Search Results (335)

Whether hydrogen should be delivered by pipeline or by truck is a large and largely irreversible investment decision. The cost information needed for this decision varies by a factor of several across the literature, and conventional single-value comparisons can reverse their conclusions depending on which value is selected. This study introduces a risk classification framework from construction management to define cost uncertainty as probability distributions grounded in the literature and in Korean empirical records. Four delivery modes were compared, specifically new pipelines, repurposed pipelines, high-pressure tube trailers, and liquefied hydrogen tanker trucks. Their twenty-year total costs were computed by Monte Carlo simulation with 20,000 draws for each combination of transport distance (10–500 km) and annual demand (1000–1,000,000 t/yr). The results are summarized as robustness maps that display only the mode with the lowest cost in at least 80% of the 20,000 cost scenarios. The synthesized cost distributions are consistent with the Korean cost records available for comparison, one of which was reserved from the model inputs. Where a repurposable pipeline exists, repurposing is effectively the only robust choice. In new corridors, new pipelines become robustly justified from 19,191 t/yr at the reference distance of 150 km, below which lies a gray band where assumptions decide the outcome. The viability of liquefied hydrogen delivery is determined not by technology but by who bears the liquefaction plant cost, and this boundary alone raises the share of the map on which liquefied hydrogen delivery is robust from 1% to 72.4%. The effective levers that advance the transition to pipelines are the operation and maintenance (O&M) rate (45.8%), the planning horizon (38.3%), and demand commitment (23.2%) rather than the carbon price (2.2%). Four announced Korean plans are located on the map in positions consistent with their project stages, which indicates that the framework can serve as a planning-stage diagnostic tool. Full article

A hybrid pumped-storage power station (hereinafter referred to as the “hybrid station”) is developed by installing reversible pump–turbine units between cascade reservoirs, providing both conventional hydropower regulation and cross-seasonal energy storage capability. However, existing studies have mainly focused on its short-term peak-shaving function, while the potential of cross-seasonal water resource allocation remains insufficiently explored. This paper develops a medium-to-long-term cross-seasonal optimal dispatch model considering the seasonal regulation characteristics of hybrid pumped-storage stations, with the objective of minimizing residual-load variance. Seasonal reservoir storage rate-of-change constraints are introduced to represent the operation mechanism of storing water during wet seasons and releasing water during dry seasons. A Variable-Phase Progressive Optimality Algorithm (VPPOA) is proposed to solve the model. Three operation modes, including no hybrid storage, hybrid daily regulation, and hybrid seasonal regulation, are established for comprehensive evaluation under different hydrological conditions, renewable outputs, load variations, and algorithm performances. The results show that the proposed model achieves an annual cross-seasonal energy transfer of 848.8 GWh. Compared with the no-hybrid-storage scheme, the hybrid seasonal regulation scheme reduces the residual-load variance by 77.3%, increases the wind–PV accommodation rate from 40.3% to 96.6%, and decreases the wet-season wind–PV curtailment rate from 38.8% to 3.9%. Compared with the hybrid daily regulation scheme, it further reduces the residual-load variance by 26.1%, improves the wind–PV accommodation rate by 9.2 percentage points, and increases dry-season supply reliability from 93.2% to 100%. Moreover, VPPOA outperforms GA, PSO, and conventional POA, achieving a lower residual-load variance of 2861.05 MW². The results demonstrate that the cross-seasonal regulation capability of hybrid pumped-storage stations can effectively enhance renewable energy accommodation and power supply reliability, providing support for the flexible operation of new-type power systems. Full article

Power conversion systems (PCSs) connect dc energy sources to the grid, but background grid-voltage disturbances can degrade grid-current quality. This paper presents a unified derivation and implementation-oriented assessment of proportional grid-voltage feedforward in the abc, αβ, and dq reference frames for an LCL-filtered three-level PCS. The derived disturbance transfer function retains the feedforward term, and attenuation is quantified at the fundamental and selected harmonics. Tests cover gain tuning and voltage harmonics, 10% voltage unbalance, 49–51 Hz operation, SCRs from 10 to 2, ±20% LCL-parameter variation, a 25–50 kW reference ramp, common-mode voltage, and a sixth-harmonic resonant benchmark. With Kff = 0.6, grid-current THD falls from 10.65% to 7.19% in the strong-grid harmonic test; the resonant benchmark reaches 7.05%. At SCR = 3, retuned resonant control gives 20.33% THD versus 11.68% for proportional feedforward, while transferring the strong-grid resonant gain gives 123.02%. The delay-inclusive loop model retains positive stability margins, whereas the switching-model results reveal that the benefit of a fixed feedforward gain is condition-dependent and may diminish or reverse under clean-grid, frequency-deviation, parameter-variation, and weak-grid conditions. Archived 100 kVA waveforms verify stable implementation in all three reference frames. The results clarify the operating conditions under which proportional feedforward is effective, together with its digital implementation requirements and limitations. Full article

We propose a gold-graphene-vanadium dioxide (VO₂) hybrid metasurface capable of reversibly switching among three operational modes in the terahertz regime. The device achieves flexible polarization control by combining the insulator-to-metal phase transition of VO₂ with the electrical tunability of graphene. Simulation results reveal three distinct behaviors depending on the biasing conditions of the materials. With graphene held at a chemical potential of 0 eV and VO₂ in the insulating state, the metasurface acts as a linear-to-linear polarization converter. The polarization conversion ratio (PCR) exceeds 0.9 over the frequency range from 5.5 to 8.6 THz. When the graphene chemical potential is raised to 0.9 eV while VO₂ remains insulating, the metasurface switches to linear-to-circular conversion. Notably, the handedness of the outgoing wave depends on the polarization of the incoming signal. Over the 6.45–8.36 THz band, the axial ratio (AR) remains below 3 dB. A third functional state emerges when VO₂ switches to its metallic phase. In this state, the device simply operates as a broadband co-polarized reflector, covering the terahertz communication band from 0.1 to 10 THz. This switchable, multifunctional behavior should prove useful for terahertz communications, polarization imaging, and sensing applications. Full article

Reversible Solid Oxide Cells (rSOCs) are highly efficient energy conversion systems for power generation in fuel cell mode (SOFC) and energy storage in electrolysis mode (SOEC). These devices are typically manufactured through multi-step processing routes based on conventional functional ceramic fabrication techniques, such as tape-casting, extrusion, screen-printing and spraying. In this work, an alternative mold-casting approach is proposed for the fabrication of planar electrolyte-supported rSOCs. Electrolytes made of 8 mol% yttria-stabilized zirconia (YSZ) were prepared via an aqueous gel-casting process using agarose as the gelling agent. The casting molds were fabricated by 3D printing with polylactic acid (PLA) filament. Dense electrolytes with well-controlled geometries were successfully obtained. Complete cells were produced using porous Ni–YSZ as a fuel electrode and porous lanthanum strontium manganite–YSZ. The cells were microstructurally characterized, and their electrochemical performance was evaluated under both SOFC and SOEC operating conditions at 800–900 °C. At 900 °C, the cell achieved a peak power density of 220 mW cm⁻² in fuel cell mode and an injected current density of 340 mA cm⁻² at 1.3 V in electrolysis mode. Mid-term galvanostatic testing in SOFC mode at 850 °C for 400 h demonstrated good durability and structural stability of the fabricated cells. After the initial stabilization period, the cell exhibited a low degradation rate of 3 mV kh⁻¹. Full article

In guided-wave stimulated Brillouin scattering (SBS), the opto-mechanical coupling strength is determined by the spatial overlap of optical and elastic fields, fundamentally constrained by symmetry. Conventional analyses based on ordinary point groups assume that fields share the waveguide’s symmetry, which is valid for standing-wave modes with zero longitudinal wavenumber. However, in waveguides with longitudinal-axis-reversing operations, such operations flip the wavenumber sign for traveling-wave modes, making the conventional framework insufficient—a limitation not addressed before. Here, we introduce the type-III Shubnikov (magnetic) point groups, combining time reversal with axis-reversing spatial operations, and establish a co-representation theory for such traveling-wave modes. We prove that these modes obey a conjugate symmetry derived from the antiunitary elements of the magnetic point group. From this, we derive a general selection rule for backward SBS: if the waveguide possesses only one nontrivial axis-reversing operation (and no other independent symmetry), the conjugate symmetry allows the coupling to be nonzero. Numerical validations on single-crystal lithium niobate, fused silica, and single-crystal silicon waveguides of a trapezoidal cross-section confirm the predicted conjugate symmetry and show that materials with lower intrinsic symmetry more favorably realize such symmetry-enabled backward SBS. This work represents a systematic introduction of magnetic group theory to nonmagnetic waveguides, offering new insights for material selection and coupling control in guided-wave SBS. Full article

Against the backdrop of the dual-carbon goals, a new power system is undergoing rapid construction, and distributed renewable energy is being connected at high density to regional ring networks. This study deeply explores the impact of photovoltaic (PV) power station connection positions on energy distribution and flow, as well as the voltage and energy loss of ring networks. Firstly, it takes the actual 220 kV/500 kV ring network in a certain city in Yunnan Province as the research object, and constructs a high-precision ETAP simulation model. It then systematically explores the mechanism of how PV power connection positions and grid connection penetration rates affect node voltage and line loss and derives the energy loss calculation formula. On this basis, two differentiated operation scenes corresponding to renewable energy output peaks and valleys are established. Through comparative analysis of multiple sets of simulation data, this study reveals the coupling laws among PV output fluctuation, bidirectional reverse power flow, system energy loss, and voltage over-limit. Finally, combined with the operational pain points of existing ring network and distribution network connection modes, this study proposes diversified loss reduction optimization strategies, including coordinated optimization of active and reactive power, and coordinated regulation of PV power and energy storage. The relevant research conclusions and optimization methods can improve the line loss analysis theory for ring networks integrated with PV power, and provide important engineering references for renewable energy planning and design, operation regulation, and loss management for similar mountain power grids. Full article

This paper explores methods to eliminate high-voltage spikes during dead time ($t_{dt}$) in high-frequency inverters for Wireless Power Transfer (WPT) systems, focusing on the transition from traditional Silicon IGBTs to enhancement-mode Gallium Nitride (GaN) HEMTs. At elevated switching frequencies, dead-time parameters strongly govern system efficiency and signal integrity. While IGBTs suffer from reverse-recovery charge ($Q_{rr}$) in antiparallel freewheeling diodes that generates severe voltage spikes, hard-switching GaN systems require precise dead-time minimization to prevent shoot-through while limiting third-quadrant conduction losses. Unlike prior WPT studies bounded by specific hardware setups, this paper presents a baseline technology benchmark that explicitly decouples intrinsic semiconductor commutation physics, specifically $Q_{rr}=0$ versus third-quadrant conduction, from macro-system parameters ($f_{sw}$, power level, and resonant topology). Experimental evaluation of a 130 kHz L-S-tuned GaN full-bridge inverter confirms that primary current commutates via third-quadrant conduction during dead time, completely eliminating reverse-recovery voltage spikes ($I_{rr}=0$). Ultimately, this work demonstrates that GaN’s spike-free operation is an intrinsic device-level property, reframing the dead-time optimization objective from transient overvoltage suppression to third-quadrant conduction loss minimization in next-generation WPT systems. Full article

Human societies depend on prestige hierarchies that confer status on demonstrated competence, alongside the dominance hierarchies that rely on coercion and that humans share with other primates. The same neural processes that support cooperative learning under prestige are hypothesized to participate in rivalry, polarization, and ideological hostility when their operating environments depart from those in which they evolved. This selective narrative review proposes a candidate integrative framework, the Hypothesized Neural Integration Model of Prestige and Pride, drawing on converging but largely indirect evidence from affective neuroscience, neuroeconomics, evolutionary psychology, and social neuroscience. The framework groups five categories of functionally pluripotent processing, each understood as engaging nodes within overlapping large-scale brain networks rather than as a localized regional mechanism: valuation-related processing implicating orbitofrontal and ventromedial prefrontal cortex, reward-learning signals indexed in the ventral striatum, self-referential and identity-relevant processing engaging medial prefrontal cortex within the default-mode network, threat- and salience-related processing involving the amygdala and anterior cingulate cortex within the salience network, and neuroendocrine output regulated through the hypothalamic–pituitary–adrenal axis and modulated by gonadal and neuropeptide systems. Consistent with Poldrack on reverse inference and with Marr on levels of analysis, the framework is presented at an integrative implementational level with candidate algorithmic mappings specified for each category, not as a computational specification of the constructs themselves, and treats high-level constructs such as prestige, status, and sacred value as emergent phenomena arising from dynamic network interactions, bodily states, cultural contexts, and historical contingencies rather than as properties localized to single regions. Because few neuroimaging paradigms isolate freely conferred deference from generic social rank, claims specific to prestige are deliberately restricted throughout, and the evidence base is presented as one concerning social rank unless a paradigm operationalizes prestige directly. Material ownership, sacred values, religious belief, and digital prestige metrics are treated as candidate domains of application, with explicit separation of direct neural evidence, behavioral evidence, and theoretical extrapolation. Symbolic escalation in consumer markets, sacred-value absolutism, and amplified social feedback on digital platforms are interpreted as candidate environmental amplifiers of ancestral status mechanisms rather than demonstrated causal pathways. Nine operational study designs are proposed to guide future preregistered tests, including one designed to establish whether a prestige-specific neural claim can be made at all. Intervention strategies are mapped to candidate processing and network targets using an explicit evidence-grading scheme, with structural and institutional measures weighted equally alongside cognitive and contemplative ones. The framework relies on correlational neuroimaging subject to reverse-inference constraints, draws primarily from samples from Western, educated, industrialized, rich, and democratic populations, and should be evaluated as a hypothesis-generating account rather than as a confirmed neural architecture. Full article

Directed inter-UAV Time-Differenced Carrier Phase (TDCP) couples an inter-node distance increment with a relative clock-bias increment, while phase differencing produces temporally correlated noise and near-planar formations retain a weak relative-height mode. We formulate a fixed-lag factor graph that combines reciprocal TDCP, Time-of-Arrival (TOA), Global Positioning System (GPS), clock dynamics, and calibrated navigation-frontend motion and altitude outputs. An invertible sum-and-difference transformation exposes geometry and clock-bias-increment-rate channels while full covariance propagation preserves the reciprocal-pair likelihood. Local information analysis shows that the reverse observation removes the single-direction geometry–clock-increment rank deficiency, and phase-level modeling yields the first-order moving-average covariance retained by block whitening. A causal motion-consistency test (MCT) compares the whitened geometry channel with an independent motion prediction before the current pair enters optimization; a flagged pair is assigned negligible information and its detector–estimator phase arc is reset. Implementation checks verify the exact four-bias-state residual, covariance-normalized reciprocal innovations, and operation under sparse single-direction ambiguity changes. Across ten paired runs at $p_s=5\%$, MCT detected all 770 injected events with a pair-level false-alarm rate of 0.169% and reduced the mean position RMSE by 96.6% relative to DCS. Full article

Cell inconsistency constrains the usable capacity, operational safety, and service life of large-scale battery energy storage systems. Most online methods infer inconsistency from voltage, current, or temperature; in parallel branches, however, self-balancing currents redistribute the operating current and can obscure its external signatures. This paper proposes a mode-adaptive assessment method based on circulating-current impedance. Circuit analysis reveals how open-circuit-voltage and resistance differences reverse the circulating-current direction among discharge, idle, and charge. The signed branch response is combined with each cell voltage to form a topology-conditioned cell-level quasi-impedance, which is mapped to a 0–100 consistency score by mode-specific rules. In controlled 6P3S experiments, the predefined resistance-disturbed cells received the two lowest scores in both same-cluster and cross-cluster scenarios; on the same 18-cell records, a baseline-corrected peak-temperature-rise feature did not place either disturbed pair among the two highest-ranked cells. Update times remained at the millisecond level for both 18- and 1200-cell configurations. A field application produced 17.328 million valid cell–window evaluations and persistent cluster-level screening patterns. These results support a physically interpretable and computationally lightweight approach to topology-conditioned cell inconsistency screening. Because independent fault labels were unavailable, the field evidence establishes operational scalability rather than diagnostic accuracy. Full article

This paper presents a modular embedded edge-AI teaching platform built around the STM32N6 microcontroller, designed to meet demand for low-power, real-time, deployable edge intelligence in engineering education. The platform uses a heterogeneous architecture combining an ARM Cortex-M55 core with a dedicated Neural-ART NPU, enabling efficient on-device inference for both classroom projects and vision-based competition tasks. To improve stability across multi-peripheral setups, a multi-power-domain supply architecture combines switched-mode power supplies with low-noise LDO regulators, plus dual-input power switching, reverse-current and reverse-polarity protection, overcurrent limiting, and soft-start control. High-speed modular peripherals are integrated on board—MIPI-CSI camera input, RGB display output, high-speed NOR Flash, and SPI, I2C, UART, and TIMER expansion interfaces—with an 80-pin board-to-board connector for flexible extension. A four-layer PCB layout improves signal integrity for reliable high-speed operation. Deploying a custom lightweight vision algorithm (PEPoseNet), the prototype achieves an inference-only latency of 18.4 ms and 28.31 FPS/Watt energy efficiency within a sub-3 W power budget. These results confirm the platform’s reliability as an educational training platform for embedded edge-AI computing. Full article

During load rejection in pumped-storage power stations, the rotational speed of the pump-turbine increases abruptly. The consequent structural deterioration of the internal flow induces high-amplitude hydraulic excitations, posing a serious threat to the operational stability of the unit. This study investigates a Francis pump-turbine to elucidate its flow evolution and instability mechanisms during load rejection. The fluid is modeled as weakly compressible water to capture finite pressure wave propagation. Dynamic mesh simulates guide vane closure, while vortex identification and short-time Fourier transform analyze transient pressure pulsations. The results indicate that the transient process can be sequentially divided into four typical stages—turbine mode, turbine-braking mode, reverse-pump mode, and return-to-turbine mode—to account for the most critical periods during the load rejection transient. The unit exhibits the poorest stability near the maximum rotational speed (443.34 r/min), where flow reversal and the full development of vortex structures significantly amplify fluctuations in hydraulic thrust. The vaneless space is identified as the primary source of pressure pulsations, whose characteristics are dominated by rotor–stator interaction mechanisms, and such disturbances decay rapidly in the downstream direction. Under turbine-braking and reverse-pump conditions, vortex rings, backflow, and asymmetric vortex structures generated within the spiral casing collectively contribute to the severe deterioration of the internal flow field quality. Full article

The high penetration of sustainable energy integration leads to severe source-side uncertainty challenges in power system dispatch, and two-stage robust optimization is a critical tool for addressing this issue. However, traditional solution methods suffer from significant iterative computational bottlenecks and fail to meet the timeliness requirements of real-time grid dispatch. Therefore, this paper proposes a data-model hybrid-driven fast solution method for two-stage robust optimization. First, the method abandons the traditional iterative solution mode and directly identifies the worst-case scenarios within the uncertainty set based on a conditional diffusion model, which transforms the two-stage robust optimization into a single-stage deterministic optimization. Then, it constructs a physics-guided conditional diffusion model and proposes a worst-case scenario physics-guided operator to apply directional adversarial guidance during the reverse denoising stage to approach the worst-case operational boundary. Finally, by establishing a sensitivity allocation model for global active power imbalance, it reformulates the non-differentiable risk constraints in the gradient operator into efficient algebraic matrix operations. Experimental results show that the proposed method accurately generates worst-case scenarios and reduces the computation time to approximately 20% of the original while ensuring near-optimal economy, which provides a new solution paradigm for balancing decision robustness and timeliness. Full article

Amphibious robots must reconcile two distinct mechanical requirements within a compact locomotion architecture. Terrestrial operation requires limb structures with sufficient load-bearing capacity, contact stability, and bending resistance, whereas aquatic operation benefits from a larger projected area for drag-based thrust generation. Conventional amphibious platforms often address these requirements by combining separate land and water propulsion modules, which increases structural redundancy, system mass, and hydrodynamic resistance. To reduce this conflict at the structural level, this study proposes a bioinspired origami morphing limb based on a modified Yoshimura pattern. The limb transforms between a closed cylindrical configuration for terrestrial support and an unfolded planar configuration for aquatic paddling. A vertex-splitting topology and thick-panel geometric constraints are introduced to suppress the bifurcation instability associated with the zero-thickness Yoshimura vertex, thereby obtaining a deterministic single-degree-of-freedom folding path suitable for robotic actuation. A screw-theory-based kinematic model is established to relate the active driving angle to the passive folding angle, and geometric parameter analysis is used to connect the folding state with load-bearing and paddling morphologies. A quadruped amphibious robot prototype is fabricated using rigid polylactic acid panels and flexible thermoplastic polyurethane hinges. Prototype-level observations qualitatively demonstrate reversible transformation within the tested operating range and show walking, crawling, rolling, water-entry, and underwater locomotion modes. Full article