Total Power Research Articles

Decoupling of peeling and ballooning thresholds for pedestal stability and reduction in ELM frequency via enhanced turbulence with edge electron cyclotron heating in DIII-D

The edge localized mode (ELM) frequency (f ELM) decreased by 63% when electron cyclotron heating (ECH) deposition location is shifted from ρ = 0.4 to ρ = 0.8 in DIII-D discharges where the power ratio between neutral beam injection (NBI) and ECH (P NBI/P ECH) is kept at ∼1. The performance of the pedestal in the ECH heated case is compared with a pure NBI reference discharge while keeping the total input power constant. All these discharges are performed at balanced input torque conditions. Furthermore, in the pure NBI discharge a strong decoupling of the peeling–ballooning (PB) thresholds is observed. The PB decoupling is preserved when the ECH is deposited at ρ = 0.8 and P NBI/P ECH ∼ 1, while the thresholds manifest a closed stability boundary when the ECH is deposited at ρ = 0.4. The inter-ELM pedestal recovery time is considerably larger for the ECH at ρ = 0.8 case. Increased pedestal turbulence is observed in beam emission spectroscopy (BES), Doppler backscattering and magnetic diagnostics for the ECH at the ρ = 0.8 case. Strong growth of a TEM-like mode is observed in BES and the mode growth is correlated with the decrease in f ELM. In view of these observations, the increased pedestal turbulence seems to be the plausible reason behind the delayed pedestal recovery following an ELM event in the ECH at ρ = 0.8 case, and the preservation of PB decoupling through temperature pedestal profile widening. TRANSP interpretative simulations show that the ECH at the ρ = 0.8 case is more susceptible to ITG/TEM turbulence.

Heart rate variability in children of younger school age in the speleoclimatotherapy

The autonomic nervous system is a key link in the course of adaptation and adaptive reactions of the organism to various environmental factors. The aim of this study was to assess the heart rate variability of primary school children during a course of speleoclimatotherapy. The heart rate variability were evaluated in 175 practically healthy children aged 7–10 years. In the course of the study the effect of speleoclimatotherapy on the balance sympathetic and parasympathetic nervoussystem was studied using the parameters of spectral analysis of heart rate variability (HRV). HRV data were analysed in the frequency domain: total wave power (TP), high frequency waves (HF), low frequency waves (LF), very low frequency waves (VLF), vagosympathetic index LF/HF. After a course of speleoclimatotherapy the analysis of the obtained results allowed us to establish statistically significant differences in the groups of boy and girls with vagotonic and normotonic type of regulation. After a course of speleoclimatotherapy reduction of the indexe of a vagosympathetic balance (LF/HF) to normal values was found in the groups of sympathotonic boys and sympathotonic girls, while in sympathotonic girls there was an increase in the value of the total power (TP). It is possible to speak about the restoration of vegetative equilibrium and increase of adaptive capabilities of the child’s organism due to adaptation to the microclimate of speleo-chambers.

Multi-Gb/s free-space laser communication at 4.6-μm wavelength using a high-speed, room-temperature, resonant-cavity infrared detector (RCID) and a quantum-cascade laser

Research has shown that free-space laser communication systems may experience fewer outages due to atmospheric impairments such as haze, fog, clouds, and turbulence by operating at a longer wavelength in the mid-wave or long-wave infrared, if disadvantages such as lower-performance transceiver components may be overcome. Here we report a resonant cavity infrared detector (RCID) with 4.6-µm resonance wavelength that enables 20-dB larger link budget than has been reported previously for ∼ 5 Gb/s operation. The device combines high responsivity, 1.97 A/W, with a low noise equivalent power (NEP) of 0.7 pW/Hz at room temperature, and a high bandwidth of 6.7 GHz at 3-dB. The relatively large surface-normal-incidence device with 30-µm diameter simplifies the coupling relative to intra-subband quantum cascade detectors. Although the RCID NEP is expected to increase with frequency to ∼ 1.5 pW/Hz, we estimate that the total equivalent noise power in a 2.5-GHz bandwidth is less than 200 nW. When combined with a relatively high power (∼100-mW) distributed-feedback quantum cascade laser, the difference of > 50 dB between modulated laser power and RCID noise significantly outpaces that of existing devices.

