Vertical Axis Research Articles

Plane SV-waves scattering by seawater convex surface topography and underlying lined tunnel in a saturated half-space

Analytical solutions of boundary-valued problems for aboveground topography and underground buried structures, especially for sites with overlying seawater, have always been challenging. Based on the region decomposition technique (RDT) and Hankel integral transform method (HITM), SV-waves scattering by the convex circular topography with seawater and underlying tunnel in a saturated half-space is solved. The primary problem is tackling additional scattered waves introduced by the water–soil interface and convex topography, while ensuring boundary conditions are all met. To this end, scattering wave potential functions in cylindrical coordinates are first transformed into the Hankel integral form in Cartesian coordinates. This greatly facilitates the straightforward application of free boundary conditions at the soil–seawater flat interface, rather than making a large circular arc approximate assumption, which, in turn, avoids the resultant accumulating errors. Secondly, scattering problem to be solved is mathematically and analytically formulated as solving a 5 × 5 linear equation system comprised of wave functions inside the convex topography and lining tunnel while satisfying all physical continuous boundary conditions. This is the main innovation and resulting consequence from the theoretical derivation process. Finally, validation of numerical examples between this paper, existing studies and theoretical analysis further demonstrates the reliability and general adaptability of solutions. Parametric studies of the incident SV waves are conducted to investigate the spatially varying seismic response. The effects of SV-waves incident angles and frequencies, tunnel burial depth, tunnel lining thickness, saturated soil porosity, and seawater depth are investigated and analyzed in detail. This study provides a feasible scheme of investigating the dynamic response of complex submarine sites, which is of great significance for both theoretical value and engineering purposes.

Investigating rheological characteristics of nonlinear fluid model in an asymmetric channel: A peristaltic pumping of blood with curvature and hydrodynamic impacts

Theoretical research is investigated for the steady rheology of incompressible blood from an asymmetric (penetrable) channel in the presence of curvature and non-linear hydrodynamic impacts. The motion takes place in an asymmetric channel due to a train of sinusoidal (complex nature) waves along the channel boundaries having different phases. In this study, the Casson fluid is used as blood. The governing equations are modeled in terms of Cartesian coordinates. The impacts of non-linear curvature become significant on the transportation of biological fluid in a complex domain such as the non-pregnant uterus at a higher Reynolds number. An approximate solution of flow models is obtained to the second order in the wavenumber (giving the curvature effect). A domain transformation is used to transform the variable cross-sectional of the flow regime into the uniform cross-section. This transformation helps to find the closed-form solution of transformed rheological equations in higher order. The physical impacts of the curvature parameter, Casson parameter, phase difference, flow rate, Reynolds number, and permeability parameter on the axial velocity, pressure gradient, stress tensor, trapping phenomena, and pressure rise are investigated. The velocity of blood is smaller as it is associated with the viscous fluid. The number of boluses was reduced by increasing the Casson parameter and Reynolds number in the trapping phenomenon. The stress tensor is an increasing function of the permeability parameter and the Reynolds number. The pressure gradient is affected by the permeability parameter. The comparison between viscous fluid and blood is also addressed in the current study. The outcomes of the current study arise in the medical domains, blood study, manufacturing of nano-blood pumps, bio-physical food processing, and chemical industry.

Investigation on the Static Performance of Surface-Throttling Frictionless Pneumatic Cylinder through Finite Element Method

The equilibrium system is essential for the high-precision movement of the ultra-precision vertical axis. However, the complex assembly process makes orifice-throttling frictionless cylinders difficult to manufacture and prone to air hammering. Surface-throttling frictionless pneumatic cylinders effectively avoid these problems. This paper establishes an improved finite element method (FEM) model of a novel surface-throttling frictionless pneumatic cylinder to investigate its static performance. Furthermore, the static equilibrium calculation of the dual-cylinder system is concerned. The radial bearing capacity and support force requirements for the surface-throttling aerostatic bearings are obtained. The outcomes provide theoretical guidance for optimizing cylinder parameters. It ensures that the ultimately optimized cylinder meets the requirements for radial bearing capacity and support force of the ultra-precision vertical axis while minimizing air consumption. Finally, the accuracy of the proposed method is verified through computational fluid dynamics (CFD) calculation and experiments.

