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Soft coarse-grained particle model for particle-fluid systems

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Particuology 2024年第1期84卷 178-193页

作者： Yanhao Ye Ji xu Wei ge State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing100049China Innovation Academy for Green Manufacture Chinese Academy of SciencesBeijing100190China

By modeling a group of neighboring real particles as a single coarse-grained particle(CGP),discrete particle method(DPM)is now capable of simulating industrial-scale particle-fluid systems.However,a systematic approach to determine the CGP properties and develop their interaction models is still lacking,which casts uncertainty on the predictivity of the method.In this study,collisions between predefined particle groups are analyzed to construct kernel functions for modeling the CGPs and then the model parameters are determined by equating the statistical properties of the CGPs and the real particles in the physical process studied.This approach is implemented for homogeneous cooling of granular gas,then demonstrated effective in simulating experimental fluidized beds.

关键词： Coarse-grain(CG) Discrete particle method(DPM) Fluidized bed Multi-scale simulation

Design study of charge-stripping scheme of heavy ion beams for HIAF-BRing

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Nuclear Science and Techniques 2024年第5期35卷 30-41页

作者： Jun-Jie Zhang zhi-You xu Jin-Quan Zhang Wen-Wen ge Liang-Ting Sun Huan-Yu Zhao Institute of Modern Physics Chinese Academy of SciencesLanzhou 730000China School of Nuclear Science and Technology University of Chinese Academy of SciencesBeijing 100049China

Charge strippers play an essential role in heavy-ion accelerators by stripping the projectile ions to higher charge states to enhance the acceleration efficiency downstream of the stripper.In the high-energy mode of the booster ring(BRing)of the high-intensity heavy-ion accelerator facility,the pre-accelerated ions from the iLinac will be stripped by a carbon foil to higher charge states and then injected into the BRing.The key parameters of the stripper and stripped ions were calculated,and the influence of stripping on the beam quality was discussed.To get high stripping efficiencies,the foil thicknesses and resultant charge state distributions for the typical ions were determined by the code ETACHA.The equilibrium thickness was obtained for the U beam,while the stripper thicknesses for the Xe and Kr beams were determined based on a compromise between the stripped charge states and the stripping efficiency.The energy loss,energy straggling,and emittance growth due to stripping have a non-negligible impact on the transport of the stripped beams and the injection of the ring.Therefore,these parameters were simulated by geANT4.In addition,the foil’s temperature evolution,which greatly affects the foil lifetime,was simulated by ANSYS.The maximum temperature of the foil bombarded by the U and Xe beams with the nominal parameters will exceed the safe value in terms of the impact of evaporation on the foil’s lifetime.Given the foil temperature constraint,the highest tolerable beam intensity and the injected ion number into the ring were derived for different beam sizes.The results of this paper will present important reference data for the optimization design and commissioning of the beamline and injection to the BRing for the stripped ions.

关键词： High-intensity heavy-ion accelerator facility Charge stripper Energy spread Thermal analysis Emittance growth Injection turns

Clinical Characteristics of Macular Hole and Macular Epiretinal Membrane in Dominant and Nondominant Eyes

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Biomedical and Environmental Sciences 2023年第1期36卷 112-116页

作者： LIU Yang WANG Xin ZHU Min xu ge zhi Eye Institute and Department of Ophthalmology Eye&ENT HospitalFudan UniversityNHC Key Laboratory of Myopia(Fudan University)Key Laboratory of MyopiaChinese Academy of Medical SciencesShanghai Key Laboratory of Visual Impairment and RestorationShanghai 200031China

Ocular dominance(OD) is referred to the superiority of one eye over the other when the visual sense is produced[1]. This condition can be considered as a preference for the particular laterality of the eye during a mono-visual task or the relative contributions of visual signal transduction between eyes[2]. Empirically, OD tendencies are exhibited in habitual and subconscious behavior.

