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Efficient transmutation of long-lived fission products in a Gamma Factory beam driven advanced nuclear energy system

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arXiv 2024年

作者： Hu, Baolong Krasny, Mieczyslaw Witold Placzek, Wieslaw Yuan, Yun Shi, Xiaoming Luo, Kaijun Luo, Wen School of Nuclear Science and Technology University of South China Hengyang421001 China Key Laboratory of Advanced Nuclear Energy Design and Safety Ministry of Education Hengyang421001 China LPNHE University Paris Sorbonne Paris75005 France CERN Geneva1211 Switzerland Faculty of Physics Astronomy and Applied Computer Science Mark Kac Center for Complex Systems Research Jagiellonian University ul. Lojasiewicza 11 Krakow30–348 Poland

The Gamma Factory (GF) project aims to generate high-intensity γ-ray beams of tunable energy and relatively small energy spread. Such beams can be optimized to generate an intense photo-neutron source, capable of driving an advanced nuclear energy system (ANES) for nuclear waste transmutation and supplying electrical power that is necessary for the GF operation mode of the Large Hadron Collider storage ring. In this study, we investigate the feasibility of driving ANES with the GF beam which is optimized to maximize the neutron production rate. The dependence of the ANES thermal power on the distance between the positions of the ANES and the GF γ-ray source is evaluated. For the γ-ray beam reaching the intensity of ∼1019 photons per second, the ANES thermal power could exceed 500 MWt. Under the assumption that ANES operates over 20 years, the transmutation rate could reach 30% for five typical long-lived fission products (LLFPs): 79Se, 99Tc, 107Pd, 129I, 137Cs. Our comparative studies show that although the neutron production efficiency of the GF γray beam (per MW of the beam power) is approximately 14 times lower than that of the 500 MeV proton beam, the overall net ANES power production efficiency for the GF beam driver scheme could be comparable to that of the proton beam driver scheme, while providing additional transmutation capacity, not available for the proton beam driven scheme. It is suggested that the GF-based ANES could provide a viable solution for the efficient transmutation of LLFPs without isotopic separation. Copyright © 2024, The Authors. All rights reserved.

关键词： Storage rings

Formation control with obstacle avoidance of second-order multi-agent systems under directed communication topology

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science China(Information sciences) 2019年第9期62卷 144-157页

作者： Guoxing WEN C.L.Philip CHEN Hui DOU Hongli YANG Chunfang LIU College of Science Binzhou University Department of Computer and Information Science Faculty of Science and Technology University of Macau College of Navigation Dalian Maritime University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Mathematics and Systems Science College Shandong University of Science and Technology

This paper addresses the obstacle avoidance problem of formation control for the multi-agent systems modeled by double integrator dynamics under a directed interconnection topology. The control task is finished by a leader-follower formation scheme combined with an artificial potential field(APF) *** leader-follower scheme is carried out by taking the desired trajectory with the desired velocity as virtual leader, while the APF method is carried out by dealing with the obstacles as the high potential points. When the obstacle avoidance tasks are finished, the artificial potential forces degrade the formation performance, so their undesired effects are treated as disturbances, which is analyzed by the robust H∞performance. Based on Lyapunov stability theory, it is proved that the proposed formation approach can realize the control objective. The result is also extended to the switching multi-agent formation. The effectiveness of the proposed formation scheme is further confirmed by simulation studies.

关键词： formation control obstacle avoidance artificial potential field method H_∞ performance second-order multi-agent system directed topology

Early warnings are too late when parameters change rapidly

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arXiv 2024年

作者： Radhakrishnan, Rohit Pavithran, Induja Livina, Valerie Kurths, Jürgen Sujith, R.I. Department of Aerospace Engineering Indian Institute of Technology Madras Chennai600036 India Centre of Excellence for studying Critical Transitions in Complex Systems Indian Institute of Technology Madras Chennai600036 India Data Science Department National Physical Laboratory Hampton Road TeddingtonTW11 0LW United Kingdom Potsdam14473 Germany Institute of Physics Humboldt Universität zu Berlin Berlin12489 Germany

Early warning signals (EWSs) forewarn a sudden transition (or tipping) from a desirable state to an undesirable state. However, we observe that EWSs detect an impending tipping past bifurcation points when control parameters are varied fast;this questions the applicability of EWSs in real-world systems. When a control parameter is changed at a finite rate, the tipping is also delayed, providing a borrowed stability (in the parameter space) before the system tips. In this study, we use the Hurst exponent as EWS in a thermoacoustic system - a horizontal Rijke tube. We find that upon receiving an EWS alert, a quick reversal of the control parameter within the region of borrowed stability cannot always prevent tipping in real-world systems. We show this failure is due to the (i) delay in receiving the EWS alert and (ii) dispersion observed in the warning points received. For fast variation of parameters, where preventive measures fall short, we demonstrate EWS-based control actions to rescue the system after tipping. Our results in a real-world system for a fast variation of parameter highlight the limits of applicability of EWSs in preventing tipping. © 2024, CC BY-NC-ND.

