Velocity Analysis Research Articles

Bouncing dynamics of binary equal-sized high-viscosity molten glass droplets in head-on collisions

Despite extensive research on head-on droplet collisions over the past decades, detailed investigations into the bouncing behavior of high-viscosity droplets, such as molten glass droplets, are still scarce. In this study, a volume-of-fluid method coupled with dual marker functions is employed to simulate the collision dynamics of molten glass droplets. The results show good agreement with experimental observations in both spatial and temporal dimensions. Theoretical analysis reveals a critical Weber number of 22 for bouncing and coalescence of molten glass droplets with a diameter of 100 μm. Below this threshold, we examine the bouncing behavior across various Weber numbers, categorizing the process into four distinct stages: mutual proximity, radial expansion, suction separation, and reverse separation, and providing a detailed analysis of velocity, pressure, and energy at each stage. As the Weber number increases, vortices sequentially emerge at 4, 8, 12, and 16, suggesting a strong correlation between droplet deformation and vortex generation. At lower Weber numbers, the air film pressure between droplets transitions smoothly between radial expansion and suction separation. However, between Weber numbers 9 and 22, a distinct concave pressure phenomenon is observed during suction separation. Pressure chattering occurs at the beginning of radial expansion and the end of suction separation. Furthermore, the results indicate that the cumulative viscous dissipation energy consistently approaches half of the initial kinetic energy, irrespective of the Weber and Ohnesorge numbers.

Unveiling mid-century conservation priorities: Co-occurrence of biodiversity, climate change exposure, and carbon storage in the Middle and Lower Yangtze River Basin, China

The global challenges of biodiversity loss and climate change necessitate the implementation of integrated conservation strategies. A forward-looking framework is necessary to reconcile climate change adaptation and mitigation efforts with biodiversity goals, supporting effective long-term planning and management of protected areas (PAs) network. This study develops a comprehensive approach to identify priority areas for biodiversity conservation until 2050, integrating assessments of species distributions, climate change exposure and carbon storage under distinct shared socioeconomic pathways. The Middle and Lower Yangtze River Basin (MLYRB) in China serves as a case study. Using an ensemble species distribution modeling (ESDM) method, we predicted the distributions of 435 threatened terrestrial vertebrate species and plants. We then mapped their richness in the MLYRB. Distance-based climate velocity analysis was performed to identify climate change coldspots and hotspots. The patch-generating land use simulation (PLUS) model and InVEST model were coupled to simulate carbon storage changes. Systematic conservation planning tool, Zonation, was used to prioritize species conservation hotspots. By examining the co-occurrence of these hotspots with climate change coldspots/hotspots and areas of high carbon storage, conservation priorities for the MLYRB were revealed. Our findings indicate that 18.27–24.94% of the MLYRB risks over 20% species richness declines by 2050 under various scenarios, while increases over 10% are projected for only 0.81–1.75% of the area. Co-occurrence analysis highlights significant associations, such as a 32.26% overlap between species conservation hotspots and climate change hotspots in SSP1-2.6. Particularly noteworthy is the substantial co-occurrence (57.93–59.50% across scenarios) between areas maximizing species conservation and carbon storage. The identified conservation priority areas, covering 41.95% of the MLYRB (441554km2), hold potential for long-term species conservation, climate resilience, and nature-based climate solutions by 2050. However, only 6.08% of these priorities currently benefit from protection. These results offer valuable guidance for region-specific landscape management and conservation policy aligned with international goals. The presented methodology provides a broader application, serving as a valuable resource for prioritizing conservation efforts in other regions integrating biodiversity, climate change adaptation, and mitigation goals.

