrate the system's resilience to small disturbances. The results are compared with the technical report on the integration of the wind power plant WPP Podveležje. This comparative analysis shows consistent patterns between the modeled calculations and empirical data, confirming the robustness of the EPS model. This alignment underscores the effectiveness of current damping mechanisms and provides a foundational strategy for enhancing system stability with increasing renewable energy penetration. The findings highlight the importance of developing advanced control strategies to sustain system stability as the integration of variable renewable energy sources continues to grow. [ABSTRACT FROM AUTHOR]

The Southern Cameroon Interconnected Network (SIG) is depicted as a large-scale power system that has shown significant instability due to a series of blackouts in recent years. These blackouts are primarily attributed to major disruptions in transmission lines and energy deficits between supply and demand. The imbalance between power supply and demand necessitates the grid to operate near its stability limits, increasing the risk of blackouts. The necessity of investigating the dynamics of SIG behavior in response to observed contingency situations serves as the primary motivation for this study. To achieve this objective, the SIG was modeled using saturated generators with ZIP static loads. Through Newton-Raphson based power flow calculations, voltage magnitude profiles of the grid were obtained for each generation scenario. An N-1 contingency consisting of a standard Newton-based continuation power flow (CPF) analysis has identified line 5–6 as the most frequent worst case of line outage. Additionally, a short-term transient analysis was conducted under three-phase short-circuit, line outage and generator outage scenarios. In the event of a short-circuit, the Mangombe-225 bus experienced the most significant impact. Concerning line outages, line 1–5 had the most adverse effect on the grid's frequency stability. However, generation outages had a lesser impact on frequency stability compared to other disturbances. Lastly, modal analysis revealed that the grid exhibited weak stability with a critical mode identified at a frequency of 4.0267 Hz, exceeding typical values. This underscores the necessity of damping the grid oscillations for enhanced stability.

The object of research is the dynamic processes that occur in the drill string during the deepening of the hole in deep wells. The work is aimed at solving the problem for an idealized system in the form of rod systems while preserving its main oscillatory properties. The nature of oscillatory processes that occur in the drill string during drilling with downhole motors is considered, in some cases it turns out to be very complicated. In the general case, the dynamic process changes according to an aperiodic law, which is superimposed by processes of an oscillating nature with an increasing (damping) nature of the amplitudes of different frequencies. The influence of the torque characteristics of the downhole motor and bit on the development of oscillatory processes in the drill string during well drilling has been theoretically determined. The results of theoretical and experimental studies of oscillatory processes and their interaction with the use of proposed models of hole deepening in the future make it possible to create a simulation model. This model would include taking into account the mode parameters of drilling, the mechanical properties of the rocks to be drilled and the layout of the drill string bottom (DSB). The obtained research results can be applied in practice in the process of designing the structure of the drill string bottom (DSB) with the use of downhole motors, in particular, screw motors, the use of which leads to energy stress, the complication of work processes and structural schemes. As a result, the nature of vibrations changes and the vibration loads on parts of the downhole motor, bits and elements of the drill string are reduced. In the future, it is necessary to take into account the hydrodynamics and the type, as well as the design and parameters of the applied downhole elements for the development of their dynamic models. [ABSTRACT FROM AUTHOR]

This article deals with the issues of identifying and studying high-amplitude, low-frequency oscillations in the electrical regime parameters (LFO ERP) of an electric power system. These problems are currently important for ensuring operating stability of the generation equipment and maintaining dynamic stability of the power system. Solving the problems of identifying LFO ERP, determining the source of the oscillations, monitoring the oscillatory stability of the power system, and effective damping of the LFO, is a necessary condition for the operational reliability of a power system. In modern power systems a wide variety of possible sources of LFO are observed, such as: periodically varying load, e.g., stops and starts of pumps in the oil and gas industry or motors for machines operating over a wide range of speeds with frequent starts and stops; disconnection of the load (of individual electrical transmission lines), that cause disruption of permissible power flows at any point of the power system, which leads to dynamic oscillatory instability; incorrect adjustment of the automatic voltage regulator (AVR) and/or channels for stabilization of the automatic excitation regulator (AER) of the generator under consideration or associated with it; periodic variation in the torque on a generator shaft. The use of devices for synchronized vector measurements (DSVM) makes it possible to determine with high accuracy the sources of the LFO in a power system, regardless of their nature and, depending on the number of installed measurement devices in the power system, these can be specified for the final primary equipment. [ABSTRACT FROM AUTHOR]

Model identification errors and time delays are often presented in power systems, which will deteriorate the effect of power system wide-area damping control. To solve the problems of random time delays and model parameter identification errors on system damping control, this paper firstly uses the pseudo-random noise excitation as the identification signal and establishes a closed-loop model for the power system under small interference conditions. Secondly, a Vinnicombe-Adaptive Multi-parameter Differential Evolutionary algorithm (VAMDE) proposed in this paper takes into account of the algorithm model identification error, directly predicts the value of the random time delay parameter, and gives the optimal damping controller that can effectively suppress low-frequency oscillations in power system. The most important thing is that the random time delay is compensated by the improved Smith Predictor. Finally, a four-machine and two-area system is tested. Compared with traditional iterative identification method, simulation results show that the proposed method can effectively improve the damping control problem caused by the model identification error and communication time delay.

Assessment of the influence of vibration isolator parameters on the distribution of the system’s natural frequencies is a significant task in the design of vibration isolation systems. The root method was used to determine the natural frequencies of the controlled vibration isolator. For a certain feedback structure of a controlled electrodynamic type vibration isolator, the need for a consistent selection of parameters has been justified. A mathematical solution has been proposed for the approximate determination of the roots of the characteristic equation of the controlled vibration isolator, which enables the analytical assessment of the influence of the vibration isolator parameters on the distribution of its natural frequencies. The research has been conducted in relative parameters, which makes it possible to generalize the results. The specificity of the inertial dynamic vibration isolator, which in some cases is associated with the implementation of anti-resonance conditions, can lead to the fact that resonant frequencies can occur on both sides of the tuning frequency of the vibration isolator. The use of an elastic suspension on flat springs to protect navigation equipment from vibration allows reduction in the intensity of translational vibration, while not changing the orientation of the device relative to the Earth. The implementation of an elastic suspension according to the scheme of the inverted pendulum allows an increase in the effectiveness of vibration isolation, under the conditions of a controlled change of the vibration isolator parameters and due to the use of feedback. The results of this research can be used in precision systems, such as vibration isolators, laser processing equipment, ultraprecision measurements or medical devices.

