Aerospace Science and Technology最新文献

{"title":"Aerodynamic shape optimization in transonic conditions through parametric model embedding","authors":"","doi":"10.1016/j.ast.2024.109611","DOIUrl":"10.1016/j.ast.2024.109611","url":null,"abstract":"<div><div>The paper presents a novel approach for aerodynamic shape optimization problems using the parametric model embedding (PME) method. PME reduces the design-space dimensionality while maintaining a connection to the original design parameters, addressing the curse of dimensionality. The optimization of an airfoil's drag in transonic conditions demonstrates the method, using the RAE-2822 airfoil at Mach 0.734 and a Reynolds number of 6.5 million. Employing the covariance matrix adaptation evolution strategy, the process is performed with 1,000 function evaluations in both original and PME-reduced design spaces. Moreover, statistical criteria based on advanced risk function are introduced to characterize and study the evolution of the optimization process. Results show that PME effectively retains essential design space characteristics, capturing at least 95% of the geometric variance associated with the original design space. This leads to significant aerodynamic improvements, including reduced drag and smoother pressure distributions. Additionally, the statistical analysis helps to understand the advantages and disadvantages of different levels of parameter space compression.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142358477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient multi-fidelity reduced-order modeling for nonlinear flutter prediction","authors":"","doi":"10.1016/j.ast.2024.109612","DOIUrl":"10.1016/j.ast.2024.109612","url":null,"abstract":"<div><div>Flutter prediction is an important part of aircraft design. However, high-fidelity predictions for transonic flutter are difficult to make because of the associated computational costs. This paper proposes a multi-fidelity reduced-order modeling (MFROM) framework for flutter predictions to achieve high-fidelity simulations with limited computational costs. The high-fidelity data were obtained from a Navier–Stokes-equation-based solver, while the low-fidelity data were taken from an Euler-equation-based flow solver. By employing a multi-fidelity neural network trained with two types of data, this methodology enables nonlinear predictions for transonic results. To demonstrate the multi-fidelity process, a widely used pitching and plunging airfoil case is considered. Verification of the approach was performed by comparing with results from time-domain aeroelastic solvers. The results showed that the proposed multi-fidelity neural network modeling framework could realize online predictions of unsteady aerodynamic forces and flutter responses across multiple Mach numbers. Compared with the typical multi-fidelity method, the proposed neural network has a higher accuracy and a stronger generalization capability. Finally, the potential of the method to reduce the computational effort of high-fidelity aeroelastic analysis was demonstrated.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relative position estimation using modulated magnetic field for close proximity formation flight","authors":"","doi":"10.1016/j.ast.2024.109597","DOIUrl":"10.1016/j.ast.2024.109597","url":null,"abstract":"<div><div>This paper presents a method to estimate relative position vectors between spacecraft equipped with magnetic coils and magnetic field sensors for close proximity operation. Filters can segregate a magnetic field with a particular frequency if spacecraft drive their coils with this specific frequency. The proposed method utilizes the amplitude of the magnetic field with a particular frequency to estimate relative position vectors. The method consists of an initial position estimator and a sequential position estimator, which is an unscented Kalman filter. The initial position estimator provides a coarse estimate for the relative position vectors using the segregated magnetic field. Relation between the magnetic field and relative position vector is derived analytically in this article for the initial position estimator. The unscented Kalman filter refines the estimation accuracy by initializing the filter with the estimate by the initial position estimator. It is shown that a spacecraft can conduct relative position vector estimation using the magnetic field of a target spacecraft, provided that a few conditions clarified in the article are satisfied. Finally, the proposed estimators are evaluated numerically via simulations.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental study on the effects of substrate hydro-/icephobicity on ice mitigation and ice shedding during the dynamic icing process over the rotating propeller of an unmanned-aerial-vehicle","authors":"","doi":"10.1016/j.ast.2024.109610","DOIUrl":"10.1016/j.ast.2024.109610","url":null,"abstract":"<div><div>In the present study, a comparative study was performed to evaluate the anti-/de-icing performance of a traditional superhydrophobic and a novel ice-phobic coating, on the dynamic icing process over the rotating propeller of a four-rotor Unmanned-Aerial-Vehicles (UAVs). The test was conducted by leveraging an icing test facility at the Aeronautics and Astronautics Department of Shanghai Jiao Tong University, which duplicates the hovering state of a UAV under typical icing conditions. During the experiments, a high-speed imaging system was utilized to record the snapshots of the dynamic icing and ice-shedding details. The detailed icing information was then extracted from the images by using the post-processing code. In addition, the Hall current sensor was used to record the power consumption during the icing process. Two coatings, a traditional Superhydrophobic coating, and an organic-inorganic hybrid ice-phobic coating were applied to achieve ice mitigation and to reduce the penalty during the dynamic icing process. Under a relatively high humidity situation, the application of traditional Superhydrophobic coating was found to have more icing area, showing no observable ice shedding within 200 s icing duration time, which requires 80% more energy to maintain the system to work properly, in comparison to 120% of baseline. The novel ice-phobic coating introduced a new idea to simultaneously achieve relatively high hydrophobicity and high icephobicity, which presents the periodic ice shedding phenomenon during 200 icing duration time, with more than 50% power consumption reduction after ice shedding occurring under the same icing environment, working with only 25% and 20% power consumption level compared to SHS treated case and baseline, respectively.