High-Fidelity OC-Seislet Stacking Method for Low-SNR Seismic Data

Seismic stacking is a core technique in seismic data processing, aimed at enhancing the signal-to-noise ratio (SNR) of data by utilizing seismic data acquisition with multifold geometry. Traditional stacking methods always have certain limitations, such as the reliance on the accuracy of velocity analysis for dip moveout (DMO) in common midpoint (CMP) stacking. The seislet transform, a compression technique tailored to nonstationary seismic data, can compress and stack along the prediction direction of seismic data, which provides a new technical idea for high-fidelity seismic imaging based on the effectiveness of the compression. This paper introduces a high-order OC-seislet stacking method for low-SNR seismic data, capable of achieving the high-fidelity stacking of reflection and diffraction waves simultaneously. With the multi-scale analysis advantages of the seislet transform, this method addresses the dependency of DMO stacking on velocity analysis accuracy. In the frequency–wavenumber–scale domain, the correction compensation of the high-order CDF 9/7 basis function is used to obtain the compression coefficients of the high-order OC-seislet transform. This approach simultaneously stacks frequency–wavenumber information of reflection and diffraction waves with high fidelity while implementing DMO processing. After normalizing the weighting coefficients and applying soft thresholding for denoising, the final result is transformed back to the original time–space domain, yielding high-fidelity stacking sections. The results of applying this method to both synthetic and field data show that, compared with conventional DMO stacking methods, the high-order OC-seislet stacking technique reasonably represents dipping layers and fault amplitudes, and it can achieve a balance of a high SNR and high fidelity in stacked profiles.

Design of ION Thruster

Ion thrusters represent a significant advancement in electric propulsion, enhancing fuel efficiency by accelerating ions for thrust generation. These systems, demonstrated in missions such as Deep Space 1 and Dawn, facilitate substantial velocity changes with minimal propellant, making them suitable for long-duration space missions. This paper outlines the design of an ion thruster aimed at achieving a thrust of 0.2 Newton, focusing on the use of xenon as the propellant and employing highvoltage grids for ion acceleration. Key design aspects include an efficient power supply delivering at least 26 W, effective thermal management, and the integration of control systems. Performance metrics target a specific impulse of 3,000 seconds and a thrust-to-power efficiency ratio greater than 0.5. Through detailed calculations, including arc distance, flow configuration and velocity analyses and testing using different materials, this study identifies optimal configurations for thrust generation. The developed ion thruster is tailored for small satellites (700-800 kg) to enhance trajectory control and station-keeping, underscoring the importance of ion propulsion in modern space exploration

Progressive evolution of the viscous dissipation mechanism from the macroscale to the nanoscale

Recent studies of viscous dissipation mechanisms in impacting droplets have revealed distinct behaviours between the macroscale and nanoscale. However, the transition of these mechanisms from the macroscale to the nanoscale remains unexplored due to limited research at the microscale. This work addresses the gap using the many-body dissipative particle dynamics (MDPD) method. While the MDPD method omits specific atomic details, it retains crucial mesoscopic effects, making it suitable for investigating the impact dynamics at the microscale. Through the analysis of velocity contours within impacting droplets, the research identifies three primary contributors to viscous dissipation during spreading: boundary-layer viscous dissipation from shear flow; rim geometric head loss; and bulk viscous dissipation caused by droplet deformation. This prompts a re-evaluation of viscous dissipation mechanisms at both the macroscale and nanoscale. It reveals that the same three kinds of dissipation are present across all scales, differing only in their relative intensities at each scale. A model of the maximum spreading factor (βmax) incorporating all forms of viscous dissipation without adjustable parameters is developed to substantiate this insight. This model is validated against three distinct datasets representing the macroscale, microscale and nanoscale, encompassing a broad spectrum of Weber numbers, Ohnesorge numbers and contact angles. The satisfactory agreement between the model predictions and the data signifies a breakthrough in establishing a universal βmax model applicable across all scales. This model demonstrates the consistent nature of viscous dissipation mechanisms across different scales and underscores the importance of integrating microscale behaviours to understand macroscale and nanoscale phenomena.

Pattern detection in the vehicular activity of bus rapid transit systems

In this paper, we explore different methods to detect patterns in the activity of bus rapid transit (BRT) systems focusing on two aspects of transit: infrastructure and the movement of vehicles. To this end, we analyze records of velocity and position of each active vehicle in nine BRT systems located in the Americas. We detect collective patterns that characterize each BRT system obtained from the statistical analysis of velocities in the entire system (global scale) and at specific zones (local scale). We analyze the velocity records at the local scale applying the Kullback-Leibler divergence to compare the vehicular activity between zones. This information is organized in a similarity matrix that can be represented as a network of zones. The resulting structure for each system is analyzed using network science methods. In particular, by implementing community detection algorithms on networks, we obtain different groups of zones characterized by similarities in the movement of vehicles. Our findings show that the representation of the dataset with information of vehicles as a network is a useful tool to characterize at different scales the activity of BRT systems when geolocalized records of vehicular movement are available. This general approach can be implemented in the analysis of other public transportation systems.

