Low-frequency Swing Research Articles

Dynamic regulation of the thermal performance of the S–CO2 minichannel using a piezoelectric oscillating fin

It is difficult to alter the thermal performance of a minichannel heat sink with a fixed structure under constant operating conditions. In particular, if the local heat transfer of the substrate cannot be regulated in real time, the dynamic heat dissipation needs of high-power electronic components cannot be met in the electrical servo systems of flight vehicles. In this paper, a new minichannel heat sink structure based on the classical rectangular channel is proposed and a piezoelectric oscillating fin (POF) is introduced to replace the fixed fin. The thermal performance of the heat sink can then be regulated using the swing of the POF, with supercritical carbon dioxide (S–CO2) as the coolant. Transient numerical simulations are applied to investigate the influence of various POF operating parameters on the heat transfer of the channel, such as the oscillation amplitude and frequency. The results demonstrate that a channel with a POF can allow for dynamic and rapid adjustment of the thermal performance through control of the oscillation frequency and amplitude of the POF, with a constant channel configuration, coolant, and operating conditions. The heat transfer can be enhanced significantly by the swing of the POF, with the local Nusselt number growing up to 8.3 times and the overall one up to 1.14 times. Both the oscillation frequency and amplitude have a positive correlation with the intensity of heat transfer. The POF also contributes to a greater pressure drop and fluctuation in pumping power. A comprehensive evaluation coefficient shows that the POF is effective at improving the overall thermal performance with a low-frequency swing, while high-frequency operation enhances the local heat transfer and decreases the local temperature near the tail end of the POF. Finally, considering the effects of the frequency and amplitude of the POF, as well as the variable thermophysical properties of the supercritical coolant, a heat transfer correlation based on the Dittus–Boelter equation is established to predict the thermal performance of the channel with a POF. This prediction has a maximum error of ±0.56%.

Control of Low-Frequency Oscillation on Electrical Power System Under Large EV-Charging Station Installation Using PSO Technique for Turning PSS Parameters

This paper presents a low-frequency oscillation compensation in an electrical power system connecting large-scale electric vehicle loads (EVs). The Particle Swarm Optimization (PSO) method has been adapted to adjust the control parameters of the generator under Power System Stabilizer (PSS) parameters. The EVs charging stations have been directly installed to the power grid for the battery charging process of the EVs according to the increasing number of EVs. The DC fast charging of the large scale EVs has been significantly affected by the low-frequency oscillation of the grids that have been considered in terms of power system stability margin. This paper has aimed to solve the methodology for turning the PSS parameters by adapting the PSO via MATLAB® and DIgSILENT®. The PSS could control the low-frequency oscillation in the proposed power grids. The simulation system has selected the 6-bus testing system, which has increased the EVs loads by 50, 100, 150, 200, and 300 percentages at bus No. B3. The simulation results have indicated that the rotor low-frequency oscillation could control instability region. Therefore, the proposed PSS controller turning could handle the power system swing and adjust the power system stability. In this condition, the proposed PSO method should have been explicitly used for low-frequency swing control of the generator's rotor into a balanced state under the large-scale EVs penetration level.

Super-Durable and Highly Efficient Electrostatic Induced Nanogenerator Circulation Network Initially Charged by a Triboelectric Nanogenerator for Harvesting Environmental Energy.

Triboelectric nanogeneration is a burgeoning and promising technology for harvesting low-frequency mechanical energy from the environment, but the energy conversion efficiency and service life of the triboelectric nanogenerator (TENG) device are limited by the inevitable frictional resistance between the tribo-surfaces. Herein, we propose an electrostatic induction nanogenerator (EING) circulation network (EICN) by integrating an arbitrary number of EING units for harvesting low-frequency mechanical energy. Because of absolute conquering of the friction resistance between the tribo-surfaces, the average power density of the EING device in the EICN by the initial charge injection (from a TENG or a power supply) is more than a 15-fold enhancement compared with the previous swing-structured TENG. The EICN can recover to the stable and optimal electrical output state in 90 s without external charge injection, even if the external triggering interrupts for 40 min and then restarts, demonstrating the excellent application feasibility of this strategy. To display the practical application scenario for harvesting large-scale mechanical energy from the environment, a high-performance and ultralow-friction TENG is designed for the initial charge injection to the EICN. Moreover, portable electronic devices are powered successfully to realize the self-powered sensing and remote marine environmental monitoring when an EICN with three EINGs is triggered by the real water wave. This EICN strategy not only can harvest low-frequency swing type mechanical energy but also has the capacity of harvesting the rotational mechanical energy after reasonable structure modification, providing an excellent candidate for large-scale blue energy harvesting in practical applications.

