The acceleration self-starting performance of hypersonic inlets is of critical importance for the stable operation of scramjet engines. The occurrence of soft unstart during the transition from hard unstart to start is an important flow state that has yet to be fully elucidated. The stability mechanism and corresponding self-starting characteristics of soft unstart remain poorly understood, and there is a pressing need for detailed modeling research in this area. This paper presents a rapid prediction model for the self-starting Mach number of two-dimensional hypersonic inlets with soft critical unstart mode, fully considering the influence of various geometric parameters and Reynolds number in the internal contraction section, and achieving a quantitative analysis of the two-dimensional soft unstart critical flow field. Given the incoming flow conditions and the inlet geometry, the prediction model is capable of accurately representing the actual viscous unstart flow field. It can fully map the unstart separation bubble and its surrounding critical wave structures, and calculate the minimum pressure rise required to maintain the current scale of the main separation bubble and the pressure rise exerted on the unstart separation bubble by the current actual flow field structure. Comparing the relative magnitude of these two pressures determines whether the inlet can transition from soft unstart to start. The proposed prediction model was validated using results from unsteady numerical simulations. The predicted results align well with the simulation results and are significantly better than previous prediction methods.
{"title":"Prediction model for self-starting of hypersonic inlets with soft critical unstart mode","authors":"Shu-Zi Yang, Wen-Zhong Xie, Cheng-Long Xu","doi":"10.1063/5.0222577","DOIUrl":"https://doi.org/10.1063/5.0222577","url":null,"abstract":"The acceleration self-starting performance of hypersonic inlets is of critical importance for the stable operation of scramjet engines. The occurrence of soft unstart during the transition from hard unstart to start is an important flow state that has yet to be fully elucidated. The stability mechanism and corresponding self-starting characteristics of soft unstart remain poorly understood, and there is a pressing need for detailed modeling research in this area. This paper presents a rapid prediction model for the self-starting Mach number of two-dimensional hypersonic inlets with soft critical unstart mode, fully considering the influence of various geometric parameters and Reynolds number in the internal contraction section, and achieving a quantitative analysis of the two-dimensional soft unstart critical flow field. Given the incoming flow conditions and the inlet geometry, the prediction model is capable of accurately representing the actual viscous unstart flow field. It can fully map the unstart separation bubble and its surrounding critical wave structures, and calculate the minimum pressure rise required to maintain the current scale of the main separation bubble and the pressure rise exerted on the unstart separation bubble by the current actual flow field structure. Comparing the relative magnitude of these two pressures determines whether the inlet can transition from soft unstart to start. The proposed prediction model was validated using results from unsteady numerical simulations. The predicted results align well with the simulation results and are significantly better than previous prediction methods.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multiphase flows are prevalent in both natural and engineered systems. The study of multiphase flow problems using numerical simulation is challenging due to the presence of high nonlinearities and moving interfaces. In this paper, an improved multiphase smoothed particle hydrodynamics (SPH) model is proposed for simulating multiphase flows. In the improved multiphase SPH model, an improved interface repulsive force model is proposed to reduce the interpenetration of particles at the multiphase interface and make the multiphase interface smooth and clear, and an improved kernel gradient correction is introduced to optimize the computational results. In addition, the particle shifting technology is applied to make the particle distribution uniform. Five numerical examples including the Rayleigh–Taylor instability, non-Boussinesq lock-exchange problem, square droplet deformation, single bubble rise, and circular droplet oscillation are investigated to verify the correctness and effectiveness of the improved multiphase SPH model. The results demonstrate that the improved multiphase SPH approach is effective in modeling multiphase flows.