A problem of efficacy of crystal growth methods for crystallization from solutions or melt has been investigated. The axial vibrational control (AVC) technique was considered as a perspective method to manage both heat-mass transfer and chemical component composition of the melts in the case of crystallization of complex chemical compounds. Numerical modeling and the search for generalized dependencies made it possible to predict the AVC parameters that provide optimal heat and mass transfer modes for creating flat liquid-solid interfaces, as well as the component composition of dissociated melts of various chemical compounds—Ge, NaNO3, CdTe. [ABSTRACT FROM AUTHOR]

Nowadays there is a significant increase the number of generation units based on renewable energy sources in electric power systems, the main goal of which is to ensure global access to affordable, reliable, sustainable and modern sources of energy. However, as the penetration level of renewable generation units increases, there are power oscillations easily occur, which create biggest challenges for the power system stability. In particular, the dominant modes of modern generation units, connected to the main grid via a voltage source converter, are in the range of higher frequencies than electromechanical oscillations. Consequently, the chance of occurrence of low-frequency oscillations increases, the parameters and the trajectory of which will differ from power oscillations in power system without renewables. The results of the analysis of low-frequency oscillation parameters in part of Eastern Siberia power system and evaluation of impact of renewable generation unit on power oscillations are presented in this article. The results were obtained by the Hybrid real time simulator based on the combination of analog, physical and digital modeling levels. The developed scheme of part of Eastern Siberia power system and simulation results were verified by SCADA system. The difference between the results of simulation and SCADA system did not exceed 1%. It indicates the adequacy of the Hybrid real time simulator and the developed scheme of power system. Based on the evaluation of the parameters of power oscillations and the calculation of the degree of damping of the transient process, it can be noted that the oscillatory stability of the power system is improved: damping time decreases, the damping ratio increases with increasing of renewables penetration level.

In order to better understand the extent to which global climate variability is linked to the frequency and intensity of heat waves and overall changes in temperature throughout the United States (US), correlations between long-term monthly mean, minimum, and maximum temperatures throughout the contiguous US on the one hand and low-frequency variability of multiple climate indices (CIs) on the other hand are analyzed for the period from 1948 to 2018. The Pearson’s correlation coefficient is used to assess correlation strength, while leave-one-out cross-validation and a bootstrapping technique (p-value) are used to address potential serial and spurious correlations and assess the significance of each correlation. Three parameters defined the sliding windows over which surface temperature and CI values were averaged: window size, lag time between the temperature and CI windows, and the beginning month of the temperature window. A 60-month sliding window size and 0 lag time resulted in the highest correlations overall; beginning months were optimized on an individual site basis. High (r ≥ 0.60) and significant (p-value ≤ 0.05) correlations were identified. The Western Hemisphere Warm Pool (WHWP) and El Niño/Southern Oscillation (ENSO) exhibited the strongest links to temperatures in the western US, tropical Atlantic sea surface temperatures to temperatures in the central US, the WHWP to temperatures throughout much of the eastern US, and atmospheric patterns over the northern Atlantic to temperatures in the Northeast and Southeast. The final results were compared to results from previous studies focused on precipitation and coastal sea levels. Regional consistency was found regarding links between the northern Atlantic and overall weather and coastal sea levels in the Northeast and Southeast as well as on weather in the upper Midwest. Though the MJO and WHWP revealed dominant links with precipitation and temperature, respectively, throughout the West, ENSO revealed consistent links to sea levels and surface temperatures along the West Coast. These results help to focus future research on specific mechanisms of large-scale climate variability linked to US regional climate variability and prediction potential.

The Mediterranean Sea is of great and manifold relevance for global oceanic circulation and climate: Mediterranean waters profoundly affect the salinity of the North Atlantic Ocean and hence the global ocean circulation. Ocean motions are forced fundamentally by the atmosphere. However, direct atmospheric forcing explains just a part of the observed Mediterranean circulation, for example, the former is not able to account for the observed north-south inclination of the sea level, one of the most prominent and persistent features of Mediterranean oceanography. This implies that a significant part of this circulation feature is caused by mechanisms that are all internal, "intrinsic" to the ocean. Yet, no effort has been made so far to disentangle intrinsic oceanic phenomena from atmospherically forced ones in the Mediterranean Sea. Here, we start filling this gap of knowledge. We demonstrate that a conspicuous part of the observed Mediterranean mean state and variability belongs to a skeleton captured for the first time by a multi-centennial ocean simulation without atmospheric forcing. This study paves the way to the identification and comprehension of further observed mean patterns and low-frequency fluctuations in the Mediterranean Sea as the result of intrinsic oceanic processes rather than by a direct effect of the atmospheric forcing and could be extended to other basins where geometry and hydrological structure significantly contribute to shaping the local dynamics. [ABSTRACT FROM AUTHOR]

Background: Cerebral small vessel disease (cSVD) is associated with endothelial dysfunction but the pathophysiology is poorly understood. Low-frequency oscillations (LFOs) in the BOLD signal partly reflect cerebrovascular function and have the potential to identify endothelial dysfunction in cSVD. A systematic review was performed to assess the reported relationships between imaging markers of cSVD and LFOs. Methods: Medline and EMBASE were searched for original studies reporting an association between LFOs and STRIVE-defined imaging markers of cSVD, including: white matter hyperintensities (WMH), enlarged perivascular spaces, lacunes, CADASIL, and cerebral microbleeds, from inception to September 1, 2022. Variations in LFOs were extracted, where available, on a global, tissue-specific, or regional level, in addition to participant demographics, data acquisition, methods of analysis, and study quality. Where a formal meta-analysis was not possible, differences in the number of studies reporting LFO magnitude by presence or severity of cSVD were determined by sign test. Results: 15 studies were included from 841 titles. Studies varied in quality, acquisition parameters, and in method of analysis. Amplitude of low-frequency fluctuation (ALFF) in resting state fMRI was most commonly assessed (12 studies). Across 15 studies with differing markers of cSVD (9 with WMH; 1 with cerebral microbleeds; 1 with lacunar infarcts; 1 with CADASIL; 3 with multiple markers), LFOs in patients with cSVD were decreased in the posterior cortex (22 of 32 occurrences across all studies, p = 0.05), increased in the deep grey nuclei (7 of 7 occurrences across all studies, p = 0.016), and potentially increased in the temporal lobes (9 of 11 occurrences across all studies, p = 0.065). Conclusion: Despite limited consensus on the optimal acquisition and analysis methods, there was reasonably consistent regional variation in LFO magnitude by severity of cSVD markers, supporting its potential as a novel index of endothelial dysfunction. We propose a consistent approach to measuring LFOs to characterise targetable mechanisms underlying cSVD. [ABSTRACT FROM AUTHOR]

