Search Results (160)

In recent years, the rapid evolution of large artificial intelligence (AI) models has placed unprecedented demands on the computing power of data center servers, driving an explosive growth in data center computing requirements. The power consumption of core computing components, represented by GPUs, has surged dramatically. When facing extremely high power densities, the traditional 12 V single-voltage power delivery architecture exposes severe limitations, including increased transmission link losses, thermal management difficulties, and low system efficiency. To address these challenges, this paper proposes and designs a hierarchical 54 V/12 V dual-plane multi-phase DC power delivery architecture for high-computing-power AI servers. By conducting refined hierarchical identification of system loads, this architecture introduces a 54 V high-voltage DC power plane for high-power loads while retaining the 12 V power plane for conventional loads. Within each power plane, multi-phase interleaved parallel Buck converters integrated with Turbo-COT control strategies and high-density DrMOS are deployed. Experimental results demonstrate that this power architecture exhibits excellent electrical characteristics: under steady-state conditions, the peak-to-peak (PK-PK) ripple voltage fluctuation amplitude of the 54 V power plane under different loads is compressed to between ±0.22% and ±0.26%, while the PK-PK ripple voltage fluctuation amplitude of the 12V power plane under different loads reaches ±0.66% to ±0.68%; in dynamic load step (0–50% and 50–100%) tests, the PK-PK voltage fluctuations of the 54 V plane are ±1.42% and ±1.33%, whereas the PK-PK voltage fluctuations of the 12 V power plane are ±2.36% and ±1.83%. Furthermore, the peak conversion efficiency of the 54 V power plane approaches 97%, and the maximum efficiency of the 12 V power plane reaches 94%, showing a measurable efficiency improvement under the tested conditions. The hierarchical multi-phase power delivery technology comprehensively reduces power supply link losses and enhances power stability, providing an important theoretical basis and engineering reference for the design of next-generation high-density AI servers and the optimization of green, energy-saving networks in data centers. Full article

This paper presents an energy-recovering active snubber in which the energy captured by the snubber capacitor is transferred back to the converter’s input using an auxiliary inverting switching stage. The snubber operates independently of the main power stage and can therefore be applied to a wide range of isolated converter topologies without modifying their primary control or structure. The proposed snubber achieves an energy-recovery efficiency of approximately 80%, thereby reducing snubber-related losses by the same proportion. As a representative implementation, the concept was experimentally validated in a 550 W dual-phase interleaved DC–DC flyback converter, where it improves the overall converter efficiency by 1.6 percentage points and reduces total losses by 18% compared with a dissipative snubber solution. The proposed snubber supports a wide input-voltage range and is well suited for multiphase converters, as most of its components can be shared between phases. Full article

DC microgrids are important platforms for renewable energy integration, energy storage interaction, and bidirectional power exchange. In these systems, multi-phase interleaved parallel DC-DC converters are widely used as key energy-router interfaces, but open-circuit faults in power devices may lead to current imbalance, waveform distortion, ripple redistribution, and system instability. To improve fault warning and diagnosis under variable operating conditions, this paper proposes a time–frequency dual-branch efficient fully convolutional network (EPFCN). The proposed model takes synchronized multi-channel voltage/current signals and their FFT-domain representations as complementary inputs. The time-domain branch extracts transient waveform features, while the FFT-domain branch captures spectral variation and harmonic-related information. An efficient channel attention (ECA) module is introduced to enhance fault-sensitive channel responses while maintaining a lightweight structure. An RT-LAB hardware-in-the-loop platform is established to construct a multi-condition diagnostic dataset covering one normal state and nine fault states. Experimental results show that the proposed EPFCN achieves high diagnostic accuracy, strong noise robustness, clear feature separability, and feasible edge-side inference performance. The proposed method provides an effective data-driven solution for online fault warning and diagnosis of multi-phase interleaved converters in DC microgrids. Full article

