Journal articles on the topic 'Flight phase prediction'
To see the other types of publications on this topic, follow the link: Flight phase prediction.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Flight phase prediction.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Wang, Ziming, Chaohao Liao, Xu Hang, Lishuai Li, Daniel Delahaye, and Mark Hansen. "Distribution Prediction of Strategic Flight Delays via Machine Learning Methods." Sustainability 14, no. 22 (November 16, 2022): 15180. http://dx.doi.org/10.3390/su142215180.
Full textAbstract:
Predicting flight delays has been a major research topic in the past few decades. Various machine learning algorithms have been used to predict flight delays in short-range horizons (e.g., a few hours or days prior to operation). Airlines have to develop flight schedules several months in advance; thus, predicting flight delays at the strategic stage is critical for airport slot allocation and airlines’ operation. However, less work has been dedicated to predicting flight delays at the strategic phase. This paper proposes machine learning methods to predict the distributions of delays. Three metrics are developed to evaluate the performance of the algorithms. Empirical data from Guangzhou Baiyun International Airport are used to validate the methods. Computational results show that the prediction accuracy of departure delay at the 0.65 confidence level and the arrival delay at the 0.50 confidence level can reach 0.80 without the input of ATFM delay. Our work provides an alternative tool for airports and airlines managers for estimating flight delays at the strategic phase.
2
Intano, Gabriel P., and William R. Howse. "Predicting Performance in Army Aviation Flight Training." Proceedings of the Human Factors Society Annual Meeting 36, no. 12 (October 1992): 907–10. http://dx.doi.org/10.1518/107118192786750304.
Full textAbstract:
The Army Research Institute Aviation Research and Development Activity successfully implemented the Multi-Track Test Battery (MTTB) and associated classification functions in 1988. The battery and functions have been used to assign flight students to their combat skills aircraft. The present program determined the applicability of the battery to prediction of student performance in flight training. Performance evaluation in training consists of flight phase grades and academic phase grades. In addition to these grades, Overall Average Grade and Overall Flight Grade were also predicted using Forward Stepwise Multiple Regression procedures. Stepwise Multiple Discriminant Analysis was used to investigate two additional measures, flight deficiency training setback and flight deficiency attrition.
3
Bramble, William J., and Jefferson M. Koonce. "The Path to Airline Employment: Flight Experience and Performance in a Full-Mission Flight Simulation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 11 (October 1998): 797–800. http://dx.doi.org/10.1177/154193129804201106.
Full textAbstract:
Commercial pilots were studied in order to determine whether systematic relationships existed between composition of flight experience and performance deficiencies during a performance evaluation in a flight simulator. Flight experience variables included: (a) multi-engine (ME) time, (b) Part 121/135 time, (c) instrument time, and (d) percentage of flight hours acquired as an instructor. A composite performance measure was generated by summing evaluator ratings across all eight phases of flight and all four task categories. Separate measures were generated from the evaluation rating form for each phase of flight and each task category as well. Errors were most common during the approach, arrival, and holding phases of flight. Errors involving control and navigation were more frequent than errors involving communication or configuration. Correlational methods were used to analyze relationships between experience and overall performance. Only ME and Part 121/135 time contributed significantly to prediction of performance in the simulator ( R = 0.42, p < 0.001). ME and Part 121/135 flight experience were associated with better performance during the arrival and approach phases of flight and with better aircraft control. ME experience was uniquely associated with better performance during the holding phase of flight and with configuration and navigation performance. Part 121/135 experience were uniquely associated with better performance during the takeoff and enroute phases of flight and with superior communication. Implications for pilot selection are discussed.
4
Xiang, Zheng, Wenqi Zhang, Deyang He, and Yu Tang. "A Centralized Algorithm with Collision Avoidance for Trajectory Planning in Preflight Stage." International Journal of Aerospace Engineering 2021 (January 6, 2021): 1–10. http://dx.doi.org/10.1155/2021/6657464.
Full textAbstract:
In order to better understand pretactical phase flow management with the flight plan centralized processing at its core, based on the flight plan centralized processing system and track-based operation, the aircraft’s 4D trajectory planning challenges require a deeper level of analysis. Firstly, through establishing a flight performance prediction model, in which the flight plan data is extracted and the time when an aircraft passed a specified waypoint is calculated, a 4D flight prediction can be derived. Secondly, the air traffic flow of the waypoint is calculated, and a converging point along a flight route is selected. Through adjusting the time and speed of the aircraft passing this point, conflict between aircraft is avoided. Finally, the flight is verified by CCA1532, with the connecting flight plan centralized processing center set in line with the company’s requirements. The results demonstrate that according to flight plans, the 4D trajectory of the aircraft can be predicted with the nearest minute and second, and the flow of a total of 20 aircraft within one hour before and after the passage of CCA1532 at key point WADUK can be calculated. When there is a conflict of 88 s between the convergence point and flight B, the speed of B aircraft is adjusted from 789 km/h to 778 km/h, and the time of passing the WADUK point is increased by 7 s, thereby realizing the conflict-free trajectory planning of the two flights.
5
Xiang, Zheng, Wenqi Zhang, Deyang He, and Yu Tang. "A Centralized Algorithm with Collision Avoidance for Trajectory Planning in Preflight Stage." International Journal of Aerospace Engineering 2021 (January 6, 2021): 1–10. http://dx.doi.org/10.1155/2021/6657464.
Full textAbstract:
In order to better understand pretactical phase flow management with the flight plan centralized processing at its core, based on the flight plan centralized processing system and track-based operation, the aircraft’s 4D trajectory planning challenges require a deeper level of analysis. Firstly, through establishing a flight performance prediction model, in which the flight plan data is extracted and the time when an aircraft passed a specified waypoint is calculated, a 4D flight prediction can be derived. Secondly, the air traffic flow of the waypoint is calculated, and a converging point along a flight route is selected. Through adjusting the time and speed of the aircraft passing this point, conflict between aircraft is avoided. Finally, the flight is verified by CCA1532, with the connecting flight plan centralized processing center set in line with the company’s requirements. The results demonstrate that according to flight plans, the 4D trajectory of the aircraft can be predicted with the nearest minute and second, and the flow of a total of 20 aircraft within one hour before and after the passage of CCA1532 at key point WADUK can be calculated. When there is a conflict of 88 s between the convergence point and flight B, the speed of B aircraft is adjusted from 789 km/h to 778 km/h, and the time of passing the WADUK point is increased by 7 s, thereby realizing the conflict-free trajectory planning of the two flights.
6
Durrant, J. T., William Doebler, Alexandra Loubeau, Mark C. Anderson, and Kent L. Gee. "Comparison and regression analysis of lateral sonic boom measurements and PCBoom predictions." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A126. http://dx.doi.org/10.1121/10.0015767.
Full textAbstract:
NASA plans to fly the X-59 aircraft over communities to gather data on the response to quiet supersonic flight. This data campaign could revolutionize the aerospace industry by enabling commercial, overland supersonic flight. To prepare for this campaign, NASA is developing PCBoom, a software suite of sonic boom modeling tools. PCBoom-predicted Perceived Level (PL) values were previously compared with measured PL values from a recent NASA test flight campaign, Quiet Supersonic Flights 2018 (QSF18), and were found to differ by an average of 6 dB. This work investigates the PCBoom prediction performance using data from NASA’s 2020 CarpetDIEM Phase I flight test using an F-18 aircraft. PL predictions are compared using the PCBoom default F-18 F-function near-field as input versus a computational fluid dynamics near-field solution for the aircraft as input. To investigate potential sources of metric variability and differences between modeled and measured metrics, Least Absolute Shrinkage and Selection Operator (LASSO) and least-squares regression are used. Because weather has a strong influence on sonic boom variability, the regression techniques are also used to guide the necessary number of ground weather measurements to capture boom metric variability. [Work supported by NASA Langley Research Center through the National Institute of Aerospace.]
7
Thotawaththa, Pramesh Chathushka, and A. W. S. Chandana. "Effectiveness of the biomechanical factors related to triple jump performance prediction during COVID 19 period in sri lanka." South Florida Journal of Development 3, no. 1 (February 21, 2022): 1351–59. http://dx.doi.org/10.46932/sfjdv3n1-104.
Full textAbstract:
The triple jump is an athletic event consisting of three phases which are hop, step, and jump. According to the reversibility training method, that reveals when these athletes can’t be able to maintain their physical fitness and performance properly, it influences for their performance negatively. This study was to identify how the athletes maintain the performances and how they obtain the performance prediction using the biomechanical method during the COVID-19 period in Sri Lanka. Those data were collected from five National standard male triple jumpers. The mean age of the participants is 26. The triple jump technique was done by using the dynamic equation which included kinematic variables for flight phase of the above three phases. The Matlab17 software was used to optimize the flight phase. Three cameras (100Hz) were used to observe the coordinates of center of mass and kinematics variables on the sagittal plane. The videos were analyzed through the Kinovea (0.9.3 version) software. The hop dominated balance technique (35.5: 30.4: 34.1) was used for the prediction. The previous performances values of the players were 14.32m to 16.07m (Before 2020). Current COVID-19 period performances were 13.13m to 15.43m. The velocity and angle were optimized by 5% and +20 outcome of the players were more than 16m. Considering this study, athletes’ phases weren’t in the optimum phase ratio. The hop dominated balance performance prediction and players’ current and previous performances were significantly different in this study. Through this research all coaches and athletes can identify their shortcoming phase and values of the optimization variables and prediction performance level. If not, coaching techniques and tactics can be modified.
