Propulsion Model Research Articles

Nonlinear Aero-Propulsive Modeling for Fixed-Wing eVTOL UAV from Flight Test Data

This paper presents a methodology for constructing an aero-propulsive system identification model for a fixed-wing propeller-driven aircraft with limited flight data. Developing a flight dynamics model is an iterative process involving costly and time-consuming flight testing to collect relevant data. To maximize the utilization of available data, this study employs a time-domain system identification procedure on flight data from various maneuvers and flights. The methodology incorporates multivariate orthogonal functions to capture the nonlinear terms representing the coupled effects of the propeller and airframe dynamics. A stepwise regression is then employed to identify the most pertinent model parameters. Estimation of variables associated with the propulsive contribution is accomplished through an electrical propulsive model, identified using command and battery data from static thrust and flight tests. Aero-propulsive derivatives are determined using the output-error method, where the accuracy is assessed based on a colored noise correction. To validate the predictability of the flight dynamics model, out-of-sample data are employed. The construction of the electrical propulsive model and identification of aerodynamic derivatives from flight data were specifically carried out for a particular eVTOL flight test vehicle; however, the techniques employed are generalizable and applicable to other aircraft models.

Integration of the exploding foil initiator with capacitor discharge unit and its performance characterization

This study presents a novel integrated exploding foil initiator system (EFIs), consisting of a planar switch, an EFI chip, and a capacitor. Additionally, we propose an evaluation method for integrated EFIs that combines numerical simulations with experimental testing, enabling a thorough assessment of their performance. Under test conditions of 900 V/0.22 μF, the EFI demonstrated an inductance of 10.2 nH and a resistance of 107.5 mΩ, measured via the sampling resistance method. The operational behavior of the EFIs was analyzed through a two-dimensional metal electrical explosion model and a one-dimensional flyer propulsion model, with the results compared to experimental data. Results indicated that under 900–1200 V/0.22 μF, the deviations between measured and calculated values for electrical explosion performance and flyer velocity were both within 5 %, validating the accuracy of the evaluation approach. Firing tests further confirmed that the EFIs successfully detonated HNS-IV at 1000 V/0.22 μF.

Modeling the hundreds-of-nanoseconds-long irradiation of tin droplets with a 2 µm-wavelength laser for future EUV lithography

Abstract The properties of an extreme ultraviolet (EUV) source driven by hundreds-of-nanoseconds-long laser pulses of λ laser = 2 µm wavelength are investigated through radiation-hydrodynamic simulations. We show that single-pulse irradiation of 30 µm-diameter tin droplets can generate in-band energies ∼ 30 mJ directed in the 2π sr solid angle subtended by the collector mirror, yielding energies ∼100 mJ produced from 45 µm-diameter droplets. Time-integrated in-band EUV emission profiles, generated by taking Abel transforms of the local net in-band emissivity, reveal EUV source sizes in the axial (laser) direction × radial direction of ∼600 (1000) × 100 (150) µm2 for 30 (45) µm-diameter droplets. We find that approximately 74% of the total in-band emission is produced during the first half of the total propulsion distance irrespective of droplet size or laser intensity. Furthermore, we propose a one-dimensional analytical propulsion model to qualitatively explain the simulated droplet trajectory and to predict the time taken for the droplet to vaporize. These findings offer motivation for the development of high-power EUV sources based on single-pulse, hundreds-of-nanoseconds-long irradiation of tin droplets.

Multidisciplinary design optimization of an autonomous underwater vehicles based on random uncertainty

Herein, discipline decomposition was performed for an autonomous underwater vehicle (AUV) based on multidisciplinary design optimization (MDO), and its design parameters were determined. Parameterized analysis of the hull-form and structure disciplines was performed, and an approximate model of these disciplines was established with a high fitting accuracy. An analysis model of propulsion, energy, and system disciplines was developed based on the formula method. Based on collaborative optimization as well as discipline and system level models, a deterministic MDO framework for AUVs was established. Subsequently, an optimized solution was obtained. By considering the random uncertainty of design variables, an MDO framework for the uncertainty of AUVs was established and optimized solutions were obtained. The distribution of solutions obtained from uncertainty optimization was more concentrated and the distribution range was smaller than that obtained using deterministic optimization. Robustness analysis was performed on the initial scheme, typical deterministic optimization schemes, and typical uncertainty optimization schemes. Results showed that fluctuations in design variables may lead to constraints that exceed boundary conditions in the deterministic optimization design scheme. Using uncertainty and objective function optimization, the robustness of the overall scheme of AUVs was improved.

