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Molecular dynamics simulation of heat transfer during liquid hydrogen boiling on surfaces at the nanoscale

Nuclear Science and Techniques 2025年第7期36卷 1-12页

作者： Li, Xiao-Jia Chen, He-Ying Sun, Yi-Zheng Fan, Zhi-Chun School of Ocean Information Engineering Jimei University Xiamen361021 China Department of Mechanical Engineering City University of Hong Kong Hong Kong Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing Jimei University Xiamen361021 China

Liquid hydrogen, known for its high energy density and eco-friendly properties, has garnered significant attention in the context of sustainable development and clean energy. A comprehensive understanding of its nucleation mechanisms and boiling heat transfer characteristics is crucial. However, current experimental and macroscopic simulation methods offer limited insights. This study employs molecular dynamics simulations to investigate the vaporization nucleation and boiling heat transfer properties of liquid hydrogen at the microscopic scale, with a focus on the effects of hydrogen film thickness, surface temperature, and wettability. The results indicate that hydrogen film thickness plays a critical role in nucleation. Thinner layers disrupt the shape of liquid films, leading to increased errors, whereas a thickness of 7 nm ensures film stability. Different heating methods and temperatures influence nucleation in various ways. Rapid heating results in a higher heat flux, while an increase in temperature under the same heating method accelerates nucleation, resulting in earlier nucleation and enhanced surface heat flow. Surfaces with varying wettability levels exhibit distinct nucleation behaviors. Specifically, an increase in α delays nucleation, causing a shift from the surface to within the liquid film due to stronger solid–liquid interaction forces. This study offers a microscale perspective on the nucleation and boiling processes of liquid hydrogen and provides valuable insights for phase transition studies. © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2025.

关键词： Electric heating

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Robust Channel Estimation for IRS-Assisted Millimeter-Wave MIMO Systems

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IEEE Transactions on Vehicular Technology 2025年

作者： Guo, Fang Zhou, Zhenhua Liao, Bin Shenzhen University State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen518060 China Shenzhen University Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen518060 China Hangzhou Dianzi University School of Communication Engineering Hangzhou310018 China

In this paper, the downlink channel estimation of the intelligent reflecting surface (IRS) assisted MIMO systems is considered in the millimeter-wave (mmWave) band. It is challenging to acquire the channel state information (CSI) of the IRS-assisted wireless communication systems, due to the large amount of passive reflecting elements at the IRS. On account of the low-rank property of the mmWave channels, a bivariate optimization problem, which balances the minimization of the fitting errors and the kernel norms, is formulated to address the estimation of the cascaded channel. By leveraging the alternating optimization method, the problem is decoupled into two subproblems, each of which is solved with the alternating direction method of multipliers (ADMM) together with the singular value thresholding (SVT) technique. In comparison with its counterparts, the proposed method provides higher estimation accuracy and stronger resistance to the uncertainty of the ranks of the channel state information matrices. © 2025 IEEE.

关键词： Channel estimation

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SIEVL-Track: Exploring Semantic information Enhancement for Visual-Language Object Tracking

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Li, Ning Zhong, Bineng Liang, Qihua Mo, Zhiyi Nong, Jian Song, Shuxiang Ministry of Education Guangxi Normal University Key Laboratory of Education Blockchain and Intelligent Technology Guilin541004 China Guangxi Normal University Guangxi Key Lab of Multi-Source Information Mining and Security Guilin541004 China Wuzhou University Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou543002 China

