Complex Flow Research Articles

Advanced Numerical Techniques for Supersonic Flow Analysis: From Euler Equations to Practical Applications in Aerospace and Turbomachinery Engineering

This paper explores advanced numerical techniques for analyzing supersonic flow, with a particular focus on the application of Euler equations in aerospace and turbomachinery engineering. Theoretical foundations such as boundary conditions, error evaluation, grid partitioning, and the Successive Over-Relaxation (SOR) method are thoroughly examined. Rigorous numerical simulations are conducted to investigate the final velocity field distribution and convergence characteristics under various conditions. The research underscores the precision and efficiency of these numerical methods, highlighting their practical applications in the aerodynamic design of aircraft and potential use in turbomachinery design. The findings contribute significantly to the advancement of computational fluid dynamics in supersonic flow regimes, providing valuable insights for engineers and researchers engaged in this specialized area. The study not only enhances understanding of complex flow dynamics but also supports the development of more effective engineering solutions in high-speed applications.

FlawCheck: Detecting Smart Contract Vulnerabilities Based on Symbolic Execution

ABSTRACTSmart contracts are turing‐complete computer programs running on blockchains. Like traditional programs, smart contracts are also vulnerable. However, unlike traditional programs, it is very difficult to modify smart contracts once they are deployed on the blockchain. Therefore, reducing potential vulnerabilities in contracts before deployment to the blockchain is very important. The existing smart contract detection tools mostly fail to fully consider the complex control flow relationships within smart contracts, leading to false positives and false negatives. To address these problems, we propose FlawCheck, a vulnerability detection tool based on symbolic execution. First, it compiles smart contract source code into bytecode. Then, it disassembles bytecode into an opcode sequence, building the dependencies of contract control flow. Next, it performs preliminary analysis on the information generated during the simulated execution on the Ethereum virtual machine to identify suspicious vulnerability paths. Finally, it detects these suspicious paths by using symbolic execution. We verified that FlawCheck can detect five types of smart contract vulnerabilities. Experimental results on a dataset of 13016 real contracts shows that FlawCheck has higher accuracy than other tools.

Particle image velocimetry study of the flow control effects of singular and multiple curved serration models

This paper reports on preliminary observations of an investigation of flows associated with models that mimic serrations on the leading edge of barn owl feathers. The objective was to use particle image velocimetry measurements to determine the capacity of singular and multiple curved (three-dimensional) serration models to modify the noise-reducing indicators of a narrow-channeled flow past a cylinder. Four models were tested: 3 singular serration models of respective angles of inclination, α = 24°, 27.5° and 31°, and a model consisting of an array of 3 serrations of α = 24°, 27.5° and 31°. Each case was subjected to flow of Reynolds number (based on the serration height and maximum velocity of the flow) of ∼2,000, simulating the flow regime of local flow around barbs of real barn owl flights. A planar particle image velocimetry technique was used to capture the midspan plane velocities to determine the effects of each model. The results show that using singular serration models of inclination angles than 30° may lead to disorganized spatial structures and enhanced turbulence levels. On the other hand, an array of only 3 curved serrations of different geometries can modify the spatial flow structure into a well-ordered one, resulting in a 50% reduction in turbulence intensities. These initial results suggest that under complex flow conditions, the insertion of single and multiple curved serrations can lead to significant flow changes that may result in potential noise modifications.

Capillary Orientation and Morphology Dictated Oscillatory Electro-magneto-imbibition of Viscoelastic Electrolytes.

We explore the intricate dynamics of imbibition by a viscoelastic electrolyte within an arbitrarily oriented, nonuniform microcapillary, while under the stimulus of external electromagnetic fields and internal electroviscous forces stemming from streaming potential. The microcapillary walls are envisaged to be tapered relative to each other, with the entire system inclined with respect to the horizontal plane. The rheological behavior of the electrolyte is characterized using the Phan-Thien-Tanner (PTT) model. To manipulate the imbibition dynamics, external transverse magnetic and electric fields are imposed. Incorporating all contributing forces, we obtain semianalytical formulations for the velocity and shear stress distributions. We identify distinct stages during the imbibition process: (i) initial, (ii) filling, (iii) oscillatory, and (iv) stagnation stages. Moreover, we scrutinize the impact of four pivotal parameters, namely, the Weissenberg number (Wi), the Hartmann number (Ha), the transverse electric to viscous force (EVF) number (S), and the electric Reynolds number (Ree), on the imbibition dynamics across different inclinations and taper angles. We also delineate the parameter space for these four parameters, identifying where the onset of oscillations occurs. Finally, through scaling analysis, we establish the existence of four distinct regimes corresponding to the aforementioned stages: (i) the linear regime, (ii) the Washburn regime, (iii) the oscillatory regime, and (iv) the equilibrium regime. Our findings are anticipated to enhance the understanding of capillary imbibition under such complex flow conditions and contribute significantly to the advancement of capillarity-driven microfluidic devices.