8
Amaro Carmona, Manuel Angel, Darius Rudinskas, and Cristina Barrado. "DESIGN OF A FLIGHT MANAGEMENT SYSTEM TO SUPPORT FOUR-DIMENSIONAL TRAJECTORIES." Aviation 19, no. 1 (March 30, 2015): 58–65. http://dx.doi.org/10.3846/16487788.2015.1015284.
Full textAbstract:
This paper presents the design and simulation of the functions of a flight Management System (FMS) in order to follow four-dimensional trajectories automatically. This is achieved by controlling the aircraft’s airspeed, altitude, heading and vertical speed in order to arrive to the merging point in a specified time. The system receives data from the aircraft and computes new control parameters based on mathematical equations and algorithms of prediction trajectories. Additional features have been added to the FMS-4D, such as the capability of predicting the arrival time taking into account previous flight parameters and speed/altitude constrains. Finally, a testing phase was carried out using a flight simulator in order to obtain the performance and results of the designed system.
9
Yeo, Hyeonsoo, and Robert A. Ormiston. "UH-60A Airloads Workshop—Setting the Stage for the Rotorcraft CFD/CSD Revolution, Part I: Background and Initial Success." Journal of the American Helicopter Society 67, no. 2 (April 1, 2022): 1–17. http://dx.doi.org/10.4050/jahs.67.022010.
Full textAbstract:
The UH-60A Airloads Workshop was a unique collaboration of aeromechanics experts from the U.S. Government, industry, and academia to address technical issues that hindered accurate rotor loads predictions. The Airloads Workshop leveraged the NASA/Army UH-60A Airloads flight test and NFAC wind tunnel test data. It functioned continuously for 17 years, from 2001 to 2018, and brought about one of the most important advancements in rotorcraft aeromechanics prediction capabilities by successfully demonstrating high-fidelity coupled computational fluid dynamics (CFD) and computational structural dynamics (CSD) analyses for both steady and maneuvering flight. The article is divided into two parts. Part I surveys the background of rotorcraft CFD/CSD development difficulties, the origins of the Airloads Workshop, and the rapid success achieved during the first phase that consisted of eight Workshops. Part II describes ongoing development during the subsequent two phases of the Airloads Workshop, the Ninth through the 13th, and the 14th through the 31st Workshops; the impact of the Airloads Workshop; and the lessons learned. Part I surveys the technical activities that led to a breakthrough for CFD/CSD coupling to successfully predict rotor blade airloads in trimmed steady-level flight conditions. This success illustrated the importance of collaboration among key experts with diverse backgrounds focused on a common objective to advance rotorcraft prediction methods.
10
Jung, JaeKyung, and DongHwan Hwang. "Impact Point Prediction of the Ballistic Target Using a Flight Phase Discrimination." Journal of the Korea Institute of Military Science and Technology 18, no. 3 (June 5, 2015): 234–43. http://dx.doi.org/10.9766/kimst.2015.18.3.234.
Full text
11
Wan, JiaQing, Qian Zhang, Hao Zhang, and JiaNing Liu. "A Midcourse Guidance Method Combined with Trajectory Prediction for Antinear-Space-Gliding Vehicles." International Journal of Aerospace Engineering 2022 (December 28, 2022): 1–18. http://dx.doi.org/10.1155/2022/4528803.
Full textAbstract:
Near-space-gliding vehicles have variable maneuver modes and dramatic changes in their ballistic parameters, which lead to a need to accurately predict an intercept point based on predictions of their trajectories. First, a trajectory prediction method builds a set of time-varying maneuver models based on flight missions combined with an adaptive grid to infer maneuver modes. An interactive multiple-model method of variable structure is proposed to identify the characteristics of the maneuver mode by introducing a fading factor and the modified Markov probability transfer matrix and then predict the trajectory through numerical integration. In the midcourse guidance method, the prediction of the target trajectory is introduced, and the zero-control interception manifold with intersection angle constraints is designed as the midcourse guidance terminal constraint. For the calculation of the starting time of the boost phase, the optimization solution satisfying the remaining flight time constraint is realized based on the Newton-Raphson iterative method. The analytical expression of a guidance command based on zero-error-miss/zero-error-velocity is established on the basis of the optimal control theory to provide an optimal flight path guiding an NSGV fly toward a point of interception. The simulation results show that the trajectory-prediction method has high prediction accuracy and strong convergency for typical maneuver modes, and the proposed midcourse guidance algorithm meets the requirements of the zero-effort intercept manifold with the intersection angle constraints, which is of important theoretical significance and acts as a reference value for intercepting high-velocity maneuver targets.
12
Kurdel, Pavol, Marek Češkovič, Natália Gecejová, František Adamčík, and Mária Gamcová. "Local Control of Unmanned Air Vehicles in the Mountain Area." Drones 6, no. 2 (February 21, 2022): 54. http://dx.doi.org/10.3390/drones6020054.
Full textAbstract:
The task of increasing the accuracy and stabilization of the flight of unmanned aerial vehicles (UAV) in the alpine environment is a complex problem. It is related to the evaluation of UAV flight parameters and control conditions for the operator’s place. The purpose of the UAV’s autonomous flight control is to ensure stable control of the UAV’s flight parameters. Flight control systems are affected by various disturbances caused by both internal and external conditions. In general, the number of autonomous control systems corresponds to the number of degrees of freedom, which determines the flight of an autonomous vehicle. An important factor in assessing the quality of such a UAV is its readiness for an autonomous flight together with the level of its safe guidance on the route. The presented article focuses on the analysis of UAV flight control and the quality of prediction and elimination of errors that exist during maneuvers toward the place of a successful UAV landing. The aim of the article is to point out the solvability of the complexities of such a flight procedure with the evaluation of the readiness for the descent phase of the autonomous UAV. The given problem is caused by the social demand for the creation of a way of providing health care in the mountain area of the High Tatras in Slovakia. The existing database of data obtained from the flying vehicles used in Slovakia was compared with the data obtained from the simulated flights, with their subsequent evaluation in the MATLAB software (Version R2021b) environment.
13
Li, Ke Yong, Fen Fen Xiong, Cheng Zhang, and Shi Shi Chen. "Range Prediction and Trajectory Correction of Long Range Rocket with Attitude Stabilization." Applied Mechanics and Materials 232 (November 2012): 299–304. http://dx.doi.org/10.4028/www.scientific.net/amm.232.299.
Full textAbstract:
The dispersion of long range rocket is significantly suppressed by the attitude stabilization in the boost phase. However, the attitude stabilization system cannot govern the propellant impulse error and mass error, which induces large dispersion in the longitudinal direction. Therefore, it is necessary to conduct range correction in the post-boost phase of flight trajectory. A range prediction method based on the elliptic ballistic theory is proposed in this paper. Elliptic ballistic equations and range estimation equations are derived and the modified range prediction method with correction factor is presented. It is verified that the proposed method can predict the residual flight range accurately. After that, the lateral pulse jets control is presented and utilized to correct the trajectory and eliminate the range error. A unique control law is reported that combines elliptic ballistic theory and control mode for lateral pulse jets. The impact point is directly controlled and rocket dispersion in the longitudinal direction is efficiently reduced.
14
Link, Johannes, Leo Schwinn, Falk Pulsmeyer, Thomas Kautz, and Bjoern M. Eskofier. "xLength: Predicting Expected Ski Jump Length Shortly after Take-Off Using Deep Learning." Sensors 22, no. 21 (November 3, 2022): 8474. http://dx.doi.org/10.3390/s22218474.
Full textAbstract:
With tracking systems becoming more widespread in sports research and regular training and competitions, more data are available for sports analytics and performance prediction. We analyzed 2523 ski jumps from 205 athletes on five venues. For every jump, the dataset includes the 3D trajectory, 3D velocity, skis’ orientation, and metadata such as wind, starting gate, and ski jumping hill data. Using this dataset, we aimed to predict the expected jump length (xLength) inspired by the expected goals metric in soccer (xG). We evaluate the performance of a fully connected neural network, a convolutional neural network (CNN), a long short-term memory (LSTM), and a ResNet architecture to estimate the xLength. For the prediction of the jump length one second after take-off, we achieve a mean absolute error (MAE) of 5.3 m for the generalization to new athletes and an MAE of 5.9 m for the generalization to new ski jumping hills using ResNet architectures. Additionally, we investigated the influence of the input time after the take-off on the predictions’ accuracy. As expected, the MAE becomes smaller with longer inputs. Due to the real-time transmission of the sensor’s data, xLength can be updated during the flight phase and used in live TV broadcasting. xLength could also be used as an analysis tool for experts to quantify the quality of the take-off and flight phases.
