This study adopts high-fidelity computational fluid dynamics (CFD) and the NSGA-II algorithm to investigate and optimize the aerodynamic performance and efficiency of a high-pressure centrifugal fan. Sensitivity analysis was conducted, and the results show that the volute’s front diffusion angle, impeller radius, and impeller-volute clearance have a significant impact on the total pressure and efficiency. A surrogate model was established to explore relationships among various parameters and was subsequently applied to efficiency optimization. The multi-objective optimization results based on the NSGA-II algorithm show that the total pressure of the fan is increased by 581.58 Pa and the efficiency is improved by 1.5%, with the prediction errors of both parameters below 0.6%, indicating that the method has high accuracy and a remarkable optimization effect.

Numerical simulations of bio-inspired fluid-structure interactions (FSI) problems are challenging and may require considerable computational effort due to the flexibility of deformable structures and their motion within the flow domain. This work presents an improved heterogeneous parallel mesoscopic CFD/CSD solver for simulating complex FSI problems with flexible flapping wings. In this method, the mesoscopic lattice Boltzmann flux solver (LBFS) is adopted as the CFD solver, the CSD solver for flexible structures is based on the finite difference method (FDM), and the newly developed immersed boundary method (IBM) with a semi-implicit coupling scheme handles the no-slip boundary condition at the fluid-solid interface. Additionally, optimizations of the DCU-based IBM are incorporated into a heterogeneous parallel strategy on the hybrid CPU-DCU framework to improve computational efficiency. The efficiency of the CFD/CSD solver is examined by the flow past a flexible flag. Finally, the heterogeneous parallel mesoscopic CFD/CSD solver is applied to study the FSI problems of double flexible flapping wings in forward flight states, considering the effects of aspect ratios (AR =1.5 4.0), where different bending/twisting stiffnesses (gamma = 0.01 0.12) are simulated. The quantitative analysis of the aerodynamic performance of the flapping wings, including force and power coefficients, reveals that the flexible deformation of the wing structure can result in phase differences in the coefficients and corresponding amplitudes. By defining the deformable angle, three distinct deformable states are observed: excessive deflection, flexible deformation, and slight deflection. The diagrams of deformable modes spanned by AR - gamma illustrate that large aspect ratios can increase the rigidity of wings and significantly affect the vortex structures in the wake stream. This work may shed new light on the mechanism of biological flows and provide a feasible and efficient tool for designing bio-inspired flying robots.

Turbulence models provide the essential mathematical closures to the Reynolds-Averaged Navier-Stokes (RANS) equations, allowing for the prediction of complex, chaotic fluid behaviors in aeronautical and astronautical applications. However, their accuracy and universality still face significant challenges, especially for compressible flows that exhibit strong adverse pressure gradients, flow separation, or high swirl. This work presents an effective local feature-augmented machine-learning optimization method for enhancing the compressible RANS model. The present optimization framework optimizes both Reynolds stress and turbulent heat flux closures simultaneously by utilizing the Ensemble Kalman Filter (EnKF) approach and artificial neural networks (ANNs). The ANNs incorporate many key features of complex compressible flows as inputs, including shock waves, compressible intensity, and flow separation. By considering multiple flow conditions across the entire flow field, shared ANN parameters are trained and optimized with the flow field solver and sparse experimental data. In particular, joint and coupled field inversion training is performed with separated compression corner flows, covering local Mach numbers from 0 to 9.22. Since the resultant enhanced SST model only depends on physical flow features, its prediction capability can thus be ensured in diverse flow scenarios beyond the training cases as long as the flow features are similar. Extensive validations on compressible turbulence benchmarks ranging from transonic to hypersonic regimes, including various compression corners, a compressible flat plate, oblique SBLI, Onera M6 wing, and ASBLI, demonstrate that the data-assimilation-enhanced SST model outperforms the baseline SST remarkably in predicting pressure, skin friction, and heat flux distributions. It seems that the applicability of the present SST model can be effectively extended to various Mach numbers, which may shed light on the development of more reliable data-assimilated turbulence models.

