Take-off Aircraft Research Articles

Automation of conceptual design and modification of aircraft type unmanned aerial vehicles using multidisciplinary optimization and evolutionary algorithms. Part 1: Methods and models

This paper proposes a method for selecting rational parameters for large-size aircraft-type unmanned aerial vehicles at the initial design stages using an optimization algorithm of differential evolution and numerical mathematical modeling of aerodynamic problems. The method assumes implementation of weight and aerodynamic balance in the main flight modes, it can consider aircraft-type unmanned aerial vehicles with one or two lifting surfaces, applies parallel calculations, and automatically generates a three-dimensional geometric model of the aircraft appearance based on the optimization results. A method for accelerating by more than three times the process of solving the problem of optimizing aircraft takeoff weight parameters by introducing the target function into the set of design variables is proposed and demonstrated. The results of assessing the reliability of the mathematical models used for aerodynamics and the correct calculation of the target function are presented, taking into account various constraints. A comprehensive check of the operability and effectiveness of the method were considered by solving demonstration problems by optimizing more than ten main design parameters of the appearance of two existing heavy-class unmanned aerial vehicles with known characteristics from open sources. Examples of using the optimization results to modify prototypes are provided.

함재기 이·착함 시뮬레이션 시스템 개발 및 활용

함재기 이·착함 시뮬레이션 시스템 개발 및 활용

All-weather airport runway foreign object detection based on mixed attention

Foreign object detection on airport runways plays a vital role in the safe takeoff and landing of aircraft. However, the existing detection algorithms have the phenomenon of missed detection and false detection under different lighting and weather runway environments. Therefore, a YOLOv5 foreign object detection algorithm suitable for all-weather airport runway environment is proposed. Aiming at the problem of a certain degree of feature loss in the pooling process of the original network, a cross-stage local spatial pyramid pooling module is designed, which can adaptively extract deep feature semantic information and enhance the multi-scale representation ability of the network; a hybrid attention module is introduced in the feature fusion part, and the channel and spatial feature weights are redistributed to strengthen the feature difference between foreign objects and irrelevant background elements; in view of the fact that small foreign objects are difficult to identify and locate, resulting in missed detection, a multi-scale positioning loss function is designed, and the detection ability of small targets is improved by adding similarity measurement; the optimized training strategy is used to train the MS-FOD dataset. Experimental results show that the improved algorithm achieves 95.83%mAP and Recall, which are respectively improved 94.31% by and 15.69% compared with the original YOLOv5 3.68% , and the detection speed is 68 frames /s , which meets the needs of real-time foreign object detection. The effectiveness of the proposed algorithm for foreign object detection on airport runways is effectively verified.

Rapid and environmentally friendly reconstruction of airport runways under combined laser and liquid energy fields: Ushering a new era of low-carbon and efficient rubber removal in the aviation industry

When the aircraft takes off or lands, the tread rubber melts and adheres to the airport runway and its embedded ground lights, forming black pavement rubber marks, affecting the smoothness of the pavement, reducing the lighting degree and friction coefficient of the pavement, and directly affecting the safety of the aircraft take-off and landing. There are many shortcomings in the standard rubber removal methods. The multi-energy field composite laser cleaning technology comprehensively utilizes the laser field and auxiliary hydrodynamic field. It leverages the high-efficiency advantages of laser processing and avoids the shortcomings of its thermal energy surplus, achieving efficient, accurate, and green material removal. Based on this, this article presents for the first time the composite energy-field laser cleaning process mechanism and related performance of rubber mud layer from the surface of cement/asphalt runway and embedded grounding light cover (aluminum alloy)/light window (tempered glass). Pulse laser single energy-field cleaning is suitable for removing rubber marks from cement runways, grounding lamp covers, and light window surfaces. The cleaning mechanism is divided into two types based on the substrate: ablation and thermal stress peeling. Composite energy-field laser cleaning is suitable for removing rubber marks from asphalt runway surfaces, and the phase explosion of the liquid film is the cleaning mechanism. Under appropriate process parameters, laser cleaning can improve the runway's skid resistance, enhance the grounding light cover's corrosion resistance, and increase the grounding light window's transparency. This study can provide a reference for the laser cleaning behavior of different materials and solve the problem of rubber removal on international civil aviation airport pavement, promoting the construction of "safe, green, and smart" airports.