15
Goettl, Barry P., and Cathy Connolly Gomez. "The Role of Observational Learning in Automated Instruction of Complex Tasks." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 39, no. 20 (October 1995): 1335–39. http://dx.doi.org/10.1177/154193129503902021.
Full textAbstract:
This study tested the prediction that observational learning will be more effective for motor tasks having substantial cognitive demands than for those that do not. Subjects were divided into three treatment groups: performers, observers, and no-observe controls. In Phase I, subjects were trained on a computer-based flight task requiring relatively little cognitive demands. In Phase II, subjects were trained on a different flight task that had significant cognitive and strategic demands. In Phase I, performers were superior to both observers and controls; the observers did not differ significantly from the controls. In Phase II, observation showed a beneficial effect for females. The female observers performed as well as the female performers. The results of this study suggest that observational learning benefits tasks with significant cognitive components more than tasks that are primarily psychomotor. Implications for computer-based training are discussed.
16
Yeo, Hyeonsoo, and Robert A. Ormiston. "UH-60A Airloads Workshop—Setting the Stage for the Rotorcraft CFD/CSD Revolution, Part II: Ongoing Progress, Impact, and Lessons Learned." Journal of the American Helicopter Society 67, no. 2 (April 1, 2022): 1–16. http://dx.doi.org/10.4050/jahs.67.022011.
Full textAbstract:
The UH-60A Airloads Workshop was a unique collaboration of aeromechanics experts from the U.S. Government, industry, and academia to address technical issues that hindered accurate rotor loads predictions. The Airloads Workshop leveraged the NASA/Army UH-60A Airloads flight test and NFAC wind tunnel test data. It functioned continuously for 17 years, from 2001 to 2018, and brought about one of the most important advancements in rotorcraft aeromechanics prediction capabilities by successfully demonstrating high-fidelity coupled computational fluid dynamics (CFD) and computational structural dynamics (CSD) analyses for both steady and maneuvering flight. The article is divided into two parts. Part I surveys the background of rotorcraft CFD/CSD development difficulties, the origins of the Airloads Workshop, and the rapid success achieved during the first phase that consisted of eight Workshops. Part II describes ongoing development during the subsequent two phases of the Airloads Workshop, the Ninth through the 13th, and the 14th through the 31st Workshops. Part II outlines development of CFD/CSD methods to predict rotor airloads for the challenging maneuvering flight condition and also describes the impact of the newly developed CFD/CSD methods and how they were transferred to the larger technical community, opening the door for practical application of CFD methods for designing future advanced rotorcraft. Part II concludes with a discussion of why the Airloads Workshop succeeded and lessons learned from the collaborative effort.
17
Oruc, Ridvan, and Tolga Baklacioglu. "Modeling of fuel flow-rate of commercial aircraft for the descent flight using particle swarm optimization." Aircraft Engineering and Aerospace Technology 93, no. 2 (February 25, 2021): 319–26. http://dx.doi.org/10.1108/aeat-09-2020-0213.
Full textAbstract:
Purpose The purpose of this paper is to create a new fuel flow rate model for the descent phase of the flight using particle swarm optimization (PSO). Design/methodology/approach A new fuel flow rate model was developed for the descent phase of the B737-800 aircraft, which is frequently used in commercial air transport using PSO method. For the analysis, the actual flight data records (FDRs) data containing the fuel flow rate, speed, altitude, engine speed, time and many more data were used. In this regard, an empirical formula has been created that gives real fuel flow rate values as a function of altitude and true airspeed. In addition, in the fuel flow rate predictions made for the descent phase of the specified aircraft, a different model has been created that can be used without any optimization process when FDR data are not available for a specific aircraft take-off weight condition. Findings The error analysis applied to the models showed that both models predict real fuel flow rate values with high precision. Practical implications Because of the high accuracy of the PSO model, it is thought to be useful in air traffic management, decision support systems, models used for trajectory prediction, aircraft performance models, strategies used to reduce fuel consumption and emissions because of fuel consumption. Originality/value This study is the first fuel flow rate model for descent flight using PSO algorithm. The use of real FDR data in the analysis shows the originality of this study.
18
Su, Qian, Xiangtian Deng, Zhenxing Liu, Chao Tan, and Feng Dong. "Phase fraction measurement of oil–gas–water three-phase flow with stratified gas by ultrasound technique." Measurement Science and Technology 33, no. 7 (April 11, 2022): 075302. http://dx.doi.org/10.1088/1361-6501/ac60f6.
Full textAbstract:
Abstract Phase fraction is one of important indexes to characterize multiphase flow. In order to measure each phase fraction of oil–gas–water three-phase flow, liquid level height is detected by time-of-flight—TOF of reflected ultrasound at gas–liquid interface, while oil phase fraction in reflection path is calculated according to the ultrasound attenuation. By studying interactions between multiphase flow and the ultrasound propagation in certain flow patterns, a prediction model for phase fraction measurement of three-phase flow is proposed based on ultrasound transmission attenuation and reflection TOF in the process of horizontal flow with actual phase distributions. Simulation and experimental results under conditions of oil–water two-phase structure with stratified gas in a horizontal pipe show that the proposed method and the established model can accurately detect gas–liquid interface, so that measure oil, gas, water phase fraction. The mechanism prediction model and the measurement device effectively solve the nonlinear response of the ultrasonic measurement parameter, so that can estimate phase fractions of liquids and gas in two-phase as well as three-phase flows simultaneously, which extends the measurement range and the applicable scope of ultrasonic technique to multiphase flow.
19
Jones, Michael, Marc Alexander, Marc Höfinger, Miles Barnett, Perry Comeau, and Arthur Gubbels. "In-Flight Test Campaign to Validate PIO Detection and Assessment Tools." Aerospace 7, no. 9 (September 10, 2020): 136. http://dx.doi.org/10.3390/aerospace7090136.
Full textAbstract:
This paper describes a joint research campaign conducted by the German Aerospace Center (DLR) and the National Research Council Canada (NRC) to explore methods and techniques to expose rotorcraft pilot-induced oscillations (PIOs) during flight testing. A flight test campaign was conducted at NRC using the Bell 205 experimental aircraft. Results show that, particularly for the lateral axis, ADS-33 tasks can be successfully applied to expose PIO tendencies. Novel subjective and objective criteria were used during the test campaign. PIO prediction boundaries of the objective phase-aggression criteria (PAC) detection algorithm were validated through results obtained. This was the first use of PAC with data recorded in-flight. To collect subjective feedback, the aircraft–pilot coupling (APC) scale was used. This was the first use of the novel scale in-flight and received favourable feedback from the evaluation pilot. Modifications to ADS-33 mission tasks were found to successfully improve the ability to consistently expose PIOs.
20
Liebing, Patricia, Matthijs Krijger, Ralph Snel, Klaus Bramstedt, Stefan Noël, Heinrich Bovensmann, and John P. Burrows. "In-flight calibration of SCIAMACHY's polarization sensitivity." Atmospheric Measurement Techniques 11, no. 1 (January 15, 2018): 265–89. http://dx.doi.org/10.5194/amt-11-265-2018.
Full textAbstract:
Abstract. This paper describes the in-flight calibration of the polarization response of the SCIAMACHY polarization measurement devices (PMDs) and a selected region of its science channels. With the lack of polarized calibration sources it is not possible to obtain such a calibration from dedicated calibration measurements. Instead, the earthshine itself, together with a simplified radiative transfer model (RTM), is used to derive time-dependent and measurement-configuration-dependent polarization sensitivities. The results are compared to an instrument model that describes the degradation of the instrument as a result of a slow buildup of contaminant layers on its elevation and azimuth scan mirrors. This comparison reveals significant differences between the model prediction and the data, suggesting an unforeseen change between on-ground and in-flight calibration in at least one of the polarization-sensitive components of the optical bench. The possibility of mechanisms other than scan mirror contamination contributing to the degradation of the instrument will be discussed. The data are consistent with a polarization phase shift occurring in the beam split prism used to divert the light coming from the telescope to the different channels and polarization measurement devices. The extension of the instrument degradation model with a linear retarder enables the determination of the relevant parameters to describe this phase shift and ultimately results in a significant improvement of the polarization measurements as well as the polarization response correction of measured radiances.
21
Zhao, Yu Chen, Léa Le Joncour, Andrzej Baczmański, Manuel François, Sebastian Wroński, Benoit Panicaud, Elżbieta Gadalińska, Chedly Braham, Thomas Buslaps, and Anna Paradowska. "Elastoplastic Deformation and Damage Process in Duplex Steel Studied Using Synchrotron and Neutron Diffraction." Materials Science Forum 905 (August 2017): 9–16. http://dx.doi.org/10.4028/www.scientific.net/msf.905.9.