{"title":"An improved smoothed particle hydrodynamics method for modeling multiphase flows","authors":"Yongze Li, Ting Long","doi":"10.1063/5.0226148","DOIUrl":"https://doi.org/10.1063/5.0226148","url":null,"abstract":"Multiphase flows are prevalent in both natural and engineered systems. The study of multiphase flow problems using numerical simulation is challenging due to the presence of high nonlinearities and moving interfaces. In this paper, an improved multiphase smoothed particle hydrodynamics (SPH) model is proposed for simulating multiphase flows. In the improved multiphase SPH model, an improved interface repulsive force model is proposed to reduce the interpenetration of particles at the multiphase interface and make the multiphase interface smooth and clear, and an improved kernel gradient correction is introduced to optimize the computational results. In addition, the particle shifting technology is applied to make the particle distribution uniform. Five numerical examples including the Rayleigh–Taylor instability, non-Boussinesq lock-exchange problem, square droplet deformation, single bubble rise, and circular droplet oscillation are investigated to verify the correctness and effectiveness of the improved multiphase SPH model. The results demonstrate that the improved multiphase SPH approach is effective in modeling multiphase flows.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lei Gao, Yaoran Chen, Guohui Hu, Dan Zhang, Xiangyu Zhang, Xiaowei Li
Physical information neural network (PINN) provides an effective method for solving partial differential equations, and many variants have been derived, the most representative of which is backward compatible physical information neural network (BC-PINN). The core of BC-PINN is to use the prediction of the previous time period as the label data of the current time period, which leads to error accumulation in the process of backward compatibility. To solve this problem, a nested backward compatible physical information neural network (NBC-PINN) is proposed in this paper. NBC-PINN has an overlap region between the computation domain of the previous time period and the computation domain of the current time period, which is trained twice in total. Numerical experiments on four representative time-varying partial differential equations show that NBC-PINN can effectively reduce error accumulation, improve computational efficiency and accuracy, and improve the L2 relative error of the numerical solution with fewer residual allocation points. The development of NBC-PINN provides a theoretical basis for the scientific calculation of partial differential equations, and promotes the progress of PINN to a certain extent.
{"title":"Development of backward compatible physics-informed neural networks to reduce error accumulation based on a nested framework","authors":"Lei Gao, Yaoran Chen, Guohui Hu, Dan Zhang, Xiangyu Zhang, Xiaowei Li","doi":"10.1063/5.0223510","DOIUrl":"https://doi.org/10.1063/5.0223510","url":null,"abstract":"Physical information neural network (PINN) provides an effective method for solving partial differential equations, and many variants have been derived, the most representative of which is backward compatible physical information neural network (BC-PINN). The core of BC-PINN is to use the prediction of the previous time period as the label data of the current time period, which leads to error accumulation in the process of backward compatibility. To solve this problem, a nested backward compatible physical information neural network (NBC-PINN) is proposed in this paper. NBC-PINN has an overlap region between the computation domain of the previous time period and the computation domain of the current time period, which is trained twice in total. Numerical experiments on four representative time-varying partial differential equations show that NBC-PINN can effectively reduce error accumulation, improve computational efficiency and accuracy, and improve the L2 relative error of the numerical solution with fewer residual allocation points. The development of NBC-PINN provides a theoretical basis for the scientific calculation of partial differential equations, and promotes the progress of PINN to a certain extent.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a variant of the immersed boundary (IB) method that implements acoustic perturbation theory to model acoustically levitated fluid droplets. Instead of resolving sound waves numerically, our hybrid method solves acoustic scattering semi-analytically to obtain the corresponding time-averaged acoustic forces on the droplet. This framework allows the droplet to be simulated on inertial timescales of interest, and therefore works with much larger time steps than traditional compressible flow solvers. To benchmark this technique and demonstrate its utility, we implement the hybrid IB method for a single droplet in a standing wave. Simulated droplet shape deformations and streaming profiles agree with available theoretical predictions. Our simulations also yield insights into the streaming profiles for elliptical droplets, for which a comprehensive analytic solution does not yet exist.
