Array System Research Articles

Research on the strategy for average consensus control of flywheel energy storage array system based on lifecycle

In the domain of clean energy, the flywheel energy storage array system (FESAS) is widely employed for efficient and renewable energy storage to stabilize power grids and smooth power variations. However, managing the lifecycle of FESAS and achieving coordinated control presents a considerable challenge. This study integrates a lifecycle parameter based on the average consensus algorithm, enabling flywheels with longer lifecycles to handle additional charging and discharging tasks, while those with shorter lifecycles participate less. This approach effectively balances flywheel lifecycles and extends the overall lifespan of FESAS. Experimental findings reveal that when the P matrix satisfies the condition of equal row sums or column sums, the power distribution parameters tend toward average consensus, enabling FESAS to efficiently smooth unbalanced power. In undirected graphs, the symmetry of the P matrix causes the auxiliary variables to tend toward average consensus, effectively suppressing unbalanced power. For directed unbalanced graphs, this study proposes Error Balancing Iterative Algorithm (EBTA) to construct a doubly stochastic matrix P, facilitating the convergence of auxiliary variables to average consensus and effectively suppressing unbalanced power. The experimental results validate the efficacy of our proposed approach. This research establishes a theoretical foundation for the intelligent coordinated control of FESAS, highlighting the pivotal role of lifecycle parameters, and offers valuable insights for enhancing the performance and lifespan of FESAS.

A Corrugated Edged Tapered Slot Antenna with Low Cross-Polarization and Moderate Gain for Phased Array Systems

ABSTRACT This paper presents a miniaturized Vivaldi antenna with a scan volume of ± 30° designed for the 6–18 GHz tactical operational band, commonly employed in phased array systems and modern surveillance applications. The proposed antenna offers enhanced radiation characteristics, low cross polarization, broad beam width, and moderate gain. The design presented in this paper follows a step-by-step approach to achieve enhanced performance in terms of multi-octave bandwidth and compact size. Initially, a traditional Vivaldi antenna was designed and examined, with a modified feed structure. Subsequently, corrugated edges were inserted into the antenna, increasing its electrical length and resulting in good impedance matching, especially in the 6–10 GHz frequency band. A prototype model is fabricated and tested to validate its performance against the simulation results. The measured results demonstrate that the return loss (S11) remains below −10 dB across the operating frequency range, achieving a 50% bandwidth, with a gain of 3–7 dB, and improved co-cross polarization of −23 dB at 6 GHz and −26 dB at 18 GHz.

Enhancing efficiency in spaceborne phased array systems: MVDR algorithm and FPGA integration

Digital Beamforming (DBF) has garnered significant attention within the space community, driven by the heightened flexibility offered by satellites equipped with active antennas for diverse applications like spaceborne synthetic aperture radar (SAR) systems and communication services. This paper presents a comprehensive exploration encompassing analysis, design, and implementation of a Minimum Variance Distortionless Response (MVDR) algorithm tailored for application in a Digital Beamforming Receiver system. The described system leverages the capabilities of the high-speed Analog to Digital Converter (ADC) device EV12AQ600, space-qualified, and the high-performance FPGA XCKU085. These components are seamlessly integrated into the EV12AQ60X-ADX-EVM evaluation board, thoughtfully provided by Teledyne e2v Semiconductors. The design methodology outlined herein is driven by the overarching objective to minimize FPGA resource utilization and power consumption for spaceborne phased array systems. This objective is chiefly met through the implementation of a systolic array structure adept at processing both real and complex input samples. This innovative approach results in a substantial reduction in allocated resources compared to conventional architectures. Furthermore, the design incorporates the use of the CORDIC algorithm to compute the inverse of the correlation matrix, obviating the need for square root and division operations. This strategic utilization of algorithms enhances the system's efficiency in terms of resource utilization, computational load, and processing time. To validate the anticipated behavior of the adaptive beamforming system, various radio frequency (RF) input signals are applied to the system, which is physically instantiated on the EV12AQ60X-ADX-EVM evaluation board. The experimental results affirm the efficacy of the proposed design, underscoring its suitability for spaceborne applications.