With the assistance of language descriptions, Visual-Language (VL) object tracking can obtain more accurate semantic information compared to traditional Visual-Only object tracking. However, the ability of current VL trackers to obtain target semantic information has not been fully developed due to limitations such as wasted modeling capabilities and insufficient utilization of historical temporal information. On the one hand, the modeling output from Transformer shallow encoders often does not directly participate in the prediction of tracking results, resulting in a certain degree of model capability waste. On the other hand, the semantic information of historical tracking results has also not been fully utilized in the tracking process, resulting in a certain degree of lack of semantic assistance capability. Therefore, we propose a novel hierarchical multi-stage VL tracker called SIEVL-Track to enhance target semantic information. Specifically, we first design a multi-stage visual language tracking framework for modeling multi-scale semantic information in Visual-Language tracking pipeline. Secondly, we propose a selective deep and shallow semantic information fusion module (S-DSFM) that explicitly integrates shallow output features into deep output features, so to reduce the waste of modeling capabilities and obtain more high-frequency semantic information related to the target. Finally, we design a temporal cue modeling module based on linguistic classification and multi-frame historical information(MHLS-TCM), with the aim of more comprehensive utilization of historical temporal semantic information. Benefit from the above designs, our VL tracker can obtain stronger target semantic information. Competitive performance from extensive experimental results on five popular vision-language tracking benchmarks, including LaSOT, OTB99-Lang, WebUAV-3M, LaSOText and TNL2K, have demonstrated the superiority and effectiveness of our SIEVL-Track. © 1991-2012 IEEE.

关键词： Semantics

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MCFNet: Multiscale Cross-domain Fusion Network for HSI and LiDAR Data Joint Classification

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Song, Qiya Mo, Feng Ding, Kexin Xiao, Lin Dian, Renwei Kang, Xudong Li, Shutao Hunan Normal University School of Information Science and Engineering Hunan Changsha410081 China School of Robotics Hunan University Hunan Changsha410082 China Fujian Key Laboratory of Spatial Information Perception and Intelligent Processing Yango University China

Hyperspectral image (HSI) encompasses abundant spatial and spectral details, while Light Detection and Ranging (LiDAR) delivers precise elevation data. The amalgamation of HSI and LiDAR data significantly improves the precision of image classification. However, most methods focus solely on spatial features while neglecting frequency domain information, limiting the ability of deep models to characterize land cover. Furthermore, how to establish a sufficient interaction between different modalities is also an important issue. In this paper, we propose a novel multiscale cross-domain fusion network (MCFNet) for joint classification of HSI and LiDAR data. The main idea is that the wavelet transform can provide details at different resolutions simultaneously, supplementing spatial domain information and enriching feature representation. In addition, the multimodal fusion module (MFM) guided by HSI and the cross-domain fusion module (CDFM) strategy are developed to integrate features from diverse modalities and domains, respectively. Specifically, frequency domain features are extracted by discrete wavelet transform, and spatial domain features of the image are captured through a set of convolution operations. Then interactive fusion is performed by MFM and CDFM, and finally the integrated features are categorized using a classification module. Extensive experiments on three widely-used HSI and LiDAR datasets indicate that MCFNet outperforms the SOTA methods. © 1980-2012 IEEE.

关键词： Frequency domain analysis

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Modality Unified Attack for Omni-Modality Person Re-Identification

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IEEE Transactions on information Forensics and Security 2025年

作者： Bian, Yuan Liu, Min Yi, Yunqi Wang, Xueping Ma, Yunfeng Wang, Yaonan Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha China Hunan Normal University Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Changsha China

Deep learning based person re-identification (re-id) models have been widely employed in surveillance systems. Recent studies have demonstrated that black-box single-modality and cross-modality re-id models are vulnerable to adversarial examples (AEs), leaving the robustness of multi-modality re-id models unexplored. Due to the lack of knowledge about the specific type of model deployed in the target black-box surveillance system, we aim to generate modality unified AEs for omni-modality (single-, cross- and multi-modality) re-id models. Specifically, we propose a novel Modality Unified Attack method to train modality-specific adversarial generators to generate AEs that effectively attack different omni-modality models. A multi-modality model is adopted as the surrogate model, wherein the features of each modality are perturbed by metric disruption loss before fusion. To collapse the common features of omnimodality models, Cross Modality Simulated Disruption approach is introduced to mimic the cross-modality feature embeddings by intentionally feeding images to non-corresponding modality-specific subnetworks of the surrogate model. Moreover, Multi Modality Collaborative Disruption strategy is devised to facilitate the attacker to comprehensively corrupt the informative content of person images by leveraging a multi modality feature collaborative metric disruption loss. Extensive experiments show that our MUA method can effectively attack the omni-modality re-id models, achieving 55.9%, 24.4%, 49.0% and 62.7% mean mAP Drop Rate, respectively. © 2005-2012 IEEE.

