Aerodynamic Database Research Articles

Machine learning-enabled estimation of crosswind load effect on tall buildings

This paper presents an approach to predict crosswind force spectra and associated response of tall buildings with rectangular cross-section based on machine learning (ML) technique and random vibration-based response analysis. An efficient ML algorithm, light gradient boosting machine (LGBM), was trained to predict crosswind force spectra of the tall buildings by using the database from the Wind Engineering Research Center at the Tamkang University embedded in the aerodynamic database of NatHaz Modelling Laboratory. Furthermore, an unsupervised ML algorithm, K-means clustering, was employed to advance the understanding of the crosswind force spectrum characteristics of the tall buildings. The effects of three factors, i.e., ground roughness, aspect ratio and side ratio, on the force spectra were discussed based on clustering. To predict the crosswind response of tall buildings, case studies were carried out to validate the predictive accuracy of the LGBM model combined with random vibration-based response analysis. The results demonstrate that the proposed method combined with the multiple database-enabled design module for high-rise buildings developed by the NatHaz Modelling Laboratory at the University of Notre Dame is effective and computationally efficient to provide fast and accurate predictions of the crosswind force spectrum and associated crosswind responses of rectangular tall buildings.

Numerical aerodynamic database in elite male runners

This study is motivated by a real lack of quantitative data concerning the aerodynamic forces exerted on world-class runners during running events. The objective of this study is to create a database representative of the morphological diversity of runners but also of the speed which is closely related to the running event. A numerical method was used to estimate the aerodynamic forces exerted on runners of size between 1.6 and 2 m and for speeds ranging from 10 to 40 km/h. The results presented in this study suggest that the aerodynamic force is inherent to two main parameters: the size of the runner which affects the body frontal area and the speed which depends on the running discipline (100 m, middle- or long-distance running…). One of the main results of this study is that, regardless of running speed, the drag force increases by about 56% for a runner's height between 1.6 m and 2 m (frontal area between 0.383 m2 and 0.596 m2). These data could be very useful to determine the value of the horizontal drag forces applied to the runner's waist during physiological measurements performed on a treadmill.

Computational simulation of ice accretion and shedding trajectory of a rotorcraft in forward flight with strong rotor wakes

To ensure safe flight in icing conditions it is essential to understand ice accretion, its effect on aerodynamic performance and ice shedding in any aircraft certification program. Ice fragments shed from a rotorcraft windshield and other locations can be detrimental if they are ingested into the engine intake or impinge on the tail rotor. Because of the lack of experimental data about the forces and moments acting on ice in such a complex flow field, the computational simulation of ice shedding trajectories becomes essential. This study presents a methodology to predict the location of ice accretion and break-off, ice shape and shedding trajectory in a rotorcraft flow field with strong rotor wakes during forward flight. The methodology includes the creation of an aerodynamic database for different ice shapes (rectangle, disc, ellipse, and glaze ice shape) at various combinations of Euler angles; the analysis of rotorcraft flow field by computational fluid dynamics for different advance ratios; and a six degree-of-freedom trajectory analysis using artificial neural networks and the Monte Carlo method. The actuator surface method was applied to account for the rotor wake effect, which is capable of modeling the tip vortices and inboard sheets emanating from the rotor blades. The main results are a probability map of the ice shedding trajectory footprints on the engine intake and tail rotor planes. Disc-shaped ice fragments with a sharp edge turned out to be most dangerous. The rotation of the main rotors also substantially affected ice accretion and shed trajectory, indicating the importance of integrated simulations of all components when designing ice protection systems for rotorcraft.

Aerodynamic identification method of maneuverable vehicles based on the Bayes estimation theorem

When a re-entry vehicle executes a large-amplitude maneuver, the aerodynamic identification method of small-amplitude maneuvers under the trim condition is inapplicable. To solve the large-amplitude problem, a priori aerodynamic model of the target interval is built using the original aerodynamic database, and its estimated parameters provide a priori information. To accurately estimate the parameters, the aerodynamic identification method applies the Bayes estimation theorem on data from the aerodynamic database and multiple flight tests. The optimal parameters can be obtained by combining the prior information with flight test information. The aerodynamic model is then updated. To avoid the effect of measurement noise, the noisy data are smoothed using the Fourier smoothing method. When the aerodynamic characteristics are determined from flight tests of the re-entry vehicle by using the above method, the results indicate that the aerodynamic coefficient well describes the aerodynamic characteristic of large-amplitude maneuvers, demonstrating the high aerodynamic-prediction capacity of this model.

