A piggyback pipeline is a special configuration of offshore pipelines for offshore oil and gas exploration and is characterized by the coupling of a large-diameter pipe with a small-diameter pipe. This study conducts ...A piggyback pipeline is a special configuration of offshore pipelines for offshore oil and gas exploration and is characterized by the coupling of a large-diameter pipe with a small-diameter pipe. This study conducts a numerical investigation of the transverse VIV characteristics of a piggyback pipeline at low Reynolds numbers, as the vortex shedding modes and vibration characteristics can be accurately represented under laminar flow conditions with minimal computational expense. The effects of influential factors, such as the mass ratio, position angle of the small pipe relative to the main pipe, and Reynolds number, on the VIV amplitude, frequency, vibration center, and mean lift coefficient are specifically examined. The results indicate that the mass ratio has a limited effect on the maximum VIV amplitude. However, as the mass ratio decreases, the lock-in region expands, and the vibration center of the piggyback pipeline deviates further from its original position. The VIV amplitude is minimized, and the lock-in region is the narrowest at a position angle of 45°, whereas the vibration center reaches its maximum displacement at a position angle of 135°. As the Reynolds number increases, the VIV amplitude slightly increases, accompanied by convergence of the vibration center toward its initial position. The mean lift coefficient and wake vortices are also analyzed to establish a connection with the vibration characteristics of the piggyback pipeline. The optimal configuration of the piggyback pipeline is also proposed on the basis of the present numerical results.展开更多
The effects of Reynolds number on the compressor efficiency are investigated by tests on three highlyloaded 10-stage axial compressors.The tests are conducted by adjusting the inlet total pressure,and thus different R...The effects of Reynolds number on the compressor efficiency are investigated by tests on three highlyloaded 10-stage axial compressors.The tests are conducted by adjusting the inlet total pressure,and thus different Reynolds numbers are obtained.The results indicate that the compressor efficiency decreases when the Reynolds number decreases.Based on the test results,reasonable correlations between the Reynolds number and compressor efficiency for each of the three compressors are obtained.The comparison between the test result-deduced correlations and Wassell correlations indicates that the effects of Reynolds number on the efficiency predicted by the Wassell correlations are less than those obtained by the test result-deduced correlations.Owing to the complex loss models and flow behavior in highly-loaded multi-stage compressors,additional influence factors,including the tip clearance and the compressor inlet duct design,should be considered for performance correlations.Nevertheless,the Wassell correlations are valid for the tendency prediction of performance changes relating to the Reynolds number,while accurate correlations still largely depend on the specific test results.展开更多
In this paper,we define the cohomology of a Reynolds Leibniz algebra with coefficients in a suitable representation.We also introduce the notion of Reynolds Leibniz 2-algebras,and prove that strict Reynolds Leibniz 2-...In this paper,we define the cohomology of a Reynolds Leibniz algebra with coefficients in a suitable representation.We also introduce the notion of Reynolds Leibniz 2-algebras,and prove that strict Reynolds Leibniz 2-algebras are equivalent to crossed modules of Reynolds Leibniz algebras.展开更多
Analysing the influence mechanism of the riblet protrusion height on turbulent drag components is more beneficial in organising the vortical structure over the riblet surface.Therefore, the Large Eddy Simulation(LES) ...Analysing the influence mechanism of the riblet protrusion height on turbulent drag components is more beneficial in organising the vortical structure over the riblet surface.Therefore, the Large Eddy Simulation(LES) is used to investigate the vortex structure over the riblet surface with different protrusion heights. Then, the variations of Reynolds stress and viscous shear stress in a turbulent channel are analysed. As a result, the drag reduction rate increases from3.4% when the riblets are completely submerged in the turbulent boundary layer to 7.9% when the protrusion height is 11.2. Further analysis shows that the protrusion height affects the streamwise vortices and the normal diffusivity of spanwise and normal vortices, thus driving the variation of Reynolds stress. Compared with the smooth surface, the vorticity strength and the number of streamwise vortices are weakened near the wall but increase in the logarithmic layer with increased protrusion height. Meanwhile, the normal diffusivity of spanwise vorticity decreases with the increase of protrusion height, and the normal diffusivity of normal vorticity is the smallest when the protrusion height is 11.2. Moreover, the protrusion height affects the velocity gradient of the riblet tip and riblet valley, thus driving the variation of viscous shear stress. With the increase of protrusion height, the velocity gradient of the riblet tip increases dramatically but decreases in the riblet valley.展开更多
