Thrust-vectoring UAVs can realize decoupling of position and attitude compared with conventional quadrotors due to the ability to change thrust direction, and are used to perform various complex indoor and outdoor missions. However, existing trajectory generation frameworks are mostly for quadrotors with fixed thrust direction and a coplanar surface, and do not consider the dynamics of thrust-vectoring UAVs. To address this, this paper proposes a multi-objective trajectory generation method for thrust-vectoring UAVs in constraint space. By parametrically modeling the constraint space, the method considers the effects of environmental boundary constraints and platform dynamics characteristics on the collision constraints and motion decoupling of the trajectory, and comprehensively optimizes the trajectory’s indicators of stability, speed, and safety to plan the states and input actions of the flight trajectory. Meanwhile, a trajectory generation evaluation system is proposed, given that compared with the conventional quadratic objective function, the proposed method is effective in reducing the attitude change of the trajectory, improving the rapidity and safety, in which $$L_{\theta}$$ and $$L_{r i s k}$$ are reduced by 70.4% and 19.1%, respectively. Meanwhile, by comparing with the conventional quadrotor, the advantages of the thrust-vectoring in decoupling motion are quantified, especially in reducing the attitude change during flight, the pitch angle of the generated trajectory is reduced from ±30° to within ±20° degrees, which exerts the motion decoupling advantages of the thrust-vectoring.
Dispersion in porous media is a multiscale process that governs the distribution and mixing of fluids in the subsurface. In underground hydrogen storage, dispersion is particularly critical due to hydrogen’s low molecular weight and large density contrast relative to natural gas. In addition to this, cyclic operations amplify mixing and transport effects beyond what is typically observed during conventional gas injection and storage. The apparent mixing observed during storage arises from the combined influences of localized dispersion, heterogeneity-driven channeling, and gravity segregation. Distinguishing between local, echo, and transmission dispersion provides a start for understanding reversible and irreversible components of mixing, and for connecting localized processes with field-scale performance. This study develops a systematic method to quantify dispersion in hydrogen storage within depleted gas reservoirs by combining analytical solutions of the convective–diffusive equation with multidimensional numerical simulations. The approach translates concentration fields into effective dispersion coefficients using different methods for mixing-zone length analysis. This enables evaluation across different permeability distributions, anisotropies, and spatial correlation lengths. The method is applied under both linear and radial flow conditions, including cyclic injection and production, to capture the distinct roles of gravity segregation, heterogeneity, and boundary conditions. Across the studied cases, the effective dispersion coefficient increases from approximately 1.03 to 3.5 m2/day as the Dykstra–Parsons coefficient increases from 0.3 to 0.9. Gravity segregation significantly alters plume evolution, reducing effective mixing zone lengths and introducing asymmetric displacement behavior. Under cyclic radial injection–production, incomplete plume reversal leads to persistent concentration halos, indicating irreversible mixing. The ratio of echo to transmission dispersion further quantifies the degree of irreversibility in the system. This work establishes a quantitative framework for characterizing dispersive transport in hydrogen storage systems and provides a basis for evaluating storage performance and reversibility under realistic subsurface conditions.
The evaluation of eyewitness memories has benefited greatly from basic memory research, which has shown that suggestive information or misinformation presented by a social source after an event can create substantial memory biases in participants’ memory, or even completely fabricated false memories. However, possible social influence occurring already at the stage of encoding (during the event) has so far been widely neglected. In basic research, meanwhile, several studies address this issue specifically with regard to incidental encoding of information (non-intentional encoding “along the way”, as it also occurs in eyewitness memories). The studies demonstrate that the social context at encoding influences how stimuli are encoded, and in one case even supports the occurrence of rich and detailed false memories. There are still many differences between the laboratory studies performed so far and any conceivable real-life scenarios of eyewitness situations. However, based on the results, it seems highly promising to evaluate the actual relevance of these initial findings for forensic science by modifying the paradigms to better reflect social encoding contexts that more closely resemble typical real-life eyewitness situations.
This review aims to address the environmental issues associated with the textile sector and explores innovative and optimal approaches for the zero-waste recycling of post-consumer cotton waste. The textile industry can transition toward a circular economy by implementing various recycling techniques. This will significantly cut the waste and raw material consumption, while promoting sustainability and environmental responsibility in textile manufacturing and consumption practices. This study focuses on several key techniques, including producing carbon fibres from waste, which provides a sustainable alternative to petroleum-based precursors. In addition, the regeneration of viscose fibres is achieved by chemical recycling of cotton waste and enzymatitc recycling. Method of Gasification and Thermochemical Valorisation, ioncell process is also discussed, emphasizing its potential to encourage resource conservation and lessen dependency on virgin resources. It also explains how cellulose nanofibrils (CNFs) can be extracted from post-consumer textiles and utilised to produce high-performance materials. Additionally, despite difficulties in preserving fibre quality, the potential of mechanical recycling techniques to yield viable yarns from recycled fibres is investigated.
We report the results of MeWO4 ceramics synthesis by the direct exposure of metal (Mg, Ca, Zn, W) oxides mixture to a high-power flux of high-energy electrons. The oxide powder particle sizes are 1–10 microns. The synthesis occurs with high efficiency in less than 1 s without the use of any additional substances and energy sources. The purpose of this work is to establish the main processes that ensure the effective synthesis of MgWO4, CaWO4, and ZnWO4 ceramics from ZnO, CaO, MgO, and WO4 oxides, which differ significantly in their physical and chemical properties. It has been found that the dependence of synthesis efficiency on the electron beam power density and the power density threshold at which synthesis begins varies significantly for simple metal oxides and is very close for the tungstates of these metals. The most probable explanation for the observed effect is redistribution of absorbed radiation energy. WO3 powder particles have a high absorptance of the incident electron radiation. The result is a cascade multiplication of primary electrons into secondary electrons with much lower energy. Secondary electrons are efficiently absorbed by MgO, CaO, and ZnO particles, leading to their efficient decomposition and the formation of a new phase.
