Quarter Cycle Research Articles

Monitoring a mass timber—BRB braced mass timber frame under cyclic loading via acoustic emission

This article focuses on the acoustic emission (AE) monitoring of a new type of mass timber buckling restrained brace (T-BRB), consisting of a wood casing made of mass plywood panel and a steel core embedded in the casing, for improving seismic resilience of mass timber structures. The casing secures the steel core through a series of bolts. To investigate the failure mechanisms of T-BRBs, two cyclic loading tests are conducted on a mass timber frame braced by T-BRBs with and without carbon fiber-reinforced polymer wraps, and an AE system is deployed for structural health monitoring (SHM). Multiple AE signatures are analyzed to infer the yielding point and failure modes of the T-BRB. AE features, including AE hit rate and cumulative energy, can successfully identify the ultimate structural failures. Results from AE hits and measured area of rectified signal envelope (MARSE) per quarter cycle suggest that the first significant feature values correspond to the cycle when the embedded steel core yielded. The b-value analysis demonstrates a general decreasing trend through the loading process and can characterize the evolution of structural damages. By evaluating both the strain energy and AE energy to reflect damage severity, the sentry function can identify the load cycle of steel core yielding and ultimate structural failure. As the first work applying AE monitoring on structural experiments of T-BRB, this research provides general guidances for SHM of T-BRB braced mass timber structures.

Design of modified long short-term memory-based zebra optimization algorithm for limiting the issue of SHEPWM in multi-level inverter.

This research work proposes unique MLSTM-ZOA to quickly measure SAs for an MLI. Within a certain MI range, the suggested method may calculate a greater count of SAs with various solutions. Here, the main objective lies in minimizing the THD with consideration of three parameters such as MI, number of pulses per quarter cycle, and duty cycle. Furthermore, by achieving a lower fitness value in less iteration, the suggested method has definitely outperformed other methods with respect to convergence behavior, according to the data. Lastly, analysis and performance associated with the experimental validation of SHE in multi-level inverter are also carried out. The proposed MLSTM-ZOA model in terms of THD is 56.25%, 81.58%, 53.33%, and 41.67% better than MPA, HHO, MGMPA, and SF-BOA respectively. Similarly, the proposed MLSTM-ZOA model with respect to HDP is 64.03%, 47.16%, 84.01%, and 27.62% advanced than MPA, HHO, MGMPA, and SF-BOA respectively.

ТЕСТУВАННЯ ЕЛЕКТРООБЛАДНАННЯ НА НЕСПРИЙНЯТЛИВІСТЬ ДО ПРОВАЛІВ НАПРУГИ, КОРОТКОЧАСНИХ ПЕРЕРИВАНЬ ТА ЗМІН НАПРУГИ

The article examines the testing of electrical equipment for immunity to voltage dips, short-term interruptions, and voltage changes. Special attention is paid to the influence of the starting point of the dip on the sensitivity of electrical equipment, as well as to the study of the resistance of the electromagnetic relay to voltage dips, phase angle jumps, and the starting and ending points of dips. The reaction mechanism of the electromagnetic relay to a voltage drop, its sensitivity to a change in frequency, the presence of harmonic distortions and changes in the nominal value of the voltage are analyzed. The symmetry of a quarter cycle with respect to a point on the wave is considered separately. Ref. 6, fig. 6.

Power quality improvement of PWM AC Chopper fed capacitor run induction motor using BFO, PSO and CSO Algorithm

This paper exhibits performance enhancement of PWM AC chopper fed capacitor run induction motor by using optimization algorithm. The PWM AC chopper utilizes enhanced asymmetrical pulse width modulation technique by incorporating four pulses in quarter cycle. The switching instants are obtained optimally by bacteria foraging optimization, particle swarm optimization and cuckoo search optimization algorithm. The power quality parameters considered in this paper are total harmonic distortion of current, total harmonic distortion of voltage, power factor and efficiency. The simulation result shows that proposed algorithm shows better performance compared to other optimization techniques.