This paper presents a five-phase, two-switch buck-boost (5P-TSBB) converter rated at 75 kW, intended for photovoltaic and energy storage applications that require a wide operating voltage range. The proposed system operates with photovoltaic input voltages ranging from 250 V to 1000 V and regulates the DC-link voltage between 600 V and 950 V. The converter supports two distinct operating modes: an independent multi-input mode for multiple independent input sources and an interleaved mode for a single high-power input. The feasible operating area of the converter is determined in the V_in–V_out plane, taking into account voltage, current, and power limitations. Simulation results and experimental investigations on a laboratory prototype, including measurements of efficiency and power losses, support the theoretical considerations. Full article

Wound-rotor synchronous machines (WRSMs) offer a promising, magnet-free alternative for safety-critical transportation sectors like electric vehicles (EVs) and marine propulsion. While multiphase structures enhance fault tolerance in these applications, conventional WRSMs still suffer from reliance on maintenance-prone slip rings and brushes. Brushless multiphase self-excitation presents a compelling solution, but it introduces a critical design challenge: ensuring decoupled control between the torque-producing (αβ) and magnetizing ($xy$) subspaces to prevent severe performance degradation. To address this cross-coupling issue, this paper proposes a 20-slot/18-pole five-phase architecture. By exploiting distinct spatial harmonics, the stator generates two independently controlled magnetic fields with a dedicated rotor harmonic winding. An integrated diode rectifier then seamlessly converts the induced AC voltages into the required DC field excitation. Extensive finite-element analysis (FEA) using ANSYS Maxwell is conducted to validate the design and rigorously evaluate subspace cross-coupling. Simulation results confirm that the proposed machine meets design specifications, demonstrating stable self-excited operation, acceptable efficiency, and representative fault-tolerant operation under a single open-phase condition, thereby confirming the electromagnetic feasibility of the proposed topology as a promising magnet-free candidate for future alternatives to PMSM-based traction solutions. Full article

With the expansion of modern protected agriculture, the amount of post-harvest tomato biomass has increased sharply. Conventional unmanaged disposal practices disrupt carbon flows and cause substantial environmental emissions. Tomato plant residues (TPRs), which are rich in lignocellulose and selected high-value secondary metabolites, have considerable potential as feedstocks for green industrial materials. However, their complex biophysical properties, high physiological moisture content, and recalcitrant cell-wall barriers hinder large-scale processing. This review systematically examines the mechanisms and process architectures for converting TPRs into macromolecular products. First, it analyzes cross-scale anatomical heterogeneity and dynamic rheological properties of TPRs, defining their physicochemical boundaries as industrial precursors. Second, it summarizes the development of physical field-coupled equipment, ranging from anti-tangling harvest-shredding to die-roller densification. Furthermore, it examines the core mechanisms of multi-field-coupled pretreatment technologies, including steam explosion, deep eutectic solvents (DES), and mechanochemistry, in deconstructing vascular skeletons and reducing multiphase mass-transfer resistance. Finally, this review discusses reconstruction pathways for TPR-derived components in advanced polymer materials, including biodegradable nanocellulose films, bio-based composites, aerogels, and lignin-based polyurethane networks. Overall, it links microscopic reaction kinetics with macroscopic equipment engineering, proposes a closed-loop material conversion system from in-field volume reduction to cascaded biorefinery, and provides an engineering framework for future multi-machine intelligent collaboration and continuous production across the industrial chain. Full article