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design perspectives of a system identification approach of the NATO AVT-316 multi-swept wing aerodynamics","authors":"","doi":"10.1016/j.ast.2024.109603","DOIUrl":"10.1016/j.ast.2024.109603","url":null,"abstract":"<div><div>Air supremacy requires enhanced maneuvering capabilities at high angles of attack and even beyond the stall angle. High angle-of-attack (high-<em>α</em>) maneuverability can be achieved using swept wings and tailored leading-edge shapes to replace local and disorganized flow separation with controlled separation-induced leading-edge vortices (LEV). Strong leading-edge vortices delay the stall to higher angles and generate a non-linear lift increment up to the angle of attack where the jet-type flow structure of LEV changes to a reversed-flow bubble (vortex breakdown phenomenon). A multi-swept wing configuration has the potential to delay the vortex breakdown to even higher angles as the vortices formed over the front wing can energize vortices formed over the main wing and lead to vortex merging. This article is focused on understanding the unsteady interactions between multiple leading edge vortices formed over multi-swept wing configurations in the subsonic speed regime. Specifically, this article investigates the aerodynamic characteristics of wings being evaluated under the initiative of the NATO STO AVT-316 Task Group. Highly refined meshes, and the use of hybrid turbulence models such as Detached Eddy Simulations (DES) and Delayed DES are required to accurately resolve the vortical flows over these wings. Simulating all flow conditions of interest is a computationally expensive approach. A system identification method was therefore proposed to rapidly and accurately generate aerodynamic models of these wings. The method uses a novel piece-wise chirp (constant amplitude and increasing frequency) motion as an input signal (training maneuver). The motion computational cost is equivalent to the cost of six static CFD simulations, however it can predict aerodynamic responses of the wings over a wide range of angles of attack. The method has been tested for double and triple delta wings. Some design considerations are provided based on predicted flow features and aerodynamic data. Prediction results with different turbulence models, sting geometries, grid resolutions and an adaptive mesh refinement approach are provided.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graph-accelerated non-intrusive polynomial chaos expansion using partially tensor-structured quadrature rules for uncertainty quantification","authors":"","doi":"10.1016/j.ast.2024.109607","DOIUrl":"10.1016/j.ast.2024.109607","url":null,"abstract":"<div><div>Recently, the graph-accelerated non-intrusive polynomial chaos (NIPC) method has been proposed for solving uncertainty quantification (UQ) problems. This method leverages the full-grid integration-based NIPC method to address UQ problems while employing the computational graph transformation approach, AMTC, to accelerate the tensor-grid evaluations. This method exhibits remarkable efficacy on a broad range of low-dimensional (three dimensions or less) UQ problems featuring multidisciplinary models. However, it often does not scale well with problem dimensions due to the exponential increase in the number of quadrature points when using the full-grid quadrature rule. To expand the applicability of this method to a broader range of UQ problems, this paper introduces a new framework for generating a tailored, partially tensor-structured quadrature rule to use with the graph-accelerated NIPC method. This quadrature rule, generated through the designed quadrature approach, possesses a tensor structure that is tailored for the computational model. The selection of the tensor structure is guided by an analysis of the computational graph, ensuring that the quadrature rule effectively capitalizes on the sparsity within the computational graph when paired with the AMTC method. This method has been tested on one 4D and one 6D UQ problem, both originating from aircraft design scenarios and featuring multidisciplinary models. Numerical results show that, when using with graph-accelerated NIPC method, our approach generates a partially tensor-structured quadrature rule that outperforms the full-grid Gauss quadrature and the designed quadrature methods (more than 40% reduction in computational costs) in both of the test problems.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid identification and early warning of axial compressor stall based on multiscale CNN-SVM-FC model","authors":"","doi":"10.1016/j.ast.2024.109604","DOIUrl":"10.1016/j.ast.2024.109604","url":null,"abstract":"<div><div>Early prewarning of compressor stall and surge is crucial to avoid aircraft engine instability, yet it is challenging due to the complex and unstable flow field characterized by multiple modes and multiscale features. To enhance the multi-scale feature representation capability of Convolutional Neural Network-Support Vector Machine (CNN-SVM) algorithm, a novel classifier modelling method combined multiscale windows with CNN-SVM is introduced for stall prewarning in this paper, named Multiscale CNN-SVM-FC. Multiscale detection windows are utilized to adaptively identify various pressure features during the stall process. Additionally, to reduce the false alarm rate, a fuzzy control algorithm is integrated with the temporal accumulation of prediction results from the multi-branch network for joint analysis. A series of test data from a five-stage axial compressor at different operating speeds is used to verify this method. The results indicate that the proposed Multiscale CNN-SVM-FC method enhances the accuracy of classification and reduces the false alarm rate compared to the standard CNN-SVM model, achieving over 99% accuracy in identifying unstable states under various speeds. Compared to three traditional stall prewarning methods, the Multiscale CNN-SVM-FC model provides an average warning signal 164 milliseconds ahead of stall, and reduces the uncertainty associated with threshold selection, which typically relies on engineering experience.