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A generative deep learning framework for airfoil flow field prediction with sparse data

Chinese Journal of Aeronautics 2022年第1期35卷 470-484页

作者： Haizhou WU Xuejun liu Wei AN hongqiang LYU MIIT Key Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Aerodynamic Noise Control Mianyang 621000China State Key Laboratory of Aerodynamics Mianyang 621000China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210023China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Deep learning has been probed for the airfoil performance prediction in recent years.Compared with the expensive CFD simulations and wind tunnel experiments,deep learning models can be leveraged to somewhat mitigate such expenses with proper means.Nevertheless,effective training of the data-driven models in deep learning severely hinges on the data in diversity and quantity.In this paper,we present a novel data augmented Generative Adversarial Network(GAN),daGAN,for rapid and accurate flow filed prediction,allowing the adaption to the task with sparse data.The presented approach consists of two modules,pre-training module and fine-tuning module.The pre-training module utilizes a conditional GAN(cGAN)to preliminarily estimate the distribution of the training data.In the fine-tuning module,we propose a novel adversarial architecture with two generators one of which fulfils a promising data augmentation operation,so that the complement data is adequately incorporated to boost the generalization of the model.We use numerical simulation data to verify the generalization of daGAN on airfoils and flow conditions with sparse training data.The results show that daGAN is a promising tool for rapid and accurate evaluation of detailed flow field without the requirement for big training data.

关键词： CFD Flow field Generative adversarial networks(GANs) Sparse data Supercritical airfoil

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A mesh optimization method using machine learning technique and variational mesh adaptation

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Chinese Journal of Aeronautics 2022年第3期35卷 27-41页

作者： Tingfan WU Xuejun liu Wei AN Zenghui HUANG hongqiang LYU MIITKey Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 211106China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210023China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Computational mesh is an important ingredient that affects the accuracy and efficiency of CFD numerical simulation.In light of the introduced large amount of computational costs for many adaptive mesh methods,moving mesh methods keep the number of nodes and topology of a mesh unchanged and do not increase CFD computational expense.As the state-of-the-art moving mesh method,the variational mesh adaptation approach has been introduced to CFD calculation.However,quickly estimating the flow field on the updated meshes during the iterative algorithm is challenging.A mesh optimization method,which embeds a machine learning regression model into the variational mesh adaptation,is proposed.The regression model captures the mapping between the initial mesh nodes and the flow field,so that the variational method could move mesh nodes iteratively by solving the mesh functional which is built from the estimated flow field on the updated mesh via the regression model.After the optimization,the density of the nodes in the high gradient area increases while the density in the low gradient area decreases.Benchmark examples are first used to verify the feasibility and effectiveness of the proposed method.And then we use the steady subsonic and transonic flows over cylinder and NACA0012 airfoil on unstructured triangular meshes to test our method.Results show that the proposed method significantly improves the accuracy of the local flow features on the adaptive meshes.Our work indicates that the proposed mesh optimization approach is promising for improving the accuracy and efficiency of CFD computation.

关键词： CFD Flow field Machine learning Moving mesh method Regression models Variational mesh adaptation

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Task assignment under constraint of timing sequential for cooperative air combat

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Journal of Systems Engineering and Electronics 2016年第4期27卷 836-844页

作者： Chengwei Ruan Zhongliang Zhou Hongqiang Liu Haiyan Yang Aeronautics and Astronautics Engineering College Air Force Engineering UniversityXi'an710038China College of Instrument Science and Technology Tsinghua UniversityBeijing100084China

According to the previous achievement, the task assignment under the constraint of timing continuity for a cooperative air combat is studied. An extensive task assignment scenario with the background of the cooperative air combat is proposed. The utility and time of executing a task as well as the continuous combat ability are defined. The concept of the matching method of weapon and target is modified based on the analysis of the air combat scenario. The constraint framework is also redefined according to a new objective function. The constraints of timing and continuity are formulated with a new method, at the same time, the task assignment and integer programming models of the cooperative combat are established. Finally, the assignment problem is solved using the integrated linear programming software and the simulation shows that it is feasible to apply this modified model in the cooperative air combat for tasks cooperation and it is also efficient to optimize the resource assignment.

