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Effect of the Graphene Oxide Incorporation on the Morphology, Corrosion Resistance and Fatigue Performance of Micro-Arc Oxidation Coating on Magnesium Alloy

SSRN

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SSRN 2024年

作者： Tan, Yansong Liu, Xin Sun, Xiaohao Gao, Lilan Liu, Debao Zhang, Chunqiu Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Cont rol School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineerin g Education Tianjin University of Technology Tianjin300384 China School of Materials Science and Engineering Tianjin University of Technology Tianjin300384 China

Magnesium (Mg) alloy has great potential in biomedical applications, but the rapid corrosion rate which mismatches with bone reconstruction rate limits its clinical use. In this study, the graphene oxides (GO) were added into alkaline electrolyte solution during micro-arc oxidation (MAO) process, aiming to form a corrosion resistant surface coating on Mg alloy. By changing the concentration of GO, the coatings' morphology, composition, corrosion resistance, and fatigue property were compared to reveal the strengthening mechanism and find out the optimal graphene concentration. The results show that the MAO coating is composed of MgO, Mg2SiO4, Mg3(PO4)2 and GO. The added GO exhibits excellent adsorption property in the MAO process, reducing the intermolecular gap, thereby improving densification and obturation of the MAO coating. The surface morphology of MAO coating initially improves with increasing GO content, but then deteriorates, reaching its best quality at 0.4 g/L. Compared to MAO samples without GO, the samples with 0.4g/L GO not only have lower corrosion current density of 5.226 μA/cm2, but also show higher fatigue lives both before and after pre-corrosion. This study offers a promising approach to enhance the corrosion resistance and fatigue performance of Mg alloy by applying a GO-strengthened MAO coating onto its surface. © 2024, The Authors. All rights reserved.

关键词： Magnesium alloys

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One-Pot Synthesis of Tetraarylpyrrolo[3,2-b]pyrrole Dopant-Free Hole-Transport Materials for Inverted Perovskite Solar Cells

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Chinese Journal of Chemical Physics 2021年第2期34卷 217-226,I0002页

作者： Liang-sheng Duan Quan-ping Wu Yuan-yuan Xu Hui Wang Zhe Sun Yu Chen Song Xue School of Materials Science and Engineering Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical SystemSchool of Mechanical EngineeringTianjin University of TechnologyTianjin 300384China

Four organic smallmolecule hole transport materials(D41, D42,D43 and D44) of tetraarylpyrrolo[3,2-b]pyrroles were prepared. They can be used without doping in the manufacture of the inverted planar perovskite solar cells. Tetraarylpyrrolo[3,2-b]pyrroles are accessible for one-pot synthesis.D42, D43 and D44 possess acceptor-π-donor-π-acceptor structure, on which the aryl bearing substitutes of cyan, fluorine and trifluoromethyl, respectively. Instead, the aryl moiety of D41 is in presence of methyl with a donor-π-donor-π-donor structure. The different substitutes significantly affected their molecular surface charge distribution and thin-film morphology, attributing to the electron-rich properties of fused pyrrole ring. The size of perovskite crystalline growth particles is affected by different molecular structures,and the electron-withdrawing cyan group of D42 is most conducive to the formation of large perovskite grains. The D42 fabricated devices with power conversion efficiency of17.3% and retained 55% of the initial photoelectric conversion efficiency after 22 days in dark condition. The pyrrolo[3,2-b]pyrrole is efficient electron-donating moiety for hole transporting materials to form good substrate in producing perovskite thin film.

关键词： Pyrrole[3,2-b]pyrrole Hole-transporting materials Organic small molecules Dopant-free Perovskite solar cells

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Research on Intelligent Temperature Control Method of Closed-Loop Cooling system Based on Deep Q-Network

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SSRN 2024年

作者： Liu, Yongchao Wang, Bo Zheng, Wei Wang, Zibo Li, Tong Cheng, Jiahao Niu, Zhenfeng Ke, Zhiwu Tan, Sichao Li, Jiangkuan Gao, Puzhen Tian, Ruifeng Zhu, Qidan Heilongjiang Provincial Key Laboratory of Nuclear Power System & Equipment Harbin Engineering University Harbin150001 China Key Laboratory of Nuclear Safety and Advanced Nuclear Energy Technology Ministry of Industry and Information Technology Harbin Engineering University Harbin150001 China Science and Technology Thermal Energy and Power Laboratory Wuhan430205 China Wuhan Second Ship Design and Research Institute Wuhan430205 China College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin150001 China