Ship propulsion shafting assembly detection: a model-data-driven approach

ABSTRACT The ship propulsion shafting assembly is one of the keys in building a ship power system, which directly affects the power performance and navigation safety. In this paper, a model-data-driven approach called semi-supervised domain-adversarial neural networks (SDANN) is proposed to solve the lack of actual training samples during ship propulsion shafting assembly. In terms of the model, a finite element model (FEM) for ship propulsion shafting considering misalignment is built in ANSYS. In terms of data, a ship propulsion shafting comprehensive test platform is set up in order to collect the actual data in the laboratory. Furthermore, a small amount of the unlabelled actual data is used to train semi-supervised networks, which can identify four different bearing elevations. The research results illustrate that the proposed method outperformed classical deep learning methods in the ship propulsion shafting assembly detection under three types of cases, with an average accuracy of 95.61% ± 0.45%.

Theoretical Investigation of Laser Ablation Propulsion Using Micro-Scale Fluid in Atmosphere

Laser ablation propulsion based on liquid propellants is a type of propulsion technology with a high specific impulse and good controllability that can be applied to space thrusters, gas metal arc welding, and extreme ultraviolet light. However, its basic mechanisms, such as flow evolution and thrust formation, have not yet been described in detail. In this study, the laser ablation of micro-scale fluid in the atmosphere was investigated. Flow evolution with different laser energy and fluid mass was observed using a schlieren system. According to the characteristic of flow evolution, a theoretical model of laser ablation propulsion in the atmosphere was established. For the first time, a theoretical hypothesis was proposed that the laser energy is divided into two parts, which act on fluid and air respectively. The model indicates that the impulses generated by fluids and air follow power laws with the laser energy, while the exponentials are 0.5 and 1, respectively. In the atmosphere, due to the shielding effect of a laser-maintained detonation wave on laser, the energy absorbed by the fluid is basically unchanged, while only the energy absorbed by the air changes. Significantly, the theoretical model is consistent with the impulse experiment and current studies.

Enhancing payload capacity to low earth orbit via a relay solution trajectory with laser-powered vehicles

ABSTRACT Low Earth Orbit (LEO) stands as the primary access point for deep space exploration endeavors, encompassing a variety of space missions such as communication satellites, Earth observation platforms, and scientific research missions. In light of the expanding scope of human activities in space, the cost associated with accessing LEO has emerged as a critical focal point for spacecraft designers. Within the spectrum of proposed solutions, laser-powered vehicle has emerged as a viable avenue toward achieving cost-effective launch options. In order to significantly augment the payload capacity of laser-powered launch vehicles destined for LEO, this study introduced a novel Relay Solution Trajectory Flight Scheme. Central to this scheme was the implementation of a relay mirror system affixed to a satellite, which served to stabilize the incident angle of the laser beam directed toward the laser-powered vehicle, thereby ensuring continuous alignment between the laser beam and the vehicle’s axis throughout the duration of the flight. Following the development of comprehensive structural, propulsive, aerodynamic, and trajectory models tailored for the laser-powered vehicle, an optimization of its flight trajectory was conducted, comparing this innovative strategy with two conventional flight strategies. The outcomes of this analysis showcased a notable enhancement of 269.29% in payload capacity compared to conventional strategies that lacked a relay satellite system, within a designated 400 km LEO flight scenario. This endeavor underscored the transformative potential of advanced relay systems in reshaping payload delivery mechanisms and elevating mission feasibility levels, notwithstanding the intricate coordination challenges posed by intricate satellite systems.

Equilibrium state of axially symmetric electric solar wind sail at arbitrary sail angles

This paper studies the equilibrium state and trajectory dynamics of an axially symmetric Electric solar wind sail (E-sail) at arbitrary sail angles. The E-sail is assumed operating in a heliocentric-ecliptic orbit at approximately one astronomic unit (au) from the Sun, and experiencing various dynamic disturbances like solar wind pressure, tether tension oscillations, and centrifugal forces. The study derives analytical expressions for the E-sail’s equilibrium state and its maximal coning angle under small coning angle assumption. Subsequently, an improved propulsion model is developed for the E-sail in this equilibrium state. To assess the precision of these formulations, a high-fidelity E-sail dynamic model is constructed using the nodal position finite element method, where the tethers are modeled as two-noded tensile elements and the central spacecraft and remote units are simplified as lumped masses. Through thorough parametric analyses, this paper conclusively demonstrates that the operation of the E-sail at the equilibrium state can be achieved in accordance with the derived analytical prediction of the equilibrium state. Furthermore, the improved propulsion model is employed in trajectory analyses for a mission to reach the solar system’s boundary. The study provides valuable insights and findings and foundation for the practical application and further advancement of the E-sail technology.

