Search Results (7,964)

This paper investigates maximum power point operation in a large-scale offshore wind energy conversion system equipped with a permanent magnet synchronous generator (PMSG). The study focuses on a 15 MW reference offshore wind turbine and aims to determine the operating conditions required for maximum energy extraction under variable wind speeds. Mathematical models of the wind turbine and the generator are developed using selected parameters derived from the International Energy Agency (IEA) 15 MW Reference Wind Turbine, while the operating characteristics are represented by a simplified analytical model. Based on these models, the turbine and generator power characteristics are derived and the equivalent generator load resistance values corresponding to maximum power point operation are determined. Dynamic simulations are performed for several wind speed profiles to evaluate the evolution of the operating point and the associated stability properties. The analysis reveal two equivalent resistance solutions, with the higher value providing stable operation under wind-speed variations and the lower value defining a potentially unstable operating branch. Furthermore, an energy-based control strategy is proposed to compensate for the influence of the large mechanical inertia and to improve maximum power point tracking performance. The proposed model represents a generic 15 MW offshore wind energy conversion system and focuses on the variable-speed operating region and its associated energetic dynamics. The proposed methodology provides a practical framework for energy-based control and stability assessment of next-generation offshore wind turbines rated above 15 MW. Full article

Menyuan, China, experienced a Mw 6.7 earthquake on 8 January 2022. This study combines GNSS and InSAR data to analyze how fault activity affects earthquake hazard assessment through fault inversion. A time-dependent version of DEFNODE (TDEFNODE) is developed to calculate fault locking and slip deficit through GNSS data and Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR)-processed Sentinel-1A data. The findings reveal that Haiyuan Fault is strongly locked before the earthquake, with a locking depth of around 30 km and a slip deficit rate between 3.1 mm/yr and 5.6 mm/yr. Meanwhile, the cumulative seismic moments correspond to moment magnitudes ranging from Mw 6.49 to Mw 6.75, which are highly consistent with the actual Menyuan earthquake. This indicates that fault locking and slip deficit provide a reference for quantitatively assessing the characteristics of pre-seismic activity. Although the seismic moments derived from different datasets vary from 6.10 × 10¹⁸ to 1.50 × 10¹⁹ N·m, the key parameters determined by TDEFNODE inversion are generally consistent with the actual focal mechanisms. Therefore, results show that a comprehensive analysis of fault inversion can provide important insights into the formation process of earthquakes and help assess regional earthquake risk. Full article

Cocoa (Theobroma cacao L.) postharvest quality can be compromised by fungal colonization across the farm-to-chocolate continuum, motivating non-chemical control options that can be engineered as unit operations. This study evaluates microwave (MW) irradiation (2.45 GHz) as a physical disinfestation process against Fusarium solani (F. solani). Experiments were conducted under a completely randomized design (CRD) by tuning MW power (140–210 W) and exposure time to reach predefined surface-temperature bands verified by infrared (IR) thermography. Post-treatment viability was assessed by incubation (27 °C, 7–10 days) and classified as Reduced Growth Rate (RGR; sublethal regrowth slower than control) or Death (D; no regrowth comparable to autoclaved negative controls). Outcomes were temperature-governed: RGR predominated in sublethal bands (60–80 °C), whereas consistent D occurred once surface temperature exceeded 80 °C. Thermodynamic modeling established a median lethal temperature ($L{T}_{50}$) of $81.0^{\circ }C$, and a 99% eradication threshold ($L{T}_{99}$) of $87.2^{\circ }C$. Maximizing the heating rate ($H_r$) to 0.381 ${}^{\circ }$C/s at 210 W ensured rapid and profound cellular suppression. Scanning electron microscopy (SEM) corroborated severe ultrastructural damage (collapsed macroconidia and disrupted hyphae) under lethal conditions, and turbidimetric monitoring over 120 h showed sustained growth suppression in treated samples. These findings define a practical lethal threshold and power–time windows to inform MW scale-up as a postharvest unit operation while minimizing thermal residence time. Full article