{"title":"Dynamics of an acoustically levitated fluid droplet captured by a low-order immersed boundary method","authors":"Jacqueline B. Sustiel, David G. Grier","doi":"10.1063/5.0223790","DOIUrl":"https://doi.org/10.1063/5.0223790","url":null,"abstract":"We present a variant of the immersed boundary (IB) method that implements acoustic perturbation theory to model acoustically levitated fluid droplets. Instead of resolving sound waves numerically, our hybrid method solves acoustic scattering semi-analytically to obtain the corresponding time-averaged acoustic forces on the droplet. This framework allows the droplet to be simulated on inertial timescales of interest, and therefore works with much larger time steps than traditional compressible flow solvers. To benchmark this technique and demonstrate its utility, we implement the hybrid IB method for a single droplet in a standing wave. Simulated droplet shape deformations and streaming profiles agree with available theoretical predictions. Our simulations also yield insights into the streaming profiles for elliptical droplets, for which a comprehensive analytic solution does not yet exist.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The thermal effect of a single-dielectric-barrier-discharge plasma actuator under steady actuation is numerically investigated. A new actuator model is proposed and validated using experimental data. A discrete Galerkin method based on high-order flux reconstruction schemes is employed to solve the flow governing equations and the actuator model equations on unstructured quadrilateral grids. By comparing the induced heated and cold flow fields of the actuator with and without a plasma thermal source, its thermal effect is revealed. The actuator generates a thermal wall jet with rich vorticity, forming a monopolar starting vortex with a high-temperature and low-density core. Over time, the starting vortex becomes unstable and transforms into a dipole. Actuator heating enhances jet velocity and width, as well as vortex stability, while slowing down vorticity generation. The relative change in density and temperature fields due to actuator heating is four orders of magnitude greater than that without actuator heating. Additionally, the actuator heating causes the background thermodynamic fields to increase approximately linearly with time. Two stages in the actuator's thermal effect are distinguished due to time accumulation. Initially, the actuator heating minimally affects the monopolar starting vortex motion, and the temperature and density fields are treated as passive variables driven by the velocity field. During this stage, the momentum and thermal effects of the actuator can be studied separately. However, after the starting vortex becomes unstable, the actuator heating significantly impacts its motion and morphology, and these two effects are coupled with each other.
{"title":"Thermal effect on the flow induced by a single-dielectric-barrier-discharge plasma actuator under steady actuation","authors":"Longxiang Zhao, Zuoli Xiao, Feng Liu","doi":"10.1063/5.0220507","DOIUrl":"https://doi.org/10.1063/5.0220507","url":null,"abstract":"The thermal effect of a single-dielectric-barrier-discharge plasma actuator under steady actuation is numerically investigated. A new actuator model is proposed and validated using experimental data. A discrete Galerkin method based on high-order flux reconstruction schemes is employed to solve the flow governing equations and the actuator model equations on unstructured quadrilateral grids. By comparing the induced heated and cold flow fields of the actuator with and without a plasma thermal source, its thermal effect is revealed. The actuator generates a thermal wall jet with rich vorticity, forming a monopolar starting vortex with a high-temperature and low-density core. Over time, the starting vortex becomes unstable and transforms into a dipole. Actuator heating enhances jet velocity and width, as well as vortex stability, while slowing down vorticity generation. The relative change in density and temperature fields due to actuator heating is four orders of magnitude greater than that without actuator heating. Additionally, the actuator heating causes the background thermodynamic fields to increase approximately linearly with time. Two stages in the actuator's thermal effect are distinguished due to time accumulation. Initially, the actuator heating minimally affects the monopolar starting vortex motion, and the temperature and density fields are treated as passive variables driven by the velocity field. During this stage, the momentum and thermal effects of the actuator can be studied separately. However, after the starting vortex becomes unstable, the actuator heating significantly impacts its motion and morphology, and these two effects are coupled with each other.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The accelerating flat plate is a useful model for studying the drag-based flapping flight (where drag is used to provide the weight-supporting force or thrust). Previous studies have mainly focused on the high Reynolds number (Re) regime pertaining to the flight of relatively large insects and birds. In this study, we numerically investigate the unsteady drag and flows of a uniformly accelerating flat plate at low Re that is typical of miniature insect flight (Re = 10–40). The following is shown. Unlike high-Re cases where the acceleration effect on drag is insensitive to Re, at low Re, the effect exhibits a strong dependence on Re: As Re decreases below 100, the acceleration effect increases rapidly, becoming 33%–56% greater than that of high-Re cases in the Re range of 10–40, before gradually decreasing. A simple model that consists of the quasi-steady, added-mass, and history force terms is proposed for drag at low Re. The scalings of the quasi-steady and added-mass force terms are well known; we find that the history force term scales approximately with the square root of the acceleration and velocity. The above result that relatively large drag is produced by the accelerating wing at Re = 10–40 is especially interesting and might explain why miniature insects fly in this Re range.