Therapeutic Efficacy of Mexiletine for Long QT Syndrome Type 2: Evidence From Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes, Transgenic Rabbits, and Patients.

Despite major advances in the clinical management of long QT syndrome, some patients are not fully protected by beta-blocker therapy. Mexiletine is a well-known sodium channel blocker, with proven efficacy in patients with sodium channel-mediated long QT syndrome type 3. Our aim was to evaluate the efficacy of mexiletine in long QT syndrome type 2 (LQT2) using cardiomyocytes derived from patient-specific human induced pluripotent stem cells, a transgenic LQT2 rabbit model, and patients with LQT2. Heart rate-corrected field potential duration, a surrogate for QTc, was measured in human induced pluripotent stem cells from 2 patients with LQT2 (KCNH2-p.A561V, KCNH2-p.R366X) before and after mexiletine using a multiwell multi-electrode array system. Action potential duration at 90% repolarization (APD90) was evaluated in cardiomyocytes isolated from transgenic LQT2 rabbits (KCNH2-p.G628S) at baseline and after mexiletine application. Mexiletine was given to 96 patients with LQT2. Patients were defined as responders in the presence of a QTc shortening ≥40 ms. Antiarrhythmic efficacy of mexiletine was evaluated by a Poisson regression model. After acute treatment with mexiletine, human induced pluripotent stem cells from both patients with LQT2 showed a significant shortening of heart rate-corrected field potential duration compared with dimethyl sulfoxide control. In cardiomyocytes isolated from LQT2 rabbits, acute mexiletine significantly shortened APD90 by 113 ms, indicating a strong mexiletine-mediated shortening across different LQT2 model systems. Mexiletine was given to 96 patients with LQT2 either chronically (n=60) or after the acute oral drug test (n=36): 65% of the patients taking mexiletine only chronically and 75% of the patients who performed the acute oral test were responders. There was a significant correlation between basal QTc and ∆QTc during the test (r= -0.8; P<0.001). The oral drug test correctly predicted long-term effect in 93% of the patients. Mexiletine reduced the mean yearly event rate from 0.10 (95% CI, 0.07-0.14) to 0.04 (95% CI, 0.02-0.08), with an incidence rate ratio of 0.40 (95% CI, 0.16-0.84), reflecting a 60% reduction in the event rate (P=0.01). Mexiletine significantly shortens cardiac repolarization in LQT2 human induced pluripotent stem cells, in the LQT2 rabbit model, and in the majority of patients with LQT2. Furthermore, mexiletine showed antiarrhythmic efficacy. Mexiletine should therefore be considered a valid therapeutic option to be added to conventional therapies in higher-risk patients with LQT2.

Utilizing deep learning towards real-time snow cover detection and energy loss estimation for solar modules

Conversion of solar energy using photovoltaic (PV) panels faces challenges due to snow accumulation on PV surface in cold regions. Despite existing methods to assess this impact, there remains a gap in real-time detection and accurate quantification of the energy loss. This study introduces a novel deep learning-based method for detecting snow coverage on PV panels for maximizing solar energy conversion. The model achieved a Dice score of 0.81 when trained on a diverse dataset of PV images, achieving a 44% improvement over conventional computer vision methods. Energy losses from snow on solar panels showed the model's predictions align closely with ground-truth data, achieving an error under 5% in snow coverage prediction. Six PV arrays were analyzed for energy loss estimation under varying snow coverage conditions. The analysis showed that the model could reliably predict energy losses due to snow accumulation with a mean error of 0.05 kWh/m2/month. The maximum energy loss was 0.23 kWh from a large PV array system covering 117 m2 area. Analysis of the impact of snow coverage duration on energy loss showed a saving potential of 0.13 kWh/m2 using timely clearing of snow coverage. This study highlights the effectiveness of CNN-based models in the early detection and measurement of snow coverage for improving the management and maintenance of PV systems.