关键词： visual dominance superiority

3D coarse-grained DPM simulation of the MIP reaction-regeneration loop

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Particuology 2024年第6期89卷 57-66页

作者： Yanhao Ye Shuai Zhang Ji xu Wei ge State Key Laboratory of Mesoscience and Engineering(formerly State Key Laboratory of Multiphase Complex Systems) Institute of Process EngineeringChinese Academy of SciencesBeijing100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing100049China

The reactor-regenerator loop is the core facility of the maximizing iso-paraffin(MIP)process.Although the discrete particle method(DPM)simulation can provide detailed information at the particle scale,it has been unable to simulate such a complex loop system due to limitations of coarse-grained(CG)models,computing software,and hardware.In this study,a newly proposed soft-shell CG-DPM model with a CG ratio of up to 800 is used to simulate a 3.5 Mt/a industrial-scale MIP reactor-regenerator loop.The solid fraction distribution obtained is found to agree well with in-situ measurements.Hydrodynamic properties including the distribution of solid fraction,gas and solid velocity,standard derivation of solid fraction with time,temporal distribution of the flow field,and particle residence time distribution are measured in the simulation,which are meaningful to better design and operate such systems in the future.

关键词： Discrete particle method Coarse-grain Maximizing iso-paraffins Full-loop Reaction-regeneration system

Gas–solid reactor optimization based on EMMS-DPM simulation and machine learning

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Particuology 2024年第6期89卷 131-143页

作者： Haolei Zhang Aiqi Zhu Ji xu Wei ge State Key Laboratory of Mesoscience and Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190ChinaFormerly State Key Laboratory of Multiphase Complex SystemsInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Innovation Academy for Green Manufacture Chinese Academy of SciencesBeijing 100190China

Design,scaling-up,and optimization of industrial reactors mainly depend on step-by-step experiments and engineering experience,which is usually time-consuming,high cost,and high risk.Although numerical simulation can reproduce high resolution details of hydrodynamics,thermal transfer,and reaction process in reactors,it is still challenging for industrial reactors due to huge computational cost.In this study,by combining the numerical simulation and artificial intelligence(AI)technology of machine learning(ML),a method is proposed to efficiently predict and optimize the performance of industrial reactors.A gas–solid fluidization reactor for the methanol to olefins process is taken as an example.1500 cases under different conditions are simulated by the coarse-grain discrete particle method based on the Energy-Minimization Multi-Scale model,and thus,the reactor performance data set is constructed.To develop an efficient reactor performance prediction model influenced by multiple factors,the ML method is established including the ensemble learning strategy and automatic hyperparameter optimization technique,which has better performance than the methods based on the artificial neural network.Furthermore,the operating conditions for highest yield of ethylene and propylene or lowest pressure drop are searched with the particle swarm optimization algorithm due to its strength to solve non-linear optimization problems.Results show that decreasing the methanol inflow rate and increasing the catalyst inventory can maximize the yield,while decreasing methanol the inflow rate and reducing the catalyst inventory can minimize the pressure drop.The two objectives are thus conflicting,and the practical operations need to be compromised under different circumstance.

关键词： Discrete particle method Artificial intelligence Machine learning Particle swarm optimization Industrial reactor optimization

Electrolyte Design for Low‑Temperature Li‑Metal Batteries:Challenges and Prospects

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Nano-Micro Letters 2024年第2期16卷 365-382页

作者： Siyu Sun Kehan Wang Zhanglian Hong Mingjia zhi Kai Zhang Jijian xu Department of Chemistry City University of Hong KongHong Kong 999077People’s Republic of China State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027People’s Republic of China State Key Laboratory of Advanced Chemical Power Sources Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education)Haihe Laboratory of Sustainable Chemical TransformationsCollaborative Innovation Center of Chemical Science and Engineering(Tianjin)College of ChemistryNankai UniversityTianjin 300071People’s Republic of China Department of Chemical and Biomolecular Engineering University of Maryland College ParkCollege ParkMD 20742USA

Electrolyte design holds the greatest opportunity for the development of batteries that are capable of sub-zero temperature operation.To get the most energy storage out of the battery at low temperatures,improvements in electrolyte chemistry need to be coupled with optimized electrode materials and tailored electrolyte/electrode interphases.Herein,this review critically outlines electrolytes’limiting factors,including reduced ionic conductivity,large de-solvation energy,sluggish charge transfer,and slow Li-ion transportation across the electrolyte/electrode interphases,which affect the low-temperature performance of Li-metal batteries.Detailed theoretical derivations that explain the explicit influence of temperature on battery performance are presented to deepen understanding.Emerging improvement strategies from the aspects of electrolyte design and electrolyte/electrode interphase engineering are summarized and rigorously compared.Perspectives on future research are proposed to guide the ongoing exploration for better low-temperature Li-metal batteries.