Full textAbstract:
In the present work, the mechanical behavior of phases in duplex steel during tensile test was studied. Special interest was taken in the analysis of damage process just before failure. In this aim two diffraction methods: in-situ time of flight neutron diffraction and X-ray synchrotron diffraction were applied. Using diffraction data, the slip mechanism on crystallographic planes during plastic deformation was investigated. In the case of aged UR45N steel, it was found that significant softening caused by damage process was initiated in the ferritic phase. The lattice strains measured in situ by two above mentioned diffraction methods were compared with prediction of the self-consistent model.
22
Baklacioglu, T., and M. Cavcar. "Aero-propulsive modelling for climb and descent trajectory prediction of transport aircraft using genetic algorithms." Aeronautical Journal 118, no. 1199 (January 2014): 65–79. http://dx.doi.org/10.1017/s0001924000008939.
Full textAbstract:
Abstract In this study, a new aero-propulsive model (APM) was derived from the flight manual data of a transport aircraft using Genetic Algorithms (GAs) to perform accurate trajectory predictions. This new GA-based APM provided several improvements to the existing models. The use of GAs enhanced the accuracy of both propulsive and aerodynamic modelling. The effect of compressible drag rise above the critical Mach number, which was not included in previous models, was considered along with the effects of compressibility and profile camber in the aerodynamic model. Consideration of the thrust dependency with respect to Mach number and the altitude in the propulsive model expression was observed to be a more practical approach. The proposed GA model successfully predicted the trajectory for the descent phase, as well, which was not possible in previous models. Close agreement was observed when comparing the time to climb and time to descent values obtained from the model with the flight manual data.
23
Wang, Shizhao, Guowei He, and Tianshu Liu. "Estimating lift from wake velocity data in flapping flight." Journal of Fluid Mechanics 868 (April 15, 2019): 501–37. http://dx.doi.org/10.1017/jfm.2019.181.
Full textAbstract:
The application of the Kutta–Joukowski (KJ) theorem to estimating the lift of a flying animal based on wake velocity fields often leads to significant underprediction of the lift, which is known as the wake momentum paradox. This work attempts to answer the puzzling question on whether the KJ theorem is legitimate in its use for complex viscous unsteady wakes generated by flapping wings. The limitations in applying the KJ theorem to flapping wings are quantitatively examined through numerical simulations of viscous incompressible flows over three flapping wing models. The three flapping wing models studied in this work are a flapping wing with a fixed wingspan, a flapping wing with a dynamically changing wingspan and a dihedral flapping wing. The KJ theorem fails to give a satisfactory prediction of the time-averaged lift unless an effective span length is correctly computed. We propose a wake-sectional Kutta–Joukowski (WS-KJ) model to predict the time-averaged lift, where the effective span length is computed based on the time-averaged distance between the streamwise vorticity centroids in the right and left half sides of the Trefftz plane. The WS-KJ model incorporates the spatial evolutionary effects of the complex vortex structures in the wake and significantly improves the prediction of the time-averaged lift. The physical foundation for such improvement is explored. In addition, the time-dependent amplitude and phase changes of the unsteady lift are discussed as the fluid acceleration effect.
24
Oruc, Ridvan, and Tolga Baklacioglu. "Modelling of fuel flow-rate of commercial aircraft for the climbing flight using cuckoo search algorithm." Aircraft Engineering and Aerospace Technology 92, no. 3 (February 10, 2020): 495–501. http://dx.doi.org/10.1108/aeat-10-2019-0202.
Full textAbstract:
Purpose The purpose of this study is to create a new fuel flow rate model adopting cuckoo search algorithm (CSA) for the climbing phase of the flight. Design/methodology/approach Using the real flight data records (FDRs) of B737-800 passenger aircraft, a new fuel flow rate model for the climbing phase of the flight was developed by incorporating CSA. In the model, fuel flow rate is given as a function of altitude and true airspeed. The aim is to create a model that yields results that are closest to the real fuel flow rate values obtained from flight data records. Various error analysis methods were used to test the accuracy of the obtained values. Finally, the effect of change of some CSA parameters on the model was investigated. Findings It was observed that the derived model is able to predict real fuel flow rate values with high accuracy. It has been deduced that increasing the number of nest (n) and discovery rate of alien nests (pa) values of CSA parameters to a certain value gradually decreases the model’s accuracy. Practical implications This model is considered to be useful in air traffic management decision support systems, simulation applications, aircraft trajectory prediction models and aircraft performance modelling studies because of the high accuracy accomplished by the CSA model. Originality/value The originality of this study is the development of a new fuel flow rate model using CSA as a first attempt in the literature. The use of real flight data is important for the originality and reliability of the model.
25
Schuster, W. "Trajectory prediction for future air traffic management – complex manoeuvres and taxiing." Aeronautical Journal 119, no. 1212 (February 2015): 121–43. http://dx.doi.org/10.1017/s0001924000010307.
Full textAbstract:
AbstractThe future air traffic management (ATM) concept envisaged by the Single European Sky ATM Research – SESAR – and the USA equivalent NextGen, mark a paradigm shift from the current reactive approach of ATM towards holistic strategic collaborative decision making. The core of the future ATM concept relies on common situational awareness over potentially large time-horizons, based upon the user operational intent. This is beyond human capabilities and requires the support of automation tools to predict aircraft state throughout the operation and provide support to optimal decision making long before any potential conflict may arise. This is achieved with trajectory predictors and conflict detectors and resolvers respectively. Numerous tools have been developed, typically geared towards addressing specific airborne applications. However, a comprehensive literature search suggests that none of the tools was designed to predict trajectories throughout the entire operation of an aircraft, i.e. gate-to-gate. Yet, such functionality is relevant in the holistic optimisation of aircraft operations. To address this gap, this paper builds on an existing en route trajectory prediction (TP) model and develops novel techniques to predict aircraft trajectories for the transitions between the ground- and enroute-phases of operation and for the ground-phase, thereby enabling gate-to-gate (or enroute -to-enroute) TP. The model is developed on the basis of Newtonian physics and operational procedures. Real recorded data obtained from a flight data record (FDR) were used to estimate some of the input parameters required by the model. The remaining parameters were taken from the BADA 3.7 model. Performance results using these flight data demonstrate that the proposed TP model has the potential to accurately predict gate-to-gate trajectories and to support future ATM applications such as gate-to-gate synchronisation.
26
M, Meghana, Rebecca Judaist, Praveen R, Rakshitha S, and Vinod Kumar S. "A Study on an Effective Model for Predicting Flight Delay." Indian Journal of Software Engineering and Project Management 1, no. 4 (July 30, 2022): 1–3. http://dx.doi.org/10.54105/ijsepm.c9013.071422.
Full textAbstract:
Amongst the most significant business concerns that airline companies face is the considerable expenses related to airlines being delays caused due to natural events and operations and maintenance flaws, which is an additional expense for the airlines, having caused scheduling and operations problems for end-users, likely to result in a negative revenue and customer displeasure. We used supervised machine learning approaches in this study to develop a two-stage prediction models for forecasting flight on-time performance. This model's initial stage uses binary classification to predict flight delays, while the second phase uses regression to estimate the delay's duration in minutes. The proposed research compares the effectiveness of decision tree classifier to logistic regression. Based on the created model, the outcomes of this simulation disclose projected congestion in airports, considering hour, day, climate, and so on. As a result, there will be less time spent waiting.
27
Wang, Bin, Yan Zhang, Chunshan Wang, and Guifa Teng. "Droplet Deposition Distribution Prediction Method for a Six-Rotor Plant Protection UAV based on Inverse Distance Weighting." Sensors 22, no. 19 (September 29, 2022): 7425. http://dx.doi.org/10.3390/s22197425.
Full textAbstract:
The aim of this work is to establish a method for real-time calculating droplet deposition distribution of a six-rotor plant protection unmanned aerial vehicle (UAV). The numerical simulation of the airflow field was carried out using computational fluid dynamics (CFD). The airflow field distribution was obtained under seven flight speeds, six flight heights, and seven crosswind speeds. The relative error verified the accuracy of the numerical model within 12% between the spatial point wind speed test and the simulated value. The numerical simulation results showed that with the improvement of the UAV flight speed and the crosswind, the relative airflow produces a vortex in the downwash wind field below the UAV and reduces the stability of the downwash wind field. The discrete droplet phase was introduced in the flow field. The ground regions were divided using a small grid of 0.5 m × 0.5 m, and statistical calculations of droplet deposition rates within each grid yielded the distribution of droplets under 294 different parameter combinations. The statistical results show that the relative airflow and crosswind caused droplet convolution, and droplet drift was increased. In the actual operation of the UAV, the flight speed should be well controlled under the condition of low environmental wind to reduce the droplet drift rate and improve the utilization rate of pesticides. Based on the distribution under 294 different parameter combinations, one droplet deposition prediction method was established using inverse distance weighting (IDW). The proposed method lays a foundation for the cumulative calculation of droplet deposition distribution during continuous operation of plant protection UAV. It provides a basis for objectively evaluating the operational quality of plant protection UAVs and optimizing the setting of operation parameters.