As one of the most important subsystem types in the nuclear power system, the closed-loop cooling system is used for the heat transfer of the system. The control quality of its operating temperature is important for the safe operation of the entire nuclear power system. This paper proposes an intelligent temperature control method based on deep reinforcement learning (DRL). First, the closed-loop cooling system simulator is built and expanded to provide an experimental platform for the implementation of DRL. Secondly, a DRL interaction system is designed based on prior knowledge such as system thermal control characteristics and temperature control targets. Finally, the improved deep Q-network (DQN) algorithm is used to train the deep neural network agent, and the optimal temperature control strategy is approached and saved through self-learning interaction. The experimental results demonstrate that the DRL controller can realize automatic control operation and has good target tracking ability and robustness. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Photocatalytic Degradation of Tetracycline Over Bimetallic Layered Double Hydroxides-Mxenes Heterostructures Under Visible Light

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SSRN 2024年

作者： Yao, Jixin Liu, Yong Tong, Xiaowei Lu, Shibin Meng, Ying Li, Guang Anhui Province Key Laboratory of Simulation and Design for Electronic Information System Universities Joint Key Laboratory of Photoelectric Detection Science and Technology in Anhui Province Hefei Normal University Hefei230601 China School of Materials Science and Engineering Anhui Key Laboratory of Information Materials and Devices Key Laboratory of Structure and Functional Regulation of Hybrid Materials Ministry of Education Institute of Physical Science and Information Technology Anhui University Hefei230601 China School of Electronic Engineering Huainan Normal University Huainan232038 China

Layered double hydroxides (LDHs) are widely used in photocatalytic degradation of antibiotic pollutants under ultraviolet (UV)-light, but their efficiency under visible light is hampered by large band gaps and layer agglomeration. To address these challenges, we have successfully developed innovative bimetallic NiCo LDHs-MXenes heterostructures (LDHs-MXenes) for enhanced degradation of tetracycline (TC) pollutants under visible light conditions. As-prepared LDHs-MXenes photocatalysts (20 mg) show exceptional performance, achieving ~97.4% TC degradation efficiency (20 mg L-1, 100 mL) within just 50 minutes under a 300 W Xe lamp. This significant enhancement underscores the synergistic effects derived from the combination of LDHs and MXenes nanosheets. © 2024, The Authors. All rights reserved.

关键词： Heterojunctions

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Prediction of boiling crisis in a full-size rod bundle with spacer grids 14

Prediction of boiling crisis in a full-size rod bundle with ...

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14th International Nuclear Fuel Cycle Conference, GLOBAL 2019 and Light Water reactor Fuel Performance Conference, TOP FUEL 2019

作者： Li, Quan Li, Yuanming Avramova, M. Huang, Yongzhong Liu, Zhenhai Ma, Chao Qi, Feipeng Zhao, Bo Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China Department of Nuclear Engineering North Carolina State University NC27695 United States

In this paper, two-phase CFD approach is used to simulate the boiling crisis in PSBT rod bundle with spacer grids. The 5×5 rod bundle contains 17 spacer grids, which are finely modeled through UG code. Eulerian two-fluid model coupled with the extended wall boiling model is used to simulate the subcooled boiling flow. The used sub-models for nucleation site density and bubble departure diameter both take the effects of high pressure into consideration. The calculated surface averaged void fraction in the central four sub-channels shows good agreement with the experimental data at high void fraction conditions, while higher than the measured data at low void fraction conditions. Based on the two-phase simulations, the void fraction distribution in the plane section on which thermocouples are placed is used as the criteria for CHF prediction. The numerical simulation of boiling two-phase flow and prediction method of CHF provide new approach for the optimization of spacer grid and fuel assembly. Copyright © GLOBAL 2019 - International Nuclear Fuel Cycle Conference and TOP FUEL 2019 - Light Water reactor Fuel Performance *** rights reserved.

关键词： Forecasting

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Non-Stoichiometric Protic Ionic Liquids for Efficient Carbon Dioxide Capture and Subsequent Conversion Under Mild Conditions

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SSRN 2024年

作者： Wang, Litian Chen, Jie Wang, Shuai Zhou, Tongyao Li, Dan Li, Cuiping Qian, Lirong Xiong, Yang Miao, Lin Xie, Zhiyong Tianjin Key Laboratory of Film Electronic and Communication Devices School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China China Tianjin Bohua Yongli Chemical Industry CO. Ltd Tianjin30045 China

Protic ionic liquids (PILs) have emerged as innovative solvents with significant potential for CO2 capture and transformation, presenting a sustainable alternative to conventional methods which often involve energy-intensive processes or environmentally detrimental chemicals. Herein, a novel strategy for CO2 capture and conversion at mild conditions using non-stoichiometric protic ionic liquids (NPILs) was demonstrated for the first time. These NPILs, employed as sorbents, solvents, and catalysts, were composed of imidazole (Im) and 1,8-diazabicyclo [5.4.0] undec-7-ene (DBU) in various ratios. Correlations between the mole ratio of DBU/Im and physicochemical properties such as viscosity, conductivity, thermal stability, and the distribution of neutral and ionic species were systematically investigated. Effects of the absorption temperature and CO2 partial pressure on the absorption capacity were also studied. Different absorption mechanisms, including carbonate and carbamate pathways, were analyzed using FT-IR and NMR spectroscopy. Moreover, the fixed CO2 could be catalytically converted to quinazoline-2,4(1H,3H)-diones under exceptionally mild reaction conditions (1atm, 50 °C, metal-free process). A plausible reaction mechanism involving simultaneous CO2 activation and substrate activation for the transformation of CO2 into quinazoline-2,4(1H,3H)-diones was verified through NMR spectra. It is believed that the new insights into the CO2 mechanism will facilitate the rationaldesign of functional ionic liquids for CO2 capture, utilization, and storage in the future. © 2024, The Authors. All rights reserved.

关键词： Carbon dioxide

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Artificial Intelligence in reactor Physics: Current Status and Future Prospects

arXiv

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arXiv 2025年

作者： Zhang, Ruizhi Zhu, Shengfeng Wang, Kan She, Ding Argaud, Jean-Philippe Bouriquet, Bertrand Li, Qing Gong, Helin School of Mathematical Sciences Shanghai Key Laboratory of Pure Mathematics and Mathematical Practice East China Normal University Shanghai200241 China Department of Engineering Physics Tsinghua University Beijing100084 China Électricité de France R&D 7 boulevard Gaspard Monge Palaiseau91120 France Électricité de France DQI 2 rue Ampère Saint-Denis93206 France Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610041 China Paris Elite Institute of Technology Shanghai Jiao Tong University Shanghai200240 China

reactor physics is the study of neutron properties, focusing on using models to examine the interactions between neutrons and materials in nuclear reactors. Artificial intelligence (AI) has made significant contributions to reactor physics, e.g., in operational simulations, safety design, real-time monitoring, core management and maintenance. This paper presents a comprehensive review of AI approaches in reactor physics, especially considering the category of Machine Learning (ML), with the aim of describing the application scenarios, frontier topics, unsolved challenges and future research directions. From equation solving and state parameter prediction to nuclear industry applications, this paper provides a step-by-step overview of ML methods applied to steady-state, transient and combustion problems. Most literature works achieve industry-demanded models by enhancing the efficiency of deterministic methods or correcting uncertainty methods, which leads to successful applications. However, research on ML methods in reactor physics is somewhat fragmented, and the ability to generalize models needs to be strengthened. Progress is still possible, especially in addressing theoretical challenges and enhancing industrial applications such as building surrogate models and digital twins. Copyright © 2025, The Authors. All rights reserved.