A testing theory for simultaneously determining asphalt mixture’s dynamic modulus in compression and tension by use of IDT test

The compressive and tensile moduli of asphalt mixtures are not equal. As a result, in order to obtain reasonable response calculation results, asphalt pavement mechanical analysis should first determine the compressive and tensile moduli of asphalt mixtures separately. Then, it should assign an appropriate modulus to the FEM element based on the stress state of the element. However, conventional uniaxial compression modulus testing protocol is typically unable to determine the actual asphalt pavement's coring specimen due to the limitation that general dynamic modulus testing protocol requires a larger size of specimen and conventional coring specimen from field usually cannot meet the requirement in regard to specimen size. In this case, the dynamic modulus of the asphalt mixture can only be ascertained using the IDT test method.Nevertheless, the current IDT test protocol is unable to distinguish between the compressive and tensile moduli of asphalt mixtures, and the testing results are usually different from those obtained by using the conventional uniaxial compression or tension method. This is because the current IDT test method for determining the dynamic modulus of asphalt mixtures generally treats asphalt mixtures as a kind of ideal elastic material and considers its compressive modulus is equal to its tensile modulus.Consequently, this paper presents a new theory, based on Ambartsumyan's bi-modulus constitutive relation theory, that can use the IDT test method to simultaneously determine the dynamic modulus of an asphalt mixture in both compression and tension. This theory assumes that the stress-strain relationship of asphalt mixture complies with the bi-modulus constitutive relation, and obtains the vertical deformation or horizontal deformation of the IDT specimen by solving a definite integral for the displacement of a small segment on the vertical or horizontal axis, which utilizes the results of the mathematical analysis of the stress distribution of the IDT specimen under distributed strip load. Then, the specimen's dynamic modulus in compression and tension can be obtained via back-calculating method, if the specimen's vertical and horizontal displacement are measured by a physical test in the lab. Obviously, this theory addresses the limitation of the conventional IDT method that cannot reflect the distinction of compressive modulus with tensile modulus, and can be better utilized to simultaneously determine compressive and tensile modulus of cored specimen from field. The verification test also demonstrates, the dynamic modulus determined by this theory are in line with the results of the conventional uniaxial test and is highly practicable.

ANN Enhanced Hybrid Force/Position Controller of Robot Manipulators for Fiber Placement

In practice, most industrial robot manipulators use PID (Proportional + Integral + Derivative) controllers, thanks to their simplicity and adequate performance under certain conditions. Normally, this type of controller has a good performance in tasks where the robot moves freely, performing movements without contact with its environment. However, complications arise in applications such as the AFP (Automated Fiber Placement) process, where a high degree of precision and repeatability is required in the control of parameters such as position and compression force for the production of composite parts. The control of these parameters is a major challenge in terms of quality and productivity of the final product, mainly due to the complex geometry of the part and the type of tooling with which the AFP system is equipped. In the last decades, several control system approaches have been proposed in the literature, such as classical, adaptive or sliding mode control theory based methodologies. Nevertheless, such strategies present difficulties to change their dynamics since their design consider only some set of disturbances. This article presents a novel intelligent type control algorithm based on back-propagation neural networks (BP-NNs) combined with classical PID/PI control schemes for force/position control in manipulator robots. The PID/PI controllers are responsible for the main control action, while the BP-NNs contributes with its ability to estimate and compensate online the dynamic variations of the AFP process. It is proven that the proposed control achieves both, stability in the Lyapunov sense for the desired interaction force between the end-effector and the environment, and position trajectory tracking for the robot tip in Cartesian space. The performance and efficiency of the proposed control is evaluated by numerical simulations in MATLAB-Simulink environment, obtaining as results that the errors for the desired force and the tracking of complex trajectories are reduced to a range below 5% in root mean square error (RMSE).

Hidden symmetry-induced effective moving double-zero-index metamaterials.

Materials possessing an effective zero refractive index are often associated with Dirac-like cone dispersion at the center of the Brillouin zone (BZ). It has been reported the presence of hidden symmetry-enforced triply degenerate points [nexus points (NP)] away from the Brillouin zone center with the stacked dielectric photonic crystals. The spin-1 Dirac-like dispersion in the xy plane near the nexus point suggests a method for achieving zero refractive index materials. The stacked photonic crystals at the nexus points can be deemed as an effective moving double-zero-index medium (MDZIM) traveling with a speed relative to the laboratory reference. The ability of this moving double-zero-index medium to enable perfect wave tunneling across barriers without reflection has been demonstrated, dependent on the incident waves' specific angular orientations.