Simulating unsteady flows on a superconducting quantum processor

Recent advancements of quantum technologies have triggered tremendous interest in exploring practical quantum advantage. The simulation of fluid dynamics, a highly challenging problem in classical physics but vital for practical applications, emerges as a potential direction. Here, we report an experiment on the digital simulation of unsteady flows with a superconducting quantum processor. The quantum algorithm is based on the Hamiltonian simulation using the hydrodynamic formulation of the Schrödinger equation. With the median fidelities of 99.97% and 99.67% for parallel single- and two-qubit gates respectively, we simulate the dynamics of a two-dimensional (2D) compressible diverging flow and a 2D decaying vortex with ten qubits. Note that the former case is an inviscid potential flow, and the latter one is an artificial vortical flow with an external body force. The experimental results well capture the temporal evolution of averaged density and momentum profiles, and qualitatively reproduce spatial flow fields with moderate noises. This work demonstrates the potential of quantum computing in simulating more complex flows, such as turbulence, for practical applications.

Simulation of complex flow with a hovering dragonfly by multi-direct forcing immersed boundary method

Simulation of complex flow with a hovering dragonfly by multi-direct forcing immersed boundary method

Neural differentiable modeling with diffusion-based super-resolution for two-dimensional spatiotemporal turbulence

Simulating spatiotemporal turbulence with high fidelity remains a cornerstone challenge in computational fluid dynamics (CFD) due to its intricate multiscale nature and prohibitive computational demands. Traditional approaches typically employ closure models, which attempt to represent small-scale features in an unresolved manner. However, these methods often sacrifice accuracy and lose high-frequency/wavenumber information, especially in scenarios involving complex flow physics. In this paper, we introduce an innovative neural differentiable modeling framework designed to enhance the predictability and efficiency of spatiotemporal turbulence simulations. Our approach features differentiable hybrid modeling techniques that seamlessly integrate deep neural networks with numerical PDE solvers within a differentiable programming framework, synergizing deep learning with physics-based CFD modeling. Specifically, a hybrid differentiable neural solver is constructed on a coarser grid to capture large-scale turbulent phenomena, followed by the application of a Bayesian conditional diffusion model that generates small-scale turbulence conditioned on large-scale flow predictions. Two innovative hybrid architecture designs are studied, and their performance is evaluated through comparative analysis against conventional large eddy simulation techniques with physics-based subgrid-scale closures and purely data-driven neural solvers. The findings underscore the potential of the neural differentiable modeling framework to significantly enhance the accuracy and computational efficiency of turbulence simulations. This study not only demonstrates the efficacy of merging deep learning with physics-based numerical solvers but also sets a new precedent for advanced CFD modeling techniques, highlighting the transformative impact of differentiable programming in scientific computing.

Recent developments on multiscale simulations for rheology and complex flow of polymers

AbstractThis review summarized the multiscale simulation (MSS) methods for polymeric liquids. Since polymeric liquids have multiscale characteristics of monomeric, mesoscopic, and macroscopic flow scales, MSSs that relate different hierarchical levels are adequate to reproduce flow properties accurately. Our review includes pioneering studies to the most advanced MSS studies on rheology predictions and flow simulations of polymeric liquids. We discuss two major types of MSS methods: the bottom-up and model-embedded MSS methods. The former method mainly connects all-atom molecular dynamics models and mesoscopic models to predict rheological properties. In contrast, the latter method, where a microscopic or mesoscopic model is embedded in a macroscopic computational domain, is designed to predict macroscopic flow properties. Finally, we also discuss MSS methods using machine learning techniques. Graphical abstract