Archived distribution studies are difficult to reuse when source calculations, public asset records, processed outputs, and proprietary model files support different levels of inference. This study develops a claim-specific audit for incomplete distribution network archives. Three evidence gates distinguish documentary consistency, asset attribution, and decision-specific adequacy; four archive stages separate preservation and integrity documentation from executable import and numerical reproduction. The method was applied to three retained operating points of a 13.8 kV feeder in Ambato, Ecuador. Eight roofs associated in the worksheet with T54 (code 21076) yielded 205.364 kWp from 1506 m² under the retained sizing assumptions. A public EEASA GIS record corroborated the code, 125 kVA rating, and 13.8/0.22 kV nominal voltages, while the physical-to-model correspondence remained unverified. In the maximum-PV state labeled 1.5825 MWp, the archived feeder-head export was 0.670 MW, and the archived T54 loading metric was 156.915%, triggering a nameplate-based review without establishing thermal overload. Only T54 satisfied the four-element documentary attribution rule; model execution and numerical reproduction were not tested. This contribution is a domain-specific synthesis of established provenance and reproducibility principles that makes claim boundaries explicit. It remains a single-case demonstration, without empirical evidence of improved analyst agreement or decision quality. Full article

Tension Leg Platform (TLP)-type Floating Offshore Wind Turbines (FOWTs) rely on continuously pre-tensioned mooring tendons, the integrity of which must be monitored to ensure safe operation. However, direct measurement of tendon tension at submerged locations is difficult in practice. This study investigates a virtual sensing approach in which the effective tension at multiple tendon points—fairlead, middle, and anchor—of a 15 MW TLP-type FOWT is estimated from responses measured at or near the free surface. Three deep learning architectures are comparatively evaluated: a Transformer-encoder-based self-attention network (EN-ATT), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). Fully coupled time-domain simulations are used to generate the training and test data, and the models are assessed under both nominal and noisy input conditions across multiple noise levels. The EN-ATT achieves the highest accuracy in terms of RMSE, MAE, and the coefficient of determination under both nominal and noisy conditions. Feature gradient analysis indicates that the self-attention model exhibits greater sensitivity to longer input lags than the recurrent networks. While the EN-ATT does not consistently outperform the recurrent networks for extreme values, the results suggest that self-attention architectures are a promising direction for mooring tension monitoring of TLP-type FOWTs. Full article

When a virtual power plant (VPP) participates in energy and reserve markets, day-ahead bids, reserve commitments, and real-time delivery share the same internal resource constraints, while aggregate models cannot readily trace internal responsibility allocation or identify local shortfalls. This study develops a fixed-responsibility partitioning framework for day-ahead bidding and real-time delivery. Fixed membership mappings are screened under a unified budget; resource-type-specific reserve certificates and sustained-delivery constraints are embedded in a finite-support Wasserstein distributionally robust optimization (WDRO) model; and hierarchical model predictive control executes the market commitments. The 365-day evaluation retains three non-dominated candidates, $\mathrm{K}\in \{6,7,8\}$, whose mean operational-fitness objective values are reduced by 25.5%–43.1% relative to the corresponding independent spectral-clustering baselines. In a common 30-day ablation study, detailed partition responsibilities increase mean daily adjusted operating profit by CNY 6442–8162 and reduce settlement deviation by 1.19–1.23 MW relative to two equivalent-responsibility rules. Here, adjusted operating profit is profit net of balancing-correction cost, settlement deviation is the schedule–settlement difference, and partition tracking error is the deviation between partition targets and aggregated resource response. The directions of these effects remain consistent across two independent 10-day windows, and hierarchical real-time coordination further reduces settlement deviation and partition tracking error. Public-aggregate-data replays show that the profit and deviation effects of WDRO relative to sample average approximation (SAA) vary with market settings and node-downscaled inputs. As an engineering extension, bounded contracted-capability factors, defined as multipliers on market-committable capability, increase mean daily adjusted operating profit by 6.00% in the 2024 holdout set, and attribution analysis indicates that most of this gain is associated with the average contracted-capability factor and released fast-response headroom. Under the tested settings, fixed-responsibility partitioning enables the continuous transfer of resource-type-specific day-ahead responsibilities into real-time resource control and makes the trade-offs among profit, delivery quality, and execution cost explicit. Full article

The heat release rate (HRR) indicates the scale of a tunnel fire, and inverting it in real time from ceiling sensors supports fire detection and ventilation control. Purely data-driven (deep learning) models are accurate within the training range but cannot extrapolate to larger fires, whereas a purely physics-based formula is less accurate and fails during the fast-growth transient. This paper proposes a data and knowledge dual-driven HRR inversion method. The data component is an encoder-only Transformer on ceiling thermocouples, and the knowledge component is a slope-corrected plume-scaling inversion. The two are coupled by a training-time soft constraint and an inference-time two-layer gate: a magnitude gate raising the physics weight beyond the training power ceiling, and a steady-state gate down-weighting it during transients. On 24 simulated cases (six slopes × four powers, 0.5–4 MW), data are split by slope and power into mutually exclusive training, validation, and test subsets, the test covering unseen slopes and powers. The method outperforms the physics formula at every power tier; on power extrapolation it far surpasses the pure deep learning model (R² = 0.84), and on slope extrapolation it matches that model (R² = 0.94). The results demonstrate, within the present single-geometry FDS tunnel configuration and the investigated working conditions (0–5% slopes, 0.5–4 MW, t² growth, natural ventilation), that physics-guided gated fusion can improve HRR estimation under a 4 MW single-power extrapolation test while retaining the accuracy of the data-driven model under slope extrapolation; the conclusions are not claimed to be directly transferable to other tunnel configurations. Full article

Quantitative geomorphic analysis provides a valuable, cost-effective tool for evaluating relative tectonic activity across active rift zones and can support, but not by itself, seismic hazard assessment and infrastructure planning. This study evaluates the relative tectonic activity of the Asir Province, southwestern Saudi Arabia, a zone transitioning from the crystalline Arabian Shield to the Cenozoic Red Sea rift system. Using a 30 m Shuttle Radar Topography Mission (SRTM) digital elevation model, six geomorphic indices, a lithologically normalized stream length–gradient index, hypsometric integral, basin asymmetry, basin shape, the valley floor width-to-height ratio, and mountain front sinuosity, were combined into a composite Relative Active Tectonics Index (RTAI), an unweighted arithmetic mean classification of 63 sub-catchments into 4 relative activity classes. The findings reveal that 32% of the sub-catchments indicate high to very high relative tectonic activity, observed mainly along the high-terrain Sarawat mountain range and active rift cliffs. Raised stream length–gradient anomalies align with mapped NW-SE and NE-SW fault trends, and their spatial pattern correlates with the epicentral area of a May 2020 earthquake near Tandaha (Mw 3.45), presenting contextual support rather than independent validation, confirmation or support for the RTAI classification. The spatial distribution of the RTAI suggests modern morphotectonic rejuvenation and localized reactivation of Proterozoic structural features, including the Nabitah Fault Zone, which appeared due to Red Sea rifting events. These results indicate that the RTAI model is a valuable tool for assigning zones of relative tectonic activity, offering baseline geomorphic evidence that can effectively inform, though not substitute, for subsequent seismic hazard assessment, engineering infrastructure planning, and sustainable land-use management. Full article

Modern wind turbines require effective control strategies to maximize energy capture under partial-load conditions while maintaining generator-speed and power regulation above the rated wind speed. This study proposes and applies a controlled and reproducible benchmarking framework for evaluating classical Differential Evolution (DE) variants in the tuning of Proportional–Integral–Derivative (PID) and Proportional–Integral–Derivative–Accelerative (PIDA) controllers for a nonlinear model of the National Renewable Energy Laboratory 5-MW reference wind turbine. Twenty classical DE variants were assessed using a fixed-seed initialization strategy, unified simulation procedures, consistent objective-function definitions, and region-specific optimization settings applied uniformly to all variants within each operating region. The controllers were evaluated in Region 2, where maximum power point tracking is required, and Region 3, where generator speed and electrical power must be regulated under above-rated wind conditions. Their generalization performance was subsequently evaluated in simulation using a measured wind-speed profile obtained from a Supervisory Control and Data Acquisition system. In Region 2, under the considered fixed-seed configuration, the DE-tuned controller achieving the lowest objective-function value reduced the objective function by approximately 2.93% compared with the baseline PID controller, indicating a moderate improvement. In Region 3, the PIDA controller tuned with the DE variant yielding the lowest objective-function value achieved a reduction of up to 92% relative to the baseline controller, demonstrating a substantially greater benefit under above-rated operation. However, validation using the measured wind profile indicated that some controllers with favorable tuning-stage results showed signs of overfitting and reduced generalization performance. Overall, the results indicate that the suitability of the controller structure and DE configuration depends on the wind turbine operating region and highlight the importance of controlled, reproducible optimization procedures and validation beyond the tuning scenario in wind turbine controller design. Full article

Potato protein hydrolysates (PPHs) produced by ultrasound-assisted enzymatic hydrolysis exhibit strong antioxidant activity. However, their inherent bitterness limits their application in food sectors. Therefore, this research investigated the effects of energy-divergent ultrasound (EDU)- and energy-gathered ultrasound (EGU)-assisted enzymatic treatment and exogenous amino acids (alanine (Ala), phenylalanine (Phe), and valine (Val)) on the peptide structure, antioxidant activity, and instrumental taste profile of Maillard reaction products (MRPs) prepared from PPHs. It was found that EDU and EGU significantly promoted the progress of the Maillard reaction (MR). All MRPs presented remarkable changes in the peptide structure compared to their PPH counterparts. Under the equal-mass addition of exogenous amino acids, MRPs from EDU with Ala at 120 min (EDU-Ala-120) presented the highest percentage of molecular weight (MW) <2 kDa fractions (68.55%), and a markedly improved oxygen radical absorption capacity value of 108.44 µg Trolox equivalent (TE)/mL. MRPs from EDU revealed significantly stronger umami taste and lower bitterness, while MRPs from EGU exhibited stronger sweetness. The umami taste of the MRPs was strongly negatively correlated with bitterness (−0.9517, p < 0.001) and positively correlated with esters (0.7293, p < 0.01), whereas the sweetness of the MRPs was positively associated with specific volatile components but negatively correlated with <1 kDa peptides (−0.6039, p < 0.05). Thus, the EDU-assisted enzymatic treatment and MR with the addition of appropriate exogenous amino acids could be a prospective way to produce natural flavor with enhanced antioxidant activity. Full article

This paper presents a novel weight-regulated, dither-based hybrid dual-stage background calibration technique for interstage gain errors (IGEs) in pipelined analog-to-digital converters (ADCs). To evaluate IGEs, a 1-bit pseudorandom dither is first injected into the first three stages. The proposed algorithm then evaluates IGEs via correlation. The first stage employs a large fixed-step Least Mean Squares (LMS) algorithm to rapidly estimate the gain error. The second stage utilizes the first stage’s output to suppress fluctuations using a weighted error and refines the estimate through a rational-quadratic adaptive-variable-step (RQ-AVS) LMS method. The proposed technique was verified using a fabricated 1.5-GS/s 12-bit pipelined ADC prototype implemented in a 28-nm CMOS process and featuring a 5.9-GHz input bandwidth. Measurement results show that at a 745 MHz input, the signal-to-noise-and-distortion ratio (SNDR) and spurious-free dynamic range (SFDR) improve from 52.1 dB and 65.8 dBc to 58.9 dB and 74.3 dBc, respectively. During calibration, the algorithm converges within 0.12 million samples, reducing steady-state estimation variation from +10.93%/−12.51% to +1.29%/−2.13%. The ADC achieves +0.25/−0.24 LSB differential nonlinearity (DNL) and +0.80/−0.75 LSB integral nonlinearity (INL) with a power consumption of 102.4 mW. Full article

The adjoining parts of Northeast India represent one of the most seismically active regions of the Indian subcontinent. This region is classified as Zone V by the Indian Seismic Code, indicating maximum seismic hazard potential. This region has a history of several great earthquakes, including the 1897 Shillong and 1950 Assam events that resulted in widespread ground shaking, liquefaction, landslides and flooding damage. Hence, accurate probabilistic forecasts are essential for regional seismic hazard mitigation. An updated earthquake catalog was compiled for the area between 87–98° E and 20–30° N, with a focus on events of M_wg ≥ 5. A unified catalog was prepared for the analysis covering the period from 1897 to 2025. The region was divided into nine seismogenic zones to account for the spatial variability in recurrence patterns. The inter-event times between successive earthquakes were calculated for each zone, and three renewal models, lognormal, Weibull and gamma, were fitted by maximum likelihood estimation. The logarithmic probability of the likelihood function (ln L) was used to assess the model performance for a range of elapsed times (t) and forecast intervals (τ). The results indicate that the lognormal distribution at zero elapsed time (t = 0) provided the best fit and is, therefore, the most robust for short-term earthquake forecasting. Meanwhile, the Weibull model always gave the maximum of the conditional probabilities for longer elapsed times, especially for τ values between 13 and 25 years, and would, therefore, be preferable for long-term forecasts. Most of the zones had a gamma model that lay between the two, with moderate fits and probabilities. The zone analysis showed strong variability, with some zones with short recurrence times and high probabilities for the short term and others with long recurrence intervals. The Indo-Burma Range and the Eastern Himalaya zones had conditional probabilities of more than 90% for M_wg ≥ 5 earthquakes during 2044–2050, implying a higher seismic risk in these areas. The results suggest that there is no single renewal model that is optimal for all seismogenic zones and that the choice of model should be adapted to the elapsed time and the seismic characteristics of each zone. The present study offers a robust time-dependent probabilistic approach for the prediction of moderate-to-large earthquakes in Northeast India by combining an updated catalog and comparative renewal modeling. The findings are anticipated to contribute to seismic hazard assessment, infrastructure resilience planning and disaster preparedness strategies in one of the country’s most vulnerable regions. Full article

To address the dependence of uncertainty analysis methods on assumed probability density functions of wind power output and the computational burden of time-domain simulations in transient stability-constrained optimal power flow (TSCOPF) problems, this paper proposes a chance-constrained transient stability-constrained optimal power flow (CCTSCOPF) solution method based on data-driven polynomial chaos expansion (DDPCE) and the maximum entropy method (MEM). The method eliminates the need for predefined distribution assumptions for wind power variables. Specifically, using N = 5000 historical wind power forecast error samples, raw statistical moments up to order 2p = 8 are extracted, and orthogonal polynomial basis functions up to order p = 4 are derived by solving a 5 × 5 linear algebraic equation system constructed from these moments. Based on the constructed polynomials, Gaussian quadrature collocation points of wind power output are obtained, and time-domain simulations are performed at these points to solve the expansion coefficients, establishing a surrogate model that maps wind power fluctuations to transient responses. The surrogate model then computes the statistical moments of transient stability indices. MEM is subsequently used to reconstruct the probability density function of the transient stability index, and the transient stability chance constraint is converted into an algebraic boundary condition. Finally, an optimization model incorporating power system operating constraints is formulated and solved. Case studies conducted on the modified IEEE 39-bus test system with two 100 MW wind farms demonstrate that the proposed surrogate model achieves high accuracy with R² = 0.987, significantly improving uncertainty quantification accuracy over the standard Wiener–Askey polynomial chaos expansion (PCE) method. Furthermore, the total computational runtime is reduced from 66,280.00 s under full-scale Monte Carlo simulations to 47.92 s, achieving a 1383× computational speedup while strictly satisfying transient stability chance constraints. Full article

An 8-bit 3.2 GS/s four-channel time-interleaved (TI) successive-approximation-register (SAR)-flash analog-to-digital converter (ADC) employing complementary dynamic amplifier (CDA)-based two-step sub-ADCs is presented for high-speed wired and wireless communication systems. Each sub-ADC uses four CDAs to perform a 4-bit asynchronous loop-unrolled (LU) SAR conversion followed by a 4.5-bit reference-embedded interpolating flash (I-Flash) conversion, achieving 8-bit resolution with reduced comparator count and input capacitance. A four-channel TI architecture with a multi-phase clock generator and an on-chip voltage-controlled delay line (VCDL) enables 3.2 GS/s operation while performing foreground offset calibration under full TI loading to accurately track inter-channel reference variations. Fabricated in a 28 nm CMOS process, the prototype ADC shows differential non-linearity (DNL) and integral non-linearity (INL) ranges of −0.78 to +0.74 LSB and −0.84 to +1.03 LSB, respectively, and achieves a signal-to-noise and distortion ratio (SNDR) and a spurious-free dynamic range (SFDR) of 41.74 dB and 58.03 dB at 3.2 GS/s with a Nyquist-rate input. Operating from a 1 V supply, the ADC core consumes 8.63 mW at 3.2 GS/s, corresponding to a Walden figure-of-merit (FoM) of approximately 27 fJ/conversion step. Full article

Ice storms threaten distribution network resilience through combined mechanical loading and secondary failures, increasing the risk of prolonged power interruptions. This paper proposes a two-stage robust energy storage planning strategy for evolving ice storm conditions. A line failure probability model combines wind, ice, and gravity loads with fuzzy inference of secondary hazard effects to generate time-varying failure scenarios. Overall and important load resilience indices characterize system performance and the restoration of essential electricity services. The optimization model coordinates energy storage siting, sizing, and scheduling while accounting for investment, operation, electricity purchase, and load-loss costs. The model is solved using column-and-constraint generation and evaluated on a modified IEEE 33-bus distribution network. In the reported worst-case scenario, total energy not supplied decreases from 18.4 to 10.9 MWh with energy storage, a reduction of 40.8%. Energy not supplied to important loads decreases from 1.33 to 0.24 MW—a reduction of 82.0%. These reductions quantify unserved energy rather than changes in the absolute resilience indices. The results indicate that coordinated storage planning and scheduling can reduce outage consequences and prioritize important loads within the evaluated network, scenarios, and benchmark parameter settings. Full article