Pano2Geo: An efficient and robust building height estimation model using street-view panoramas

Building height serves as a crucial parameter in characterizing urban vertical structure, which has a profound impact on urban sustainable development. The emergence of street-view data offers the opportunity to observe urban 3D scenarios from the human perspective, benefiting the estimation of building height. In this paper, we propose an efficient and robust building height estimation model, which we call the Pano2Geo model, by precisely projecting street-view panorama (SVP) coordinates to geospatial coordinates. Firstly, an SVP refinement stratagem is designed, incorporating NENO rules for observation quality assessment from four aspects: number of buildings, extent of the buildings, number of nodes, and orthogonal observations, followed by the application of the art gallery theorem to further refine the SVPs. Secondly, the Pano2Geo model is constructed, which provides a pixel-level projection transformation from SVP coordinates to 3D geospatial coordinates for locating the height features of buildings in the SVP. Finally, the valid building height feature points in the SVP are extracted based on a slope mutation test, and the 3D geospatial coordinates of the building height feature points are projected using the Pano2Geo model, so as to obtain the building height. The proposed model was evaluated in the city of Wuhan in China, and the results indicate that the Pano2Geo model can accurately estimate building height, with an average error of 1.85 m. Furthermore, compared with three state-of-the-art methods, the Pano2Geo model shows superior performance, with only 10.2 % of buildings have absolute errors exceeding 2 m, compared to the Map-image-based (27.2 %), Corner-based (16.8 %), and Single-view-based (13.9 %) height estimation methods. The SVP refinement method achieves optimal observation quality with less than 50 % of existing SVPs, leading to highly efficient building height estimation, particularly in areas of a high building density. Moreover, the Pano2Geo model exhibits robustness in building height estimation, maintaining errors within 2 m even as building shape complexity and occlusion degree increase within the SVP. Our source dataset and code are available at https://github.com/Giser317/Pano2Geo.git.

MolSym: A Python package for handling symmetry in molecular quantum chemistry.

A consideration of the point group symmetry of molecules is often advantageous from a computational efficiency standpoint and sometimes necessary for the correct treatment of chemical physics problems. Many modern electronic structure software packages include a treatment of symmetry, but these are sometimes incomplete or unusable outside of that program's environment. Therefore, we have developed the MolSym package for handling molecular symmetry and its associated functionalities to provide a platform for including symmetry in the implementation and development of other methods. Features include point group detection, molecule symmetrization, arbitrary generation of symmetry element sets and character tables, and symmetry adapted linear combinations of real spherical harmonic basis functions, Cartesian displacement coordinates, and internal coordinates. We present some of the advantages of using molecular symmetry as achieved by MolSym, particularly with respect to Hartree-Fock theory, and the reduction of finite difference displacements in gradient/Hessian computations. This package is designed to be easily integrated into other software development efforts and may be extended to further symmetry applications.

Natural Frequency Transmissibility for Detection of Cracks in Horizontal Axis Wind Turbine Blades.

Defects on horizontal axis wind turbine blades are difficult to identify and monitor with conventional forms of non-destructive examination due to the blade's large size and limited accessibility during continuous operation. This article examines both strain and acceleration transmissibility as methods of continuous damage detection on wind turbine blades. A scaled 117 cm offshore wind turbine blade was first designed, 3D printed, and modelled numerically in ANSYS. Transverse cracks were deliberately introduced to the blade at 10 cm intervals along its leading edge. Subsequent changes in the transmissibility, relative to an undamaged baseline model, were measured using different variable combinations at the blade's first three natural frequencies. Experimental results indicated that strain transmissibility was able to locate a 1.0 cm defect at a range of 70-110 cm from the blade hub using the amplitudes of the first natural frequency of vibration. The numerical model was able to simulate the strain experimental results and was determined to be valid for future defect characterization. Acceleration transmissibility was unable to experimentally identify defects sized at 1.0 cm and below but was able to identify 1.0 cm sized defects numerically. It was concluded that transmissibility is viable for continuous damage detection on blades but that further research into other defect types and locations is required prior to conducting full-scale testing.

Geometric epitope and paratope prediction.

