Intermittent Behavior Research Articles

Signature of intermittency during emission of target associated particles in heavy ion collisions at SPS energies

A study of intermittent type of fluctuations of target fragments produced in the interactions of 32 S-AgBr at 200 AGeV using the method of scaled factorial moments, F q has been performed. An intermittent behaviour is observed for fast and slow target fragments for the experimental data in terms of new scaled variable X(Cosθ) suggested by Bialas and Gazdzicki. The variations of the anomalous fractal dimensions, d q , and the generalized dimensions, D q , with the order of the moments, q , are investigated with the help of F q , moments. The anomalous dimension, d q increases linearly with the order of moments, q, suggesting the multifractality with the production mechanism of target associated fragments.

Locomotion, interactions and information transfer vary according to context in a cryptic fish species

The behaviour of animals is strongly influenced by the detection of cues relating to foraging opportunity or to risk, while the social environment plays a crucial role in mediating their behavioural responses. Despite this, the role of the social environment in the behaviour of non-grouping animals has received far less attention than in social species. Here, we present the results of an experiment on a cryptic species of goby (Pseudogobius sp.), which does not form social groups in its natural habitat. Gobies were presented sequentially with chemical cues relating to food, conspecific alarm and control, while in the presence of conspecifics. The intermittent locomotory behaviour of the gobies, which is typical of many cryptic animals, was influenced by the type of cues presented. Gobies decreased the duration of bouts of stasis in the presence of food cues and were generally more active. By contrast, those detecting alarm cues decreased the duration of movement bouts and were generally less active. In line with previous studies involving shoaling species, gobies in the presence of food cues adopted a more dispersed distribution, while clustering together in the presence of alarm cues. Finally, we used calculations of transfer entropy as a means of inferring information transfer among experimental subjects. In contrast to previous studies that have focused on social species, transfer entropy between gobies was detectable only in the conspecific alarm treatment. Taken together, our results show that members of this cryptic species detect and respond to chemical cues by adjusting their movement and distancing to conspecifics. Furthermore, they augment their own information with social cues but only when they perceive a threat. Animals are routinely exposed to an array of cues within their environment that convey valuable information about risk and foraging opportunities and must adapt their behaviour accordingly. To facilitate this, animals often use information arising from the behaviour of conspecifics to inform their own responses; however, this has rarely been considered in species which do not exhibit strong grouping tendencies. We used a non-shoaling fish, the goby (Pseudogobius sp.), to examine both their responses to ecologically relevant cues and the effect of the social environment on these responses. The gobies adapted their distances relative to one another according to the cues present and responded most strongly to information arising from conspecifics (measured as transfer entropy) in the presence of a potential threat. This demonstrates the potential importance of social information even to species that do not live in social groups with others of their own kind.

Forecasting of photovoltaic power using probabilistic approach

With the developing establishment in the power network of photovoltaic sources and the increasing demand, the requirement of Photovoltaic plants is essential. But the major drawback in PV system is forecasting of power generation because of intermittent behavior of solar energy. Power produced by PV majorly depends on environmental conditions like temperature, irradiance, and humidity which are highly uncertain in nature.Using probabilistic distribution functions, the probability of solar irradiance and temperature is predicted in three seasons i.e., summer, rainy and winter season. The predicted values of temperature and irradiance are used to forecast PV output power for three seasons i.e., summer, winter and rainy seasons. The forecasted PV output power is useful to meet the load demand with reliability and can be used for extending the capacity of PV plant to meet future load demand.

Exploring the consequences of patient commitment to cardiac rehabilitation program: A qualitative study.