Numerical Simulation of the Unsteady Airwake of the Liaoning Carrier Based on the DDES Model Coupled with Overset Grid

The wake behind an aircraft carrier under heavy wind condition is a key concern in ship design. The Chinese Liaoning ship’s upturned bow and the island on the deck could cause serious flow separation in the landing and take-off area. The flow separation induces strong velocity gradients and intense pulsations in the flow field. In addition, the sway of the aircraft carrier caused by waves could also intensify the flow separation. The complex flow field poses a significant risk to the shipboard aircraft take-off and landing operation. Therefore, accurately predicting the wake of an aircraft carrier during wave action motion is of great interest for design optimization and recovery aircraft control. In this research, the aerodynamic around an aircraft carrier (i.e., Liaoning) was analyzed using the computational fluid dynamics technique. The validity of two turbulence models was verified through comparison with the existing data from the literature. The upturned bow take-off deck and the right-hand island were the main areas where flow separation occurred. Delayed detached eddy simulation (DDES), which combines the advantages of LES and RANS, was adopted to capture the full-scale spatial and temporal flow information. The DDES was also coupled with the overset grid to calculate the flow field characteristics under the effect of hull sway. The downwash area at 15° starboard wind became shorter when the hull was stationary, while the upwash area and turbulence intensity increased. The respective characteristics of the wake flow field in the stationary and swaying state of the ship were investigated, and the flow separation showed a clear periodic when the ship was swaying. Comprehensive analysis of the time-dependent flow characteristic of the approach line for fixed-wing naval aircraft is also presented.

Simultaneous optimization of design and takeoff trajectory for an eVTOL aircraft

When designing a vertical takeoff and landing (VTOL) aircraft, it is crucial to consider various operating conditions, including hover, wing-borne cruise, and transition. Takeoff transition and climb phases are critical for vehicle conceptual design because they drive the motor and battery sizing. However, these flight phases are often ignored or simplified in the conceptual design literature due to the complexity of transition dynamics. To address this limitation, we propose simultaneous optimization of VTOL aircraft conceptual design and takeoff trajectory. Simultaneous optimization incorporates the takeoff transition and climb flight dynamics into VTOL design optimization in a fully coupled manner. This paper presents the design-trajectory optimization of lift-plus-cruise and tailsitter UAVs for delivery missions. As a result, simultaneous optimization reduces total energy consumption by 7.4% compared to uncoupled optimization and by 4.8% from iterative sequential optimization in the lift-plus-cruise configuration. It also achieves a 29% energy reduction from uncoupled optimization in the tailsitter configuration. Incorporating takeoff trajectory optimization in UAV sizing enables accurate estimation of takeoff and climb energy, which avoids undersizing or oversizing the battery. Furthermore, simultaneous optimization trades the vehicle weight penalty for a more energy-efficient climb with early transition. These system-level trade-offs can only be captured by simultaneous optimization; they cannot be captured by uncoupled or iterative sequential optimization.

An investigation of superstructure length on bi-stable ship wake flow

The variation in the geometry of a ship model has the potential to eliminate the flow asymmetry in ship wake and improve its aerodynamic performance. This study investigates the impact of the length of superstructure on the wake flow bi-stability of the ship model using IDDES at Re = 8 × 104. Also, this article studied the effect of ship's funnel structure using two models, with and without funnel, on the wake flow asymmetry, providing smooth transition into the study of the length of superstructure. The result indicates that when the funnel is removed, the length of flow reattachment after separation at the hanger increases for the top step and decreases for the second step for the case with no funnel. The asymmetric flow at wake persists, however, the configuration is different, showing difference in flow state. When the length of the superstructure is reduced, the turbulence at the wake increases, the size of recirculation bubble at the flight deck and behind the stern reduces and the overall pressure area decreases significantly. Behind the stern, all three cases indicate an asymmetrical flow, however, compared to Case 1, the asymmetry at the flight deck in Case 2 is weak, while a symmetrical flow is achieved with Case 3. Consequently, this research proposes a novel approach to improving wake flow and ensure safe aircraft take-off and landing operations on the ship deck.

