Innovative Research and Applications in Hydrodynamics and Flow Control, 2nd Edition

In light of the European Union’s zero-emissions policy and the growing demand for energy associated with technological advances, it is necessary to consider adopting technologies and innovative solutions that simultaneously reduce greenhouse gas emissions while increasing potential extraction from existing hydrocarbon deposits, for example. This can result in increased production from deposits with low reservoir energy values or those in which the energy value does not allow the resource to be exploited on its own. By using a hydraulic drilling nozzle that harnesses the hydraulic energy of the fluid stream for workover, the possibility of increasing the contact between the reservoir layer and the producing well increases in direct proportion to the number of small-diameter radial wells drilled with a hydraulic rotary head from a horizontal well toward the reservoir layer. The main aspect of this paper is to outline an algorithm for the design of rotary drilling heads to maximize the use of the hydraulic energy from fluid streams flowing from the face of innovative drilling tools. The presented design algorithm allows changing the mutual position between the holes in the face section and the angle of the holes with respect to the longitudinal axis of the designed hydraulic rotary nozzle, simplifying the design work. The use of the rotary head developed using this algorithm enables seamless drilling in rocks with compressive strength R_c = 50 MPa, considering the drilling progress at ROP = 4 mm/s. Full article

The use of tag devices in marine environments has become indispensable in attaining a better understanding of marine life and contributing to conservation efforts. However, the successful deployment and operation of underwater tags both depend significantly on their hydrodynamic characteristics, particularly their resistance to motion and stability in various environmental conditions. Herein, a comprehensive study on the hydrodynamic characteristics and optimization of an underwater tag designed for monitoring blue sharks is presented. Firstly, a validation process is conducted by comparing the computational fluid dynamics (CFD) results with the experimental data from Myring’s study, focusing on the resistance characteristics of the tag’s body and the impact of various operational conditions. Subsequently, the validated CFD model is applied to assess the hydrodynamic performance of the tag under different flow conditions, velocities, and angles of attack. Through iterative simulations, including mesh independence studies and boundary condition adjustments, the study identifies key parameters influencing the tag’s resistance and stability. Furthermore, the paper proposes and implements design modifications, including the incorporation of stabilizing fins, aimed at minimizing resistance and improving the tag’s equilibrium position. The effectiveness of these design enhancements is demonstrated through a comparative analysis of resistance and pitching moments for both preliminary and optimized tag configurations. Overall, the study provides valuable insights into the hydrodynamic behavior of underwater tags and offers practical recommendations for optimizing their design to minimize interference with the movement of tagged marine animals. Full article

The entrance in the Sulina channel in the Black Sea is the target area of this study. This represents the southern gate of the seventh Pan-European transport corridor, and it is usually subjected to high navigation traffic. The main objective of the work is to provide a more comprehensive picture concerning the past and future expected dynamics of the environmental matrix in this coastal area, including especially the extreme wind and wave conditions in connection with the possible navigation risks. The methodology considered assumes analyses performed at three different levels. First, an analysis of some in situ measurements at the zero-kilometer point of the Danube is carried out for the 15-year period of 2009–2023. Together with the maximum wind speed and the maximum value of the wind gusts, the water level variation was analyzed at this point. As a second step, the analysis is based on wind speed data provided by regional climate models. Two periods, each spanning 30 years, are considered. These are the recent past (1976–2005), when comparisons with ERA5 reanalysis data were also performed, and the near future (2041–2070), when two different models and three climate scenarios were considered. The focus was on the extreme wind speed values, performing comparisons between the past and future expected extreme winds. Finally, the third analysis is related to the wave conditions. Thus, using as a forcing factor each of the wind fields that was previously analyzed, simulations employing a spectral wave model were carried out. The wave modeling system was focused using three different computational domains with increasing resolution towards the target area, and the nearshore wave conditions were evaluated. The results show that both the extreme wind and wave conditions are expected to slightly increase in the future. Especially in the wintertime, strong wind fields are often expected in this area, with wind gusts exceeding more than 70% of the hourly average wind velocity. With regard to the waves, due to the complex nearshore phenomena, considerable enhancements in terms of significant wave heights are induced, and there is also an elevated risk of the occurrence of rogue waves. This work is still ongoing, and taking into account the high navigation risks highlighted, the next step would be to elaborate the risk assessment of severe shipping conditions, particularly related to the likelihood or probability of adverse conditions with the potential of generating hazardous situations in this coastal environment. Full article