Experimental investigations on start-up and thermal performance of sodium heat pipe under swing conditions

High-temperature heat pipes (HTHPs) have a potential of being used for passive heat dissipation of marine nuclear reactors in emergency. In order to understand the influence of wave action on the performance of HTHPs, a sodium heat pipe is fabricated and experimentally tested in this work. The effects of low-frequency swing on start-up and thermal performance of this heat pipe are examined and compared with the static state tests. The results show that swinging motion has a negligible influence on the whole start-up performance of the heat pipe, however, it would lead to the small-amplitude periodic temperature fluctuations especially at the evaporator. Temperature fluctuation frequency is nearly corresponding to the swing, and the temperature fluctuation amplitude is increased with the swing amplitude. The steady-state thermal performance is slightly decreased with increasing swing speed and decreasing swing amplitude in terms of thermal resistance under test conditions, but the influence seems negligible as well.

Design and Performance Analysis of Anti-sway & Anti-vibration System for Marine Operating Table with Inerter

In order to solve the low-frequency swing and vibration problems of the marine operating table, the inerter was added to the system of anti-sway and anti-virbation in this paper. The manuscript designed a simple system of anti-sway and anti-virbation for marine operating table with inerter and deduced its dynamic model. The analysis shows that the inerter can improve anti-sway and anti-virbation performance of marine operating table. Specifically, results show that all the anti-sway and anti-vibration performance that we analyzed can be improved by more than 45% when the inertance-mass ratio is greater than 0.5 (η>0.5). This work provides a design guidance for the anti-sway and anti-virbation design of marine operating table, which has a practical engineering significance.

Multi-objective attuned design of damping controllers using frequency-based functions in smart grids

Increasing expansion of power systems is accompanied by innovations in smart grid solutions to maintain system stability. This paper formulates the dual-dimensional supplementary damping controller (SDC) and accelerating power system stabilizer (PSS2B) design as a multi-objective optimization procedure including both performance and robustness criteria. In wide-area operation, PSS2B is used for damping low-frequency swings and maintaining the robustness of controller in a wide range of swing frequencies. A dual-dimensional controller model is employed for the SDC. The robustness requirement is procured by using the idea of pseudospectra to handle the changes of power system parameters and the time delay introduced by wide-area damping controller (WADC). The multi-objective optimization problem is solved using an improved non-dominated sorting genetic algorithm-II (INSGA-II) based on fuzzy decision making (FDM) method. Different simulations are carried out on a 4-machine 2-area test system in order to validate the effectiveness and robustness of the designed controllers.

Piezoelectric monolayers as nonlinear energy harvesters

We study the dynamics of h-BN monolayers by first performing ab-initio calculations of the deformation potential energy and then solving numerically a Langevine-type equation to explore their use in nonlinear vibration energy harvesting devices. An applied compressive strain is used to drive the system into a nonlinear bistable regime, where quasi-harmonic vibrations are combined with low-frequency swings between the minima of a double-well potential. Due to its intrinsic piezoelectric response, the nonlinear mechanical harvester naturally provides an electrical power that is readily available or can be stored by simply contacting the monolayer at its ends. Engineering the induced nonlinearity, a 20 nm device is predicted to harvest an electrical power of up to 0.18 pW for a noisy vibration of 5 pN.

Concurrently attuned design of a WADC-based UPFC PSDC and multiinput PSS for improving power system dynamic performance

A new controller design for a unied power ow controller (UPFC) for damping of power system swings, focusing on interarea modes, is described in this paper. The proposed controller is a dual-layer controller, where the rst layer is derived from local signals and the second layer is supplied by global signals, as additional measuring information from suitable remote network locations, where swings are well observable. For damping of low-frequency swing in wide-area operation, since there is little system information in the active power as input of the conventional power system stabilizer (CPSS), the eectiveness of the CPSS is low. For solving this problem, a multiinput power system stabilizer (MPSS) is used for the damping of low-frequency swings, where the choice of the MPSS location is based on modal analysis. Since an uncoordinated controller for the UPFC and MPSS may cause unwanted interactions, the concurrently attuned design of the controller parameters is necessary. The attuned design is presented as an optimization problem, where the particle swarm optimization algorithm is applied to search for the optimal controller parameters. The introduced time delay by remote signal transmission and processing in a wide-area damping controller (WADC) may be problematic for system stability and may decrease system robustness. The Lyapunov theory and model reduction technique are used to investigate the delay-dependent stability of a power system equipped with a WADC. The designed controller's eectiveness and robustness are investigated on a typical 2-area 4-machine benchmark power system.