Developmental patterns of athletic performance and physical fitness in youth baseball players: A longitudinal analysis

ABSTRACT This study aimed to evaluate developmental patterns in athletic performance during youth and determine their association with changes in physical fitness. The testing included three athletic performance (i.e. ball speed in pitching, swing velocity in batting, 30-metre sprint time) and two physical fitness tests (i.e. medicine ball [MB] back throw and modified star excursion balance test [SEBT]). Data from 235 players (557 measurements) aged 6 to 14 were eligible for a longitudinal evaluation. The statistical analysis was based on the latent growth curve models of the athletic performance development process and the random-effect panel data multivariate regression analysis for ball speed, swing velocity, and 30-metre sprint time. The 30-metre sprint time showed a small curvature but an accelerated increase around 12‒13 years old. However, the ball speed, swing velocity, and modified SEBT demonstrated a slower or less accelerated change in the developmental pattern starting around 12‒13 years old. Multivariate longitudinal analysis revealed that developmental change in athletic performance was positively associated with age and MB back throw. Our findings highlight the developmental patterns of athletic performance associated with baseball exhibiting stagnation as well as acceleration, which may help develop effective age-appropriate strategies for improving performance in youth baseball players.

Evaluating interseismic deformation patterns in the North Tabriz Fault (Iran) using enhanced fitting of velocity field and analysis of surface deformation

Understanding the mechanisms and locations of interseismic strain accumulation along faults is essential for assessing earthquake hazards. However, the mechanical response during the transition from deep fault locking to creep behavior remains uncertain. Estimating the slip deficit within these transition zones is challenging. This study challenges the assumption of a constant depth distribution of interseismic slip rate along the fault over time and proposes variable locking depths as an alternative model. By rejecting the constant locking depth assumption, singularity issues during stress theorem resolution are resolved. To address this, we employ a methodology considering creep propagation within a fully elastic medium. This approach incorporates long-term deformation resulting from viscoelastic flow in the upper mantle and lower crust. Including viscoelastic effects improves the fit to interseismic deformation rates, yielding lower locking depths compared to fully elastic models. To conduct the investigation, the GPS velocity field is recovered using the forward problem and the boundary element method. Subsequently, a physics-based inversion approach, deep interseismic creep, is employed to determine interseismic deformation patterns on a strike-slip fault. Furthermore, this study examined the correlation between the dislocation parameters and their relationship, as well as established the probability distributions associated with each faulting parameter. This research highlights the importance of considering variable locking depths in understanding interseismic strain accumulation and the transition to creep behavior along faults. The findings contribute to improved earthquake hazard assessment and mitigation strategies by providing valuable insights into fault behavior mechanics along the North Tabriz Fault.

Experimental Investigation of Meter-Level Resolution Radar Measurement at Ka Band in Yellow Sea

The backscatter characteristics of ocean surfaces are of great importance in active marine remote-sensing fields. This paper presents the high spatial and temporal resolution dual co-polarized (VV and HH) and cross-polarized (HV) Ka-band sea-surface backscattering measurements taken from the Yellow Sea research platform at incidence angles ranging from 30° to 50° and in the wind speed range from 5.8 to 8.6 m/s. The experimental results show that the backscattering coefficient in HH polarization is close to (or even surpassing) that in VV polarization within a wind speed range of 7.1 to 8.6 m/s for Ka band under high resolution at medium incidence angles (30°–50°). Further analysis of the 10-ms short-time observation samples found that the sea surface echoes in VV polarization are more sensitive to wave motions, exhibiting more complex scattering characteristics such as multi-peaks and reducing scattering energy, especially at high wind speeds and large incident angles. The Doppler velocity analysis also confirms that rapid ocean wave changes can be detected within a short observation period, especially in VV polarization. The research in this article not only demonstrates the high spatial and temporal resolution capabilities of Ka-band radar for ocean surface observation but also reveals its great potential in interpreting and inversing rapidly evolving marine phenomena.