关键词： Solid electrolyte interphase Li metal Low temperature Electrolyte design Batteries

Gut-targeted therapies for type 2 diabetes mellitus: A review

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World Journal of Clinical Cases 2024年第1期12卷 1-8页

作者： Tian-Cheng xu Yun Liu zhi Yu Bin xu Key Laboratory of Acupuncture and Medicine Research of Ministry of Education Nanjing University of Chinese MedicineNanjing 210023Jiangsu ProvinceChina

Type 2 diabetes mellitus(T2DM)is a chronic metabolic disorder characterized by hyperglycemia and insulin resistance.The global prevalence of T2DM has reached epidemic proportions,affecting approximately 463 million adults worldwide in 2019.Current treatments for T2DM include lifestyle modifications,oral antidiabetic agents,and insulin therapy.However,these therapies may carry side effects and fail to achieve optimal glycemic control in some patients.Therefore,there is a growing interest in the role of gut microbiota and more gut-targeted therapies in the management of T2DM.The gut microbiota,which refers to the community of microorganisms that inhabit the human gut,has been shown to play a crucial role in the regulation of glucose metabolism and insulin sensitivity.Alterations in gut microbiota composition and diversity have been observed in T2DM patients,with a reduction in beneficial bacteria and an increase in pathogenic bacteria.This dysbiosis may contribute to the pathogenesis of the disease by promoting inflammation and impairing gut barrier function.Several gut-targeted therapies have been developed to modulate the gut microbiota and improve glycemic control in T2DM.One potential approach is the use of probio-tics,which are live microorganisms that confer health benefits to the host when administered in adequate amounts.Several randomized controlled trials have demonstrated that certain probiotics,such as Lactobacillus and Bifidobacterium species,can improve glycemic control and insulin sensitivity in T2DM patients.Mechanisms may include the production of short-chain fatty acids,the improvement of gut barrier function,and the reduction of inflammation.Another gut-targeted therapy is fecal microbiota transplantation(FMT),which involves the transfer of fecal material from a healthy donor to a recipient.FMT has been used successfully in the treatment of Clostridioides difficile infection and is now being investigated as a potential therapy for T2DM.A recent randomized controlled trial showed that FMT from lea

关键词： Type 2 diabetes mellitus Gastroenterology Bacteria Implanted device

A novel clinical artificial intelligence model for disease detection via retinal imaging

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The Innovation 2024年第2期5卷 11-12页

作者： Yidian Fu Liang Ma Sheng Wan Shengfang ge zhi Yang Department of Ophthalmology Ninth People’s HospitalShanghai JiaoTong University School of MedicineShanghai 200011China Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology Shanghai 200011China PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of EducationNanjing 210000China Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and EngineeringNanjing University of Science and TechnologyNanjing 210000China

Artificial intelligence(AI)is an emerging field in which computerized systems are used to carry out complex tasks in place of humans.Medical AI algorithms have been developed for disease diagnosis and prediction and treatment recommendation across various clinical data types,e.g.,chest X-rays,electrocardiograms,and other radiological images.1 In ophthalmology,particularly,great progress has been made in AI systems over the past decade.Color fundus photography(CFP)and optical coherence tomography(OCT),which are readily available in routine clinical practice,are both mainstream and useful retinal imaging modalities in ophthalmology.In September 2023,the 2023 Lasker-Debakey Clinical Medical Research Award was awarded to three scientists for their work on OCT for accurate retinal disease detection.

关键词： clinical routine diagnosis

Reinforcement learning based adaptive control for uncertain mechanical systems with asymptotic tracking

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Defence Technology（防务技术） 2024年第4期34卷 19-28页

作者： Xiang-long Liang zhi-kai Yao Yao-wen ge Jian-yong Yao School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing210094China College of Automation&College of Artificial Intelligence Nanjing University of Post and TelecommunicationNanjing210023China

This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.

关键词： Adaptive control Reinforcement learning Uncertain mechanical systems Asymptotic tracking