Precise and accurate speed measurements in rapidly flowing dense suspensions

We introduce a method for precise and accurate measurements of particle speeds in dense suspensions flowing at high rates and demonstrate the utility of the approach for revealing complex flow fluctuations during shearing in a setup that combines imaging with a confocal microscope and shearing with a rheometer. We scan the focal point in one dimension, aligned with direction of flow, producing absolute measurements of speed that are independent of suspension structure and particle shape. We compare this flow-direction line scanning approach with a complementary method we introduced previously, measuring speed using line scanning in the vorticity direction. By comparing results in various flow conditions, including shear-thinning and thickening regimes, we demonstrate the efficacy of our new approach. We find that both approaches exhibit qualitatively similar flow profiles, but a comparative analysis reveals a 15%–25% overestimation in speed measurement using vorticity line scanning, with discrepancies generated by anisotropic suspension microstructure under flow. Moreover, in the thickening regime where complex flow fields are present, both approaches capture local speed fluctuations. However, line scanning in the flow direction reveals and precisely captures stagnation and backflows, a capability not achievable with vorticity line scanning. The approach introduced here not only provides a refined technique for speed measurement in fast-flowing suspensions but also emphasizes the significance of accurate measurement techniques in advancing our understanding of flow behavior in dense suspensions, particularly in contexts where strong non-affine flows are prevalent.

A typology of potential hydraulic barriers to adult salmon migration in a bedrock river

Adult Pacific salmon (Oncorhynchus spp.) in the Fraser River, British Columbia, can die trying to retrace and ascend the river network to their natal spawning grounds due to hydraulic barriers, where encounter velocities exceed swim speeds of adult salmon. We evaluated river hydraulics, river morphology, and swimming ability to better understand these potential hydraulic barriers. A 375 km centerline velocity survey of the Fraser Canyon identified 22 high velocity locations where the distribution of velocity within the reach could produce a hydraulic barrier. We identified and studied three flow types associated with these 22 high velocity locations: 1) plunging flows, 2) rapids, and 3) overfalls, using drone footage at various discharges to examine flow structure and compare surface velocities with swimming modes. Complex flow within the major hydraulic features highlight the spatial locations requiring anaerobic swimming and areas of potential recovery that change with discharge. This approach can be used to improve the understanding of fish migration limits in a natural river system and aid in future mitigation.

A multimodal zebrafish developmental atlas reveals the state-transition dynamics of late-vertebrate pluripotent axial progenitors

Elucidating organismal developmental processes requires a comprehensive understanding of cellular lineages in the spatial, temporal, and molecular domains. In this study, we introduce Zebrahub, a dynamic atlas of zebrafish embryonic development that integrates single-cell sequencing time course data with lineage reconstructions facilitated by light-sheet microscopy. This atlas offers high-resolution and in-depth molecular insights into zebrafish development, achieved through the sequencing of individual embryos across ten developmental stages, complemented by reconstructions of cellular trajectories. Zebrahub also incorporates an interactive tool to navigate the complex cellular flows and lineages derived from light-sheet microscopy data, enabling in silico fate-mapping experiments. To demonstrate the versatility of our multimodal resource, we utilize Zebrahub to provide fresh insights into the pluripotency of neuro-mesodermal progenitors (NMPs) and the origins of a joint kidney-hemangioblast progenitor population.

The effect of particle size distribution on the collapse of wet polydisperse granular materials

Low-saturation liquid-containing granular materials are commonly encountered in both natural and industrial settings, where interstitial liquids significantly affect the motion of particles, while particle size polydispersity plays a crucial role in determining the level of system cohesion. In this study, the collapse of wet polydisperse granular columns is numerically investigated based on the developed discrete element model, with corresponding dam-break experiments performed to validate our numerical model and methodology. The dependence of the dynamics and flow mobility on particle size distribution is primarily examined, and the underlying mechanisms are also explored by analyzing particle path lengths and average fidelity. Building upon the effective Bond number proposed using the mixing theory, a macroscopic cohesion parameter at the material scale is defined by considering the dependence of the collapse on the system size effect. The relevance of this cohesion parameter in describing different wet polydisperse granular collapses is further validated based on our designed experimental tests and DEM simulations. The approach of constructing the cohesion parameters at different scales can be extended to characterize cohesion effects in more complex wet polydisperse granular flows and describe their associated rheological behaviors.

Emissions and Flame Stability Assessment of Hydrogen Addition and Air Dilution in a Micro Gas Turbine Combustor Using 0D/1D Modeling by Chemical Reactor Network

