Engineering Model Research Articles

Model-Assisted Probabilistic Neural Networks for Effective Turbofan Fault Diagnosis

A diagnostic method for gas-path faults of turbofan engines, relying on a Probabilistic Neural Network (PNN) coupled with a thermodynamic model of the engine, is presented. The novel aspect of the method is that its training information is generated dynamically by an accompanying Engine Performance Model. In the proposed approach, the PNN efficiently addresses the first step of a diagnostic process (i.e., detection of the faulty component at the current operating point), while with the aid of an adaptive engine model, the fault is then further isolated and identified. A description of the proposed method and training aspects of the PNN are presented. The method is applied to the case of a mixed-flow turbofan engine to diagnose common gas-path faults in compressors and turbines (i.e., fouling, FOD, erosion, and tip clearance). Its performance is evaluated using realistic fault data that may be acquired at various operating conditions within a flight envelope.

Experimental Determination of a Mixture Composed of Camisea Natural Gas and CO2 Laminar Burning Velocity

The aim of this work is to provide new experimental data on laminar burning velocities for a new synthetic mixture composed of Camisea natural gas and CO2. It was found that the relevant published experimental background data are l imited to mixtures composed of methane and CO2; considering the fact that Camisea natural gas is widely used in Peru, this experimental research will serve as a supportive resource for further experimental and industrial implementations in this country, such as the design and modeling of new engines or industrial burners that are designed to be fueled by this mixture. An experimental setup for analyzing three types of flame geometry, which is feasible to implement for a wide range of conditions, was built in PUCP PI0735 laboratory and all the measurements were obtained for a range of mixtures (0%, 21.2%, 28.5%, 38.9%, 50% CO2) and ratios from around 0.55 to 0.95 at atmospheric conditions. The laminar burning velocities results obtained were analyzed in groups based on %CO2. In addition, the experimental margin error was determined by considering all the sources. The following conclusions were reached: (1) The laminar burning velocity decreases with the increase in CO2 percentage in the mixture due to the CO2 decreasing the flame temperature effect. (2) The flat flame type provided the highest value of burning velocity for each group of CO2 percentage in which it appears. (3) The highest obtained laminar burning velocity value was 22.64 ± 0.15 cm/s, for a flat flame with a ratio of 0.72 and 29.98% of CO2, while the lowest obtained value was 6.78 ± 0.15 cm/s for a conical trunk flame with a ratio of 0.59 and 49.83% of CO2. (4) The highest evaluated CO2 percentage was 50.97% for a conical trunk flame with a ratio of 0.69 and a burning velocity value of 11.04.

Intelligent sliding mode fault-tolerant control for aircraft engines with actuator dynamics and faults based on adaptive dynamic programming

Abstract The fault-tolerant control issue of aircraft engines with actuator dynamics and faults is investigated in this paper. By proposing a novel intelligent sliding mode fault-tolerant control (ISMFTC) method, which combines an adaptive dynamic programming (ADP) sliding surface with Grey Wolf Optimizer (GWO) for controller parameter optimisation, the goal is to achieve quality steady-state and dynamic performance in aircraft engines while maintaining strong fault-tolerance properties. Firstly, by considering not only actuator dynamics but also actuator faults, an uncertain nonlinear cascaded model of aircraft engines is developed according to characteristic of aircraft engines and their actuators. Secondly, an ADP-based sliding surface is proposed for considered aircraft engine uncertain nonlinear cascaded system. It can obtain a certain sense of optimised performance, and could be solved by ADP strategy off-line as well. Thirdly, fault-tolerant controller is obtained on the basis of sliding mode theory and adaptive fault estimation law, namely, ADP-based ISMFTC controller. Meanwhile, GWO is integrated into the investigation of ADP-based ISMFTC controller, optimised designable control parameters are obtained subsequently. Besides, robustness analysis is elaborated according to Lyapunov theory, fault estimation error is bounded and states of closed-loop system are uniformly ultimately bounded. Simulation on a twin-shaft turbofan aircraft engine, indicates the effect of proposed ADP-based ISMFTC method.

