Search Results (12)

This study evaluates the effectiveness of the Weather Research and Forecasting (WRF) model in simulating high-resolution atmospheric conditions for Almaty, Kazakhstan, a city prone to stagnant winter air. While the previously used Bougeault and Lacarrere scheme for parameterizing the planetary boundary layer was applied in high-resolution modeling, the number of vertical levels was increased, and a detailed local climate zones (LCZs) map was included. Ground-based observations from meteorological stations and monitoring stations, remote sensing data, and radiosonde measurements are used to verify the model. Comparison results with ground-based observations show that the WRF model with the LCZ map provides a better representation of the wind and thermal regimes of Almaty compared to the three-class land use map, including in high resolution. A good correspondence of wind direction is demonstrated by comparing the modeling results with pollutant transport plumes recorded by remote sensing data. In addition, a good correlation was found between land surface temperature from satellite data and air temperature simulated by WRF with a resolution of 333 m. A comparison of simulated data and aerological measurements confirmed that downscaling did not have a significant impact on boundary layer calculations. Analysis of turbulent processes showed that the adopted model effectively describes the attenuation and dissipation of turbulent kinetic energy and reflects the typical diurnal variations of meteorological processes in the atmosphere of Almaty in the anticyclonic winter period. The results of high-resolution WRF modeling can form the basis for the development of a hybrid system capable of modeling atmospheric processes at the building level. Full article

A novel combination of three control systems is presented in this paper: an adaptive control system, a type-two fuzzy logic system, and a super-twisting sliding mode control (STSMC) system. This combination was developed at the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity (LARCASE). This controller incorporates two methods to calculate the gains of the switching term in the STSMC utilizing the particle swarm optimization algorithm: (1) adaptive gains and (2) optimized gains. This methodology was applied to a nonlinear model of the Cessna Citation X business jet aircraft generated by the simulation platform developed at the LARCASE in Simulink/MATLAB (R2022b) for aircraft lateral motion. The platform was validated with flight data obtained from a Level-D research aircraft flight simulator manufactured by the CAE (Montreal, Canada). Level D denotes the highest qualification that the FAA issues for research flight simulators. The performances of controllers were evaluated using the turbulence generated by the Dryden model. The simulation results show that this controller can address both turbulence and existing uncertainties. Finally, the controller was validated for 925 flight conditions over the whole flight envelope for a single configuration using both adaptive and optimized gains in switching terms of the STSMC. Full article

Contrails created by aircraft are a very hot topic today because they contribute to the warming of the atmosphere. Air traffic density is very high, and current forecasts predict a further significant increase. Increased air traffic volume is associated with an increased occurrence of contrails and induced cirrus clouds. The scientific level of contrails and their impact on the Earth’s climate is surprisingly low. The scientific studies published so far are mainly based on global models, in situ measurements, and satellite observations of contrails. The research is based on observations of contrails in flight paths in the vicinity of Děčín and Prague, and the collection of flight and meteorological data. It focused on the influence of the meteorological situation on the formation of persistent contrails. The collected data on contrails and meteorological variables were statistically processed using machine learning methods for classification models. Several models were developed to predict and simulate the properties of contrails as a function of given air traffic and meteorological conditions. The Random Forests model produced the best results. Dependencies between meteorological conditions, formation, and contrail lifetime were found. The aim of the study was to identify the possibility of using available meteorological data to predict persistent contrails. Full article

A novel distributed-vector-propulsion UAV (DVPUAV) is introduced in this paper, which has the capability of Vertical takeoff and landing (VTOL), and can realize relatively high-speed cruise. As the core of the DVPUAV, the propulsion wing designed under the guidance of the integration idea is not only a lifting body but also a propulsion device and a control mechanism. However, this kind of aircraft has a series of difficult problems with complex aero-propulsion coupling, flight modes switching, and so many inputs and control coupling. In order to describe this coupling effect to improve the accuracy of dynamics, an aero-propulsion coupling model is developed, considering both computation reliability and real-time. Afterward, a unique control framework is designed for the DVPUAV. By optimizing control logic, this control framework realizes the decoupling of longitudinal and lateral directional control and even the decoupling of roll and yaw control. Next, based on the Iterative linear quadratic regulator (ILQR), a new Model Predictive Control (MPC) controller with the ability to solve complex nonlinear problems is proposed which achieves the unification of the controller for the full flight envelope. Finally, the good performance of the control framework and controller is verified in the whole process of the flight simulation from take-off to landing. Full article