28
Ma, Ning, Xiangrui Weng, Yunfeng Cao, and Linbin Wu. "Monocular-Vision-Based Precise Runway Detection Applied to State Estimation for Carrier-Based UAV Landing." Sensors 22, no. 21 (November 1, 2022): 8385. http://dx.doi.org/10.3390/s22218385.
Full textAbstract:
Improving the level of autonomy during the landing phase helps promote the full-envelope autonomous flight capability of unmanned aerial vehicles (UAVs). Aiming at the identification of potential landing sites, an end-to-end state estimation method for the autonomous landing of carrier-based UAVs based on monocular vision is proposed in this paper, which allows them to discover landing sites in flight by using equipped optical sensors and avoid a crash or damage during normal and emergency landings. This scheme aims to solve two problems: the requirement of accuracy for runway detection and the requirement of precision for UAV state estimation. First, we design a robust runway detection framework on the basis of YOLOv5 (you only look once, ver. 5) with four modules: a data augmentation layer, a feature extraction layer, a feature aggregation layer and a target prediction layer. Then, the corner prediction method based on geometric features is introduced into the prediction model of the detection framework, which enables the landing field prediction to more precisely fit the runway appearance. In simulation experiments, we developed datasets applied to carrier-based UAV landing simulations based on monocular vision. In addition, our method was implemented with help of the PyTorch deep learning tool, which supports the dynamic and efficient construction of a detection network. Results showed that the proposed method achieved a higher precision and better performance on state estimation during carrier-based UAV landings.
29
Kusaba, A., S. Nitta, K. Shiraishi, T. Kuboyama, and Y. Kangawa. "Beyond ab initio reaction simulator: An application to GaN metalorganic vapor phase epitaxy." Applied Physics Letters 121, no. 16 (October 17, 2022): 162101. http://dx.doi.org/10.1063/5.0119783.
Full textAbstract:
To develop a quantitative reaction simulator, data assimilation was performed using high-resolution time-of-flight mass spectrometry (TOF-MS) data applied to a GaN metalorganic vapor phase epitaxy system. Incorporating ab initio knowledge into the optimization enables it to reproduce not only the concentration of CH4 (an impurity precursor) as an objective variable but also known reaction pathways. The simulation results show significant production of GaH3, a precursor of GaN, which has been difficult to detect in TOF-MS experiments. Our proposed approach is expected to be applicable to other applied physics fields that require quantitative prediction that goes beyond ab initio reaction rates.
30
Holzäpfel, Frank. "Analysis of potential wake vortex encounters at a major European airport." Aircraft Engineering and Aerospace Technology 89, no. 5 (September 4, 2017): 634–43. http://dx.doi.org/10.1108/aeat-01-2017-0043.
Full textAbstract:
Purpose In this study, 12 potential wake vortex encounters that were reported at a major European airport have been investigated. Because almost all encounters occurred in ground proximity, most pilots conducted a go-around. The primary purpose of this study is to discriminate between incidents caused by wake vortices or rather by effects like wind shear or turbulence. Detailed knowledge of real-world encounter scenarios and identification of worst-case conditions during the final approach constitute highly relevant background information to assess the standard scenario used for the definition of revised wake turbulence separations. Design/methodology/approach Wake vortex predictions using the probabilistic two-phase wake vortex model (P2P) are used to investigate the incidents in detail by using data from the flight data recorder, meteorological instrumentation at the airport and numerical weather prediction. Findings In the best documented cases, the flight tracks through the vortices could be reconstructed in good agreement with wake vortex predictions and recorded aircraft reactions. Out of the eight plausible wake vortex encounters, five were characterized by weak crosswinds below 1.5 m/s combined with tailwinds. This meteorological situation appears favourable for encounters because, on the one hand, weak crosswinds may compensate the self-induced lateral propagation of the upwind vortex, such that it may hover over the runway directly in the flight path of the following aircraft. On the other hand, tailwinds limit the propagation of the so-called end effects caused by the breakdown of lift during touchdown. Practical implications The installation of plate lines beyond the runway tails may improve safety by reducing the number of wake vortex encounters. Originality/value The conducted investigations provide high originality and value for both science and operational application.
31
Förster, Stanley, Michael Schultz, and Hartmut Fricke. "Probabilistic Prediction of Separation Buffer to Compensate for the Closing Effect on Final Approach." Aerospace 8, no. 2 (January 26, 2021): 29. http://dx.doi.org/10.3390/aerospace8020029.
Full textAbstract:
The air traffic is mainly divided into en-route flight segments, arrival and departure segments inside the terminal maneuvering area, and ground operations at the airport. To support utilizing available capacity more efficiently, in our contribution we focus on the prediction of arrival procedures, in particular, the time-to-fly from the turn onto the final approach course to the threshold. The predictions are then used to determine advice for the controller regarding time-to-lose or time-to-gain for optimizing the separation within a sequence of aircraft. Most prediction methods developed so far provide only a point estimate for the time-to-fly. Complementary, we see the need to further account for the uncertain nature of aircraft movement based on a probabilistic prediction approach. This becomes very important in cases where the air traffic system is operated at its limits to prevent safety-critical incidents, e.g., separation infringements due to very tight separation. Our approach is based on the Quantile Regression Forest technique that can provide a measure of uncertainty of the prediction not only in form of a prediction interval but also by generating a probability distribution over the dependent variable. While the data preparation, model training, and tuning steps are identical to classic Random Forest methods, in the prediction phase, Quantile Regression Forests provide a quantile function to express the uncertainty of the prediction. After developing the model, we further investigate the interpretation of the results and provide a way for deriving advice to the controller from it. With this contribution, there is now a tool available that allows a more sophisticated prediction of time-to-fly, depending on the specific needs of the use case and which helps to separate arriving aircraft more efficiently.
32
Li, Chunlai, Zhendong Wang, Rui Xu, Gang Lv, Liyin Yuan, Zhiping He, and Jianyu Wang. "The Scientific Information Model of Chang’e-4 Visible and Near-IR Imaging Spectrometer (VNIS) and In-Flight Verification." Sensors 19, no. 12 (June 22, 2019): 2806. http://dx.doi.org/10.3390/s19122806.
Full textAbstract:
The Chang’e-4 (CE-4) lunar rover, equipped with a visible and near-IR imaging spectrometer (VNIS) based on acousto-optic tunable filter spectroscopy, was launched to the far side of the moon on December 8, 2018. The detection band of the VNIS ranges from 0.45 to 2.4 μm. Because of the weak reflection of infrared radiation from the lunar surface, a static electronic phase-locked acquisition method is adopted in the infrared channel for signal amplification. In this paper, full-link simulations and modeling are conducted on the infrared channel information flow of the instrument. The signal characteristics of the VNIS are analyzed in depth, and the signal to noise ratio (SNR) prediction and laboratory verification are presented. On 4 January 2019, the VNIS started working successfully and acquired high-resolution spectrum data of the far side of the moon for the first time. Through analysis we have found that the SNR ratio is in line with our predictions, and the data obtained by VNIS in orbit are consistent with the information model proposed in this paper.
33
Wang, Zhengzhi, and Chunling Zhu. "Numerical simulation of three-dimensional rotor icing in hovering flight." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 232, no. 3 (December 9, 2016): 545–55. http://dx.doi.org/10.1177/0954410016682273.
Full textAbstract:
Rotor icing is a serious threat to helicopter flight safety and computational fluid dynamics technology is very useful in icing prediction. In this work, a numerical simulation method is presented to calculate three-dimensional rotor icing in hovering flight. The rotor flow fields are obtained using overlapping grids. According to Euler two-phase flow, the droplet trajectories and impingement characteristics are predicted. On the basis of three-dimensional ice accretion model, a new runback water distribution method based on shear force and centrifugal force is proposed to simulate liquid water flow and ice shape. The calculation results are compared with the experimental results under different conditions in order to verify the correctness of the method. Furthermore, the effects of blades rotation on the liquid water content distribution and droplet impingement characteristics are studied, and the effect of centrifugal force on ice shape is analyzed. The results show that the blade will influence others with the blade tip Mach number increasing, and centrifugal force will cause the ice thickness increases on leading edge and decreases at both frozen limitations.
34
Li, Shanmei, Dongfan Xie, Xie Zhang, Zhaoyue Zhang, and Wei Bai. "Data-Driven Modeling of Systemic Air Traffic Delay Propagation: An Epidemic Model Approach." Journal of Advanced Transportation 2020 (August 3, 2020): 1–12. http://dx.doi.org/10.1155/2020/8816615.
