Output Operation Research Articles

Switchable Dual-Wavelength Fiber Laser with Narrow-Linewidth Output Based on Parity-Time Symmetry System and the Cascaded FBG

In this paper, a dual-wavelength narrow-linewidth fiber laser based on parity-time (PT) symmetry theory is proposed and experimentally demonstrated. The PT-symmetric filter system consists of two optical couplers (OCs), four polarization controllers (PCs), a polarization beam splitter (PBS), and cascaded fiber Bragg gratings (FBGs), enabling stable switchable dual-wavelength output and single longitudinal-mode (SLM) operation. The realization of single-frequency oscillation requires precise tuning of the PCs to match gain, loss, and coupling coefficients to ensure that the PT-broken phase occurs. During single-wavelength operation at 1548.71 nm (λ1) over a 60-min period, power and wavelength fluctuations were observed to be 0.94 dB and 0.01 nm, respectively, while for the other wavelength at 1550.91 nm (λ2), fluctuations were measured at 0.76 dB and 0.01 nm. The linewidths of each wavelength were 1.01 kHz and 0.89 kHz, with a relative intensity noise (RIN) lower than −117 dB/Hz. Under dual-wavelength operation, the maximum wavelength fluctuations for λ1 and λ2 were 0.03 nm and 0.01 nm, respectively, with maximum power fluctuations of 3.23 dB and 2.38 dB. The SLM laser source is suitable for applications in long-distance fiber-optic sensing and coherent LiDAR detection.

Graphene-enhanced ferroelectric domain wall high-output memristor

Recent studies on memristive materials and technologies have expanded beyond conventional memory elements, driven by their potential application in novel information processing concepts. Among these materials, conductive domain walls in ferroics are especially promising, offering conductive tunability suitable for reconfigurable multi-state devices. However, challenges such as domain stability, time-dependent conductivity, and low current output have impeded progress in the field. Here, we study the graphene/Pb(Zr,Ti)O3/SrRuO3 system, which demonstrates robust domain wall conduction up to 100 nA/μm2 for 2 V bias, while addressing the critical issue of stability of switched domains. The introduction of graphene electrodes enhances low-voltage stochastic domain formation with limited domain expansion that promotes the emergence of multi-domain states. The developed micrometer sized capacitor devices enable electrically programmable multiple distinct conduction states with robust retention combined with high current output and low operation voltage. These features are highly desirable for memristors and mark the significant potential of domain wall electronics for neuromorphic computing.

An Integrated Double-Sided LCC Compensation Based Dual-Frequency Compatible WPT System with Constant-Current Output and ZVS Operation

This article presents an integrated double-sided inductance and double capacitances (DS-LCC) compensation based dual-frequency compatible wireless power transfer (WPT) system. A cascaded single-phase multi-frequency inverter (CSMI) is constructed to generate the independent dual-frequency power transfer signals. In order to achieve the load-independent constant-current output (CCO) at two frequencies, an integrated DS-LCC compensated topology is reconstructed. By configuring the frequency-selective resonating compensation (FSRC) network in the primary side, the power transfer signals at two frequencies can be superimposed into a single transmitting coil, reducing the cost and volume of the system. Furthermore, to implement zero-voltage switching (ZVS) of the CSMI throughout the entire power range, a general parameter design method of the proposed system is also introduced. A 1.5-kW experimental prototype is built to validate the practicability of the presented dual-frequency compatible WPT System. The system can supply power to different loads at two frequencies simultaneously with CCO and ZVS properties. The peak efficiency reaches 91.75% at a 1.2-kW output power.

Differentiable programming for gradient-based control and optimization in physical systems

This paper presents an exploration of the application of control theory, particularly utilizing a gradient-based algorithm, to automate and optimize the operation of photovoltaic panels and refrigeration systems in warehouse environments. The study emphasizes achieving coordination between energy generation and consumption, specifically harnessing surplus solar energy for efficient refrigeration. The complex interplay between fluctuating solar irradiance, thermal dynamics of the warehouse, and refrigeration needs underscores the significance of control theory in designing algorithms to dynamically adjust PV panel output and refrigeration system operation. The paper discusses foundational control theory principles, proposes a tailored framework for warehouse operations, and highlights the potential for sustainable energy practices. This paper explores the use of data-driven approaches based on NeuralODEs vs classical ones using physics equations.