Transient flow and noise characteristics of vortex-turbulence-noise interaction in centrifugal pump

Centrifugal pump operation noise is an avoidable common phenomenon in engineering practices, and its characteristics are closely influenced by the flow characteristics of the fluid. In this paper, a numerical simulation of centrifugal pump operation with different flow rates is carried out using the detached eddy simulation turbulence model and compared with the experimental results. Then the noise source and far-field radiated noise characteristics of the centrifugal pump are investigated using Lighthill’s analogy. The results show that the noise of centrifugal pump is closely related to the flow characteristics of impeller, especially the generation and development of vortex. The relationship between turbulent kinetic energy (TKE) and vortex is complex, involving the generation, development and shedding of vortex. The influence of flow rate variation on vortex structure in impeller is studied by vortex transport equation. It is found that the relative vortex stretching (RVS) term is the main driving force of vortex distribution. The distribution of the Coriolis force (CORF) term is mainly concentrated in the inlet and outlet areas of the flow channel, which is related to the rotational motion of the impeller and the dynamic characteristic of the fluid. The power spectral density inside the impeller is mainly concentrated in the low frequency region, indicating that the low frequency noise component is dominant in energy. The directivity curve of far-field noise pressure level is influenced by hydrodynamic effect, impeller rotation direction and pump design structure, and will have a certain deviation. The spectral curve analysis of velocity, vorticity, pressure and sound pressure level shows that these physical quantities have strong correlation on the spectrum, in which the low frequency component is large, and the high frequency component is complex and volatile.

Sex-specific proximal tubular cell differentiation pathways identified by single-nucleus RNA sequencing

Postnatal kidney growth is substantial and involves expansion in kidney tubules without growth of new nephrons, which are the functional units of the kidney. Proliferation and differentiation pathways underpinning nephron elongation are not well defined. To address this, we performed sequential characterization of mouse kidney transcriptomics at the single cell level. Single nuclear RNA sequencing (snRNA-seq) was performed on kidney tissue from male and female mice at 1, 2, 4 and 12 weeks of age using the 10x Chromium platform. Unbiased clustering was performed on 68,775 nuclei from 16 animals. 31 discrete cellular clusters were seen, which were identified through comparison of their gene expression profiles to canonical markers of kidney cell populations. High levels of proliferation were evident at early time points in some cell types, especially tubular cells, but not in other cell types, for example podocytes. Proliferation was especially evident in Proximal Tubular Cells (PTCs) which are the most abundant cell type in the adult kidney. Uniquely when compared to other kidney cell types, PTCs demonstrated sex-specific expression profiles at late, but not early, time points. Mapping of PTC differentiation pathways using techniques including trajectory and RNA Velocity analyses delineated increasing PTC specialization and sex-specific phenotype specification. Our single-cell transcriptomics data characterise cellular states observed during kidney growth. We have identified PTC differentiation pathways that lead to sex-specific tubular cell phenotypes. Tubular proliferative responses are of central importance in postnatal kidney growth and have also been linked to kidney recovery versus fibrosis following injury. Our unbiased and comprehensive dataset of tubular cell development can be used to identify candidate pathways for therapeutic targeting.

Undrained cyclic responses of sandy soils improved by soybean-induced calcium carbonate precipitation

ABSTRACT This study investigates the behaviour of sandy soils under cyclic conditions, emphasising the efficacy of soybean-induced calcium carbonate precipitation (SICP) treatment in mitigating liquefaction. Analysis of shear wave velocity and undrained cyclic responses was conducted, with a focus on understanding deformation response and development of excess pore pressure. Results revealed CaCO3 content as a definitive indicator for improvements in soil stiffness, with its distribution influenced by soil’s relative density and number of SICP injections. Enhanced cementation efficacy was observed in denser or deeper layers of sand column, attributed to prolonged SICP retention. A marked correlation between shear wave velocity and CaCO3 content highlighted SICP’s role in enhancing the liquefaction resistance of loose sandy soils. Dynamic triaxial testing showed the nuanced strain behaviours across varying relative densities and cyclic stress ratio (CSR) values, emphasising the strengthening influence of CaCO3 formations in the soil matrix. The empirical equation served as a testament to the potential of SICP in soil stabilisation endeavours. The intervention of SICP treatment presents a potent tool for bolstering soil stability, especially in regions susceptible to seismic activities. The insights garnered advocate for further research aimed at harnessing and optimising this soil improvement technique on a global scale.