Identifying the binding sites of antibodies is essential for developing vaccines and synthetic antibodies. In this article, we investigate the optimal representation for predicting the binding sites in the two molecules and emphasize the importance of geometric information. Specifically, we compare different geometric deep learning methods applied to proteins' inner (I-GEP) and outer (O-GEP) structures. We incorporate 3D coordinates and spectral geometric descriptors as input features to fully leverage the geometric information. Our research suggests that different geometrical representation information is useful for different tasks. Surface-based models are more efficient in predicting the binding of the epitope, while graph models are better in paratope prediction, both achieving significant performance improvements. Moreover, we analyze the impact of structural changes in antibodies and antigens resulting from conformational rearrangements or reconstruction errors. Through this investigation, we showcase the robustness of geometric deep learning methods and spectral geometric descriptors to such perturbations. The python code for the models, together with the data and the processing pipeline, is open-source and available at https://github.com/Marco-Peg/GEP.

Real-time tracing and location for critical parts of moving objects with single-pixel detection

A scenario based on single-pixel input of recognizing and tracing the critical parts of the moving targets has been proposed. The one-dimensional single-pixel matrix is achieved by bucket measurement by making use of pre-training illumination suitable for the target datasets. The designed recognition network can export the real-time position coordinates of the key components of the moving targets through single-pixel detection. Compared with the general random illumination light field, the results of the pre-training illumination show significant improvement in both recognition efficiency and accuracy. The recognition efficiency can reach 100Hz in the experimental detection of moving model planes. It may have important application prospects in military target tracking and hyperspectral remote sensing.

Anisotropy in shale and its impact on AVO modelling and prospect de-risk: a case study of a Central North Sea field

The inherent anisotropy in shale is an attribute associated with its clay minerals platelets alignment and layering and very common with transversely isotropic (TI) medium. This implies that velocity is fastest along the horizontal axis and slowest along the vertical axis, which could affect velocity signature from sonic tools measurements in deviated wells. This may lead to wrong amplitude variation with offset (AVO) signature, inaccurate depth conversions, seismic-to-well tie difficulty etc. Nineteen (19) wells in Forties field andthirteen (13) in Huntington field were investigated and interpreted for the presence of anisotropy effect within the caprock over the reservoir Forties sands of the Sele (shales) Formation. In order to analyse the Thomsen weak anisotropy parameters (ϵ, γ and δ) per field, wells with closer Sele depth range were considered. The well inclinations ( θ ), average compressional (α) and shear (β) velocities per well were utilised for forward and inverse modelling of Thomsen anisotropy equations. The estimated anisotropy (VTI) parameters and the P-wave ( α o ) and S-wave velocities (βo ) at zero inclinations in Sele Formation for the studied wells are: α o = 2448 ± 15.9 m/s, β o = 1003 ± 34.8 m/s, ϵ = 0.15 ± 0.02, γ = 0.33 ± 0.10, δ = 0.030 ± 0.015 in the Forties field Sele, while α o = 2775 ± 23.6 m/s, β o = 1306 ± 47.9 m/s, ϵ = 0.22 ± 0.02, γ = 0.43 ± 0.14, δ = 0.022 ± 0.018 in the Huntington field. AVO responses were compared, assuming both isotropic and anisotropic P–P reflectivity models. Result shows an increase in AVO gradient for all anisotropic case in both fields. AVO signatures were either completely or averagely masked in both fields using the isotropic assumptions. There is also an increase in AVO gradient for all anisotropic cases in both fields. Velocity decreases of about 1.2% and 3.5% were observed in the Sele Formation for the Forties and Huntington fields respectively for anisotropy. The corrected two-way traveltime (TWT) should in principle allow for a better seismic-to-well tie estimation. Similarly, using the faster deviated velocity (i.e. uncorrected velocity) in any depth conversion would result in under estimation of the actual depth across the field.

Development and modeling of algorithms for calculating target angle in the coordinate system of the onboard radar

The article is devoted to the development of algorithms for calculating the target angle in the coordinate system of an onboard radar and modeling their operation. To construct an algorithm for calculating the target angle, a fixed terrestrial coordinate system and a moving coordinate system of an onboard radar are used. Expressions are presented for recalculating the Cartesian coordinates of an object from the earth coordinate system to the on-board radar coordinate system. The concept of azimuth and elevation planes is introduced for the coordinate system of an onboard radar. Algorithms for calculating target angles in the azimuthal and elevation planes are presented. It is shown that the algorithm for calculating the target angle in the elevation plane has a different form depending on the sign of the target elevation angle. In addition, the type of the mentioned algorithm depends on whether the target is approaching or moving away from the onboard radar. The resulting algorithms for calculating the target angle use information about the coordinates of the target speed in the coordinate system of the onboard radar. Since the coordinates of the velocity vector in the onboard radar cannot be measured, they are estimated from two contacts with the target during the review period. Modeling of the developed algorithms has been carried out.