Procedure in developing a longitudinal-torsional vibration-assisted micro-milling system

Micromachining is an advanced microfabrication technique for micro-sized or micro-accuracy products through subtractive manufacturing such as micro-milling. Vibration-assisted machining (VAM) is a method in which small amplitude vibrations are applied to the tool or workpiece to enhance the fabrication process. Milling results could be improved by adding longitudinal and torsional vibration to the tool using piezoelectric components vibrating at the ultrasonic frequency with an amplitude of less than 1 μm is used. A slip ring is required to transmit electric power from a static structure to a rotating frame. After the power has been transmitted to the system, an ultrasonic horn, called an acoustic horn or sonotrode, amplifies the vibrations at the tool’s tip. Since the excitation vibration is only longitudinal, the magnification of the vibration at the tooltip is also only longitudinal. Grooves are added to the side of the ultrasonic horn to produce torsional vibrations. This vibration is then simulated through finite element analysis software, explicitly using explicit dynamics. A 3D simulation is run for a quarter cycle of micro-milling through a Ti-6Al-4V material. It could be concluded that the LTVAM application may improve machining quality, such as temperature reduction of up to 9%, cutting force reduction of up to 35%, and surface roughness improvement of up to 27%.

Broad Learning System Using Rectified Adaptive Moment Estimation for Harmonic Detection and Analysis

The extensive application of nonlinear components and power electronic devices in power systems has led to increasingly deteriorating harmonic pollution. The rapid and high-precision harmonic detection and analysis technology will set the prerequisite for mitigating the harmonic crisis. This paper presents a robust, stable and real-time approach based on broad learning system (BLS) for detecting and analyzing the amplitudes of fundamental and harmonic components, which only requires half or even quarter cycle input. Additionally, a fast-converging adaptive parameter learning strategy using rectified adaptive moment estimation (RAdam) for BLS is proposed. To obtain the actual distorted signals, the signal acquisition system is built on the basis of the designed multi-pulse rectifier power supply (6/18 pulse). With the fundamental frequency deviation, interharmonics and noise, etc., the simulated signals synthesized by MATLAB tool and the actual signals acquired from the built system are attained to verify the performance of methods. The proposed approach differentiates from other existing methods not only due to its superior precision and robustness in the presence of multitudinous interference factors but also its real-time performance because of low average computing time.

Effects of electrical parameters on weak shock waves induced by spark discharge

The effects of the electrical parameters, including storage capacitance, additional inductance, charging voltage, and electrode gap, on the shock wave induced by spark discharge in gas were experimentally investigated. The results showed that the shock waves induced by spark discharge conform to the attenuation law for weak spherical shock waves outside the spark core. The shock wave amplitude is approximately proportional to the electrode gap and storage energy and decreases with increasing inductance. The effect of the charging voltage on the shock wave amplitude can be almost ignored if the storage energy is the same. The average power in the first quarter cycle of spark discharge was found to be closely related to the shock wave amplitude. An empirical equation was given between the shock wave amplitude and the average discharge power, which provides convenient access to set appropriate electrical parameters to generate shock waves of specified amplitude induced by spark discharge.

