Search Results (324)

Driven by the rapid advancement of Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) technologies, improving power quality and system stability during charging and discharging has become a research focus. To address this, this paper proposes a Model Predictive Control (MPC) strategy for Active Neutral-Point Voltage Balancing (ANPVB) in a single-phase three-level converter used in on-board V2G chargers. Traditional converters rely on passive balancing using redundant vectors, which cannot ensure neutral-point (NP) voltage stability under sudden load changes or frequent power fluctuations. To solve this issue, an auxiliary leg is introduced into the converter topology to actively regulate the NP voltage. The proposed method avoids complex algorithm design and weighting factor tuning, simplifying control implementation while improving voltage balancing and dynamic response. The results show that the proposed Model Predictive Current Control-based ANPVB (MPCC-ANPVB) and Model Predictive Direct Power Control-based ANPVB (MPDPC-ANPVB) strategies maintain the NP voltage within ±0.7 V, achieve accurate power tracking within 50 ms, and reduce the total harmonic distortion of current (THDi) to below 1.89%. The proposed strategies are tested in both V2G and G2V modes, confirming improved power quality, better voltage balance, and enhanced dynamic response. Full article

We propose a hybrid-integrated III–V-silicon optical-phased-array (OPA) based on passive alignment flip–chip bonding technology and provide new solutions for LiDAR. To achieve a large range of vertical beam steering in a hybrid-integrated OPA, a multi-lines OPA in a single chip is introduced. The system allows parallel hybrid integration of multiple dies onto a single wafer, achieving a multi-fold improvement in tuning efficiency. In order to increase the range of horizontal beam steering, we propose a half-wavelength pitch waveguide emitter with non-uniform width to reduce the crosstalk, which can remove the higher-order grating lobes in free space. In this work, we simulate OPA individually for four-lines and eight-lines. As a result, we simultaneously achieved a beam steering with nearly ±90° (horizontal) × 17.2° (vertical, when four-line OPA) or 39.6° (vertical, when eight-line OPA) field of view (FOV) and a high tuning efficiency with 1.13°/nm (when eight-line OPA). Full article

The dynamic control of vibrations in skyscrapers is a critical consideration in sustainable building design, particularly in response to environmental excitations such as wind impact or seismic activity. Effective vibration neutralisation plays a crucial role in providing the safety of high-rise buildings. This research introduces an innovative concept for an active vibration damper that operates based on fluid dynamic transport to adaptively alter a skyscraper’s natural frequency, thereby counteracting resonant vibrations. A distinctive feature of this system is an adjustable-length cable mechanism, allowing for the dynamic modification of the pendulum’s effective length in real time. The structure, based on cable length adjustment, enables the PTMD to precisely tune its natural frequency to variable excitation conditions, thereby improving damping during transient or resonance phenomena of the building’s dynamic behaviour. A comprehensive mathematical model based on Lagrangian mechanics outlines the governing equations for this system, capturing the interactions between pendulum motion, fluid flow, and the damping forces necessary to maintain stability. Simulation analyses examine the role of initial excitation frequency and variable damping coefficients, revealing critical insights into optimal damper performance under varied structural conditions. The findings indicate that the proposed pendulum damper effectively mitigates resonance risks, paving the way for sustainable skyscraper design through enhanced structural adaptability and resilience. This adaptive PTMD, featuring an adjustable-length cable, provides a solution for creating safe and energy-efficient skyscraper designs, aligning with sustainable architectural practices and advancing future trends in vibration management technology. The study presented in this article supports the development of modern skyscraper design, with a focus on dynamic vibration control for sustainability and structural safety. It combines advanced numerical modelling, data-driven control algorithms, and experimental validation. From a sustainability perspective, the proposed PTMD system reduces the need for oversized structural components by providing adaptive, efficient damping, thereby lowering material consumption and embedded carbon. Through dynamically retuning structural stiffness and mass, the proposed PTMD enhances resilience and energy efficiency in skyscrapers, lowers lifetime energy use associated with passive damping devices, and enhances occupant comfort. This aligns with global sustainability objectives and new-generation building standards. Full article

Defect engineering has recently emerged as a cutting-edge discipline for precise modulation of electronic structures in nanomaterials, shifting the paradigm in nanoscience from passive ‘inherent defect tolerance’ to proactive ‘defect-controlled design’. The deliberate introduction of defect—including vacancies, dopants, and interfaces—breaks the rigid symmetry of crystalline lattices, enabling new pathways for optimizing catalysis performance. This review systematically summarizes the mechanisms underlying defect-mediated electronic structure at active sites regulation, including (1) reconstruction of the electronic density of states, (2) tuning of coordination microenvironments, (3) charge transfer and localization effects, (4) spin-state and magnetic coupling modulation, and (5) dynamic defect and interface engineering. These mechanisms elucidate how defect-induced electronic restructuring governs catalytic activity and selectivity. We further assess advanced characterization techniques and computational methodologies for probing defects-induced electronic states, offering deeper mechanistic insights at atomic scales. Finally, we highlight recent breakthroughs in defect-engineered nanomaterials for catalytic applications, including hydrogen evolution reaction (HER), oxygen evolution reaction (OER) and beyond, while discussing existing challenges in scalability, defect stability, and structure–property causality. This review aims to provide actionable principles for the rational design of defects to tailor electronic structures toward next-generation energy technologies. Full article