This work presents a feature-consistent field inversion and machine learning framework to enhance the capability of the Reynolds-averaged Navier-Stokes (RANS) turbulence model in predicting complex flows with separations. It effectively assimilates direct numerical simulation solutions and sparse experimental data, including velocity profiles, pressure distribution, and aerodynamic forces, into the improved k-w shear stress transport (SST) closure model using the regularized ensemble Kalman inversion method. An artificial neural network (ANN) model is built to reconstruct the destruction term by considering local flow features. A modified analytical scheme with a prior mean-based regularization constraint is used to facilitate the model's exploration of the most influential regions for correction. The training process of the ANN model not only integrates the solution of the RANS equations but also minimizes the loss function by considering multiple flow conditions simultaneously so that feature inconsistency is avoided, resulting in a more effective model that delivers more accurate RANS results. Typical turbulent flow problems are simulated to validate the proposed method, including the separation flows over slopes and steps with low Reynolds numbers and the separation flows over airfoils with high Reynolds numbers. It is demonstrated that the proposed framework is capable of training a robust and consistent ANN-improved k-w SST turbulence model for predicting turbulent flows with separations at both low and high Reynolds numbers. It also shows that the present ANN-improved k-w SST turbulence model achieves generalization for separated flows with unforeseen geometries and Reynolds numbers.

This paper presents an efficient and high-order WENO-based Upwind Rotated Lattice Boltzmann Flux Solver (WENO-URLBFS) on graphics processing units (GPUs) for simulating three-dimensional (3D) compressible flow problems. The proposed approach extends the baseline Rotated Lattice Boltzmann Flux Solver (RLBFS) by redefining the interface tangential velocity based on the theoretical solution of the Euler equations. This improvement, combined with a weighted decomposition of the numerical fluxes in two mutually perpendicular directions, effectively reduces numerical dissipation and enhances solution stability. To achieve high-order accuracy, the WENO interpolation is applied in the characteristic space to reconstruct physical quantities on both sides of the interface. The density perturbation test is employed to assess the accuracy of the scheme, which demonstrates 5th- and 7th-order convergence as expected. In addition, this test case is also employed to confirm the consistency between the CPU serial and GPU parallel implementations of the WENO-URLBFS scheme and to assess the acceleration performance across different grid resolutions, yielding a maximum speedup factor of 1208.27. The low-dissipation property of the scheme is further assessed through the inviscid Taylor-Green vortex problem. Finally, a series of challenging three-dimensional benchmark cases demonstrate that the present scheme achieves high accuracy, low dissipation, and excellent computational efficiency in simulating strongly compressible flows with complex features such as strong shock waves and discontinuities.

Suppose that M is a complete Riemannian manifolds with nonnegative sectional curvature. We prove that for the exponentially harmonic heat flow (3) on bounded regular domain with the Dirichlet initial-boundary value data, there exists a unique global solution. We prove that for any bounded solution of the exponentially harmonic function heat flow on M, there is a gradient estimate. As a consequence of this estimate, we derive the Liouville type theorem for bounded ancient solutions to exponentially harmonic function heat flow on M. We also obtain Liouville type results for the exponentially harmonic functions with finite weighted L2 norms. (c) 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

The predictive modeling of dynamic wake flow for floating offshore wind turbines presents significant challenges. In this paper, we propose a predictive data-driven model of wake flow for floating offshore wind turbines. The data-driven model is based on a high-order variant of the dynamic mode decomposition approach, incorporating a network of optimized data probe points and a discrete empirical interpolation method in preprocessing. A high-fidelity computational fluid dynamics model is utilized to study the wake flow pattern and generate data for our data-driven model. Our data-driven model can quickly forecast wake dynamics based on a limited number of physical state inputs, which are measured at a few probe points behind the wind turbine. The results show that our model can give a highly accurate future forecast of wake dynamics behind the wind turbine for up to 30 s and a moderately accurate forecast for up to 100 s and beyond. The frequency spectrum of our predictions also agrees well with the benchmark solutions.

Gas-liquid-solid (GLS) three-phase interactions play a significant role in many essential areas but present many critical challenges for computational fluid dynamics methods to study. In this paper, we present a GLS contact condition-enforced immersed boundary method (IBM) for simulating multiphase flow problems with curved and moving boundaries on simple Cartesian meshes. Together with the phase field conditions, a GLS contact condition is introduced in the Cahn-Hillard model and then dealt with by the IBM to effectively eliminate mass leakage at the solid boundary. Both the phase field and contact conditions are consistently enforced by proposing a second-order moving-least-squares (MLS)-based IBM. In addition, the velocity correction IBM is applied to enforce the no-slip condition at the solid surface. The flow field is solved by using the multiphase lattice Boltzmann flux solver (MLBFS), which is suitable for multiphase flows at large density ratios. The performance of the present method is well examined through many challenging benchmark tests, including both steady and unsteady GLS problems, such as droplet spreading and impacting circular solid surfaces with different wettabilities. The good agreements with theoretical and available numerical data published in the literature show that the present GLS contact condition-enforced IB-MLBFS can accurately enforce the Dirichlet and Neumann boundary conditions and efficiently restrain nonphysical liquid/mass penetrations near the solid surfaces. Applications of the present method to study more complex GLS problems at large density ratios O(103), including droplets impacting porous solid structures and a flapping wing, have also been carried out to further demonstrate its reliability and high potential.