A new wake superposition model and its application in collision prevention control of tri-riser array system

In the field of offshore oil exploitation, the compact multi-riser arrangement increases the risk of collision and has an adverse impact on production and the marine environment. The solution to this problem involves accurate motion prediction and collision prevention control under the effect of flow field superposition between risers, but there is little research on this related theory. This paper improves the traditional wake shielding effect model and further proposes a wake shielding superposition effect model for the mutual influence between risers, in order to establish a comprehensive accurate motion control model for tri-riser array system. A solution method is introduced for this model, both vibration and collision analysis are conducted for the system. The study revealed that solely augmenting the spacing inadequately mitigates system collisions, and active control is an inevitable choice. Based on this, this paper further designs an active boundary controller that is easy to implement in engineering, to achieve collaborative collision prevention control for three risers, and verifies its stability. Compared with traditional PD control, the proposed control method exhibits significant superiority, which can effectively reduce vibration amplitude, significantly increase dynamic spacing, and thus effectively prevent collisions between risers.

Exosomal Preconditioning of Human iPSC-Derived Cardiomyocytes Beneficially Alters Cardiac Electrophysiology and Micro RNA Expression.

Experimental evidence, both in vitro and in vivo, has indicated cardioprotective effects of extracellular vesicles (EVs) derived from various cell types, including induced pluripotent stem cell-derived cardiomyocytes. The biological effects of EV secretion, particularly in the context of ischemia and cardiac electrophysiology, remain to be fully explored. Therefore, the goal of this study was to unveil the effects of exosome (EXO)-mediated cell-cell signaling during hypoxia by employing a simulated preconditioning approach on human-induced pluripotent stem cell-derived cardiomyocytes (hIPSC-CMs). Electrophysiological activity of hIPSC-CMs was measured using a multielectrode array (MEA) system. A total of 16 h of hypoxic stress drastically increased the beat period. Moreover, hIPSC-CMs preconditioned with EXOs displayed significantly longer beat periods compared with non-treated cells after 16 h of hypoxia (+15.7%, p < 0.05). Furthermore, preconditioning with hypoxic EXOs resulted in faster excitation-contraction (EC) coupling compared with non-treated hIPSC-CMs after 16 h of hypoxia (-25.3%, p < 0.05). Additionally, microRNA (miR) sequencing and gene target prediction analysis of the non-treated and pre-conditioned hIPSC-CMs identified 10 differentially regulated miRs and 44 gene targets. These results shed light on the intricate involvement of miRs, emphasizing gene targets associated with cell survival, contraction, apoptosis, reactive oxygen species (ROS) regulation, and ion channel modulation. Overall, this study demonstrates that EXOs secreted by hIPSC-CM during hypoxia beneficially alter electrophysiological properties in recipient cells exposed to hypoxic stress, which could play a crucial role in the development of targeted interventions to improve outcomes in ischemic heart conditions.

A pragmatic data processing system for large resistive sensor arrays.

Large resistive sensor arrays (RSAs) show great potential in tactile perception. However, the large number of sensors can result in great hardware overhead and bring difficulties for acquiring and processing mass data timely in transient measurement applications. This paper implements a field programmable gate array (FPGA)-based data processing system for a large RSA of 96 × 96, which shows good power consumption and high-speed wireless data update. For crosstalk-free measure, the zero potential method is improved with bus switches, leading to fewer operational amplifiers required and less negative power consumption. A real-time embedded data processing system is realized by FPGA for excellent parallel processing ability. A high-speed wireless transfer scheme with automatic regulated transfer size is proposed and realized by a wireless fidelity module, which allows timely data analysis at the remote end. Moreover, fault identification of RSAs fabricated by micro-electromechanical system technology is achieved. Tests carried out on a 32 × 32 RSA show that the total power consumption is 2209 mW, including 1261 mW of processors and 948 mW of readout circuits, corresponding to 2.15 mW/pixel. The total negative power consumption of 549 mW has been reduced by 50% compared with the zero potential method. The scanning speed is 400fps, and the wireless transfer speed is up to 120fps when the transceiver and receiver are 5m apart.

28 GHz Compact LNAs With 1.9 dB Minimum NF Using Folded Three-Coil Transformer and Dual-Feedforward Techniques for Phased Array Systems

28 GHz Compact LNAs With 1.9 dB Minimum NF Using Folded Three-Coil Transformer and Dual-Feedforward Techniques for Phased Array Systems

Battery-Free, Wireless Multi-Modal Sensor, and Actuator Array System for Pressure Injury Prevention.