A-344 Don't Get Rejected: Reduce Specimen rejection in Phlebotomy

Abstract Background Pre-analytical specimen rejection plagues laboratories, patient care decisions, and satisfaction. Rejection data used for quality improvement varies and often excludes pediatric-only populations. With an outdated benchmark of 2.2% total rejections, our phlebotomy department was maintaining a baseline rejection rate of 1.39%. We assessed only tests where a result was not able to be given for reasons of: Quantity Not Sufficient (QNS), Clotted, Hemolyzed, improperly collected or handled, and unlabeled or mislabeled. While our department exceeded current benchmarks, continued improvements were desired to provide the best care and experience. We collaborated with the Vascular access team (VAT) at our institution to improve our processes. Methods Specimen rejection was defined as any sample(s) collected for analysis not performed due to Quantity Not Sufficient (QNS), Clot, Hemolysis, improper collection/handling, and unlabeled/mislabeled specimens. Over the next 3 months, samples obtained by outpatient and inpatient phlebotomist draws were reviewed for pre-analytical errors. VAT and phlebotomy began meeting monthly and developed a 1-day shadow experience for new phlebotomy hires and a mechanism to identify DVA patients. In collaboration with Information Management, coping comfort plans (CCP) were implemented in patient medical record which documented patient preferences and staff observations for potentially painful procedures. The CCP paved updates tip sheets, purchases of transilluminators, and stock heat packs in phlebotomy stations. Additional aids were purchased for patient comfort in outpatient areas. A communication center installed and allowed for an area to write down room numbers of DVAs and to display current rejection rates. Improved staff communication regarding rejected samples was publicly posted on the communication center by phlebotomist name. These characterized type and number of rejections as well as a stoplight color coding to depict acceptable, at risk, and unacceptable errors by phlebotomists monthly. Goals were posted monthly in the communication center. 18 months was allotted for implementation of the final goal of ≤0.5% total rejections, allowing for quarterly reports, changes, and PDSA cycles. Results Initial staff surveys discovered 71% of staff were unaware of their rejected samples, 57% of staff were unaware this was a monitored metric, 100% of staff agreed importance. During quarter one of data reporting, it was assumed that all rejections would fall ≤1.25% monthly in Q2-Q3, ≤1.00% in Q4, and by Q2 of the following fiscal year to ≤0.50%. The average rejection rates were: Q1: 1.05%, Q2: 1.0%, Q3: 0.69%, Q4: 0.70%. In year 2 rejection rates were: Q1: 0.5%, Q2: 0.3%. Post-implementation survey conducted resulting in 100% of staff were aware of their rejected samples, aware of the metric, and agreed it was important. Staff additionally suggested improvements and have noted to have higher morale and trust within their group by partnering in this project to improve inpatient workflows. Average rejection rates were reviewed at 1- and 2-year post implementation: 0.05% and 0.42% respectively. Conclusion Rejection not only causes waste but a risk to patients as results and treatment can be delayed. By changing configurations in workflow, tools, communication and medical records, phlebotomy staff can be the key drivers of change

Transmission Line Protection Using Decaying DC Information in Fault Current

Today use of fast and reliable transmission line protection is of importance. This paper presents two protection techniques for transmission lines using information obtained from the decaying DC component of fault current and the pre-fault voltage signal. The fault direction is obtained using the polarities of pre-fault voltage and decaying DC of fault current. Internal faults in the transmission lines are detected with exchange of information on the decaying DC currents at both ends. The protection decisions are derived within a quarter cycle with a signal sampling rate of 4 kHz. Upon testing on a 400 kV simulated transmission system for different fault types, resistances, inception angles, and field data from a 400 kV line, the proposed techniques are found to be accurate.

Novel Approach for Synchronous Generator Protection Using New Differential Component

A new stator fault detection and classification scheme for synchronous generators (SGs), based on an amplified discrete Teager-kaiser energy operator (ADTKEO) of a new differential component ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DC_SI</i> ), is proposed. Detection of an internal fault is based on the fulfillment of the ADTKEO ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ξ</i> ) with respect to the pre-determined threshold along with the checking of second-harmonic content in the current transformer (CT) secondary current. Afterward, the classification of internal faults is performed based on ‘ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ξ</i> ’. The performance of the proposed scheme is tested on various fault cases obtained from a simulation network developed in a real-time digital simulator and the developed laboratory prototype of the SG. The results indicate that the proposed scheme not only provides 100% winding coverage against phase-to-ground faults but is also capable of detecting other phase faults within a quarter cycle for low-resistance grounded SGs. At the same time, it stays extremely stable for external faults, even considering errors in CT along with its saturation (without compromising speed/sensitivity). The proposed scheme is independent of the sampling frequency, loading condition, decaying dc component present in the acquired signals, and rating of the SG.