Design and Analysis of a High-Gain, Low-Noise, and Low-Power Analog Front End for Electrocardiogram Acquisition in 45 nm Technology Using gm/ID Method

In this work, an analog front-end (AFE) circuit for an electrocardiogram (ECG) detection system has been designed, implemented, and investigated in an industry-standard Cadence simulation framework using an advanced technology node of 45 nm. The AFE consists of an instrumentation amplifier, a Butterworth band-pass filter (with fifth-order low-pass and second-order high-pass sections), and a second-order notch filter—all are based on two-stage, Miller-compensated operational transconductance amplifiers (OTA). The OTAs have been designed employing the gm/ID methodology. Both the pre-layout and post-layout simulation are carried out. The layout consumes an area of 0.00628 mm2 without the resistors and capacitors. Analysis of various simulation results are carried out for the proposed AFE. The circuit demonstrates a post-layout bandwidth of 239 Hz, with a variable gain between 44 and 58 dB, a notch depth of −56.4 dB at 50.1 Hz, a total harmonic distortion (THD) of −59.65 dB (less than 1%), an input-referred noise spectral density of <34 μVrms/Hz at the pass-band, a dynamic range of 52.71 dB, and a total power consumption of 10.88 μW with a supply of ±0.6 V. Hence, the AFE exhibits the promise of high-quality signal acquisition capability required for portable ECG detection systems in modern healthcare.

Optimal Scheduling of a Cascade Hydropower Energy Storage System for Solar and Wind Energy Accommodation

The massive grid integration of renewable energy necessitates frequent and rapid response of hydropower output, which has brought enormous challenges to the hydropower operation and new opportunities for hydropower development. To investigate feasible solutions for complementary systems to cope with the energy transition in the context of the constantly changing role of the hydropower plant and the rapid evolution of wind and solar power, the short-term coordinated scheduling model is developed for the wind–solar–hydro hybrid pumped storage (WSHPS) system with peak shaving operation. The effects of different reservoir inflow conditions, different wind and solar power forecast output, and installed capacity of pumping station on the performance of WSHPS system are analyzed. The results show that compared with the wind–solar–hydro hybrid (WSH) system, the total power generation of the WSHPS system in the dry, normal, and wet year increased by 10.69%, 11.40%, and 11.27% respectively. The solar curtailment decreased by 68.97%, 61.61%, and 48.43%, respectively, and the wind curtailment decreased by 76.14%, 58.48%, and 50.91%, respectively. The high proportion of wind and solar energy connected to the grid in summer leads to large net load fluctuations and serious energy curtailment. The increase in the installed capacity of the pumping station will promote the consumption of wind and solar energy in the WSHPS system. The model proposed in this paper can improve the operational flexibility of hydropower station and promote the consumption of wind and solar energy, which provides a reference for the research of cascade hydropower energy storage system.

Industrial Park low-carbon energy system planning framework: Heat pump based energy conjugation between industry and buildings

The accelerating urbanization, rapid industrial development, and excessive consumption of fossil fuels pose survival challenges such as energy depletion and environmental degradation for humanity. In the context of industrial park development, constructing a low-carbon energy system, increasing the proportion of renewable energy, enhancing energy-level matching, and utilizing heat pumps for deep waste heat recovery are effective approaches to reduce fossil energy consumption and alleviate environmental pressures. Addressing issues such as diverse thermal flows in industrial sites, complex electricity-heat-cooling energy demands, and unclear industrial-building energy coupling mechanisms, this paper proposes a two-stage planning framework, comprising the following five steps: (1) constructing a waste heat utilization system centered around heat pumps, (2) establishing a mechanism for matching heat sources, equipment, and thermal sinks, (3) establishing an energy conversion model and energy quality quantification system, (4) optimizing waste heat utilization path allocation, and (5) conducting a system energy flow analysis. Case studies demonstrate that the proposed system achieves optimized matching of multiple heat sources and sinks in industrial and building scenarios through thermal integration, meeting diverse energy demands in the park, including electricity, cooling, and multi-grade heat. After coupling with traditional steam pipeline networks, the annual total cost and annual steam power consumption decrease by 33% and 39% respectively, with a waste heat contribution rate of up to 26% and a renewable energy penetration rate of up to 25%, and a waste heat recovery system payback period of 6 years. By establishing an energy quality quantification system and conducting multi-objective optimization considering losses and economic costs, this paper provides Pareto frontier solutions, offering references for engineering proposals. The proposed networked waste heat recovery system is characterized by low energy consumption and high economic efficiency, effectively integrating the energy characteristics of industrial parks and demonstrating engineering applicability.