This paper presents a WENO-based upwind rotated lattice Boltzmann flux solver (WENO-URLBFS) in the finite difference framework for simulating compressible flows with contact discontinuities and strong shock waves. In the method, the original rotating lattice Boltzmann flux solver is improved by applying the theoretical solution of the Euler equation in the tangential direction of the cell interface to reconstruct the tangential flux so that the numerical dissipation can be reduced. The fluxes at each interface are evaluated using a weighted summation of lattice Boltzmann solutions in two local perpendicular directions decomposed from the direction vector so that the stability performance can be improved. To achieve high-order accuracy, both fifth and seventh-order WENO reconstructions of the flow variables in the characteristic spaces are carried out. The order accuracy of the WENO-URLBFS is evaluated and compared with the traditional Lax–Friedrichs scheme, Roe scheme, and the LBFS by simulating the advection of the density disturbance problem. It is shown that the fifth and seventh-order accuracy can be achieved by all considered flux-evaluation schemes, and the present WENO-URLBFS has the lowest numerical dissipation. The performance of the WENO-URLBFS is further examined by simulating several 1D and 2D examples, including shock tube problems, Shu–Osher problems, blast wave problems, double Mach reflections, 2D Riemann problems, K-H instability problems, and High Mach number astrophysical jets. Good agreements with published data have been achieved quantitatively. Moreover, complex flow structures, including shock waves and contact discontinuities, are successfully captured. The present WENO-URLBFS scheme seems to present an effective numerical tool with high-order accuracy, lower numerical dissipation, and strong robustness for simulating challenging compressible flow problems.

A single-rotor UAV fitted with a pulse-jet thermal fogging machine was developed. Computational fluid dynamics (CFD) was employed to simulate the downwash airflow and fog distribution of a single-rotor UAV fitted with a pulse-jet thermal fogger. The developed CFD models were validated in three steps by comparing the calculated results with the measurement experiments. Predicted air velocities of the single-rotor UAV downwash airflow agreed well with measured velocities. The model was also able to predict the fog droplet deposition density of the pulse-jet thermal fogger alone, and fitted to the single-rotor UAV, with the relative errors within 20% and 30%, respectively. The validated CFD model was then employed to investigate the effects of the headwind, crosswind and UAV operating height on the downwash airflow and the fog distribution. Results indicated that when the pulse-jet thermal fogging machine was mounted on the UAV, crosswinds needed to be avoided. At the UAV flight speed of 2 m s(-1) and natural wind speed of 1 m s(-1), a modest headwind appearance could help improve thermal fogging efficiency at different operating heights. The results have important research value and practical significance for improving the pesticide efficiency of UAV sprayers.

In this study, optical frequency domain reflectometry (OFDR) was used to monitor the thermoforming processes of carbon fiber reinforced thermoplastics (CFRTPs) to address the limitations of conventional sensors including large size and low spatial resolution. A bare single-mode fiber with a polyimide coating and a fiber encapsulated by a long metal capillary were cascaded and embedded into composite laminates to withstand the high pressure and temperature during thermoforming, and then connected to the OFDR for monitoring. A fiber encapsulated by a 2 cm short metal capillary was also embedded to demonstrate that a 1 mm resolution of the OFDR is beneficial for reflecting the local change in the composite. After processing by wavelet denoising, signal extraction, and decoupling, the frequency shift along the optical fiber sensor was successfully converted to strain and temperature. In two repeated thermoforming experiments that involved cooling from 340 degrees C, the average temperature difference measured by the OFDR and reference thermocouple was only 4.64 degrees C. The strain measured by the OFDR and reference fiber Bragg grating (FBG) decreases in the cooling stage, and has a clear knee point of 250 degrees C when correlated with the temperature and strain. This knee point is consistent with the liquid-liquid transition temperature of the polyetherimide and indicates the beginning of consolidation when the composite changes its properties significantly. The average strain difference measured by OFDR and the reference FBG was 69 mu epsilon when the total strain is approximately 1820 mu epsilon if only considering the consolidation process from 250 degrees C. The results of 1 mm spatial resolution and high accuracy demonstrate that OFDR is a promising high-resolution sensing solution for the in-situ temperature and strain monitoring of the thermoforming of CFRTPs.

