Because an aircraft gas turbine operates under various flight conditions that change with altitude, flight velocity, and ambient temperature, the performance estimation that considers the flight conditions must be known before developing or operating the gas turbine. More so, for the unmanned aerial vehicle (UAV) where the engine is activated by an onboard engine controller in emergencies, the precise performance model including the estimated steady-state and transient performance data should be provided to the engine control system and the engine health monitoring system. In this study, a graphic user interface (GUI) type steady-state and transient performance simulation model of the PW206C turboshaft engine that was adopted for use in the Smart UAV was developed using SIMULINK for the performance analysis. For the simulation model, first the component maps including the compressor, gas generator turbine, and power turbine were inversely generated from the manufacturer’s limited performance deck data by the hybrid method. For the work and mass flow matching between components of the steady-state simulation, the state-flow library of SIMULINK was applied. The proposed steady-state performance model can simulate off-design point performance at various flight conditions and part loads, and in order to evaluate the steady-state performance model their simulation results were compared with the manufacturer’s performance deck data. According to comparison results, it was confirmed that the steady-state model agreed well with the deck data within 3% in all flight envelopes. In the transient performance simulation model, the continuity of mass flow (CMF) method was used, and the rotational speed change was calculated by integrating the excess torque due to the transient fuel flow change using the Runge–Kutta method. In this transient performance simulation, the turbine overshoot was predicted.

A hardware-in-the-loop simulation of a three-shaft gas turbine engine for ship propulsion was established. This system is composed of computers, actual hardware, measuring instruments, interfaces between actual hardware and computers, and a network for communication, as well as the relevant software, including mathematical models of the gas turbine engine. “Hardware-in-the-loop” and “volume inertia effects” are the two innovative features of this simulation system. In comparison to traditional methods for gas turbine simulation, the new simulation platform can be implemented in real time and also can test the physical hardware’s performance through their integration with the mathematical simulation model. A fuel control strategy for a three-shaft gas turbine engine, which can meet the requirement to the acceleration time and not exceeding surge line, was developed using this platform.

The gas turbine engine is a complex assembly of a variety of components that are designed on the basis of aerothermodynamic laws. The design and operation theories of these individual components are complicated. The complexity of aerothermodynamic analysis makes it impossible to mathematically solve the optimization equations involved in various gas turbine cycles. When gas turbine engines were designed during the last century, the need to evaluate the engines performance at both design point and off design conditions became apparent. Manufacturers and designers of gas turbine engines became aware that some tools were needed to predict the performance of gas turbine engines especially at off design conditions where its performance was significantly affected by the load and the operating conditions. Also it was expected that these tools would help in predicting the performance of individual components, such as compressors, turbines, combustion chambers, etc. At the early stage of gas turbine developments, experimental tests of prototypes of either the whole engine or its main components were the only method available to determine the performance of either the engine or of the components. However, this procedure was not only costly, but also time consuming. Therefore, mathematical modelling using computational techniques were considered to be the most economical solution. The first part of this paper presents a discussion about the gas turbine modeling approach. The second part includes the gas turbine component matching between the compressor and the turbine which can be met by superimposing the turbine performance characteristics on the compressor performance characteristics with suitable transformation of the coordinates. The last part includes the gas turbine computer simulation program and its philosophy. The computer program presented in the current work basically satisfies the matching conditions analytically between the various gas turbine components to produce the equilibrium running line. The computer program used to determine the following: the operating range (envelope) and running line of the matched components, the proximity of the operating points to the compressor surge line, and the proximity of the operating points at the allowable maximum turbine inlet temperature. Most importantly, it can be concluded from the output whether the gas turbine engine is operating in a region of adequate compressor and turbine efficiency. Matching technique proposed in the current work used to develop a computer simulation program, which can be served as a valuable tool for investigating the performance of the gas turbine at off-design conditions. Also, this investigation can help in designing an efficient control system for the gas turbine engine of a particular application including being a part of power generation plant.

It is well known that turbocharged diesel engines suffer from an inadequate response to sudden load increase, this being a consequence of the nature of the energy exchange between the engine and the turbocharger. The dynamic response of turbocharged diesel engines could be improved by electric assisting systems, either by direct energy supply with an integrated starter-generator-booster (ISG) mounted on the engine flywheel, or indirect energy supply with an electrically assisted turbocharger. A previously verified zero dimensional computer simulation method was used for the analysis of both types of electrical assistance. The credibility of the data presented is further assured by the experimentally determined characteristics of the electric motors used as input parameters of the simulation. The paper offers an analysis of the interaction between a turbocharged diesel engine operating under various load conditions and electric assisting systems, as well as the requirements for supporting electric motors suitable for the improvement of an engine’s dynamic response. It is evident that an electrically assisted turbocharger outperforms an integrated starter-generator-booster for vehicle application, however ISG is the preferred solution when instant power increase is demanded.