关键词： cooperative air combat task assignment timing constraint task utility integer programming

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Influence of volume compression on the unloading deformation behavior of red sandstone under damage-controlled cyclic triaxial loading

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第5期15卷 1200-1212页

作者： Huaizhong liu Jianliang Pei Jianfeng liu Mingli Xiao Li Zhuo hongqiang Xie State Key Laboratory of Hydraulics and Mountain River Engineering College of Water Resources and HydropowerSichuan UniversityChengdu610065China

A reasonable evaluation of unloading deformation characteristics is of great significance for the effective analysis of deformation and stability of surrounding rocks after underground excavation.In this study,the damage-controlled cyclic triaxial loading tests were conducted to investigate the pore compaction mechanism and its influences on the unloading deformation behavior of red sandstone,including Young’s modulus,Poisson’s ratio,volumetric strain,and irreversible strain.The experimental results show that the increases of volumetric and irreversible strains of rocks can be attributed to the compaction mechanism,which almost dominates the entire pre-peak deformation process.The unloading deformation consists of the reversible linear and nonlinear strains,and the irreversible strain under the influence of the porous grain structure.The pre-peak Young’s modulus tends to increase and then decrease due to the influence of the unloading irreversible strain.However,it hardly changes with the increasing volumetric strain compaction under the influence of reversible nonlinear strain.Instead,the initial unloading tangent modulus is highly related to the volumetric strain,and clearly reflects the compaction state of red sandstone.Furthermore,both the reversible nonlinear and irreversible unloading deformations are independent of confining pressure.This study is beneficial for the theoretical modeling and prediction of cyclic unloading deformation behavior of red sandstone.

关键词： Cyclic loading tests Compaction mechanism Volumetric strain Unloading tangent modulus Red sandstone

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Change of Disease Spectrum Characteristics of Psychiatric Inpatients Before and After Lockdown Lifted During the COVID-19 Pandemic—Wuhan City,Hubei Province,China,2021

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China CDC weekly 2022年第18期4卷 389-392,I0002-I0004页

作者： Jingfang liu Xuan Gong Xiaofen Li Zhiying Wan hongqiang Sun Lijun Kang Zhongchun liu Department of Psychiatry Renmin Hospital of Wuhan UniversityWuhan CityHubei ProvinceChina Peking University Sixth Hospital Peking University Institute of Mental HealthNHC Key Laboratory of Mental Health(Peking University)National Clinical Research Center for Mental Disorders(Peking University Sixth Hospital)National Center for Mental HealthChinese Center for Disease Control and PreventionBeijingChina

Summary What is already known about this topic?The coronavirus disease 2019(COVID-19)pandemic poses a significant threat to mental health globally and may change the proportion of hospitalized patients.What is added by this report?This report analyzed and compared the disease characteristics of psychiatric inpatients one year before and after Wuhan lifted lockdown during COVID-19.About 50%of the inpatients were diagnosed with bipolar disorder;females and adolescents had a higher prevalence of mental disorders.What are the implications for public health practice?More attention should be paid to the mental health of children,adolescents,and females.

关键词： Wuhan globally COV

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Pseudogene HMGN2P46 as a microRNA sponge to regulate HMGN2 expression via competing for miR-590-3p in severe acute pancreatitis

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BIOCELL 2022年第5期46卷 1299-1308页

作者： hongqiang ZHAO QI liu HAORUN liu WEIMIN LI JIANGYANG LU Department of Pathology Fourth Medical Center of the Chinese PLA General HospitalBeijing100048China Translational Medicine Research Center Fourth Medical Center and Medical Innovation Research Division of the Chinese PLA General HospitalBeijing100048China Faculty of Hepato-Pancreato-Biliary Surgery Chinese PLA General HospitalBeijing100853China