Development of a Modularized Virtual Flight Simulator based on Multiple Discipline Coupled Method

The problem of aircraft control involves multiple subjects and has always been extremely complicated in mechanics modelling. Virtual flight simulation was put forward in order to reduce the cost of full-scale airplane flying test and wind tunnel experiment. A typical virtual flight simulator includes a computational fluid dynamics (CFD) solver, a structure dynamics (FD) function, and a flight controller. However, existed virtual flight solver usually ignores the universal modelling of dynamics for complex aircraft configuration and the modularization of CFD, FD and flight controller module, which makes it very inconvenient for many in-house virtual flight codes for engineering application and commercial software development. A new framework of virtual flight simulation platform is established with a parallel Reynolds Averaged Navier-Stokes (RANS) solver, a structured moving overlapping grid function, a generic multiple body dynamics (MBD) solver, and a plug-in type flight controller platform. A universal data exchange interface between MBD and flight controller is presented. An X-wing missile flying forward and pitching-up maneuvering validation case is conducted with the current virtual flight simulator, the result is compared with Matlab Simulink solver based on steady aerodynamic database and good agreement is obtained.

New approach of inverse design of transonic compressor rotor blade via prescribed isentropic Mach distributions without modification of governing equations

Shock loss is the primary source of total pressure loss of transonic axial compressors. Reducing the shock by redesigning the geometry of rotor is of great interest for turbomachinery designers. However, the complex flow field involving shock waves, shock-boundary interaction, intense secondary flows, etc., in the compressor makes the design of rotor difficult. The conventional method of design and optimization is computationally intensive and time-costly. This study introduces an inverse design method to design rotor blades corresponding to prescribed isentropic Mach number distributions with no modification of flow-governing equations. An artificial neural network is trained to predict the isentropic Mach number distributions of any deformed blades. Then, with the pattern search optimization, the blade corresponding to the prescribed isentropic Mach number distributions can be achieved. When the aerodynamic parameter database is calculated and the neural network is obtained, this method can design large numbers of blades of changed isentropic Mach number distributions immediately, without modifying the computational fluid dynamics (CFD) flow solver. The design process is fully automatic and efficient. In this study, NASA Rotor 37 is redesigned and optimized as test cases. Some analysis on the influence of blade shape on aerodynamic characteristics of the rotor is represented in this study.

Aerodynamic Characterization of Hypersonic Transportation Systems and Its Impact on Mission Analysis

This paper aims to provide technical insights on the aerodynamic characterization activities performed in the field of the H2020 STRATOFLY project, for the Mach 8 waverider reference configuration. Considering the complexity of the configuration to be analyzed at conceptual/preliminary design stage, a build-up approach has been adopted. The complexity of the aerodynamic model increases incrementally, from the clean external configuration up to the complete configuration, including propulsion systems elements and flight control surfaces. At each step, the aerodynamic analysis is complemented with detailed mission analysis, in which the different versions of the aerodynamic databases are used as input for the trajectory simulation. eventually, once the contribution to the aerodynamic characterization of flight control surfaces is evaluated, stability and trim analysis is carried out. The comparison of the results obtained through the different mission analysis campaigns clearly shows that the accuracy of aerodynamic characterization may determine the feasibility or unfeasibility of a mission concept.

