Fast Variations Research Articles

Nonequilibrium Control of Thermal and Mechanical Changes in a Levitated System.

Fluctuation theorems are fundamental extensions of the second law of thermodynamics for small nonequilibrium systems. While work and heat are equally important forms of energy exchange, fluctuation relations have not been experimentally assessed for the generic situation of simultaneous mechanical and thermal changes. Thermal driving is indeed generally slow and more difficult to realize than mechanical driving. Here, we use feedback cooling techniques to implement fast and controlled temperature variations of an underdamped levitated microparticle that are 1 order of magnitude faster than the equilibration time. Combining mechanical and thermal control, we verify the validity of a fluctuation theorem that accounts for both contributions, well beyond the range of linear response theory. Our results allow the investigation of general far-from-equilibrium processes in microscopic systems that involve fast mechanical and thermal changes at the same time.

A Comparison of Distribution Models for Fast Variations in the Indoor Radio Channel at 5G Frequency Range 1 Microwave Bands

The use of long-term (slow variations) for modelling radio propagation behavior in indoor scenarios limits the validity of such models, as most of the environments induced fast variations overlapped with the slow ones. Real world data gathered at different locations in two bands within Fifth Generation FR1 spectrum, 3 GHz and 5 GHz, provide insight on the effect of such fast variations and on the distribution models that would be useful to complement the long term analysis with short term behavior in order to improve the design of such 5G microwave networks. Comparisons among short term performance taking into account both the frequency, the visibility conditions and the environment size, shape and furnishing are presented with the focus on modelling as accurate as possible the narrowband channel. The use of ΔBIC (describing the difference between Bayesian Information Criteria indexes of each fitting) complements and confirms the insight provided by direct inspection on traditional fitting plots. This parameter could be interesting for future network deployments.

Pulsations of microwave emission from a solar flare in a twisted loop caused by intrinsic magnetohydrodynamic oscillations

ABSTRACT We present results revealing microwave pulsations produced in a model of a flaring twisted solar coronal loop, without any external oscillatory driver. Two types of oscillations are identified: slowly decaying oscillations with a period of about 70–75 s and amplitude of about 5–10 per cent seen in loops both with and without energetic electrons, and oscillations with a period of about 40 s and amplitude of a few tens of per cent observed only in loops with energetic electrons for about 100 s after the onset of fast energy release. We interpret the longer-period oscillations as the result of a standing kink mode modulating the average magnetic field strength in the loop, whilst the short-period intermittent oscillations associated with energetic electrons are likely to be produced by fast variations of the electric field, which produces energetic electrons in this scenario. The slowly decaying oscillations can explain the quasi-periodic pulsations often observed in the flaring corona.

Nonlinear Hierarchical Easy-to-Implement Control for DC MicroGrids

In this work is considered the connection of a photovoltaics (PV) solar plant to the main grid through a Direct Current (DC) MicroGrid and a hybrid storage system, composed of a battery and a supercapacitor, in order to satisfy constraints of grid connection (the so-called Grid-Codes). The objective, and main contribution of this paper, is to stabilize the DC MicroGrid voltage in spite of large variations in production and consumption, using a nonlinear hierarchical easy-to-implement control strategy. Here is presented the MicroGrid’s control design based on detailed models of the photovoltaic energy sources and the storage systems. Such DC grids may present an unstable behavior caused by the PV’s intermittent output power, by switching ripples from the power converters and their power electronics, and oscillatory currents produced by some types of loads. Therefore, the system is subject to both fast and slow variations, and its stabilization is based on different technologies of storage, such as battery and supercapacitor, and control algorithms designed thanks to the use of time-scale separation between different components of the storage systems. The obtained nonlinear results are stronger than current linear controllers, allowing to keep operating margins around the voltage reference. At the same time, in this work, insights from power systems practice have been used, aiming to obtain a very simple and easy-to-implement control scheme. Detailed simulation results are provided to illustrate the behavior and effectiveness of the proposed stabilization technique.