加速平板是研究基于阻力的拍击飞行（利用阻力提供重量支撑力或推力）的有用模型。以往的研究主要集中在与相对较大的昆虫和鸟类飞行有关的高雷诺数 (Re) 机制。在本研究中，我们用数值方法研究了在低雷诺数（Re = 10-40）条件下均匀加速平板的非稳定阻力和流动，这是微型昆虫飞行的典型特征。结果如下。与加速度对阻力的影响对 Re 值不敏感的高 Re 值情况不同，在低 Re 值情况下，加速度对阻力的影响对 Re 值有很强的依赖性：当 Re 值减小到 100 以下时，加速度效应迅速增加，在 Re 值为 10-40 的范围内，加速度效应比高 Re 值情况下的加速度效应大 33%-56%，然后逐渐减小。针对低 Re 条件下的阻力，提出了一个由准稳定力、附加质量和历史力项组成的简单模型。准稳力和附加质量力项的标度是众所周知的；我们发现历史力项的标度近似于加速度和速度的平方根。上述结果特别有趣，即在 Re = 10-40 时，加速翼产生的阻力相对较大，这或许可以解释为什么微型昆虫会在此 Re 范围内飞行。
{"title":"Drag force on an accelerating flat plate at low Reynolds numbers","authors":"Wenjie Liu, Mao Sun","doi":"10.1063/5.0223050","DOIUrl":"https://doi.org/10.1063/5.0223050","url":null,"abstract":"The accelerating flat plate is a useful model for studying the drag-based flapping flight (where drag is used to provide the weight-supporting force or thrust). Previous studies have mainly focused on the high Reynolds number (Re) regime pertaining to the flight of relatively large insects and birds. In this study, we numerically investigate the unsteady drag and flows of a uniformly accelerating flat plate at low Re that is typical of miniature insect flight (Re = 10–40). The following is shown. Unlike high-Re cases where the acceleration effect on drag is insensitive to Re, at low Re, the effect exhibits a strong dependence on Re: As Re decreases below 100, the acceleration effect increases rapidly, becoming 33%–56% greater than that of high-Re cases in the Re range of 10–40, before gradually decreasing. A simple model that consists of the quasi-steady, added-mass, and history force terms is proposed for drag at low Re. The scalings of the quasi-steady and added-mass force terms are well known; we find that the history force term scales approximately with the square root of the acceleration and velocity. The above result that relatively large drag is produced by the accelerating wing at Re = 10–40 is especially interesting and might explain why miniature insects fly in this Re range.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A fluid–structure interaction (FSI) mechanism of a shock-type underwater muzzle brake is examined. A bidirectional coupling interior ballistic approach is employed to achieve accurate projectile velocity. A velocity–pressure separation solution algorithm, semi-implicit method for pressure-linked equations and the Schnerr–Sauer cavitation model are used to address the volume of fluid multiphase Navier–Stokes equations with compressible cavitation. The full ballistic muzzle flow field distribution is comprehensively modeled. Analyzing the force and flow parameters of the T-shaped underwater muzzle brake based on the numerical solution reveals detailed insights. The underwater muzzle brake provides significant braking force in the interior ballistic period due to the presence of the water medium, which is quite different from air launch. Moreover, while both the internal and intermediate ballistic periods utilize the kinetic energy of the fluid against the wall, the muzzle brake principle in the interior ballistic period is a positive kinetic impact of water, mainly dependent on the flow velocity inside the barrel, and provides 17% recoil impulse. The side holes are significantly affected by cavitation phenomena. In contrast, during the intermediate ballistic period, the kinetic impact of gas, primarily dependent on the high-pressure gas expansion, decreases exponentially with time and provides 36% recoil impulse.