Performance Prediction Program for Wind-Assisted Cargo Ships

Wind-Assisted Propulsion Systems (WAPS) can play a key role in achieving the IMO 2050 targets on reducing the total annual GHG emissions from international shipping by at least 50%. The present project deals with the development of a six degree of freedom (DoF) Performance Prediction Program (PPP) for wind-assisted cargo ships aimed at contributing knowledge on WAPS performance. It is a fast and easy tool, able to predict the performance of any commercial ship with three possible different WAPS installed: rotor sails, rigid wing sails and DynaRigs; with only the ship main particulars and general dimensions as input data. The tool is based on semi-empirical methods and a WAPS aerodynamic database created from published data on lift and drag coefficients, which can be interpolated with the aim to scale to different sizes and configurations. A model validation is carried out to evaluate its reliability. The results are compared with the real sailing data of a Long Range 2 (LR2) class wind-assisted tanker vessel, the Maersk Pelican. The study indicates that the PPP shows good agreement with the technology suppliers’ own modelling tool and reasonable agreement with the trends of the real sailing measurements. However, for downwind sailing conditions, the predictions are more conservative than the measured values. Lastly, results showing and comparing power savings for the three different WAPS are presented. Rotor Sails are found to be the most efficient WAPS studied with a much higher potential of driving force generation per square meter of projected sail area.

Computational method in database-assisted design for wind engineering with varying performance objectives

The concept of Performance objective assessment is extended to wind engineering. This approach applies using the Database-Assisted Design technique, relying on the aerodynamic database provided by the National Institute of Standards and Technology (NIST). A structural model of a low-rise building is analyzed to obtain influence coefficients for internal forces and displacements. Combining these coefficients with time histories of pressure coefficients on the envelope produces time histories of load effects on the structure, for example knee and ridge bending moments, and eave lateral drift. The peak values of such effects are represented by an extreme-value Type I Distribution, which allows the estimation of the gust wind speed leading to the mean hourly extreme loading that cause specific performance objective compromises. Firstly a fully correlated wind field over large tributary areas is assumed and then relaxed to utilize the denser pressure tap data available but with considerably more computational effort. The performance objectives are determined in accordance with the limit state load combinations given in the ASCE 7-16 provisions, particularly the Load and Resistance Factor Design (LRFD) method. The procedure is then repeated for several wind directions and different dominant opening scenarios to determine the cases that produce performance objective criteria. Comparisons with two approaches in ASCE 7 are made.

Enhancement of light aircraft 6 DOF simulation using flight test data in longitudinal motion

Abstract This paper proposes a procedure to improve the accuracy of the light aircraft 6 DOF simulation model by implementing model tuning and aerodynamic database correction using flight test data. In this study, the full-scale flight testing of a 2-seater aircraft has been performed in specific longitudinal manoeuver for model enhancement and simulation validation purposes. The baseline simulation model database is constructed using multi-fidelity analysis methods such as wind tunnel (W/T) test, computational fluid dynamic (CFD) and empirical calculation. The enhancement process starts with identifying longitudinal equations of motion for sensitivity analysis, where the effect of crucial parameters is analysed and then adjusted using the model tuning technique. Next, the classical Maximum Likelihood (ML) estimation method is applied to calculate aerodynamic derivatives from flight test data, these parameters are utilised to correct the initial aerodynamic table. A simulation validation process is introduced to evaluate the accuracy of the enhanced 6 DOF simulation model. The presented results demonstrate that the applied enhancement procedure has improved the simulation accuracy in longitudinal motion. The discrepancy between the simulation and flight test response showed significant improvement, which satisfies the regulation tolerance.

A fault detection method for FADS system based on interval-valued neutrosophic sets, belief rule base, and D-S evidence reasoning

Fault detection, with the characteristics of strong uncertainty and randomness, has always been one of the research hotspots in the field of aerospace. Considering that devices will inevitably encounter various unknown interference in the process of use, which greatly limits the performance of many traditional fault detection methods. Therefore, the main aim of this paper is to address this problem from the perspective of uncertainty and randomness of measurement signal. In information engineering, interval-valued neutrosophic sets (IVNSs), belief rule base (BRB), and Dempster-Shafer (D-S) evidence reasoning are always characterized by the strong ability in revealing uncertainty, but each has its drawbacks. As a result, the three theories are firstly combined in this paper to form a powerful fault detection algorithm. Besides, a series of innovations are proposed to improve the method, including a new score function based on p-norm for IVNSs and a new approach of calculating the similarity between IVNSs, which are both proved by authoritative prerequisites. To illustrate the effectiveness of the proposed method, flush air data sensing (FADS), a technologically advanced airborne sensor, is adopted in this paper. The aerodynamic model of FADS is analyzed in detail using knowledge of aerodynamics under subsonic and supersonic conditions, meanwhile, the high-precision model is established based on the aerodynamic database obtained from CFD software. For further confirming the validity and feasibility, a comparison with the methods based on parity equation, χ2 distribution, and information fusion method ordered weighted averaging (OWA) with three sets of weight vectors are conducted.