Predictions are presented of mean values of statistical variables of large-scale turbulent flow of the widely used basic k-$ϵ$ model, and of a new model, which is based on general statistical descriptions of turbulence. The predictions are verified against published results of direct numerical simulations (DNSs) of Navier–Stokes equations. The verification concerns turbulent channel flow at shear Reynolds numbers of 950, 2000, and ${10}^4$. The basic k-$ϵ$ model is largely based on empirical formulations accompanied by calibration constants. This contrasts with the new model, where descriptions of leading statistical quantities are based on the general principles of statistical turbulence at a large Reynolds number and stochastic theory. Predicted values of major output variables such as turbulent viscosity, diffusivity of passive admixture, temperature, and fluid velocities compare well with DNS for the new model. Significant differences are seen for the basic k-$ϵ$ model. Full article

Cyclone separators, which have a high separation performance, play a crucial role in mitigating the occurrence of dust explosion incidents. This study aims to improve the performance of an axial cyclone separator using the results of simulations employing the $\mathrm{RNG} k-\epsilon$ model together with a user-defined function to simulate the wall collision process. The effectiveness of various structural modifications to the vortex tube has been addressed. Specifically, we found that increasing the number of blades, reducing the blade exit angle, and adopting L-shaped blades increase separation efficiency. Additionally, enlarging the guide vane and exhaust pipe diameters, as well as increasing the exhaust pipe inclination angle, contribute to an improved separation performance due to the developed tangential velocity and vortex cores. However, it also increases the pressure drop losses due to the increase in the turbulence pulsation entropy and the wall entropy, while the time-averaged entropy is found to be less significant. As a result, our study sheds light on the flow characteristics, the gas–solid separation process, and the energy loss mechanism in the cyclone separator. Full article

A new area of underwater equipment research focus is the use of underwater unmanned vehicles (UUVs) with launch mechanisms to deploy lightweight and small-sized robots for functions including communication, exploration, and detection. The internal ballistic mathematical model of the underwater launch system for small robots is established in this paper. The internal ballistic parameters and the robot displacement and velocity change rule over time are obtained. The optimization calculation of the crucial parameters to be determined by the particle swarm algorithm is completed. Following optimization, the gas cylinder’s initial pressure is 2 MPa, its capacity is 30 L, its opening area is 9.683 × 10⁻⁵ m², and its opening time is 0.02 s. A numerical simulation is performed for the small robot’s underwater launch process, based on the mathematical and physical model supplied by Fluent 2020 software. The results yield the robot’s motion law and the properties of the flow field during the launch process. The purpose of the underwater launcher experiment is to determine the robot’s motion characteristics. The accuracy of the theoretical model is confirmed by comparing and analyzing the numerical simulation results with the actual data. Full article

Convolutional neural networks (CNN) have been widely adopted in fluid dynamics investigations over the past few years due to their ability to extract and process fluid flow field characteristics. Both in sparse-grid simulations and sensor-based experimental data, the establishment of a dense flow field that embeds all spatial and temporal flow information is an open question, especially in the case of turbulent flows. In this paper, a deep learning (DL) method based on computational CNN layers is presented, focusing on reconstructing turbulent open channel flow fields of various resolutions. Starting from couples of images with low/high resolution, we train our DL model to efficiently reconstruct the velocity field of consecutive low-resolution data, which comes from a sparse-grid Direct Numerical Simulation (DNS), and focus on obtaining the accuracy of a respective dense-grid DNS. The reconstruction is assessed on the peak signal-to-noise ratio (PSNR), which is found to be high even in cases where the ground truth input is scaled down to 25 times. Full article