{"title":"Mechanisms of fluid–structure interaction in an underwater muzzle brake","authors":"Zhiqun Sun, Qiang Li, Pu Qu","doi":"10.1063/5.0227525","DOIUrl":"https://doi.org/10.1063/5.0227525","url":null,"abstract":"A fluid–structure interaction (FSI) mechanism of a shock-type underwater muzzle brake is examined. A bidirectional coupling interior ballistic approach is employed to achieve accurate projectile velocity. A velocity–pressure separation solution algorithm, semi-implicit method for pressure-linked equations and the Schnerr–Sauer cavitation model are used to address the volume of fluid multiphase Navier–Stokes equations with compressible cavitation. The full ballistic muzzle flow field distribution is comprehensively modeled. Analyzing the force and flow parameters of the T-shaped underwater muzzle brake based on the numerical solution reveals detailed insights. The underwater muzzle brake provides significant braking force in the interior ballistic period due to the presence of the water medium, which is quite different from air launch. Moreover, while both the internal and intermediate ballistic periods utilize the kinetic energy of the fluid against the wall, the muzzle brake principle in the interior ballistic period is a positive kinetic impact of water, mainly dependent on the flow velocity inside the barrel, and provides 17% recoil impulse. The side holes are significantly affected by cavitation phenomena. In contrast, during the intermediate ballistic period, the kinetic impact of gas, primarily dependent on the high-pressure gas expansion, decreases exponentially with time and provides 36% recoil impulse.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xudong Ma, Yang Zhang, Xiaogang Xu, Hui Wang, Tianbo Wang
The ice accretion on the aircraft's surface under low temperatures and high humidity is crucial for flight safety. With respect to the limitation of traditional icing simulation methods, it is very hard to predict exact ice profiles, which can extremely affect the flight performance of an aircraft. A conditional generative adversarial network (CGAN) is utilized to rapidly predict ice accretion and reconstruct three-dimensional ice patterns along the leading edge of a wing. The CGAN is trained using experimental data obtained from a wing with varying sweep angles. The results indicate that the CGAN achieves a high level of accuracy, specifically 97.5%, in predicting the similarity of ice shapes in the test set. When assessing the sample feature capture and prediction capability of the predictive model, it is shown that the CGAN exhibits superior predictive performance across different sample sizes.
{"title":"Wing ice accretion prediction based on conditional generation adversarial network","authors":"Xudong Ma, Yang Zhang, Xiaogang Xu, Hui Wang, Tianbo Wang","doi":"10.1063/5.0223205","DOIUrl":"https://doi.org/10.1063/5.0223205","url":null,"abstract":"The ice accretion on the aircraft's surface under low temperatures and high humidity is crucial for flight safety. With respect to the limitation of traditional icing simulation methods, it is very hard to predict exact ice profiles, which can extremely affect the flight performance of an aircraft. A conditional generative adversarial network (CGAN) is utilized to rapidly predict ice accretion and reconstruct three-dimensional ice patterns along the leading edge of a wing. The CGAN is trained using experimental data obtained from a wing with varying sweep angles. The results indicate that the CGAN achieves a high level of accuracy, specifically 97.5%, in predicting the similarity of ice shapes in the test set. When assessing the sample feature capture and prediction capability of the predictive model, it is shown that the CGAN exhibits superior predictive performance across different sample sizes.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cross-diffusion effects, including Soret and Dufour effects, are enhanced around the pseudo-critical temperature (Tpc) of a binary mixture. Their influences on heat transfer at supercritical pressure have been scarcely studied. To bridge this gap, large-eddy simulations (LES) are conducted to investigate forced convective heat transfer of a CO2–ethane mixture at supercritical pressures in a circular pipe subject to a uniform heat flux. Both heating and cooling conditions, along with varying initial concentrations and thermodynamic pressures, are included in the simulations. The LES results reveal that the Soret effect causes concentration separation, resulting in a concentration boundary layer. The magnitudes of the thermodiffusion factor (kT) and the radial temperature gradient control the intensity of separation, which is more pronounced at near-critical pressure and high heat flux. Since kT is significant only around Tpc, downstream decay of the concentration separation is observed as the loci of T=Tpc migrate away from the wall so that the local radial temperature gradient diminishes. The primary factors affecting heat transfer are the variations in thermal conductivity and isobaric specific heat resulting from concentration separation. In contrast, the Dufour effect and the accompanying inter-diffusion play negligible roles. In deterioration scenarios, the bulk Nusselt number (Nub) shows a maximum relative drop of 8%, whereas in enhancement scenarios, Nub shows a maximum relative increase in 10%, with both deterioration and enhancement decaying downstream. Cross-diffusion effects have negligible impacts on density and streamwise velocity, but noticeably alter streamwise velocity fluctuation and turbulent kinetic energy.
