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During aircraft development, mathematical models are elaborated from our knowledge of fundamental physical laws. Those models are used to gain knowledge in order to make decisions in all development stages. Since engine model is one of the most important items in aircraft simulation, the aviation industry has recently developed a high interest on t...
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Context 1
... others words, -system identification‖ includes the model structure definition and the estimation of parameters defining the model, as shown is Figure 2. As seen in Figure 2, the identification process is divided in two steps. ...
Context 2
... others words, -system identification‖ includes the model structure definition and the estimation of parameters defining the model, as shown is Figure 2. As seen in Figure 2, the identification process is divided in two steps. In a first step, a mathematical model that described the studied system (i.e. ...
Citations
... Aircraft and engine models for the Cessna Citation X and the CRJ-700 have been developed at the LARCASE [33]. Examples of their work on engine models include system identification [34][35][36], adaptive algorithms [37], and neural networks [38][39][40]. Different cycle model analyses have also been performed at the LARCASE over the past few years [31,[41][42][43]. ...
A deterioration cycle model is presented, designed to consider the turbomachinery efficiency losses that are expected during real engine in-service operations. The cycle model was developed using information from practical experience found in the literature to account for both short- and long-term deterioration effects; the former occurring during the first flight cycles, the latter due to regular in-service operation. This paper highlights the importance of analyzing the inter-turbine temperature margin () to track engine deterioration to determine the extent of an in-service engine life. The proposed model was used to assess the and fuel consumption impact in the CRJ-700 regional aircraft (powered by two CF34-8C5B1 engines) for three representative missions: short (0.4 h), average (1.4 h), and long (2.5 h), considering different levels of engine deterioration, from the new engine level up to fully deteriorated. The fuel consumption at the new engine level (zero deterioration) was validated against a real-time engine model embedded in a Level-D flight simulator, the so-called Virtual Research Flight Simulator located at the Laboratory of Applied Research in Active Control, Avionics, and AeroServoElasticity. The errors found in this validation for the trip mission fuel consumption in the short, average, and long missions were −3.6, +0.9, and +0.6%, respectively. The cycle model predictions suggest the for a new engine is 55.2 °C, whereas for a fully deteriorated engine, it is 26.4 °C. Finally, in terms of fuel consumption, the results presented here show that an average CF34-8C5B1 engine shows an increase in the cumulative fuel consumption of 2.25% during its life in service, which translates to a 4.5% impact in aircraft fuel consumption.
... The first submodel related to the static engine state, while the second referred to the engine dynamics (i.e., transient state). There are several existing static models in the literature [21,26,30,31], which are very similar in nature; however, the model in [30] has been proven to outperform the others. In this study, for aerodynamic identification purposes and to not increase the number of unknown parameters, the transient engine dynamics were neglected. ...
... The first submodel related to the static engine state, while the second referred to the engine dynamics (i.e., transient state). There are several existing static models in the literature [21,26,30,31], which are very similar in nature; however, the model in [30] has been proven to outperform the others. In this study, for aerodynamic identification purposes and to not increase the number of unknown parameters, the transient engine dynamics were neglected. ...
For developing high-fidelity flight simulations, an accurate and complete representation of the aerodynamic characteristics of the aircraft is necessary. To obtain a realistic aerodynamic database, system identification methods can be used to describe the applied forces and moments acting on the aircraft. This study is based on simulated flight test data from a nonlinear simulation of the F-16 aircraft. It is demonstrated that the complete set of aerodynamic coefficients can be reconstructed from the flight test data. Thrust forces and moments are obtained from ground tests. A practical system identification methodology based on the iterative equation error method to determine the nonlinear aerodynamic and engine thrust models in the absence of engine manufacturer data is developed. The estimated values obtained using the method are compared with the actual parameter values. A mathematical engine model that can be used to estimate the thrust force for any flight condition is also developed. The findings demonstrate that the proposed method yields accurate results. The developed methodology is well-suited for the identification of isolated aerodynamic drag and lift coefficients and the thrust model.
... The Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity (LARCASE) has a broad experience developing aircraft and engine models [12]. Regarding engine models, several methods have been explored, such as: system identification [13,14], empirical equations [15], component level modeling [16], neural networks [17,18]. Now, with the development of the ODGM, physics-based aerothermodynamic modeling will be pursued. ...
View Video Presentation: https://doi.org/10.2514/6.2022-3642.vid In this paper, a high-fidelity aerothermodynamic Off-Design Generic Model is proposed. The model was completely developed in-house at the Laboratory of Applied Research in Active Control, Avionics and AeroServoElasticity using Matlab. The Design Point and the turbomachinery Component Maps scaling factors are proposed and discussed. Additionally, the set of nonlinear equations that define the Off-Design model are established, furthermore, two numerical methods to solve the system of equations are briefly reviewed. The Off-Design Generic Model results are compared against those of the Numerical Propulsion System Simulation, a high-fidelity platform for aerothermodynamic simulations used in the Gas Turbine Engine industry. A series of considerations are proposed to prevent any systematic bias in the comparison between the two models. The Generic Model proposed in this work presented good precision compared to the Numerical Propulsion System Simulation. From representative conditions (Sea-Level, 20k, and 35k) at different power settings, the average errors found in the Specific Fuel Consumption are negligible (less than ± 0.06%), and these errors in the net thrust were +0.03%, +0.25%, and +0.29%, respectively.