TATPat based explainable EEG model for neonatal seizure detection

The most cost-effective data collection method is electroencephalography (EEG) to obtain meaningful information about the brain. Therefore, EEG signal processing is very important for neuroscience and machine learning (ML). The primary objective of this research is to detect neonatal seizures and explain these seizures using the new version of Directed Lobish. This research uses a publicly available neonatal EEG signal dataset to get comparative results. In order to classify these EEG signals, an explainable feature engineering (EFE) model has been proposed. In this EFE model, there are four essential phases and these phases: (i) automaton and transformer-based feature extraction, (ii) feature selection deploying cumulative weight-based neighborhood component analysis (CWNCA), (iii) the Directed Lobish (DLob) and Causal Connectome Theory (CCT)-based explainable result generation and (iv) classification deploying t algorithm-based support vector machine (tSVM). In the first phase, we have used a channel transformer to get channel numbers and these values have been divided into three levels and these levels are named (1) high, (2) medium and (3) low. By utilizing these levels, we have created an automaton and this automaton has three nodes (each node defines each level). In the feature extraction phase, transition tables of these nodes has been extracted. Therefore, the proposed feature extraction function is termed Triple Nodes Automaton-based Transition table Pattern (TATPat). The used EEG signal dataset contains 19 channels and there are 9 (= 32) connection in the defined automaton. Thus, the presented TATPat extracts 3249 (= 19 × 19 × 9) features from each EEG segment. To choose the most informative features of these 3249 features, a new feature selector which is CWNCA has been applied. By cooperating findings of this feature selector and the presented DLob, the explainable results have been obtained. The last phase is the classification phase and to get high classification performance from this phase, an ensemble classifier (tSVM) has been presented and the classification results have been obtained using two validation techniques which are 10-fold cross-validation (CV) and leave-one subject-out (LOSO) CV. The proposed EFE model generates a DLob string and by using this string, the explainable results have been obtained. Moreover, the presented EFE model attained 99.15% and 76.37% classification accuracy deploying 10-fold and LOSO CVs respectively. According to the classification performances, the recommended TATPat-based EFE is a good model at EEG signal classification. Also, the presented TATPat-based EFE model is a good model for explainable artificial intelligence (XAI) since TTPat-based EFE is cooperating by the DLob.

Innovative Design and Fast Iterative Manufacturing of Micro-Turbojet Engines at Low Cost

The turbojet is the foundation of the gas turbine engine, which combines knowledge of fluid dynamics, thermodynamics, heat transfer, mechanical design, manufacturing, and jet propulsion. This paper describes in detail the inspiration source, design process, fluid dynamics analysis, manufacturing steps, ignition test method and test process of small jet engines. 3D modeling software SolidWorks was used for the preliminary modeling and fluid simulation was performed to optimize the design. Part of the model was produced by 3D resin printing technology, and the turbine engine model was driven by compressed air for no-load testing to verify the feasibility and structural stability of the resin model. Subsequently, some parts were printed with metal materials, combined with traditional machining techniques to complete production and assembly, and finally successfully carried out static ignition tests. The micro turbojet engine designed in this paper has successfully achieved static ignition test and demonstrated the feasibility of efficient development with limited resources and low manufacturing cost. This exploration proves the feasibility of rapid iteration technology route. The market prospect and manufacturing cost of micro turbojet are also analyzed.

The Enhancement of Machine Learning-Based Engine Models Through the Integration of Analytical Functions

The integration of analytical functions into machine learning-based engine models represents a significant advancement in predictive performance and operational efficiency. This paper focuses on the development of hybrid approaches to model engine combustion and temperature indices and on the synergistic effects of combining traditional analytical methods with modern machine learning techniques (such as artificial neural networks) to enhance the accuracy and robustness of such models. The main innovative contribution of this paper is the integration of analytical functions to improve the extrapolation capabilities of the data-driven models. In this work, it is demonstrated that the integrated models achieve superior predictive accuracy and generalization performance across dynamic engine operating conditions, with respect to purely neural network-based models. Furthermore, the analytical corrective functions force the output of the complete model to follow a physical trend and to assume consistent values also outside the domain of values assumed by the input features during the training procedure of the neural networks. This study highlights the potential of this integrative approach based on the implementation of the effects superposition principle. Such an approach also allows us to solve one of the intrinsic issues of data-driven modeling, without increasing the complexity of the training data’s collection and pre-processing.

