Abstract The effect of a square-mesh wire grid on the compressible flow of an organic vapor was investigated, utilizing a closed-loop wind tunnel facility working with the fluid Novec 649 in the dilute gas regime. Due to its thermodynamic properties, this working fluid enabled hot-wire anemometry investigations while avoiding typical issues related to calibration and data reduction as usually observed in compressible flows. Due to the low speed of sound, the mean velocity level could be kept low, which was helpful regarding frequency resolution issues. The results of the experiments conducted under essentially incompressible flow conditions agreed well with the predictions of the turbulence theory, and a good level of isotropy was achieved downstream of the grid. With increasing flow Mach number, the anisotropy of the turbulence increased, and the isotropy was practically lost at flow Mach numbers in the range of the grid choking Mach number. The flow Mach number normalized by the grid choking Mach number was identified as a useful, primary variable for presenting the experimental data.

Abstract The current high-accuracy fluid–solid coupling algorithms based on immersed boundary method with a multidirect forcing scheme are not efficient due to the absence of a criterion to properly stop the cycles of the multidirect forcing scheme with acceptable precision to avoid redundant calculations. Therefore, a criterion based on the immersed forces on different cycles is proposed to end the unnecessary calculations after satisfactory results are obtained during the simulation. The numerical tests are based on immersed boundary–lattice Boltzmann method (IB–LBM) with a case of an oscillating sphere. The results have shown that the criterion proposed is more efficient than the fixed-number multidirect forcing scheme to achieve the same accuracy, and the time consumed by the multidirect forcing scheme with the criterion is significantly less. To extend this approach to other simulations, the threshold of error can be determined by the case configurations.

Abstract Conventional signal decomposition of raw flow visualizations with a limited field of view fails to accurately identify cavitation instabilities in turbopump inducers. Therefore, a new deep learning-based framework is proposed to directly analyze visualization data and identify such instabilities. The framework employs a hybrid convolutional-recurrent neural network to learn the spatio-temporal features of instability modes. The trained model successfully captures alternate blade cavitation in a two-bladed inducer and super-synchronous rotating cavitation in a three-bladed inducer. Notably, the approach requires neither pre-processing of the visualization data nor extensive measurement durations, as only a few shaft revolutions are sufficient for accurate identification. By eliminating the dependence on unsteady pressure transducers, the proposed framework provides a robust tool for identifying turbopump inducer cavitation instabilities and can be extended to other systems where low-order modal patterns are dominant.

Abstract The erosion that results from droplet impact on a solid surface is significant for many parts of industrial machinery. Even though many modeling and experimental studies have been done on this subject, few have included quantitative research, particularly in regard to wind turbine blade erosion. Furthermore, most methods assume that there is no local turbulence or vortex shedding and that the striking droplets are perfectly spherical. This study focuses on examining droplet characteristics and movement in a controlled lab environment because the droplet erosion process could be influenced by multiple aspects, including the impact velocity, shape, and size of the droplets. For this, particle image velocimetry (PIV) techniques and high-speed imaging are employed. PIV is utilized in both disturbed and undisturbed flow regimes to quantify the size, velocity, and circularity of the falling droplets. Additional information on the droplets' travel path in the presence of turbulence can be obtained from high-speed camera images. A range of blunt needle gauge sizes 14 GA to 21 GA is used in the experiments to create distinct droplet sizes at different flow rates. It was observed that after each leading droplet, the blunt needles create a train of droplets of varying sizes. By employing PIV and high-speed imaging to investigate a larger range of needle sizes and flow rates, this study builds on the earlier research. It offers a more thorough understanding of droplet behavior and explains their properties and mobility in a laboratory setting under both disturbed and undisturbed flow circumstances. This is an important finding that will directly affect the amount of erosion and should be taken into account in any future modeling projects.

Abstract This study presents a unified geometrical theory framework for predicting the flow characteristics of nozzle flapper valves and annular restrictors employed in thrust bearing applications. Building on the minor loss formulation introduced in a previous work, the approach separates geometric effects from discharge phenomena, enabling accurate regression of the flow coefficient K across both incompressible and compressible regimes. The theory incorporates the simulation of choking and a blended discharge coefficient model that transitions smoothly between exponential and Busemann forms. Parameter identification is performed with a Levenberg–Marquardt algorithm, calibrated against experimental data from the Hayashi (nozzle flapper) and Belforte (aerostatic restrictor) test cases. Results demonstrate that the unified model reproduces measured K trends–including the decline of K at high Reynolds numbers and the onset of choking-more faithfully than the conventional equation proposed in literature, while requiring far fewer computational resources than full CFD simulations. Sensitivity analyses reveal the dominant influence on both geometric loss coefficients and discharge behavior of the design parameters tuned in the previous work, i.e. flow path parameter and Reynolds number. The validated framework offers a rapid, physics based tool for designers of precision pneumatic systems and aerostatic bearings, facilitating early stage sizing, performance optimization, and integration with Reynolds equation based load calculations without resorting to intensive numerical modelling.