Rational and Near‐Rational Bubbles Without Drift

This paper derives a general class of intrinsic rational bubble solutions in a standard Lucas-type asset pricing model. I show that the rational bubble component of the pricedividend ratio can evolve as a geometric random walk without drift. The volatility of bubble innovations depends exclusively on fundamentals. Starting from an arbitrarily small positive value, the rational bubble expands and contracts over time in an irregular, wholly endogenous fashion, always returning to the vicinity of the fundamental solution. I also examine a near-rational solution in which the representative agent does not construct separate forecasts for the fundamental and bubble components of the asset price. Rather, the agent constructs only a single forecast for the total asset price that is based on a geometric random walk without drift. The agent’s forecast rule is parameterized to match the moments of observable data. In equilibrium, the actual law of motion for the price-dividend ratio is stationary, highly persistent, and nonlinear. The agent’s forecast errors exhibit near-zero autocorrelation at all lags, making it di¢ cult for the agent to detect a misspeci…cation of the forecast rule. Unlike a rational bubble, the near-rational solution allows the asset price to occasionally dip below its fundamental value. Under mild risk aversion, the near-rational solution generates pronounced low-frequency swings in the price-dividend ratio, positive skewness, excess kurtosis, and time-varying volatility— all of which are present in long-run U.S. stock market data. An independent contribution of the paper is to demonstrate an approximate analytical solution for the fundamental asset price that employs a nonlinear change of variables.

Rational and Near-Rational Bubbles without Drift

This paper derives a general class of intrinsic rational bubble solutions in a standard Lucas-type asset pricing model. I show that the rational bubble component of the price-dividend ratio can evolve as a geometric random walk without drift. The volatility of bubble innovations depends exclusively on fundamentals. Starting from an arbitrarily small positive value, the rational bubble expands and contracts over time in an irregular, wholly endogenous fashion, always returning to the vicinity of the fundamental solution. I also examine a near-rational solution in which the representative agent does not construct separate forecasts for the fundamental and bubble components of the asset price. Rather, the agent constructs only a single forecast for the total asset price that is based on a geometric random walk without drift. The agent's forecast rule is parameterized to match the moments of observable data. In equilibrium, the actual law of motion for the price-dividend ratio is stationary, highly persistent, and nonlinear. The agent's forecast errors exhibit near-zero autocorrelation at all lags, making it difficult for the agent to detect a misspecification of the forecast rule. Unlike a rational bubble, the near-rational solution allows the asset price to occasionally dip below its fundamental value. Under mild risk aversion, the near-rational solution generates pronounced low-frequency swings in the price-dividend ratio, positive skewness, excess kurtosis, and time-varying volatility--all of which are present in long-run U.S. stock market data. An independent contribution of the paper is to demonstrate an approximate analytical solution for the fundamental asset price that employs a nonlinear change of variables.

Time-varying U.S. inflation dynamics and the New Keynesian Phillips curve

This paper introduces a form of boundedly-rational inflation expectations in the New Keynesian Phillips curve. The representative agent is assumed to behave as an econometrician, employing a time series model for inflation that allows for both permanent and temporary shocks. The near-unity coefficient on expected inflation in the Phillips curve causes the agent's perception of a unit root in inflation to become close to self-fulfilling. In a “consistent expectations equilibrium,” the value of the Kalman gain parameter in the agent's forecast rule is pinned down using the observed autocorrelation of inflation changes. The forecast errors observed by the agent are close to white noise, making it difficult for the agent to detect a misspecification of the forecast rule. I show that this simple model of inflation expectations can generate time-varying persistence and volatility that is broadly similar to that observed in long-run U.S. data. Model-based values for expected inflation track well with movements in survey-based measures of U.S. expected inflation. In numerical simulations, the model can generate pronounced low-frequency swings in the level of inflation that are driven solely by expectational feedback, not by changes in monetary policy.

New parametric transducer for resonant detectors: advances and room temperature test

We are developing a prototype of cryogenic parametric converter transducer operating at 5 GHz, for the upgrade of the ROG Collaboration resonant G. W. antennas. This device is built on the experience of the Niobe detector (D. G. Blair et al.), with substantial modifications that should let us achieve better stability and sensitivity. The prototype uses asparametric converter a superconducting coaxial cavity with a 50 micron gap (Q 0 = 5 × 10 8 at1.5K and 100μW RF power dissipation), and a contacless RF coupling for thermal insulation between the 2K stage and the ultra cryogenic (100mK) antenna. The coupler features a constant transmission loss of 0.2dB over a range of displacements of ± 5mm in x, y and z around the nominal operating position with a separation of 8mm between the two halves of the coupler. In this way the large, low frequency swings (0.5 and 17 Hz), of the 2 Tons antenna around its suspension point have no influence on the transducer performance. To test all the components of the transducer and the system performance, a room temperature prototype is installed on the TART (Test Antenna at Room Temperature) facility at the INFN labs. Using critical coupling for the RF cavity input coupler we manage to keep to a minimum the leakage of the drive signal to the first RF amplifier. In this way we avoid degradation of the RF amplifier noise figure (0.6 dB at room temperature) produced by the RF amplifier saturation Experimental results agree with the full analysis of the room temperature detector performances.