Full textAbstract:
To better understand the mechanism of air traffic delay propagation at the system level, an efficient modeling approach based on the epidemic model for delay propagation in airport networks is developed. The normal release rate (NRR) and average flight delay (AFD) are considered to measure airport delay. Through fluctuation analysis of the average flight delay based on complex network theory, we find that the long-term dynamic of airport delay is dominated by the propagation factor (PF), which reveals that the long-term dynamic of airport delay should be studied from the perspective of propagation. An integrated airport-based Susceptible-Infected-Recovered-Susceptible (ASIRS) epidemic model for air traffic delay propagation is developed from the network-level perspective, to create a simulator for reproducing the delay propagation in airport networks. The evolution of airport delay propagation is obtained by analyzing the phase trajectory of the model. The simulator is run using the empirical data of China. The simulation results show that the model can reproduce the evolution of the delay propagation in the long term and its accuracy for predicting the number of delayed airports in the short term is much higher than the probabilistic prediction method. The model can thus help managers as a tool to effectively predict the temporal and spatial evolution of air traffic delay.
35
Jonglez, Clément, Julian Bartholomäus, Philipp Werner, and Enrico Stoll. "Initial Tracking, Fast Identification in a Swarm and Combined SLR and GNSS Orbit Determination of the TUBIN Small Satellite." Aerospace 9, no. 12 (December 3, 2022): 793. http://dx.doi.org/10.3390/aerospace9120793.
Full textAbstract:
Flight dynamics is a topic often overlooked by operators of small satellites without propulsion systems, as two-line elements (TLE) are easily accessible and accurate enough for most ground segment needs. However, the advent of cheap and miniaturized global navigation satellite system (GNSS) receivers and laser retroreflectors as well as modern, easy-to-use, open-source software tools have made it easier to accurately determine an orbit or to identify a spacecraft in a swarm, which helps with improving the space situational awareness in orbits that are more and more crowded. In this paper, we present tools for small satellite missions to generate orbit predictions for the launch and early orbit phase (LEOP), identify spacecraft in a swarm after a rideshare launch, and carry out routine orbit determination from multiple sources of tracking data. The TUBIN mission’s LEOP phase set a new standard at Technische Universität Berlin: the first global positioning system (GPS) data were downloaded less than four hours after separation, orbit predictions allowed successful tracking by the ground stations, and the spacecraft could be identified in the swarm as soon as the TLE were released by Space-Track. Routine orbit determination from GPS and satellite laser ranging (SLR) tracking data was carried out over several months, and the quality of the orbit predictions was analyzed. The range residuals and prediction errors were found to be larger than those of most SLR missions, which was due to the difficulty of modeling the atmospheric drag of a tumbling, non-spherical spacecraft at low orbital altitudes.
36
Sulia, Kara J., Hugh Morrison, and Jerry Y. Harrington. "Dynamical and Microphysical Evolution during Mixed-Phase Cloud Glaciation Simulated Using the Bulk Adaptive Habit Prediction Model." Journal of the Atmospheric Sciences 71, no. 11 (October 29, 2014): 4158–80. http://dx.doi.org/10.1175/jas-d-14-0070.1.
Full textAbstract:
Abstract A bulk microphysics scheme predicting ice particle habit evolution has been implemented in the Weather Research and Forecasting Model. Large-eddy simulations are analyzed to study the effects of ice habit and number concentration on the bulk ice and liquid masses, dynamics, and lifetime of Arctic mixed-phase boundary layer clouds. The microphysical and dynamical evolution simulated using the adaptive habit scheme is compared with that assuming spherical particles with a density of bulk ice or a reduced density and with mass–dimensional parameterizations. It is found that the adaptive habit method returns an increased (decreased) ice (liquid) mass as compared to spheres and provides a more accurate simulation as compared to dendrite mass–size relations. Using the adaptive habit method, simulations are then completed to understand the microphysical and dynamical interactions within a single-layer mixed-phase stratocumulus cloud observed during flight 31 of the Indirect and Semi-Direct Aerosol Campaign. With cloud-top longwave radiative cooling as a function of liquid mass acting as the primary dynamic driver of turbulent eddies within these clouds, the consumption of liquid at the expense of ice growth and subsequent sedimentation holds a strong control on the cloud lifetime. Ice concentrations ≥ 4 L−1 collapse the liquid layer without any external maintaining sources. Layer maintenance is possible at 4 L−1 when a constant cloud-top cooling rate or the water mass lost due to sedimentation is supplied. Larger concentrations require a more substantial source of latent or sensible heat for mixed-phase persistence.
37
Gao, Xinglong, Qingbin Zhang, and Qiangang Tang. "Fluid-Structure Interaction Analysis of Parachute Finite Mass Inflation." International Journal of Aerospace Engineering 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/1438727.
Full textAbstract:
Parachute inflation is coupled with sophisticated fluid-structure interaction (FSI) and flight mechanic behaviors in a finite mass situation. During opening, the canopy often experiences the largest deformation and loading. To predict the opening phase of a parachute, a computational FSI model for the inflation of a parachute, with slots on its canopy fabric, is developed using the arbitrary Lagrangian-Euler coupling penalty method. In a finite mass situation, the fluid around the parachute typically has an unsteady flow; therefore, a more complex opening phase and FSI dynamics of a parachute are investigated. Navier-Stokes (N-S) equations for uncompressible flow are solved using an explicit central difference method. The three-dimensional visualization of canopy deformation as well as the evolution of dropping velocity and overload is obtained and compared with the experimental results. This technique could be further applied in the airdrop test of a parachute for true prediction of the inflation characteristics.
38
Głębocki, Robert, and Mariusz Jacewicz. "Parametric Study of Guidance of a 160-mm Projectile Steered with Lateral Thrusters." Aerospace 7, no. 5 (May 21, 2020): 61. http://dx.doi.org/10.3390/aerospace7050061.
Full textAbstract:
The development of projectile guidance requires consideration of a large number of possible flight scenarios with various system parameters. In this paper, the Monte-Carlo parametric study for a 160 mm artillery rocket equipped with a set of 34 small, solid propellant lateral thrusters located before the center of mass was evaluated to reduce projectile dispersion and collateral damage. The novelty of this paper lies in the functionality of modifying the shape of the trajectory in the terminal phase using lateral thrusters only. A six degree of freedom mathematical model implemented in MATLAB/Simulink was used to investigate the influence of numerous parameters on the resulting accuracy at several launch elevation angles. Augmented impact point prediction guidance was applied in the descending portion of the flight trajectory to achieve the trajectory shaping functionality. The optimum combination of thruster magnitude and algorithm parameters was obtained. The real data from the LN200 inertial measurement unit were used to investigate the influence of noise on the resulting accuracy. It was shown that with the proposed guidance method, the dispersion could be reduced by more than 250 times and the projectile impact angle might be increased when compared to an unguided projectile.
39
Steimes, J., and P. Hendrick. "Dimensional analysis of an integrated pump and de-aerator solution in more electric aero engine oil systems." Aeronautical Journal 121, no. 1240 (May 11, 2017): 803–20. http://dx.doi.org/10.1017/aer.2017.28.
Full textAbstract:
ABSTRACTAero-engine oil systems need to pump and de-aerate air-oil flows. Engine sub-components performing these tasks are undergoing important changes due to the development of more-electric engines. A new integrated pump and separation system that can be electrically entrained was developed and characterised experimentally to reduce footprint on the engine and increase reliability and performance. This prototype combines the pumping, de-aeration and de-oiling function of the scavenge part of oil systems. Previous works have failed to address in-flight performance of the prototype. To address this need, a dimensional analysis of the Pump and Separation System that allows in-flight performance prediction is proposed in this paper. This model is used to assess different prototype sizes and the influence of a more-electric engine. This analysis illustrates that by switching to an electric entrainment, the footprint of the Pump and Separation system on the engine is reduced by 34%, and de-aeration performances are improved by 55% at maximum take-off and 17% in cruise phase. This study opens the way for a more accurate design of the prototypes based on engine requirements.
40
Polovinchuk, N. Y., S. V. Ivanov, M. Y. Zhukova, and D. G. Belonozhko. "Method of terminal control in ascent segment of unmanned aerial vehicle with ballistic phase." Vestnik of Don State Technical University 19, no. 1 (April 1, 2019): 93–100. http://dx.doi.org/10.23947/1992-5980-2019-19-1-93-100.
Full textAbstract:
Introduction. The solution to the problem on the centroidal motion control synthesis (guidance problem) of an unmanned aerial vehicle (UAV) with long-range capabilities in the boost phase is considered. Control condition requires optimum fuel consumption. The principle of dynamic programming considering the restrictions to the vector modulus of the thrust output is used to solve the problem. The implementation of terminal guidance requires the formation of control as a function of the object state at the end of the ascent phase. The attainment of these boundary conditions determines the further transition to the ballistic flight phase.Materials and Methods. Bellman’s principle of dynamic programming is the most reasonable from the point of view of the implementability of the computationally efficient on-board algorithms and the solution to the problems in the form of synthesis. With natural scarcity of thrust and energy resources on board, this principle enables to obtain solutions free from the switching functions. In this case, the optimal control is a smooth function (without derivative discontinuity) of the current and final parameters of the UAV.Research Results. A new algorithmic method for the synthesis of terminal motion control is developed. Its difference is that the UAV movement control in the ascent phase is formed by the function of the motion actual and terminal parameters. This ensures movement along an energetically optimal trajectory into the given region of space. The problem solution results enable to build closed terminal guidance algorithms for the boost phase of the UAV trajectory with long-range capabilities. Such algorithms have good convergence and injection accuracy due to the prediction of parameters during the flight at a shorter time interval.Discussion and Conclusions. The most preferred is the principle of dynamic programming. It should be used when solving the problem on the centroidal motion control synthesis (guidance problem) of the UAV with long-range capabilities in the boost phase.
