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A cavitation flow can greatly impact a vehicle's attitude and stability when exiting water. This paper adopts an improved delayed detached eddy turbulence model and a Schnerr–Sauer cavitation model as well as the volume-of-fluid method and an overlapping grid technique to investigate this effect. In addition, the experimental system of the underwater launch is designed and built independently, which the numerical results are in good agreement with the experimental results. The transient cavitation flow structure and motion characteristics of the projectiles successively launched underwater are studied. When the axial spacing ranges from 0 to 1.0 times the diameter of the projectile, both projectiles are severely affected to various extents in cavitation pattern, vortex structure, and motion characteristics. It is worth noting that the internal cavity of the secondary projectile is disturbed by the wake of the primary projectile, resulting in large-scale fractures and detachment of the internal cavity, but its motion stability is good. [ABSTRACT FROM AUTHOR]

For integrated pose control of six-degree-of-freedom (6-DOF) leader–following spacecraft formations, the coupled relative pose between two spacecraft is described by a unified model in the framework of twistors, based on which a finite-time control law is devised for the 6-DOF dynamic system. Firstly, some necessary coordinate frames are defined, and then, relative 6-DOF dynamics of the follower spacecraft with respect to the desired frame are modeled by using twistors. Secondly, an integrated pose controller is designed for the 6-DOF formation that takes full advantage of homogeneous theory to guarantee finite-time stability. Finally, numerical simulations are carried out to validate the effectiveness of the proposed controller. Developing integrated 6-DOF formation control law based on twistors is more straightforward than conventional methods, and the finite-time algorithm achieves stronger robustness than asymptotic ones. [ABSTRACT FROM AUTHOR]

In order to improve the problem of overly relying on situational information, high computational power requirements, and weak adaptability of traditional maneuver methods used by hypersonic vehicles (HV), an intelligent maneuver strategy combining deep reinforcement learning (DRL) and deep neural network (DNN) is proposed to solve the hypersonic pursuit–evasion (PE) game problem under tough head-on situations. The twin delayed deep deterministic (TD3) gradient strategy algorithm is utilized to explore potential maneuver instructions, the DNN is used to fit to broaden application scenarios, and the intelligent maneuver strategy is generated with the initial situation of both the pursuit and evasion sides as the input and the maneuver game overload of the HV as the output. In addition, the experience pool classification strategy is proposed to improve the training convergence and rate of the TD3 algorithm. A set of reward functions is designed to achieve adaptive adjustment of evasion miss distance and energy consumption under different initial situations. The simulation results verify the feasibility and effectiveness of the above intelligent maneuver strategy in dealing with the PE game problem of HV under difficult situations, and the proposed improvement strategies are validated as well. [ABSTRACT FROM AUTHOR]

This paper proposes a novel finite-time adaptive neural control method for a class of high-order nonlinear systems with high powers in the presence of dead zone input nonlinearities and unmodeled dynamics. By utilizing prescribed performance functions and radial basis function neural networks, the tracking error and state errors are limited within the preassigned range in a finite time, which can be specified by the designer in advance according to the chosen the parameters of the novel prescribed performance functions. Nonlinear transformed error surfaces are designed to counteract the effects of dead zone input nonlinearities in nonlinear high-order systems with unknown system nonlinearities and unmodeled dynamics. Based on the Lyapunov theorem, the tracking errors are proven to converge into a preassigned set in a finite time previously specified by the novel prescribed performance function. Finally, simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a distributed asymptotic tracking control strategy is investigated by establishing filters and barrier function-based consensus control scheme to address the control of heterogenous power-chained multiagent systems (MASs) under a directed graph subject to the unknown input deadzone nonlinearities and unknown control coefficients. First, to generate estimation information from the leader, a two-order filter is exploited for every agent which solves the difficultly of the time-varying control coefficients in multiagent systems with a directed topology. Then, based on the two-order filters, prescribed performance method and barrier functions are utilized to establish the distributed tracking protocol to handle the power-chained deadzone input nonlinearities, such that the MAS can reach the global consensus while guaranteeing the prescribed tracking error performance. Using the Lyapunov stability theorem, the proof of the convergence is accomplished rigorously. Ultimately, the efficacy and advantage of the devised method are validated by two simulation examples. [ABSTRACT FROM AUTHOR]

Groundwater can be contaminated by PFAS emissions, yet research on the presence and associated risks of PFAS in groundwater underlying different land-use areas remains limited. Herein, high-resolution mass spectrometry-based suspect and nontarget analyses were performed to determine PFAS occurrence in groundwater samples obtained from a rural area, a planting region, and the vicinities of a pharmaceutical park, an airport, and an industrial park in Datong City, China. A total of 31 PFAS (16 emerging and 15 legacy PFAS) were identified, and the ΣPFAS concentrations ranged from 0.775 (rural area) to 80.7 ng/L (pharmaceutical park). In terms of the average concentration of ΣPFAS, legacy PFAS were predominant in rural groundwater, whereas emerging PFAS were predominant in the other four land-use areas. PFOA, PFDA, PFUnDA, and 6:2 FTS were detected in all groundwater samples. To further prioritize the risk of identified PFAS in groundwater, the detection frequency; concentration; and persistence, bioaccumulation, and toxicity attributes were adopted, which showed that high-risk compounds varied across different land-use areas. Our results further reveal the ubiquitous contamination of PFAS in groundwater environments, even in areas with limited human activity, and highlight the necessity of suspect and nontarget analysis for assessing PFAS exposure through groundwater.

Knowledge of the biotransformation of tetrabromobisphenol A (TBBPA) and its related contaminants by human gut microbiota (GM) remains unexplored. Here, TBBPA and its four analogs were incubated with mixed GM strains, and nine rhamnosylated or debrominated transformation products (TPs) were discovered. Remarkably, rhamnosylation was identified as a common and unique microbial transformation pathway for these contaminants, and six of the seven rhamnosylated TPs were reported for the first time. Additionally, a kinetic transformation study also showed a rapid and strong bioaccumulation of TBBPA and TPs by Clostridium manihotivorum . Genomic analysis and phylogenetic studies identified C1.1_02053 as the gene encoding the C. manihotivorum working rhamnosyltransferase (CmRT), showing elevated gene expression with higher TBBPA exposure. Molecular docking identified five critical amino acid residues in CmRT that catalyze TBBPA rhamnosylation, and molecular dynamics simulations further confirmed the stability of the CmRT-TBBPA complex. Dynamic metabolomics analysis showed microbial growth-dependent disturbing effects in C. manihotivorum upon TBBPA exposure, and key metabolic pathways related to rhamnosyltransferase showed changes closely related to the transformation process. These findings provide insights into the unique transformation of environmental contaminants by the GM and highlight the disturbing effects of exogenous chemicals on the GM, as well as the potential impacts on overall human health.