Online Learning for Adaptive Video Streaming in Mobile Networks

In this paper, we propose a novel algorithm for video bitrate adaptation in HTTP Adaptive Streaming (HAS), based on online learning. The proposed algorithm, named Learn2Adapt (L2A) , is shown to provide a robust bitrate adaptation strategy which, unlike most of the state-of-the-art techniques, does not require parameter tuning, channel model assumptions, or application-specific adjustments. These properties make it very suitable for mobile users, who typically experience fast variations in channel characteristics. Experimental results, over real 4G traffic traces, show that L2A improves on the overall Quality of Experience (QoE) and in particular the average streaming bitrate, a result obtained independently of the channel and application scenarios.

Fast data reduction by space partitioning via convex hull and MBR computation

Large volumes of training data introduce high computational cost in instance-based classification. Data reduction algorithms select or generate a small (condensing) set of representative training prototypes from the available training data. The Reduction by Space Partitioning algorithm is one of the most well-known prototype generation algorithms that repetitively divides the original training data into subsets. This partitioning process needs to identify the diameter of each subset, i.e., its two farthest instances. This is a costly process since it requires the calculation of all distances between the instances in each subset. The paper introduces two new very fast variations that, instead of computing the actual diameter of a subset, choose a pair of distant-enough instances. The first variation uses instances belonging to an exact 3d convex hull of the subset, while the second one uses instances belonging to the minimum bounding rectangle of the subset. Our experimental study shows that the new variations vastly outperform the original algorithm without a penalty in classification accuracy and reduction rate.

A regional geomagnetic field model over Southern Africa derived with harmonic splines from Swarm satellite and ground-based data recorded between 2014 and 2019

A regional harmonic spline geomagnetic main field model, Southern Africa Core Field Model (SACFM-3), is derived from Swarm satellite and ground-based data for the southern African region, in the eastern part of the South Atlantic Anomaly (SAA) where the field intensity continues to decrease. Using SACFM-3 and the global CHAOS-6-×9 model, a detailed study was conducted to shed light on the high spatial and temporal geomagnetic field variations over Southern Africa between 2014 and 2019. The results show a steady decrease of the radial component Z in almost the entire region. In 2019, its rate of decrease in the western part of the region has reached high values, 76 nT/year and 78 nT/year at Tsumeb and Keetmanshoop magnetic observatories, respectively. For some areas in the western part of the region the radial component Z and field intensity F have decreased in strength, from 1.0 to 1.3% and from 0.9 to 1.2%, respectively, between the epochs 2014.5 and 2019.5. There is a noticeable decrease of the field intensity from the south-western coast of South Africa expanding towards the north and eastern regions. The results show that the SAA area is continuing to grow in the region. Abrupt changes in the linear secular variation in 2016 and 2017 are confirmed in the region using ground-based data, and the X component shows an abrupt change in the secular variation in 2018 at four magnetic observatories (Hermanus, Hartebeesthoek, Tsumeb and Keetmanshoop) that needs further investigation. The regional model SACFM-3 reflects to some extent these fast core field variations in the Z component at Hermanus, Hartebeesthoek and Keetmanshoop observatories.Graphical

An Ensembled Spatial Enhancement Method for Image Enhancement in Healthcare.

Most medical images are low in contrast because adequate details that may prove vital decisions are not visible to the naked eye. Also, due to the low-contrast nature of the image, it is not easily segmented because there is no significant change between the pixel values, which makes the gradient very small Hence, the contour cannot converge on the edges of the object. In this work, we have proposed an ensembled spatial method for image enhancement. In this ensembled approach, we first employed the Laplacian filter, which highlights the areas of fast intensity variation. This filter can determine the sufficient details of an image. The Laplacian filter will also improve those features having shrill disjointedness. Then, the gradient of the image has been determined, which utilizes the surrounding pixels for the weighted convolution operation for noise diminishing. However, in the gradient filter, there is one negative integer in the weighting. The intensity value of the middle pixel might be deducted from the surrounding pixels, to enlarge the difference between the head-to-head pixels for calculating the gradients. This is one of the reasons due to which the gradient filter is not entirely optimistic, which may be calculated in eight directions. Therefore, the averaging filter has been utilized, which is an effective filter for image enhancement. This approach does not rely on the values that are completely diverse from distinctive values in the surrounding due to which it recollects the details of the image. The proposed approach significantly showed the best performance on various images collected in dynamic environments.