A low-voltage, high-performing CMOS transistor based on multiple- output operation transconductance amplifier for current mode KHN Universal filter applications

This study proposes a current-mode KHN universal filter design that can perform three standard functions simultaneously: low-pass, high-pass, and band-pass. The circuit is built around a multiple-output operation transconductance amplifier (MO-OTA), which allows for electronically adjustable pole frequency and quality factor by modifying input bias currents (IB). The circuit layout is straightforward, with two MO-OTAs and two grounded capacitors, eliminating the need for external resistors and depending entirely on grounded components. Because of its simplicity, the circuit is suited for use in a tiny, efficient design. The proposed circuit's operation was validated using LT-Spice simulations, and the results were in line with theoretical expectations. The circuit used around 298μW of power at ±0.2V power supply voltages. These results demonstrate the circuit's potential for low-power applications, which are crucial in many modern electronic devices. The suggested current-mode KHN universal filter offers a viable option for combining various filter functions in a single circuit with customizable parameters. Its simplicity, efficiency, and performance qualities make it a feasible choice for incorporation into a variety of electronic systems, allowing for more filter design freedom.

Modified Re‐Entrant‐Like (K, Na)NbO3‐Based Relaxors with Superior Electrostrain Properties

AbstractPiezoceramics with large strain output, low hysteresis, and wide operation temperature are indispensable for the high‐end displacement control. Unfortunately, requiring these merits simultaneously remains a long‐standing challenge for lead‐free piezoceramics promising for replacing lead‐based ones. Herein a new strategy to resolve this challenge by developing modified re‐entrant‐like potassium sodium niobate ((K, Na)NbO3, KNN) relaxors is presented. Multi‐scale structural analysis reveals the presence of the significant local disorder, nano‐sized multi‐phase coexistence, and ultra‐fine grains, which facilitate the polarization rotation, effectively eliminate non‐180° domains, and erase polymorphic phase transition features in re‐entrant‐like KNN relaxors. Consequently, a combination of large strain (≈0.19%), ultra‐low hysteresis (<7%), high electrostriction coefficient (Q33 = 0.049 m4 C−2), and benign temperature stability (i.e., strain varies less than 10.6% within 30–120 °C) is realized, superior to other lead‐free relaxors. Therefore, this strategy provides a novel paradigm for designing high‐performance lead‐free piezoceramics used for high‐precision actuators.

Broad, Tunable and Stable Single-Frequency Erbium Fiber Compound-Ring Lasers Based on Parallel and Series Structures in L-Band Operation

In this demonstration, we present two erbium-doped fiber (EDF) lasers, with series and parallel three sub-ring configurations, respectively, to achieve tunable channel output and stable single longitudinal mode (SLM) operation in the L-band range. Here, the fiber ring cavity contains the L-band EDF as a gain medium. Based on the measured results of the two quad-ring structures of the EDF lasers, tunable output bandwidth for the two lasers can be obtained from 1558.0 to 1618.0 nm simultaneously. All the 3 dB linewidths measured for both fiber lasers are 312.5 Hz over the effective wavelength output range. Furthermore, the related optical signal-to-noise ratio (OSNR), output power, output stabilities of the central wavelength and power, and equal output power range of the two proposed EDF lasers are also examined and discussed.