Power Components Mean Values Determination Using New Ip-Iq Method for Transients

This paper deals with the quasi-instantaneous determination (in a single-step response time) of apparent, active, and reactive (i.e., blind and distortion) power mean values including the total power factor, total harmonic distortion, and phase shift of fundamentals of a power electronic and electrical system (PEES) using the ip-iq method, which is the main contribution of the paper. The power components’ mean values are investigated during the transient and steady states. The power components’ mean values can be determined directly from phase current and voltage quantities, using an integral calculus over one period within the next calculation step and using moving average and moving rms techniques (or digital filtering). Consequently, the power factor can be evaluated with known values of a phase shift of fundamentals (using a Fourier analysis). The results of this study show how a distortion power component during transients is generated even under a harmonic supply and linear resistive–inductive load. The paper contains a theoretical base, modeling, and simulation for the three and single phases of the transients in power electronic systems. The worked-out results can be used to determine and size any PES. The presented approach brings a detailed time waveform verified by simulations in Matlab/Simulink 2022a and the Real-time HW Simulator Plecs RT Box 1.

Short-Term Changes in Hypsarrhythmia Assessed by Spectral Analysis: Group and Individual Assessments.

Objectives: To perform spectral analysis on previously recorded electroencephalograms (EEGs) containing hypsarrhythmia in an initial recording and to assess changes in spectral power (µV2) in a follow-up recording after a period of 10-25 days. Methods: Fifty participants, aged 2-39 months, with hypsarrhythmia in an initial recording (R1), were compared with regard to their spectral findings in a later recording (R2). Typically, anticonvulsant therapy was initiated or modified after R1. Average delta, theta, alpha, and beta power was derived from approximately 3 min of artifact-free EEG data recorded from 19 electrode derivations. Group and individual changes in delta power between R1 and R2 formed the main analyses. Results: Delta accounted for 84% of the total power. In group comparisons, median delta power decreased statistically significantly between R1 and R2 in all 19 derivations, for example, from 3940 µV2 in R1 to 1722 µV2 in R2, Cz derivation. When assessing individual participants, delta power decreases in R2 were >50% in 60% of the participants, but <25% in 24% of the participants. Conclusion: Spectral analysis may be used as an additional tool for providing a potential biomarker in the assessment of short-term changes in hypsarrhythmia, including the effects of treatment.

Effect of cutting process using cutting insert of grade UTi20T

In the metal-cutting industry, the precision of the metal-cutting process is of paramount importance. Errors in the metal-cutting process not only lead to damage to the cutting tool but also result in the production of low-quality materials. The incorporation of insert materials in the cutting process is aimed at maintaining cutting precision and achieving superior results. This research seeks to investigate the impact of the cutting process utilizing grade KC5410 cutting insert under minimum quantity lubrication (MQL) Conditions. In this study, machining tests were conducted using the ALPHA 1350S 2-axis computer numerical control (CNC) lathe machine under MQL conditions, employing cutting tool inserts UTi20T supplied by Mitsubishi. Two types of tools were utilized in the cutting process, namely UTi20T. Critical aspects such as cutting force, total power consumption, surface roughness, and tool life were analyzed to provide comprehensive insights into the efficiency of the cutting process. The findings of this study significantly contribute to the understanding of how the integration of Grade KC5410 cutting inserts under MQL conditions can enhance the overall efficiency of metal-cutting operations. The successful machinability assessment was conducted by implementing sustainable machining practices.

