Search Results (70)

Current research in commercial aviation is exploring numerous propulsion and aircraft technologies to mitigate its environmental impact. While purely hydrogen-powered aircraft face manifold challenges, combining hydrogen and conventional fuel may facilitate the introduction of hydrogen-based flight. This study dives into the conceptual design of a parallel-hybrid dual-fuel regional aircraft retrofit based on the D328eco. The assessed retrofit approach aims to extend airframe service life and reduce emissions by incorporating a novel propulsion system. By integrating high-temperature fuel cells (FCs) to assist conventional turboshaft engines, the powertrain reduces fuel consumption. Utilizing the Bauhaus Luftfahrt Aircraft Design Environment, various aircraft-level sensitivities and hybridization strategies were assessed. The fuel/payload ratio was identified as a key metric, and enabling FC support during diversion climb while minimizing that ratio shifted the corresponding hybridization degree from 20.3% to 37.2%. Retaining the reference turboshaft-engine for reduced retrofit development costs, a hybridization degree of 20.2% was attainable while the minimum allowable payload was carried aboard. Subsequent off-design mission analysis revealed a decrease in transport efficiency for reduced mission ranges, underlining the importance of market-tailored aircraft designs. The main studies were complemented by a higher-level emission and climate impact assessment to set the basis for more generalized retrofit statements. Full article

Heat exchanger integration is a key design consideration for engines adapted to run on hydrogen and requiring liquid hydrogen to be preheated prior to combustion. For a typical small turboshaft, a comparison is made of fuel heating via an intercooler, a recuperator, or both in combination. This steady-state, zero-dimensional thermodynamic assessment examines the overall performance effects of the heat exchanger installations, heat loads and setpoint temperatures. It shows that exhaust gas recuperation provides up to 15% SFC reduction relative to an engine using power offtake for fuel preconditioning, with an average reduction of 14% across the evaluated operating points. Fuel heating via an intercooler is constrained by off-design and low-temperature thermal management requirements, so it only gives modest SFC benefits and will reduce specific power unless the engine is substantially redesigned. Within the evaluated design space, the combined intercooled and recuperated arrangement does not provide the lowest SFC, but it offers a balanced heat load distribution that may help to mitigate the risk of local air-side icing in the heat exchangers. Unlike previous works that considered turbofan engine architectures, this study focuses on turboshaft and turbogenerator installations where shaft power objectives and operating constraints determine the relative merits of alternative heat exchanger integration strategies. It includes an assessment of potential effects on NOx emissions as well as SFC. The study provides guidance for preliminary design and sizing of heat exchangers for fuel thermal management, but analysis of transients in the cryogenic systems and detailed assessments of aircraft-level integration penalties will be specific to particular engine applications and are beyond the scope of the present study. Full article

This paper presents a thermodynamic analysis of free-turbine turboshaft engines, focusing on the quantitative distribution of turbine power and related energy parameters between the gas generator turbine and the free power turbine. The study is based on an analytical calculation model combining catalog specifications and validated experimental data, applied to a series of turboshaft engines from different manufacturers with similar free-turbine architectures and power classes ranging from approximately 960 kW to 2100 kW. The comparative analysis is conducted at take-off conditions for the engine series, while a detailed regime-dependent investigation from idle to take-off is performed for the TV2-117A reference engine. The results indicate that, at take-off, the gas generator turbine typically absorbs between 55% and 66% of the total turbine power to drive the compressor, whereas the free power turbine delivers the remaining 34% to 45% as usable shaft output. For all analyzed engines, the total actual specific enthalpy drop of the expansion process exceeds 98% of the available thermal potential, demonstrating efficient turbine energy utilization. Total turbine temperature drops are found to range between approximately 335 K and 565 K, depending on engine power class and cycle characteristics. In the case of the TV2-117A engine, the gas generator turbine power share decreases from about 75% at idle to roughly 65% at take-off, confirming a clear regime-dependent redistribution of expansion work. Thermal efficiency values at take-off vary between approximately 23% and 31% across the analyzed engine series. Unlike previous studies primarily focused on single-engine modeling or control strategies, this work introduces a unified and experimentally validated multi-engine thermodynamic framework that quantifies internal turbine power distribution patterns and provides transferable design-oriented benchmarks for free-turbine turboshaft engines. Full article