Abstract The aerodynamic and aeroacoustic performance of wind turbines is strongly influenced by boundary layer transition, especially over thick trailing-edge airfoils commonly used near the blade root. Accurate prediction of transitional flow behavior is therefore critical for optimizing wind turbine efficiency and reducing noise emissions. In this study, a new transitional improved delayed detached-eddy simulation (IDDES) method, referred to as Tr-IDDES, is developed by coupling the γ–Reθt–k–ωSST transitional Reynolds-averaged Navier–Stokes (RANS) model into the IDDES framework. The Tr-IDDES method is applied to study the flow over the DU97FlatBack airfoil and is compared against the traditional fully turbulent IDDES (Ft-IDDES) method. The results demonstrate that the Tr-IDDES method successfully captures key transitional flow features such as laminar separation bubbles (LSBs) and boundary layer transition, which are not resolved by the Ft-IDDES model. It also demonstrates improved accuracy in predicting aerodynamic forces and better agreement with experimental results. Furthermore, the aeroacoustic behavior of the DU97FlatBack airfoil is studied using the IDDES methods and the Ffowcs-Williams and Hawkings equation for far-field noise prediction; the Tr-IDDES model more accurately predicts peak sound pressure levels and the spectral distribution of self-noise.

Abstract This research introduces an approach for modifying the wake structure of submersibles during descent by integrating flexible appendages onto their surface, with the goal of achieving drag reduction. To quantify the impact of these appendages on hydrodynamic drag and wake patterns, experiments employing a six-component force sensor and high-speed particle image velocimetry (PIV) were conducted on submersible models equipped with appendages of varying lengths. The findings indicate that flexible appendages can reduce drag by up to 8.7% during vertical descent. Analysis of the time-averaged and transient flow fields at a Reynolds number of 109,582 reveals that the appendages disrupt the wake vortices under vertical diving conditions. To elucidate the underlying mechanism, the proper orthogonal decomposition (POD) technique was applied. POD results demonstrate that the flexible appendages modify the vortex structure within the wake, leading to a reduction in vortex energy and a suppression of vortex shedding phenomena.

Abstract Offshore and onshore wind turbine blades present significant inspection, maintenance and repair challenges arising from location, economic drivers, environment and the specific blade architecture concerned. In-situ tasks have traditionally been undertaken by people abseiling from the tower or use of gantries. Harsh conditions associated with windy environs, along with pressures to limit downtime, have led to a range of new technologies becoming available. This paper presents results from the use of ultrasonic nondestructive testing (NDT) measurements of subsurface blade topography arising from in situ and static blade inspection for a range of wind turbine types. The measurements have been enabled using a hexapod robot that can accommodate NDT scanners within its chassis and can, using pneumatic suction for the robot pedipulators, navigate the convex, concave, and flexing form of in situ wind turbine blades. The arising NDT tomographic scans provide detailed information on blade integrity, the presence or otherwise of bonding materials, and local feature condition. Measurements, presented over a 600 mm traverse span, have confirmed the reliability of the robotic platform to deliver high-quality, consistent, and reliable data to be acquired with limited NDT experience and to allow subsurface inspections to be performed and analyzed remotely. In addition to detailed measurement of subsurface blade features, the robot system has also demonstrated the capacity to undertake functions such as lightning protection system verification.

Abstract Environmental conditions of a poultry incubator impact chick embryo development and pathogen survivability and spread. The current practices of monitoring and control based on limited sensor locations inside an incubator give incomplete knowledge of the overall spatiotemporal distributions of important environmental factors such as temperature, humidity, and carbon dioxide. To better understand the environmental conditions inside an incubator, a computational fluid dynamics (CFD) model was developed to predict air ventilation patterns and scalar transport in a small-scale commercial incubator with two egg racks (1620 eggs total) over 18-day incubation period. Various modeling approaches were investigated to identify cost-effective numerical models for long duration simulations. The CFD model was validated using experimental datasets procured at four interior locations measuring velocity, temperature, humidity, and CO2. The CFD model compared within 12% of the experimental data for velocity, temperature, and CO2 accumulation predictions, but showed higher 37% error for relative humidity (RH). The limitation in temperature predictions was attributed to challenges in modeling heat generation by the eggs. The large errors for relative humidity were attributed to the negligence of intermittent water spray. Overall, this study demonstrates the potential of CFD in accurately predicting complex biological spatiotemporal gradients of relevant environmental factors in a poultry incubator.

Abstract The independent effects of aqueous-phase salinity and acidity on oil–water dispersions remain insufficiently understood, as most prior investigations have emphasized mixed electrolytes containing monovalent and divalent salts to mimic crude-oil brines. As a result, the specific contribution of individual ionic species to emulsion stability has not been clearly established. The present study systematically examines the influence of sodium chloride and hydrochloric acid on the stability of emulsifier-free oil-in-water (O/W) and water-in-oil (W/O) emulsions. Emulsions were generated by mixing Exxsol™ D110 mineral oil with distilled water (DW) at 2500 rpm for 5 min. The oil-to-water density and viscosity ratios were maintained at 0.805 and 0.330, respectively. Sodium chloride concentrations in the aqueous phase were varied from 1 to 60 g L−1, while acidity was adjusted with 1.0 M HCl to achieve pH values between 4.80 and 1.88. Four dispersed-phase volume fractions (25%, 50%, 75%, and 90%) were investigated, and stability was assessed over time scales ranging from less than 1 min to approximately 4 h. Results demonstrate that elevated salinity and acidity substantially reduce the stability of O/W emulsions, particularly at higher water fractions (75% and 90%), where lifetimes decreased from several hours to only minutes. By contrast, W/O emulsions at 25% and 50% water fractions exhibited negligible sensitivity to aqueous-phase modifications, displaying consistently short stability times. These findings contribute to a more fundamental understanding of electrolyte-driven destabilization mechanisms in simple dispersions and establish a baseline for interpreting salt and acid effects in complex emulsion systems.