Chirp-coded ultrasound for localization of linear and nonlinear scatterers in isotropic media

Chirp-coded ultrasound has been under active research for reciprocal Time Reversal with Nonlinear Elastic Wave Spectroscopy for ultrasonic wave focusing and additionally detection and analysis of nonlinear defects. Localization and imaging of defects under these principles, without scanning or use of other complicated methods, is an open problem. Frequency Modulated Constant Wave technology is widely known in radar applications where the distance to multiple reflecting targets, their velocities and angles of return are found from the chirp signal. These principles are not yet widely used in ultrasound technology. Chirp-coded ultrasound is common between the two methods and enable to maximize total power on target due to longer transmitted signals (as opposed to pulsed operation). This work proposes to unite the Frequency-Modulated Constant-Wave scatterer localization with reciprocal Time Reversal – Nonlinear Elastic Wave Spectroscopy principles to enable the localization of scatterers distant from the transducers and the analysis of their nonclassical nonlinearity which often can be caused by microdamage or cracking. In this paper only the first part (localization of scatterers using frequency-modulated constant wave ultrasound) of the problem is investigated. The main goal is to verify the feasibility of the method for ultrasound in solids and identify the main problems to be solved. Physical experiments and simulations are used to ascertain the detectability of linear and nonlinear scatterers in an isotropic solid medium (acrylic) using ultrasound. Potential problems with this approach are identified, to be solved in future work. In the future, this approach could enable to spatially filter the return signals, enabling to use reciprocal time reversal for focusing the wave energy in space directly onto selected scatterers, using the simplest of test setups: one transmitting and two receiving transducers.

A broadband and multiband magnetism-plucked rotary piezoelectric energy harvester

This study introduces a broadband and multiband piezoelectric energy harvester characterized by an E-shaped structure based on the rotational magnetic excitation. The piezoelectric oscillator is comprised of a trio of piezoelectric beams, which is like the letter 'E'. To elucidate the harvester's performance, this work employs both finite element analysis and experimental methods to explore the effects of pivotal parameters. Length ratio (Lr) and mass ratio (Mr) can influence the first two modes of vibration of the E-shaped oscillator. Lr = 1.0 and Mr = 3.0 are the critical points for mode transition of the E-shaped oscillator. Changing the added mass can reduce the gap between the resonance speed regions of the inner and outer beams, thus achieving the purpose of broadband. When piezoelectric patches are arranged in a "品" shape on the inner and outer beams, the total output power of a single oscillator can reach 5.33 mW, with the inner and outer beams contributing 4.01 mW and 1.32 mW respectively. Besides, when rotating magnets are two, a single piezoelectric oscillator can have 9 effective working regions. These can enhance the efficacy of energy harvesters, particularly in the realm of autonomous and self-powered systems.

A full wave solver integrated with a Fokker–Planck code for optimizing ion heating with ICRF waves for the ITER deuterium–tritium plasma

Efficient ion heating is crucial for future fusion devices, and the only way to heat ions directly is ion cyclotron resonance heating. Reported here is a full wave solver integrated with a Fokker–Planck code for optimizing ion heating with ion cyclotron range of frequency waves for the International Thermonuclear Experimental Reactor deuterium–tritium plasma. Both the direct absorption of minority ions and the power transfer to bulk ions via collisions are considered, while also accounting for the edge effects on ion absorption near the core. The simulation results show that the appropriate scrape-off layer density profile and parallel wave number lead to enhanced edge coupling and broaden the absorption region with moderate absorption intensity of the minority ions, which is very important for ion heating. More power from the heated ions is transferred to bulk ions than to electrons through collisions in our simulation via optimization, and reducing the total RF power results in a significant increase of the absorbed fraction of bulk ions.

Estimation of Total Real and Reactive Power Losses in Electrical Power Systems via Artificial Neural Network

Estimation of Total Real and Reactive Power Losses in Electrical Power Systems via Artificial Neural Network

An intelligent non-intrusive load monitoring model based on power encoding and convolutional state modules