关键词： Modality unified attack Multi Modality Collaborative Disruption Omni-Modality re-id

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Prescribed Performance Bipartite Consensus control for MASs Under Data-Driven Strategy

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IEEE/CAA Journal of Automatica Sinica 2025年第5期12卷 937-946页

作者： Zhou, Qi Yin, Caiyun Ma, Hui Ren, Hongru Li, Hongyi School of Automation Guangdong University of Technology Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou 510006 China School of Mathematics and Statistics Guangdong University of Technology Guangzhou 510006 China College of Electronic and Information Engineering Southwest University Chongqing 400715 China

This paper investigates the bipartite consensus control problem for discrete time nonlinear multiagent systems (MASs) based on data-driven adaptive method. To begin with, a dynamic linearization strategy is utilized to establish the relationship between bipartite tracking error and control input for MASs. Secondly, the unknown parameter linearly associated with control input is acquired by the adaptive control approach, and a discrete time extended state observer is designed to estimate nonlinear uncertainties. Thirdly, in order to achieve the prescribed performance, the constrained bipartite consensus error is transformed through a strictly increasing function. Based on the converted equivalent unconstrained error function, a sliding mode controller using only the input and output data of the MASs is designed. Finally, the efficacy of the controller is confirmed by simulations. © 2014 Chinese Association of Automation.

关键词： Data-driven nonlinear multiagent systems (MASs) prescribed performance sliding mode control

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Optimizing Fixed-Time Generalized Nash Equilibrium Seeking in Multi-Unmanned Aerial Vehicle Games

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Hua, Menghu Yao, Xiang-Yu Liu, Wen-Jin Geng, Mei-Jie Lv, Maolong China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan430074 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai 200240 China Air Force Engineering University College of Air Traffic Control and Navigation Xi'an710038 China

This study addresses a fixed-time generalized noncooperative game involving multiple unmanned aerial vehicles (UAVs) that encounter challenges such as discontinuous communication and external disturbances. Each UAV, motivated by selfinterest, seeks to optimize its performance function by adjusting its actions within shared equality and inequality constraints. To facilitate this, a fixed-time generalized Nash equilibrium (GNE) seeking algorithm is proposed for games with shared equality constraints, incorporating an internal dynamic system to ensure compliance with these constraints. By employing penalty methods, an auxiliary performance function is developed to manage games with mixed constraints. Furthermore, an error decomposition method and a fixed-time observer are introduced to address the issues of discontinuous communication and external disturbances. The study establishes sufficient conditions for the convergence of the fixed-time GNE seeking algorithm and provides an explicit upper bound on the settling time based on Lyapunov stability theory. The effectiveness of the proposed algorithms is demonstrated through various simulation examples. © 1965-2011 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Conditional Disturbance Compensation-Based Fault-Tolerant Group Consensus control for MASs: An Event-Based Switching Method

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 13828-13841页

作者： Liu, Pei-Ming Guo, Xiang-Gui Wang, Jian-Liang Che, Wei-Wei Wu, Zheng-Guang University of Science and Technology Beijing Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering Beijing100083 China University of Science and Technology Beijing Shunde Innovation School Foshan528000 China Beihang University Hangzhou Innovation Institute Autonomous Intelligent Systems Department Hangzhou310051 China Northeastern University College of Information Science and Engineering Shenyang266071 China Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou310027 China