Supplementary Damping Controller Design using Direct Heuristic Dynamic Programming in Complex Power Systems

In modern, large scale interconnected power grids, low-frequency oscillation is a key roadblock to improved power transmission capacity. Supplementary generator control, flexible AC transmission system (FACTS), and high voltage direct currents (HVDC) are engineered devices designed to damp such low frequency swings. In this paper a neural network-based approximate dynamic programming method, namely direct heuristic dynamic programming (direct HDP), is applied to power system stability enhancement. Direct HDP is a learning and approximation based approach to addressing nonlinear system control problems under uncertainty, and it is also a model-free design strategy. The action and critic networks of the direct HDP are implemented using multi-layer perceptrons; learning is carried out based on the interactions between the controller and the power system. For this design approach, real time system responses are provided through wide-area measurement system (WAMS). The controller learning objective is formulated as a reward function that reflects global characteristics of the power system under low frequency oscillation, as well as tight coupling effects among system components. Direct HDP control design is illustrated by case studies, which are also used to demonstrate the learning control performance. The proposed direct HDP learning control is also developed as a new solution to a large scale system coordination problem by using the China Southern Power Grid as a major test bed.

Rational and Near-Rational Bubbles Without Drift

This paper derives a general class of intrinsic rational bubble solutions in a standard Lucas-type asset pricing model. I show that the rational bubble component of the price-dividend ratio can evolve as a geometric random walk without drift, such that the mean of the bubble growth rate is zero. Driftless rational bubbles are part of a continuum of equilibrium solutions that involve an explicit trade-off between the mean and volatility of the bubble growth rate. I also propose a near-rational asset pricing solution in which the representative agent does not construct separate forecasts for the fundamental and bubble components of the asset price. Rather, the agent constructs only a single forecast for the total asset price that is similar in form to the corresponding rational forecast, but involves fewer parameters. The parameters of the agent's forecast rule are chosen to match the moments of observable data. In the near-rational equilibrium, the actual law of motion for the price-dividend ratio is stationary, highly persistent, and nonlinear. The agent's forecast errors exhibit near-zero autocorrelation at all lags, making it difficult for the agent to detect a misspecification of the forecast rule. Unlike a rational bubble, the near-rational solution allows the asset price to occasionally dip below its fundamental value. Under mild risk aversion, the near-rational solution generates pronounced low-frequency swings in the price-dividend ratio, positive skewness, excess kurtosis, and time-varying volatility - all of which are present in long-run U.S. stock market data. An additional contribution of the paper is to demonstrate an approximate analytical solution for the fundamental asset price that employs a nonlinear change of variables.

The VIRGO suspensions

The VIRGO suspensions are chains of passive mechanical filters designed to isolate the interferometer mirrors from seismic noise starting from a few Hz. In order to reduce the low-frequency swing of the mirror along the beam, an active control system, acting at the level of the suspension point, damps the main resonant modes of the system (all below 2.5 Hz). Another control loop, at the level of the optical payload, makes use of a digital camera monitoring the mirror position in all six degrees of freedom. Its main goal is to decrease the rms angular displacements of the mirror, on a time scale of several minutes, down to less than 1 μrad. All the seven suspensions of the VIRGO central interferometer are presently in operation, while the assembly of the last two, for the terminal mirrors, is in progress. The design and performance of the system are described in this paper.

Struggling to Understand the Stock Market

Economists are as perplexed as anyone by the behavior of the stock market. Figure 1 shows a broad measure of stock-market value in relation to GDP from 1947 through 2000. In addition to saw-tooth movements including the contraction in late 2000, the value of the stock market has large, low-frequency swings, moving upward from 1950 to 1965, then downward to 1982, and upward until early 2000. I entertain the hypothesis that these large movements are the result of rational (if not accurate) appraisal of the cash likely to be received by shareholders in the future. The hypothesis receives some support from work by financial economists showing that irrational markets create profit opportunities for active traders and that passive traders consistently earn higher returns. Most of my discussion will be complementary to the work of financial economists—I will look at the fundamentals underlying stock-market values. The lecture considers three potential contributors to the big movements shown in Figure 1: