Acta Energiae Solaris Sinica•2026•DOI: 10.19912/j.0254-0096.tynxb.202608_9656
This study investigates a serial composite gasification process for biomass and coal using computational particle fluid dynamics (CPFD) modeling. The model comprehensively accounts for bed hydrodynamics, particle dynamics, heat and mass transfer, and homogeneous and heterogeneous chemical reactions. The effects of various operating variables on gas composition, gas yield, and gasification efficiency are examined. Results indicate that increasing gasification temperature is beneficial, and the influence of turbulence within the reactor must be considered. The gasification reaction mechanisms differ under varying steam-to-biomass mass ratios (SBR): at low SBR, gas-solid reactions in the dense phase are promoted, whereas at high SBR, homogeneous reactions at the dilute phase outlet are enhanced. A higher biomass-to-coal mass ratio (BCR) is recommended. The gasification performance of different biomass feedstocks shows minimal variation, demonstrating the substitutability of biomass raw materials in this process. The study provides a theoretical basis for optimizing gasification technology and improving efficiency.
Power Automation Equipment•2026•DOI: 10.16081/j.epae.202606023
Conventional Thévenin equivalent models fail to capture the nonlinear low-voltage ride-through (LVRT) and current-limiting behavior of inverter-interfaced renewable generators, leading to significant errors in short-circuit current calculations near transmission-distribution boundaries. This paper proposes a transient equivalent model and parameter estimation method for transmission networks with high renewable penetration under specific operating conditions. The model augments the traditional ideal voltage source and equivalent impedance with a voltage-controlled current source (VCCS) and an additional short-circuit impedance. The VCCS control function aggregates all renewable generators, distinguishing between units that enter LVRT and those that do not. A data-driven regression approach estimates equivalent parameters using the additional short-circuit impedance as input. Validation on a modified IEEE 39-bus system with high renewable penetration confirms the model's rationality and the accuracy of the parameter estimation. The proposed model achieves superior short-circuit current calculation accuracy compared to the conventional Thévenin model, particularly for faults near the transmission-distribution interface where renewable generators experience voltage dips below 0.9 p.u. and exhibit non-smooth current response characteristics.
Power Automation Equipment•2026•DOI: 10.16081/j.epae.20251130012
Parameter identification for electromagnetic transient (EMT) models of grid-connected photovoltaic (PV) systems suffers from weak identifiability of controller parameters when environmental, electrical, and controller parameters are optimized simultaneously. This paper proposes a two-stage identification framework that partitions parameters by physical meaning into an environmental/electrical set and a controller set. For the environmental/electrical set, a Sobol global sensitivity analysis based on variance decomposition screens key parameters. For the controller set, a dynamic response feature clustering method combined with an unsupervised screening strategy using an inter-cluster mean difference index reduces the parameter space. Differentiated fitness functions are constructed for each stage, and an improved quantum dung beetle optimization (IQDBO) algorithm incorporating quantum angle encoding and a stagnation perturbation mechanism performs the identification sequentially. Case studies demonstrate that the proposed method compresses the search space and improves controller parameter identifiability. Compared with particle swarm optimization (PSO) and grey wolf optimizer (GWO), the IQDBO-based method achieves superior identification accuracy and convergence stability. Environmental and electrical parameter identification errors remain below 1%, while controller parameter errors remain below 3%. The framework addresses the weak identifiability bottleneck in unified optimization and provides a practical pathway for EMT model calibration in PV grid-connected systems. Future work will extend the method to multiple operating conditions and noisy field data, and develop accelerated computation strategies.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3759-7
The inherent strength-ductility trade-off in materials science poses a significant challenge for structural applications. In composites, rational regulation of reinforcement structure and distribution can enhance both strength and ductility. Typical structures such as network, layered, and columnar have proven effective, yet issues like narrow size ranges, uneven distribution, and weak interfacial bonding limit performance. Here, we present a bioinspired multi-scale heterogeneous layered composite (MHLC) that achieves an optimal balance between strength and ductility. This heterogeneous layered structure comprises alternately stacked Cu-Ti layers and GNPs/Cu layers. The Cu-Ti layer contains uniformly distributed plate-like β-Cu4Ti intermetallic compounds, while the GNPs/Cu layer contains layered graphene nanoplatelets (GNPs). The size, distribution, and shape of reinforcements can be adjusted through heat treatment and cold rolling, enabling a balance between strength and ductility. Molecular dynamics simulation and finite element simulation were conducted to investigate the structural evolution of β-Cu4Ti and the influence of reinforcements on tensile properties, respectively. Results show that under tensile deformation, high-strain regions in the Cu-Ti layer are more numerous than in the GNPs/Cu layer. At an applied strain of 7.96%, fracture and deformation of reinforcements occur; at 23.98%, voids appear and develop into cracks. Cracks propagate along high-strain paths, forming a zigzag fracture pattern at the interface, indicating high interfacial bonding strength. The bending deformation of β-Cu4Ti suggests it possesses high hardness, strength, and excellent toughness. Our results provide important references for exploring multi-scale heterogeneous layered structures in enhancing strength and ductility of composites.
Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202511054
A novel S-scheme heterojunction photocatalyst, Bi6O5(OH)3(NO3)5·3H2O/BiOBr0.8I0.2 (BON@BI), was synthesized via a one-step hydrothermal method using Bi6O5(OH)3(NO3)5·3H2O (BON), KBr, and KI as precursors. The mass ratio of BON to BiOBr0.8I0.2 (BI) was optimized, revealing that the 20% BON@BI composite (BON@BIOPT) exhibited the highest visible-light photocatalytic activity. Under 30 min of visible-light irradiation, BON@BIOPT achieved a 99.8% degradation efficiency of Rhodamine B (RhB), approximately twice that of pristine BI (52.2%). The composite displayed a rod-like morphology with uniform nanosheets, and its specific surface area increased from 32.54 m²·g⁻¹ (BI) to 44.7 m²·g⁻¹. The absorption edge red-shifted from 560 nm (BI) to 580 nm, narrowing the bandgap from 2.55 eV to 2.43 eV. The S-scheme heterojunction formed between BON and BI generates an internal electric field that effectively suppresses recombination of strongly reducing photogenerated electrons and strongly oxidizing holes, with superoxide radicals (O₂•⁻) and holes (h⁺) identified as the primary reactive species. BON@BIOPT exhibited excellent stability, retaining 88.6% degradation efficiency after seven consecutive cycles. It also demonstrated robust environmental adaptability, maintaining 85–98% degradation efficiency under various pH conditions and in the presence of interfering anions. The degradation pathway of RhB involves N-de-ethylation, cleavage of the conjugated chromophore, and deamination, ultimately mineralizing into low-molecular-weight organics, inorganic salts, CO₂, and H₂O. These results underscore the potential of BON@BIOPT for practical remediation of organic pollutants in water.