Modeling and Performance Analysis of Variable Cycle Engine with Ceramic Matrix Composite Turbine Blades

To meet the requirements of future aircraft for power systems, the turbine inlet temperatures of aero engines are gradually increasing. Ceramic matrix composite (CMC), with its higher thermal limit, has become the preferred material for the turbine blades of variable cycle engines (VCEs). However, the impact of CMC turbine blades on the performance of a VCE is still unknown. In this research project, the comprehensive cooling-efficiency characteristics of CMC are determined through a fluid–solid coupling calculation; a cooling calculation model for turbine blades is established, and cooling airflow solution and control technology (CSCT) for an air system is developed. Additionally, a VCE simulation model is established to analyze the influence of CMC turbine blades on the cooling airflow of the air system and the overall performance of the engine. The results show that, for the design condition, the CMC turbine blade can reduce the cooling airflow of the air system by approximately 10%, and the net thrust is increased by 6.07–7.98%. For the off-design conditions, with the CSCT, the specific fuel consumption can be reduced by 3.06–5.73% while ensuring that the engine net thrust remains unchanged. A comprehensive analysis of the performance for both the design point and off-design points indicates that the use of CMC for high-pressure turbine (HPT) guide vanes and rotor blades yields significant performance benefits, while the performance improvement from the use of CMC for low-pressure turbine (LPT) rotor blades is minimal.

Mimicking Urinary Tract Infections Caused by Uropathogenic Escherichia coli Using a Human Three-Dimensional Tissue Engineering Model

Uropathogenic Escherichia coli are the main causal agent of urinary tract infections. These diseases can affect more than half of women during their lifetime. Moreover, recurrent urinary tract infections can affect up to 30% of patients, leading to higher social and economic costs for the community. No efficient treatment against the recurrent form of the disease has been discovered. Due to the low average rate of successful translation from 2D cell culture and in vivo animal models into clinical trials, new models that mimic pathologies, such as those produced by tissue engineering, are needed. A model of human-derived 3D bladder mucosa was produced by tissue engineering techniques using collagen gels and organ-specific primary human stromal and epithelial cell populations. This model was used to mimic the different steps of a urinary tract infection: adhesion, invasion, intracellular bacterial community and quiescent intracellular reservoir formation and, finally, bacteria resurgence after umbrella cell exfoliation through chitosan exposure to mimic the recurrent infection. The uropathogenic strain UTI-89-GFP was used as infectious bacteria and BL-21-GFP strain as a control. Our model is unique and is the first step toward mimicking the different phases of a UTI in a human context.

An Engineering Model to Represent Positive Return Strokes—An Extension of the Modified Transmission Line (MTL) Model

An engineering model to represent positive return strokes is introduced as an extension of the Modified Transmission Line model with Linear Current Decay (MTLL). This extension is grounded in experimental data on the electric fields and currents associated with positive return strokes. The core premise of the model is that once the return stroke front reaches the cloud, recoil leader-type activities within the cloud feed the lightning channel with a positive charge. This positive charge then travels to the ground in the form of an M-component, enhancing both the amplitude and duration of the impulse current in the channel and at ground level. The propagation of the return stroke current along the channel follows the MTLL model, while the M-component is treated as a current pulse traveling from the cloud to the ground. At ground level, the M-component current is fully reflected. The model successfully generates electromagnetic fields that resemble those observed from positive return strokes, and it is easily applicable to studies involving the interaction of positive return stroke fields with power lines and the Earth’s upper atmosphere.

Equivalent Simulation Study of Delta-Rotor Engine

The mechanical structure, movement mode, and combustion process of a triangular rotor engine differ from those of a conventional engine with a crank connecting rod mechanism as the core. This makes it impossible to directly use existing simulation software to simulate the performance of the entire engine, rendering it difficult to conduct structural evaluation and performance prediction during the engine development stage. Therefore, using existing performance simulation software to establish a performance-equivalent model for a triangular rotor engine is crucial. To solve the above problems, this study proposes a performance-equivalent simulation modelling method for a triangular rotor engine based on a three-dimensional simulation model and the operating principles of the triangular rotor and four-stroke engines. Compared to various performance indicators obtained from the three-dimensional simulation model, the results show that the equivalent model established in this study has sufficient accuracy for key indicators such as the cylinder pressure, cylinder temperature, and in-cylinder quality under various working conditions. This can satisfy the requirements of the complete machine-performance simulation of a triangular rotor engine.