Abstract Hydrogen emerges as a promising fuel for clean and sustain- able electricity production when utilized in micro gas turbines (mGTs). However, some challenges linked to hydrogen usage must be overcome as its high reactivity can lead to increased NOx emissions and flame instabilities. Literature suggests that combustion air humidification and/or exhaust gas recirculation (EGR) may be methods to reduce this reactivity. However, these measures are limited due to the small operating range of the mGT combustor. In this context, a 20 kWth mGT combustor is investigated un- der various inlet conditions to assess the effect of EGR towards increased flame stability and emission control when operating under hydrogen-enriched methane firing, using a Chemical Re- action Network (CRN) model. The CRN modeling is a fast and low computational complexity tool to model combustion perfor- mance and emissions by representing complex reactive flow fields through idealized reactor models, leading to reduced computa- tional costs. This study examines partial load conditions, fuel compositions, and the effect of combustion air dilution through EGR. The CRN model of the combustion process is designed based on combustion zones extracted from the main flow fields with similar thermo-chemical states from CFD, while emission predictions are experimentally validated for different operating points. Predicted NOx and CO emissions by the proposed CRN model show an acceptable agreement with the experimental data at high power loads. However, its accuracy diminishes for loads below 70% due to the variability in model tuning parameters across different loads, whereas the

Prediction of Transonic Shock Buffet over Supercritical Airfoil OAT15A Based on Zonal Detached-Eddy Simulation

The zonal detached-eddy simulation (ZDES) method divides the flow field into different computational modes, offering flexibility in the simulation of complex flows. The transonic shock buffet on the upper surface of the OAT15A supercritical airfoil is numerically simulated by ZDES based on the k-ω SST model. The results show that the error in the low-frequency characteristics of the transonic shock buffet predicted by ZDES compared to experiments is within 3%. Its predictions of pressure fluctuations and averaged velocity agree better with the experimental data. Overall, ZDES is effective in predicting the periodic oscillations of shock waves along the streamwise direction, flow separation induced by shock wave motion, and the small-scale vortex structures in the wake region.

On the Complex Flow Dynamics of Shear Thickening Fluids Entry Flows

Due to their nature, using shear thickening fluids (STFs) in engineering applications has sparked an interest in developing energy-dissipating systems, such as damping devices or shock absorbers. The Rheinforce technology allows the design of customized energy dissipative composites by embedding microfluidic channels filled with STFs in a scaffold material. One of the reasons for using microfluidic channels is that their shape can be numerically optimized to control pressure drop (also known as rectifiers); thus, by controlling the pressure drop, it is possible to control the energy dissipated by the viscous effect. Upon impact, the fluid is forced to flow through the microchannel, experiencing the typical entry flow until it reaches the fully developed flow. It is well-known for Newtonian fluid that the entrance flow is responsible for a non-negligible percentage of the total pressure drop in the fluid; therefore, an analysis of the fluid flow at the entry region for STFs is of paramount importance for an accurate design of the Rheinforce composites. This analysis has been numerically performed before for shear-thickening fluids modeled by a power-law model; however, as this constitutive model represents a continuously growing viscosity between end-viscosity plateau values, it is not representative of the characteristic viscosity curve of shear-thickening fluids, which typically exhibit a three-region shape (thinning-thickening-thinning). For the first time, the influence of these three regions on the entry flow on an axisymmetric pipe is analyzed. Two-dimensional numerical simulations have been performed for four STFs consisting of four dispersions of fumed silica nanoparticles in polypropylene glycol varying concentrations (7.5–20 wt%).

Leak-Rate Through Carbon Brush Seals: Experimental Tests Versus Predictions From a Porous Medium Approach

Abstract This study presents a detailed comparative analysis between experimental leakage flow rates and numerical predictions for carbon brush seals with long bristles, utilizing a porous medium model approach. A series of tests were carried out on a static rig (without rotor rotation). The experimental setup allows tests under various interference conditions, revealing significant insights into the flow behavior through the brush seal. A numerical model based on the Darcy-Forchheimer equation is developed to interpret the complex flow dynamics within the brush seal, accounting for viscous, compressible and inertial effects. The study evaluates the impact of brush deformation and porosity on flow resistance, leveraging experimental data to refine the numerical model parameters. This investigation not only deepens the understanding of brush seal flow physics but also improves the predictive accuracy of the numerical model in simulating operational conditions.

Re-interpreting renewable and non-renewable water resources in the over-pressured Pannonian Basin

With climate change, population growth and the resulting escalating water shortage, humanity is increasingly turning to non-renewable and even fossil groundwater resources, which poses a major challenge to sustainable water management. In this study, 2D basin-scale numerical simulations were carried out on the COMSOL Multiphysics® finite element numerical platform to identify non-renewable water resources in the Central Pannonian Basin (Central Europe, Hungary) based on the lack of hydraulic connection to recharge areas. The concept and boundary conditions (fixed water table configuration at the top, pressure-elevation profiles on the lateral sides, and constant pressure on the bottom) were derived from a previous basin-scale hydraulic data evaluation study, while the hydrostratigraphic subdivision was based on seismic and well log interpretations. As a result, topography-driven groundwater flow systems fed by meteoric water infiltration were separated from a transition zone, which contains non-renewable groundwater resources and covers 85% area of the simulated 110 km long and roughly 1600 m deep cross-section what was previously thought to be fully renewable. Such complex flow pattern and re-interpretation of the renewable and non-renewable groundwater resources can be expected in any terrestrial sedimentary basin with over-pressured flow domains.