Intelligence Enabled by 2D Metastructures in Antennas and Wireless Propagation Systems

The development of the next generation of wireless systems is bringing renewed attention to the physical layer of the communication link. Indeed, the new low-latency requirements cannot be satisfied relying only upon the extreme virtualization of the hardware functions. Moreover, conventional wireless systems with fixed characteristics and functionalities are not appropriate to modern electromagnetic environments, which undergo continuous and fast variations. Embedded smartness is a required feature for widening the range of the possible electromagnetic responses to support advanced and novel functionalities. In this paper, we show how the combination of 2D metastructures with conventional antennas and reflectors enables an unprecedented electromagnetic behavior, which is at the basis of new properties, capabilities, and applications. In particular, we propose an emerging design approach based on the shifting of the reconfigurability, adaptivity, sensing, and power management of a wireless system at the physical level, thanks to the use of properly designed 2D metastructures to be coupled with standard antennas and reflectors.

Efficient Flatness Based Energy Management Strategy for Hybrid Supercapacitor/Lithium-ion Battery Power System

This article offers a flatness theory-based energy management strategy (FEMS) for a hybrid power system consisting of a supercapacitor (SC) and lithium-ion battery. The proposed FEMS intends to allocate the power reference for the DC/DC converters of both the battery and SC while attaining higher efficiency and stable DC bus voltage. First, the entire system model is analyzed theoretically under the differential flatness approach to reduce the model order as a flat system. Second, the proposed FEMS is validated under different load conditions using MATLAB/Simulink. Thus, this FEMS provides high-quality energy to the load and reduces the fluctuations in the bus voltage. Moreover, the performance of the FEMS is compared with the load following (LF) strategy. The obtained results show that the proposed FEMS meet the real load power under fast variations with good power quality compared to the classical LF strategy, where the maximum overshoot of the bus voltage is 5%.

Fast and Efficient Target Appearance Variations Consistency Tracking

Fast and Efficient Target Appearance Variations Consistency Tracking

Frequency Excursion Likelihood Constrained Resource Scheduling for Large-Scale Renewable Energy Integration

Net-load variability and uncertainty in high renewable penetration networks have imposed new challenges to the system operators; adequate ramping, restart, and wider frequency and voltage operation capabilities provided by responsive resources are required to preserve acceptable service quality. Flexibility indicators and resource requirement constraints are proposed for unit commitment studies to address fast net-load variations. However, there is a gap in demonstrating the application of proposed flexibility indicators to determine the required minimum cost flexibility reserves to maintain desired operational performance. To address this issue for system operation planning purposes, a two-stage corrective flexibility constrained unit commitment (FCUC) formulation supported by a data-driven scheme for uncertainty quantification of flexibility shortage driven under and over frequency events is proposed. The first stage unit commitment (UC) is solved with relaxed flexibility constraints to determine the nominal resource schedules. A statistical test is used to determine if the second stage UC is needed. The second stage UC is solved with tighter flexibility constraints. A procedure to quantify the additional flexibility resources needed in the second stage UC to achieve adequate frequency regulation performance with lower operational costs is presented. Test results under various operation scenarios and comparisons with previous flexibility deployment methods illustrate the effectiveness of the proposed method. Test results indicate that in certain situations, flexible resources should remain online and be prioritized against less flexible (although cheaper) resources. The costs incurred by the additional system flexibility required to maintain good frequency control performance can be evaluated.

The Computational Fluid Dynamics (CFD) Analysis of the Pressure Sensor Used in Pulse-Operated Low-Pressure Gas-Phase Solenoid Valve Measurements.