State consistence of data-driven reduced order models for parametric aeroelastic analysis

This paper investigates the state consistence of parametric data-driven reduced order models (ROMs) in a state-space form obtained by various system identification methods, including autoregressive exogenous (ARX) and subspace identification (N4SID), for aeroelastic analysis in varying flight conditions. The target flight envelop is first partitioned into discrete grid points, on each of which an aerodynamic ROM is constructed using system identification to capture the dependence of the generalized aerodynamic force on the generalized displacement of structural modes. High-fidelity aeroelastic modal perturbation simulations are used to generate the ROM training and verification data. Aerodynamic ROMs not on the grid point are obtained by interpolating those at neighboring grid points. Through a thorough analysis of the model coefficients and pole migration, it is found that only the ARX-based aerodynamic ROM preserves the state consistence, and hence, allowing direct interpolation of system matrices at the non-grid point and rapid aerodynamic ROM database development in the entire flight parameter space. In contrast, N4SID-based ROM destroys the state consistence and yields physically meaningless results when ROMs are interpolated. The origin of the difference in the state consistence caused by both methods is also discussed. The interpolated ARX aerodynamic ROMs coupled with the structural ROM for parametric aeroelastic analysis exhibit excellent agreement with the high fidelity full order model (mostly <5% relative error) and salient computational efficiency.

Development and validation of a mobile bluff-body to understand extreme wind loading

The collection of valuable wind loading data from winds generated by convective events presents a significant challenge to the wind engineering field. The spatial and temporal characteristics of these events make data acquisition challenging. A mobile bluff-body capable of recording wind-induced pressure data during extreme wind events was developed to solve this issue. The bluff-body is called mSWERF3 for mobile Smart Wind Engineering Research Facility. This paper introduces mSWERF3, discussing its design, the scaling techniques, and validation using full-scale data from the Silsoe cube and the Wind Engineering Research Field Laboratory (WERFL) building, and wind tunnel data from the Tokyo Polytechnic University (TPU) Aerodynamic Database. The validation includes a comparison of mean, standard deviation, minimum, and maximum pressure coefficients using the Silsoe and the TPU data, and a comparison of power spectra density of surface pressures on similar flow regimes using the WERFL and the TPU data. The results of these comparisons show that the aerodynamics of mSWERF3 is similar to those in larger full-scale buildings and wind tunnel models. Therefore, it is shown that mSWERF3 can provide valuable data to improve our understanding of extreme wind loading.

Mars InSight Entry, Descent, and Landing Trajectory and Atmosphere Reconstruction

The InSight mission landed on the surface of Mars on 26 November 2018. The InSight system performance met all design requirements, although several performance metrics fell near the boundaries of the predictions. The peak deceleration was high, the overall timeline was short, and the landing site was uprange and crossrange from the target. This paper describes the reconstruction of the entry, descent, and landing trajectory and atmosphere. The approach uses a Kalman filter to blend sensor data to obtain the vehicle trajectory. The aerodynamic database is used in combination with the sensed accelerations to obtain estimates of the atmosphere-relative state, which in turn is used to derive the freestream atmospheric conditions during entry. The results indicate that the reconstructed atmospheric density was approximately smaller than the preflight atmosphere model. Analysis of the reconstructed vehicle attitude angles indicates that the aerodynamic lift was oriented downward at entry. The vehicle developed a roll rate during entry, which directed a component of the lift to the north. The low density and aerodynamic lift direction are determined to be the primary causes of the high deceleration, short timeline, and location of the landing site relative to the target.