In order to better understand the extent to which global climate variability is linked to the frequency and intensity of heat waves and overall changes in temperature throughout the United States (US), correlations between long-term monthly mean, minimum, and maximum temperatures throughout the contiguous US on the one hand and low-frequency variability of multiple climate indices (CIs) on the other hand are analyzed for the period from 1948 to 2018. The Pearson's correlation coefficient is used to assess correlation strength, while leave-one-out cross-validation and a bootstrapping technique (p-value) are used to address potential serial and spurious correlations and assess the significance of each correlation. Three parameters defined the sliding windows over which surface temperature and CI values were averaged: window size, lag time between the temperature and CI windows, and the beginning month of the temperature window. A 60-month sliding window size and 0 lag time resulted in the highest correlations overall; beginning months were optimized on an individual site basis. High (r ≥ 0.60) and significant (p-value ≤ 0.05) correlations were identified. The Western Hemisphere Warm Pool (WHWP) and El Niño/Southern Oscillation (ENSO) exhibited the strongest links to temperatures in the western US, tropical Atlantic sea surface temperatures to temperatures in the central US, the WHWP to temperatures throughout much of the eastern US, and atmospheric patterns over the northern Atlantic to temperatures in the Northeast and Southeast. The final results were compared to results from previous studies focused on precipitation and coastal sea levels. Regional consistency was found regarding links between the northern Atlantic and overall weather and coastal sea levels in the Northeast and Southeast as well as on weather in the upper Midwest. Though the MJO and WHWP revealed dominant links with precipitation and temperature, respectively, throughout the West, ENSO revealed consistent links to sea levels and surface temperatures along the West Coast. These results help to focus future research on specific mechanisms of large-scale climate variability linked to US regional climate variability and prediction potential. [ABSTRACT FROM AUTHOR]

The operation of power systems requires a set of requirements and studies to ensure the continuous and safe supply of electricity to consumer centers. In small-signal stability studies, low-frequency oscillation modes need to be evaluated as they can compromise the operation of power systems if they are not properly damped. Many structures and control devices have been proposed to mitigate these oscillation modes and the Wide-Area Power System Stabilizers (WAPSSs) have proven to be effective in improving the damping rates of these modes as they use remote system signals from Phasor Measurement Units (PMUs). However, cyber-attacks and communication failures can affect WAPSS communication channels and affect its operation in the power system. This article proposes a method based on a multiobjective optimization model for WAPSS design that is robust to the permanent loss of one WAPSS communication channel. Bio-Inspired Algorithms are applied and compared to solve the optimization problem. A set of case studies were conducted and discussed for the IEEE 68-bus system through modal analysis and time domain simulations. The achieved results showed the need for a fault-robust damping controller and the WAPSS-type controller was able to guarantee good dynamic performance regardless of permanent communication failures. Furthermore, different bio-inspired algorithms provided different results for the closed-loop control system when applied to the proposed optimization model.

Summary: This paper utilizes a static var compensator in coordination with an intelligent online controller, to enhance the oscillation damping of the power system at various operating conditions and communication delays. For system identification, a linear identifier is used that ensures a low computational burden and facilitates its real‐time implementation. This identifier accurately estimates the system's local linear model using local measurements and continuously updates its parameters in real time to account for system's changing operational states. The learning rate of the identifier is also adaptively adjusted such that the stability of the learning algorithm and optimal speed of convergence are guaranteed. The location of the controller is selected based upon the controllability and bus voltage participation factors, and an effective feedback signal is obtained using the observability. An empirical expression has also been proposed to offset the effects of communication time delays caused due to use of wide‐area signals. Time‐domain simulations are performed on single‐ and multi‐machine power systems to check the efficacy of the proposed intelligent controller. The performance of the controller is compared with the residue‐based conventional controller and also with the recently proposed wide‐area damping controller. [ABSTRACT FROM AUTHOR]

This work discusses the production of a novel hybrid algorithm by combining the gorilla troops optimizer (GTO) with the gradient-based optimizers (GBO) approach. The novel approach is called GTO-GBO, it is offered as a useful tool for optimizing the power system stabilizer (PSS) used in the IEEE four-generator, two-area multi-machine power system subjected to a three-phase short-circuit fault. MATLAB/Simulink software was utilized to carry out the assessments. The suggested approach is initially evaluated using multiple benchmark functions with unimodal and multimodal properties. The results are then compared to other competing algorithms (artificial ecosystem optimizer, artificial rabbits optimizer, Coati Optimization Algorithm, and northern goshawk optimization). The comparisons with various algorithms reveal the developed hybrid GTO-GBO algorithm’s considerable promise. This demonstrates the GTO-GBO algorithm’s improved balance of global and local search stages. The proposed GTO-GBO algorithm’s performance is also evaluated by developing an optimum performing PSS for further examination, allowing observation of its capabilities for difficult real-world engineering challenges. To illustrate the applicability and superior performance of the suggested hybrid algorithm for such a complicated real-world engineering problem, the PSS damping controller is formulated as an optimization problem, and the developed GTO-GBO algorithm is used to search for optimal controller parameters. The latter case’s findings are compared to the competitive optimization algorithms where the GTO-GBO demonstrates the efficiency and robustness of this suggested optimization algorithm to enhance power system stability.

The mapping of damping ratios and damping factors by Sine-Cosine Algorithm (SCA) is significant in the analysis of low frequency oscillations generated in an integrated network having multiple conventional and renewable energy sources. Multiple random models with unknown search spaces and uncertain conditions and constraints, which incorporate the fluctuation of solutions towards or outwards at the initial stage for solving real-time problems can be analyzed by a revamped sine-cosine algorithm (RSCA) model. In this paper, the SCA has been revamped to explore the stability threshold for a stable system under dynamic nonlinear operating conditions. It is achieved with the infusion of suitable mathematical functions for optimizing the parameters of Power System Stabilizers (PSSs) and Doubly Fed Induction Generator (DFIG) system-based oscillation dampers to enhance the Small Signal Stability of power systems through effective damping of low-frequency oscillations (LFOs). These LFOs weaken the effective power generation and demand management cycle in conventional power systems when the system faces conditions like intermittent renewable energy sources, overloading conditions, impulsive faults etc. The small-signal and transient stability studies for various disturbances and different operating conditions are investigated, and the performance of the proposed RSCA for optimized parameter tuning of system stabilizers and oscillation dampers are analyzed on the modified benchmarking systems with wind generators using MATLAB Ⓡ simulations. The efficiency and robustness of the proposed algorithm has been verified under selective critical operating conditions, line outages, and load uncertainties to prove that the low frequency modes are damped with an elevated positive damping ratio and rapid settling time with reduced oscillations. The application of system stabilizers and oscillation dampers optimized through the proposed RSCA shows a reduced settling time in the LFOs created and improved damping ratio of 0.22 for an increase in 20% loading and 50% of wind power generation in the case study of Two Area Four Machine System.