41
Pogorzelski, G., and F. J. Silvestre. "Autonomous soaring using a simplified MPC approach." Aeronautical Journal 123, no. 1268 (March 15, 2019): 1666–700. http://dx.doi.org/10.1017/aer.2019.6.
Full textAbstract:
ABSTRACTThe need for efficient propulsion systems allied to increasingly more challenging fixed-wing UAV mission requirements has led to recent research on the autonomous thermal soaring field with promising results. As part of that effort, the feasibility and advantages of model predictive control (MPC)-based guidance and control algorithms capable of extracting energy from natural occurring updrafts have already been demonstrated numerically. However, given the nature of the dominant atmospheric phenomena and the amplitude of the required manoeuvres, a non-linear optimal control problem results. Depending on the adopted prediction horizon length, it may be of large order, leading to implementation and real-time operation difficulties. Knowing that, an alternative MPC-based autonomous thermal soaring controller is presented herein. It is designed to yield a simple and small non-linear programming problem to be solved online. In order to accomplish that, linear prediction schemes are employed to impose the differential constraints, thus no extra variables are added to the problem and only linear bound restrictions result. For capturing the governing non-linear effects during the climb phase, a simplified representation of the aircraft kinematics with quasi-steady corrections is used by the controller internal model. Flight simulation results using a 3 degree-of-freedom model subjected to a randomly generated time varying thermal environment show that the aircraft is able to locate and exploit updrafts, suggesting that the proposed algorithm is a feasible MPC strategy to be employed in a practical application.
42
Fu, Chen-Zhao, Wen-Rong Si, Ke-Ke Fang, and Jian Yang. "Heat Transfer Simulation and Temperature Rapid Prediction for Trench Laying Cable." Mathematical Problems in Engineering 2021 (October 29, 2021): 1–18. http://dx.doi.org/10.1155/2021/9271283.
Full textAbstract:
Heat transfer process for trench laying cable is complex. To guarantee safe operation of the cable, it is necessary to predict the temperature and maximum current capacity of trench laying cable rapidly and accurately. Therefore, in this study, an adaptive optimized particle swarm optimization algorithm (LFVPSO) is proposed based on Levy flight algorithm, and it is used to modify the back propagation neural network algorithm (LFVPSO-BPNN). Then, combined with numerical simulations, a network algorithm for temperature prediction of trench laying cable is developed using LFVPSO-BPNN. Finally, the maximum current capacity of four-loop three-phase trench laying cable is calculated using LFVPSO-BPNN together with genetic algorithm (GA&LFVPSO-BPNN). At first, it is found that the LFVPSO-BPNN algorithm proposed in this study is reliable and accurate to predict the cable maximum temperature for different loops (Tmax,i) in the trench. Furthermore, as compared with other similar algorithms, when LFVPSO-BPNN algorithm is used to predict the temperature of trench laying cable, its computation time would be reduced and the prediction accuracy would be improved as well. Second, it is revealed that the effect of ground air temperature (Tsur) on the maximum current capacity of trench laying cable (It,max) is remarkable. As Tsur increases, the It,max for both flat-type and trefoil-type trench laying cable would significantly decrease. In addition, with the same Tsur, the It,max for the flat-type trench laying cable are obviously higher.
43
Rodríguez, José-Víctor, Ignacio Rodríguez-Rodríguez, and Wai Lok Woo. "Machine Learning-based Prediction of Sunspots using Fourier Transform Analysis of the Time Series." Publications of the Astronomical Society of the Pacific 134, no. 1042 (December 1, 2022): 124201. http://dx.doi.org/10.1088/1538-3873/aca4a3.
Full textAbstract:
Abstract The study of solar activity holds special importance since the changes in our star’s behavior affect both the Earth’s atmosphere and the conditions of the interplanetary environment. They can interfere with air navigation, space flight, satellites, radar, high-frequency communications, and overhead power lines, and can even negatively influence human health. We present here a machine learning-based prediction of the evolution of the current sunspot cycle (solar cycle 25). First, we analyze the Fourier Transform of the total time series (from 1749 to 2022) to find periodicities with which to lag this series and then add attributes (predictors) to the forecasting models to obtain the most accurate result possible. Consequently, we build a trained model of the series considering different starting points (from 1749 to 1940, with 1 yr steps), applying Random Forests, Support Vector Machines, Gaussian Processes, and Linear Regression. We find that the model with the lowest error in the test phase (cycle 24) arises with Random Forest and with 1915 as the start year of the time series (yielding a Root Mean Squared Error of 9.59 sunspots). Finally, for cycle 25 this model predicts that the maximum number of sunspots (90) will occur in 2025 March.
44
Li, Boxin, Boyang Liu, Dapeng Han, and Zhaokui Wang. "Autonomous Tracking of ShenZhou Reentry Capsules Based on Heterogeneous UAV Swarms." Drones 7, no. 1 (December 27, 2022): 20. http://dx.doi.org/10.3390/drones7010020.
Full textAbstract:
The safe landing and rapid recovery of the reentry capsules are very important to manned spacecraft missions. A variety of uncertain factors, such as flight control accuracy and wind speed, lead to a low orbit prediction accuracy and a large landing range of reentry capsules. It is necessary to realize the autonomous tracking and continuous video observation of the reentry capsule during the low-altitude phase. Aiming at the Shenzhou return capsule landing mission, the paper proposes a new approach for the autonomous tracking of Shenzhou reentry capsules based on video detection and heterogeneous UAV swarms. A multi-scale video target detection algorithm based on deep learning is developed to recognize the reentry capsules and obtain positioning data. A self-organizing control method based on virtual potential field is proposed to realize the cooperative flight of UAV swarms. A hardware-in-the-loop simulation system is established to verify the method. The results show that the reentry capsule can be detected in four different states, and the detection accuracy rate of the capsule with parachute is 99.5%. The UAV swarm effectively achieved autonomous tracking for the Shenzhou reentry capsule based on the position obtained by video detection. This is of great significance in the real-time searching of reentry capsules and the guaranteeing of astronauts’ safety.
45
Chou, Chih-Chun, Paul J. Kushner, Stéphane Laroche, Zen Mariani, Peter Rodriguez, Stella Melo, and Christopher G. Fletcher. "Validation of the Aeolus Level-2B wind product over Northern Canada and the Arctic." Atmospheric Measurement Techniques 15, no. 15 (August 2, 2022): 4443–61. http://dx.doi.org/10.5194/amt-15-4443-2022.
Full textAbstract:
Abstract. In August 2018, the European Space Agency (ESA) launched the Aeolus satellite, whose Atmospheric LAser Doppler INstrument (ALADIN) is the first space-borne Doppler wind lidar to regularly measure vertical profiles of horizontal line-of-sight (HLOS) winds with global sampling. This mission is intended to assess improvement to numerical weather prediction provided by wind observations in regions poorly constrained by atmospheric mass, such as the tropics, but also, potentially, in polar regions such as the Arctic where direct wind observations are especially sparse. There remain gaps in the evaluation of the Aeolus products over the Arctic region, which is the focus of this contribution. Here, an assessment of the Aeolus Level-2B (L2B) wind product is carried out, progressing from specific locations in the Canadian North to the pan-Arctic. In particular, Aeolus data are compared to a limited sample of coincident ground-based Ka-band radar measurements at Iqaluit, Nunavut, to a larger set of coincident radiosonde measurements over the Canadian North, to Environment and Climate Change Canada (ECCC)'s short-range forecast, and to the reanalysis product, ERA5, from the European Centre for Medium-Range Weather Forecasts (ECMWF). Periods covered include the early phase of the first laser flight model (flight model A – FM-A; September to October 2018), the early phase of the second laser flight model (flight model B – FM-B; August to September 2019), and the middle phase of FM-B (December 2019 to January 2020). The adjusted r-squared between Aeolus and other local datasets is around 0.9 except for lower values for the comparison to the Ka-band radar, reflecting limited sampling opportunities with the radar data. This consistency is degraded by about 10 % for the Rayleigh winds in the summer due to solar background noise and other possible errors. Over the pan-Arctic, consistency, with correlation greater than 0.8, is found in the Mie channel from the planetary boundary layer to the lower stratosphere (near surface to 16 km a.g.l.) and in the Rayleigh channel from the troposphere to the stratosphere (2 to 25 km a.g.l.). In all three periods, Aeolus standard deviations are found to be 5 % to 40 % greater than those from ECCC-B and ERA5. We found that the L2B estimated error product for Aeolus is coherent with the differences between Aeolus and the other datasets and can be used as a guide for expected consistency. Our work shows that the high quality of the Aeolus dataset that has been demonstrated globally applies to the sparsely sampled Arctic region. It also demonstrates the lack of available independent wind measurements in the Canadian North, lending urgency to the need to augment the observing capacity in this region to ensure suitable calibration and validation of future space-borne Doppler wind lidar (DWL) missions.