HMGN2 have functions in inflammatory response.However,the role of HMGN2 in severe acute pancreatitis(SAP)remains unclear.Here,our study was to discuss the role and regulatory mechanism ofHMGN2 in SAP.In this study,the SAP cell model of AR42J was used to study the function and mechanism of HMGN2 in SAP.The protein expression in cells and serums were examined by western blot and ELISA assay.qPCR was used to test the transcriptional RNA level.Cell viability were examined by MTT assay.Luciferase assay was used to evaluate the interaction between gene and gene.Our results showed that HMGN2 was significantly upregulated in SAP patients.The database predicted and luciferase assay data indicated the HMGN2 was directly binding with miR-590-3p.ELISA,MTT and western blot experiments showed that the HMGN2 were promoted the cell proliferation,reduced the inflammation,and repressed the cell autophagy.Mechanism studies showed that the pseudogene HMGN2P46 level was positively correlated with HMGN2 and upregulated HMGN2 expression by competing for miR-590-3p in SAP.Taken together,all over these results showed upregulation of HMGN2 alleviates SAP,this process was regulated by HMGN2P46 competitively binding with miR-590-3p,which may provide a new insight for the treatment and intervention in SAP.Pseudogene HMGN2P46 was a miRNA sponge to regulate HMGN2 level by competing for miR-590-3p to alleviate the process of SAP.It provided a novel strategy for the diagnosis and treatment of severe acute pancreatitis.

关键词： HMGN2 Pseudogene Severe acute pancreatitis Inflammation miR-590-3p

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On developing data-driven turbulence model for DG solution of RANS

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Chinese Journal of Aeronautics 2019年第8期32卷 1869-1884页

作者： Liang SUN Wei AN Xuejun liu hongqiang LYU College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210093China

High-order Discontinuous Galerkin(DG) methods have been receiving more and more attentions in the area of Computational Fluid Dynamics(CFD) because of their high-accuracy property. However, it is still a challenge to obtain converged solution rapidly when solving the Reynolds Averaged Navier–Stokes(RANS) equations since the turbulence models significantly increase the nonlinearity of discretization system. The overall goal of this research is to develop an Artificial Neural Networks(ANNs) model with low complexity acting as an algebraic turbulence model to estimate the turbulence eddy viscosity for RANS. The ANN turbulence model is off-line trained using the training data generated by the widely used Spalart–Allmaras(SA) turbulence model before the Optimal Brain Surgeon(OBS) is employed to determine the relevancy of input features.Using the selected relevant features, a fully connected ANN model is constructed. The performance of the developed ANN model is numerically tested in the framework of DG for RANS, where the‘‘DG+ANN' method provides robust and steady convergence compared to the ‘‘DG+SA' method. The results demonstrate the promising potential to develop a general turbulence model based on artificial intelligence in the future given the training data covering a large rang of flow conditions.

关键词： Artificial neural network Discontinuous Galerkin method Fluid Optimal brain surgeon Spalart–Allmaras turbulence model

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Preparation and Performance of Chitosan/Citric Acid Modified Magnesium Oxychloride Cement

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Journal of Wuhan University of Technology(Materials Science) 2023年第6期38卷 1326-1334页

作者： SONG Zijian liu Lang YU Peipei ZHANG Yunsheng LI Xincheng CHU hongqiang JIANG Linhua College of Mechanics and Materials Hohai UniversityNanjing 2100China School of Civil Engineering Lanzhou University of TechnologyLanzhou 730050China Yunnan Institute of Building Research Co. LtdKunming 650223China

Citric acid(CA)and chitosan(CS)were employed to modify magnesium oxychloride cement(MOC).Multiscale measurements were implemented to study the properties of the modified MOC pastes.Results show that the addition of CA/CS significantly changes the content of each phase and the microstructure of phase 5.The single addition of CA can effectively increase the compressive strength of MOC after 7 d curing,while CS exerts no obvious effect on the compressive strength.As to the simultaneous addition of CA and CS,the compressive strength of MOC gradually decreases with the increasing content of CS.Interestingly,mixing CA and CS significantly enhances the water resistance of MOC and decreases the degradation rate of MOC in phosphate buffered solution,which can be ascribed to the low specific surface area of the plate-like crystals in the modified MOC and the reduction of pores in the structure.