Moving object detection based on bioinspired background subtraction

Flying insects rely mainly upon visual motion to detect and track objects. There has been a lot of research on fly inspired algorithms for object detection, but few have been developed based on visual motion alone. One of the daunting difficulties is that the neural and circuit mechanisms underlying the foreground-background segmentation are still unclear. Our previous modeling study proposed that the lobula held parallel pathways with distinct directional selectivity, each of which could retinotopically discriminate figures moving in its own preferred direction based on relative motion cues. The previous model, however, did not address how the multiple parallel pathways gave the only detection output at their common downstream. Since the preferred directions of the pathways along either horizontal or vertical axis were opposite to each other, the background moving in the opposite direction to an object also activated the corresponding lobula pathway. Indiscriminate or ungated projection from all the pathways to their downstream would mix objects with the moving background, making the previous model fail with non-stationary background. Here, we extend the previous model by proposing that the background motion-dependent gating of individual lobula projections is the key to object detection. Large-field lobula plate tangential cells are hypothesized to perform the gating to realize bioinspired background subtraction. The model is shown to be capable of implementing a robust detection of moving objects in video sequences with either a moving camera that induces translational optic flow or a static camera. The model sheds light on the potential of the concise fly algorithm in real-world applications.

Dynamics of novel soliton and periodic solutions to the coupled fractional nonlinear model

This study secures the soliton solutions of the (2+1)-dimensional Davey–Stewartson equation (DSE) incorporating the properties of the truncated M-fractional derivative. The DSE and its coupling with other systems have extensive applications in many fields, including physics, applied mathematics, engineering, hydrodynamics, plasma physics, and nonlinear optics. Various solutions, such as dark, singular, bright-dark, bright, complex, and combined solitons, are derived. In addition, exponential, periodic, and hyperbolic solutions are also generated. The newly designed integration method, known as the modified Sardar subequation method (MSSEM), has been applied in this study for extracting the solutions. The approach is efficient in explaining fractional nonlinear partial differential equations (FNLPDEs) by confirming pre-existing solutions and producing new ones. Furthermore, we plot the density, 2D, and 3D graphs with the associated parameter values to visualize the solutions. The outcomes of this work indicate the effectiveness of the method utilized to improve nonlinear dynamical behavior. We anticipate that our work will be helpful for a large number of engineering models and other related problems.

3DSGIMD: An accurate and interpretable molecular property prediction method using 3D spatial graph focusing network and structure-based feature fusion

A comprehensive representation of molecular structure is essential for establishing accurate and reliable molecular property prediction models. However, fully extracting and learning intrinsic molecular structure information, especially spatial structure features, remains a challenging task, leading that many molecular property prediction models still have no enough accuracy for the real application. In this study, we developed an innovative and interpretable deep learning method, termed 3DSGIMD, which predicted the molecular properties by integrating and learning the spatial structure and substructure information of molecules at multiple levels, and generated the focusing weights by aggregating spatial and adjacency information of molecules to improve understanding of prediction results. We evaluated the model on 10 public datasets and 14 cell-based phenotypic screening datasets. Extensive experimental results indicated that 3DSGIMD achieved superior or comparable predictive performance compared with some existing models, and the individually designed components contributed significantly to the advanced performance of the model. In addition, we also provided insight into the interpretability of our model via visualizing the focusing weights and perturbation analysis, and the results showed that 3DSGIMD can pinpoint crucial local structures and bits of molecular descriptors associated with the predicted properties. In summary, 3DSGIMD is a competitive molecular property prediction method that holds the potential to aid drug design and optimization.

Large-eddy simulations of turbulent wake flows behind helical- and straight-bladed vertical axis wind turbines rotating at low tip speed ratios

Large-eddy simulations of turbulent wake flows behind helical- and straight-bladed vertical axis wind turbines rotating at low tip speed ratios

Prediction of Back Disability Using Clinical, Functional, and Biomechanical Variables in Adults with Chronic Nonspecific Low Back Pain.

Background: Researchers are focusing on understanding the etiology and predisposing factors of chronic nonspecific low back pain (CNSLBP), a costly prevalent and disabling disorder. Related clinical, functional, and biomechanical variables are often studied, but in isolation. We aimed to identify key factors for managing CNSLBP by examining the relationship between back disability and related clinical, functional, and biomechanical variables and developed prediction models to estimate disability using various variables. Methods: We performed a cross-sectional correlational study on 100 recruited patients with CNSLBP. Clinical variables of pain intensity (visual analog score), back extensor endurance (Sorenson test), functional variables of the back performance scale, 6 min walk test, and the biomechanical variable C7-S1 sagittal vertical axis were analyzed to predict disability (Oswestry disability index). Results: All variables independently, as well as in multi-correlation, were significantly correlated to disability (p < 0.05). The bivariate regression models were significant between back disability and pain intensity (Y = 11.24 + 2.189x), Sorensen results (Y = 105.48 - 0.911x), the back performance scale (Y = 6.65 + 2.486x), 6 min walk test (Y = 49.20 - 0.060x), and sagittal vertical axis (Y = 0.72 + 4.23x). The multi-regression model showed significant contributions from pain (p = 0.001) and Sorensen results (p = 0.028) in predicting back disability, whereas no significant effect was found for other variables. Conclusions: A multidisciplinary approach is essential not only for the management of but also for the assessment of chronic nonspecific low back pain, including its clinical, functional, and biomechanical characteristics. However, special emphasis should be placed on clinical characteristics, including the intensity of pain and back extensor endurance.

Multi-Objective Optimization Design of Dynamic Performance of Hydrofoil with Gurney Flap

The horizontal axis tidal turbine, as a crucial device for capturing tidal energy, has gained significant attention because it has better energy efficiency performance. Enhancing the performance of foils, a vital part of tidal turbine blades, can significantly improve tidal turbine performance. Among numerous methods to enhance the foil performance, the Gurney flap has gained significant attention due to its avoidance of complex structural design. Currently, there is limited research on optimizing the design of Gurney flaps while considering the dynamic performance of foils. In this study, the S809 foil with a blade cross-section was selected as the research subject, a multi-objective optimization design platform was created by integrating a multi-objective optimization algorithm with Computational Fluid Dy-namics (CFD) numerical simulation techniques. The objective of this platform is to enhance the dynamic performance of the hydrofoil by optimizing the geometric structure of the Gurney flap. The improvement of dynamic lift and the size of the dynamic stall hysteresis loop are used as objective variables in this study to evaluate the hydrofoil’s dynamic performance. The optimal Latin hypercube design method is used in the optimization process to choose sample locations, and the Kriging approximation model is used to determine the relationship between the design variables and the objective variables. Meanwhile, the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is used to create a multi-objective optimization platform for solving the optimization problem, and the optimized results are validated using CFD. Comparative validation results show that quantifying the dynamic performance during hydrofoil pitching oscillation and using the optimal Latin hypercube design method and Kriging approximation model for optimizing the Gurney flap structure is rational and accurate. This study explores the mechanism of the Gurney flap through in-depth CFD numerical simulations and finds that the Gurney flap affects the flow characteristics at the hydrofoil’s trailing edge, thereby influencing the performance. It increases the pressure difference between the pressure and suction surfaces, thus enhancing the hydrofoil’s lift. Finally, this article provides three recommended parameters to improve the dynamic performance of the hydrofoil. This research can serve as a reference for the application of Gurney flaps in tidal turbine blade design.

An Integrated Geometric Obstacle Avoidance and Genetic Algorithm TSP Model for UAV Path Planning

In this paper, we propose an innovative approach for the path planning of Uninhabited Aerial Vehicles (UAVs) that combines an advanced Genetic Algorithm (GA) for optimising missions in advance and a geometrically based obstacle avoidance algorithm (QuickNav) for avoiding obstacles along the optimised path. The proposed approach addresses the key problem of determining an optimised trajectory for UAVs that covers multiple waypoints by enabling efficient obstacle avoidance, thus improving operational safety and efficiency. The study highlights the numerous challenges for UAV path planning by focusing on the importance of both global and local path planning approaches. To find the optimal routes, the GA utilises multiple methods of selection to optimise trajectories using the Cartesian Coordinate System (CCS) data transformed from a motion capture system. The QuickNav algorithm applies linear equations and geometric methods to detect obstacles, guaranteeing the safe navigation of UAVs and preventing real-time collisions. The proposed methodology has been proven useful in reducing the total distance travelled and computing times and successfully navigating UAVs across different scenarios with varying numbers of waypoints and obstacles, as demonstrated by simulations and real-world UAV flights. This comprehensive approach provides advantageous perspectives for real-world applications in a variety of operational situations and improves UAV autonomy, safety, and efficiency.