BACKGROUND:Commitment to implementing cardiac rehabilitation (CR) plays an important role in managing the problems caused by heart diseases. Commitment to the treatment plan implementation is accompanied by numerous positive consequences. This study was carried out to explain the consequences of commitment to CR.MATERIALS AND METHODS:Data were collected through semi-structured individual interviews with 26 participants (13 CR specialists and 13 patients), using purposeful sampling. Interview questions focused on the factors influencing the formation of commitment to the CR and its consequences. Conventional content analysis with Graneheim and Lundman's approach was used to analyze the data. To obtain data trustworthiness, Lincoln and Guba's criteria were used.RESULTS:The findings were classified in three categories: purposeful of a purposeful behavior structure (sense of controlling and managing the condition, sense of responsibility, sense of security), formation of active performance structure (interaction between the patient-family-treatment team, stabilization of behavior and prevention of intermittent behavior, no cessation of the treatment plan and adherence to it, directing behaviors and adaptation to conditions) and achieving dynamic and effective care (active follow-up of the treatment plan, sense of satisfaction, reduced readmission, reduced costs, improved quality of life, reduced anxiety and concerns about treatment failure, increased self-care ability).CONCLUSION:The results show that the patient's commitment to CR is accompanied by optimal consequences. The results of this study can help design the training plan for the CR staff and develop the clinical practice guidelines to provide educational-care approaches to patients to reinforce their commitment.

On the non-monotonic behaviour of fire spread

A conceptual model based on the dynamic interaction between fire, the fuel bed and the surrounding flow to explain the non-monotonic or intermittent behaviour of fires is proposed. According to the model, even in nominally permanent and uniform boundary conditions, the fire-induced flow modifies the geometry of the flame and its rate of spread. After an initial acceleration, there is a reduction in the rate of spread followed by one or more cycles of growth. Carefully controlled experiments of fires in slopes and canyons show that the evolution of fire properties, namely flame angle and rate of spread, have high-frequency oscillations superimposed on the low-frequency fire growth cycle described above.

Power quality enhancement of a hybrid energy source powered packed e-cell inverter using an intelligent optimization technique

The most installed Renewable Energy Sources (RES) in micro-grids (MG) are Photovoltaic (PV) power and wind power. Due to the intermittent behaviour of renewable sources, parallel operation of RES and battery storage known as hybrid system is important particularly in remote micro-grids to reduce the fuel consumption by diesel generators and continuity of supply to the load. In this paper, multilevel inverter called Packed E-Cell (PEC) is used for parallel operation of RES and battery storage optimally for micro-grid applications. The PEC requires less components compared to other Multi-level inverters (MLI) topology with relatively low total harmonic distortion (THD). Further, selective harmonic technique based on optimization principle is used to enhance the harmonic profile using low frequency switching technique. The 3rd and 5th harmonics are eliminated using Genetic Algorithm (GA) optimization technique. The simulation-based analysis is done using Simulink/MATLAB and the results obtained for THD in the output current and voltage are presented and discussed in the paper. A comparative analysis is also presented with high frequency modulation technique phase disposition pulse width modulation (PDPWM) technique. The experimental validation of the proposed scheme is done using Typhoon HIL (hardware in loop).

Intelligent energy flow management of a nanogrid fast charging station equipped with second life batteries

In this paper we investigate a public Fast Charge (FC) station nanogrid equipped with a Photovoltaic (PV) system and an Energy Storage System (ESS) using second-life Electric Vehicle (EV) batteries. Since the nanogrid is intended for installation in urban areas, it is designed with a very limited connection with the grid to assure peak shaving and encourage PV autoconsumption. To demostrate the effectiveness of this approach to FC stations, an Energy Management System (EMS) is developed to manage the energy demand uncertainty of EVs and the power gap between the grid connection and the FC service. In particular, we propose a machine learning procedure for the automatic synthesis of a suitable (fuzzy) rule-based EMS. Indeed, we posit that a prediction based EMS would result not effective because of the stochastic and intermittent behavior of the FC load, and that a crisp rule-based system, defined by expert knowledge, would be too limited to capture uncertain behavior. The concept is demonstrated in a simulated environment inspired by the “Smart Columbus” project, implementing a mixed deterministic-stochastic process to simulate EV energy demand. In particular, different EV fleets and PV sizes are considered for EMS training, offering insights into the optimal size of PV system and nanogrid system effectiveness. The proposed approach is evaluated by comparing the EMS performance with related optimal benchmark solutions, evaluated by considering known a priori the overall PV and FC demand. The results show that the EMS performance is approximately within 10% of the benchmark optimal value.