Many gas turbines simulation codes have been developed to estimate power plant performance both in design and off-design conditions in order to establish the adequate control criteria or the possible cycle improvements; estimation of pollutant emissions would be very important using these codes in order to determine the optimal performance satisfying legal emission restrictions. This paper present the description of a one-dimensional emission model to simulate different gas turbine combustor typologies, such as conventional diffusion flame combustors, dry-low NO x combustors (DLN) based on lean-premixed technology (LPC) or rich quench lean scheme (RQL) and the new catalytic combustors. This code is based on chemical reactor analysis, using detailed kinetics mechanisms, and it is integrated with an existing power plant simulation code (ESMS Energy System Modular Simulator) to analyze the effects of power plant operations and configurations on emissions. The main goal of this job is the study of the interaction between engine control and combustion system. This is a critical issue for all DLN combustors and, in particular, when burning low-LHV fuel. The objective of this study is to evaluate the effectiveness of different control criteria with regard to pollutant emissions and engine performances. In this paper we present several simulations of actual engines comparing the obtained results with the experimental published data.

For gas turbine engine performance analysis, a variety of simulation tools is available. In order to minimize model development and software maintenance costs, generic gas turbine system simulation tools are required for new modeling tasks. Many modeling aspects remain engine specific however and still require large implementation efforts. One of those aspects is adaptive modeling. Therefore, an adaptive modeling functionality has been developed that can be implemented in a generic component-based gas turbine environment. A single component in a system modeling environment is able to turn any new or existing model into an adaptive model without extra coding. The concept has been demonstrated in the GSP gas turbine modeling environment. An object-oriented architecture allows automatic addition of the necessary equations for the adaptation to measurement values. Using the adaptive modeling component, the user can preconfigure the adaptive model and quickly optimize gas path diagnostics capability using experimentation with field data. The resulting adaptive model can be used by maintenance engineers for diagnostics. In this paper the integration of the adaptive modeling function into a system modeling environment is described. Results of a case study on a large turbofan engine application are presented.

A high-fidelity real-time simulation code based on a lumped, nonlinear representation of gas turbine components is presented. The code is a general-purpose simulation software environment useful for setting up and testing control equipments. The mathematical model and the numerical procedure are specially developed in order to efficiently solve the set of algebraic and ordinary differential equations that describe the dynamic behavior of gas turbine engines. For high-fidelity purposes, the mathematical model takes into account the actual composition of the working gases and the variation of the specific heats with the temperature, including a stage-by-stage model of the air-cooled expansion. The paper presents the model and the adopted solver procedure. The code, developed in Matlab-Simulink using an object-oriented approach, is flexible and can be easily adapted to any kind of plant configuration. Simulation tests of the transients after load rejection have been carried out for a single-shaft heavy-duty gas turbine and a double-shaft aero-derivative industrial engine. Time plots of the main variables that describe the gas turbine dynamic behavior are shown and the results regarding the computational time per time step are discussed.

This paper describes the design concepts and object-oriented architecture of Onyx, an extensible domain framework for computational simulation of gas turbine engines. Onyx provides a flexible environment for defining, modifying, and simulating the component-based gas turbine models described in Part 1 of this paper. Using advanced object-oriented technologies such as design patterns and frameworks, Onyx enables users to customize and extend the framework to add new functionality or adapt simulation behavior as required. A customizable visual interface provides high-level symbolic control of propulsion system construction and execution. For computationally-intensive analysis, components may be distributed across heterogeneous computing architectures and operating systems. A distributed gas turbine engine model is developed and simulated to illustrate the use of the framework. [S0742-4795(00)02403-0]

Designing and developing new aerospace propulsion systems is time-consuming and expensive. Computational simulation is a promising means for alleviating this cost, but requires a flexible software simulation system capable of integrating advanced multidisciplinary and multifidelity analysis methods, dynamically constructing arbitrary simulation models, and distributing computationally complex tasks. To address these issues, we have developed Onyx, a Java-based object-oriented domain framework for aerospace propulsion system simulation. This paper presents the design of a common engineering model formalism for use in Onyx. This approach, which is based on hierarchical decomposition and standardized interfaces, provides a flexible component-based representation for gas turbine systems, subsystems and components. It allows new models to be composed programmatically or visually to form more complex models. Onyx’s common engineering model also supports integration of a hierarchy of models which represent the system at differing levels of abstraction. Selection of a particular model is based on a number of criteria, including the level of detail needed, the objective of the simulation, the available knowledge, and given resources. The common engineering model approach is demonstrated by developing gas turbine component models which will be used to compose a gas turbine engine model in Part 2 of this paper. [S0742-4795(00)02303-6]

A nonlinear dynamic model is developed in this study to simulate the overall performance of a naturally aspirated, single cylinder, four-stroke, direct injection diesel engine under cold start and fully warmed-up conditions. The model considers the filling and emptying processes of the cylinder, blowby, intake, and exhaust manifolds. A single zone combustion model is implemented and the heat transfer in the cylinder, intake, and exhaust manifolds are accounted for. Moreover, the derivations include the dynamics of the crank-slider mechanism and employ an empirical model to estimate the instantaneous frictional losses in different engine components. The formulation is coded in modular form whereby each module, which represents a single process in the engine, is introduced as a single block in an overall Simulink engine model. The numerical accuracy of the Simulink model is verified by comparing its results to those generated by integrating the engine formulation using IMSL stiff integration routines. The engine model is validated by the close match between the predicted and measured cylinder gas pressure and engine instantaneous speed under motoring, steady-state, and transient cold start operating conditions.