关键词： Nuclear industry

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Numerical Trajectory Planning of Panel Installation with Optimal Energy Consumption for Redundant Articulating Crane

SSRN

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SSRN 2024年

作者： Li, Penghao Zhang, Bangji Zhang, Zheshuo Hu, Wen Zhang, Jie Dai, Di State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha China Intelligent Transportation System Research Center Hangzhou City University Hangzhou China School of Vehicle and Mobility Tsinghua University Beijing China College of Automotive and Mechanical Engineering Changsha University of Science and Technology Changsha China

The automatic installation of panels has become crucial in numerous industries scenarios. This paper proposed a trajectory planning method to addresses the position and posture adjustment of panel installation using redundant articulating cranes. Configuration space of the crane and rotation matrix are combined to investigate the strong coupling of the panel's position and posture. Moreover, the study combines the motion modes of the crane with the sequential analysis of redundant motion to assess energy consumption, incorporating energy efficiency as one of the planning objectives. Simultaneously, an intrinsic connection between the motion sequences within the C-space and safety considerations is analyzed. The installation experiment is performed with a real crane. The experimental results indicate that the proposed method achieves the function of installation of panels, which can make both the panel’s position and posture safely reach the predetermined state with less energy consume. © 2024, The Authors. All rights reserved.

关键词： Cranes

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Effect of thermal-hydraulic parameters and pH on the corrosion product deposition in steam generator based on CFD

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Annals of Nuclear Energy 2025年 223卷

作者： Yunchen Lai Haiyan Xie Shiyu Tan Ke Wang Dongyun Li Xuesong Li Yang Gao Hongguo Hou Nan Chao Caishan Jiao Yu Zhou Fundamental Science on Nuclear Safety and Simulation Technology Laboratory College of Nuclear Science and Technology Harbin Engineering University Harbin 150001 Heilongjiang Province China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu 610041 Sichuan Province China

The deposition of corrosion products in the primary circuit of a pressurized water reactors is known to have an adverse impact on reactor system’s performance, which can cause localized corrosion. They can also impede the flow of coolant, or in severe cases block the tube channels. Besides, the deposits have a lower thermal conductivity than the structural materials, which may increase the thermal resistance, thus reducing heat transfer efficiency. Despite the presence of a considerable amount of corrosion products in steam generators, research on the deposition of corrosion products within is still insufficient. A comprehensive 3-D model of thermal–hydraulic and chemical processes was used to investigate the factors affecting the deposition of corrosion products in a steam generator. For the purpose of determine the deposition distribution along the heat transfer tube, the tube was separated into 11 main nodes based on the equal temperature differences according to the thermal–hydraulic data calculated. The simulation results indicate that the deposition thickness is sensitive to coolant temperature, flow velocity and pH value, and it was shown that higher temperature(from 560 K to 600 K decreasing 9.31 %), pH value (from 6.5 to 8.0 decreasing 9.92 %) and lower flow velocity (from 5 m/s to 20 m/s increasing 8.13 %)was effective for reducing the corrosion product deposition due to the physicochemical properties of the coolant and the turbulent flow, while working pressure has less influence on it(from 6 MPa to 15 MPa increasing only 1.03 %).

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Small-Target Infrastructure Detection with Spatial Tracking and Multi-Level Feature Extraction of Railway Track Scenes

Small-Target Infrastructure Detection with Spatial Tracking ...

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Intelligent Communication, Sensing and Electromagnetics (ICSE), International Conference on

作者： Heng Du Huaiming Cang Yiwen Bai Xinyi Wang Beijing Elephant Technology Co. Ltd Beijing China School of Transportation Science and Engineering Beihang University Beijing China The State Key Lab of Intelligent Transportation System Beijing China Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin China

ISBN: (数字)9798350354935

ISBN: (纸本)9798350354942

In the field of railway transportation, with the continuous improvement of train running speed and the continuous increase of operating mileage, it becomes particularly important to ensure the safety and integrity of small-target infrastructure along the railway train. Although many small-target detection methods have been proposed, the research on small-target infrastructure detection along rail trains is very rare. To solve this problem, this paper proposes a small-target infrastructure detection network with spatial tracking and multi-level feature extraction based on Yolov8n. The experimental results show that ST-YOLO has a 3.6% mAP improvement on the OSDaR23 dataset compared to the baseline Yolov8n, and shows significant advantages over other state-of-the-art methods.

关键词： Rails Transportation Railway safety Switches Feature extraction Rail transportation Real-time systems Sensors Safety Monitoring

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