Nonzero Output Research Articles

Maximum-Power Stirling-like Heat Engine with a Harmonically Confined Brownian Particle

Heat engines transform thermal energy into useful work, operating in a cyclic manner. For centuries, they have played a key role in industrial and technological development. Historically, only gases and liquids have been used as working substances, but the technical advances achieved in recent decades allow for expanding the experimental possibilities and designing engines operating with a single particle. In this case, the system of interest cannot be addressed at a macroscopic level and their study is framed in the field of stochastic thermodynamics. In the present work, we study mesoscopic heat engines built with a Brownian particle submitted to harmonic confinement and immersed in a fluid acting as a thermal bath. We design a Stirling-like heat engine, composed of two isothermal and two isochoric branches, by controlling both the stiffness of the harmonic trap and the temperature of the bath. Specifically, we focus on the irreversible, non-quasi-static case—whose finite duration enables the engine to deliver a non-zero output power. This is a crucial aspect, which enables the optimisation of the thermodynamic cycle by maximising the delivered power—thereby addressing a key goal at the practical level. The optimal driving protocols are obtained by using both variational calculus and optimal control theory tools. Furthermore, we numerically explore the dependence of the maximum output power and the corresponding efficiency on the system parameters.

Quantitative assessment methods and qualitative evaluation system for the complementary characteristics of multi-energy

Assessing and analyzing the complementary characteristics of renewable energy (RE) is crucial for designing, operating, and optimizing multi-energy complementary systems (MECSs). However, unified and precise quantitative descriptions of the complementary and stability characteristics among various energy outputs in MECSs have lacked attention and research. Here, this study innovatively proposed a mathematical model for the multi-energy complementarity index (MECI), which considers the complementarity rates of multiple energy outputs during zero and non-zero output periods, and a mathematical model for the multi-energy volatility index (MEVI), which accounts for fluctuation thresholds and the overall volatility of output processes. An evaluation system for multi-energy complementarity characteristics qualitative analysis has been established. The natural output processes of RE at three MECSs in China were applied in the case calculations and verification. Results show that the hydropower rated discharge (Qrating) has a significant negative correlation with MECI, with the MECI decreasing by an average of 0.0046 for every 5 m³/s increase in Qrating. The relationship between the Qrating and MEVI shows an overall negative correlation with local fluctuations. Notably, The MECI of the BeiPan River MECSs exhibits significant seasonal characteristics, with the MEVI in summer (0.378) and autumn (0.395) higher than those in spring (0.132) and winter (0.160), closely related to the natural seasonal variations of the three energy sources: water, wind, and solar. We believe that the study can assist in evaluating and making decisions on the multi-energy complementarity characteristics of RE bases in the future, making a significant contribution to achieving dual carbon goals.

On annular short-time stability conditions for generalised Persidskii systems

This paper studies the trajectory behavior evaluation for generalised Persidskii systems with an essentially bounded input on a finite time interval. Also, the notions of annular settling and output annular settling for general nonlinear systems are introduced. We propose conditions for annular short-time stability, short-time boundedness with a nonzero initial state, annular settling, and output annular settling for a class of Persidskii systems. These conditions are based on the verification of linear matrix inequalities. An application to recurrent neural networks illustrates the usefulness of the proposed notions and conditions.

Ferrimagnet based spin Hall detector of subterahertz frequency signals

A concept of a subterahertz (sub-THz) frequency range signals detector based on a ferrimagnet/normal metal (FiM/NM) heterostructure is proposed. An external linearly polarized electromagnetic (EM) wave excites precession in the FiM and spin pumping at the FiM/NM interface. The excited spin current in the NM converts into a direct current via the inverse spin Hall effect. We show that non-zero uncompensation between magnetic spins in FiM gives a non-zero output rectified voltage for both “easy axis” and “easy plane” uniaxial anisotropies. The increase in the uncompensation parameter removes degeneracy from two normal resonance modes and changes the sensitivity to the EM wave. Namely, the sensitivity of the higher mode increases, and the lower mode decreases with increasing the uncompensation parameter. We believe that our results can be helpful for the practical development of sub-THz frequency tunable resonance detector based on the FiM.