Modeling, Simulation, and Cruise Characteristics of Wingtip-Jointed Composite Aircraft

In this paper, multibody dynamic modeling and a simulation method for the wingtip-jointing process of a new-concept composite aircraft system are investigated. When the wingtips of two aircraft are jointed, the resultant wingtip-jointed aircraft is regarded as variable-geometry multiple rigid bodies, and a seven-degree-of-freedom non-linear dynamic model is established by mathematical derivation. The slip-meshing method is adopted to analyze the unsteady aerodynamic influence. We also present specific aerodynamic database acquisition methods under the quasi-steady assumption. Based on this, the simulation results indicate that the longitudinal and lateral movements are highly jointed and complex. A new composite aircraft system is investigated, in order to meet the balance requirement. With the lift–drag ratio (K) considered, the piecewise cubic Hermite interpolation (PCHIP) method, with a sufficient sample size, was utilized to help the cruise strategy optimization analysis under fixed altitude and speed conditions. Meanwhile, distribution of cruise characteristics with different sampling values of composite flight characteristic parameters were also analyzed. The research results can be used as a reference for new-concept composite aircraft model establishment, simulation, and multibody dynamic characteristic investigation.

Neural Network-Based System Identification for Quadcopter Dynamic Modeling: A Review

A quadcopter is a rotorcraft with a simple mechanical construction. It has the same hovering capability similar to the traditional helicopter, but it is easier to maintain. The quadcopter is hard to control due to its unstable system with highly coupled and non-linear dynamics. In order to design a robust control algorithm, it is crucial to obtain a precise quadrotor flight dynamics through system identification approach. System identification is a method of finding the mathematical model of the dynamics system using the input-output data measurement. Neural network (NN) based system identification is excellent alternative modeling because it reduces development costs and time by avoiding governing equations and large aerodynamic database. NN based system identification has successfully identified the quadcopter dynamics with good accuracy. This paper gives an overview of the characteristic of the quadcopter and presents a comprehensive survey of the modeling techniques used to determine the flight dynamics of a quadrotor with a particular focus on NN based system identification method. The presented research works have been classified into different categories such as the first principle modeling, system identification and implementation of NN based system identification in quadcopter platform. Finally, the paper highlights challenges that need to be addressed in developing efficient NN based system identification model for unmanned quadcopter system.

Using additive manufactured parametric models for wind tunnel test-based aerodynamic shape optimization

PurposeThe purpose of this paper is to propose a new approach of using additively manufactured parametric models in the wind tunnel test-based aerodynamic shape optimization (ASO) framework and to present its applicability test results obtained from a realistic aircraft design problem.Design/methodology/approachFor aircraft shape optimization, the following three methodologies were used. First, as a validation study, the possibility of using rapid prototyping (RP) model in the wind tunnel test was verified. Second, through the wind tunnel test-based ASO, the application and feasibility of the real fighter aircraft shape optimization were verified. A generic fighter configuration is parameterized to generate various test models using additive manufacturing. Wind tunnel tests are conducted to measure their stability criteria in high angle of attack (AOA). Finally, a computational fluid dynamics (CFD) study was performed and analysis procedures, costs and results compared to the wind tunnel test were compared and reviewed.FindingsRP technology can significantly reduce the time and cost of generating parametric wind tunnel models and can open up new possibilities for wind tunnel tests to be used in the rigorous aerodynamic design loop. There was a slight difference between the results of the RP model and the metallic model because of rigidity and surface roughness. However, the tendency of the aerodynamic characteristics was very similarly predictable. Although there are limitations to obtaining precise aerodynamic data, it is a suitable method to be applied to comparative studies on various shapes with large geo-metric changes in the early phase of design. The CFD analysis indicates that the wind tunnel-based ASO using the RP model shows the efficiency corresponding to the CFD shape optimization.Research limitations/implicationsThe RP parametric models may have various assembly error sources and rigidity problems. The proposed methodology may not be suitable for collecting the accurate aerodynamic database of a final design; rather, the methodology is more suitable to screen out many configurations having fairly large shape variation in the early stage of the design process.Practical implicationsThe wind tunnel test-based ASO can replace or supplement CFD-based ASO. In areas where CFD accuracy is low, such as high AOA flight characteristics, RP model wind tunnel-based ASO can be a research method that can secure both efficiency and accuracy advantages, providing ten times more effective in terms of cost and time. The wind tunnel test is used to obtain aerodynamic data at the final stage of shape design. It can be extended to a comparative study of several shapes in the early design phase. This procedure can be applied for both industrial level and educational aircraft design activities.Originality/valueThis study is the application to be applied as a parametric study on the whole aircraft, rather than using the RP model applying a simple partial control surface or configuration change of a part of the wing. The possibility of using the RP model was confirmed by comparing and verifying each other in a medium-sized wind tunnel using a relatively large RP model and a metallic model. It was verified that it can be applied in the shape design process, not the shape verification in the traditional design procedure, and a comparison with the CFD method was also performed. With further development and validation efforts, the new design framework may become an industrial standard for future aircraft development.