The presentation and modeling of turbulence anisotropy are crucial for studying large-scale turbulence structures and constructing turbulence models.However,accurately capturing anisotropic Reynolds stresses often rel...The presentation and modeling of turbulence anisotropy are crucial for studying large-scale turbulence structures and constructing turbulence models.However,accurately capturing anisotropic Reynolds stresses often relies on expensive direct numerical simulations(DNS).Recently,a hot topic in data-driven turbulence modeling is how to acquire accurate Reynolds stresses by the Reynolds-averaged Navier-Stokes(RANS)simulation and a limited amount of data from DNS.Many existing studies use mean flow characteristics as the input features of machine learning models to predict high-fidelity Reynolds stresses,but these approaches still lack robust generalization capabilities.In this paper,a deep neural network(DNN)is employed to build a model,mapping from tensor invariants of RANS mean flow features to the anisotropy invariants of high-fidelity Reynolds stresses.From the aspects of tensor analysis and input-output feature design,we try to enhance the generalization of the model while preserving invariance.A functional framework of Reynolds stress anisotropy invariants is derived theoretically.Complete irreducible invariants are then constructed from a tensor group,serving as alternative input features for DNN.Additionally,we propose a feature selection method based on the Fourier transform of periodic flows.The results demonstrate that the data-driven model achieves a high level of accuracy in predicting turbulence anisotropy of flows over periodic hills and converging-diverging channels.Moreover,the well-trained model exhibits strong generalization capabilities concerning various shapes and higher Reynolds numbers.This approach can also provide valuable insights for feature selection and data generation for data-driven turbulence models.展开更多
A two-dimensional（2-D） incompressible plane jet is investigated using the lattice Boltzmann method（LBM） for low Reynolds numbers of 42 and 65 based on the jet-exit-width and the maximum jet-exit-velocity. The resu...A two-dimensional（2-D） incompressible plane jet is investigated using the lattice Boltzmann method（LBM） for low Reynolds numbers of 42 and 65 based on the jet-exit-width and the maximum jet-exit-velocity. The results show that the mean centerline velocity decays as x-1/3 and the jet spreads as x2/3 in the self-similar region, which are consistent with the theoretical predictions and the experimental data. The time histories and PSD analyses of the instantaneous centerline velocities indicate the periodic behavior and the interaction between periodic components of velocities should not be neglected in the far field region, although it is invisible in the near field region.展开更多
Reynolds推出了Reynolds方程以来,人们花费大量精力研究方程的封闭性。Taylor首先引入相关概念并提出各态历经假说。Prandtl提出著名的混合长度理论:Karman给出混合长度的另外形式。周培源(Chou P Y)对各向同性湍流做了大量研究工作,获...Reynolds推出了Reynolds方程以来,人们花费大量精力研究方程的封闭性。Taylor首先引入相关概念并提出各态历经假说。Prandtl提出著名的混合长度理论:Karman给出混合长度的另外形式。周培源(Chou P Y)对各向同性湍流做了大量研究工作,获得了满意的结果。最近高歌用侧偏系综平均取代Reynolds平均。展开更多
基金financially supported by the National Natural Science Foundation of China (Grant Nos. 52371289 and 51979192)。
文摘A piggyback pipeline is a special configuration of offshore pipelines for offshore oil and gas exploration and is characterized by the coupling of a large-diameter pipe with a small-diameter pipe. This study conducts a numerical investigation of the transverse VIV characteristics of a piggyback pipeline at low Reynolds numbers, as the vortex shedding modes and vibration characteristics can be accurately represented under laminar flow conditions with minimal computational expense. The effects of influential factors, such as the mass ratio, position angle of the small pipe relative to the main pipe, and Reynolds number, on the VIV amplitude, frequency, vibration center, and mean lift coefficient are specifically examined. The results indicate that the mass ratio has a limited effect on the maximum VIV amplitude. However, as the mass ratio decreases, the lock-in region expands, and the vibration center of the piggyback pipeline deviates further from its original position. The VIV amplitude is minimized, and the lock-in region is the narrowest at a position angle of 45°, whereas the vibration center reaches its maximum displacement at a position angle of 135°. As the Reynolds number increases, the VIV amplitude slightly increases, accompanied by convergence of the vibration center toward its initial position. The mean lift coefficient and wake vortices are also analyzed to establish a connection with the vibration characteristics of the piggyback pipeline. The optimal configuration of the piggyback pipeline is also proposed on the basis of the present numerical results.
文摘The effects of Reynolds number on the compressor efficiency are investigated by tests on three highlyloaded 10-stage axial compressors.The tests are conducted by adjusting the inlet total pressure,and thus different Reynolds numbers are obtained.The results indicate that the compressor efficiency decreases when the Reynolds number decreases.Based on the test results,reasonable correlations between the Reynolds number and compressor efficiency for each of the three compressors are obtained.The comparison between the test result-deduced correlations and Wassell correlations indicates that the effects of Reynolds number on the efficiency predicted by the Wassell correlations are less than those obtained by the test result-deduced correlations.Owing to the complex loss models and flow behavior in highly-loaded multi-stage compressors,additional influence factors,including the tip clearance and the compressor inlet duct design,should be considered for performance correlations.Nevertheless,the Wassell correlations are valid for the tendency prediction of performance changes relating to the Reynolds number,while accurate correlations still largely depend on the specific test results.