关键词： Bifurcation (mathematics)

Embedding theory of reservoir computing and reducing reservoir network using time delays

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Physical Review Research 2023年第2期5卷 L022041-L022041页

作者： Xing-Yue Duan Xiong Ying Si-Yang Leng Jürgen Kurths Wei Lin Huan-Fei Ma School of Mathematical Sciences Soochow University Suzhou 215006 China School of Mathematical Sciences SCMS and SCAM Fudan University Shanghai 200433 China Research Institute of Intelligent Complex Systems and Centre for Computational Systems Biology Fudan University Shanghai 200433 China Academy for Engineering and Technology Fudan University Shanghai 200433 China State Key Laboratory of Medical Neurobiology LCNBI and MOE Frontiers Center for Brain Science Institutes of Brain Science Fudan University Shanghai 200032 China Potsdam Institute for Climate Impact Research (PIK) Potsdam 14473 Germany Shanghai Artificial Intelligence Laboratory Shanghai 200232 China

Reservoir computing (RC), a particular form of recurrent neural network, is under explosive development due to its exceptional efficacy and high performance in reconstruction and/or prediction of complex physical systems. However, the mechanism triggering such effective applications of RC is still unclear, awaiting deep and systematic exploration. Here, combining the delayed embedding theory with the generalized embedding theory, we rigorously prove that RC is essentially a high-dimensional embedding of the original input nonlinear dynamical system. Thus, using this embedding property, we unify into a universal framework the standard RC and the time-delayed RC where we introduce time delays only into the network's output layer, and we further find a trade-off relation between the time delays and the number of neurons in RC. Based on these findings, we significantly reduce the RC's network size and promote its memory capacity in completing systems reconstruction and prediction. More surprisingly, only using a single-neuron reservoir with time delays is sometimes sufficient for achieving reconstruction and prediction tasks, while the standard RC of any large size but without time delay cannot complete them yet.

关键词： Control & applications of chaos Mathematical physics Neuronal networks Patterns in complex systems

A mechanism for ice growth on the surface of a spherical water droplet

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arXiv 2025年

作者： Li, Yang Parashar, Prachi Brevik, Iver Persson, Clas Malyi, O.I. Boström, Mathias School of Physics and Materials Science Nanchang University Nanchang330031 China Institute of Space Science and Technology Nanchang University Nanchang330031 China John A. Logan College CartervilleIL62918 United States Department of Energy and Process Engineering Norwegian University of Science and Technology TrondheimNO-7491 Norway Department of Materials Science and Engineering KTH Royal Institute of Technology StockholmSE-100 44 Sweden Qingyuan Innovation Laboratory Quanzhou362801 China Centre of Excellence ENSEMBLE3 Sp. z o. o. Wolczynska Str. 133 Warsaw01-919 Poland Chemical and Biological Systems Simulation Lab Centre of New Technologies University of Warsaw Banacha 2C Warsaw02-097 Poland

The formation and growth of ice particles, particularly on the surfaces of spherical water droplets, bear profound implications for localized weather systems and global climate. Herein, we develop a theoretical framework for ice nucleation on minuscule water droplets, establishing that 10 ∼ 5000 nm droplets can considerably increase in volume, making a substantial contribution to ice formation within mist, fog, or even cloud systems. We reveal that the Casimir-Lifshitz (van der Waals) interaction within these systems is robust enough to stimulate both water and ice growth on the surfaces of ice-cold spherical water droplets. The significant impacts and possible detectable phenomena from the curvature are demonstrated. © 2025, CC BY-NC-ND.

关键词： Van der Waals forces

Event-triggered Consensus Control of Heterogeneous Multi-agent systems: Model- and Data-based Analysis

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arXiv 2022年

作者： Wang, Xin Sun, Jian Wang, Gang Chen, Jie The School of Automation The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