Data Mining and Machine Learning Techniques for Aerodynamic Databases: Introduction, Methodology and Potential Benefits

Machine learning and data mining techniques are nowadays being used in many business sectors to exploit the data in order to detect trends, discover certain features and patters, or even predict the future. However, in the field of aerodynamics, the application of these techniques is still in the initial stages. This paper focuses on exploring the benefits that machine learning and data mining techniques can offer to aerodynamicists in order to extract knowledge from the CFD data and to make quick predictions of aerodynamic coefficients. For this purpose, three aerodynamic databases (NACA0012 airfoil, RAE2822 airfoil and 3D DPW wing) have been used and results show that machine-learning and data-mining techniques have a huge potential also in this field.

Development and Analysis of Variable Pitch Propeller with Aerodynamic Stable Blades

For small short/vertical takeoff and landing (S/VTOL) unmanned aerial vehicles, the propeller design should reach a compromise between S/VTOL and cruise. But the complexity cost of a variable-pitch propeller is too high to be applied to small propellers. To achieve the propeller pitch variability with minimum mechanic complexity and weight cost, an aerostable concept was used in the design of the blades. In this case, the propeller pitch was variable under the aerodynamic moment. First, the simulation method based on the computational fluid dynamics was validated by experiments of the NACA 5868-9 propeller and Gall’s biplane/winglet configuration. Second, the propeller design process for a four-blade aerostable propeller with high disk loading was presented. The design was based on the Blade Element Momentum Theory, with a section aerodynamic database modeled by an artificial neural network. To eliminate dynamic imbalance moment, a prebalance method based on the Parallel-Axis Theorem was established. Third, the thrust, power, and efficiency of the designed propeller was analyzed in both S/VTOL and cruise condition. The trim points of the blade were analyzed, and the pitch moment coefficient and the stability margin of the blade were discussed.

Neural Network-Based System Identification for Quadcopter Dynamic Modeling: A Review

A quadcopter is a rotorcraft with a simple mechanical construction. It has the same hovering capability similar to the traditional helicopter, but it is easier to maintain. The quadcopter is hard to control due to its unstable system with highly coupled and non-linear dynamics. In order to design a robust control algorithm, it is crucial to obtain a precise quadrotor flight dynamics through system identification approach. System identification is a method of finding the mathematical model of the dynamics system using the input-output data measurement. Neural network (NN) based system identification is excellent alternative modeling because it reduces development costs and time by avoiding governing equations and large aerodynamic database. NN based system identification has successfully identified the quadcopter dynamics with good accuracy. This paper gives an overview of the characteristic of the quadcopter and presents a comprehensive survey of the modeling techniques used to determine the flight dynamics of a quadrotor with a particular focus on NN based system identification method. The presented research works have been classified into different categories such as the first principle modeling, system identification and implementation of NN based system identification in quadcopter platform. Finally, the paper highlights challenges that need to be addressed in developing efficient NN based system identification model for unmanned quadcopter system.