Abstract Non-intrusive load monitoring (NILM) identifies device power consumption or on/off states solely based on total power data, which is highly valuable for consumers to understand their appliance usage behavior and take necessary measures to reduce energy consumption, especially for the benefit of energy consumers’ living production. However, a challenge faced by NILM is the tendency to focus excessively on power disaggregation while neglecting the disaggregation of on/off states, leading to lower classification accuracy, particularly owning to imbalanced states. This study proposes a model that integrates the power and on/off states to simultaneously disaggregate the power and device on/off states. The model comprises two main modules: a power encoding module for power disaggregation, and a convolutional state module (CSM) for on/off state disaggregation. The power encoding module utilizes BERT-LSTM and long short-term memory networks for initial energy disaggregation. In contrast, the CSM employs convolutional neural networks for device state disaggregation. The output of the power-encoding module is multiplied by the probability of on/off states to obtain the final power. The proposed model is evaluated using the REDD and UK-DALE datasets. Compared to the baseline models, the results show an improvement in the device state classification average accuracy from 0.948 to 0.957, and a decrease in the average error between the real power and disaggregated power from 26.356 W to 25.108 W. Additionally, real-world experiments conducted using the designed platform for collecting and disaggregating power data achieve an average accuracy of 0.997. The proposed model demonstrates competitiveness in the NILM field and underscores its significance in aiding energy-consumption reduction efforts.

Improved mountain gazelle optimizer based interactive distributed strategy to solving large scale OPF

This paper focuses on solving the multi-objective optimal power flow of large-scale power systems under critical loading margin stability with accuracy using a novel improved mountain gazelle optimizer (IMGO)-based flexible distributed strategy. Multi-shunt compensator-based flexible alternative current transmission systems (FACTS), such as SVC and STATCOM devices, are integrated at specified locations to exchange reactive power with the network. Several metaheuristic methods can solve the standard OPF related to small and medium test systems. However, by considering large-scale electric systems based on FACTS devices and renewable energy and by considering the operation under loading margin stability, the majority of these techniques fail to achieve a near-global solution because of the high dimension and nonlinearity of the problem to be solved. This study proposes the Multi-Objective OPF-Based Distributed Strategy (MO-OPFDS), a new planning strategy that optimizes individually and simultaneously various objective functions, in particular the total power loss (T∆P), and the total voltage deviation (T∆V). Standard MGO search is enhanced by automatically balancing exploration and exploitation throughout the search. The robustness of the proposed variant was validated on a large electric test system, the IEEE 118-Bus, and on the Algerian Network 114-Bus under normal conditions and at critical loading margin stability. The obtained results compared with several recent techniques clearly confirm the high performance of the proposed method in terms of solution accuracy and convergence behavior.

Sustainable and green removal of arsenic from crude tin via vacuum gasification–directional condensation

In the realm of high–tech industries, Sn has emerged as an indispensable strategic metal. However, the pyrometallurgical refining process of crude Sn is marred by the production of a substantial amount of hazardous solid waste, notably As–Al slag, posing a direct threat to the ecological safety of the production areas. This study delineates a novel process for the removal of As from crude Sn, employing vacuum gasification–directional condensation, corroborated by theoretical calculations and laboratory experimental research. Theoretically, at a system pressure ranging from 1–10 Pa, the initial volatilization temperatures of Sn and As exhibit significant variance. However, the formation of intermetallic compounds can induce Sn volatilization. Experimentally, the condensation temperature for As was predominantly within 331.7–484.7 K. During the vacuum gasification–directional condensation process, the presence of Sn4As3 intermetallic compounds impeded As volatilization. And under optimal conditions, the As content in the Sn product was recorded at 0.0053 %. Inspired from the calculations, a multistage vacuum distillation method was successfully proposed and achieved to remove As from crude tin. Typically, the total material recovery rate is 99.96 %, and the direct rate of Sn is 93.02 %. The total power consumption and emission of this process are better than the corresponding parameters of other treatment processes, which is a promising solution for the cleaning and effective removal of As.

Discriminatory ability of perioperative heart rate variability in predicting postoperative complications in major urologic surgery: a prospective cohort study