关键词： magnesium oxychloride cement modifier citric acid chitosan

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A discrete element exploration of V-shaped breakout failure mechanisms in underground opening

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Underground Space 2020年第4期5卷 281-291页

作者： Huaizhong liu Jeen-Shang Lin Jiangda He hongqiang Xie State Key Laboratory of Hydraulics and Mountain River Engineering College of Water Resources and HydropowerSichuan UniversityChengdu 610065SichuanChina Department of Civil and Environmental Engineering University of PittsburghPittsburghPA 15261USA Department of Mechanical Engineering and Material Science University of PittsburghPittsburghPA 15261USA Department of Bioengineering University of PittsburghPittsburghPA 15261USA

V-shaped breakouts,which may appear in underground opening during excavation,are the results of two different failure mechanisms:tensile spalling and shear fracturing.This study uses discrete elements in exploring the conditions that would lead to different breakout mechanisms under plane strain conditions.The test tunnel of the Mine-by Experiment in Lac du Bonnet granite batholith is adopted as the base problem.In order to carry out the study,some fundamental issues need to be addressed.First,an exponential softening bond that enables the incorporation of fracture energy is adopted.In order to obtain a reasonable ratio between the uniaxial compressive strength,rc,and the uniaxial tensile strength,rt,discrete disc particles are tied together to form an irregular shape clump as the basic discrete element.This effort is supported by a successful reproducing of test results from Lac du Bonnet granite in DEM modeling.The issue of sensitivity of discrete particle size on results is examined.The reduction of strength with increase in specimen size is also modeled.After the calibration work is completed,the Mine-by tunnel behavior is studied.Finally,this study shows that a reduction in rc/rt ratio,under the same setup,would cause the failure mechanism to transit from tensile spalling to shear fracturing in V-shaped breakouts.

关键词： Tensile spalling Shear fracturing V-shaped breakouts Mine-by tunnel Discrete element method

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Research on a Composite Biomass Insulation Material with Geopolymers as Binders and Forestry Waste as Fillers

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Journal of Thermal Science 2022年第2期31卷 590-605页

作者： LI hongqiang ZOU Si liu Tiantian WANG Shuang ZOU Jun ZHANG Xiaofeng liu Lifang BAI Chengying ZHANG Guoqiang College of Civil Engineering Hunan UniversityChangsha 410082China National Center for International Research Collaboration in Building Safety and Environment(NCIRCBSE) Hunan UniversityChangsha 410082China Key Laboratory of Building Safety and Energy Efficiency of the Ministry of Education Hunan UniversityChangsha 410082China State Key Laboratory of Plant Physiology and Biochemistry China Agricultural UniversityBeijing 100193China College of Energy and Power Engineering Changsha University of Science and TechnologyChangsha 410114China College of Civil Engineering Hunan University of Science and TechnologyXiangtan 411201China Key Laboratory of Superlight Materials and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001China

A composite biomass insulation material,which uses geopolymers as adhesives and forestry waste as fillers,was proposed and experimentally tested.The orthogonal experimental method was adopted to analyze the optimum theoretical oxide molar ratios and the mass ratio of mixing water to binder(m_(w2)/m__(B))for preparing geopolymers.The influences of curing regimes(including one-stage and two-stage curing methods)and m_(w2)/m_(B) ratios of the insulation materials on mechanical,thermal,and hydraulic performances were also studied by experiment.The results indicated that the optimum combination scheme of preparing geopolymers was molar ratio x_(SiO_(2))/x_(Na_(2)O)=3.3,x_(SiO_(2))/x_(Al_(2)O_(3))=3.2 and m_(w2)/m_(B)=0.5 with the highest mechanical strength of 34.21 MPa.Besides,the best curing conditions of the composite material were the curing temperatures of 85°C and 70°C under the two-stage curing regime,which could achieve the low heat conductivity of 0.123 and 0.125 W/(m·K),and the high mechanical strength of 1.70 MPa and 1.71 MPa,respectively.The optimum m_(w2)/m_(B)ratios of the biomass material were 0.5 to 0.55 with heat conductivity of 0.114 to 0.125 W/(m·K).This novel composite insulation material has satisfying physical performances,which is helpful for achieving building energy conservation.

关键词： sawdust forestry waste energy conservation prefabricated buildings composite biomass insulation materials

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