Supplementary damping controller (SDC) for static var compensator (SVC) can be used to damp interarea low-frequency oscillations, but the influence of signal transmission delay on damping performance is generally neglected in the previous research. Because the delay may deteriorate damping performance or even cause instability for power system, this work intensively investigates the influence of signal transmission delay on input signal selection and parameter setting in SDC design. A novel evaluation method based on delay-dependent stability criterion and model order reduction is proposed to obtain the tradeoff between damping performance and delay margin for the SDC to be designed. Delay margin, determined by the proposed method, is taken as a critical index to evaluate the delay influence on SDC design. Case studies are carried out on two-area four-generator power system. Results show that for input signals with higher mode observability by residue method, such as current magnitude and active power of transmission line, delay margin decreases with the increase of SDC gain or delay variation ratio, which indicates that appropriately setting the gain can ensure SDC with better damping performance and larger delay margin.

In order to better understand the extent to which global climate variability is linked to long-term mean and extreme sea level patterns, correlations between average sea levels at coastal sites throughout North America and low-frequency oscillations of several climate indices (CIs) were analyzed for the entire period of 1948–2018 as well as three equal-length sub-periods using correlation analysis. Correlation strength was assessed using Pearson's correlation coefficient, while significance was estimated using Leave-One-Out Cross-Validation and a bootstrapping technique (p-value). The sliding window size, lag time, and beginning month were varied for optimal correlation; 60-month sliding windows, along with 0 lag time, resulted in the strongest correlations. Strong (r >= 0.60) and significant (p-value <= 0.05) correlations were identified. The Western Hemisphere Warm Pool Eastern Asia/Western Russia index and ENSO exhibited the strongest and most widespread correlation with coastal sea levels. Further analysis was performed to identify and quantify the magnitude of any sea level trends using the Theil–Sen estimator, while the Mann–Kendall (MK) test was used to estimate the significance of said trends. The results revealed that a complex set of ocean–atmosphere interactions govern long-term coastal sea level variability in large coastal regions of North America. The final results of this study allow a greater understanding of potential links between climate variability and long-term sea levels along the coasts of North America, as well as insights into sudden shifts in these relationships, which will contribute toward more accurate long-term forecasts. [ABSTRACT FROM AUTHOR]

BackgroundCerebral small vessel disease (cSVD) is associated with endothelial dysfunction but the pathophysiology is poorly understood. Low-frequency oscillations (LFOs) in the BOLD signal partly reflect cerebrovascular function and have the potential to identify endothelial dysfunction in cSVD. A systematic review was performed to assess the reported relationships between imaging markers of cSVD and LFOs.MethodsMedline and EMBASE were searched for original studies reporting an association between LFOs and STRIVE-defined imaging markers of cSVD, including: white matter hyperintensities (WMH), enlarged perivascular spaces, lacunes, CADASIL, and cerebral microbleeds, from inception to September 1, 2022. Variations in LFOs were extracted, where available, on a global, tissue-specific, or regional level, in addition to participant demographics, data acquisition, methods of analysis, and study quality. Where a formal meta-analysis was not possible, differences in the number of studies reporting LFO magnitude by presence or severity of cSVD were determined by sign test.Results15 studies were included from 841 titles. Studies varied in quality, acquisition parameters, and in method of analysis. Amplitude of low-frequency fluctuation (ALFF) in resting state fMRI was most commonly assessed (12 studies). Across 15 studies with differing markers of cSVD (9 with WMH; 1 with cerebral microbleeds; 1 with lacunar infarcts; 1 with CADASIL; 3 with multiple markers), LFOs in patients with cSVD were decreased in the posterior cortex (22 of 32 occurrences across all studies, p = 0.05), increased in the deep grey nuclei (7 of 7 occurrences across all studies, p = 0.016), and potentially increased in the temporal lobes (9 of 11 occurrences across all studies, p = 0.065).ConclusionDespite limited consensus on the optimal acquisition and analysis methods, there was reasonably consistent regional variation in LFO magnitude by severity of cSVD markers, supporting its potential as a novel index of endothelial dysfunction. We propose a consistent approach to measuring LFOs to characterise targetable mechanisms underlying cSVD.

Infrared drying of bulk agricultural products is becoming increasingly widespread in processing and food industries due to energy efficiency, compactness of technological equipment, and ease of operation. The purpose of the presented research is to determine the influence of the technological parameters of the process of infrared drying of the moving layer of oil-containing raw materials. An experimental model of a vibro-conveyor dryer and a set of measuring equipment were developed to solve the problems. The scientific novelty of the work is the confirmation that in the conditions of a vibro-liquefied layer of products, unique conditions are created for the constant renewal of heat exchange surfaces and, accordingly, the leveling of the negative thermal radiation effect on the products, the possibility of advancing the product layer along the working zone, reducing the forces of internal friction in the technological mass, which leads to a decrease in energy consumption on the process Laws have been established regarding the effect of the number of thermoradiation blocks, the load on the flexible belt of the wave conveyor, the speed of product advancement on the belt on the dynamics of infrared drying of soybeans and rapeseed. The practical value of the work was the substantiation of the operating modes of thermoradiation drying with the help of a vibrating wave conveyor installation based on the energy saving of the technological impact, high intensification of the process and minimization of the negative effect on the properties of the processed products.

A problem of efficacy of crystal growth methods for crystallization from solutions or melt has been investigated. The axial vibrational control (AVC) technique was considered as a perspective method to manage both heat-mass transfer and chemical component composition of the melts in the case of crystallization of complex chemical compounds. Numerical modeling and the search for generalized dependencies made it possible to predict the AVC parameters that provide optimal heat and mass transfer modes for creating flat liquid-solid interfaces, as well as the component composition of dissociated melts of various chemical compounds—Ge, NaNO3, CdTe.

The population size of DE plays a significant role in the way the algorithm performs as it influences whether good solutions can be found. Generally, the population size of DE algorithm is a user-defined input that remains fixed during the optimization process. Therefore, inadequate selection of DE population size may seriously hinder the performance of the algorithm. This paper investigates the impact of DE population size on (i) the performance of DE when applied to the optimal tuning of power system stabilizers (PSSs); and (ii) the ability of the tuned PSSs to perform efficiently to damp low-frequency oscillations. The effectiveness of these controllers is evaluated based on frequency domain analysis and validated using time-domain simulations. Simulation results show that a small population size may lead the algorithm to converge prematurely, and thus resulting in a poor controller performance. On the other hand, a large population size requires more computational effort, whilst no noticeable improvement in the performance of the controller is observed.