We report a passively Q-switched self-Raman laser using a dual-end composite c-cut Nd:YVO₄ crystal, which generates switchable visible emissions at 533 nm, 560 nm, and 589 nm. A Cr⁴⁺:YAG/YAG composite crystal served the role of a saturable absorber to achieve passive Q-switching. An angle-tuned BBO crystal was used to achieve the frequency mixing between the first-tokes wave and the fundamental wave. At an incident pump power of 9.5 W, the maximum average output powers were 425 mW for the 589 nm yellow laser, 193 mW for the 560 nm lime laser, and 605 mW for the 533 nm green laser, with corresponding pulse widths of approximately 3.8, 3.6, and 35.1 ns, respectively. This result shows that a passive Q-switching operation with self-Raman crystals presents a promising approach for compact multi-wavelength pulse laser sources. Full article

The dynamic vibration absorber (DVA) based on delayed fractional PID (DFOPID) can achieve a more superior vibration suppression effect. However, the strong nonlinear characteristics of the system and the computational burden resulting from its high dimensionality make solving and optimizing more challenging. This paper presents a coupled model of DFOPID and DVA, exploring its parameter tuning mechanism and optimization problem. First, using the averaging method and Lyapunov stability theory, the amplitude-frequency equation and the stability condition of the steady-state solution of the primary system are derived. Numerical simulations validate the accuracy of the analytical result. Next, based on the mechanics of vibration, the approximate expressions of the controller under different differential conditions are calculated, and their equivalent action mechanisms are analyzed. Finally, by minimizing the maximum amplitude of the primary system as the objective function, the Particle Swarm Optimization (PSO) algorithm is applied to optimize the parameters of the passive DVA and the DVA models controlled by PID, FOPID, and DFOPID, successfully addressing the parameter optimization challenges posed by traditional fixed-point theory. The vibration reduction performance is compared across different loading environments. The results demonstrate that the model presented in this paper performs the best, exhibiting excellent vibration suppression and robustness. Full article

This paper presents a simulation-based investigation of passive frequency tunability in frequency-selective surfaces (FSSs) enabled by Moiré pattern interference. By overlapping two identical hexagonal FSS layers and introducing rotational misalignment between them, we demonstrate that the resulting Moiré patterns induce significant shifts in the resonance frequency without any external bias or active components. Using full-wave simulations in HFSS, we show that rotating the second layer from 0° to 30° can shift the resonant frequency from 4.4 GHz down to 1.2 GHz. This tunable behavior emerges solely from geometrical manipulation, offering a low-complexity alternative to active tuning methods that rely on varactors or micro-electromechanical systems (MEMSs). We discuss the theoretical basis for this tuning mechanism based on effective periodicity modulation via rotational interference and highlight potential applications in passive reconfigurable filters and refractive index sensors. The proposed approach provides a promising route for implementing tunable electromagnetic structures without compromising simplicity, power efficiency, or integration compatibility. Full article

The increasing demand for high-capacity, energy-efficient wireless networks poses significant challenges in maintaining spectral efficiency, minimizing interference, and ensuring sustainability. Traditional direct-link communication suffers from signal degradation due to path loss, multipath fading, and interference, limiting overall performance. To mitigate these challenges, this paper proposes a unified RIS framework that integrates passive and active Reconfigurable Intelligent Surfaces (RISs) for enhanced communication and ambient RF energy harvesting. Our methodology optimizes RIS-assisted beamforming using successive convex approximation (SCA) and adaptive phase shift tuning, maximizing desired signal reception while reducing interference. Passive RIS efficiently reflects signals without external power, whereas active RIS employs amplification-assisted reflection for superior performance. Evaluations using realistic urban macrocell and mmWave channel models reveal that, compared to direct links, passive RIS boosts SNR from 3.0 dB to 7.1 dB, and throughput from 2.6 Gbps to 4.6 Gbps, while active RIS further enhances the SNR to 10.0 dB and throughput to 6.8 Gbps. Energy efficiency increases from 0.44 to 0.67 (passive) and 0.82 (active), with latency reduced from 80 ms to 35 ms. These performance metrics validate the proposed approach and highlight its potential applications in urban 5G networks, IoT systems, high-mobility scenarios, and other next-generation wireless environments. Full article