Simultaneous monitoring of critical parameters (e.g., pressure, shear, and temperature) at bony prominences is essential for the prevention of pressure injuries in a systematic manner. However, the development of wireless sensor array for accurate mapping of risk factors has been limited due to the challenges in the convergence of wireless technologies and wearable sensor arrays with a thin and small form factor. Herein, a battery-free, wireless, miniaturized multi-modal sensor array is introduced for continuous mapping of pressure, shear, and temperature at skin interfaces. The sensor array includes an integrated pressure and shear sensor consisting of 3D strain gauges and micromachined components. The mechanically decoupled design of the integrated sensor enables reliable data acquisition of pressure and shear at skin interfaces without the need for additional data processing. The sensor platform enables the analysis of interplay among localized pressure, shear, and temperature in response to changes in the patient's movement, posture, and bed inclination. The validation trials using a novel combination of wireless sensor arrays and customized pneumatic actuator demonstrate the efficacy of the platform in continuous monitoring and efficient redistribution of pressure and shear without repositioning, thereby improving the patient's quality of life.

Characteristic Study of a Typical Satellite Solar Panel under Mechanical Vibrations.

As the most common energy source of spacecraft, photovoltaic (PV) power generation has become one of the hottest research fields. During the on-orbit operation of spacecraft, the influence of various uncertain factors and the unbalanced inertial force will make the solar PV wing vibrate and degrade its performance. In this study, we investigated the influence of mechanical vibration on the output characteristics of PV array systems. Specifically, we focused on a three-segment solar panel commonly found on satellites, analyzing both its dynamic response and electrical output characteristics under mechanical vibration using numerical simulation software. The correctness of the simulation model was partly confirmed by experiments. The results showed that the maximum output power of the selected solar panel was reduced by 5.53% and its fill factor exhibited a decline from the original value of 0.8031 to 0.7587, provided that the external load applied on the panel increased to 10 N/m2, i.e., the vibration frequency and the maximal deflection angle were 0.3754 Hz and 74.9871°, respectively. These findings highlight a significant decrease in the overall energy conversion efficiency of the solar panel when operating under vibration conditions.

Miniaturized Sniffing Device based on an Array of Fluorescent Carbon Quantum Dots and Metallic Nanoclusters Efficiently Identifies Hematologic Malignancy in Adults.

The study demonstrates the potential of an optical nose made by depositing an array of fluorescent nanomaterials on a paper substrate for the early detection of leukemia in adults. This is based on the fact that blood volatile organic compounds (VOCs) are useful leukemia biomarkers. The integrated design was miniaturized and comprised both sensing zones and a sample holding zone, which were installed on a small sheet of paper within a miniature cubic reaction chamber fabricated by using 3D printing technology. The sensing device, comprising seven fluorescent sensing elements, namely, metal nanoclusters, quantum dots, and carbon dots was capable of detecting VOCs in the blood headspace and providing a colorimetric signature that could discriminate between blood samples from healthy and cancerous individuals. A total of 70 new leukemia cases and 51 healthy controls aged 20-50 years were studied. The device required a 60 μL portion of the blood sample and reacted to blood VOCs after 3 h when kept at 50 °C. The imaging data from the device was processed by linear discriminant analysis, and the results confirmed efficient identification of patient samples from healthy samples with 100% accuracy. Overall, the array system is noninvasive (or minimally invasive), portable, fast, inexpensive, and requires only a small amount of blood sample.

Microlens arrays for multichannel laser-to-waveguide coupling

An optical multichannel coupling system for coupling laser arrays to waveguide arrays is developed. Based on a microlens array, the system enables coupling of nine individual optical channels, with one aspheric microlens per channel at a lateral channel pitch of 100 µm. The design process criteria for the proposed microlenses, with 97 µm diameter and working distances from laser to lens and lens to waveguide of 150 µm and 275 µm, respectively, are described. The microlens array is fabricated on a 4mm×2mm×0.41mm fused silica chip and contains an orthogonal grid with 32×16 microlenses, of which a row of nine adjacent microlenses is used for coupling. Uniform coupling over all channels can be achieved, as well as specific coupling for each channel individually with less than −13.5dB crosstalk. The coupling system is designed for optical neural stimulators.