Power systems have an increasing demand for operational condition monitoring and safety control aspects. Low-frequency oscillation mode identification is one of the keys to maintain the safe and stable operation of power systems. To address the problems of low accuracy and poor anti-interference of the current low-frequency oscillation mode identification method for power systems, a low-frequency oscillation mode feature identification method combining the adaptive variational modal decomposition and sparse time-domain method is proposed. Firstly, the grey wolf optimization algorithm (GWO) is used to find the optimal number of eigenmodes and penalty factor parameters of the variational modal decomposition (VMD). And the improved method (GWVMD) is used to decompose the measured signal with low-frequency oscillations and then reconstruct the signal to achieve a noise reduction. Next, the processed signal is used as a new input for the identification of the oscillation modes and their parameters using the sparse time-domain method (STD). Finally, the effectiveness of the method is verified by the actual low-frequency oscillation signal identification in the Hengshan power plant and numerical signal simulation experiments. The results show that the proposed method outperforms the conventional methods such as Prony, ITD, and HHT in terms of modal discrimination. Meanwhile, the overall reduction in the frequency error is 34, 44, and 21%, and the overall reduction in the damping error is 37, 41, and 18%, compared with the recently proposed methods such as the EFEMD-HT, RDT-ERA, and TLS-ESPRIT. The effectiveness of the methods in suppressing the modal confusion and noise immunity is demonstrated. [ABSTRACT FROM AUTHOR]

The relevance of the study is determined by the need to optimise the process of mixing minced meat in the production of sausages “Ozdorovchi” to reduce the duration of the technological operation, energy and raw material costs. Therefore, the article is concerned with the substantiation and determination of the amplitude-force parameters of a vibro-mechanical machine for mixing sausage mince ingredients. The leading method for studying this issue is mathematical modelling, which allows for comprehensive consideration of the patterns of changes in the main parameters of the oscillatory process. The article theoretically substantiates the expediency of using vibration impact to provide a rapid and uniform distribution of components in the minced mass. An experimental model of a vibrating machine for mixing minced sausage ingredients has been developed. The calculation scheme of the investigated technical system of the process of vibration mixing of minced sausages “Ozdorovchi” is compiled. The equation of motion of the executive bodies of the system is compiled. The dependences for the equations of motion of the actuators of the vibration mixer are determined. Dependences for the main characteristics of the oscillatory system under study are calculated. Based on the analysis of the graphical representation of the amplitude-force dependences, the working amplitude of oscillations of the mixing tank is substantiated in the range of 2-2.5 mm. It is established that the implementation of the required operating oscillatory mode requires for a given capacity relatively small power consumption in the range of 500-600 W. Optimal parameters for mixing minced meat with vibration intensification of the process, as well as the use of appropriate ingredients, allow for achieving a comprehensive technological effect while minimising energy consumption. Therefore, the materials of the article are of practical value for the meat processing industry in the technology of boiled sausage products with health-improving properties

Aimed at the problem of low-frequency oscillations caused by cross-region power transmissioin of large-scale wind farms, a single neuron adaptive proportion integration differentiation (PID) additional damping control strategy for low-frequency oscillations of the damping system is proposed in this paper. By analyzing the dynamic frequency response characteristics of doubly-fed wind turbines, a wind farm damping system oscillation controller is constructed by introducing quadratic performance indicators into the single neuron adaptive PID control algorithm. By adaptively adjusting the excitation frequency converter, the wind farm can quickly generate active power and the maximum positive damping, and suppress the low-frequency oscillation of the damping system. MATLAB is used to build a four-machine two-region power system simulation model with a wind farm. The comparison verifies that the method proposed in this paper can effectively suppress the swing of the power angle of the synchronous generator when low-frequency oscillation occurs in the system, improve the inertial response of the system, and reduce the risk of low-frequency oscillation in the power grid.

The Mediterranean Sea is of great and manifold relevance for global oceanic circulation and climate: Mediterranean waters profoundly affect the salinity of the North Atlantic Ocean and hence the global ocean circulation. Ocean motions are forced fundamentally by the atmosphere. However, direct atmospheric forcing explains just a part of the observed Mediterranean circulation, for example, the former is not able to account for the observed north-south inclination of the sea level, one of the most prominent and persistent features of Mediterranean oceanography. This implies that a significant part of this circulation feature is caused by mechanisms that are all internal, “intrinsic” to the ocean. Yet, no effort has been made so far to disentangle intrinsic oceanic phenomena from atmospherically forced ones in the Mediterranean Sea. Here, we start filling this gap of knowledge. We demonstrate that a conspicuous part of the observed Mediterranean mean state and variability belongs to a skeleton captured for the first time by a multi-centennial ocean simulation without atmospheric forcing. This study paves the way to the identification and comprehension of further observed mean patterns and low-frequency fluctuations in the Mediterranean Sea as the result of intrinsic oceanic processes rather than by a direct effect of the atmospheric forcing and could be extended to other basins where geometry and hydrological structure significantly contribute to shaping the local dynamics.

The existing semi-fluidisation devices are described by high-energy consumption during operation, heavy metal structure, and complexity of the drive mechanism. Therefore, the search for effective heat exchange schemes in low-temperature processing of fruit and vegetable products, provided that its damage and energy consumption for the process are minimised, constitutes the relevance of this study. The purpose of this study was to determine and substantiate the amplitude-frequency and power mode parameters of the vibration wave driving organ of the semi-fluidisation machine for freezing fruit and berry products, the regularities of changes in the main characteristics of low-frequency vibrations in the process under study. To perform these tasks, an experimental model of a semi-fluidisation machine with a vibration wave driving organ was developed and a set of special devices was manufactured in the form of a microcontroller system that provides measurement and automatic adjustment of the main parameters of the process under study. Intensification of heat exchange in the process of fluidisation freezing in the conditions of a pseudo-suspended state of products is described by a high heat transfer coefficient, which can exceed typical convective processes by several orders of magnitude; an increase in the active heat exchange surface up to 100% is observed; the contact surface with the energy carrier increases proportionally, which leads to a decrease in the active temperature difference; there is a 2-3 times decrease in internal friction in the mass of products and, accordingly, the technological resistance in the mass of loading is reduced, which is a potential for increasing the technical and economic characteristics of the low-temperature processing under study. The practical value of this study can be attributed to the application of vibro-slush freezing of the proposed structure with a vibration-wave product driver and a spatial elastic system for levelling out parasitic vibrations, which allows simplifying the structure, reducing power loads and, accordingly, energy costs