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive neural network based quadrotor UAV formation control under external disturbances","authors":"","doi":"10.1016/j.ast.2024.109608","DOIUrl":"10.1016/j.ast.2024.109608","url":null,"abstract":"<div><div>The formation control of a team comprised of multiple quadrotor Unmanned Aerial Vehicles (UAVs) may severely be affected by the unknown external disturbances. The external disturbances are caused by wind forces to create aero-dynamical disturbances. This article addresses the robust formation control problem of multiple UAVs system despite the effect of external disturbances that allow sustaining a stable network connection among the UAVs and maintaining different formations assigned to them. First, a Radial Basis Function Neural Network (RBFNN) based model is developed to reciprocate the external disturbances along the positional and the attitude subsystems. Then incorporating the estimated disturbance values a distributed adaptive formation controller is devised using the Lyapunov theory. It consists of a positional and an attitude controller associated with the translational and the rotational movements of the UAVs. The stability is validated by satisfying the criteria of the Lyapunov stability function. The UAVs are connected through variable adjacency matrix based directed network topology and the network connectivity is established through the properties of the Laplacian Matrix. The robustness of the designed controller is justified via rigorous simulation studies for different sets of desired formations such as triangular, squared, tetrahedron, octahedron and cube shaped. The reference trajectories are considered as spiral, straight line and circular shaped. The time varying external disturbances are considered of sinusoidal waveform of different magnitudes. The simulation results signifies that the proposed RBFNN based formation controller reciprocate different sinusoidal waveforms to achieve the desired formations successfully. Extensive comparative studies demonstrate the efficacy of the proposed adaptive formation controller over the existing controllers presented in the literature for different shapes of trajectories and desired formations.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geometric extended state observer on TSE(3) with fast finite-time stability: Theory and validation on a multi-rotor vehicle","authors":"","doi":"10.1016/j.ast.2024.109596","DOIUrl":"10.1016/j.ast.2024.109596","url":null,"abstract":"<div><div>This article presents an extended state observer for a vehicle modeled as a rigid body in three-dimensional translational and rotational motions. The extended state observer is applicable to a multi-rotor aerial vehicle with a fixed plane of rotors, modeled as an under-actuated system on the state-space <span><math><mi>T</mi><mrow><mi>SE</mi><mo>(</mo><mn>3</mn><mo>)</mo></mrow></math></span>, the tangent bundle of the six-dimensional Lie group <span><math><mi>SE</mi><mo>(</mo><mn>3</mn><mo>)</mo></math></span>. This state-space representation globally represents rigid body motions without singularities. The extended state observer is designed to estimate the resultant external disturbance force and disturbance torque acting on the vehicle. It guarantees stable convergence of disturbance estimation errors in finite time when the disturbances are constant, and finite time convergence to a bounded neighborhood of zero errors for time-varying disturbances. This extended state observer design is based on a Hölder-continuous fast finite time stable differentiator that is similar to the super-twisting algorithm, to obtain fast convergence. Numerical simulations are conducted to validate the proposed extended state observer. The proposed extended state observer is compared with other existing research to show its advantages. A set of experimental results implementing disturbance rejection control using feedback of disturbance estimates from this extended state observer is also presented.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A gradient-enhanced univariate dimension reduction method for uncertainty propagation","authors":"","doi":"10.1016/j.ast.2024.109602","DOIUrl":"10.1016/j.ast.2024.109602","url":null,"abstract":"<div><div>The univariate dimension reduction (UDR) method stands as a way to estimate the statistical moments of the output that is effective in a large class of uncertainty quantification (UQ) problems. UDR's fundamental strategy is to approximate the original function using univariate functions so that the UQ cost only scales linearly with the dimension of the problem. Nonetheless, UDR's effectiveness can diminish when uncertain inputs have high variance, particularly when assessing the output's second and higher-order statistical moments. This paper proposes a new method, gradient-enhanced univariate dimension reduction (GUDR), that enhances the accuracy of UDR by incorporating univariate gradient function terms into the UDR approximation function. Theoretical results indicate that the GUDR approximation is expected to be one order more accurate than UDR in approximating the original function, and it is expected to generate more accurate results in computing the output's second and higher-order statistical moments. Our proposed method uses a computational graph transformation strategy to efficiently evaluate the GUDR approximation function on tensor-grid quadrature inputs, and uses the tensor-grid input-output data to compute the statistical moments of the output. With an efficient automatic differentiation method to compute the gradients, our method preserves UDR's linear scaling of computation time with problem dimension. Numerical results show that the GUDR is more accurate than UDR in estimating the standard deviation of the output and has a performance comparable to the method of moments using a third-order Taylor series expansion.</div></div>","PeriodicalId":50955,"journal":{"name":"Aerospace Science and Technology","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}