Intelligent completion technologies, including Inflow Control Valves (ICVs), have become increasingly important for remotely managing zonal production in complex well architectures. However, quantifying flow rates and phase fractions in such systems remains challenging due to space constraints and the harsh downhole environment, which limit the deployment of conventional sensors. Distributed Acoustic Sensing (DAS) provides a promising solution by converting standard fiber-optic cables into dense arrays of acoustic sensors. While DAS has been successfully applied in applications such as integrity monitoring and leak detection, its use for direct two-phase flow characterization within intelligent completions remains largely unexplored. In this study, we present a DAS-based methodology to monitor and analyze oil–water two-phase flow in horizontal experiments that mimic field conditions. Acoustic data collected from DAS are transformed into time–frequency spectrograms using Short-Time Fourier Transform (STFT) to extract dynamic spectral features. These features are then correlated with pressure drop across the ICV and flow rate, revealing distinct frequency band behaviors associated with fluid changes. To quantify flow characteristics, a power-law model is trained using spectral features to predict flow rate and phase fractions. The results demonstrate strong predictive capability for pressure drop and flow rate under controlled laboratory conditions, highlighting the potential of DAS for multiphase flow diagnostics in field applications with intelligent completions, while water cut prediction remains challenging due to the complex and non-unique relationship between flow conditions and DAS response and is left for future work. This research not only provides new insights into the acoustic response of oil–water flows but also introduces a data-driven framework for leveraging DAS in real-time flow monitoring and control within ICV-equipped completions. Full article

Sulfate roasting is a critical pyrometallurgical pre-treatment for extracting Cu and Co from low-grade Cu–Co–Fe sulfide ores, yet conventional phase diagrams provide limited quantitative guidance for process control. To address this gap, a multicomponent/multiphase thermodynamic equilibrium model based on Gibbs free energy minimization was developed to systematically investigate the oxidative roasting behavior of single sulfides (Cu₂S, CoS₂, FeS₂) and their ternary mixture, with respect to air supply, temperature, and total pressure. The model reveals that each sulfide follows distinct, temperature-dependent phase transformation pathways: Cu₂S forms the acid-leachable product CuO·CuSO₄ at temperatures ≤ 588 °C with a stoichiometric air supply of 11.9 mol, transitioning to oxides at ≥800 °C; CoS₂ converts completely to CoSO₄ below 727 °C and to CoO at higher temperatures; FeS₂ yields sulfate phases at low temperatures and iron oxides above 654 °C. In the ternary Cu₂S–CoS₂–FeS₂ system, competitive oxidation reactions produce refractory mixed oxides (CuO·Fe₂O₃, CoO·Fe₂O₃) whose formation is governed by temperature, air supply, and sulfide molar ratios. The results demonstrate that low-temperature roasting (≤641 °C) with precisely controlled air supply maximizes the formation of water-soluble sulfates, providing a quantitative thermodynamic basis for process optimization and enhanced recovery of Cu and Co from complex sulfide ores. Full article

Future More-Electric and All-Electric Aircraft (MEA/AEA) require electric power systems (EPS) with higher installed power, improved reliability, and reduced complexity, motivating a fundamental reshape of the architecture and key system-level design choices. This paper applies a structured design process to future DC-based EPS and derives justified decisions from a comprehensive assessment of state-of-the-art research. Among three possible topologies, the bipolar three-wire DC grid is selected as the preferred architecture due to its superior corona suppression, insulation behavior, electromagnetic compatibility, safety, and reliability. A voltage-level study shows that increasing the low-voltage bus from 28 V to 48 V yields the most significant wiring-weight reduction (∼20%), while increasing the high-voltage level from 800 V to 1200 V offers only marginal benefits and introduces additional insulation and partial-discharge challenges. For power conversion, both isolated and non-isolated DC/DC converters are required: non-isolated multiphase interleaved converters are suited for smaller subnetworks, whereas isolated dual active bridge converters are foreseen for inter-grid power exchange. Midpoint grounding via a resistor is identified as a robust baseline concept that ensures fault detectability and operational continuity while providing controlled fault currents and limited voltage deviations, with the final resistance value to be refined based on the finalized grid configuration. The study focuses on architecture-level assessment and does not include dynamic simulations or experimental validation, which are identified as areas for future work. Full article