This article deals with model- and data-based consensus control of heterogenous leader-following multi-agent systems (MASs) under an event-triggering transmission scheme. A dynamic periodic transmission protocol is developed to significantly alleviate the transmission frequency and computational burden, where the followers can interact locally with each other approaching the dynamics of the leader. Capitalizing on a discrete-time looped-functional, a model-based consensus condition for the closed-loop MASs is derived in form of linear matrix inequalities (LMIs), as well as a design method for obtaining the distributed controllers and event-triggering parameters. Upon collecting noise-corrupted state-input measurements during open-loop operation, a data-driven leader-following MAS representation is presented, and employed to solve the data-driven consensus control problem without requiring any knowledge of the agents' models. This result is then extended to the case of guaranteeing an H∞ performance. A simulation example is finally given to corroborate the efficacy of the proposed distributed event-triggering scheme in cutting off data transmissions and the data-driven design method. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

ON THE BOUNDEDNESS OF NON-STANDARD ROUGH SINGULAR INTEGRAL OPERATORS

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arXiv 2022年

作者： Hu, Guoen Tao, Xiangxing Wang, Zhidan Xue, Qingying School of Applied Mathematics Beijing Normal University Zhuhai519087 China Department of Mathematics School of Science Zhejiang University of Science and Technology Hangzhou310023 China School of Mathematical Sciences Beijing Normal University Laboratory of Mathematics and Complex Systems Ministry of Education Beijing100875 China

Let Ω be homogeneous of degree zero, have vanishing moment of order one on the unit sphere Sd−1(d ≥ 2). In this paper, our object of investigation is the following rough non-standard singular integral operator TΩ, Af(x) = p. v. ∫ Rd Ω(x - y)/|x - y|d+1 (A(x) − A(y) − ∇A(y)(x − y))f(y)dy, where A is a function defined on Rd with derivatives of order one in BMO(Rd). We show that TΩ, A enjoys the endpoint Llog L type estimate and is Lp bounded if Ω ∈ L(log L)2(Sd−1). These resuts essentially improve the previous known results given by Hofmann [24] for the Lp boundedness of TΩ, A under the condition Ω ∈ Lq(Sd−1) (q > 1), Hu and Yang [28] for the endpoint weak Llog L type estimates when Ω ∈ Lipα(Sd−1) for some α ∈ (0, 1]. Quantitative weighted strong and endpoint weak Llog L type inequalities are proved whenever Ω ∈ L∞(Sd−1). The analysis of the weighted results relies heavily on two bilinear sparse dominations of TΩ, A established *** Codes 42B20, 47G10 © 2022, CC BY.

关键词： Mathematical operators

Learning Network-Invariant and Label-Discriminative Representations for Cross-Network Node Classification

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Learning Network-Invariant and Label-Discriminative Represen...

2021 China Automation Congress, CAC 2021

作者： Yang, Linyao Xu, Yancai Hou, Jiachen Dai, Yuxin Lv, Chen The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Institute of Systems Engineering Macau University of Science and Technology China School of Electrical Engineering and Automation Wuhan University Wuhan China China Electric Power Research Institute Beijing China

ISBN: (纸本)9781665426473

Networks are ubiquitous data structures in the real world. The accurate and efficient analysis of networks is critical to realizing many intelligent network-based services. However, most existing network analysis methods are developed for single networks and require a lot of labeled data, which is costly and time-consuming to acquire. Transfer learning has been widely accepted as an effective paradigm for tackling this problem by reusing the model trained on a supervised task. However, transfer learning on the non-euclidean network data has been investigated by no more than a few studies. To realize accurate node classification based on the knowledge learned from the labeled source network, this paper proposes to learn network-invariant and label-discriminative representations based on graph embedding and linear discriminant analysis. Specifically, we embed the source and target networks into adjacent vector spaces based on the graph attention network by minimizing the Sinkhorn distributional distances between their embeddings. To obtain label-discriminative features for learning better classification models, we then utilize a transferable linear discriminative analysis method to project the embeddings into label-discriminative subspaces. In the end, a support vector machine model trained on the labeled source network is utilized to classify the target nodes. Experiments on two pairs of networks illustrate that our method achieves the best performance and evaluates the effectiveness of the proposed modules. © 2021 IEEE

关键词： Embeddings

Model-Based and Data-Driven Control of Event- and Self-Triggered Discrete-Time LTI systems

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arXiv 2022年

作者： Wang, Xin Berberich, Julian Sun, Jian Wang, Gang Allgöwer, Frank Chen, Jie The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70550 Germany The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

The present paper considers the model-based and data-driven control of unknown linear time-invariant discretetime systems under event-triggering and self-triggering transmission schemes. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which also offers a way of co-designing the ETS matrix and the controller. To further alleviate the sampling burden of ETS due to its continuous/periodic detection, a self-triggering scheme (STS) is developed. Leveraging pre-collected input-state data, an algorithm for predicting the next transmission instant is given, while achieving system stability. Finally, numerical simulations showcase the efficacy of ETS and STS in reducing data transmissions as well as of the proposed co-design methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities