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3D particle streak velocimetry by defocused imaging

Particuology 2023年第1期72卷 1-9页

作者： Xiangrui Dong Xiaoxiao Wang Wu Zhou Fangting Wang Xinran Tang Xiaoshu Cai School of Energy and Power Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Multiphase Flow and Heat Transfer for Power Engineering Shanghai 200093China

Particle streak velocimetry (PSV) has become one of the important branches of flow filed measurements. It extracts velocity information from particle trajectories captured by single frame long exposure images. Since the defocus of moving particle is inevitable during a long exposure time and under a large magnification, a novel three-dimensional (3D) velocity measurement method named defocusing particle streak velocimetry (DPSV) is proposed in this paper. On the one hand, an extension from two-dimensional (2D) to 3D velocity measurement with a monocular system is carried out. The depth information of the particle, which reflects the position in the third dimension, is indicated by the defocusing degree (characteristic parameter σ) of the particle images. The variation of σ along the trajectory is recognized by surface fitting of the gray value distribution of particle images, assuming that σ varies linearly along the trajectory. On the other hand, based on the linear fitting for the straight trajectory, an arc fitting model is developed for curved trajectories which are commonly captured in turbulent flow. The relationship between σ and the particle depth position z is experimentally calibrated using a LED light and a diaphragm. Finally, the DPSV method is verified in a submerged jet flow field as well as in a microchannel flow field to obtain the 3D velocity field with single monocular system.

关键词： Defocusing particle streak velocimetry Curve trajectory Three-dimensional velocity Gray value distribution

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Research on vorticity driven reward for active flow control over airfoil based on deep reinforcement learning

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Journal of Hydrodynamics 2025年第1期37卷 124-137页

作者： Xiang-rui Dong Sun-yu You Qi Wang Jia-hao Zhu Zhi-hao Jin School of Energy and Power Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Multiphase Flow and Heat Transfer for Power Engineering University of Shanghai for Science and TechnologyShanghai 200093China

An intelligent flow control on the flow separation over an airfoil under weak turbulent conditions is investigated and solved by deep reinforcement learning(DRL)*** single and synthetic jet control at the airfoil angles of attack of 10°,13°,15°are compared by training a neural network for closed-loop active flow control strategy based on the soft actor-critic(SAC)*** training results demonstrate the effectiveness of the deep reinforcement learning-based active flow control method in suppressing the flow separation at high angles of attack,validating its potential in complex flow *** improve the stability of the shedding vortex alley over airfoil,a novel reward function considering the vorticity statistics in terms of both vortex and asymmetric shear intensity is first proposed in this *** vorticity driven reward is demonstrated to perform better in suppressing the rotation and shear intensity and the aerodynamic optimization than the traditional ***,it can accelerate the convergence speed during the exploration ***,it can accelerate the convergence speed during the exploration *** study provides valuable insights for future applications of DRL in active flow control under more complex flow conditions.

关键词： Fluid mechanics flow control deep reinforcement learning(DRL) multiple attack angle synthetic jet

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Uncertainty and sensitivity analysis of in-vessel phenomena under severe accident mitigation strategy based on ISAA-SAUP program

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Nuclear Science and Techniques 2024年第1期35卷 108-123页

作者： Hao Yang Ji-Shen Li Zhi-Ran Zhang Bin Zhang Jian-Qiang Shan School of Nuclear Science and Technology Xi’an Jiaotong UniversityXi’an 710049China State Key Laboratory of Multiphase Flow in Power Engineering Xi’an Jiaotong UniversityXi’an 710049China

The phenomenology involved in severe accidents in nuclear reactors is highly ***,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce considerable ***,in recent years,the field of severe accidents has shifted its focus toward applying uncertainty analysis methods to quantify uncertainty in safety assessment programs,known as“best estimate plus uncertainty(BEPU).”This approach aids in enhancing our comprehension of these programs and their further development and *** study concentrates on a third-generation pressurized water reactor equipped with advanced active and passive mitigation *** an Integrated Severe Accident Analysis Program(ISAA),numerical modeling and uncertainty analysis were conducted on severe accidents resulting from large break loss of coolant *** uncertainty parameters of the ISAA program were meticulously *** Wilks'formula,the developed uncertainty program code,SAUP,was employed to carry out Latin hypercube sampling,while ISAA was employed to execute batch *** analysis was then conducted on two figures of merit,namely hydrogen generation and the release of fission products within the pressure *** calculations revealed that hydrogen production and the fraction of fission product released exhibited a normal distribution,ranging from 182.784 to 330.664 kg and from 15.6 to 84.3%,*** ratio of hydrogen production to reactor thermal power fell within the range of 0.0578–0.105.A sensitivity analysis was performed for uncertain input parameters,revealing significant correlations between the failure temperature of the cladding oxide layer,maximum melt flow rate,size of the particulate debris,and porosity of the debris with both hydrogen generation and the release of fission products.

关键词： Gen-III PWR Severe accident mitigation Wilks’formula Hydrogen Fission products Uncertainty and sensitivity analysis

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Synergistic effect of oxygen species and vacancy for enhanced electrochemical CO_(2) conversion to formate on indium oxide

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eScience 2024年第3期4卷 134-141页

作者： Tengfei Ma Zihao Jiao Haoran Qiu Feng Wang Ya Liu Liejin Guo International Research Center for Renewable Energy State Key Laboratory of Multiphase Flow in Power EngineeringXi'an Jiaotong UniversityXi'an 710049China

Indium-based oxides are promising electrocatalysts for producing formate via CO_(2) reduction reaction,in which*OCHO is considered the key ***,we identified that the*COOH pathway could be preferential to produce formate on In_(2)O_(3)of In/In_(2)O_(3) heterojunction due to the synergistic effect of oxygen species and ***,*CO_(2) and *COOH were observed on In_(2)O_(3) and related to formate production by in situ Raman *** theoretical calculations further demonstrated that the energy barrier of the*COOH formation on In_(2)O_(3) was decreased in the presence of oxygen vacancy,similar to or lower than that of the*OCHO formation on the In *** a result,a formate selectivity of over 90%was obtained on prepared In/In_(2)O_(3) heterojunction with 343±7mAcm^(-2) partial current ***,when using a Si-based photovoltaic as an energy supplier,10.11%solar-to-fuel energy efficiency was achieved.

关键词： Electrocatalytic CO_(2)reduction Formate In_(2)O_(3) Oxygen species Oxygen vacancy

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An active learning workflow for predicting hydrogen atom adsorption energies on binary oxides based on local electronic transfer features

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Green Energy & Environment 2024年第10期9卷 1489-1496页

作者： Wenhao Jing Zihao Jiao Mengmeng Song Ya Liu Liejin Guo International Research Center for Renewable Energy State Key Laboratory of Multiphase Flow in Power EngineeringXi'an Jiaotong UniversityShaanxi710049Xi'anChina Department of Energy and Power Engineering Shandong University of TechnologyZibo255000ShandongChina

Machine learning combined with density functional theory(DFT)enables rapid exploration of catalyst descriptors space such as adsorption energy,facilitating rapid and effective catalyst ***,there is still a lack of models for predicting adsorption energies on oxides,due to the complexity of elemental species and the ambiguous coordination *** work proposes an active learning workflow(LeNN)founded on local electronic transfer features(e)and the principle of coordinate rotation *** accurately characterizing the electron transfer to adsorption site atoms and their surrounding geometric structures,LeNN mitigates abrupt feature changes due to different element types and clarifies coordination *** a result,it enables the prediction of^(*)H adsorption energy on binary oxide surfaces with a mean absolute error(MAE)below 0.18 ***,we incorporate local coverage(θ_(l))and leverage neutral network ensemble to establish an active learning workflow,attaining a prediction MAE below 0.2 eV for 5419 multi-^(*)H adsorption *** findings validate the universality and capability of the proposed features in predicting^(*)H adsorption energy on binary oxide surfaces.

关键词： Machine learning Adsorption energy Binary oxide Electron transfer Active learning

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Numerical simulation of local and global mixing/segregation characteristics in a gas–solid fluidized bed

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Chinese Journal of Chemical engineering 2022年第4期35卷 72-86页

作者： Zhen Wan Youjun Lu State Key Laboratory of Multiphase Flow in Power Engineering Xi’an Jiaotong UniversityXi’an 710049China

Researches on solids mixing and segregation are of great significance for the operation and design of fluidized bed *** this paper,the local and global mixing and segregation characteristics of binary mixtures were investigated in a gas–solid fluidized bed by computational fluid dynamics-discrete element method(CFD-DEM)coupled approach.A methodology based on solids mixing entropy was developed to quantitatively calculate the mixing degree and time of the *** mixing curves of global mixing entropy were acquired,and the distribution maps of local mixing entropy and mixing time were also *** comparing different operating conditions,the effects of superficial gas velocity,particle density ratio and size ratio on mixing/segregation behavior were *** showed that for the partial mixing state,the fluidized bed can be divided into three parts along the bed height:complete segregation area,transition area and stable mixing *** areas showed different mixing/segregation *** gas velocity promoted the local and global mixing of binary *** increase in particle density ratio and size ratio enlarged the complete segregation area,reduced the mixing degree and increased the mixing time in the stable mixing area.

关键词： Discrete element method Solids mixing Binary mixtures Fluidized bed

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Development of a fan-stirred constant volume combustion chamber and turbulence measurement with PIV

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Frontiers in Energy 2022年第6期16卷 973-987页

作者： Haoran ZHAO Jinhua WANG Xiao CAI Zhijian BIAN Hongchao DAI Zuohua HUANG State Key Laboratory of Multiphase Flow in Power Engineering Xi’an Jiaotong UniversityXi’an 710049China

A fan-stirred combustion chamber is developed for spherically expanding flames,with P and T up to 10 bar and 473 K,*** characteristics are estimated using particle image velocimetry(PIV)at different initial pressures(P=0.5-5 bar),fan frequencies(ω=0-2000 r/min),and impeller diameters(D=100 and 114 mm).The flame propagation of methanol/air is investigated at different turbulence intensities(u′=0-1.77 m/s)and equivalence ratios(f=0.7-1.5).The results show that u′is independent of P and proportional toω,which can be up to 3.5 m/s at 2000 r/min.L_(T)is independent of P and performs a power regression withω*** turbulent field is homogeneous and isotropic in the central region of the chamber while the inertial subrange of spatial energy spectrum is more collapsed to-5/3 law at a high Re_(T).Compared to laminar expanding flames,the morphology of turbulent expanding flames is wrinkled and the wrinkles will be finer with the growth of turbulence intensity,consistent with the decline of the Taylor scale and the Kolmogorov *** determined S_(L)in the present study is in good agreement with that of previous *** S_(L)and S_(T)of methanol/air have a non-monotonic trend with f while peak S_(T)is shifted to the richer side compared to S_(L).This indicates that the newly built turbulent combustion chamber is reliable for further experimental study.

关键词： fan-stirred combustion chamber turbulence characteristics particle image velocimetry(PIV) methanol turbulent expanding flames

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Optimization of cold-end system of thermal power plants based on entropy generation minimization

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Frontiers in Energy 2022年第6期16卷 956-972页

作者： Yue FU Yongliang ZHAO Ming LIU Jinshi WANG Junjie YAN State Key Laboratory of Multiphase Flow in Power Engineering Xi’an Jiaotong UniversityXi’an 710049China

Cold-end systems are heat sinks of thermal power cycles,which have an essential effect on the overall performance of thermal power *** enhance the efficiency of thermal power plants,multi-pressure condensers have been applied in some large-capacity thermal power ***,little attention has been paid to the optimization of the cold-end system with multi-pressure condensers which have multiple parameters to be ***,the design optimization methods of coldend systems with single-and multi-pressure condensers are developed based on the entropy generation rate,and the genetic algorithm(GA)is used to optimize multiple *** parameters,including heat transfer area of multi-pressure condensers,steam distribution in condensers,and cooling water mass flow rate,are optimized while considering detailed entropy generation rate of the cold-end *** results show that the entropy generation rate of the multi-pressure cold-end system is less than that of the single-pressure cold-end system when the total condenser area is ***,the economic performance can be improved with the adoption of the multi-pressure cold-end *** compared with the single-pressure cold-end system,the excess revenues gained by using dual-and quadruplepressure cold-end systems are 575 and 580 k$/a,respectively.