Model test on dynamic response of coral sand in island dredging airport under wave, tidal and aircraft landing load

The construction of an island airport on a coral reef will inevitably encounter wave, tidal and aircraft takeoff and landing loads. To study the dynamic response of the coral sand island airport under these loads, a 1:50 laboratory model test was conducted with Meiji Reef Airport as the engineering background. The model test studied the pore water pressure characteristics of the coral sand strata beneath the airport runway under wave loads with different wave heights, tidal loads with different tidal heights, and aircraft impact loads with different cyclic loading times. Additionally, the displacement characteristics of the coral sand strata beneath the airport runway under the aircraft impact loads with different cyclic loading times were also studied. The results show that the pore water pressure of coral sand strata under the airport runway decreases with the increasing offshore distance under the wave and tidal loads. The change of wave height has little influence on the pore water pressure of coral sand strata, while the change of tidal water level has a significant effect on it. As the number of aircraft impact load cycles increases, the cumulative excess pore pressure in the coral sand strata under the airport runway no longer increases and plastic deformation occurs. The research can provide a reference for the runway foundation treatment of the island airport under construction and planning.

Ionblox’s SiOx-Based, High-Energy, High-Power Li-Ion Battery for Performance Electric Vehicles and Electric Aviation

Demands on land-based, high-performance electric vehicles (EVs) and electric aviation, by means of electric conventional takeoff and landing aircraft (eCTOLs) and electric vertical takeoff and landing aircraft (eVTOLs) demand more on a secondary cell chemistry than ever before. There are many secondary cells on the market that offer energy density, power density, fast-charge capability, or cycle life, but few, if any other manufacturing-ready cells, offer a combination of all four. IONBLOX has solved this by pairing it’s patented, Pre-lithiated SiOx anode with a high nickel, NMC cathode to produce cells exceeding 330 wh/kg. Herein we describe the performance of our 32 Ah cell, featuring high-energy density, high-power density, extreme fast charge capability, and good cycle life, within a package that is already in production.In particular, challenges for the eVTOL market will be addressed, which require peak power demand on the cell at low state-of-charge, without reducing the energy density. Methods for characterizing cells for such high-power applications will be further explored. DCIR pulse characterization and more customized testing like usable energy testing, which is important for identifying the applicable energy density for high-power use cases, will be demonstrated. Additionally, extreme fast charge capability is described on our large format cells with 5 min charge to >60% total cell capacity, over 1000 cycles. This shows such a cell is up to the expectations of a consumer familiar with the timing of a standard gasoline pump. Contribution from the information presented herein demonstrates the state of Si-based anode chemistry and can serve as useful guidelines to the academic community as future technologies are pursued for similar applications Figure 1

Dynamic Takeoff and Landing Control for Multi-Rotor eVTOL Aircraft

Dynamic Takeoff and Landing Control for Multi-Rotor eVTOL Aircraft

Nenadzirana praktična analiza ponašanja aviona A320 i B738 provedena u međunarodnoj zračnoj luci Sultan Hasanuddin

The purpose of this research was to look at the behavior of two well-known commercial aircraft types in Indonesia (the A320 and the B738) during the take-off phase. This was done to provide new information in the field of aviation, particularly flight safety. Observations were made at Sultan Hasanuddin International Airport by observing aircraft ADS-B data, which defines the behavior of the flight pattern. This ADS-B data is the subject of data analysis, which will subsequently be taught to the machine (computer) so that it can recognize the pattern and construct clusters. The purpose of this study is to utilize unsupervised learning, specifically K-Means clustering, to categorize and identify patterns in unlabeled ADS-B data obtained from AERO-TRACK. To prepare the raw data and create a dataset, data analysis techniques were employed. The machine learning model generates three distinct clusters: cluster 1 represents aircraft take-off on two-thirds of the runway, cluster 2 represents aircraft take-off on the entire runway, and cluster 3 represents aircraft take-off on one-third of the runway. The elbow method is utilized to analyze and interpret the three clusters produced by the model. An interesting observation is that the B738 aircraft dominate in all three clusters, while the A320 aircraft dominate in clusters 1 and 3. Notably, in cluster 2, there is a significant number of commercial planes taking off, accounting for 145 out of 628 flights. Based on the observed data spanning 91 days (September 26 to December 26, 2022), there is a 23% probability of runway excursion (overshooting the runway) in this cluster. Additionally, the research reveals that A320 aircraft demonstrate a safe zone take-off rate of 87%, whereas the B738 aircraft demonstrate a rate of 70.5%. These findings, derived from the analysis of ADS-B data such as GPS-Altitude and Coordinate, are intended to serve as valuable knowledge for aviation authorities, aviation users, and other stakeholders in the aviation industry.