The differential interferometric synthetic aperture radar (DInSAR) method is based on phase variation between the complex value of pixels of timely separated scenes in interferometric SAR pairs. This phase variation has five components: surface topography, curvature of planet’s surface, terrain displacement, volume scatterers, and atmospheric propagation effects. The terrain displacement is the main product of the DInSAR method, while the last two effects are unpredictable and bring inaccuracy into the terrain displacement measurements. In this work, the propagation conditions in the troposphere and ionosphere were studied during two DInSAR measurements examining the Zagreb 22 March 2020 earthquake, with terrain raising of up to +3 cm at the epicenter. For the troposphere, the vertical profile of the modified refraction index, which incorporates local curvature change with height, was reconstructed using aerological balloon probing data. Ionospheric conditions were determined based on total electron content (TEC) calculated from the Croatian positioning system (CROPOS) and global navigation satellite system (GNSS) reference stations’ measurements. One of the DInSAR measurements was conducted in unfavorable tropospheric refractive conditions, which resulted in an overall bias of −2 cm. The variability of propagation conditions indicates the need for examining the atmospheric propagation effects when calculating terrain displacements using the DInSAR method. The results of DInSAR indicate slight displacements, comparable with the amplitude of atmospheric variations, and should therefore be approached with caution. Full article

Interpreting the results of a high-level clouds (HLCs) lidar study requires a comparison with the vertical profiles of meteorological quantities. There are no regular radiosonde measurements of vertical profiles of meteorological quantities in Tomsk. The nearest aerological stations are several hundred kilometers away from the lidar and perform radiosonde measurements only a few times a day, whereas lidar experiments are performed continuously throughout the day. To estimate meteorological conditions at the HLC altitudes, we propose to use the ERA5 reanalysis. Its reliability was tested by comparing with the data from five aerological stations within a radius of 500 km around Tomsk. A labeled database of the lidar, radiosonde, and ERA5 data (2016–2020) for isobaric levels 1000–50 hPa was created. The temperature reconstruction error over the entire altitude range was characterized by an RMSE of 0.8–2.8 °C, bias of 0–0.9, and Corr ~1. The accuracy of the relative vertical profiles (RMSE 25–40%, Bias 10–22%, and Corr <0.7) and specific humidity (RMSE 0.2–1.2 g/kg, Bias ~0 g/kg, and Corr ~0) at the HLC altitudes were unsatisfying. The ERA5 data on wind direction and speed for the HLC altitudes were promising. Full article

The safety and reliability of the measuring elements of an aero-engine are important preconditions of the stable operation of the engine control system. The number of control parameters of a variable cycle engine increases by 20%–40% compared to traditional engines. Therefore, it is important to conduct study on the analytical redundancy, design fault diagnosis and isolation of the sensors, as well as the signal reconstruction system, so as to increase the ratability and fault-tolerant capability of the variable cycle engine control system. The analytical redundancy method relies on the accuracy of the mathematical model of the engine. During the service cycle of the engine, it is inevitable that the engine performance will deteriorate, resulting in a mismatch with the model. In this paper, the adaptive model of the variable cycle engine is built with a Kalman filter. Based on this, the strategy of analytical redundancy logic is built and the dynamic adaptive calculation of the threshold is introduced. Simulation results reflect that this method can effectively increase the reliability of sensor fault diagnosis and the accuracy of the analytical redundancy when there is performance degradation of the variable cycle engine. Full article

With the application of more electric aircraft (MEA) technology, variable frequencies and high power ratings become import features of aero-generators. The brushless synchronous generator, which has a three-stage structure, is the most commonly used type of aero-generator. Due to the variation of operating conditions, the implementation of generator controllers becomes more and more difficult. In this paper, a state space model of a generator is derived and the influence of different operating conditions on the frequency response characteristics of the generator is revealed. Based on a fuzzy PI controller, an additional fuzzy logic controller is applied to modify the PI parameters of the voltage loop by introducing the generator speed to cope with the speed variation. Finally, the results of the simulations and experiments demonstrate that the dual fuzzy PI controller can improve both the steady-state and dynamic performance of the brushless synchronous generator, verifying the previous theoretical study. Full article