Adaptive large neighborhood search algorithm with reinforcement search strategy for solving extended cooperative multi task assignment problem of UAVs

In response to the increasing complexity of military operations, the use of multiple heterogeneous unmanned aerial vehicles (UAVs) is essential for efficiently executing complex missions. This paper introduces an extended cooperative multi-task assignment problem (ECMTAP), which involves deploying heterogeneous UAVs from different base stations to accomplish specific missions, with a focus on minimizing overall mission completion time. ECMTAP categorizes targets into various types, each associated with unique task sets including {reconnaissance}, {attack, evaluation}, and {reconnaissance, attack, evaluation}. ECMTAP requires that attack tasks follow reconnaissance tasks, and evaluation tasks follow attack tasks, adding complexity due to specific timing constraints on each task. To tackle this problem, we propose a novel algorithm, the reinforcement search strategy-based adaptive large neighborhood search (RSALNS). To enhance the search capability, RASLNS utilizes two key destroy-repair operations: the intra-target tasks adjustment strategy and the evaluation tasks adjustment strategy. The former operation dismantles and reconstructs task sequences within a target, potentially resulting in suboptimal assignment of evaluation tasks, while the latter operation reassigns these tasks based on the first operation's output. Extensive experiments validate the effectiveness of the RSALNS algorithm in solving the ECMTAP, demonstrating its capability to generate high-quality solutions efficiently.

Research on bearing fault diagnosis based on novel MRSVD-CWT and improved CNN-LSTM

As a critical component in mechanical equipment, rolling bearings play a vital role in industrial production. Effective bearing fault diagnosis provides a more reliable guarantee for the safe operation of the industrial output. Traditional data-driven bearing fault diagnosis methods often have problems such as insufficient fault feature extraction and poor model generalization capabilities, resulting in reduced diagnostic accuracy. To solve these problems and significantly improve the diagnosis accuracy, this paper proposes a novel fault diagnosis method based on multi-resolution singular value decomposition (MRSVD), continuous wavelet transform (CWT), improved convolutional neural network (CNN) enhanced by convolutional block attention module, and long short-term memory (LSTM). Through MRSVD, the vibration signal is decomposed layer by layer into multiple denoised signals, thus signal noise can be eliminated to the greatest extent to gain the optimal denoised signals; then through CWT, the optimal denoised signals are converted into two-dimensional time-frequency images so that the local and global characteristic information can be fully captured. Finally, through improved CNN-LSTM, feature extraction is greatly enhanced, resulting in high accuracy of fault diagnosis. Lots of experiments are organized to test the performance, and the experimental results show that the proposed method on various datasets has better diagnosis accuracy and generalization ability under different working conditions than other methods.

The application study of preventive maintenance during normal operation for APR1400 nuclear power plants considering risk

Preventive Maintenance(PM) for safety component during power operation at nuclear power plants, On-Line Maintenance(OLM) refers to intentionally entering the Limited Condition of Operation(LCO) specified in the Technical Specification(TS) for safety-related systems and components in order to perform preventive maintenance within the Allowed Outage Time (AOT). This study assessed the feasibility of conducting OLM at the domestic APR1400 nuclear power plant. It focused on preventive maintenance duration and risk perspectives. A total of 78 FEGs were developed for 4450 facilities, considering system functions and preventive maintenance scope during output operation for eight safety-related systems. Additionally, maintenance items included in FEGs were selected, designated as targets for OLM, and their maintenance durations were evaluated and compared with AOT for each maintenance item. As a result, the Auxiliary Feedwater and Essential Chilled Water systems were identified as systems allowing OLM. Furthermore, utilizing the Risk Monitoring System (RIMS), the increased risk value due to the unavailability of target equipment during preventive maintenance was analyzed to determine whether it falls within the acceptable range.Regarding the temporary risk increase caused by OLM, it was observed that in all systems, it falls within Zone III according to NUMARC93-01 standards, allowing for normal equipment arrangement for OLM. However, according to the risk increase standards rate in domestic nuclear power plants, when maintaining the A-train in four systems including Component Cooling Water, they are all evaluated as 'Orange,' indicating that measures for risk mitigation are necessary for OLM to be feasible. When considering extending AOT up to 1.6 times the maintenance time, the risk increase falls within Zone III according to permissible change in risk standards, indicating that AOT extension might be feasible based solely on risk changes. To apply OLM within the permissible risk management scope in domestic nuclear power plants, regulatory policies need to allow voluntary LCO entry for preventive maintenance, necessitating clear determination by regulatory agencies using risk-informed policies. While OLM seems viable concerning maintenance duration and quantitative risk aspects, for inducing regulatory policy changes, comprehensive OLM guidelines are necessary, including risk management strategies.