This study presents a novel approach to passive human counting in indoor environments using Bluetooth Low Energy (BLE) signals and deep learning. The motivation behind this research is the need for non-intrusive, privacy-preserving occupancy monitoring in sensitive indoor settings, where traditional camera-based solutions may be unsuitable. Our method leverages the deformations that BLE signals undergo when interacting with the human body, enabling occupant detection and counting without requiring wearable devices or visual tracking. We evaluated three deep neural network models—Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and a hybrid CNN+LSTM architecture—under both classification and regression settings. Experimental results indicate that the hybrid CNN+LSTM model outperforms the others in terms of accuracy and mean absolute error. Notably, in the regression setup, the model can generalize to occupancy values not present in the fine-tuning dataset, requiring only a few minutes of calibration data to adapt to a new environment. We believe that this approach offers a valuable solution for real-time people counting in critical environments such as laboratories, clinics, or hospitals, where preserving privacy may limit the use of camera-based systems. Overall, our method demonstrates high adaptability and robustness, making it suitable for practical deployment in diverse indoor scenarios. Full article

The present work reports the evaluation of a sliding mode observer (SMO) for a passive interferometric fiber-optic gyroscope (IFOG). To achieve that, the experimental setup was designed and evaluated to provide two out-of-phase signals as required by the SMO system employed. This led to the operation of the IFOG-SMO implemented in a passive mode with a 3 × 3 optical fiber directional coupler, which dismissed the use of optical phase modulators, such as piezoelectric or electro-optic devices. Simulations were performed and provided a qualitative analysis of the dependence of the system gain as a function of the sigmoid factor and sample rate, which resulted in a method for tuning the gain value according to the expected input signal. The experimental results show proper working of the IFOG-SMO and the capability for measuring large and small amplitude angular velocities and the expansion of the full scale. This is, to the best of our knowledge, the first time a sliding mode control technique has been employed and evaluated for an interferometric fiber-optic gyroscope. Full article

In this paper, we present a novel passive dual-tuned magnetic metasurface, which can enhance the field distribution produced by a closely placed radio-frequency coil for both ¹H and ²³Na 1.5 T MRI imaging. In particular, the proposed solution comprises a 5 × 5 capacitively loaded array, in which each unit-cell is composed of two concentric spiral coils. Specifically, the unit-cell internal spiral coil operates at the proton Larmor frequency (64 MHz), whereas the external is at the sodium one (17 MHz). Therefore, the paper aims to demonstrate the possibility of enhancing the magnetic field distribution in transmission and reception for 1.5 T MRI scanners by using the same metasurface configuration for imaging both nuclei, thus drastically simplifying the required instrumentation. We first describe the theoretical model used to design and synthetize the dual-tuned magnetic metasurface. Next, full-wave simulations are carried out to validate the approach. Finally, we report the experimental results acquired by testing the fabricated prototype at the workbench, observing a good agreement with the theoretical design and the numerical simulations. In particular, the metasurface increases the transmission efficiency T_x in presence of a biological phantom by a factor 3.5 at 17 MHz and by a factor 5 at 64 MHz, respectively. The proposed solution can pave the way for MRI multi-nuclei diagnostic technique with better images quality, simultaneously reducing the scanning time, the invasiveness on the patient and the overall costs. Full article

All-perovskite tandem solar cells (APTSCs) offer a promising pathway to surpassing the efficiency limits of single-junction photovoltaics. The wide-bandgap (WBG) subcell, serving as the top absorber, plays a critical role in optimizing light harvesting and charge extraction in tandem architectures. This review comprehensively summarizes recent advancements in WBG subcells, focusing on material design, defect passivation strategies, and interfacial engineering to address challenges such as phase instability, halide segregation, and voltage losses. Key innovations, including compositional tuning, additive engineering, and charge transport layer optimization, are critically analyzed for their contributions to efficiency and stability enhancement. Despite significant progress, challenges remain regarding scalability, long-term stability under illumination, and cost-effective fabrication. Future research directions include the development of lead-reduced perovskites, machine learning-guided material discovery, and scalable deposition techniques. This review provides insights into advancing WBG subcells toward high-efficiency, stable, and eco-friendly APTSCs for next-generation solar energy applications. Full article

