Calcium looping (CaL) is a great way to store thermal energy because it holds a lot of energy. But there is a big problem: CaO adsorbents quickly lose their activity. When they get hot, they sinter. Also, the product layer blocks diffusion. Because of these issues, we cannot easily use CaL on a large scale right now. To fix this, researchers are adding oxygen vacancies at the atomic level. This paper reviews how oxygen vacancies change CaO-based materials for the better. First, we look at how people make these vacancies in the lab. For example, they use aliovalent doping or change the material's shape. We also list the main tools used to check them. Next, the paper explains the science behind this using Density Functional Theory (DFT) calculations. These calculations show us exactly how the vacancies work. They give ions an easier path to travel, which speeds up the physical movement (better kinetics). At the same time, the vacancies act as Lewis basic sites. They grab CO₂ molecules tighter, which helps the reaction happen (better thermodynamics). Finally, we talk about the remaining hurdles, especially keeping the materials stable at very high heat. We suggest that future work should combine live testing (in-situ) with data-driven computer models to build much stronger energy storage materials.

Show more

To address the bottleneck in thermal management of high power density electronic devices, an active thermal management system architecture based on intelligent fluid drive is proposed in this paper. In this study, a dynamic model covering electric-flow-thermal multi-physical field coupling is constructed, and the intrinsic orthogonal decomposition technology is used to break through the computational power barrier of high-dimensional nonlinear systems, which provides an important theoretical paradigm and engineering path for the next generation of adaptive intelligent thermal control technology.

Show more

Reliable navigation under GNSS degradation requires exploiting complementary sensors and estimation methods that can tolerate nonlinearity and outliers. This paper presents a multi-source integrated navigation approach for unmanned aerial vehicles (UAVs) that combines an inertial measurement unit (IMU), GNSS, a ground-based laser ranging-and-angle sensor, and a ground-based RF radar. A practical calibration and alignment pipeline is first established, including IMU intrinsic calibration (misalignment, scale factors, and biases), GNSS lever-arm compensation, and weighted least-squares calibration for range/angle channels of the laser sensor and radar. On this basis, a sliding-window factor-graph optimization framework is constructed with IMU preintegration as the time backbone, while GNSS, laser, and radar measurements are introduced as factors. Marginalization is applied to bound the problem size, and residual-based down-weighting is used to suppress gross errors. Simulation results on a maneuvering UAV trajectory demonstrate clear accuracy gains over an extended Kalman filter (EKF): the mean position error decreases from about 2.16–2.20 m to 0.69–0.79 m, and the mean velocity error decreases from about 0.24–0.28 m/s to 0.10–0.11 m/s. These results indicate that factor-graph smoothing can provide more accurate and stable navigation estimates for multi-rate heterogeneous sensing.

Show more

In this era of advanced information technology, it is common to observe that our university facing demands for blended teaching skills in physical education (PE). This study aimed to qualitatively analyze Blended Teaching Competency based on five exemplary sports course (including dance, martial arts, and yoga) in Hubei Province. According to human-computer collaborative thoery, we propose a four-dimensional evaluation framework: covering teaching integration, technology application, adaptive intelligence, and smart feedback. This framework support not just skill acquisition but the holistic psychological, physical, and emotional development of university students. Our analysis, obviously, revealed that tools like ARs and motion recognition instruments are game-changer. More interesting, these tools allowed for dynamic group coordination exercises and personalized learning paths based on real-time task for student. Ultimately, this framework embodies three core principle: "student-computer-teacher collaboration," "data-driven instruction," and "intelligent PE." We believe it offers a concrete, practical roadmap for enhancing PE teachers' competence in designing and executing blended learning environments.

Show more