Analysis and Design of a Microphone Preamplifier for Mobile Applications

A design of an on-chip ac-coupling preamplifier for mobile applications is presented. A microphone preamplifier should have a large input impedance to mitigate the effective-gain reduction caused by the microphone’s non-zero output impedance. From a review of previously reported microphone preamplifier structures in terms of input impedance, feasibility of on-chip ac-coupling, and noise performance, we chose an inverting amplifier structure with capacitive feedback. In addition, to provide dc bias path, we used off-state MOSFET switches as pseudo-resistors of very large resistance in the giga-ohm range. The large resistance enables on-chip ac-coupling with sufficient noise performance. A fast start-up is achieved by turning-on the switch for a short period during the preamplifier start-up. The gain of the preamplifier can be programmed from 0 dB to 21 dB with 3 dB steps. A 2-stage pseudo-class-AB amplifier was adopted to reduce power consumption. The proposed preamplifier was implemented using a 28 nm CMOS process and achieves 107 dB dynamic range in a 20 kHz bandwidth under 0 dB gain setting and balanced differential input signal. The preamplifier dissipates a power of 270 μW with a 1.8 V supply.

Learning Neural Representations and Local Embedding for Nonlinear Dimensionality Reduction Mapping

This work explores neural approximation for nonlinear dimensionality reduction mapping based on internal representations of graph-organized regular data supports. Given training observations are assumed as a sample from a high-dimensional space with an embedding low-dimensional manifold. An approximating function consisting of adaptable built-in parameters is optimized subject to given training observations by the proposed learning process, and verified for transformation of novel testing observations to images in the low-dimensional output space. Optimized internal representations sketch graph-organized supports of distributed data clusters and their representative images in the output space. On the basis, the approximating function is able to operate for testing without reserving original massive training observations. The neural approximating model contains multiple modules. Each activates a non-zero output for mapping in response to an input inside its correspondent local support. Graph-organized data supports have lateral interconnections for representing neighboring relations, inferring the minimal path between centroids of any two data supports, and proposing distance constraints for mapping all centroids to images in the output space. Following the distance-preserving principle, this work proposes Levenberg-Marquardt learning for optimizing images of centroids in the output space subject to given distance constraints, and further develops local embedding constraints for mapping during execution phase. Numerical simulations show the proposed neural approximation effective and reliable for nonlinear dimensionality reduction mapping.

Investigating minimum income condition orders on European power exchanges: Controversial properties and enhancement proposals

One of the most difficult challenges of deregulated electricity markets is the proper management and operation planning of economically non-convex generators. The origin of economic non-convexity is twofold. Firstly, generators generally have non-zero minimum output power (MOP) levels, below which they cannot sustain operation. Secondly, they might have substantial fixed costs. The direct consideration of these characteristics leads to very hard non-convex mathematical problems with the increased probability of computational difficulties and long solution time for the market clearing process.Complex orders with explicit Minimum Income Conditions (MICs) have been invented to provide a method to represent non-convex generators on European day-ahead power exchanges. The rationale is that a MIC can be attached to a set of simple supply bids, which means that these bids can be accepted only if their acquired incomes surpass bidder-specified minimal values.The present research is conducted to investigate several controversial issues concerning the current use of MICs from the viewpoint of market participants. Firstly, no direct mechanism is provided to handle the MOP of generators. Secondly, simple bid price constraints and simultaneously attached income criteria can have contradictory implications that lead to sub-optimal clearing results. Thirdly, the current use of MICs contributes to cheating opportunities, because it entails distortions in the social welfare calculation. The paper defines new ways of MIC attachment to circumvent the revealed hindrances. For this purpose, several modification techniques are considered such as the discretization of bid quantities, the relaxation of elementary bid pricing rules and the revision of social welfare calculation. Two novel order types are proposed, supported by comparative numerical simulations using realistic market data.

Impact of imperfect homodyne detection on measurements of vacuum states shot noise

The secret key rate of a continuous variables quantum key distribution system (CV-QKD) depends highly on the loss and excess noise of the quantum channel. A proper modelling of the quantum channel is essential to detect and prevent an eavesdropping attack. In CV-QKD, homodyne detection is widely used to measure the quadratures of the modulated optical signal. Nevertheless, the homodyne detector (HD) can be a source of noise for the CV-QKD system. In this paper, a HD is modelled considering intrinsic imperfections. Moreover, an improved method is proposed to obtain mean, variance and auto-covariance functions for estimation of the HD performance, considering ideal and unbalanced HD operation modes with ideal and non-ideal local oscillator pulse intensity functions being compared. The imbalance of the HD leads to non-zero mean output and a quadratic relation of voltage variance. Despite that, the rebalance of the system was attained with the cost of lowering the system voltage output intensity.

Data-driven model-free adaptive damping control with unknown control direction for wind farms

The wide-area damping control (WADC) designed by conventional model-based methods faces the challenge from the strong nonlinearity, time-varying structure, and disturbances from complex operating conditions of the interconnected multi-machine power systems. In this paper, as one of the data-driven methods, the model-free adaptive control (MFAC), which employs the pseudo-partial derivative (PPD) to linearize the nonlinear power system dynamically, is adopted to design WADC for its advantages of the low cost, simple structure & low calculation burden, and the analyzable stability. However, when applied to the WADC design, the prototype MFAC is infeasible due to the assumed known control direction, the non-zero steady-state controller output, and unconsidered disturbances. To solve these problems, a novel data-driven adaptive WADC, consisting of control direction correction, PPD updating, one-step-ahead weighted predictive control, is proposed, moreover, the stability of the closed-loop system considering disturbances is thoroughly analyzed. Finally, case studies with various disturbances are conducted to validate the proposed control strategy.

Low counting rate measurement on thermal neutron induced fission using cross-correlation technique

The measurement procedure based on the continuous thermal neutron beam modulation with a mechanical chopper was developed for delayed neutron yield measurement of the thermal neutron induced fission of [Formula: see text]Np. The idea of the procedure is similar to that widely used in modern computer communications to prevent unauthorized data access. The data is modulated with a predefined pattern before transmission to the public network, and only the recipient that has the modulation pattern is able to demodulate it upon receipt. For thermal neutron induced reaction applications, the thermal neutron beam modulation pattern was used to demodulate the measured delayed neutron intensity signals on the detector output, resulting in nonzero output only for the detector signals correlated with the beam modulation. The comparison of the method with the conventional measurement procedure was provided, and it was demonstrated that the cross-correlation procedure has special features making it superior to the conventional one, especially when the measured value is extremely small in comparison with the background. Due to the strong sensitivity of the measurement procedure on the modulation pattern of the neutron beam, one can implement the modulation pattern of a specific shape to separate the effect of the thermal part of the beam from the higher energy part in the most confident way in the particular experiment. The remarkable property of our method is related to the unique possibility of separation of the effects caused exclusively by thermal neutrons using the neutron time-of-flight measurement available on the IBR-2 pulsed reactor.

Exact detectability and exact observability of discrete-time linear stochastic systems with periodic coefficients

This paper is devoted to the problem of detectability and observability of a class of time-varying stochastic systems. The main contribution of this note is to propose a PBH-type test which is equivalent to the detectability of the considered stochastic systems in the sense that all unstable modes produce some non-zero output. Then, we apply the obtained results in order to derive a criterion of exponential stability in mean square sense as well as existence conditions for the stabilizing solution of a class of discrete-time time-varying Riccati equations.

Residual intensity modulation-induced error in resonator fiber optic gyroscopes with triangular phase modulation.

The residual intensity modulation (RIM) is one of the major sources of instability in optical detection based on phase modulation. In resonator fiber optic gyroscopes (RFOGs), the RIM leads to a nonzero output signal at the resonance center frequency, which degrades the bias stability of the RFOG. While the origins of the RIM are not fully understood, we present experimental results of the RIM in the Y-branch waveguide modulator with triangular phase modulation. We establish a model to analyze the RIM-induced error in the RFOG with triangular phase modulation and pointed out that symmetrical acquisition in a triangular wave period can reduce the RIM-induced error. We experimentally study the equivalent modulation depth of the RIM with different acquisition times in a triangular wave period and symmetrical acquisition in a triangular wave period. The results show that symmetrical acquisition in a triangular wave period can eliminate the RIM-induced error.