Exposure of propulsion gas turbines to inlet flow contaminated with dust, sand, or ash particulates can lead to a myriad of complex and interrelated damage modes that reduce engine operational life, increase maintenance costs, and pose a safety risk to passengers and hardware assets. Experimental and computational research is ongoing to better understand the fundamental physics underlying this phenomenon, but data from full-scale engine tests with particles are needed for anchoring and validation under fully representative conditions. In this study, compressor blade/particle interactions are investigated at field-relevant conditions using Rolls-Royce/Allison M250-C20C turboshaft engines in an instrumented engine test cell. A novel experimental dataset was produced, yielding a qualitative visualization of particle impact regions on blades and vanes of an on-engine full six-stage axial compressor at transonic tip speeds for two particle compositions and two inlet particle delivery configurations. This investigation contributes the first experimental dataset of its kind for a rotating frame at transonic blade tip speeds (nominal Mach 1.0). By comparing the resulting impact patterns produced in this work to those of fielded hardware, it is shown that for field-relevant high-Stokes number particle conditions at the first-stage rotor, particle/engine dynamics simplify significantly due to ballistic inertial particle behavior. In addition, the spatial distribution of particle concentration and particle velocities across the compressor inlet plane was found to have only minor effects on the resulting particle/blade impact patterns for the two dust injection configurations tested. Full article

The research aims to propose a basic parameter estimation method for high-speed vertical take-off and landing (HSVTOL) aircraft, balancing rotor and fixed-wing mode requirements. Flight profiles and performance indicators are defined based on mission phases, and maximum take-off weight is estimated using the fuel fraction method. A pre-estimation model for a turboshaft–turbofan variable cycle engine (TSFVCE) was established, and the conversion between thrust and power was conducted. Constraints related to different performance requirements were analyzed, and the relationship between the rotor and the wing was established, resulting in the generation of constraint diagrams for the selection of basic parameters. This method allows for the rapid and effective estimation of basic parameters, including maximum take-off weight, rotor disk loading, and wing loading. Two tiltrotor aircraft were analyzed using this method. The estimated results closely matched actual values, with errors within a reasonable range. These findings demonstrate the method’s reliability and provide a reference for HSVTOL conceptual design and engine power matching. Full article

The exhaust duct of aero-engine exhibits complex vibration response characteristics under the influence of temperature fields and vibration loads. Taking the non-axisymmetric exhaust duct of turboshaft engine as the object of study, a finite element model of the exhaust duct was established using three-dimensional finite element analysis methods to analyze the thermal modal and random vibration response characteristics under axial loading for large thin-walled non-axisymmetric exhaust ducts. The simulation analysis method was validated through thermal vibration experiments on the scaled model. In a thermal environment, the shape of the power spectral density curves for displacement and stress of the exhaust duct remains largely unchanged in the low-frequency range; however, the response frequencies exhibit a significant forward shift. When subjected to Y-axial loading, the amplitude of the X- and Z-direction displacement response at 1st order (12.96 Hz) and the stress response at 6th order (30.92 Hz) significantly increase. Random vibration loads excite multiple modes of the exhaust duct, with lower-order modes being more easily stimulated. When subjected to X- and Z-axial loading, 1st order (12.96 Hz) has the greatest impact on the X- and Z-direction displacement responses, while 2nd order (16.93 Hz) and 13th order (82.79 Hz) frequencies have the greatest impact on the displacement response in the Y-direction and equivalent stress response. When subjected to Y-axial loading, the 5th order (22.35 Hz) and 12th order (81.69 Hz) modes have the most significant effects on the displacement responses in the X, Y, and Z directions and equivalent stress responses. Attention to these orders is essential during the design process, along with implementing certain stiffness reinforcement measures to reduce response amplitudes. Full article

Aero-engine performance monitoring is a core component of the engine health management system and an important approach to enhancing flight safety and reliability. Meanwhile, to improve engine operation efficiency, control systems are evolving from traditional centralized architectures to distributed control architectures. To alleviate the negative impact of network uncertainties, this paper proposes a Distributed Adaptive Kalman Filter (DAKF), which resolves the estimation performance degradation of the classical Kalman Filter under network uncertainty by designing measurement reconstruction and buffer-based signal fusion strategies, expanding the engineering applicability of the Kalman Filter in distributed control architectures. Furthermore, a distributed hardware architecture was established based on the time-triggered protocol/class (TTP/C) bus protocol, communication programs between simulation nodes were developed, and the proposed DAKF algorithm was deployed in the hardware architecture for experimental validation. This study focuses on the steady-state operations of the turboshaft engine to investigate the performance of the proposed distributed Kalman Filter algorithm under network uncertainties. The results demonstrated the effectiveness of the proposed method, providing a basis for the engineering application of distributed performance monitoring methods. Full article