Extreme electromagnetic rotation, chemical reaction, Hall and ion slip effects on weakly ionized fluid in a Riga channel

The utilization of external magnetic or electric fields, particularly through a Riga setup, markedly enhances flow dynamics by mitigating frictional forces and turbulent fluctuations, thereby facilitating superior flow management. Such improvements are especially beneficial in optimizing the operational efficiency of machinery and turbines. Our research focuses on the behaviour of a weakly ionized fluid within a porous, infinitely extended Riga channel (or electromagnetic channel) set in a rotational frame work affected by Hall and ion-slip electric fields. This model integrates the cumulative repulsions of an abruptly apply pressure gradients, electro-magnetic force, electromagnetic radiation, as well as chemical reactions. The physical configuration of the model features a stationary RHS wall as well as the LHS wall subjected to transversal vibration, establishing a complex flow environment. This circumstance is analytically modeled utilizing time dependent PDE, with the Laplace transform method applied to achieve a closed-format resolution for the course controlling equations. Through detailed graphical and tabular data, the investigations explored the impacts of assorted pivotal parameters on the model's flow traits and quantities. Our results indicate that an upswing in the modified Hartmann number significantly enhances fluids flow in the conduit, with the most important resultant flow showing marked improvement as Hall and ion-slip parameters amplify, and secondly the resultant flow diminishing chemical reaction parameter. Additionally, species concentration lowers with higher Schmidt numbers and chemical reaction rates, while an expanded modified Hartmann number correlate with enhanced shear stress near the conduit wall. Moreover, an elevation in the radiating parameter reduces the rate of temperature transport at the vibrating wall, whereas this at the stationary wall improves. This study has profound implications across several fields, notably in fusion energy research, spacecraft propulsion systems, satellite operations, aerospace engineering, and advanced manufacturing technologies.

Exploration of initiation and stabilization properties of oblique detonation in a combustor with hydrogen fuel pre-injection

This study delves into the innovative aspects of hydrogen fuel injection and mixing within the duct of an oblique detonation engine (ODE) from both theoretical and numerical perspectives. By solving the multi-species reactive Reynolds-Averaged Navier-Stokes (RANS) equations alongside a hydrogen combustion model, the fluid dynamics and combustion processes in the combustor are thoroughly examined. The analysis shows that employing ramp-cantilever injectors for fuel delivery leads to fuel accumulation in the gas stream core, leaving a deficiency near the wall area. By supplementing ramp-cantilever injectors with wall injectors, fuel distribution adjacent to the wall is significantly enhanced, enabling the successful establishment of a detonation mode. However, the confined space and geometric constraints generate complex flow patterns, particularly due to boundary layer separation. The combustor operates in a stable configuration featuring an oblique shock-oblique detonation-separation shock (OSW-ODW-SSW) structure. Conversely, an oblique shock-oblique detonation-normal detonation-separation shock (OSW-ODW-NDW-SSW) arrangement is found to be unstable. Adjusting the position of the expansion corner on the upper wall forward stabilizes the unstable configuration, maintaining the ODW. Spatial flow inhomogeneities, especially equivalence ratio variations, are identified as crucial factors that can hinder ODW initiation and stability. These findings emphasize the pivotal role of optimizing fuel distribution, refining geometrical design, and ensuring flow uniformity in guaranteeing the efficiency and stability of oblique detonation engines. The outcomes provide valuable insights for future improvements in ODE design and operation.

Fission Dynamics of a Ferrofluid Droplet on a Smooth Plate under a Nonuniform Magnetic Field.

A ferrofluid droplet on a plate undergoes interesting fission under a magnetic field. In this article, a recently developed simplified multiphase lattice Boltzmann method coupled with a self-correction solution for the magnetic potential equation is employed to explore this complex flow phenomenon. It is found that the droplet fission follows a four-pattern process under a nonuniform magnetic field. The mechanisms behind this behavior are influenced by the strength and gradient of the magnetic field, surface tension, droplet size, and the wetting boundary condition. These findings provide valuable insights into the application of ferrofluids in droplet microfluidics and contribute to advancements in this field.