Voltage instability in a power system produces low-frequency oscillations (LFOs), causing adverse effects in power distribution. Intelligent control schemes can overcome the limitations of fixed-parameter structures in power system stabilizers (PSS). Flexible alternating current transmission system (FACTS) control along with some supplementary control have remarkable potential in damping the oscillations. This paper proposes an adaptive neurofuzzy based recurrent wavelet control (ANRWC) scheme to enhance the power system stability. The proposed scheme utilizes recurrent Gaussian as antecedent part’s membership function and recurrent wavelet function in consequent parts. Our scheme uses gradient descent, adadelta, adaptive moment estimation (ADAM) and proximal gradient descent algorithms for optimization in which parameters of the scheme are updated using a back-propagation algorithm. A multi-machine power system is used for testing the controller. We evaluate the proposed control scheme in comparison to conventional lead-lag control and an adaptive neurofuzzy takagi sugeno kang (ANFTSK) control scheme. For comparison, we calculate the performance indices (PIs) for different controllers. Both quantitative and qualitative evaluations assert the effectiveness of the proposed control as compared to other schemes.

Dynamic interactions among the AC railway traction network and power electronics converters feeding the trains have been reported to cause low-frequency oscillations (LFO) of the catenary voltage and current. This can result in railway system instability, eventually leading to a power outage and the shutdown of the train traffic. To avoid LFO, control of train power electronic converters must be properly designed and tuned. Experimental verification of control performance regarding the LFO phenomenon in the railway traction network is not easy. Alternatively, the railway traction network can be emulated using a power electronic converter, which would feed the train power converter under test. This paper addresses the design of a network emulator able to reproduce the dynamic behavior of the actual network at low frequencies, including LFO. Three different options will be considered for the network emulator. Their performance will be studied first by means of simulations. Finally, the selected solution will be verified on a downscale test bench.

This paper aims at improving the Enhanced-PLL (E-PLL) to mitigate the transient low-frequency oscillations, which is inherent to single-phase circuits. These improvements resulted in a new PLL configuration, designated here as the Double-Frequency Mitigation SOGI-EPLL, or simply DFM-SOGiEPLL. We integrate the EPLL with a Second-Order Generalized Integrator (SOGI), by modifying the computation of the internal error signals of the phase-and-frequency loop and the amplitude loop. Thus, the proposed DFM-SOGiEPLL is able to extinguish transient low-frequency oscillations, in a short time period, in comparison to the conventional EPLL. A dynamic model approach of both EPLLs, including four different test-cases, was implemented through numerical simulations and hardware experiments to verify the better performance of the proposed one. [ABSTRACT FROM AUTHOR]

Synchronous generators are usually equipped with power system stabilizers (PSS) to damp low-frequency oscillations. Among the various types of PSS, it has recently been demonstrated that the Multi-Band PSS (MB-PSS) has a better performance to handle all global, inter-area and local modes. However, the performance of this PSS may degrade since the power supply system is intrinsically non-linear and its operating conditions frequently change. This paper introduces a new design of MB-PSS based on Mamdani Fuzzy inference (Fuzzy-MB-PSS). Compared to the IEEE standard MB-PSS, the proposed stabilizer is more efficient owing to its ability to deal with oscillations at different operating points. The controller is tested on a power system benchmark under various disturbance conditions to prove its robustness and to demonstrate its superiority over conventional PSS and MB-PSS. [ABSTRACT FROM AUTHOR]

Non-stationarity of extreme climate events has been reported worldwide in recent decades, and traditional stationary analysis methods are no longer sufficient to properly reveal the occurrence probability of climate extremes. Based on the 0.25°C × 0.25°C gridded precipitation data (i.e., CN05.1), stationary and non-stationary models of generalized extreme value (GEV) and generalized Pareto (GP) distributions are adopted to estimate the occurrence probability of extreme precipitation over China during 1961–2018. Low-frequency oscillation (LFO) indices, such as El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO), are included as time-varying covariates in the non-stationary GEV and GP models. Results illustrate that the occurrence probability of extreme precipitation estimated from the stationary GEV and GP distributions shows a significant increasing trend in northwestern and southeastern China, and the opposite trend in southwestern, central, and northeastern China. In comparison with stationary model, the fitness of extreme precipitation series is improved for both the GEV and GP distributions if these LFO indices are used as time-varying covariates. Positive ENSO, IOD and PDO tend to cause negative anomalies in the occurrence probability of extreme precipitation in northeastern China and Tibet Plateau, and positive anomalies in southern China. Positive NAO and SAM phases mainly tend to cause positive anomalies in southern China. The circulation patterns of extreme precipitation anomalies associated with these LFO indices are discussed from aspects of precipitable water, vertical integrated moisture transport, 500-hPa geopotential height and 850-hPa wind field.

Cerebrospinal fluid (CSF) movement through the pathways within the central nervous system is of high significance for maintaining normal brain health and function. Low frequency hemodynamics and respiration have been shown to drive CSF in humans independently. Here, we hypothesize that CSF movement may be driven simultaneously (and in synchrony) by both mechanisms and study their independent and coupled effects on CSF movement using novel neck fMRI scans. Caudad CSF movement at the fourth ventricle and hemodynamics of the major neck blood vessels (internal carotid arteries and internal jugular veins) was measured from 11 young, healthy volunteers using novel neck fMRI scans with simultaneous measurement of respiration. Two distinct models of CSF movement (1. Low-frequency hemodynamics and 2. Respiration) and possible coupling between them were investigated. We show that the dynamics of brain fluids can be assessed from the neck by studying the interrelationships between major neck blood vessels and the CSF movement in the fourth ventricle. We also demonstrate that there exists a cross-frequency coupling between these two separable mechanisms. The human CSF system can respond to multiple coupled physiological forces at the same time. This information may help inform the pathological mechanisms behind CSF movement-related disorders. [ABSTRACT FROM AUTHOR]