Conceptual design of an autonomous single-container vessel

The growth of maritime shipping is leading to the creation of larger vessels. However, this expansion in size brings with it several challenges, including the development of maritime infrastructure, the potential for growth in third-world countries, and the emission of greenhouse gases. In response to these challenges, this research explores the feasibility of designing an autonomous ship capable of transporting a single standardized 40 ft. container overseas using mainly passive propulsion methods. Using advanced design tools, including CAD software and CFD simulations, as well as conducting a comprehensive analysis of relevant literature, the designs for a hull and sails were developed, and an overview of the potential active control systems required for autonomous operation was provided. The study also performed an initial analysis of strength, stability, and velocity to validate the design choices. The ship proves to adhere to the basic strength and stability requirements while reaching its maximum hull velocity at certain wind speeds. The results of the study indicate that it is possible to design and manufacture a mainly passively propelled ship capable of transporting a 40 ft. standardized container overseas and rethink the logistics at scale.

Paradigm on Levenberg–Marquardt neural algorithm analysis of heat conduction optimization for ternary hybrid nanofluid with entropy generation

AbstractThe significance of the present article is to enhance the thermal management and energy efficiency of complex engineering infrastructures such as energy storage systems, modern electric vehicles, thermal insulations, heavy‐duty machinery, and production units. This research aims to understand the intricate relationship between the thermal conductivity performance of ternary () hybrid nanomaterial and entropy generation to optimize material design and efficacy. A synergetic combination of three distinct nanomaterials silicon dioxide, ferric oxide, and titanium oxide with ethylene glycol and water in the ratio 3:2 as a base solvent is comprised of contributing unique thermophysical properties. To elucidate the impact of this hybrid composition on thermal conductivity, various factors are analyzed. The advanced computational technique of Artificial intelligent feed‐forward neural network (AIFFNN) is utilized. The problem governed the system of PDEs, which is transformed into ODEs by dimensionless similarity. Adams method provided the dataset which is filtered and embedded into Marquardt–Levenberg Algorithm (LMA). The study examines the role of nanomaterial constituents, morphology, and boundary conditions on thermal performance and entropy generation. Graphical analysis of velocity, temperature, and entropy is provided with respect to varying parameters, including surface absorption (λ), magnetic strength (Tesla M), radiation parameter (Rd), Brownian motion (Br), and Eckert number (Ec). The findings have practical significance for optimizing material design in engineering and industrial applications.

Interferometric Rayleigh Scattering for Flow Temperature and Velocity Analysis

A new processing method is developed to analyze images from a Fabry–Pérot interferometer in order to extract point measurements of temperature and velocity within a gas flow, using Rayleigh scattering. Two types of interferograms are generated from a Fabry–Pérot model combined with a simulated light source. The first type is obtained from a diffuse coherent light source, namely, a laser beam on a diffuser. The interferometer characteristics, defined by only two independent parameters, are retrieved within 0.1% accuracy. The knowledge of these parameters is mandatory to analyze interferograms from Rayleigh scattered light. The second type corresponds to Rayleigh scattered light from a small volume under flow conditions, lighted with a focused laser beam and captured with long exposure time. Several flow parameters are chosen to generate these interferograms. The relative errors on the temperature and velocity estimates are found to be weak. Noise is also added to assess the robustness of the processing method. The error induced by the estimates of the instrument function is found to be of second order compared to the error induced by the image analysis.

The influence of longitudinal duct profiling on unsteady gas dynamics and the heat transfer of pulsating gas flows in the outlet system of reciprocating-engine

Heat machines based on reciprocating-engines remain in demand in various fields of engineering and technology. Therefore, further research is needed to improve the efficiency, reliability, and environmental friendliness of engines. The thermomechanical improvement of non-stationary processes in outlet systems is an appropriate way to improve engine performance. The purpose of this research is to obtain and analyse the gas-dynamic and heat transfer characteristics of pulsating gas flows in an outlet system with ducts of various designs, using a laboratory model to simulate the outlet process in an engine. Thermal anemometry is used to receive data on the instant velocity values and local heat transfer coefficient of unsteady flows in ducts. The article examines two designs of outlet ducts, namely cylindrical (basic) and conical (with a taper of 0.0225) ducts. Spectral analysis of velocity, pressure and heat transfer coefficient pulsations, assessment of turbulence intensity, and calculation of flow characteristics of pulsating flows were performed to obtain detailed information on gas dynamics in the outlet system. The use of a conical duct (in comparison with a cylindrical one) leads to a slight increase in the turbulence intensity by up to 12 %, a decrease in the heat transfer coefficient by 15–20 %, and a change in volumetric gas flow within ± 7.5 %. Thus, the use of a conical duct will lead to the stabilisation of the flow in the outlet system, improved cleaning of the cylinder from outlet gases, a reduction in thermal stress, and a slight growth in the specific power of engines.