Support vector machine for fast fault detection and classification in modern power systems using quarter cycle data

This work proposes a support vector machine (SVM) based fault detection and classification method for a transmission system. The novelty of this work is that the time and frequency series parameters at both the ends of a line, amounting to 144, computed over the most recent eight samples, are considered the input data for the developed SVM model. With this higher number of features for the SVM model, the power system faults are detected and classified with a quarter cycle data of power frequency. The developed SVM, trained with operating scenarios involving 25,168 faults and no faults conditions with different fault resistances and angles of fault inception, can classify all symmetrical non-symmetrical faults. The algorithm is tested on an IEEE 9-bus system with 32 samples per cycle sampling rate and is evaluated with ten-fold cross-validation and four evaluation metrics. This methodology provides an average accuracy of 99.89 per cent for all fault scenarios despite measurement noise having a signal-to-noise ratio of 30 dB, 35 dB, and 40 dB. The comparative analysis presented in this work reveals that the developed SVM model performs better than five other reported classification algorithms in terms of the accuracy of the classification of faults.

Optimal PWM in Three-Level Inverter for THD Minimization with Quarter Wave Symmetry Relaxed

Background: Previous works on total harmonic distortion (THD) minimization for multilevel inverters (MLI’s) has made a symmetrical approach that imposes Quarter Wave Symmetry (QWS) and Half Wave Symmetry (HWS) with the aim to restrict the computational difficulties to solve the finalized non-linear expressions. Objective: However, QWS constraint can be abolished, which leads to more generalized formulations and multiple solutions corresponding to minimum THD for complete modulation index-range. Methods: A systematic search approach using MATLAB in-build function is adopted to investigate ideal angles of switching related to three-level, three-phase inverter restricted to only HWS as a constraint for two and three (i.e., N= 2 and 3) switching transitions per quarter cycle. Results: On account of the effective minimization of the dominant low-order odd line voltage harmonics, the proposed pulse-width-modulation (PWM) scheme proved its superiority based on minimum THD% performance compared to the previously reported PWM techniques with both HWS and QWS being retained. Conclusion: The simulation, as well as experimental results to confirm the efficacy of the proposed non-symmetrical PWM scheme over the traditional PWM method restricted to QWS and HWS symmetries over the entire modulation-index range with added advantage of general formulation and multiple solutions.

Disentangling interferences in the photoelectron momentum distribution from strong-field ionization

Using the semiclassical two-step model for strong-field ionization, we theoretically investigate subcycle interference structures in the photoelectron momentum distribution. Specifically, we focus on the low-momentum fanlike interference structure. Employing a time-variable soft-core Coulomb potential, we demonstrate that the low-momentum interference arises from the interference between drifted and undrifted electrons from opposite direct quarter cycles. We also find that the main scattering in the nuclear Coulomb potential occurs just after ionization. Our findings suggest that the low-momentum region of the photoelectron spectrum is particularly sensitive to the ion potential and thereby offers another path to probe ultrafast electronic structure dynamics.

Holocene Multi‐Centennial Variations of the Asian Summer Monsoon Triggered by Solar Activity

AbstractSolar activity affects Asian summer monsoon (ASM) at various time scales. However, it remains unknown if and how solar activity can influence ASM on the centennial time scale. Using the Community Earth System Model, we conduct a solar activity forced Holocene transient simulation with an acceleration factor of 10 and show that during the middle–late Holocene ASM precipitation exhibits a significant 300–600‐year periodicity under solar forcing. This model‐produced multi‐centennial variation is also suggested by proxy data. The leading mode of the multi‐centennial ASM variation shows a “wet tropics–dry subtropics” pattern, which lags the corresponding solar activity by about a quarter cycle. The western North Pacific (WNP) circulation system is responsible for the multi‐centennial ASM variation, through enhancing the climatological south Asia–WNP monsoon trough. We suggest that solar activity modulates the zonal SST gradients of the tropical Pacific, inducing the anomalous WNP cyclone and enhancing ASM precipitation in a delayed mode.