Polarity control of siloxane composite films for triboelectric nanogenerator based self-powered body temperature monitoring

Body temperature monitoring systems serve as key indicators for identifying potential patients with various illnesses such as influenza and COVID-19. Conventionally, these monitoring devices rely on batteries, limiting their long-term and widespread application. Self-powered thermometers are considered a sustainable solution that enable continuous monitoring. Among various self-charging power sources, triboelectric nanogenerators (TENGs) are a novel development, but suffer several critical drawbacks for medical applications. In this study, we present a high-performance TENG for self-powered body temperature monitoring systems by controlling the polarity of glass-fabric reinforced vinyl-thiol functionalized hybrid materials (GFR-VTHs) by varying the phenyl group contents. The effect of polarity modification on the performance of the developed TENG was confirmed by the high electrical output and stable operation under 10,000 cycles of repetitive pressing tests. Finally, self-powered body temperature monitoring systems were constructed by measuring human body temperature with a clinical thermometer powered by the GFR-VTH-based TENG, demonstrating device feasibility as a power source for self-powered healthcare systems.

Performance analysis and comparison of a novel Steiner-Quadrature Space Shift Keying (S-QSSK) scheme in massive MIMO systems

This paper introduces Steiner-quadrature space shift keying (QSSK) (S-QSSK), an innovative modulation scheme tailored for multiple–input multiple–output (MIMO) systems. The study compares S-QSSK with existing modulation schemes (S-space shift keying (SSK)(S-SSK), QSSK, generalized quadrature space shift keying (GQSSK)) across various performance metrics, considering diverse channel conditions, transmit antenna numbers, and spectral efficiencies. Theoretical average bit error rate (ABER) analysis, validated by Monte Carlo simulations, establishes a close agreement between analytical and practical results, especially at realistic signal-to-noise-ratio (SNR) values. Additionally, capacity and mutual information formulas shed light on the system’s information transmission capabilities. The research delves into the outage probability, power consumption, and computational complexity of S-QSSK MIMO systems. It unveils a promising trade-off, demonstrating that S-QSSK achieves competitive performance in ABER, capacity, and mutual information, positioning it as a practical modulation technique. Importantly, S-QSSK exhibits about a 1 dB ABER performance decrease compared to S-SSK and QSSK, while offering a noteworthy 2 dB improvement over GQSSK. Despite requiring slightly more transmit antennas than GQSSK, S-QSSK demands significantly fewer than both S-SSK and traditional QSSK, particularly when targeting high spectral efficiencies. Moreover, the analysis underscores the advantageous power consumption and favorable computational complexity of S-QSSK relative to other modulation schemes. The proposed S-QSSK MIMO system thus presents itself as an efficient solution, enabling high data rates with fewer transmit antennas, resulting in substantial reductions in power consumption and computational complexity without a significant sacrifice in ABER and mutual information. These attributes make it a compelling choice for various applications, including those requiring efficient massive multiple–input multiple–output (mMIMO) operations.

Tomofast-x 2.0: an open-source parallel code for inversion of potential field data with topography using wavelet compression

Abstract. We present a major release of the Tomofast-x open-source gravity and magnetic inversion code that incorporates several functionalities enhancing its performance and applicability for both industrial and academic studies. The code has been re-designed with a focus on real-world mineral exploration scenarios, while offering flexibility for applications at regional scale or for crustal studies. This new version includes several major improvements: magnetisation vector inversion, inversion of multi-component magnetic data, wavelet compression, improved handling of topography with support for non-uniform grids, a new and efficient parallelisation scheme, a flexible parameter file, and optimised input–output operations. Extensive testing has been conducted on a large synthetic dataset and field data from a prospective area of the Eastern Goldfields (Western Australia) to explore new functionalities with a focus on inversion for magnetisation vectors and magnetic susceptibility, respectively. Results demonstrate the effectiveness of Tomofast-x 2.0 in real-world studies in terms of both the recovery of subsurface features and performances on shared and distributed memory machines. Overall, with its updated features, improved capabilities, and performances, the new version of Tomofast-x provides a free open-source, validated advanced and versatile tool for constrained gravity and magnetic inversion.

