Yangzhou Polytechnic Institute

To address the challenges associated with inter-module energy interaction and mode adjustment at load ports in distributed energy systems in the context of the energy transition, this paper proposes and designs a multi-port wireless energy interaction system based on LC series resonance and multi-coil magnetic coupling. The system aims to facilitate flexible energy interaction among power sources, energy storage units, and loads, as well as multi-modal port regulation. The system employs a multi-coil coupled full-bridge topology combined with a phase-shift control strategy to achieve energy exchange and power regulation among multiple ports. To meet the power demands of different ports, a port state control method incorporating a mode preset mechanism is proposed, enabling the intermediate port to switch seamlessly among input (source), output (load), and active relay modes. This paper analyzes the operating modes of a single port and establishes the dynamic mathematical model of the overall three-coil system as well as the small-signal model of the port output. Furthermore, it investigates the energy interaction mechanism to derive the operating characteristics and conditions under different modes, and elucidates the energy relay mechanism with zero active power consumption. A three-port hardware experimental platform was constructed based on a dsPIC33 controller. Experimental results indicate that: (1) the prototype achieved a maximum transmission power of 100 W; (2) the peak system efficiency reached 83.1% under different load conditions; and (3) during mode switching, the system response time was less than 200 ms with no significant overshoot. The study demonstrates that the proposed topology and control strategy effectively realized dynamic energy interaction and seamless mode switching among multiple ports, providing a theoretical basis and engineering reference for multi-port energy interaction and wireless power transfer networks.

The continuous increase in power density of electronic devices imposes stringent requirements on the design of lightweight, high-efficiency heat sinks. To overcome the limitations of conventional single-gradient or monomaterial heat sinks—namely, their suboptimal heat-transfer efficiency and poor structural adaptability—this study proposes a dual-gradient, triply periodic minimal surface (TPMS)-based multimaterial heat sink architecture fabricated from CuCrZr and AlSi7Mg. Thermal performance was quantified experimentally using infrared thermography, while the underlying flow-field mechanisms were investigated numerically via computational fluid dynamics (CFD) simulations employing the standard k–ε turbulence model. With the TPMS material volume ratio fixed at 3:3 (CuCrZr:AlSi7Mg), the Z-axis gradient configuration P-Z4-5 delivered the best overall thermal performance, achieving a heat-transfer coefficient (HTC) of 1557.63 W·m−2·K−1 and a thermal resistance as low as 1.83 K·W−1 at an inlet velocity of 5 m·s−1. In contrast, the Y-axis gradient configuration P-Y3-6 yielded the most uniform temperature distribution, exhibiting a maximum surface temperature difference of only 21.5 °C under the same inlet condition. Velocity and turbulence distribution analyses reveal that the dual-gradient design enhances both the narrow-tube effect and flow-induced disturbances; furthermore, increasing the inlet velocity from 5 m·s−1 to 21.65 m·s−1 significantly intensifies vorticity-driven fluid mixing. Among all configurations evaluated, P-Z4-5 exhibited the highest j/f factor (i.e., the ratio of Colburn j-factor to Fanning friction factor), followed by P-Z3.5-5.5 and P-Z3-6. These findings establish a promising new pathway for the development of high-performance, lightweight heat sinks tailored for next-generation high-power electronics.

Amidst the burgeoning discourse on Artificial Intelligence (AI) in education, its application within Early Childhood Education (ECE), particularly for value-laden domains such as Education for Sustainable Development (ESD), remains a subject of intense debate. While AI presents significant opportunities for resource generation, concerns persist regarding its potential to undermine the humanistic essence of early childhood pedagogy. This paper addresses a pivotal question: How can AI empower ECE teachers while safeguarding their pedagogical autonomy? Employing a theoretical-speculative methodology, we propose an "AI Co-Pilot" model that conceptualizes AI not as a replacement, but as a synergistic partner operating under the teacher's strategic leadership. We establish a three-dimensional integrated framework—comprising "Value-Guidance, Function-Matching, and Boundary-Constraints"—to operationalize this collaborative dynamic. Specifically, we illustrate how AI’s supportive, supplementary, and adaptive functions can bridge critical teacher capability gaps in resource provision and individualized differentiation, while robust boundary constraints mitigate inherent ethical risks. This framework directly contributes to the realization of Sustainable Development Goal (SDG) 4.7 and SDG 12.8 by equipping educators with adaptive tools for value transmission. Ultimately, the study demonstrates how the "AI Co-Pilot" approach harmonizes technological efficiency (instrumental rationality) with value rationality to uphold humanistic educational objectives.

To meet the development needs of high-rise timber structures, current cross-laminated timber (CLT) shear walls typically feature a single-layer thickness of 35 mm with more than three laminations in the stack. However, such thickness easily leads to resource waste in small-scale residential buildings, while increasing transportation and hoisting costs, which is not conducive to the prefabrication and lightweight development of timber structures. To adapt to the development trend of China’s timber structure market towards public buildings such as cultural and tourism projects and small-scale residential buildings including new rural housing renovation, this study focuses on thin CLT shear walls with an overall thickness of 48 mm (16 mm per layer) and conducts research on their lateral load-bearing performance. Monotonic lateral static load tests and finite element (FE) simulations were carried out on thin CLT shear walls without openings, with different opening areas, and with the same opening area but different positions. A corresponding FE model was established and validated, with a focus on analyzing the influence of opening parameters on the shear performance of the walls. The research results show that wall openings significantly reduce the bearing capacity and shear stiffness of the walls: compared with the wall without openings, the ultimate load and shear stiffness of the walls with openings decrease by 20.4–28.6% and 36.3–42.3%, respectively. Among them, increasing the opening height has a more obvious weakening effect on the bearing capacity; for the same opening area, a wider opening results in a more significant decrease in stiffness. The FE model exhibits reliable accuracy, with the error between the experimental and simulation results in the elastic stage controlled within 10%, and the influence of the under-wall support on the shear stiffness is relatively small. Opening parameters have a prominent impact on the stiffness of the wall in the elastic stage, and the influence of the opening position is more critical—the smaller the distance from the opening to the top of the wall, the more obvious the decrease in overall stiffness.