In the current work, two novel tandem-based tuned mass damper configurations are introduced. These configurations extend the recently proposed tuned tandem mass damper inerter (TTMDI) by replacing the linking dashpot with an inerter (i.e., the inerter-connected TTMDI (ICTTMDI)), and an integrated tuned tandem mass damper inerter (I-TTMDI) by integrating recently proposed tuned tandem mass damper (TTMD) configurations. The control efficiency of the optimally designed dampers for a single-degree-of-freedom (SDOF) system was evaluated in a uniform framework to reveal and compare the performances of the ICTTMDI and I-TTMDI with those of other recently proposed tandem-based configurations. The optimum design of all the studied configurations was determined by the particle swarm optimization (PSO) algorithm. The evaluation of the performances included the effectiveness in the frequency domain and that of the norm and maximum reduction in the displacement and absolute acceleration in the time domain under 21 earthquake records with different characteristics. Additionally, the strokes of the dampers, the structure energies, and the power spectral densities (PSDs) of the responses were investigated. The optimum design of the I-TTMDI revealed the best configuration by determining the optimum distributions of the mass and inertance between the tandem mass and inerter links, respectively. The proposed configuration not only demonstrated improved response reduction across the displacement and acceleration measures but also maintained remarkable robustness under 21 earthquake records (far-fault, near-fault forward-directivity, and fling-step records). Furthermore, the advantages of the side inerter distribution were particularly effective at widening the operating frequency band, breaking through the traditional limitations of TMD-based devices. The consistent performances of the newly proposed configurations prove that they can be used to advance the development of more reliable structural control systems. Full article

In the contemporary field of wireless sensing, passive sensing leveraging channel state information (CSI) has found widespread applications across diverse scenarios, including behavior recognition, keystroke recognition, breath detection, and indoor localization. To ensure optimal sensing performance, wireless devices often collect a substantial number of CSI packets. However, when these packets need to be transmitted to a server or the cloud for time series analysis, the transmission load on the passive sensing system escalates rapidly, thereby impeding the system’s real-time performance. To address this challenge, we introduce the KCS algorithm, a novel compressed sensing (CS) algorithm grounded in K-Singular Value Decomposition (KSVD). The primary objective of the KCS algorithm is to enable the efficient transmission of CSI data. Departing from the use of a universal sparse matrix in traditional CS, the KCS algorithm constructs an overcomplete sparse matrix. This construction not only substantially bolsters the sparse representation capacity but also fine-tunes the compression performance. By doing so, it ensures the secure and efficient transmission of data. We applied the KCS algorithm to human behavior recognition and prediction. The experimental outcomes reveal that even when the volume of CSI data is reduced by 90%, the system still attains an average accuracy of 90%. This showcases the effectiveness of the KCS algorithm in balancing data compression and recognition performance, offering a promising solution for realistic applications where efficient data transmission and accurate sensing are crucial. Full article

This paper presents a numerical study on the structural vibrations of a TLP-supported NREL 5MW wind turbine equipped with a tuned vibration absorber (TVA) in the nacelle. The analysis was focused on tower bending deflections and was conducted using a reference OpenFAST V3.5.3 dedicated wind turbine modelling software and a finite element simulation framework based on Comsol Multiphysics V6.3 which was newly developed for this study. The obtained four-degree-of-freedom (4-DOF) tower bending model was transferred using modal decomposition to the MATLAB/Simulink R2020b environment, where a 2-DOF TLP surge/sway model and a bidirectional (2-DOF) TVA model were embedded. The wind field was approximated by a Weibull distribution of velocities (8.86 m/s mean, 4.63 m/s standard deviation). It was combined with the wave actions simulated using a Bretschneider spectrum with a significant height of 2.5 m and a peak period of 8.1 s. The TVA model used was either the standard NREL reference 20-ton passive TVA, a 10-ton passive, or a 10-ton controlled TVA (the latter two tuned to the tower’s first bending mode). The controlled TVA utilised a magnetorheological (MR) damper, either operating independently (forming a semi-active MR-TVA) or simultaneously with a force actuator, forming, in this case, a hybrid H-MR-TVA. Both aligned and 45°/90° misaligned wind–wave excitations were examined to investigate the performance of a 10-ton real-time controlled (H-)MR-TVA operating with less working space. In aligned conditions, the semi-active and hybrid MR-TVA solutions demonstrated superior tower vibration mitigation, reducing maximum tower deflections by 11.2% compared to the reference TVA and by 14.9% with regard to the structure without TVA. The reduction in root-mean-square deflection reached up to 4.2%/2.9%, respectively, for the critical along-the-waves direction, while the TVA stroke reduction reached 18.6%. For misaligned excitations, the tower deflection was reduced by 4.3%/4.8% concerning the reference 20-ton TVA, while the stroke was reduced by 22.2%/34.4% (for 45°/90° misalignment, respectively). It is concluded that the implementation of the 10-ton real-time controlled (H-)MR-TVA is a promising alternative to the reference 20-ton passive TVA regarding tower deflection minimisation and TVA stroke reduction for the critical along-the-waves direction. The current research results may be used to design a full-scale semi-active or hybrid TVA system serving a TLP-supported floating offshore wind turbine structure. Full article