基金Supported by the National Natural Science Foundation of China(Grant No.12271292)。
文摘In this paper,we define the cohomology of a Reynolds Leibniz algebra with coefficients in a suitable representation.We also introduce the notion of Reynolds Leibniz 2-algebras,and prove that strict Reynolds Leibniz 2-algebras are equivalent to crossed modules of Reynolds Leibniz algebras.
基金the National Natural Science Foundation of China(No. 52176032)the Natural Science Foundation of Tianjin Municipal Science and Technology Commission, China(No. 22JCQNJC00050)the National Science and Technology Major Project, China(No.2017-Ⅱ-0005-0016)
文摘Analysing the influence mechanism of the riblet protrusion height on turbulent drag components is more beneficial in organising the vortical structure over the riblet surface.Therefore, the Large Eddy Simulation(LES) is used to investigate the vortex structure over the riblet surface with different protrusion heights. Then, the variations of Reynolds stress and viscous shear stress in a turbulent channel are analysed. As a result, the drag reduction rate increases from3.4% when the riblets are completely submerged in the turbulent boundary layer to 7.9% when the protrusion height is 11.2. Further analysis shows that the protrusion height affects the streamwise vortices and the normal diffusivity of spanwise and normal vortices, thus driving the variation of Reynolds stress. Compared with the smooth surface, the vorticity strength and the number of streamwise vortices are weakened near the wall but increase in the logarithmic layer with increased protrusion height. Meanwhile, the normal diffusivity of spanwise vorticity decreases with the increase of protrusion height, and the normal diffusivity of normal vorticity is the smallest when the protrusion height is 11.2. Moreover, the protrusion height affects the velocity gradient of the riblet tip and riblet valley, thus driving the variation of viscous shear stress. With the increase of protrusion height, the velocity gradient of the riblet tip increases dramatically but decreases in the riblet valley.
基金supported by the National Natural Science Foundation of China(Grant No.92152301).
文摘The presentation and modeling of turbulence anisotropy are crucial for studying large-scale turbulence structures and constructing turbulence models.However,accurately capturing anisotropic Reynolds stresses often relies on expensive direct numerical simulations(DNS).Recently,a hot topic in data-driven turbulence modeling is how to acquire accurate Reynolds stresses by the Reynolds-averaged Navier-Stokes(RANS)simulation and a limited amount of data from DNS.Many existing studies use mean flow characteristics as the input features of machine learning models to predict high-fidelity Reynolds stresses,but these approaches still lack robust generalization capabilities.In this paper,a deep neural network(DNN)is employed to build a model,mapping from tensor invariants of RANS mean flow features to the anisotropy invariants of high-fidelity Reynolds stresses.From the aspects of tensor analysis and input-output feature design,we try to enhance the generalization of the model while preserving invariance.A functional framework of Reynolds stress anisotropy invariants is derived theoretically.Complete irreducible invariants are then constructed from a tensor group,serving as alternative input features for DNN.Additionally,we propose a feature selection method based on the Fourier transform of periodic flows.The results demonstrate that the data-driven model achieves a high level of accuracy in predicting turbulence anisotropy of flows over periodic hills and converging-diverging channels.Moreover,the well-trained model exhibits strong generalization capabilities concerning various shapes and higher Reynolds numbers.This approach can also provide valuable insights for feature selection and data generation for data-driven turbulence models.
基金Supported by the National Nature Science Foundation of China(10472046)the Scientific Innova-tion Research of College Graduate in Jiangsu Province(CX08B-035Z)the Innovation and Excellence Foundation of Doctoral Dissertation of Nanjing University of Aeronautics and Astronautics(BCXJ08-01)~~
文摘A two-dimensional（2-D） incompressible plane jet is investigated using the lattice Boltzmann method（LBM） for low Reynolds numbers of 42 and 65 based on the jet-exit-width and the maximum jet-exit-velocity. The results show that the mean centerline velocity decays as x-1/3 and the jet spreads as x2/3 in the self-similar region, which are consistent with the theoretical predictions and the experimental data. The time histories and PSD analyses of the instantaneous centerline velocities indicate the periodic behavior and the interaction between periodic components of velocities should not be neglected in the far field region, although it is invisible in the near field region.
文摘Reynolds推出了Reynolds方程以来,人们花费大量精力研究方程的封闭性。Taylor首先引入相关概念并提出各态历经假说。Prandtl提出著名的混合长度理论:Karman给出混合长度的另外形式。周培源(Chou P Y)对各向同性湍流做了大量研究工作,获得了满意的结果。最近高歌用侧偏系综平均取代Reynolds平均。