Corrigendum: Coupling plasma physics and chemistry in the PIC model of electric propulsion: application to an air-breathing, low-power Hall thruster

Corrigendum: Coupling plasma physics and chemistry in the PIC model of electric propulsion: application to an air-breathing, low-power Hall thruster

Extended state observer-based continuous finite time control for a fixed-wing vertical take-off and landing unmanned aerial vehicle

Dual system Vertical Take-Off and Landing (VTOL) fixed-wing Unmanned Aerial Vehicles (UAVs) combine the advantages of both the rotorcraft and fixed-wing UAV, characterizing horizontal and vertical flight capabilities. However, they face challenges such as aerodynamic coupling between propulsion systems, model uncertainty, and external disturbances, significantly deteriorating the tracking accuracy and robustness. This paper proposes an Extended State Observer based Continuous Finite-Time Control (ESO-CFTC) scheme to solve the attitude and trajectory tracking problem of such a VTOL fixed-wing UAV. Initially, the Nonsingular Fast Terminal Sliding Mode (NFTSM) controller guarantees the tracking errors reach a prescribed manifold in finite time with a continuous reaching law, then converge to the origin in finite time while avoiding singularities. To suppress the inherent chattering problem of the sliding mode control, an ESO technique is incorporated into the ESO-CFTC scheme, which is completely decoupled with the basic NFTSM controller. The supremum of the estimation residual set is derivated theoretically. The scheme forces the tracking errors to converge into the neighborhood of the origin in finite time without requiring prior knowledge of lumped disturbance supremum values. Finally, the numerical simulation results in a Matlab/Simulink environment demonstrate that the presented method outperforms existing benchmark in terms of disturbance estimation, tracking accuracy, convergence rate, and robustness.

Modelling the nonlinear system performance of hybrid-electric propulsion systems with aerothermodynamic interdependencies

The development of commercial aircraft with hybrid-electric propulsion systems is currently a subject of extensive research in order to improve local air quality and reduce combustion emissions. Among the various types of engines being studied, the two-spool parallel hybrid-electric turbofan engine is particularly challenging due to the low-pressure compressor (LPC). The hybridisation process tends to throttle the LPC, accentuating its significance in the propulsion system. For reliable operation of such systems, accurate predictions of the LPC performance during time-sensitive manoeuvres such as a go-around are important. These manoeuvres are heavily influenced by time-dependent effects that govern the propulsion system’s performance. Often, the aerothermodynamic interplay between these effects is overlooked in propulsion models. In this study, the influence of these aerothermodynamic interdependencies on the modelling results is investigated. To investigate these aerothermodynamic interactions, a dynamic model is developed to simulate the performance of the hybrid-electric turbofan engine. In comparison, a constant mass flow model is used, which is not able to simulate these interdependencies. The results show that the aerothermodynamic interdependencies significantly affect the modelled time-resolved performance, especially for surge margin of the LPC, with this effect becoming more pronounced at higher levels of hybridisation. Therefore, the study recommends the adoption of dynamic simulation methodologies for hybrid-electric engines to guarantee high simulation precision, enhance reliability, and satisfy safety standards.

Investigating Tailless UAV Flight Dynamics through Modeling, Simulation, and Flight Testing

Tailless Unmanned Aerial Vehicles (UAVs) offer several advantages over their conventional counterparts, including enhanced maneuverability, higher durability, and better stealth. However, they are challenging in their stability and control due to the absence of stabilizing and control surfaces that typically exist in conventional empennage. A crucial process for analyzing the tailless UAVs’ stability/performance characteristics and determining/validating their flight control parameters is done via the modeling and simulation of flight dynamics. This paper presents a comprehensive and systematic procedure for investigating the flight dynamics of a tailless UAV, including modeling, simulation, analytical verification, and flight testing, while also explaining the interconnections among these elements. It also addresses the common challenge of limited accessibility of UAV essential data through using diverse analytical, empirical, and experimental methods. First, a rapid and effective first-principles modeling approach is introduced to simulate the nonlinear six-degree-of-freedom flight dynamics of a small tailless UAV case study. The modeling process follows a modular framework where well-defined experiments and commercial of-the-shelf software, tools, and sensors are employed to build the necessary sub-models, including geometric, mass–inertia, aerodynamic, propulsion, and actuator models. Then, all sub-models are integrated into a simulation environment to allow the prediction of the UAV dynamic response obtained from the given control inputs. The developed flight dynamic model is subjected to a thorough verification process to ensure its integrity and proper functionality by comparing the simulated trim and natural flight modes with the calculated analytical results. Finally, a set of specific flight tests are performed to validate the developed simulation model and verify relevant performance characteristics for the case-study UAV. The results show that the proposed approach provides a systematic and straightforward method for examining the flight dynamics of small tailless UAVs with reasonable accuracy.