Discrete Stepping and Nonlinear Ramping Dynamics Underlie Spiking Responses of LIP Neurons during Decision-Making

Neurons in LIP exhibit ramping trial-averaged responses during decision-making. Recent work sparked debate over whether single-trial LIP spike trains are better described by discrete "stepping" or continuous "ramping" dynamics. We extended latent dynamical spike train models and used Bayesian model comparison to address this controversy. First, we incorporated non-Poisson spiking into both models and found that more neurons were better described by stepping than ramping, even when conditioned on evidence or choice. Second, we extended the ramping model to include a non-zero baseline and compressive output nonlinearity. This model accounted for roughly as many neurons as the stepping model. However, latent dynamics inferred under this model exhibited high diffusion variance for many neurons, softening the distinction between continuous and discrete dynamics. Results generalized to additional datasets, demonstrating that substantial fractions of neurons are well described by either stepping or nonlinear ramping, which may be less categorically distinct than the original labels implied.

Origin of the DC output voltage from a high-Tc superconducting dynamo

Despite their proven ability to output DC currents of >100 A, the physical mechanism which underpins the operation of a high-Tc superconducting (HTS) dynamo is still debated widely. Here, we show that the experimentally observed open-circuit DC output voltage, Vdc, is due to the action of overcritical eddy currents within the stator wire. We demonstrate close agreement between experimental results and numerical calculations, and show that large over-critical currents flow within the high-Tc stator during certain parts of the dynamo cycle. These overcritical currents experience a non-linear local resistivity which alters the output voltage waveform obtained in the superconducting state. As a result, the full-cycle integral of this altered waveform outputs a non-zero time-averaged DC voltage. We further show that the only necessary requirement for a non-zero Vdc output from any dynamo is that the stator must possess a non-linear local resistivity. Here, this is provided by the flux-flow regime of an HTS coated conductor wire, where conduction is described by the E–J power law. We also show that increased values of Vdc can be obtained by employing stator wires which exhibit a strong in-field dependence of the critical current Jc(B,θ). However, non-linear resistivity is the key requirement to realize a DC output, as linear magneto-resistance is not sufficient. Our results clarify this longstanding conundrum, and have direct implications for the optimization of future HTS dynamo devices.

A Slack-Based Measures for Improving the Efficiency Performance of Departments in Universitas Malikussaleh

Data Envelopment Analysis (DEA) is a data-oriented performance evaluation method that has a very satisfactory performance when there are multiple inputs and outputs presented in the form of set of peer Decision Making Units (DMU). In the discussion of DEA, basically measures the efficiency of each DMU in specific performance based on DEA Efficiency Scores. In DEA, when there is a value of Non-Zero Input and Output Slacks then this often means inefficiency. This scalar measures directly with the input surplus and the output of the short decision of the decision making unit (DMU). Universitas Malikussaleh as one of the State Universities in Indonesia, it is necessary to follow the regulations of the Ministry of Research, Technology and Higher Education of the Republic of Indonesia (KEMENRISTEKDIKTI), one of which is the measurement of efficiency based on the number of lecturers research, the efficient use of resources included in the number of lecturers and employees, as well as students who can be accommodated based on efficiency measurements using DEA. This paper will measure the efficiency of each department in Malikussaleh University and if there is an inefficient department then it will be measured based on slack-based measures to advise aspects that need attention so that the department can be efficient.