Evaluation of the influence of amplitude-frequency and power parameters of external technological action on bulk products in the process of separation of the impact, the way of lowfrequency oscillations of the working bodies of the separator and the angle of inclination of the container during processing determines the main indicators of technical and economic efficiency of the explored process, which is the relevance of the research. The purpose of the study is to substantiate the operating parameters of the explored separator of volume vibrations by determining the patterns of change in the kinematic and power characteristics of the vibration drive. To determine the rational parameters of the vibration screening process, the equations of motion of the working bodies in the form of a conical sieve surface were obtained using the method of Lagrange equations of the 2nd kind. Using the solution of the Cauchy problem for linear inhomogeneous differential equations, the solution of the latter was obtained. Using the Math CAD mathematical environment, the dependences of the amplitude of oscillations, vibration velocity and vibration acceleration, and the intensity of oscillatory motion were obtained, which allowed performing a mathematical analysis of the power and energy characteristics of the vibration drive of the explored separator. The main effects of the developed design of the vibrating separator are an increase in the driving force of the process of separation of bulk solids in this work, which was achieved by providing the working cylindrically-conical container with vibratory motion; improvement of the conditions for the passage of product particles through the perforations, which was achieved by providing the sieve surface with volumetric vibrations; reduction of energy consumption and improvement of the operating conditions of the supporting units during the operation of the designed vibrating screen, which was achieved by installing additional elastic elements between the separator body The inclined arrangement of the conical sieve surface allows for spatial gyratory or circular translational motion, which allows implementing of the advantages of bulk separation of bulk solids. The results of the analytical study allowed substantiation of the optimal angle of inclination of the working sieve surface. Based on the analysis, the design parameters of the vibration exciter were substantiated and specified and the design of this technical system was presented. The practical value of the conducted research can be attributed to using the designed kinematic combined vibration exciter of volumetric oscillations in the separator, which allows reducing the weight of the oscillating parts of the drive and, accordingly, the energy consumption for the separation process

Cerebrospinal fluid (CSF) movement through the pathways within the central nervous system is of high significance for maintaining normal brain health and function. Low frequency hemodynamics and respiration have been shown to drive CSF in humans independently. Here, we hypothesize that CSF movement may be driven simultaneously (and in synchrony) by both mechanisms and study their independent and coupled effects on CSF movement using novel neck fMRI scans. Caudad CSF movement at the fourth ventricle and hemodynamics of the major neck blood vessels (internal carotid arteries and internal jugular veins) was measured from 11 young, healthy volunteers using novel neck fMRI scans with simultaneous measurement of respiration. Two distinct models of CSF movement (1. Low-frequency hemodynamics and 2. Respiration) and possible coupling between them were investigated. We show that the dynamics of brain fluids can be assessed from the neck by studying the interrelationships between major neck blood vessels and the CSF movement in the fourth ventricle. We also demonstrate that there exists a cross-frequency coupling between these two separable mechanisms. The human CSF system can respond to multiple coupled physiological forces at the same time. This information may help inform the pathological mechanisms behind CSF movement-related disorders.

• Implementation of two low-frequency oscillation damping strategies on a doubly-fed asynchronous generator embodying a novel grid-forming control. • System stability assessment. • Control implementation in a real-time control platform. • Control tested on a comprehensive system model for inter-area oscillations analysis. • Inter-area oscillations are succesfully mitigated against two different disturbances. The integration of wind power generation into modern power systems necessitates the development of advanced control strategies to enhance grid stability and reliability. Among these strategies, grid-forming control has emerged as a promising solution, enabling converter-interfaced generation technologies to provide services traditionally supplied by conventional generation. This paper specifically addresses the challenge of low-frequency oscillations damping in power systems incorporating Doubly-Fed Induction Generators embodying grid-forming control. In this paper, two low-frequency oscillations damping strategies are proposed and tested, designed to complement a doubly-fed induction generator grid-forming control strategy. The first, called POD-Q, uses reactive power; while the second, POD-P, acts on the active power injection. Both strategies are analyzed through small-signal stability analysis and experimental testing. For the small-signal stability analysis, a dynamic model of a conventional system with a certain penetration of doubly-fed induction generation has been employed. Experimental results are obtained within a real-time simulation environment, using the hardware-in-the-loop technique to communicate a real controller board with the real-time simulator. The results indicate that the POD-P strategy is more efficient in low-frequency oscillations damping compared to a synchronous generator with a conventional power system stabilizer and also in comparison to the POD-Q strategy. However, both proposed strategies have demonstrated improvements in low-frequency oscillations damping. [ABSTRACT FROM AUTHOR]

• Mitigating fluctuations of output active power of WF. • Compensating output reactive power of WF. • Participating in system primary frequency regulation. • Providing damping control (POD) of inter-area oscillations. This paper presents a concept of multi-purpose Battery Energy Storage System (BESS) which is integrated into a large wind farm (WF). The BESS aims to suppress the fluctuation of the output of active power and reactive power of the wind farm WF, participate in frequency regulation and damp low-frequency oscillations. Firstly, the concept and structure of the multi-purpose of BESS is presented. After that, the digital twin technology is applied to configure the capacity of the BESS. The performance of the multi-purpose BESS is demonstrated in the two-area system model constructed using DIgSILENT PowerFactory. The simulation results show that the multi-purpose BESS significantly improves the stability of the system in terms of suppressing the fluctuation of the out of WF, frequency regulation and damping low-frequency oscillations, which is the essential step to the practical implementation of the multi-purpose BESS. [ABSTRACT FROM AUTHOR]

In order to better understand the extent to which global climate variability is linked to long-term mean and extreme sea level patterns, correlations between average sea levels at coastal sites throughout North America and low-frequency oscillations of several climate indices (CIs) were analyzed for the entire period of 1948–2018 as well as three equal-length sub-periods using correlation analysis. Correlation strength was assessed using Pearson’s correlation coefficient, while significance was estimated using Leave-One-Out Cross-Validation and a bootstrapping technique (p-value). The sliding window size, lag time, and beginning month were varied for optimal correlation; 60-month sliding windows, along with 0 lag time, resulted in the strongest correlations. Strong (r >= 0.60) and significant (p-value

Low-frequency oscillations are an inevitable phenomenon of a power system. This paper proposes an Ant lion optimization approach to optimize the dual-input power system stabilizer (PSS2B) parameters to enhance the transfer capability of the 400 kV line in the North-West region of the Ethiopian electric network by the damping of low-frequency oscillation. Double-input Power system stabilizers (PSSs) are currently used in power systems to damp out low-frequency oscillations. The gained minimum damping ratio and eigenvalue results of the proposed Ant lion algorithm (ALO) approach are compared with the existing conventional system to get better efficiency at various loading conditions. Additionally, the proposed Ant lion optimization approach requires minimal time to estimate the key parameters of the power oscillation damper (POD). Consequently, the average time taken to optimally size the parameters of the PSS controller was 14.6 s, which is pretty small and indicates real-time implementation of an ALO developed model. The nonlinear equations that represent the system have been linearized and then placed in state-space form in order to study and analyze the dynamic performance of the system by damping out low-frequency oscillation problems. Finally, conventional fixed-gain PSS improves the maximum overshoot by 5.2% and settling time by 51.4%, but the proposed optimally sized PSS employed with the ALO method had improved the maximum overshoot by 16.86% and settling time by 78.7%. [ABSTRACT FROM AUTHOR]