Spatial Mode Division Multiplexing of Free-Space Optical Communications Using a Pair of Multiplane Light Converters and a Micromirror Array for Turbulence Emulation

Multi-plane light converters (MPLC) are a means of deconstructing a wavefront into constituent modes that are focused at specific spatial locations, and the reverse—that specific inputs result in controlled modal output. We have used a pair of MPLCs with 21 Hermite–Gaussian modes to represent a free-space optical connection. The effects of strong atmospheric turbulence (Cn2 = 10−13 m−2/3) are emulated using a micromirror array producing a time sequence of aberrating frames. The modal crosstalk between transmitter and receiver modes induced by the turbulence is presented by measuring the intensity in receiver channels for the same turbulence. Six receiver modes are used for optical communication channels with a rate of 137 Gbits/s displaying the benefits of single input multiple output (SIMO) operation for overcoming the deleterious effects of turbulence.

A new strategy of dual-material reactors for stable thermal output of sorption thermal battery

Sorption thermal battery driven by air humidity is a promising alternative technology to traditional methods of burning fossil fuels for space heating. Its dominant design of one-material reactor faces technical bottlenecks of unstable discharging thermal output and low energy efficiency. Herein, a new strategy of cascaded dual-material reactors was proposed as a solution, by utilizing their different sorption characterizations at material level and “reaction wave” properties at system level. A proof-of-concept prototype was established, whose main and regulatory reactor were packed with AA-15% LiCl composite and SrBr2·H2O, respectively. Experimental results demonstrated that the regulatory reactor has a strong stabilization function of the unstable output temperature of the main reactor, with the average output temperature fluctuations under 1.5 °C. The discharging/charging energy efficiency was increased by 0.4–1.7 times compared with one-material reactor. The output temperature level and heating power can be simply adjusted by changing the inlet air humidity and air velocity. Moreover, the influences of the lengths of two reactors on the thermal output and system operations were evaluated. Possible strategies to further enhance the multistage utilization of the charging energy were proposed. This new design strategy can contribute to the popularization and application of sorption thermal battery.

Distributed and Analogous simulation framework for the control of pests and diseases in plants using IoT Technology

In contemporary society, agriculture is progressively embracing technological innovations called Precision Agriculture. The utilization of various pest control and disease management strategies is of considerable importance in the surveillance of plants. The current framework encounters multiple challenges. The pest control and disease surveillance system employs a solitary Graphical Processing Unit (GPU) to manage the diverse array of connected sensors. Hence, this paper proposes utilizing the Distributed and Analogous Simulation Framework (DASF) in conjunction with the Internet of Things (IoT) to address the issue of pest control and diseases in plants. The approach reduces the strain on a specific GPU, effectively allocates the computational tasks across all accessible GPUs concurrently, and ensures continuous data transmission to the dashboards even in the event of GPU malfunction. The implementation of this procedure is anticipated to result in a reduction in overall system performance. In the DASF multi-threading framework, the allocation of tasks to particular auxiliary cores is performed by each GPU unit. The execution of the different functions within this system is allocated among four levels: disease management, pest recognition and control, output operations, and input functions. The data is analyzed concurrently and managed in a proficient and regulated manner. The proposed system demonstrates a significant enhancement in performance measures, with a value of 99.05%.

A Robust Initialization of Residual Blocks for Effective ResNet Training Without Batch Normalization.