Towards Efficient Battery Electric Bus Operations: A Novel Energy Forecasting Framework

As the adoption of battery electric buses (BEBs) in public transportation systems grows, the need for precise energy consumption forecasting becomes increasingly important. Accurate predictions are essential for optimizing routes, charging schedules, and ensuring adequate operational range. This paper introduces an innovative forecasting methodology that combines a propulsion and auxiliary energy model with a novel concept, the environment generator. This approach addresses the primary challenge in electric bus energy forecasting: estimating future environmental conditions, such as weather, passenger load, and traffic patterns, which significantly impact energy demand. The environment generator plays a crucial role by providing the energy models with realistic input data. This study validates various models with different levels of model complexity against real-world operational data from a case study of over one year with 16 electric buses in Göttingen, Germany. Our analysis thoroughly examines influencing factors on energy consumption, like altitude, temperature, passenger load, and driving patterns. In order to comprehensively understand energy demands under varying operational conditions, the methodology integrates data-driven models and physical simulations into a modular and highly accurate energy predictor. The results demonstrate the effectiveness of our approach in providing more accurate energy consumption forecasts, which is essential for efficient electric bus fleet management. This research contributes to the growing body of knowledge in electric vehicle energy prediction and offers practical insights for transit authorities and operators in optimizing electric bus operations.

Neural Networks and Support Vector Regression for the CRJ-700 Longitudinal Dynamics Modeling

This paper presents a new methodology to identify the aerodynamic coefficients and predict the short-period and phugoid dynamics of an aircraft using two types of supervised learning models: artificial neural network (ANN), and support vector regression (SVR). The study was validated on the CRJ 700 regional jet. Simulated flight tests data were collected during various maneuvers performed on a Level D CRJ-700 Virtual Research Simulator (VRESIM) designed by CAE and Bombardier. Level D is the highest qualification for flight dynamics and propulsion models given by the FAA. Both ANN and SVR models were trained using the data collected from the VRESIM to develop multidimensional models capable of predicting the aerodynamic coefficients of the aircraft for any conditions in the flight envelope, defined by altitude, speed, weight, and center-of-gravity position. The choice of solvers and the optimization of hyperparameters are detailed for both types of models. These models were validated by comparing predicted flight parameters with experimental data obtained from the CRJ 700 Level D VRESIM considering the same pilot inputs. The results showed that both types of models (ANN and SVR) were able to reproduce with excellent accuracy the nonlinear behavior of the short-period and phugoid dynamics.

An experimental investigation of the dynamic response of a liquid metal jet subjected to nanosecond laser ablation

The dynamic response of a micrometer-sized gallium–indium (Ga-In) jet in nitrogen subjected to intense Neodymium-doped Yttrium Aluminum Garnet (Nd: YAG) laser pulses with energy ranging from 0.35 to 5.0 mJ per pulse is investigated experimentally. The rapid deformation of the jet was visualized using timed-delayed stroboscopic shadowgraphy. The laser pulse disrupts the jet to form a gap, and the length of the gap grows according to a logarithm relationship with respect to the dimensionless time normalized a characteristic timescale τ, which is determined by the pulse energy Ep. The ablation impulse bends and flattens the jet into a thin curved film that resembles a wind-blown sail. The area of the sail increases with t6/5Ep13/15, where t is time. The sail eventually breaks up into fine mist. Additionally, we found that the laser-blast-induced initial bending velocity of the jet could be predicted using the semi-empirical laser-ablated propulsion model for an In-Sn droplet of tens of micrometers.