Performance degradation modeling of civil aviation engines based on component characteristic map optimization

In order to provide a theoretical basis for the degradation of the air path performance of civil aviation engines at the unit level, the CFM56-3 engine was used as the research object. First, on the basis of using the characteristic map scaling method to obtain the component characteristic equation, the selection process of the scaling reference point of the fan general characteristic map was optimized, and a surface fitting method of the characteristic map was proposed to construct an engine component-level benchmark performance model that meets specific speed conditions under steady-state conditions. Then, by introducing the fault factor to generate the fault coefficient matrix, the deviation of the engine monitoring parameters as the component efficiency decreases was calculated, and compared with the fingerprint map data of the GE training manual, it was verified that the engine steady-state performance model that integrates the fan characteristic map scaling reference point optimization and the characteristic map surface fitting method has good accuracy and use in the analysis of air path performance degradation.

An Analysis of a Complete Aircraft Electrical Power System Simulation Based on a Constant Speed Constant Frequency Configuration

Recent developments in aircraft electrical technology, such as the design and production of more electric aircraft (MEA) and major steps in the development of all-electric aircraft (AEA), have had a significant impact on aircraft’ electrical power systems (EPSs). However, the EPSs of the latest aircraft produced by the main players in the market, Airbus with the Neo series and Boeing with the NG and MAX series are still completely traditional and based on the constant speed constant frequency (CSCF) configuration. For alternating current ones, the EPS is composed of the following: prime movers, namely the aircraft turbofan engine (TE); the electrical power source, i.e., the integrated drive generator (IDG); the command and control system, the generator control unit (GCU); the transmission and the system distribution system; the protection system, i.e., the CBs (circuit breakers); and the electrical loads. This paper presents the analysis of this system using the Simscape package from Simulink v 8.7, a MATLAB v 9.0 program, which is actually the development of some systems designed in two previous personal papers. For the first time in the literature, a complete MATLAB modelled EPS system was presented, i.e., the aircraft turbofan engine model, driven by the constant speed drive system (CSD) (model presented in the first reference as a standalone type and with different parameters), linked to the synchronous generator (SG) (model presented in second reference for lower power and rotational speed) in the so-called integrated drive generator (IDG) and electrical loads.

An energy trade-off management strategy for hybrid ships based on event-triggered model predictive control

This paper addresses the energy management problem of hybrid ships by proposing an event-triggered model predictive control (ET-MPC) method. The novelty in this work lies in the establishment of an event-triggered mechanism and a state prediction model for energy management of hybrid ships. First, torque models of the internal combustion engine (ICE) and electric machine (EM) are developed using a data-driven approach, followed by the construction of fuel consumption and carbon emission models. Second, an event-triggered mechanism, dependent on state prediction error, is introduced and updated at each time step based on the system’s current state. Additionally, a cubature Kalman filter (CKF) is employed to estimate and correct the state prediction error, minimizing inaccuracies. A trade-off coefficient is incorporated to optimize the balance between fuel consumption and carbon emissions. The ET-MPC method results in a 0.68% difference in fuel consumption and 3.43% increase emissions compared to the traditional MPC method. However, ET-MPC significantly reduces computational overhead by 56.66. The ET-MPC method effectively allocates the ship’s energy according to the varying trade-off coefficient, achieving optimal energy management under different constraints.

The Research of Diesel Engine Assembly Consistency Influence NOx Emission Based on Uniform Design Method

ABSTRACT Diesel engines need to meet the higher emission requirement according to the Euro VI emission standards, and changes in the assembly tolerance of diesel engines will affect the consistency of nitrogen oxides(NOx) emissions. To study the influence of assembly tolerance on NOx emission, a heavy diesel engine was used as the research prototype. The combustion model of the diesel engine was simulated by the Converge software and calibrated with the bench test data. Because the combustion system parameters have a significant impact on emissions, a three-factor eleven-level uniform design is arranged with three parameters, including compression ratio, fuel injection nozzle extension height and injection advance angle. The regression analysis method is used to obtain the relationship between the parameters and NOx emissions. The R2 test value of the regression equation is 0.916 and the F test value is 43.5, which shows that the results of the analysis are very effective. Then the single factor test method is applied to analyze the varying laws of compression ratio, nozzle extension height and fuel injection advance angle on NOx emissions, and the results reveal the inherent law similar to the regression equation. According to the Euro VI emission standards and the law of diesel engine emission performance consistency, the tolerance variation range of the key dimensions of the assembly parameters is obtained.