A three-dimensional (3D) Rotated Lattice Boltzmann Flux Solver (RLBFS) is proposed and analyzed with matrix-based linear stability theory for simulating compressible flows in a wide range of Mach numbers. The 3D RLBFS applies the finite volume method to discrete the Navier-Stokes equations and evaluates its fluxes at each cell interface. To improve numerical stability, the convective fluxes are obtained in a hybrid way by using the D1Q4 lattice Boltzmann model in two perpendicular directions decomposed by the outer normal vector of each cell interface. The viscous fluxes are computed in a conventional way using the second-order central scheme. The stability performance and order accuracy of the proposed 3D RLBFS are examined by using the matrix-based stability theory and L2 errors on different meshes respectively. It is shown that the 3D RLBFS is stable even at high Mach number and has the second-order accuracy in space. The reliability and capability of the proposed method is further evaluated by simulating several challenging compressible flow problems, including subsonic flow over the DLR-F4, transonic flow over the ONERA M6 wing, supersonic flow around NACA0012 wing, hy-personic flow over the Viking lander capsule, hypersonic flow over a hemisphere and hypersonic flow around a blunt nose double cone. The obtained numerical results are in good agreement with experimental and/or nu-merical data published in the literature, indicating that the present method provides a reliable and effective tool for simulating practical three-dimensional compressible flow problems in aeronautics and astronautics.

This work presents a two-dimensional (2D) numerical study on the flow-induced vibrations (FIV) of elastically mounted rectangular cylinders without and with barrier walls in a wide range of reduced velocities U*=1–200 and Scruton numbers Sc=0–64 at the Reynolds number of 1000. It reveals that a slender rectangular cylinder of aspect ratio 5:1 without barrier walls may experience vortex-induced vibration (VIV), while the one with barrier walls can have both VIV and soft galloping motions. The VIV motions of both cylinders occur at relatively small reduced velocities U*≤20, and their maximum amplitudes are gradually reduced with the increase in the Scruton number. The galloping motions of the cylinder with barrier walls take place at higher reduced velocities U*>30 with smaller frequencies and larger oscillation amplitudes. Quantitative analysis on the amplitude, displacement, and frequency of oscillation for both cylinders is carried out. Two phase diagrams of the vortex-shedding flow patterns are presented to illustrate the flow characteristics in VIV and galloping modes. Meanwhile, the dynamic mode decomposition analysis indicates the difference between the dominant mode of the dynamic flow field in the VIV and galloping motions. With the quasi-steady theory, it further shows that the occurrence of the soft galloping motion of the cylinder with barrier walls is caused by the negative slope of the lift coefficient at the angle of attack zero. These results may shed new light onto deeper understanding of the FIV phenomenon and provide some inspirations to engineering applications in the design of civil and offshore structures.

"饭圈"是当代青年追星的主要场域,然而,近几年来却乱象频出,一定程度上对我国主流意识形态造成冲击."饭圈"乱象与部分青年心理需求的外显与异化、资本增殖的天性与演绎、技术异化的存续与变迁以及西方谋求霸权的延续与拓展密不可分."饭圈"乱象对主流意识形态的冲击主要表现为泛娱乐风气削弱主流意识形态的严肃性、狂热式追星挑战主流意识形态的权威性、封闭型群组阻滞主流意识形态的辐射性、匿名化交流淡化主流意识形态的约束性、多维度渗透动摇主流意识形态的稳定性.治理"饭圈"乱象,应坚守正确导向,掌握主流意识形态在"饭圈"的话语权;坚持人民至上,提升主流意识形态在"饭圈"的亲和力;讲好"大思政课",扩大主流意识形态在"饭圈"的影响力;凝聚各方力量,打造协同维护主流意识形态的优质队伍;增强制度供给,推动"饭圈"乱象治理的制度化、法治化.