{"title":"Turbulent pipe flow and heat transfer of a binary mixture at supercritical pressure: Influences of cross-diffusion effects","authors":"Yangjian Ren, Mingfei Xiao, Zhan-Chao Hu","doi":"10.1063/5.0221800","DOIUrl":"https://doi.org/10.1063/5.0221800","url":null,"abstract":"Cross-diffusion effects, including Soret and Dufour effects, are enhanced around the pseudo-critical temperature (Tpc) of a binary mixture. Their influences on heat transfer at supercritical pressure have been scarcely studied. To bridge this gap, large-eddy simulations (LES) are conducted to investigate forced convective heat transfer of a CO2–ethane mixture at supercritical pressures in a circular pipe subject to a uniform heat flux. Both heating and cooling conditions, along with varying initial concentrations and thermodynamic pressures, are included in the simulations. The LES results reveal that the Soret effect causes concentration separation, resulting in a concentration boundary layer. The magnitudes of the thermodiffusion factor (kT) and the radial temperature gradient control the intensity of separation, which is more pronounced at near-critical pressure and high heat flux. Since kT is significant only around Tpc, downstream decay of the concentration separation is observed as the loci of T=Tpc migrate away from the wall so that the local radial temperature gradient diminishes. The primary factors affecting heat transfer are the variations in thermal conductivity and isobaric specific heat resulting from concentration separation. In contrast, the Dufour effect and the accompanying inter-diffusion play negligible roles. In deterioration scenarios, the bulk Nusselt number (Nub) shows a maximum relative drop of 8%, whereas in enhancement scenarios, Nub shows a maximum relative increase in 10%, with both deterioration and enhancement decaying downstream. Cross-diffusion effects have negligible impacts on density and streamwise velocity, but noticeably alter streamwise velocity fluctuation and turbulent kinetic energy.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Understanding the dispersion of particles in enclosed spaces is crucial for controlling the spread of infectious diseases. This study introduces an innovative approach that combines an unsupervised learning algorithm with a Gaussian mixture model to analyze the behavior of saliva droplets emitted from a coughing individual. The algorithm effectively clusters data, while the Gaussian mixture model captures the distribution of these clusters, revealing underlying sub-populations and variations in particle dispersion. Using computational fluid dynamics simulation data, this integrated method offers a robust, data-driven perspective on particle dynamics, unveiling intricate patterns and probabilistic distributions previously unattainable. The combined approach significantly enhances the accuracy and interpretability of predictions, providing valuable insights for public health strategies to prevent virus transmission in indoor environments. The practical implications of this study are profound, as it demonstrates the potential of advanced unsupervised learning techniques in addressing complex biomedical and engineering challenges and underscores the importance of coupling sophisticated algorithms with statistical models for comprehensive data analysis. The potential impact of these findings on public health strategies is significant, highlighting the relevance of this research to real-world applications.
{"title":"On particle dispersion statistics using unsupervised learning and Gaussian mixture models","authors":"Nicholas Christakis, Dimitris Drikakis","doi":"10.1063/5.0229111","DOIUrl":"https://doi.org/10.1063/5.0229111","url":null,"abstract":"Understanding the dispersion of particles in enclosed spaces is crucial for controlling the spread of infectious diseases. This study introduces an innovative approach that combines an unsupervised learning algorithm with a Gaussian mixture model to analyze the behavior of saliva droplets emitted from a coughing individual. The algorithm effectively clusters data, while the Gaussian mixture model captures the distribution of these clusters, revealing underlying sub-populations and variations in particle dispersion. Using computational fluid dynamics simulation data, this integrated method offers a robust, data-driven perspective on particle dynamics, unveiling intricate patterns and probabilistic distributions previously unattainable. The combined approach significantly enhances the accuracy and interpretability of predictions, providing valuable insights for public health strategies to prevent virus transmission in indoor environments. The practical implications of this study are profound, as it demonstrates the potential of advanced unsupervised learning techniques in addressing complex biomedical and engineering challenges and underscores the importance of coupling sophisticated algorithms with statistical models for comprehensive data analysis. The potential impact of these findings on public health strategies is significant, highlighting the relevance of this research to real-world applications.","PeriodicalId":20066,"journal":{"name":"Physics of Fluids","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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