With respect to the group consensus control for multi-agent systems (MASs) with disturbances and actuator nonidentical and unknown direction faults (NUDFs), this paper proposes a novel fault-tolerant control scheme by incorporating an event-based switching function and a saturation function. The event-based switching function is implemented to directly switch to the desired working mode, thereby reducing invalid switching after a reverse fault. Concurrently, the saturation function, acting at the software level, can not only prevent the instantaneous impact of excessive reverse input caused by a reverse fault, but also eliminate input peaking and state chattering after switching the working mode. It is worth mentioning that the proposed switching-based fault-tolerant control method can avoid the control chocks and excessive control gains as in the existing methods by using Nussbaum functions and thus improve the transient performance. Additionally, for disturbances, the designed conditional disturbance compensation mechanism ensures a smaller steady-state error, and less energy consumption by utilizing beneficial disturbances and compensating for harmful ones. Besides, the conditional compensation mechanism also reduces the saturation error. Finally, the effectiveness of the proposed control scheme are verified through a simulation example of uncrewed aerial vehicles (UAVs). © 2004-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A Unified Framework for Analysis and Optimization of RIS-Assisted MIMO Multiple Access Networks

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IEEE Internet of Things Journal 2025年

作者： Wang, Siqiang Zheng, Zhong Guo, Jing Fei, Zesong Sun, Zhi Zhang, Qin Beijing Institute of Technology School of Information and Electronics Beijing China Beijing Institute of Technology School of Information and Electronics National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing100081 China Tsinghua University Department of Electronic Engineering Beijing China

Recently, reconfigurable intelligent surfaces (RISs) are gaining increasing attention in communication systems due to their ability to adapt themself according to the wireless environment. Therefore, the communication systems with massive RIS deployments are able to extend high-quality coverage ubiquitously. This is especially beneficial for Internet of Things (IoT) systems as the IoT devices can be located in hard-to-reach area. On the other hand, current methods to analyze and optimize the performance of communication systems with multiple RISs deployment are ad hoc, which depends on the specific system configurations. There lacks a unified theoretical framework that provides general analytical treatment for both passive and active RIS-assisting systems, possibly having multiple concatenated reflections via RISs, which is typical in IoT communication scenarios. Thus, we investigate general uplink RIS-assisted multi-user multiple-input multiple-output (MU-MIMO) communication systems under general Rician fading channels, where the number of cascaded RIS panels are arbitrary and the RIS elements can be active or passive. By utilizing the linearization trick and the operator-valued free probability theory, a unified analytic expression of the ergodic sum rate for the considered MU-MIMO systems is derived. Then, we further propose a low-complexity optimization approach to design the RISs’ phase shifts, thus enhancing the ergodic sum rate. Numerical results verify the accuracy of the analytical results for RIS-assisted systems. In addition, the convergence and effectiveness of the proposed optimization algorithm are demonstrated. © 2014 IEEE.

关键词： Fading channels

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Resilient Distributed Quadrotor UAVs Game: Addressing FDI and Physical Attacks

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IEEE Transactions on Vehicular Technology 2025年

作者： Geng, Mei-Jie Ding, Hua-Feng Yao, Xiang-Yu Lv, Maolong China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan430074 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Air Force Engineering University College of Air Traffic Control and Navigation Xi'an710038 China

Distributed quadrotor unmanned aerial vehicles (UAVs) are increasingly deployed in critical applications, including reconnaissance, disaster response, and transportation, where system resilience is paramount. However, their complex dynamics and reliance on cyber-physical systems make them highly vulnerable to adversities such as uncertain dynamics, time-varying input disturbances, false data injection (FDI), and physical attacks. This paper proposes a hierarchical framework consisting of a game layer and an execution layer to enhance the resilience of a noncooperative game involving distributed UAVs. In the game layer, a novel FDI observer mitigates communication and computational FDI attacks, facilitating convergence to infinitesimal ranges around the Nash equilibrium (NE) point. The execution layer addresses uncertain dynamics and physical attacks, ensuring that UAVs can track a narrow neighborhood of the NE even in the presence of actuator failures. Extensive simulations validate the algorithm's effectiveness and robustness against mixed attack scenarios, underscoring its potential for real-world UAV applications. © 1967-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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