Thermal modeling and triple objective optimization of a new compressed air energy storage system integrated with Rankine cycle, PEM fuel cell, and thermoelectric unit

Intermittent behavior of renewable energy triggered researchers for using energy storage systems to provide continues operation of renewable-based energy systems. In the current study, an integrated energy system including compressed air energy storage, Rankine cycle, Proton Exchange Membrane (PEM) fuel cell (FC), and thermoelectric generator (TEG) modules are investigated to introduce a new system. To show effects of adding TEG units and PEM fuel cell in the new configuration, three arrangements including conventional compressed air energy storage system (CAES), CAES/TEG and CAES/TEG-FC are investigated. It is found that the proposed CAES/TEG-FC system energy efficiency is 31.85%, which is 1.6% higher than conventional CAES. The exergy efficiency of CAES/TEG-FC is 35.13%, which is 1.44% higher than the conventional one. The proposed system generates 35.6 kW hot water and charge/discharge time are 2.91 hr/4.64 hr. A parametric analysis conducted on the discharge mass flow rate, intercooler outlet temperature, compression pressure ratio, and wind velocity with charging time, exergy efficiency, and total useful products as three major outputs. The tri-objective optimization shows by the technique for order of preference by similarity to ideal solution the optimized value of exergy efficiency, total useful output, and charge time are 34%, 1078.46 kW, and 5.28 hr.

Short-term electricity load and price forecasting by a new optimal LSTM-NN based prediction algorithm

Nowadays, a basic commodity for a human being to lead a standard lifestyle with human comfort irrespective of the nature of environmental conditions is electric power. The electricity load demand increases tremendously especially for a metropolitan city due to climatic conditions, population growth, local area development, industries expansion, air pollution, thermal device usage, etc. Hence, the accuracy of electricity load and its price forecasting is a deciding factor for the power distribution network to retain as an efficient, sustainable, and secure consumer-friendly network. On the other hand, based on the volatile, intermittent, and uncertain behavior of electricity load and price, an accurate, and robust forecast model should be designed. In this paper, a new hybrid forecast model for short-term electricity load and price prediction has been developed. The proposed method includes three modules: wavelet transform that is used to eliminate fluctuation behaviors of the electricity load and price time series, feature selection based on entropy and mutual information has been proposed to rank candidate inputs and eliminate redundant inputs according to their information value, and a new learning algorithm. The proposed learning method consists of a deep learning algorithm with LSTM networks which improves the accuracy of predictions. The performance of the proposed method has been validated successfully on load and price data collected from the Pennsylvania-New Jersey-Maryland (PJM) and Spain electricity markets. Also, for further test, the load data in Iran have been used.

Awake delta and theta-rhythmic hippocampal network modes during intermittent locomotor behaviors in the rat.

Delta-frequency network activity is commonly associated with sleep or behavioral disengagement accompanied by a dearth of cortical spiking, but delta in awake behaving animals is not well understood. We show that hippocampal (HC) synchronization in the delta frequency band (1-4 Hz) is related to animals' locomotor behavior using detailed analyses of the HC local field potential (LFP) and simultaneous head- and body-tracking data. In contrast to running-speed modulation of the theta rhythm (6-10 Hz), delta was most prominent when animals were stationary or moving slowly, that is, when theta and fast gamma (65-120 Hz) were weak, and often developed rapidly when animals paused briefly between runs. We next combined time-frequency decomposition of the LFP with hierarchical clustering algorithms to categorize momentary estimations of the power spectral density (PSD) into putative modes of HC activity. Delta and theta power were strikingly orthogonal across spectral modes, as well as across bouts of precisely defined running and stationary behavior. Delta-band and theta-band coherences between HC recording sites were monotonically related to theta-delta ratios across modes; and whereas theta coherence between HC and medial prefrontal cortex (mPFC) increased during running, delta-band coherence between mPFC and HC increased during stationary bouts. Taken together, our findings suggest that delta-dominated network modes (and corresponding mPFC-HC couplings) represent functionally distinct circuit dynamics that are temporally and behaviorally interspersed among theta-dominated modes during navigation. As such, delta modes could play a fundamental role in coordinating encoding and retrieval mechanisms or decision-making processes at a timescale that segments event sequences within behavioral episodes. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Event‐based switching control for networked switched systems under nonperiodic DoS jamming attacks