Exploring convective entropy optimization and activation energy impact on magneto-nanofluid flow over a vertical stretched plate with Hall current and nonlinear thermal radiation using SQLM

This paper investigates the profound impact of entropy generation and activation energy on the dynamics of hydromagnetic nanofluids, focusing on nonlinear thermal radiation, viscous and Ohmic dissipation, and Hall current effects over a linear stretching sheet. Various nanoparticles are incorporated into the nanofluid formulation using the thermophoresis and Brownian motion model. Through similarity transformation, the system of nonlinear equations is solved with high precision using the Spectral Quasilinearization Method (SQLM). Comprehensive analyses of velocity, cross-flow velocity, temperature, concentration, and entropy generation profiles are conducted for numerous physical parameters. Results indicate that velocity and cross-flow velocity increase with the Hall parameter while temperature and concentration profiles decrease. Both the velocity and cross-flow velocity profiles enhance for mixed convection parameters closer to the sheet, whereas the temperature and concentration profiles exhibit the contrary tendency. Prandtl number diminishes the profiles of horizontal velocity, cross-flow velocity and concentration distributions. Temperature distribution profile hikes for both the Brownian motion parameter and thermophoresis parameter. The activation energy parameter enhances the cross-flow velocity, with a corresponding decline in temperature distribution and a similar trend is observed in the concentration profile. Further, entropy generation profiles increase with higher Brinkman and Reynolds numbers while exhibiting mixed tendencies with the Schmidt number. These findings reveal that Hall current introduces complex interactions within the nanofluid flow, significantly influencing thermal, concentration, and entropy generation characteristics, particularly in magnetic fields and activation energy.

A Radar-Based Concept for Simultaneous High-Resolution Imaging and Pixel-Wise Velocity Analysis for Tracking Human Motion

A Radar-Based Concept for Simultaneous High-Resolution Imaging and Pixel-Wise Velocity Analysis for Tracking Human Motion

TBM Advanced Geological Prediction via Ellipsoidal Positioning Velocity Analysis

Traditional seismic wave-based tunnel advanced geological forecasting techniques are primarily designed for drill and blast method construction tunnels. However, given the fast excavation speed and limited prediction space in tunnel boring machine (TBM) construction tunnels, traditional methods have significant technical limitations. This study analyzes the characteristics of different types of TBM construction tunnels and, considering the practical construction conditions, identifies an effective observation system and data acquisition method. To address the challenges in advanced forecasting for TBM construction tunnels, a method of ellipsoid positioning velocity analysis, which takes into account the constraints of three-component data directions, is proposed. Based on the characteristics of the advanced forecasting observation system, this method compares the maximum values on the spatial isochronous ellipsoidal surface to determine the average velocity of the geological layer rays, thereby enabling accurate inversion of the spatial distribution ahead. Utilizing numerical simulation, a model for the advanced detection of typical unfavorable geological formations is established by obtaining the wave field response characteristics of seismic waves in three-dimensional space, and the velocity structure of the model is retrieved through this velocity analysis method. In the engineering example, the fracture property, water content, and weathering degree of the surrounding rock are predicted accurately.

Numerical Investigation of Flow Characteristics in Internally Flowing Pipes with Varying Roughness and Helical Angles of Vortex Generators

In this study, the turbulent behavior inside a pipe containing an aluminum helical vortex generator plate was investigated using computational fluid dynamics (CFD) methods, considering different plate roughness and helical angle values. Accordingly, numerical analyses of velocity and pressure distributions for a liquid flow with a constant inlet velocity of 0.5 m/s and four different helical angles were performed and compared in a computer software. To observe the effects of the roughness values of the metal plate on flow behavior, analyses were conducted for three different roughness values for each helical angle and the results were compared and interpreted. As a result of the study, the combination of a roughness value of 0.04 and a helical angle of 0° led to the highest pressure and velocity values, while the same roughness value combined with a 270° helical angle resulted in the lowest pressure and velocity values. Detailed analysis showed that helical angles (90° and 180°) presented moderate pressure and velocity values, indicating a non-linear relationship between helical angle and flow characteristics. The results demonstrate that optimizing the helical angle and roughness is crucial for enhancing the efficiency of vortex generators. This way, a design will be developed to prevent performance degradation in industrial applications that require flow efficiency and pressure management.