Hilbert–Huang transform and decision tree based islanding and fault recognition in renewable energy penetrated distribution system

A fast protection algorithm based on Hilbert–Huang transform (HHT) is proposed in this paper for islanding and fault detection, classification, and location in a distribution system penetrated by a solar renewable energy source. The three-phase current signals measured at the substation are utilized to extract the instantaneous features from the first level residue using Hilbert Transform (HT) after empirical mode decomposition (EMD). The feature indices computed per phase for each event using minimum post-disturbance data are then fed to a decision tree machine learning (DTML-1) model to classify disturbances into four classes: normal, fault, islanding, and switching transient. Once a fault is determined, another DTML-2 model classifies the fault into one of the seven types of faults, namely 3P-ABC (three-phase faults), 2P-AB, 2P-BC, 2P-AC (two-phase faults), 1P-AG, 1P-BG, and 1P-CG (single-phase faults). Subsequently, seven DT models based on the fault type locate the IEEE 13 bus system’s zone of fault. Variations in noise levels, DG capacity, and fault incidence angles test the proposed algorithm to achieve a good accuracy level in less time. Switching transients like capacitor switching, feeder on/off, and transformer excitation/de-excitation are also successfully classified within a quarter cycle contaminated with noise levels of 20 dB SNR.

Digital-image-correlation observation of cyclic plastic strain field during the damage-accumulation mode of fatigue crack propagation under pure cyclic mode II loading for cold-rolled SUS430 steel

Fatigue cracks propagate intermittently by the cyclic initiation and coalescence of voids in front of the fatigue crack tip during fatigue crack propagation in the damage accumulation mode. In this study, digital image correlation is used to measure the evolution of the measured plastic strain distribution near the crack tip with loading and cyclic loading during one cycle. The evolution is estimated based on strain distribution measurements results and mechanical considerations. The strain is set at the unloading point because results indicate that the crack propagated in the region where the experimental shear plastic strain is the maximum in the first quarter cycle (at the first maximum load); the measured plastic strain is almost constant in the region where the crack propagates, and the crack is initiated by a subsequent cyclic strain localization and coalescence with the main crack. This study clarified the damage accumulation mode fatigue crack propagation mechanism with the measured strain behavior, and presents a method to use continuum plastic strain at the crack tip as a mechanical driving force for this mode.

Influence of Coulomb potential on photoelectron momentum distributions in few-cycle linearly polarized laser field

We investigate the influence of the Coulomb potential on the photoelectron momentum distributions of H atoms in few-cycle linearly polarized laser field by numerically solving the time-dependent Schrödinger equation and using the semi-classical method. We demonstrate that the electrons ionized from the different time windows will contribute to different interference types and regions in the photoelectron momentum distributions. The typical trajectories of the photoelectrons are used to illustrate the effect of the Coulomb potential on the interference stripes. We mainly investigate the photoelectron momentum distribution contributed by the electron wave packets, which are emitted within the nonadjacent falling edges of the electric field. In this case, a discontinuous region near the center of the photoelectron momentum distribution can be clearly observed, which exhibits a strong dependence on the Coulomb potential. We also observe a shift in the photoelectron momentum distributions in each quarter cycle. We quantitatively illustrate that the shift is induced by the Coulomb correction along the axis of polarization. Our results may provide a reference for further analytical research about the shift of the photoelectron momentum distributions in few-cycle strong laser field.