This article presents a method for researching processes in automatic control systems based on the operator approach for modelling the control object and the controller. Within the method framework, a system of equations has been developed that describes the relations between the control error, the reference and control action, the output coordinate and the controller and the control object operators. The traditional PI controller modification, including a switching function for adaptation to operating conditions, allows for the system’s effective control in real time. The controller optimization algorithm is based on a functional expression with weighting coefficients that take into account control errors and the control action. To train the neural network through implementing the proposed method, a multilayer architecture was used, including nonlinear activation functions and a dynamic training rate, which ensure high accuracy and accelerated convergence. The TV3-117 turboshaft engine was chosen as the research object, which allows the method to be demonstrated in practical applications in aviation technology. The experimental results showed a significant improvement in control characteristics, including a reduction in the gas-generator rotor speed parameter transient time to ≈1, which is two times faster than the traditional method, where the transient process reaches ≈0.5. The model achieved a maximum accuracy of 0.993 with 160 training epochs, minimizing the error function to 0.005. In comparison with similar approaches, the proposed method demonstrated better results in accuracy and training speed, which was confirmed by a reduction in the number of iterations by 1.36 times and an improvement in the mean square error by 1.86–6.02 times. Full article

Based on GJB 242A, a detailed experimental procedure for the sand and dust ingestion of a turboshaft engine was established. A specific type of turboshaft engine was used to conduct 54 h full-engine sand and dust ingestion experiments. This research studied the impact of sand and dust ingestion on the engine’s common operating line, power loss, specific fuel consumption, and gas turbine exhaust temperature, among other performance parameters. The experimental results indicate that under the same equivalent power conditions, the impact of short-term sand and dust ingestion on the engine’s common operating line is minimal; as the sand and dust ingestion time increases, the equivalent airflow decreases significantly, causing the engine’s common operating line to shift upward and the gas turbine exhaust temperature to rise, with the maximum increase reaching 27.9 °C. However, the impact of sand and dust ingestion on the gas turbine exhaust temperature at high power levels is relatively small. After completing the sand and dust ingestion test, the engine’s power loss at maximum continuous operation was approximately 11.33%, and the specific fuel consumption increased by about 6.05%. The power loss does not meet the requirement of being less than 10% as stipulated in GJB 242A. Based on the engine disassembly inspection results, subsequent improvement suggestions were proposed. The findings of this paper can provide a scientific and rational basis and reference for the sand and dust resistance design and sand ingestion testing of similar aero-engines. Full article

An effective neural network system for monitoring sensors in helicopter turboshaft engines has been developed based on a hybrid architecture combining LSTM and GRU. This system enables sequential data processing while ensuring high accuracy in anomaly detection. Using recurrent layers (LSTM/GRU) is critical for dependencies among data time series analysis and identification, facilitating key information retention from previous states. Modules such as SensorFailClean and SensorFailNorm implement adaptive discretization and quantisation techniques, enhancing the data input quality and contributing to more accurate predictions. The developed system demonstrated anomaly detection accuracy at 99.327% after 200 training epochs, with a reduction in loss from 2.5 to 0.5%, indicating stability in anomaly processing. A training algorithm incorporating temporal regularization and a combined optimization method (SGD with RMSProp) accelerated neural network convergence, reducing the training time to 4 min and 13 s while achieving an accuracy of 0.993. Comparisons with alternative methods indicate superior performance for the proposed approach across key metrics, including accuracy at 0.993 compared to 0.981 and 0.982. Computational experiments confirmed the presence of the highly correlated sensor and demonstrated the method’s effectiveness in fault detection, highlighting the system’s capability to minimize omissions. Full article

In this article, a fuzzy controller mathematical model synthesising method that uses cognitive computing and a genetic algorithm for automated tuning and adaptation to changing environmental conditions has been developed. The technique consists of 12 stages, including creating the control objects’ mathematical model and tuning the controller coefficients using classical methods. The research pays special attention to the error parameters and their derivative fuzzification, which simplifies the development of logical rules and helps increase the stability of the systems. The fuzzy controller parameters were tuned using a genetic algorithm in a computational experiment based on helicopter flight data. The results show an increase in the integral quality criterion from 85.36 to 98.19%, which confirms an increase in control efficiency by 12.83%. The fuzzy controller use made it possible to significantly improve the helicopter turboshaft engines’ gas-generator rotor speed control performance, reducing the first and second types of errors by 2.06…12.58 times compared to traditional methods. Full article