Modified convex hull pricing for power markets with price-sensitive load

We consider a general power market with price-sensitive consumer bids and non-convexities originating from supply (start-up and no-load costs, nonzero minimum output limits of generating units, etc.) and demand. The convex hull (minimum-uplift) pricing method produces the set of power prices that minimizes the total uplift payments to the market players needed to compensate their potential profits lost by accepting the centralized dispatch solution. All opportunities to supply (consume) any other output (consumption) volumes allowed by market player individual operational constraints are considered as foregone in the convex hull pricing method. We modify the convex hull pricing algorithm by defining for each market player a modified individual feasible set that is utilized in the lost profit calculation. These sets are based on the output (consumption) volumes that are economically and technologically feasible in the centralized dispatch. The new pricing method results in the generally different set of market prices and lower (or equal) total uplift payment compared to the convex hull pricing algorithm.

Parameter design and hot seamless transfer of single-phase synchronverter

This paper reveals the parameter design of single-phase synchronverter (SPSV) and proposes a hot seamless transfer method for SPSV. The design challenge of SPSV lies in its necessary for single-phase power calculation to generate an average value of active/reactive power and the high order system feature caused by the virtual inertia element. The small signal analysis shows that the low-pass filter time constant and SPSV active power loop time constant determine the system damping ratio together. Then we proposed a SPSV parameter design method to provide a proper damping ratio and guarantee system small signal stability. Based on the SPSV parameter design method, a hot seamless-transfer is proposed. During the disconnection and reconnection processes, SPSV can maintain a non-zero power output, which is essential for the critical local loads when the SPSV serves as an uninterrupted power source. The SPSV parameter design method and hot seamless transfer are investigated by simulation. Finally, a 500W SPSV prototype is built for further demonstration.

A Slack-Based Measures within Group Common Benchmarking using DEA for Improving the Efficiency Performance of Departments in Universitas Malikussaleh

Measurement of the efficiency of the university performance. Data Envelopment Analysis (DEA) is a data-based performance evaluation method used when multiple inputs and outputs are represented in the Decision-Making Unit (DMU) set. In DEA, when there is a value of Non-Zero Input and Output Slacks then this often means inefficiency. This scalar measure directly with the input of surplus and the output of the short decision of the decision-making unit (DMU). DEA Structure usually apply in general settings, actually DMUs can fall into distinct groups whose members experience similar circumstances. The targets of the Ministry of Research, Technology and Higher Education of the Republic of Indonesia (KEMENRISTEKDIKTI), one of which is the measurement of the efficiency based on the number of lecturers' research, the efficient use of resources. This study will group each department at the Universitas Malikussaleh using the Group Common Benchmarking approach and then provide suggestions for improvements to each group by using Slack-Based Measures.

Influence of adhesive non-uniformity on zero offset of micro accelerometer

Adhesive attaching is a common method used in the packaging of high accurate MEMS devices. A full understanding of the effects of adhesive on device performance, therefore, plays a significant role in MEMS design because the thermal stress formed in packaging process highly depends on the shape, size, amount, properties and layout of the die attach adhesive. This paper investigates intensively the influence of adhesive nonuniformity in the sensitive direction of microaccelerometers on the distribution of thermal stress during the variation of environment temperature. The thermal stress will induce a movement of anchors and lead to nonzero voltage output of microaccelerometer. The influence of the adhesive with different levels of nonuniformity [Formula: see text] on zero voltage output is investigated and the results show that the adhesive nonuniformity significantly influences the zero offset of the sensors, and the maximum one can reach 8.6 mV when nonuniformity factor is 0.975.

Diverging, but negligible power at Carnot efficiency: Theory and experiment.

We discuss the possibility of reaching the Carnot efficiency by heat engines (HEs) out of quasistatic conditions at nonzero power output. We focus on several models widely used to describe the performance of actual HEs. These models comprise quantum thermoelectric devices, linear irreversible HEs, minimally nonlinear irreversible HEs, HEs working in the regime of low-dissipation, overdamped stochastic HEs and an underdamped stochastic HE. Although some of these HEs can reach the Carnot efficiency at nonzero and even diverging power, the magnitude of this power is always negligible compared to the maximum power attainable in these systems. We provide conditions for attaining the Carnot efficiency in the individual models and explain practical aspects connected with reaching the Carnot efficiency at large power output. Furthermore, we show how our findings can be tested in practice using a standard Brownian HE realizable with available micromanipulation techniques.