This paper presents a flow analysis of the original pressure sensor used to determine times until full opening and closing of the pulse-operated low-pressure gas-phase solenoid valve. The sensor in question, due to the fast variation of the process lasting several milliseconds, has high requirements in terms of response time and ability to identify characteristic parameters. A CFD code has been employed to successfully model the flow behavior of the original pressure sensor used to determine times until full opening and closing of the pulse-operated low-pressure gas-phase solenoid valve at different inlet flow conditions, using the Eulerian multiphase model, established on the Euler–Euler approach, implemented in the commercial CFD package ANSYS Fluent. The results of the modelling were validated against the experimental data and also give more comprehensive information on the flow, such as the plunger displacement waveform. The flow calculations were dynamic in nature; therefore, the experimental plunger displacement waveforms were entered as input in the software for dynamic mash implementation. In identifying the times until full opening and closing, the characteristic points of the pressure waveform on the pressure sensor plate were adopted. CFD flow calculations confirmed the accuracy of identifying the times until full opening and closing by relating them to the results from the plunger displacement sensor. The validation of the results of calculations with the analyzed sensor and the original stand also confirmed the correctness of the use of this type of method for the assessment of gas injector operating times. In the case of time until full opening, the CFD calculations were shown to be consistent with experimental tests, with only a few cases where the relative difference with respect to the displacement sensor reached 3%. The situation was slightly worse in the case of time until full closing, where the results of CFD calculations were in agreement with the displacement sensor, while the experimental test stands had a relative difference of up to 21%. It should be remembered that the sensor evaluates times below 5 × 10−3 s, and its construction and response time determine the use depending on the adopted level of accuracy.

SATWIKA LIFE STYLE THROUGH THE DESIGN OF MEASURING EQUIPMENT BODY MASS INDEX (BMI) BASED ON IOT

<span>The satwika lifestyle refers to the understanding that the physical body should be </span><span>maintained through wise thoughts and behavior in determining what is good and bad for the </span><span>body so that it is always in a fit and fit state. Technology affects the lifestyle of modern society. </span><span>Practical lifestyles are not necessarily balanced with health awareness. Fast food variations and </span><span>online food delivery services are practical choices even though they do not meet nutritional </span><span>standards that can affect health quality. Body Mass Index (BMI) can be an indicator of health, </span><span>so it can guide a person to control the food consumed. This study innovates the development </span><span>of a manual BMI measurement tool at STMIK STIKOM Indonesia into a BMI measurement </span><span>tool that can be accessed online with a concept called IoT (Internet Of Things). The design of </span><span>the IoT Based BMI Measurement Tool at STMIK STIKOM Indonesia is expected to help </span><span>lecturers, staff, and students at STMIK STIKOM Indonesia to be able to check their BMI </span><span>regularly so that they can optimize the satwika lifestyle. The data of this research were obtained </span><span>by conducting observation, e-questionnaire, and interview methods and then elaborated with </span><span>qualitative descriptive to describe that the BMI measuring instrument can function and assist </span><span>the academic community of STMIK STIKOM Indonesia in maintaining a satwika lifestyle.</span>

A uniformly accurate numerical method for a class of dissipative systems

We consider a class of ordinary differential equations mixing slow and fast variations with varying stiffness (from non-stiff to strongly dissipative). Such models appear for instance in population dynamics or propagation phenomena. We develop a multi-scale approach by splitting the equations into a micro part and a macro part, from which the original stiffness has been removed. We then show that both parts can be simulated numerically with uniform order of accuracy using standard explicit numerical schemes. As a result, solving the problem in its micro-macro formulation can be done with a cost and an accuracy independent of the stiffness. This work is also a preliminary step towards the application of such methods to hyperbolic partial differential equations and we will indeed demonstrate that our approach can be successfully applied to two discretized hyperbolic systems (with and without non-linearities), though with some ad-hoc regularization.

Far Fields of Internal Gravity Waves under Fast Density Variation in a Radial Symmetry Source

Far Fields of Internal Gravity Waves under Fast Density Variation in a Radial Symmetry Source

Computation of gravitational particle production using adiabatic invariants

Analytic and numerical techniques are presented for computing gravitational production of scalar particles in the limit that the inflaton mass is much larger than the Hubble expansion rate at the end of inflation. These techniques rely upon adiabatic invariants and time modeling of a typical inflaton field which has slow and fast time variation components. A faster computation time for numerical integration is achieved via subtraction of slowly varying components that are ultimately exponentially suppressed. The fast oscillatory remnant results in production of scalar particles with a mass larger than the inflationary Hubble expansion rate through a mechanism analogous to perturbative particle scattering. An improved effective Boltzmann collision equation description of this particle production mechanism is developed. This model allows computation of the spectrum using only adiabatic invariants, avoiding the need to explicitly solve the inflaton equations of motion.

