AI, Robotics and Space

Browse

Browsing AI, Robotics and Space by Publisher "MDPI"

Now showing 1 - 4 of 4
  • Thumbnail Image
    ItemOpen Access
    A review of diffuse interface-capturing methods for compressible multiphase flows
    (MDPI, 2025-04-03) Adebayo, Ebenezer Mayowa; Tsoutsanis, Panagiotis; Jenkins, Karl W.
    This paper discusses in detail the classification, historical development, and application of diffuse interface-capturing models (DIMs) for compressible multiphase flows. The work begins with an overview of the development of DIMs, highlighting important contributions and key moments from classical studies to contemporary advances. The theoretical foundations and computational methods of the diffuse interface method are outlined for the full models and the reduced models or sub-models. Some of the difficulties encountered when using DIMs for multiphase flow modelling are also discussed.
  • Thumbnail Image
    ItemOpen Access
    Analysis of China’s high-speed railway network using complex network theory and graph convolutional networks
    (MDPI, 2025-04-16) Xu, Zhenguo; Li, Jun; Moulitsas, Irene; Niu, Fangqu
    This study investigated the characteristics and functionalities of China’s High-Speed Railway (HSR) network based on Complex Network Theory (CNT) and Graph Convolutional Networks (GCN). First, complex network analysis was applied to provide insights into the network’s fundamental characteristics, such as small-world properties, efficiency, and robustness. Then, this research developed three novel GCN models to identify key nodes, detect community structures, and predict new links. Findings from the complex network analysis revealed that China’s HSR network exhibits a typical small-world property, with a degree distribution that follows a log-normal pattern rather than a power law. The global efficiency indicator suggested that stations are typically connected through direct routes, while the local efficiency indicator showed that the network performs effectively within local areas. The robustness study indicated that the network can quickly lose connectivity if key nodes fail, though it showed an ability initially to self-regulate and has partially restored its structure after disruption. The GCN model for key node identification revealed that the key nodes in the network were predominantly located in economically significant and densely populated cities, positively contributing to the network’s overall efficiency and robustness. The community structures identified by the integrated GCN model highlight the economic and social connections between official urban clusters and the communities. Results from the link prediction model suggest the necessity of improving the long-distance connectivity across regions. Future work will explore the network’s socio-economic dynamics and refine and generalise the GCN models.
  • Thumbnail Image
    ItemOpen Access
    Designing and testing of HDPE–N2O hybrid rocket engine
    (MDPI, 2025-03-13) Arora, Triyan Pal; Buttrey, Noah; Kirman, Peter; Khadtare, Sanmukh; Kamath, Eeshaan; del Gatto, Dario; Isoldi, Adriano
    Hybrid Rocket Engines (HREs) combine the advantages of solid and liquid propellants, offering thrust control, simplicity, safety, and cost efficiency. Part of the research on this rocket architecture focuses on optimising combustion chamber design to enhance performance, a process traditionally reliant on time-consuming experimental adjustments to chamber lengths. In this study, two configurations of HREs were designed and tested. The tests aimed to study the impact of post-chamber lengths on rocket engine performance by experimental firings on a laid-back test engine. This study focused on designing, manufacturing, and testing a laid-back hybrid engine with two chamber configurations. The engine features a small combustion chamber, an L-shaped mount, a spark ignition, and nitrogen purging. Data acquisition includes thermocouples, pressure transducers, and a load cell for thrust measurement. Our experimental findings provide insights into thrust, temperature gradients, pressure, and plume characteristics. A non-linear regression model derived from the experimental data established an empirical relationship between performance and chamber lengths, offering a foundation for further combustion flow studies. The post-chamber length positively impacted the engine thrust performance by 2.7%. Conversely, the pre-chamber length negatively impacted the performance by 1.3%. Further data collection could assist in refining the empirical relation and identifying key threshold values.
  • Thumbnail Image
    ItemOpen Access
    Resilient time dissemination fusion framework for UAVs for smart cities
    (MDPI, 2025-03-17) Negru, Sorin Andrei; Arora, Triyan Pal; Petrunin, Ivan; Guo, Weisi; Tsourdos, Antonios; Sweet, David; Dunlop, George
    Future smart cities will consist of a heterogeneous environment, including UGVs (Unmanned Ground Vehicles) and UAVs (Unmanned Aerial Vehicles), used for different applications such as last mile delivery. Considering the vulnerabilities of GNSS (Global Navigation System Satellite) in urban environments, a resilient PNT (Position, Navigation, Timing) solution is needed. A key research question within the PNT community is the capability to deliver a robust and resilient time solution to multiple devices simultaneously. The paper is proposing an innovative time dissemination framework, based on IQuila’s SDN (Software Defined Network) and quantum random key encryption from Quantum Dice to multiple users. The time signal is disseminated using a wireless IEEE 802.11ax, through a wireless AP (Access point) which is received by each user, where a KF (Kalman Filter) is used to enhance the timing resilience of each client into the framework. Each user is equipped with a Jetson Nano board as CC (Companion Computer), a GNSS receiver, an IEEE 802.11ax wireless card, an embedded RTC (Real Time clock) system, and a Pixhawk 2.1 as FCU (Flight Control Unit). The paper is presenting the performance of the fusion framework using the MUEAVI (Multi-user Environment for Autonomous Vehicle Innovation) Cranfield’s University facility. Results showed that an alternative timing source can securely be delivered fulfilling last mile delivery requirements for aerial platforms achieving sub millisecond offset.