Fault diagnosis of landing gear retraction system with bond graph under uncertain conditions.

Given the lack of sufficient historical data for aircraft landing gear retractor systems, a model-based fault diagnosis approach is needed to overcome this data deficiency. Meanwhile, inherent uncertainties are inevitable in engineering practice, and it is a great challenge to construct a model that accurately reflects the complexity of the actual system under uncertain conditions. Due to the urgent need for reliable model-based diagnostic methods and the need to cope with inherent uncertainties, this paper proposes an improved fault diagnostic method aimed at increasing the diagnostic efficiency of the landing gear retractor system, a critical component in aircraft take-off and landing operations. Due to a lack of historical data, the model-based fault diagnosis method can solve the problem of lack of data. The proposed uncertainty method addresses the challenge of multiple sources of uncertainty by using subsystems to reduce complexity. Fault diagnosis is achieved by comparing residuals with thresholds derived from a diagnostic bond graph (DBG) model. To address the problem of limited fault data, we modeled and simulated the landing gear retractor system using AMESim®. In addition, the linear fractional transform (LFT) approach has been used to resolve parametric uncertainties, but is unable to resolve system structural uncertainties. Therefore, we also analyzed the comparative fault diagnosis results derived from the linear fractional transformation-DBG (LFT-DBG) and the subsystem-DBG approaches. The experimental results support the effectiveness of the subsystem approach in improving fault diagnosis accuracy and reliability, highlighting its potential as a viable diagnostic strategy in aerospace engineering applications.

Aircraft Takeoff and Landing Weight Estimation from Surveillance Data

Aircraft weight estimation is a common problem facing researchers working with aircraft surveillance data. Although knowledge of an aircraft’s weight and thrust is required for many types of analyses, such as those evaluating aircraft acoustic noise, fuel burn, and emissions, these parameters are typically not available from surveillance sources. Instead, researchers generally only have access to basic aircraft states: lateral position, groundspeed, and altitude. Therefore, methods for estimating the weight of aircraft from these basic states become necessary in cases where aircraft performance is a key component of the analysis. This paper introduces two weight estimation models: one for the estimation of aircraft takeoff weight from departure data, and another for the estimation of aircraft landing weight from arrival data. The models are mathematically simple but grounded in knowledge of aircraft certification, airline operations, and aircraft flight management system logic. The landing weight estimation model proposed is shown to have a mean absolute error equivalent to 2.66% of maximum takeoff weight and a standard deviation of 3.35% of maximum takeoff weight when validated using onboard data recordings from 240 Airbus A320 flights. Similarly, the proposed takeoff weight estimation model is shown to have a mean absolute error of 2.83% of the maximum takeoff weight and a standard deviation of 3.55% of the maximum takeoff weight when applied to the same validation dataset.