The relevance of the study is determined by the need to optimise the process of mixing minced meat in the production of sausages “Ozdorovchi” to reduce the duration of the technological operation, energy and raw material costs. Therefore, the article is concerned with the substantiation and determination of the amplitude-force parameters of a vibro-mechanical machine for mixing sausage mince ingredients. The leading method for studying this issue is mathematical modelling, which allows for comprehensive consideration of the patterns of changes in the main parameters of the oscillatory process. The article theoretically substantiates the expediency of using vibration impact to provide a rapid and uniform distribution of components in the minced mass. An experimental model of a vibrating machine for mixing minced sausage ingredients has been developed. The calculation scheme of the investigated technical system of the process of vibration mixing of minced sausages “Ozdorovchi” is compiled. The equation of motion of the executive bodies of the system is compiled. The dependences for the equations of motion of the actuators of the vibration mixer are determined. Dependences for the main characteristics of the oscillatory system under study are calculated. Based on the analysis of the graphical representation of the amplitude-force dependences, the working amplitude of oscillations of the mixing tank is substantiated in the range of 2-2.5 mm. It is established that the implementation of the required operating oscillatory mode requires for a given capacity relatively small power consumption in the range of 500-600 W. Optimal parameters for mixing minced meat with vibration intensification of the process, as well as the use of appropriate ingredients, allow for achieving a comprehensive technological effect while minimising energy consumption. Therefore, the materials of the article are of practical value for the meat processing industry in the technology of boiled sausage products with health-improving properties. [ABSTRACT FROM AUTHOR]

The modular multilevel matrix converter (M3C) is an ac to ac power converter composed of 9 arms and is proposed for high power applications such as motor drive and wind energy conversion systems. Energy Control of the M3C is achieved using four circulating currents, and is frequently divided into the different frequency mode (DFM) and equal frequency mode (EFM). EFM is more challenging, because of the larger capacitor voltage oscillations that can be produced. The control schemes are typically different for EFM/DFM operation and this further increases the complexity. In this article, a continuous-control-set model predictive control for energy management of the M3C is proposed. The control scheme is based on solving an equality constrained quadratic programming problem, where the optimal solution is analytically obtained. The result is a single and simple control law to obtain the circulating current references, where good performance is achieved for both EFM and DFM. The proposed strategy is experimentally validated using a scaled-down M3C prototype composed of 27 power cells. [ABSTRACT FROM AUTHOR]

It is vital to improve the stability of the power system by accurately identifying the modal parameters of damped low-frequency oscillations (DLFO) and controlling the oscillation in time. A new method based on empirical mode decomposition (EMD), stochastic subspace identification (SSI), and Prony algorithms, called synthetical modal parameters identification (SMPI) method, is developed by efficiently matching the modal parameters of DLFO which are acquired from the SSI and Prony algorithm. In this approach, EMD is used for denoising the raw oscillation signals thereby enhancing the noise resistance, and then using the SSI and Prony algorithms to identify the precise modal parameters assisted by parameter matching. It is demonstrated that the proposed SMPI method holds great accuracy in identifying full modal parameters including natural frequencies, damping ratios, amplitudes, and phase angles with simulated signals with known modal parameters and real-time signals from some power system case studies. The strategy of SMPI has effectively overcome the weakness of a single approach, and the identification results are promising to heighten the stabilization of power systems. Besides, SMPI shows the potential to troubleshoot in different fields, such as construction, aeronautics, and marine, for its satisfactory robustness and generalization ability. [ABSTRACT FROM AUTHOR]

• Analysis of focal epilepsy low-frequency oscillations prior to interictal epileptiform discharges (IEDs) using MEG. • Our study demonstrates consistent low-frequency oscillations prior to IED onset. • These results indicate that IEDs arise from a focal cortical inhibition. Interictal epileptiform discharges (IEDs) constitute a diagnostic signature of epilepsy. These events reflect epileptogenic hypersynchronization. Previous studies indicated that IEDs arise from slow neuronal activation accompanied by metabolic and hemodynamic changes. These might induce cortical inhibition followed hypersynchronization at IED onset. As cortical inhibition is mediated by low-frequency oscillations, we aimed to analyze the role of low-frequency oscillations prior the IED using magnetencephalography (MEG). Low-frequency (1–8 Hz) oscillations pre-IED ([-1000 milliseconds (ms), IED onset]) were analyzed using MEG in 14 focal epilepsy patients (median age = 23 years, range = 7–46 age). Occurrence of local pre-IED oscillations was analyzed using Beamformer Dynamical Imaging of Coherent Sources (DICS) and event-related desynchronization/synchronization (ERD-ERS) maps constructed using cluster-based permutation tests. The development of pre-IED oscillations was characterized using Hilbert transformation. All patients exhibited statistically significant increase in delta (1–4 Hz) and/or theta (4–8 Hz) oscillations pre-IED compared to baseline [-2000 ms, −1000 ms]. Furthermore, all patients exhibited low-frequency power increase up to IED onset. We demonstrated consistently occurring, low-frequency oscillations prior to IED onset. As low-frequency activity mediates cortical inhibition, our study demonstrates that a focal inhibition precedes hypersynchronization at IED onset. [ABSTRACT FROM AUTHOR]

In this paper, a new fractional-order fuzzy controller named proportional fuzzy ا integral fuzzy + deferential fuzzy (FP + Fla + FDp) is proposed. The proposed controller is single gain, integrate, derivative and fractional order in its structure. The controller has a structure with two adjustable fractions and is simply designed. This controller performs the stability process in a short time. The response time can also be changed by adjusting the coefficient of time scale a and p, which makes it more flexible and efficient compared to the classic PID controller. On the other hand, in the design of the proposed controller, the optimal adjustment of the controller gain and fuzzy members has turned into an optimization problem, which is done by a hybrid algorithm based on the vcs and the HBC colony (ABC) based on a function in the time domain. In the proposed hybrid algorithm, attempts have been made to take advantage of local and final search as the strengths of these controllers to dramatically reduce the possibility of locating in local points. Investigations of different load variation scenarios, better performance of the proposed controller facing load disturbances from the root mean square, rise and fall time, will show the number of oscillations, and the fall time of the frequency changes. [ABSTRACT FROM AUTHOR]