Very lean hydrogen flames were thought to quench in narrow confined geometries. We show for the first time how flames with very low fuel concentration undergo an unprecedented propagation in narrow gaps: ${\mathrm{H}}_2$-air flames can survive very adverse conditions by breaking the reaction front into isolated flame cells that travel steadily in straight lines or split to perform a fractal-like propagation that resembles the pathway of starving fungi or bacteria. The combined effect of hydrogen mass diffusivity and intense heat losses act as the two main mechanisms that explain the experimental observations.

This article presents a real-time trajectory calculation system for shore-to-ship operations using Unmanned Aerial Vehicles (UAVs). This is a concept, aimed to improve the efficiency of the transportation system by using UAVs to carry out parcel deliveries to offshore ships. During these operations, the UAVs would need to fly relatively close to manned vessels, posing significant risks for the crew in the event of any incident. Besides, in these marine areas the UAVs are exposed to meteorological phenomena such as wind gusts, which may compromise the stability of the flight and lead to potential collisions. Furthermore, this is a phenomenon difficult to predict, which poses a risk that must be considered in the operations. For these reasons, this work proposes a gust-aware multi-objective optimization solution for calculating fast and safe trajectories, considering the risk of flying in areas prone to the formation of intense gusts. Moreover, the system establishes a risk buffer with respect to all vessels to ensure compliance with EASA (European Union Aviation Safety Agency) regulations. For this purpose, Automatic Identification System (AIS) data are used to determine the position and velocity of the different vessels, and trajectory calculations are periodically updated based on their motion. The system computes the minimum-cost trajectory between the ground base and a moving destination ship while keeping these risk buffer constraints. The problem was solved through an Optimal Control formulation discretized on a dynamic graph with time-dependent costs and constraints. The solution was obtained using a Reaching Method that allowed efficient and real-time computations.

Unmanned Aerial Vehicles (UAVs), commonly known as drones, have experienced a significant surge in both civilian and military applications, owing to their versatility and cost-effectiveness. However, a negligent use or the operation with harmful intent of these aircraft poses a potential risk to public safety and the privacy of individuals. In response to this threat, counter-drone systems have been developed in recent years, including technologies to detect, position, and neutralize these aircraft. This paper presents a review of different existing commercial counter-drone systems, the technologies behind detection, tracking, and classification, as well as soft and hard kill mitigation.