This study addresses the event-based control of networked switched systems subject to cyber attacks. A novel mode-based event-triggered mechanism is proposed, which is capable of characterising non-periodic denial-of-service (DoS) attacks. A switching control law is employed in each subsystem to weaken the negative effects caused by DoS attacks. The time sequences of system switchings, event triggerings and intermittent DoS attack behaviours are fully investigated, which yields a resultant closed control system. Then, by using piecewise Lyapunov functional methods, sufficient conditions are formulated to guarantee the concerned system exponentially stable. Meanwhile, the co-design methods for switching controllers and event-triggering parameters can be developed. Finally, a numerical simulation example and a practical example of a second-order oscillating circuit are presented to verify the proposed methods.

Chimera states in coupled map lattices: Spatiotemporally intermittent behavior and an equivalent cellular automaton.

We construct an equivalent cellular automaton (CA) for a system of globally coupled sine circle maps with two populations and distinct values for intergroup and intragroup coupling. The phase diagram of the system shows that the coupled map lattice can exhibit chimera states with synchronized and spatiotemporally intermittent subgroups after evolution from random initial conditions in some parameter regimes, as well as to other kinds of solutions in other parameter regimes. The CA constructed by us reflects the global nature and the two population structure of the coupled map lattice and is able to reproduce the phase diagram accurately. The CA depends only on the total number of laminar and burst sites and shows a transition from co-existing deterministic and probabilistic behavior in the chimera region to fully probabilistic behavior at the phase boundaries. This identifies the characteristic signature of the transition of a cellular automaton to a chimera state. We also construct an evolution equation for the average number of laminar/burst sites from the CA, analyze its behavior and solutions, and correlate these with the behavior seen for the coupled map lattice. Our CA and methods of analysis can have relevance in wider contexts.

An advanced technique for determining NC machining tool path to fabricate drawing die surface considering non-uniform thickness distribution in stamped blank

Drawing process represents a significant area of production technology since it influences the feasibility of producing auto-body die panels. In the drawing process, the plastic deformation of blank is not uniform due to the intermittent deformation behavior of the material. This primes a non-uniform thickness distribution in the formed panels, which directly affects the die life and the quality of panels. In the presented study, a new algorithm was proposed for constructing the numerical control machining tool path for the new die surface obtained from FEM simulation and mesh mapping. The commercial package LS-DYNA was employed for the FEM simulation and to calculate the thickness distribution in the drawn workpiece. In order to construct the new numerical control machining tool path according to the new die surface, the positions of all cutter location points relative to the movement of new die mesh were determined. A set of forming die was machined using the proposed algorithm to fabricate a real workpiece of steel DC04. A comparison between the measured thicknesses in the fabricated workpiece and the FEM simulation results shows that they agree with each other very well, which directly validates the proposed algorithm. The developed method can improve product quality, increase production efficiency, and reduce labor intensity.

Impact of turbulence on the coherent flame dynamics in a bluff-body stabilized flame

Coherent flame oscillations generated by large-scale flow instabilities have been shown to significantly influence combustor performance and thermoacoustic instability. This study examines the influence of turbulence intensity on the large-scale dynamics of rod-stabilized flames. Instability in the flow field of a bluff-body stabilized flame, which is a function of mean shear in the flow field, turbulence intensity of the incoming flow, and the location of the flame with respect to the shear layer, manifests as coherent vortex shedding. However, this vortex shedding is not self-excited if the flow is globally stable, as is often the case in reacting flows. In this experiment, time-resolved, three-component velocity measurements from high-speed stereoscopic particle image velocimetry are taken at three turbulent inlet flow conditions and at three bulk flow velocities. To identify whether these instabilities occur, the velocities fields are filtered using a wavelet transform around select spectral bands and then decomposed using proper orthogonal decomposition to extract the most energetic motion in the flow; this filtering method retains any time-dependent, intermittent behavior. The results show that vortex shedding is intermittent and the degree of intermittency is dependent on the in-flow turbulence level. Although all the cases tested were determined to be globally stable, variations in the flow velocity change the structure of the flame and flow, which alters the receptivity of the flow to turbulent perturbations. As a result, the strength and regularity of vortex shedding increase with increasing turbulence level and increased receptivity, indicating that the system is a noise-forced globally-stable oscillator.