A modified dispersed frequency and phase consensus algorithm based on differential evolution and credibility weighting matrix

In distributed antenna array systems, accurate synchronization of the frequency and phase of the transmission signals among subarrays is a premise for beamforming. To solve this problem, a modified dispersed frequency and phase consensus (MDFPC) algorithm, which is based on differential evolution (DE) and the credibility weighting matrix, is proposed in this paper. DE algorithm is adopted to optimize the mixing matrix of MDFPC algorithm, and the convergence speed of consensus algorithm can be improved. Moreover, Lanczos method is adopted to calculate the fitness of individuals during optimization, thus the computation amount of the eigenvalue decomposition of the large-scale, sparse and symmetric mixing matrix can be effectively reduced. In addition, the influence of the transmission distance between subarrays on the received Signal-to-Noise Ratio (SNR) is considered, and the credibility weighting matrix can be obtained. Then the contribution of low-credible frequency and phase messages to the iterative updated values can be decreased by the credibility weighting matrix, thus more accurate frequency and phase updated values can be obtained in each iteration. It is shown from simulation results that the proposed algorithm can further reduce the phase synchronization error by at least 8% and achieve at least 18% convergence speed improvement compared to dispersed frequency and phase consensus (DFPC) algorithm.

Leakage current suppression methods for single-phase photovoltaic inverters

Given the swift expansion of the worlds population and economy, the decline in environmental quality caused by global warming, frequent climate disasters, ecosystem damage, sea level rise and other problems makes the world energy structure is changing, which means many countries start to develop their new energy industry and technology in order to meet their growing demand for energy. Therefore, promoting the energy transformation and innovation has become a new focus, and photovoltaic (PV) power generation as a green energy source is the focus of attention. PV inverters are essential components of photovoltaic array systems since they are the principal equipment capable of converting the fluctuating DC voltage produced by solar panels into mains frequency alternating current. However, the leakage current problem appeared during its operation has become one of the most important focuses of electrical engineers in recent years. This paper takes three aspects which is topology, filter and modulation mode to discuss how to suppress common mode leakage current in inverters. This paper reviews the existing research results and looks forward to their future development trends, which provides a reference for the following research.

Genetic diversity and population structure of a modified three-way tomato hybrids for determining fruit size traits

The assessment of genetic diversity and genetic structure of crops has a vital impact on the plant breeding program, including the characterization, use and conservation of genetic material. The genetic diversity and genetic structure of a set of 94 F3 tomato hybrids were assessed with 25 polymorphic SNP markers of quantitative trait loci (QTLs) underlying fruit size in tomatoes using Sequenom Mass ARRAY system. A total of 50 alleles were amplified and the average polymorphic information content (PIC) was 0.2220. Nei's genetic distance ranged from 0 to 0.62. Therefore, single nucleotide sequence (SNP) markers detected a significantly high degree of polymorphism in tomato hybrids. Cluster analysis using the unweighted pair group method with arithmetic mean methods (UPMA) indicated that the tomato hybrids studied are grouped into four main groups, which is to some extent consistent with the size, shape and number of locules of the tomatoes studied. Analysis of population structure with SNP markers revealed three subpopulations. Association mapping using 25 SNP markers detected 9 markers with a significant association with mean fruit weight, fruit length, fruit diameter, number of locules, and fruit shape index. The nine markers detected in this study are recommended for the tomato fruit size improvement breeding program.

Malfunctioning conformal phased array: Radiation pattern recovery with particle swarm optimisation

AbstractThe electronic beam steering in conformal phased arrays is formed by exciting the multiple antennas with appropriate phase shifts. However, the malfunctioning of phase shifters connected to the central antenna elements in the conformal array distorts the radiation pattern of the array system severely as compared to edge elements resulting in the reduction of the array gain and increase in the side lobe levels. Here, the authors propose a non‐dominated sorting multi‐objective particle swarm optimisation (NS‐MOPSO) technique capable of recalculating the independent phases of working antenna elements in the array in such a manner as to correct the overall radiation pattern. To illustrate the radiation pattern's recovery capabilities of the optimisation technique in case of malfunctioning of any random phase shifter(s), a 1 x 7 microstrip patch antenna array operating at 2.45 GHz on a wedge‐shaped conformal structure was designed in CST simulator. To test, the radiation pattern's recovery capabilities of the NS‐MOPSO approach, phase shifters connected to the antenna elements in the array were made to malfunction. Then the optimisation algorithm recalculates the phases for individual antenna elements to achieve the desired corrected radiation pattern. The simulated and measured radiation pattern recovery results are in good agreement with each other.

Millimeter wave negative refractive index metamaterial antenna array

In this paper, a novel negative refractive index metamaterial (NIM) is developed and characterized. The proposed metamaterial exhibits negative effective permittivity (εeffe) and negative effective permeability (µeffe) at millimeter wave frequency of 28 GHz. This attractive feature is utilized to enhance the gain of a microstrip patch antenna (MPA). Two thin layers of 5 × 5 subwavelength unit cell array of NIM are placed above a single MPA to enhance the gain of the antenna. Each unit cell has an area of 3.4 × 3.4 mm2. A gain increase of 7.9 dBi has been observed when using the proposed NIM as a superstrate. Furthermore, the NIM array is placed over a 2 × 2 array of MPAs with four ports to demonstrate versatility of the metamaterial. The total size of the 2 × 2 antenna array system with N-MTM is about 61.1 × 34 × 16mm3 (5.71λ × 3.18λ × 1.5λ, where λ is the free-space wavelength at 28 GHz). The measurement result indicate that the maximum gain of the antenna array is 13.5dBi. A gain enhancement of 7.55 dB in E-Plane and 7.25 dB in H-Plane at the resonant frequency of 28 GHz is obtained. The proposed antenna structure is suitable for 5G millimeter wave communications, in particular, for possible implementation in future millimeter wave access points and cellular base stations.

A High-Performance and Ultra-Low-Power Accelerator Design for Advanced Deep Learning Algorithms on an FPGA

This article addresses the growing need in resource-constrained edge computing scenarios for energy-efficient convolutional neural network (CNN) accelerators on mobile Field-Programmable Gate Array (FPGA) systems. In particular, we concentrate on register transfer level (RTL) design flow optimization to improve programming speed and power efficiency. We present a re-configurable accelerator design optimized for CNN-based object-detection applications, especially suitable for mobile FPGA platforms like the Xilinx PYNQ-Z2. By not only optimizing the MAC module using Enhanced clock gating (ECG), the accelerator can also use low-power techniques such as Local explicit clock gating (LECG) and Local explicit clock enable (LECE) in memory modules to efficiently minimize data access and memory utilization. The evaluation using ResNet-20 trained on the CIFAR-10 dataset demonstrated significant improvements in power efficiency consumption (up to 22%) and performance. The findings highlight the importance of using different optimization techniques across multiple hardware modules to achieve better results in real-world applications.

Engineering human midbrain organoid microphysiological systems to model prenatal PFOS exposure

Perfluorooctane sulfonate (PFOS), a class of synthetic chemicals detected in various environmental compartments, has been associated with dysfunctions of the human central nervous system (CNS). However, the underlying neurotoxicology of PFOS exposure is largely understudied due to the lack of relevant human models. Here, we report bioengineered human midbrain organoid microphysiological systems (hMO-MPSs) to recapitulate the response of a fetal human brain to multiple concurrent PFOS exposure conditions. Each hMO-MPS consists of an hMO on a fully 3D printed holder device with a perfusable organoid adhesion layer for enhancing air-liquid interface culturing. Leveraging the unique, simply-fabricated holder devices, hMO-MPSs are scalable, easy to use, and compatible with conventional well-plates, and allow easy transfer onto a multiple-electrode array (MEA) system for plug-and-play measurement of neural activity. Interestingly, the neural activity of hMO-MPSs initially increased and subsequently decreased by exposure to a concentration range of 0, 30, 100, to 300 μM of PFOS. Furthermore, PFOS exposure impaired neural development and promoted neuroinflammation in the engineered hMO-MPSs. Along with PFOS, our platform is broadly applicable for studies toxicology of various other environmental pollutants.