Design, assembly and testing of an upgraded aeroacoustics wind tunnel facility

The Aeroacoustics Laboratory in the Department of Aerospace Engineering at Penn State currently serves several areas of experimental research. Most notable in the laboratory is the Anechoic Chamber of which the Aeroacoustics Wind Tunnel is an integral part. In recent years the dominant areas of research have included model aircraft exhaust jets and model rotors for helicopter applications involving detailed noise experiments. In the jet noise area, the applications have included aircraft in both flyover and take-off configurations. In the flyover application the air flow surrounding the exhaust jet has a significant effect on the radiated noise and must be simulated to produce experimental results that will be most useful in preliminary design of noise suppression applications. The Aeroacoustics Wind Tunnel at Penn State serves the purpose for this simulation. During aircraft take-off, the aircraft airspeed is in a range exceeding 250 ft per second, or Mach number of over M = 0.22. In the years preceding 2022, the velocity of the free jet flow of the Penn State facility was limited to less than 200 ft/sec. This paper reports on a project to design upgrades to the existing wind tunnel to improve the test section flow velocity to values closer to the 250 ft/sec target. The approach began with a preliminary design of the return flow ducting to convert the open jet, open return wind tunnel to a closed return tunnel. The concept is to make use of the flow energy in the exhaust of the tunnel to boost the input energy to the inlet fan that drives the flow to the test section. An integral part of the preliminary design involved making use of an upgraded flow analysis computer code to predict the gain in test section velocity of the new facility. For the available horsepower of two fans in the facility, the configurations of the existing and upgraded wind tunnel were entered into this analysis code based on a quasi-one-dimensional formulation. The code included empirical data formulated to include the various shapes of the components of the tunnels. The relative flow velocities in each section used simple incompressible continuity to calculate all velocities in the component sections. The average dynamic pressure in each section is calculated from the flow (constant) density and the velocity squared. Each section had a non-dimensional pressure loss parameter calculated from empirical data (from the relevant literature). The basic code (using the Excel algorithms) was based on a predictor-corrector concept in which the calculation was initialized with the estimated velocity and pressure of the flow at the entrance to the test section. The loss in each following section is estimated to determine the loss in the total pressure and the cumulated loss compared to the gains made at the two fans in the circuit. The initial guess is adjusted based on the total pressure value at the end of the circuit. During the related experiments, measurements of the total and dynamic pressure were performed at several joints between sections and compared to the values predicted in the analysis code. Various settings of the horsepower of the drive fans were used and the results were compared to flow measurements for the tunnel configurations (predominantly for the open return and closed return tunnel setups available before and after the upgrade project.) Results of the analysis and experiments are presented and analyzed together with the remaining activities planned for the coming months.

Analysis of landing gear simplified modeling and simulation based on amesim

Aiming at the theoretical research of aircraft take-off and landing taxiing control characteristics and real-time interactive application scenarios, the simplified model modeling method of landing gear is studied. Through the reasonable simplification hypothesis of the landing gear pillar, a benchmarked, general, and pillar-type simplified model of the landing gear is formed. In the process of ground motion, based on the force analysis of aircraft taxiing, a six-degree-of-freedom mathematical model of ground taxiing is established. Based on the Amesim six-degree-of-freedom model, the aircraft is built, and the simulation test of aircraft taxiing turning and landing brake is carried out in combination with the simplified take-off and landing model. The results show that the general benchmarked pillar landing gear model formed in this paper is reasonable and feasible, and can quickly construct the aircraft landing gear model, which is convenient for subsequent optimization and design.

Investigation of the Internal Flow Characteristics of a Tiltrotor Aircraft Engine Inlet in a Gust Environment

In the vertical take-off and landing (VTOL) state of tiltrotor aircraft, the inlet entrance encounters the incoming airflow at a 90° attack angle, resulting in highly complex internal flow characteristics that are extremely susceptible to gusts. Meanwhile, the flow quality at the inlet exit directly affects the performance of the aircraft’s engine. This work made use of an unsteady numerical simulation method based on sliding meshes to investigate the internal flow characteristics of the inlet during the hover state of a typical tiltrotor aircraft and the effects of head-on gusts on the inlet’s aerodynamic characteristics. The results show that during the hover state, the tiltrotor aircraft inlet features three pairs of transverse vortices and one streamwise vortex at the aerodynamic interface plane (AIP). The transverse vortices generated due to the rotational motion of the air have the largest scale and exert the strongest influence on the inlet’s performance, which is characterized by pronounced unsteady features. Additionally, strong unsteady characteristics are present within the inlet. Head-on gusts mainly affect the mechanical energy and non-uniformity of the air sucked into the inlet by influencing the direction of the rotor’s induced slipstream, thereby impacting the performance of the inlet. The larger head-on gusts have beneficial effects on the performance of the inlet. When the gust velocity reaches 12 m/s, there is a 1.01% increase in the total pressure recovery (σ) of the inlet, a 25.72% decrease in the circumferential distortion index (DC60), and a reduction of 62.84% in the area where the swirl angle |α| exceeds 15°. Conversely, when the gust velocity of head-on gusts reaches 12 m/s in the opposite direction, the inlet’s total pressure recovery decreases by 1.13%, the circumferential distortion index increases by 14.57%, and the area where the swirl angle exceeds 15° increases by 69.59%, adversely affecting the performance of the inlet. Additionally, the presence of gusts alters the unsteady characteristics within the inlet.