Experimental study of bidirectional seiching in an open-channel, lateral cavity in the time and frequency domain

This experimental laboratory study presents a detailed analysis of the surface oscillations inside a square cavity connected laterally to an open channel. For an approaching steady and one-dimensional main stream with a high (subcritical) Froude number, interaction with the dead water volume in the cavity area triggers high-amplitude free-surface oscillations, denoted seiches. In the present study, the length of the square cavity equals half of the combined width of the cavity and the main channel. This particular geometry enables two-dimensional or bidirectional seiching with standing waves being excited in both directions simultaneously. In this work, the (relative) magnitude of the different seiching modes (transverse and longitudinal) is measured and analyzed for a range of flow conditions with varying Froude number. The current experimental results confirm earlier findings indicating that the magnitude and dominance of the longitudinal seiching mode (with respect to the transverse mode) grows with increasing Froude number of the main stream. Additionally, a wavelet analysis in the time and frequency domains reveals that the amplitude of the two modes fluctuates significantly in the course of a single experiment, such that seiching cannot be considered a steady phenomenon. Therefore, two alternative strategies are presented to quantify the amplitude of both modes using a more time-localized approach that is less affected by the intermittent behavior of seiching. Although more research is necessary to fully understand what determines the dominant mode at a given moment, an in-depth analysis of the surface recordings at multiple locations in the cavity suggests that the transition from transverse to longitudinal seiching (and vice versa) is related to the phase difference between the bidirectional seiching waves at the (inner) corners of the cavity.

Simultaneous sitting and sizing photovoltaic unit and distribution static compensator in distribution grid considering the effect of geographical conditions

AbstractThis paper proposes a model to allocate photovoltaic unit (PVU) and distribution static compensator (DSTATCOM) that incorporate the operation effect of PVU in sizing and sitting problem. The model is based on the dynamic assessment of PVU production and the effect of it on placement of PVU and DSTATCOM. Geographical conditions are interfered in placement problem of PVU and DSTATCOM simultaneously. The model is verified in a multi‐objective form. The multi‐objective problem is formulated based on voltage stability, liability, power loss and total cost of PVU and DSTATCOM. This problem is solved by employing optimization technique and the results of optimization processes are tested in different scenarios. Uncertainty in network loads is an inevitable task that should be considered in network planning. Uncertainty in the presented model has been defined as a set of divided parts in the presented model. The proposed model has been evaluated on two test system, 33‐bus and 69‐bus. The obtained results indicate that the presented model can be employed to study the intermittent behavior of PVU in placement problem.

Adaptive bidding strategy for real-time energy management in multi-energy market enhanced by blockchain

Energy trading in the multi-energy market is affected by many uncertainties, especially the fluctuation of renewable energy sources and intermittent demand behavior of customers. The real-time energy management can effectively solve the impact of various uncertainties, ensure the instantaneous balance of energy and improve trading returns. A bidding strategy for multi-energy market is presented, in which reserve price adjustment and dynamic compensation mechanism is innovatively integrated into adaptive learning process. All energy trading participants conduct adaptive learning bidding adjustment based on real-time information in order to obtain higher transaction rate and transaction income. Meanwhile, adding dynamic compensation to the quoted price of fossil energy increases the consumption rate of renewable energy and reduces the emissions of pollutants. Furthermore, blockchain technology can ensure the seamless and effective performance of the presented bidding strategy. In the case study, the results show that our bidding strategy has an obvious advantage in social welfare and allocation efficiency than existing bidding strategies. Moreover, the problem of environmental pollution can be solved to a certain extent through flexible dynamic compensation. Finally, a decentralized application of blockchain is developed to demonstrate how the system could realize real-time energy management and dynamic trading in practice.