Hypersonic vehicle terminal velocity improvement considering ramjet safety boundary constraint

The air-breathing ramjet is an essential power plant to improve the terminal velocity of hypersonic vehicles. The high-performance requirement of ramjet makes it operate close to the safety boundary, and the optimization of the terminal velocity of vehicle is faced with challenges. An integrated flight/ propulsion model considering thrust and safety performance is constructed, and the trajectory optimization method for the whole flight phase operating process of hypersonic vehicles with multiple performance optimization indicators and complex safety constraints is studied. Moreover, the trajectory optimization results of the whole flight phase for CAV-H and X-43A (powered/unpowered) plans are compared and analyzed, and the dive-acceleration-climb strategy can improve the maneuverability of the vehicle in the ramjet operating phase. Furthermore, the terminal flight velocity of the vehicle in the powered plan is increased from 363.60 m/s to 943.57 m/s under the effect of ramjet. In addition, the trajectory optimization results of vehicle with different geometrical configurations of the ramjet are compared under safety constraints. The results show that the variable geometry ramjet enables the vehicle to increase its terminal velocity by up to 9.73 % with respect to the fixed geometry engine. Hypersonic vehicle terminal velocity is effectively improved by considering ramjet variable geometry adjustment.

Plasma propulsion modeling with particle-based algorithms

This Perspective paper deals with an overview of particle-in-cell/Monte Carlo collision models applied to different plasma-propulsion configurations and scenarios, from electrostatic (E×B and pulsed arc) devices to electromagnetic (RF inductive, helicon, electron cyclotron resonance) thrusters, as well as plasma plumes and their interaction with the satellite. The most important items related to the modeling of plasma–wall interaction are also presented. Finally, the paper reports new progress in the particle-in-cell computational methodology, in particular, regarding accelerating computational techniques for multi-dimensional simulations and plasma chemistry Monte Carlo modules for molecular and alternative propellants.

Trajectory planning of stratospheric airship for station-keeping mission based on improved rapidly exploring random tree

The station-keeping mission is one of the common missions of stratospheric airships. Its movement is sensitive to wind due to the large size and low airspeed of stratospheric airships. When the wind speed exceeds the maximum airspeed of the airship, the airship may fly out of the given mission region. Therefore, station-keeping trajectory planning is a new trajectory planning problem that has never existed before. A rapidly exploring random tree algorithm for station-keeping(RRT-SK) is proposed to solve the trajectory planning problem under multiple constraints of the airship, and an artificial potential field method (APF) considering wind field and relative position is designed as the objective function of the RRT-SK algorithm, both of which form the RRT-SK strategy used for the stratospheric airship station-keeping trajectory planning under multiple constraints. A multidisciplinary model is developed to simulate multiple constraints on the airship flight, including the energy model, thermal model, propulsion model, and kinematic model. The performance of the RRT-SK strategy is demonstrated in this multidisciplinary model with real wind fields. The results show that the multi-constrained station-keeping problem can be solved by the RRT-SK strategy. Compared with the conventional strategy, the RRT-SK strategy can improve the success rate of the airship’s 24-h stationing flight and well cope with the impact of wind field changes and stationing area changes. Moreover, the RRT-SK strategy has better advantages in actual long-duration use.

Position and Attitude Tracking Control of a Biomimetic Underwater Vehicle via Deep Reinforcement Learning

This article addresses a deep reinforcement learning (DRL) control method of position and attitude tracking for a biomimetic underwater vehicle (BUV). The BUV is actuated by two biomimetic propulsors. Each propulsor has a thick and flexible fin, which is manipulated by 12 short fin rays and can undulate in multiple wave patterns for propulsion. To achieve position and attitude tracking control on the BUV, a periodic dynamics-reparameterized soft actor-critic (SAC) algorithm is proposed. In detail, the algorithm uses the DRL method of SAC to train the controller by interacting with a simulated BUV, which is based on the propulsion model of the undulatory fin. Considering that the simulated environment may be inaccurate when compared with the real environment, some specially designed tricks are proposed. Simulations and experiments are conducted to prove the effectiveness and robustness of the proposed controller.

Study on the turning and heading performance of ship in stern and beam waves

Based on the open-source code OpenFOAM, a hybrid method based on the fully nonlinear potential flow method (FNPT) and the viscous flow method, combined with the propulsion model of the propeller and rudder, is used to simulate the turning and zigzag maneuvering motion of a single-screw ship in stern and beam waves. The wave is generated by FNPT, and the 6DOF maneuvering motion in waves and the ship-wave interaction are simulated by the viscous flow method in the internal field. The force and moment of the propeller and rudder are obtained by the propulsion model to improve the computational efficiency. The KVLCC2 model is used as the object for numerical simulation, and the numerical method is validated by the self-propulsion tank test. The maneuvering motion of the ship at the designed speed in stern and beam waves is simulated, and the turning and heading performance of the ship in the stern and beam waves is studied and analyzed by changing the wavelength.