Geographic Variation in the Petiole-Lamina Relationship of 325 Eastern Qinghai-Tibetan Woody Species: Analysis in Three Dimensions.

The petiole–lamina relationship is central to the functional tradeoff between photosynthetic efficiency and the support/protection cost. Understanding environmental gradients in the relationship and its underlying mechanisms remains a critical challenge for ecologists. We investigated the possible scaling of the petiole–lamina relationships in three dimensions, i.e., petiole length (PL) vs. lamina length (LL), petiole cross sectional area (PCA) vs. lamina area (LA), and petiole mass (PM) vs. lamina mass (LM), for 325 Qinghai–Tibetan woody species, and examined their relation to leaf form, altitude, climate, and vegetation types. Both crossspecies analysis and meta-analysis showed significantly isometric, negatively allometric, and positively allometric scaling of the petiole–lamina relationships in the length, area, and mass dimensions, respectively, reflecting an equal, slower, and faster variation in the petiole than in the lamina in these trait dimensions. Along altitudinal gradients, the effect size of the petiole–lamina relationship decreased in the length and mass dimensions but increased in the area dimension, suggesting the importance of enhancing leaf light-interception and nutrient transport efficiency in the warm zones in petiole development, but enhancing leaf support/protection in the cold zones. The significant additional influences of LA, LM, and LA were observed on the PL–LL, PCA–LA, and PM–LM relationships, respectively, implying that the single-dimension petiole trait is affected simultaneously by multidimensional lamina traits. Relative to simple-leaved species, the presence of petiolule in compound-leaved species can increase both leaf light interception and static gravity loads or dynamic drag forces on the petiole, leading to lower dependence of PL variation on LL variation, but higher biomass allocation to the petiole. Our study highlights the need for multidimension analyses of the petiole–lamina relationships and illustrates the importance of plant functional tradeoffs and the change in the tradeoffs along environmental gradients in determining the relationships.

Prediction of wind farm reactive power fast variations by adaptive one-dimensional convolutional neural network

One of the prominent problems in wind farms is voltage flicker emission. To prevent flicker emission or mitigate the impact as best as possible, a static VAr compensator (SVC) is a great candidate both economically and technically. However, SVCs cannot completely compensate the fast-changing reactive power due to delays caused by the reactive power calculation unit and the triggering fire angle of the SVC. This paper proposes a predictive control system for SVCs, by merging an additional predictive control block into the conventional control system. It is constructed based on deep neural networks, namely adaptive one-dimensional convolutional neural network (1D-CNN). The training process is conducted based on the adaptive learning weights process to enhance the prediction accuracy and training computational complexity of the 1D-CNN. Numerical results on the actual dataset in a wind farm in Manjil, Iran, have verified the forecasting accuracy and flicker mitigation of the proposed controller.

Superconducting magnetic energy storage coupled static compensator for stability enhancement of the doubly fed induction generator integrated system

The presence of intermittent Renewable Energy Sources (RES) has insisted on the need of finding more feasible solutions to the rising stability and reliability issues. The wind-based energy systems have emerged as prominent energy source leading to its large capacity integration in the system. Doubly Field Induction Generator (DFIG) based wind power plant, due to its various advantages are gaining popularity in the energy sector. So, it is very important to examine the stability issues and maintaining the grid connectivity in the presence of DFIG, as these are very sensitive to transient conditions. The energy storage devices can play a crucial role in mitigating these dynamic variations. In this research work,the application of the Static Compensator (STATCOM) coupled Superconducting Magnetic Energy Storage (SMES) controller is investigated for mitigating transient stability issues in the presence of DFIG connected system. The paper represents a novel control scheme for the DC link chopper circuit between STATCOM and SMES. The proposed control scheme considers the impact of three phase symmetrical fault and fast wind speed variations on the system consisting of Synchronous Generator (SG) and DFIG based Wind Energy System (WES). The comparative study of different parameters of SG and DFIG with and without the presence of this controller has been analyzed using MATLAB/Simulink environment. Simulation results indicate that the proposed control scheme can damp the oscillations of the system quickly and can achieve its equilibrium state at earliest, thus improving the stability of the system.