The mixing ventilation (MV) system could spread airborne infectious diseases in airplane cabins, such as the flu and Corona-virus infection (COVID-19). As a result, it is critical to improve the current design of airline cabin ventilation systems. Six innovative customized ventilation (PV) systems were proposed and investigated through numerical simulations in this study to reduce pollutant transport. At first, two environmental chambers' experimental data on airflow, air temperature, and pollutant concentration were utilized to validate the Computational Fluid Dynamics (CFD) model used for the present numerical study. The six PVs were then studied to analyze the distributions of air velocity, air temperature, pollutant concentration, and carbon dioxide (CO2) concentration in a part of the Boeing 767 cabin using the validated CFD model. It is found that the passenger's personal outlet set up on both sides of his or her head (PV-1) has the best distribution of carbon dioxide concentration, velocity, temperature, and contaminant concentration when compared to the six personalized air distribution systems. It can reduce pollutant concentrations more than the other proposed systems. The present study may shed new light on the design of PVs with the potential for reducing the spreading of airborne infectious diseases.

中国特色社会主义现代化道路的本质特征、发展历程与未来指向,决定着其自身蕴含着丰富的辩证智慧.一方面,从比较视域透视中国式现代化道路,经济结构、政治体制、价值选择和对外关系等方面是其根本性变化之处,与西方国家存在本质性区别;另一方面,从自身发展的内在逻辑出发,对中国式现代化道路加以审视和剖析,其指导思想、领导核心、发展理念和伟大梦想等实质内容依然保持相对稳定且难以改变.科学地认知和把握中国式现代化道路所蕴含的辩证关系,需要正确处理"变"与"不变"之关系,在"万变"之中把握"不变"之内容,以"不变"之内容应对"万变"之挑战.

"躺平主义"是部分青年群体应对非创造性劳动困境的一种"暂时性"心理调节机制和"战术性"行为调整策略.作为一种青年亚文化现象,"躺平主义"的群像特征表现为一系列独特的心理表征、价值构境、话语叙事和形象定位."躺平主义"的生成有着深层的利益动因和时代缘由,是当代青年面临的时代困境的群像反映.有效遏制劳动功利化倾向所造成的负面影响,使劳动本身成为当代青年的一种幸福,有助于推动"躺平青年"变为"奋斗青年",让青年一代在劳动的幸福体验中实现积极健康的发展.

在当前中国社会价值多元化的现实图景中,强化社会主义核心价值观在价值观领域的话语权,牢牢掌握社会价值建构的主导权,是巩固文化自信、推动新时代中国特色社会主义精神文明建设的应有之义.作为社会主义意识形态在价值观领域的重要体现,社会主义核心价值观面临着西方"普世价值"话语霸权冲击、话语体系建设滞后、话语传播能力不足、网络阵地建设薄弱等多重困境,使得其话语影响力被削弱.因此,提升社会主义核心价值观话语权需要将人民的普遍需求转化为共识性的话语表达,彰显话语本质;将党的执政优势转化为实现价值目标的治理效能,提升话语权威;促进多元价值观话语的互动融合,丰富话语内涵;将中华民族愿景融入人类命运共同体,破除西方话语崇拜;促进传统媒体与新兴媒体深度融合、优势互补,推动话语传播.

生态正义是生态价值体系的核心范畴,也是新时代生态文明建设的重要哲学内涵.人类只有将关于生态价值的理性考量纳入到实践活动之中,才可能实现人与自然的正义之境,从而推进人类社会的可持续发展.当代中国生态正义既是对中国传统生态智慧的传承,也是对西方生态伦理思想的镜鉴超越;既是对马克思主义生态正义思想的弘扬,也是对新时代中国生态文明建设的理论表征.深刻把握生态效益与经济效益、公共利益与个人利益、公共权力与生态权利、生态权益与生态责任、美丽中国与绿色家园的辩证关系,是全面展示当代中国生态正义的重要路径.

中国式现代化道路是我们党团结带领中国人民在复杂的世界现代性语境中创造的人类文明新形态,具有强大生命力和巨大优越性.以方法论自觉将中国式现代化道路置于世界现代化坐标中进行历时性和共时性比较,可以充分彰显其超越性.坚持以人民为中心的发展逻辑,实现了对西方现代化道路的价值性超越;坚持科学社会主义理论逻辑和中国社会发展历史逻辑相统一,实现了对苏联社会主义现代化道路的历史性超越;坚持以实事求是和独立自主为逻辑基点,实现了对后发国家依附型现代化道路的实践性超越.