46
Martiz, Alejandro, Zoltán Károly, Eszter Bódis, Péter Fazekas, Miklós Mohai, Imre Bertóti, and Anna Mária Keszler. "In-flight Synthesis of Nanosized ZrC Particles from Various Precursors in RF Thermal Plasma." Periodica Polytechnica Chemical Engineering 65, no. 3 (January 28, 2021): 331–42. http://dx.doi.org/10.3311/ppch.16574.
Full textAbstract:
Synthesis of zirconium carbide (ZrC) powder was investigated applying a non-conventional atmospheric radiofrequency (RF) thermal plasma process. In one case, zirconium dioxide (ZrO2) was reacted with solid carbon or with methane with varying molar ratio. In the other, zirconium-propoxide (NZP), containing both constituents, was thermally decomposed in the Ar plasma.
Temperature-dependent thermodynamic analysis was performed in the 500-5500 K temperature range to estimate the formation of possible equilibrium products for each reaction stoichiometry. Broad temperature range exists for the stability of solid ZrC for each explored reaction system. In accordance with this prediction, X-ray diffraction studies detected the ZrC as the major phase in all the prepared powders. The yield of particular runs ranged from 39 % to 98 %. Practically, full conversion was typical for the case of NZP precursor, however only partial conversion could be detected in ZrO2 reactions.
The average particle size of the powders falls between 10 nm and 100 nm depending on the type of the reaction systems (either calculated from the specific surface area or derived from broadening the XRD reflections). The transmission electron micrographs indicated mostly globular shape of the nanosize particles. Quantitative analysis of the surface of the powders by X-ray photoelectron spectroscopy revealed the presence of oxygen and carbon. Evaluating the spectra of the powders prepared from NZP, and taking in the account its spherical shape, a ZrC core covered by a very thin (≈1.0 nm) ZrO2 layer may be accounted for the measured oxygen and a thicker carbonaceous layer.
47
Calderon, Raul, Bertrand Aupoix, Benoit Calmels, and Christophe David. "Modelling Aerodynamics Unsteady Loads on the Horizontal Tail Plane of a Civil Aircraft." Applied Mechanics and Materials 232 (November 2012): 543–47. http://dx.doi.org/10.4028/www.scientific.net/amm.232.543.
Full textAbstract:
During flight, emergency descent situations are part of those extreme conditions that can lead the empennage of an aircraft to vibrate. These vibrations are mainly due to the separated flow on the upper surface of the structure which increases the pressure fluctuations on the empennage, sometimes leading to buffeting. This situation can cause structural fatigue and can induce certification and design constraints on the structure. Hence, an accurate prediction of the unsteady loads is needed to take these forces into account in the early phase of the empennage design. This paper presents a new approach to accurately model the unsteady aerodynamic loads resulting from the interaction between the horizontal tail plane and the wing wake. The method is based upon the coherence method and is compared to the method developed by Soumillon [2], based upon the correlation method. The results obtained by this new model show good agreements with the experimental data.
48
Darby, Lisa S., and Gregory S. Poulos. "The Evolution of Lee-Wave–Rotor Activity in the Lee of Pike’s Peak under the Influence of a Cold Frontal Passage: Implications for Aircraft Safety." Monthly Weather Review 134, no. 10 (October 1, 2006): 2857–76. http://dx.doi.org/10.1175/mwr3208.1.
Full textAbstract:
Abstract A lee-wave–rotor system interacting with an approaching cold front in the lee of Pike’s Peak near Colorado Springs, Colorado, on 1 April 1997 is studied observationally and numerically. Dynamical effects associated with the approaching cold front caused the amplification of the evolving lee wave and rotor, creating increasingly more hazardous flight conditions for nearby airports. The rapidly evolving winds measured by a Doppler lidar and 915-MHz wind profilers, and simulated by the Regional Atmospheric Modeling System (RAMS), produced light-to-moderate turbulence for a research aircraft making missed approaches at the Colorado Springs Airport during the wave amplification phase. As the cold front approached the foothills, the lee-wave–rotor system ended abruptly, reducing hazardous flight conditions. The Doppler lidar’s detailed measurements of the lee-wave–rotor system allowed for an evaluation of RAMS ability to capture these complex wind features. Qualitative and quantitative comparisons between the lidar range–height measurements and model x–z cross sections are presented. In a broad sense, the numerical simulations were successful in the prediction of the prefrontal amplification and the postfrontal decay of the waves as measured by the lidar. RAMS also predicted observed wind reversals above the lee waves, which were indicators of breaking wave instability. At times RAMS performed poorly by over- or underpredicting the wind speeds in the lee wave, as well as the horizontal extent of the lee wave or rotor.
49
Khan, Muhammad Kamran, Muhammad Hamza Zafar, Saad Rashid, Majad Mansoor, Syed Kumayl Raza Moosavi, and Filippo Sanfilippo. "Improved Reptile Search Optimization Algorithm: Application on Regression and Classification Problems." Applied Sciences 13, no. 2 (January 10, 2023): 945. http://dx.doi.org/10.3390/app13020945.
Full textAbstract:
The reptile search algorithm is a newly developed optimization technique that can efficiently solve various optimization problems. However, while solving high-dimensional nonconvex optimization problems, the reptile search algorithm retains some drawbacks, such as slow convergence speed, high computational complexity, and local minima trapping. Therefore, an improved reptile search algorithm (IRSA) based on a sine cosine algorithm and Levy flight is proposed in this work. The modified sine cosine algorithm with enhanced global search capabilities avoids local minima trapping by conducting a full-scale search of the solution space, and the Levy flight operator with a jump size control factor increases the exploitation capabilities of the search agents. The enhanced algorithm was applied to a set of 23 well-known test functions. Additionally, statistical analysis was performed by considering 30 runs for various performance measures like best, worse, average values, and standard deviation. The statistical results showed that the improved reptile search algorithm gives a fast convergence speed, low time complexity, and efficient global search. For further verification, improved reptile search algorithm results were compared with the RSA and various state-of-the-art metaheuristic techniques. In the second phase of the paper, we used the IRSA to train hyperparameters such as weight and biases for a multi-layer perceptron neural network and a smoothing parameter (σ) for a radial basis function neural network. To validate the effectiveness of training, the improved reptile search algorithm trained multi-layer perceptron neural network classifier was tested on various challenging, real-world classification problems. Furthermore, as a second application, the IRSA-trained RBFNN regression model was used for day-ahead wind and solar power forecasting. Experimental results clearly demonstrated the superior classification and prediction capabilities of the proposed hybrid model. Qualitative, quantitative, comparative, statistical, and complexity analysis revealed improved global exploration, high efficiency, high convergence speed, high prediction accuracy, and low time complexity in the proposed technique.
50
Lopes, Guido R., Sílvia Petronilho, Andreia S. Ferreira, Mariana Pinto, Claúdia P. Passos, Elisabete Coelho, Carla Rodrigues, Cláudia Figueira, Sílvia M. Rocha, and Manuel A. Coimbra. "Insights on Single-Dose Espresso Coffee Capsules’ Volatile Profile: From Ground Powder Volatiles to Prediction of Espresso Brew Aroma Properties." Foods 10, no. 10 (October 19, 2021): 2508. http://dx.doi.org/10.3390/foods10102508.
Full textAbstract:
Single-dose coffee capsules have revolutionized the coffee market, fueling espresso coffee popularity and offering access to a wide selection of coffee blends. Nevertheless, scarce information related to coffee powder and brew’s combined volatile characterization is available. In this study, it is hypothesized that coffee brew aroma characteristics can be predicted based on coffee powder’s volatile composition. For this, headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry detection (GC × GC-ToFMS) was used. The data were combined via chemometric tools to characterize in depth the volatile composition of eight blends of capsule-coffee powder and respective espresso brews, simulating the consumer’s perception. A total of 390 volatile compounds were putatively identified, 100 reported for the first time in roasted coffee or brews. Although the same chemical families were determined among the coffee powders and espresso brews, a different volatile profile was determined for each matrix. The Pearson correlation of coffee powders and respective brews allowed to identify 15 volatile compounds, mainly terpenic and esters recognized by their pleasant notes, with a strong relationship between the amounts present in both matrices. These compounds can be key markers to predict the volatile aroma potential of an espresso brew when analyzing the coffee powder.