We aimed to determine if continuous perioperative heart rate variability (HRV) monitoring could improve risk stratification compared to a short preoperative measurement in radical cystectomy patients. Electrocardiography (ECG) recordings were collected continuously preoperatively to discharge in 83 patients. Two, 5-min ECG signal segments (preoperative and at 24-h post ECG placement) were analyzed offline to extract HRV metrics. HRV metric discriminatory ability to identify patients with 30-day postoperative complications were analyzed using receiver operating characteristics curves. Sixty participants were included for analysis of which 27 (45%) developed a complication within 30 days postoperative. HRV was reduced in patients with complications. Postoperative standard deviation NN intervals and root mean square of successive differences had area under the curves (AUC) of 0.67 (95% CI 0.54 to 0.81) and 0.68 (95% CI 0.54 to 0.82), respectively. Significant discriminatory abilities were also reported for postoperative frequency metrics of absolute low frequency (LF) [AUC = 0.65 (95% CI 0.51 to 0.79)] and high frequency (HF) powers [AUC = 0.69 (95% CI 0.55 to 0.83)] and total power [AUC = 0.66 (95% CI 0.53 to 0.80)]. Postoperative acquired HRV metrics demonstrated improved discriminatory ability. Our findings suggest that longer-term perioperative HRV monitoring presents with superior ability to stratify complication risk.

Innovative claw rotor design for claw vacuum pump and its power consumption analysis

The claw vacuum pump is extensively utilized in semiconductor, photovoltaic and aerospace industries because of its dry oil-free and compact structure. In order to reduce the power consumption of the claw vacuum pump caused by its special mixing process during operation, a novel pair of claw rotors was proposed. This innovation involves replacing the conventional circular arc at the dedendum of the claw rotors with an eccentric circular arc. A geometric model of the novel claw rotor was established, and the geometric characteristics of both the novel and conventional claw rotors were compared. Subsequently, the optimal design parameters were determined. The pressure distribution and power consumption of two claw vacuum pumps were analyzed with numerical simulations. Study results indicates that the power consumption of the proposed claw vacuum pump in the mixing process is reduced by 72.3 %, and the total power consumption is reduced by 12.6 % compared to the conventional pump. The study is of great significance for reducing power consumption of the claw vacuum pumps and improving application.

Shewhart-EWMA chart for monitoring binomial data subject to shifts of random amounts

Attribute charts are used widely for monitoring binary events in manufacturing, service, and healthcare processes. While Shewhart type charts are efficacious in detecting large or sudden shifts in a nonconforming rate p, exponentially weighted moving average (EWMA) type charts tend to be more powerful for detecting smaller or gradual shifts. Since many processes can shift by various amounts, this paper proposes a combined optimized Shewhart-EWMA dual chart that combines the strengths of both charts to quickly detect shifts of any random magnitude within a defined range. The performance of this combined Shewhart-EWMA chart is optimized by allocating total detection power between the Shewhart chart element and EWMA chart element in a manner that yields the best overall effectiveness while maintaining the false alarm rate at a specified desired level. In numeric analysis under a range of settings, the detection speed of this combined Shewhart-EWMA chart is found to outperform individual Shewhart and EWMA charts, with up to 499% and 31% fewer average number of defective items respectively until process shifts of random sizes are detected. It also demonstrates enhanced overall efficacy when compared to synthetic, cumulative sum, combined Shewhart-synthetic, and combined Shewhart-CUSUM charts.

Statistical spatial information based power optimization algorithm for multi-user massive MIMO systems

Power optimization has a significant role in multi-user massive multiple-input and multiple-output (mMIMO) wireless communication systems, whereas the acquisition of instantaneous channel state information (I-CSI) is a serious challenge in practical scenarios. The statistical spatial information (SPI), which contains angle-of-departures (AoDs) and corresponding large-scale fading factors, is slowly varying. The power optimization based on SPI to improve system performance needs to be explored for multi-user mMIMO systems. In this paper, two novel algorithms for SPI-based power optimization are proposed to maximize the ergodic sum-rate (ESR) under total power constraint for the system. Specifically, the minorization-maximization-based power optimization (MM-PO) algorithm and the closed-form power optimization (CF-PO) algorithm are proposed utilizing the minorization-maximization (MM) method and the fractional programming (FP) method, respectively. Moreover, the ESR is expressed based on the extracted SPI. The approximate expression of the ESR is derived. The complexity of the algorithms depends on the number of users, and the algorithms are scalable in the system. The proposed algorithms can effectively achieve the advantages of SPI while being robust to the uncertainty of I-CSI. Simulation results verify the ESR of our two proposed algorithms is 1.47 and 1.4 times higher than that of the equal power allocation algorithm at a high SNR when the number of antenna and user are equal to 64 and 20, respectively.