Adaptive Strategies and Sustainable Innovations of Chinese Contractors in the Belt and Road Initiative: A Social Network and Supply Chain Integration Perspective

As global economic integration and rapid technological advancements transform international business, international engineering contracting has become essential for achieving sustainable development goals (SDGs). This paper investigates the significant impact of China’s strategic initiatives, notably the “Going Global” strategy and the Belt and Road Initiative (BRI), on the operational practices of Chinese enterprises involved in overseas investments. Central to this transformation is the Engineering, Procurement, and Construction (EPC) model, which emphasizes the integration of supply chain management and stakeholder collaboration to enhance performance in international EPC projects and underscores the crucial role of these elements in promoting sustainability. Incorporating insights from social network data analysis, this study reveals that contractors collaborating with various stakeholders—such as owners/consulting engineers, domestic and foreign customs departments, and group headquarters/design parties—exhibit a high degree of similarity in personnel profiles. This suggests that the internal organizational structure and personnel allocation of contractors could be optimized to enhance operational efficiency, aligning with the collaborative patterns identified. This study addresses a critical research gap by exploring how effective supply chain management and collaborative stakeholder engagement within multinational EPC projects contribute to sustainable outcomes. Employing advanced social network analysis software, the research examines the complex interactions among stakeholders and their influence on procurement dynamics. Findings indicate that strong relational networks and strategic collaborations significantly enhance procurement efficiency and project success, underscoring the importance of supply chain integration. Ultimately, integrating supply chain management principles into the EPC model not only offers innovative perspectives for advancing sustainability in international projects but also provides actionable insights for improving project outcomes within the BRI framework. This research underscores the pivotal role of supply chain organization and stakeholder cooperation in achieving sustainability objectives, thereby enriching the discourse on sustainable enterprise operation and supply chain management in the context of global initiatives.

The effect of the design angle of the turbine nozzle outlet of the piston engine boost system on its effectiveness

The article is devoted to the actual problem of insufficient energy efficiency of combined internal combustion engines. One of the directions of its solution, which became the goal of this work, is a reasonable choice of the optimal value of the design angle of installation of nozzles in a radial-axial turbine, taking into account both its effective power and the coefficient of completeness of using the supplied pulse energy. The authors applied a closed-loop model of the combined engine, embedded in a new calculation method, which was divided into conditional blocks. In the first block, the method of indefinite Lagrange multipliers calculates the optimal values of the turbine elements in which the gas moves. In the second block, for a preliminary assessment of the calculated geometrical parameters of the flow path, the turbine characteristics are calculated: an assumption is made about the one-dimensionality and quasi-stationary flow. For calculations, a method for calculating the parameters of a stage at an average radius was used, supplemented by a semi-empirical method for calculating gas energy losses during the movement of the latter from the turbine inlet to the outlet section. In the third block, the efficiency of the turbine was estimated when working together with a piston engine by using a closed model for it. This made it possible to objectively evaluate such characteristics of the turbine as efficiency and power, which are functionally related to the pressure pulse in the exhaust tract, which will make it possible to predict the operational characteristics of the turbine operating in conjunction with the combined engine.

Optimization of operational parameters of marine methanol dual-fuel engine based on RSM-MOPSO

Methanol and natural gas, as green fuels for environmental protection, have shown great potential in the field of maritime transportation. This study explores how the methanol energy fraction (MEF), exhaust gas recirculation (EGR), excess air ratio (λ), and engine injection timing (EIT) influence combustion and emission traits in marine dual-fuel (DF) engine. Initially, a DF engine model was formulated through experiments using CONVERGE software, while the CHEMKIN program devised a chemical mechanism involving 100 compounds and 512 reactions. The response surface methodology (RSM) was subsequently utilized to design the experiment and develop the regression model. The improved multi-objective particle swarm optimization (MOPSO) algorithm was applied to optimize three critical variables: brake thermal efficiency (BTE), carbon monoxide (CO), and nitrogen oxide (NOx) emissions. Ultimately, feature-optimized scenarios from the Pareto front were chosen for comparative evaluation to derive the optimal configuration. The results show that when the decision variables MEF, EGR, λ and EIT are 22.33 %, 10 %, 1.81 and 11°CA BTDC respectively, there is a better trade-off between the three target variables. Compared with the original case, the change of ITE, NOx and CO emissions in the optimal case are +0.97 %, −39.53 % and −14.51 %, respectively. Overall, based on the intelligent optimization approach, the rational selection of DF engine parameters improved the ITE and most NOx and CO emissions were effectively suppressed.