Global Strong Winds Occurrence Characteristics and Climate Index Correlation

Guided by entering the deep sea and achieving deep marine development in marine construction, the factors hindering marine construction cannot be ignored. Strong ocean winds have a devastating impact on tasks such as ship navigation, carrier aircraft take-off and landing, naval operations and military exercises, and affect the planning of sea routes and the development of the long-distance sea. This paper uses ERA5 wind field data and key climate indices to conduct a systematic analysis of catastrophic winds in the global ocean using methods such as climate statistical analysis, the Theil–Sen trend method, Pearson correlation and contribution rate calculation. It points out the spatiotemporal distribution, variation trend, climate index correlation and contribution rate characteristics of strong winds occurrence (SWO) and hopes that the results of this study can serve as a guide for maritime route planning and provide technical assistance and decision-making support for marine development and other needs. The results show the following: The high global SWO occurs in the Southern Ocean, the North Atlantic, the North Pacific, near Taiwan, China, the Arabian Sea and other locations, with the strongest SWO in summer. The growth trend of SWO in the Southern Ocean is strongest, with decreasing regions near the Arabian Sea and the Bay of Bengal, and the growth trend is reflected in all four seasons. The climate indices with the strongest correlation and highest contribution to the global SWO are AAO (Antarctic Oscillation) and EP–NP (East Pacific–North Pacific pattern) with a correlation between −0.5 and 0.5 and a contribution rate of up to −50%~50%.

A long sequence time-series forecasting model for ship motion attitude based on informer

Influenced by marine environmental factors, a ship sailing at sea will experience six degrees of freedom oscillating motions. These oscillating motions pose safety risks to ship navigation and maritime operations. Especially in severe weather conditions, these oscillating motions have a significant impact on the takeoff and landing of carrier aircraft, as well as the launch of carrier missiles. Therefore, studying and forecasting the ship motion attitude in wind and waves holds immense significance. This paper presents a sparrow search algorithm (SSA) optimized Informer model based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to forecast the long sequence time-series of ship motion attitude. Firstly, the ship motion attitude time series, as measured by the inertial navigation system, is decomposed using CEEMDAN to obtain several intrinsic mode functions (IMFs) and a residual. Then, the IMFs and residual are fed into SSA-Informer, where SSA is used to optimize the hyperparameter of Informer. Finally, the forecast values of IMFs and residual are superimposed and reconstructed to get the ship motion attitude forecasting result. The forecasting experiment under slight, moderate and rough sea conditions in the East China Sea shows that the proposed model achieves better performance and longer forecasting time compared with other popular methods.

Small-Scale Foreign Object Debris Detection Using Deep Learning and Dual Light Modes

The intrusion of foreign objects on airport runways during aircraft takeoff and landing poses a significant safety threat to air transportation. Small-scale Foreign Object Debris (FOD) cannot be ruled out on time by traditional manual inspection, and there is also a potential risk of secondary foreign body intrusion. A deep-learning-based intelligent detection method is proposed to solve the problem of low accuracy and low efficiency of small-scale FOD detection. Firstly, a dual light camera system is utilized for the collection of FOD data. It generates a dual light FOD dataset containing both infrared and visible light images. Subsequently, a multi-attention mechanism and a bidirectional feature pyramid are integrated into the baseline network YOLOv5. This integration prioritizes the extraction of foreign object features and boosts the network’s ability to distinguish FOD from complex backgrounds. Additionally, it enhances the fusion of higher-level features to improve the representation of multi-scale objects. To ensure fast and accurate localization and recognition of targets, the Complete-IoU (CIoU) loss function is used to optimize the bounding boxes’ positions. The experimental results indicate that the proposed model achieves a detection speed of 36.3 frame/s, satisfying real-time detection requirements. The model also attains an average accuracy of 91.1%, which is 7.4% higher than the baseline network. Consequently, this paper verifies the effectiveness and practical utility of our algorithm for the detection of small-scale FOD targets.

Charging Demand Prediction: Small All-Electric Aircraft and Electric Vertical Takeoff and Landing Aircraft

Charging Demand Prediction: Small All-Electric Aircraft and Electric Vertical Takeoff and Landing Aircraft