Servo systems are important actuators of aeroengines. The repetitive, reciprocating motion of the servo system leads to significant changes in its time delay and gain characteristics, and degradation increases the uncertainty of these changes. These characteristic variations may have an adverse effect on the dynamic performance of the aeroengine. Therefore, a neural network-based parameter estimation and a multi-loop neural network-based predictive control (ML-NNPC) method for aeroengine inlet guide vane (IGV) servo systems (SVS) were proposed. In this study, the time delay estimation of the servo system was treated as a classification problem, and an SE (squeeze-and-excitation)-GRU (gated recurrent unit) network was proposed to estimate the time delay by using the selected dynamic data of the servo system. The estimated delay was embedded into an online sequential extreme learning machine, and a nonlinear model predictive controller was designed to obtain an optimal control sequence. The compensation control loop was designed to reduce the impact of the model and delay mismatch problems of the control system. The proposed method was applied to the IGV SVS control of a turboshaft engine. The simulation results demonstrate that the time delay is estimated accurately and compensated effectively. Compared to the existing PI and PI with Smith predictor methods, the ML-NNPC method achieves better control performance in the control of both the SVS and the engine rotor speed system. The stability and robustness of the ML-NNPC also show superiority. The results verify the effectiveness of the proposed time delay estimation method and the ML-NNPC method. Full article

This article proposes a mathematical model for protecting helicopter turboshaft engines from surges, starting with fuel metering supply and maintaining stable compressor operation. The model includes several stages: first, fuel is supplied according to a specified program; second, an unstable compressor operation signal is determined based on the gas temperature in front of the compressor turbine and the gas generator rotor speed derivatives ratio; at the third stage, when the ratios’ threshold value is exceeded, fuel supply is stopped, and the ignition system is turned on. Then, the fuel supply is restored with reduced consumption, and the rotor speed is corrected, followed by a return to regular operation. The neural network model implementing this method consists of several layers, including derivatives calculation, comparison with the threshold, and correction of fuel consumption and rotor speed. The input data for the neural network are the gas temperature in front of the compressor turbine and the rotor speed. A compressor instability signal is generated if the temperature and rotor speed derivatives ratio exceed the threshold value, which leads to fuel consumption adjustment and rotor speed regulation by 28…32%. The backpropagation algorithm with hyperparameter optimization via Bayesian optimization was used to train the network. The computational experiments result with the TV3-117 turboshaft engine on a semi-naturalistic simulation stand showed that the proposed model effectively prevents compressor surge by stabilizing pressure, vibration, and gas temperature and reduces rotor speed by 29.7% under start-up conditions. Neural network quality metrics such as accuracy (0.995), precision (0.989), recall (1.0), and F1-score (0.995) indicate high efficiency of the proposed method. Full article

The transition to alternative electrical energy solutions for drone propulsion systems presents several challenges, particularly in managing noise. This noise, compounded by that from the propellers, can produce spectra that are either unpleasant to humans or detrimental to mission objectives. This study explores potential solutions to mitigate noise produced by a micro turboshaft engine, focusing on the solutions’ impact on weight, power output, and acoustic level. We propose two modular, scalable designs—one for the intake and one for the exhaust—based on well-known applications in cold and hot flows. These designs aim to operate effectively across the audible frequency spectrum and incorporate various Helmholtz resonator geometries, including combinations of different lengths, perforated metal sheet parameters, and cavity-filling materials, to enhance bandwidth and noise reduction. Experimental results indicate that these designs can achieve tonal noise reductions of up to 40 dB. While the results are promising, further analysis is required to evaluate the practical applicability and comprehensive impact of these solutions on drone performance. Full article

This article presents a detailed approach to constructing a numerical model of a free power turbine engine specifically designed for performance analysis in the Matlab R2024b environment. The core innovation of this model lies in its integration of precise engine geometry parameters, calculated at the design point, and performance characteristics of key components such as the compressor and power turbine. These components are modeled to reflect significant variations in their performance based on changing operational conditions, including rotor speed and environmental factors. To validate the model’s assumptions, data from the PZL-3W engine were used. The model was created by meticulously incorporating the engine’s specific design characteristics, allowing for an in-depth examination of how performance characteristics shift with adjustments to high-pressure rotor settings or changes in ambient conditions. The resulting calculations demonstrated a high level of agreement between the model’s output and empirical data available for the PZL-3W engine, as well as with data found in the relevant scientific literature. This alignment underscores the model’s robustness and reliability in simulating engine performance across a range of operating scenarios, making it a valuable tool for further engineering analyses and optimization of free power turbine engines and their possible application. Full article