Batch normalization is an essential component of all state-of-the-art neural networks architectures. However, since it introduces many practical issues, much recent research has been devoted to designing normalization-free architectures. In this brief, we show that weights initialization is key to train ResNet-like normalization-free networks. In particular, we propose a slight modification to the summation operation of a block output to the skip-connection branch, so that the whole network is correctly initialized. We show that this modified architecture achieves competitive results on CIFAR-10, CIFAR-100 and ImageNet without further regularization nor algorithmic modifications.

Unlocking the structure and cation synergistic modulation of Prussian blue analogues with double redox mechanism for improved aqueous nonmetallic ion storage.

Prussian blue analogs (PBAs) exhibit high energy density and a good electrochemical stability window in aqueous non-metallic ion batteries, which is conducive to achieving high energy output and stable operation. Additionally, their synthesis process is simple and environmentally friendly, meeting the demands of sustainable development. However, the poor conductivity, structural stability issues, and inadequate ion diffusion pathways limit their application in batteries. To overcome these challenges, researchers have adopted various optimization strategies: enhancing the conductivity of PBAs by compositing with high-conductivity carbon materials such as graphite, carbon nanotubes, or graphene; optimizing synthesis conditions such as temperature and reaction time to improve the defect and structural water content of PBAs, thereby enhancing their stability and electrochemical performance; employing surface modification techniques, such as conductive polymer encapsulation and acid etching, to improve their electrochemical stability and ion transport performance; and optimizing ion diffusion efficiency and battery kinetics by selecting suitable electrolytes and additives. These comprehensive measures contribute to improving the electrochemical performance of PBAs and promoting the development of their commercial applications. Based on prior research advancements, we introduce a novel synergistic regulation strategy: the creation of multi-redox-active centers to augment the transport capability of non-metallic ions and the optimization of defect structures through the establishment of a metal ion concentration gradient, thereby enhancing both electrochemical stability and performance.

State-of-Charge Balancing Control for Dual-Bus Battery System with Low-Voltage Output Regulation

This article introduces a new method for balancing the state of charge (SOC) in a dual-bus battery system architecture. The system consists of multiple battery cells or modules connected in series to provide high voltage output. Additionally, low-power flyback converters are connected in series with each battery cell or module at the inputs, and their outputs are connected in parallel to provide lower voltage output. The SOC balancing algorithm ensures that the lower voltage output remains at a desired reference value by adjusting the average duty cycle of each power converter, while also balancing the rate of charge or discharge of each battery cell or module. This SOC balancing process does not affect the normal operation of the high voltage power output. In other words, the dual output (high voltage and low voltage) of the battery system can function independently, and the balancing current only flows through the low voltage power path. Experimental results from a prototype are provided and discussed to validate the proposed dual-bus battery system and controller.

A segmented‐region optimum EPS modulation scheme based on unified parameter algorithm in DAB‐based EV charger circuit

AbstractDue to galvanic isolation, bidirectional power transmission and extensive voltage adjustment, dual active bridge (DAB) exerts significant interface between renewable sources and electric vehicle (EV) storage port. However, for DAB operations, under light load or high voltage gain conditions, minimization of root‐mean‐square (RMS) current (MRMS) causes a restricted soft‐switching range. With variations of output power and operation modes, maintenance for all switches ZVS operation is difficult to maintain. Therefore, here, a segmented‐region optimum modulation (SROM) scheme based on extended‐phase‐shift (EPS) control is proposed to solve the aforementioned problems and solve complicated coupled relationship among different optimization methods. Firstly, based on voltage gain and transmission power, all EPS modes are divided clearly. Then, for switching loss reduction, fully‐power‐range ZVS (FZVS) is realized through transitions among EPS modes. Thirdly, either all semiconductors ZVS or not, most suitable optimization method is selected for different EPS regions by SROM. Further, to establish accurate boundaries among these optimization methods, relationship between inner phase‐shift ratio D1 and outer phase‐shift ratio D2 are quantified by unified parameter algorithm with unified parameter m. Therefore, for any EPS modes, efficiency is promoted comprehensively. A DAB‐based prototype is established and experimental results verify correctness and effectiveness of proposed method.