关键词： cold-end system entropy generation minimization optimization economic analysis genetic algorithm(GA)

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Reconstruction of particle distribution for tomographic particle image velocimetry based on unsupervised learning method

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Particuology 2024年第10期93卷 349-363页

作者： Duanyu Zhang Haoqin Huang Wu Zhou Mingjun Feng Dapeng Zhang Limin Gao School of Energy and Power Engineering University of Shanghai for Science and TechnologyShanghai200093China Shanghai Key Laboratory of Multiphase Flow and Heat Transfer for Power Engineering University of Shanghai for Science and TechnologyShanghai200093China National Key Laboratory of Aerodynamic Design and Research Northwestern Polytechnical UniversityXi'an710072China

The development of deep learning has inspired some new methods to solve the 3D reconstruction problem for Tomographic Particle Image Velocimetry (Tomo-PIV). However, the supervised learning method requires a large number of data with ground truth as training information, which is very difficult to gather from experiments. Although synthetic datasets can be used as alternatives, they are still not exactly the same with the real-world experimental data. In this paper, an Unsupervised Reconstruction Technique based on U-net (UnRTU) is proposed to reconstruct volume particle distribution explicitly. Instead of using ground truth data, a projection function is used as an unsupervised loss function for network training to reconstruct particle distribution. The UnRTU was compared with some traditional algebraic reconstruction algorithms and supervised learning method using synthetic data under different particle density and noise level. The results indicate that UnRTU outperforms these traditional approaches in both reconstruction quality and noise robustness, and is comparable to the supervised learning methods AI-PR. For experimental tests, particles dispersed in cured epoxy resin are moved by an electric rail with a certain speed to obtain the ground truth data of particle velocity. Compared with other algorithms, the reconstructed particle distribution by UnRTU has the best reconstruction fidelity. And the accuracy of the 3D velocity field estimated by UnRTU is 12.9% higher than that from the traditional MLOS-MART algorithm. It demonstrates significant potential and advantages for UnRTU in 3D reconstruction of particle distribution. Finally, UnRTU was successfully applied to the high-speed planar cascade airflow field, demonstrating its applicability for measuring complex fluid flow fields at higher particle density.

关键词： Tomographic particle image velocimetry 3D reconstruction Unsupervised learning Convolutional neural network

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Lattice-mismatch-induced formation of defect-rich Pd-Cu alloy nanocages for enhanced formic acid oxidation activity

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Science China Chemistry 2025年第2期68卷 481-491页

作者： Zhaojun Liu Zhengyan Wang Zhaoyu Wang Hao Yuan Yuke Bai Xiaoxiao Wang Zerui Mu Chunxia Wu Kai Liu Zhun Hu Chuanbo Gao Sate Key Laboratory of Multiphase Flow in Power Engineering Frontier Institute of Science and TechnologyXi’an Jiaotong UniversityXi’an 710049China Institute of Industrial Catalysis School of Chemical Engineering and TechnologyXi’an Jiaotong UniversityXi’an 710049China

Crystallographic defects in noble metal nanocrystals are recognized as highly active catalytic sites,significantly enhancing activities in many important *** their importance,synthesizing noble metal nanocrystals with a high density of defects poses a considerable synthetic ***,we present a novel lattice mismatch-induced formation mechanism to create high-density defects in noble metal *** approach takes advantage of lattice mismatch to enable nonepitaxial nucleation and growth of a noble metal on a foreign metal substrate,forming abundant noble metal crystallites with random lattice orientations not dictated by the substrate *** these crystallites grow extensively,they merge,forming numerous grain boundaries and yielding defect-rich noble metal ***-rich alloy nanocrystals can also be synthesized through a subsequent vacancy-diffusion alloying *** take defective PdCu alloy nanocages as an example and demonstrate the effectiveness of crystallographic defects in enhancing catalytic performance of noble metal *** nanocages exhibit superior activity in the electrocatalytic formic acid oxidation reaction,which is 1.6 times greater than their defect-free *** strategy offers a new avenue for creating defect-rich noble metal nanocrystals as highly efficient catalysts for a wide array of catalytic applications.

关键词： noble metal nanocrystals defects non-epitaxial growth electrocatalysis formic acid oxidation reaction

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