Growing municipal solid wastes, environmental deterioration, and the world’s increasing energy demand highlight the urgent need for effective, sustainable energy recovery solutions. Uncontrolled municipal solid wastes contribute explicitly to the global crises of climate change, pollution, and biodiversity loss. Food and organic waste are converted into value-added products using biochemical and thermochemical techniques. Anaerobic digestion (AD) is a versatile, multi-phase waste-to-energy technology that transforms organic waste into renewable energy in an oxygen-free environment. AD uses microorganisms to break down waste, yielding biogas (mostly methane and carbon dioxide) and digestate, a nutrient-fortified by-product. Compared with traditional Single-Stage Anaerobic Digesters (SSAD), Two-Stage Anaerobic Digesters (TSAD) offer notable benefits by separating hydrolysis–acidogenesis from acetogenesis–methanogenesis. These include increased methane yield, improved process control, increased microbial stability, and resistance to inhibitory substances. According to the literature, TSAD systems have been shown to increase methane yield by about 10–30% compared to SSAD. This article covers the dynamics of the microbial population at various stages, the impact of operational factors (HRT, OLR, pH, and temperature), and novel reactor designs with modular and multi-state functions. In line with Oman’s Vision 2040, this study discusses the continuous operation of a two-phase AD co-digestion process and the in-depth techno-economic feasibility of decentralized waste management through optimized biogas production. Optimizing the carbon-to-nitrogen (C/N) ratio within the range of 20–30 in co-digestion systems significantly enhances microbial activity and methane production. The potential of recent developments, such as microbial immobilization, biogas generation techniques, and hybrid integration with photobioreactors or electrochemical systems, to enhance the scalability and efficiency of bioconversion is addressed in a TSAD system. In addition to encouraging circular economy principles through efficient organic waste valorization, this review identifies TSAD as a promising approach to achieving the SDGs related to sustainable cities, clean energy, and responsible consumption. Full article

This paper proposes a low weight hybrid battery–supercapacitor energy storage system interfaced with bidirectional DC/DC converters with high power/current capability for aircraft applications. The supercapacitor converter having high power uses two pairs of interleaved coupled inductors to reduce the overall current ripple whilst increasing the converter’s power density. Due to the sensitive performance to saturation of the coupled inductors, a phase current balancing strategy is proposed to counter the effect current imbalance in the channels that would cause saturation degrading overall performance. A power management strategy (PMS) is implemented along with a low pass filter to separate the supercapacitor high frequency power component reference from the battery low frequency power component; therefore, separating the energy and power requirement for the energy storage system contributing to minimizing its weight whilst ensuring the current/power stresses are correctly handled. The validity of the system design is validated by a series of transient tests is conducted both in a simulation model as well as experimentally. Full article

This paper presents a quadruple step-down (QSD) trans-inductor voltage regulator (TLVR) converter to accommodate the high-current and fast-transient requirements of processor power supplies. Evolved from dual-step-down (DSD) topology, the QSD configuration offers stronger load capacity; three additional flying capacitors are introduced between adjacent phases to break the 25% duty cycle constraint, thereby extending the output voltage range and accelerating the transient response. Moreover, the converter’s transient response is optimized to its full potential through both multi-phase simultaneous operation and the incorporation of the dedicated TLVR architecture. A modified adaptive on-time (AOT) controller supporting four-phase simultaneous operation is employed. Designed and verified via post-layout simulation in a 180 nm BCD process with all 6 V power transistors, the converter achieves a peak efficiency of 96.1% at 24 V input and 3 V output, as well as a maximum load capacity of 20 A. Under a 19 A load current step with a 19 ns rise time, it exhibits only a 37 mV output voltage droop and a 2 μs settling time, even with a 100 μF output capacitor. Full article

This paper presents a dual-phase dual-path hybrid buck–boost (DPBB) converter with an offset-controlled zero-current detector for Li-ion battery applications. Compared with inductive buck–boost converters, the proposed hybrid converter has a continuous input current, reducing the input voltage (V_IN) ripple, which is caused by the parasitic inductance of the bonding wire. The proposed switching operation of the DPBB topology shows a low inductor current ripple with the continuous output delivery current; therefore, the ripple of the output voltage (V_OUT) is reduced with the efficiency improvement. Compared with the prior hybrid buck–boost converters, it supports the buck and boost modes only by adjusting the duty cycle, so this addresses the issues of mode transitions. The proposed work utilizes the dual-phase operation to lower the conduction loss and improve the dynamic range. The proposed offset-controlled zero-current detector compensates for the timing error owing to the propagation delay of the control signals to reduce the reverse current from the output. The chip is fabricated using a 180-nm BCD process. It regulates V_OUT at 3.3 V with a wide V_IN range of 2.8 V to 4.2 V. Peak efficiencies of 95.88% and 93.08% are achieved in the buck and boost modes, respectively, with 140 mΩ of inductor DC resistance. Full article

Methane hydrate formation in multiphase transportation pipelines represents a critical challenge to flow assurance under low-temperature conditions. Gaining insight into the kinetic effects of crude oil on hydrate formation aids in developing countermeasures for mixed oil–gas transportation. For this purpose, experiments were carried out at 50 vol% to 90 vol% water cut and pressure of 6.0–7.5 MPa under crude oil–methane–water systems. Results demonstrate that crude oil has kinetic inhibition on hydrate formation, which is caused by mass transfer resistance in emulsion gels. The gas consumption increased by 81.38% when the water cut increased from 60 vol% to 70 vol%. Tween-80 converts crude oil W/O emulsions into O/W emulsions. The addition of Tween-80 to a 50 vol% water cut system resulted in only a 10.04% increase in gas consumption compared to the 90% water cut condition. The results indicate that Tween-80 significantly promotes the formation of hydrates. Furthermore, analysis of gas consumption reveals that the O/W system is more conducive to hydrate growth than the W/O system. Observations through the viewing window revealed that lowering the temperature and hydrates synergistically disrupt the stability of the emulsion. This is caused by the phase transition of wax and asphaltene in crude oil. These findings provide insights for developing flow assurance strategies in crude oil multiphase transportation pipeline operations. Full article

Background/Objectives: To investigate and develop a non-invasive parametric radiomics model derived from dynamic contrast-enhanced MRI (DCE-MRI) time-intensity curve (TIC) kinetics for predicting breast cancer molecular subtypes (HR+/HER2−, HER2+ and triple-negative breast cancer). Methods: This multicenter retrospective study enrolled 935 female patients with histologically confirmed breast cancer who underwent pretreatment breast DCE-MRI from August 2017 to July 2022. Based on the wash-in rate (WIR) and the area under the TIC, the original multiphase DCE-MRI images were converted into two types of parametric images. Radiomics features were extracted from TIC-WIR and TIC-Area images and analyzed using low variance filtering, the elimination of highly correlated features, and the least absolute shrinkage and selection operator regression. The categorical boosting algorithm was employed to develop multiclass prediction models for breast cancer molecular subtyping. A TIC-Combined model was further established by integrating the calibrated probability outputs of the TIC-WIR and TIC-Area models using a decision-level fusion strategy. The discrimination, calibration, and interpretability of the models were evaluated in the study datasets. Results: The TIC-Combined model achieved superior predictive performance in both the internal validation set (micro-average AUC: 0.79, macro-average AUC: 0.77) and the external validation set (micro-average AUC: 0.77, macro-average AUC: 0.75). For subtype-specific classification by the TIC-Combined model, the highest one-vs-rest AUCs were 0.81 for triple-negative breast cancer in the internal validation set and 0.76 for HER2+ breast cancer in the external validation set. The TIC-Combined model also showed good calibration and high interpretability which ensured reliable predictions and provided clear insights into feature importance. Conclusions: Interpretable parametric radiomics from TIC-derived parametric maps links kinetic features to molecular phenotypes, enabling accurate and non-invasive classification of breast cancer molecular subtypes. Full article