Research on phase-locked loop technique based on three-dimensional coordinate transformation

The traditional phase-locked loop (PLL) technique widely used in three-phase four-wire system can only obtain one phase angle, and cannot obtain other parameters of unbalanced voltages, such as the amplitude and phase angle of each phase voltage. In order to improve the performance of PLL in unbalanced three-phase four-wire system with disturbance and reduce the order of PLL to improve the stability of the system, a PLL technique based on three-dimensional (3D) coordinate transformation was proposed in this paper. Firstly, the phase detector error of three-phase unbalanced voltage was deduced based on the 3D coordinate transformation. The error can be regarded as the expression form in Hilbert space after linearizing of it. Based on the correspondence between the orthonormal basis in Hilbert space and the unit vectors in Euclidean space, the error can be mapped to Euclidean space, and the detection control law for each voltage parameter can be designed respectively based on the principle of perpendicular decoupling. Then, the voltage parameter detection control law in Euclidean space is mapped back to Hilbert space, so the PLL technique scheme can be obtained which is beneficial to the implementation in the actual system. The control law of each unbalance indices, such as the amplitude and initial phase of each phase voltage, can be decoupled into a first-order or second-order system, so the system structure is simple, and the control parameter design is convenient. The detection of unbalance indices of the three-phase unbalanced voltages with zero-sequence component can be realized with fast and stable characteristics. The simulation and experiments of the proposed PLL technique are carried out finally under several transient conditions of grid voltages, stable within a quarter cycle at the fastest and always stable in 50 ms, so as to validate the rapidness and stability of the proposed PLL technique.

Cylindrical metal liner implosion at extremes of pressure and material velocity on an intense pulsed power facility-FP-2.

Highly precise and controllable liner implosions driven by a pulsed power facility have extensive applications in exploration of advanced hydrodynamics at the extremes of pressure and material velocity. In this paper, we describe a new pulsed power facility developed in China named FP-2 (a series of facilities for Fluid Physics investigations-the second generation) for liner implosions. Benefiting from the reliable and stable operation of 48 rail gap switches, the FP-2 facility can steadily transmit a current of 10.5 MA to a dummy load of 10 nH in the case of a charging voltage of ±40kV. The first quarter cycle is 5.5 µs, and the percentage shot-to-shot deviation of the current history is less than 1%. When the aluminum liners of 60mm in height and 0.6mm in thickness are adopted, the maximum velocity of 4.5 and 7.5 km/s has been achieved with the liner diameter of 90 and 60mm, respectively, at the diameter of 10mm. Experimental results show that the percentage shot-to-shot deviation of the liner velocity history is less than 1%. As impact on the target, the maximum of the impact time deviation measured from four perpendicular fiber pins is less than 20ns. Due to the modular design of FP-2, it is convenient for a future upgrade. The confirmation of high-quality implosion on FP-2, such as high repeatability, high reliability, and high symmetry, makes it a bright prospect to explore the advanced hydrodynamic problems at extremes of pressure and material velocity in the future.

Data mining model and Gaussian Naive Bayes based fault diagnostic analysis of modern power system networks

In this paper, different machine learning (ML) algorithms like Gaussian Naïve Bayes (GNB), K-Nearest Neighbours (KNN), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF) and Adaptive Boosting Classifier (ABC) are used to classify the different types of faults on the transmission line. The faults and non-faults on the transmission line are created by simulating the transient behaviour of the long length transmission line by using PSCAD/EMTDC software. While simulating the faults and non-faults on the transmission line, fault resistance, fault inception angle, fault location and fault type are varied within their practical range. During the simulation, currents and voltages of three phases on both sides of the TL are measured using Current Transformers (CT) and Potential Transformers (PT) . Measured currents and voltages are pre-processed to produce the time series and frequency series parameters data set by using Fourier Transform in full cycle, half cycle, and quarter cycle from the fault instant. Feature reduction techniques select very important parameters among the calculated time series and frequency series parameters. After completing the data generation and pre-processing and application of feature reduction techniques, the machine learning algorithms are applied to the data in python software to get the comparative analysis. Noise analysis is also carried out in this work to assess the performance of the ML algorithms in dealing with the nonlinear data due to CT, PT saturation, and measurement errors.