A comprehensive propulsion system analysis: an integrated approach utilising engine simulation and free-running model experiments

Regulations concerning the environmental impact and energy efficiency of ships are becoming increasingly stringent. To meet these demanding criteria, new technologies are actively being developed to achieve emission reductions while maintaining efficient fuel energy conversion into propulsion power. However, the propulsion system behaviour in a dynamic environment of the actual sea is highly nonlinear and complex, and a profound understanding of the mutual interactions is still lacking. This paper proposes an integrated approach for comprehensive propulsion system analysis. The key feature of this technique is the utilisation of an intelligent propeller drive controlled by a marine diesel engine simulator (MDES) to drive the free-running model of a ship, providing real-like behaviour of the engine model in real-time in response to actual measured values. The core of the MDES consists of a continuous cycle-mean value dynamic engine model supplemented with a detailed combustion cycle evaluation. The developed fast calculation algorithm of crank-angle resolved thermodynamic equations of the gas state in the engine cylinder enables the complete engine model to be integrated into the real-time environment of a physical model ship. Thus, the propulsion system's performance can be analysed under conditions that closely mimic those of the actual sea environment.

The Spider Stellar Engine: a Fully Steerable Extraterrestrial Design?

A long-lived civilization will inevitably have to migrate towards a nearby star as its home star runs out of nuclear fuel. One way to achieve such a migration is by transforming its star into a stellar engine, and to control its motion in the galaxy. We first provide a brief overview of stellar engines and conclude that looking for technosignatures of stellar engines has taken two roads: on the observational side, hypervelocity stars have been the target of such searches, but without good candidates. On the theoretical side, stellar engine concepts have been proposed but are poorly linked to observable technosignatures. Since about half the stars in our galaxy are in binary systems where life might develop too, we introduce a model of a binary stellar engine. We propose mechanisms for acceleration, deceleration, steering in the orbital plane and outside of the orbital plane. We apply the model to candidate systems, spider pulsars, which are binary stars composed of one millisecond pulsar and a very low-mass companion star that is heavily irradiated by the pulsar wind. We discuss potential signatures of acceleration, deceleration, steering, as well as maneuvers such as gravitational assists or captures. Keywords: Pulsars: Spiders, Technosignatures, Stellar engine, Interstellar travel

0-D Dynamic Performance Simulation of Hydrogen-Fueled Turboshaft Engine

In the last few decades, the problem of pollution resulting from human activities has pushed research toward zero or net-zero carbon solutions for transportation. The main objective of this paper is to perform a preliminary performance assessment of the use of hydrogen in conventional turbine engines for aeronautical applications. A 0-D dynamic model of the Allison 250 C-18 turboshaft engine was designed and validated using conventional aviation fuel (kerosene Jet A-1). A dedicated, experimental campaign covering the whole engine operating range was conducted to obtain the thermodynamic data for the main engine components: the compressor, lateral ducts, combustion chamber, high- and low-pressure turbines, and exhaust nozzle. A theoretical chemical combustion model based on the NASA-CEA database was used to account for the energy conversion process in the combustor and to obtain quantitative feedback from the model in terms of fuel consumption. Once the engine and the turbomachinery of the engine were characterized, the work focused on designing a 0-D dynamic engine model based on the engine’s characteristics and the experimental data using the MATLAB/Simulink environment, which is capable of replicating the real engine behavior. Then, the 0-D dynamic model was validated by the acquired data and used to predict the engine’s performance with a different throttle profile (close to realistic request profiles during flight). Finally, the 0-D dynamic engine model was used to predict the performance of the engine using hydrogen as the input of the theoretical combustion model. The outputs of simulations running conventional kerosene Jet A-1 and hydrogen using different throttle profiles were compared, showing up to a 64% reduction in fuel mass flow rate and a 3% increase in thermal efficiency using hydrogen in flight-like conditions. The results confirm the potential of hydrogen as a suitable alternative fuel for small turbine engines and aircraft.