Multipoint reconstruction of wind speeds

Abstract. The most intermittent behaviour of atmospheric turbulence is found for very short timescales. Based on a concatenation of conditional probability density functions (cpdf's) of nested wind speed increments, inspired by a Markov process in scale, we derive a short-time predictor for wind speed fluctuations around a non-stationary mean value and with a corresponding non-stationary variance. As a new quality this short-time predictor enables a multipoint reconstruction of wind data. The used cpdf's are (1) directly estimated from historical data from the offshore research platform FINO1 and (2) obtained from numerical solutions of a family of Fokker–Planck equations in the scale domain. The explicit forms of the Fokker–Planck equations are estimated from the given wind data. A good agreement between the statistics of the generated and measured synthetic wind speed fluctuations is found even on timescales below 1 s. This shows that our approach captures the short-time dynamics of real wind speed fluctuations very well. Our method is extended by taking the non-stationarity of the mean wind speed and its non-stationary variance into account.

Generalized Description of Intermittency in Turbulence via Stochastic Methods

We present a generalized picture of intermittency in turbulence that is based on the theory of stochastic processes. To this end, we rely on the experimentally and numerically verified finding by R. Friedrich and J. Peinke [Phys. Rev. Lett. 78, 863 (1997)] that allows for an interpretation of the turbulent energy cascade as a Markov process of velocity increments in scale. It is explicitly shown that phenomenological models of turbulence, which are characterized by scaling exponents ζn of velocity increment structure functions, can be reproduced by the Kramers–Moyal expansion of the velocity increment probability density function that is associated with a Markov process. We compare the different sets of Kramers–Moyal coefficients of each phenomenology and deduce that an accurate description of intermittency should take into account an infinite number of coefficients. This is demonstrated in more detail for the case of Burgers turbulence that exhibits pronounced intermittency effects. Moreover, the influence of nonlocality on Kramers–Moyal coefficients is investigated by direct numerical simulations of a generalized Burgers equation. Depending on the balance between nonlinearity and nonlocality, we encounter different intermittency behavior that ranges from self-similarity (purely nonlocal case) to intermittent behavior (intermediate case that agrees with Yakhot’s mean field theory [Phys. Rev. E 63 026307 (2001)]) to shock-like behavior (purely nonlinear Burgers case).

A Robust Adaptive Overcurrent Relay Coordination Scheme for Wind-Farm-Integrated Power Systems Based on Forecasting the Wind Dynamics for Smart Energy Systems

Conventional protection schemes in the distribution system are liable to suffer from high penetration of renewable energy source-based distributed generation (RES-DG). The characteristics of RES-DG, such as wind turbine generators (WTGs), are stochastic due to the intermittent behavior of wind dynamics (WD). It can fluctuate the fault current level, which in turn creates the overcurrent relay coordination (ORC) problem. In this paper, the effects of WD such as wind speed and direction on the short-circuit current contribution from a WTG is investigated, and a robust adaptive overcurrent relay coordination scheme is proposed by forecasting the WD. The seasonal autoregression integrated moving average (SARIMA) and artificial neuro-fuzzy inference system (ANFIS) are implemented for forecasting periodic and nonperiodic WD, respectively, and the fault current level is calculated in advance. Furthermore, the ORC problem is optimized using hybrid Harris hawks optimization and linear programming (HHO–LP) to minimize the operating times of relays. The proposed algorithm is tested on the modified IEEE-8 bus system with wind farms, and the overcurrent relay (OCR) miscoordination caused by WD is eliminated. To further prove the effectiveness of the algorithm, it is also tested in a typical wind-farm-integrated substation. Compared to conventional protection schemes, the results of the proposed scheme were found to be promising in fault isolation with a remarkable reduction in the total operation time of relays and zero miscoordination.