The aircraft anti-skid braking system (AABS) is an essential aero electromechanical system to ensure safe take-off, landing, and taxiing of aircraft. In addition to the strong nonlinearity, strong coupling, and time-varying parameters in aircraft dynamics, the faults of actuators, sensors, and other components can also seriously affect the safety and reliability of AABS. In this paper, a reconfiguration controller-based adaptive fuzzy active-disturbance rejection control (AFADRC) is proposed for AABS to meet increased performance demands in fault-perturbed conditions as well as those concerning reliability and safety requirements. The developed controller takes component faults, external disturbance, and measurement noise as the total perturbations, which are estimated by an adaptive extended state observer (AESO). The nonlinear state error feedback (NLSEF) combined with fuzzy logic can compensate for the adverse effects and ensure that the faulty AABS maintains acceptable performance. Numerical simulations are carried out in different runway environments. The results validate the robustness and reconfiguration control capability of the proposed method, which improves AABS safety as well as braking efficiency. Full article

Multivariable time series prediction has been widely studied in power energy, aerology, meteorology, finance, transportation, etc. Traditional modeling methods have complex patterns and are inefficient to capture long-term multivariate dependencies of data for desired forecasting accuracy. To address such concerns, various deep learning models based on Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) methods are proposed. To improve the prediction accuracy and minimize the multivariate time series data dependence for aperiodic data, in this article, Beijing PM2.5 and ISO-NE Dataset are analyzed by a novel Multivariate Temporal Convolution Network (M-TCN) model. In this model, multi-variable time series prediction is constructed as a sequence-to-sequence scenario for non-periodic datasets. The multichannel residual blocks in parallel with asymmetric structure based on deep convolution neural network is proposed. The results are compared with rich competitive algorithms of long short term memory (LSTM), convolutional LSTM (ConvLSTM), Temporal Convolution Network (TCN) and Multivariate Attention LSTM-FCN (MALSTM-FCN), which indicate significant improvement of prediction accuracy, robust and generalization of our model. Full article

The increasing demand for miniaturized radio-controlled vehicles inspired the following research. The uses of these unmanned miniaturized/micro vehicles range from aero-modeling to drones for urban control and military applications too. The common characteristic of these vehicles is the need for a light and compact propulsion system. The radio-controlled (RC) turbines for modeling are ideally suited for this purpose, guaranteeing the necessary thrust with compactness and lightness. This device is a miniaturized turbojet, and it is generally composed of three basic elements: compressor, combustion chamber and turbine. The main goal of the paper is to evaluate the turbojet performance for considering the possibility of its use as a range extender in a hybrid vehicle. Considering the total volume constraints, it will be important to evaluate the specific fuel consumption. Also from the environmental point of view, the possibility of feeding the device with gas has been considered and, consequently, the needed device modifications performed. The test bench has been realized and assembled at the University Department Laboratory. Several different experimental configurations are reproduced and reported here, to obtain performance maps. The experiments results have been compared to previous tests results, as well as numerical simulations. Therefore, it has been possible to make a comparison between the two different fuels. The results show that this device can be used as a range extender for a hybrid vehicle. Moreover, the various tests have shown that, acting on the control unit, it is possible to feed the device with gas (mixture of propane and butane), obtaining a further benefit from the economic point of view. Surely, an in-depth study of the turbine management logic would produce a further advantage in terms of fuel consumption. Full article

This paper presents a case study of the DHL Express and Lufthansa Cargo strategic joint venture cargo airline ‘AeroLogic’, the global air cargo industry’s largest operative joint venture between an airline and a leading international express and logistics provider. The study used a qualitative research approach. The data gathered for the study was examined by document analysis. The strategic analysis of the AeroLogic joint venture was based on the use of Porter’s Five Forces framework. The study found that the AeroLogic joint venture airline has provided synergistic benefits to both partners and has allowed the partners to access new markets and to participate in the evolution of the air cargo industry. The new venture has also enabled both joint venture partners to enhance their competitive position in the global air cargo industry through strengthened service offerings and has provided the partners with increased cargo capacities, a larger route network, and greater frequencies within their own route networks. The study also found that the AeroLogic business model is unique in the air cargo industry. A limitation of the study was that AeroLogic’s annual revenue or freight traffic data was not available. It was, therefore, not possible to analyse the business performance of the joint venture. Full article