... These models have been derived from simulated flight tests performed in our Level-D Research Aircraft Flight Simulator (RAFS); according to the Federal Aviation Administration (FAA), the level-D corresponds to the highest qualification level for flight dynamics and engine modeling [3], thus, deemed suitable to create and validate our models. Among the different techniques used at the LARCASE to develop these models we found: empirical equations [4], Component Level Modeling (CLM) [5], system identification [3,6], adaptive algorithms [7], and Neural Network (NN) algorithms [8,9]. ...
View Video Presentation: https://doi.org/10.2514/6.2022-0774.vid In this paper, the methodology and results of a new generic model for aerothermodynamic design point calculations is presented. The generic model was completely developed in-house at the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity. Our model accounts for rigorous physics modeling and accurate calculations of thermodynamic properties of interest. The validation of the precision of our generic model was performed against the Numerical Propulsion System Simulation, a high-fidelity commercial platform commonly used in the Gas Turbine industry to create aerothermodynamic cycle models. The validation is performed in two phases, first, validating each thermodynamic process in the engine, second, in the high-level performance parameters of interest. Three compressor bleed extraction scenarios were considered in our validation: no bleed extraction, bleed extraction for Environmental Control System, and bleed extraction for Environmental Control System combined with turbine cooling. The results showed that the maximum absolute errors found in our validation regarding the three scenarios are, 0.38% for the net thrust and 0.24% for the Specific Fuel Consumption. The reduced errors confirm a good precision between our generic model and the Numerical Propulsion System Simulation
... To verify the values of longitudinal aerodynamic forces and moments that the aerodynamic model (OpenFoam) provides as output, we used the Virtual Research Simulator (VRESIM) located at the Research Laboratory in Active Controls, Avionics and AeroServoElasticity (LARCASE) [27][28][29][30][31][32][33]. The VRESIM is a Virtual Simulator (VSIM) product designed and assembled by CAE Inc., that deliver flight test data of the CRJ700 aircraft. ...
This study is focused on the development of longitudinal aerodynamic models for steady flight conditions. While several commercial solvers are available for this type of work, we seek to evaluate the accuracy of an open source software. This study aims to verify and demonstrate the accuracy of the OpenFoam solver when it is used on basic computers (32–64GB of RAM and eight cores). A new methodology was developed to show how an aerodynamic model of an aircraft could be designed using OpenFoam software. The mesh and the simulations were designed only using OpenFoam utilities, such as blockMesh , snappyHexMesh , simpleFoam and rhoSimpleFoam . For the methodology illustration, the process was applied to the Bombardier CRJ700 aircraft and simulations were performed for its flight envelope, up to M0.79. Forces and moments obtained with the OpenFoam model were compared with an accurate flight data source (level D flight simulator). Excellent results in data agreement were obtained with a maximum absolute error of 0.0026 for the drag coefficient, thus validating a high-fidelity aerodynamic model for the Bombardier CRJ-700 aircraft.
... Numerous simple static models exist in the literature [46] [47] [54] [55] [56], and [57], and it is shown that the model in Ref. [54] is superior to others. ...
... Numerous simple static models exist in the literature [46] [47] [54] [55] [56], and [57], and it is shown that the model in Ref. [54] is superior to others. ...
This doctorate study aims to provide a methodology for developing aerodynamic and engine thrust models using simulated flight test data for the F16 fighter aircraft. An accurate and comprehensive representation of an aircraft's aerodynamic characteristics is required to design a flight control system or develop a high-fidelity flight simulator. Modern computational methods and wind tunnel testing can provide the aerodynamic database, but flight test data is required to obtain a more accurate and realistic aerodynamic database. As a result, system identification methods can characterize applied forces and moments acting on the aircraft. The F-16 nonlinear model also includes sensor models to simulate the actual flight data. The flight tests are carried out in the F16 simulation model using different excitations on the control surfaces. Simulation data is collected in predefined trim points. The equation error and output error methods are employed to analyze simulated data to estimate aerodynamic parameters in the time domain. The equation-error method is used firstly to identify aerodynamic parameters, and the results are then utilized as a starting point in the output-error process for fine-tuning. In general, thrust forces and moments are obtained from ground tests. The contribution of this doctoral study is to implement an iterative aerodynamic and thrust estimation approach in the absence of engine manufacturer data. The validation of resulting models is accomplished by comparing the measured flight data to the model’s predictions for identical control inputs, as specified by the Federal Aviation Administration (FAA).
... Pertinent specifications and limitations relative to the Cessna Citation X are given in Table 1 for the convenience of the readers [36]. The models used to determine the aerodynamic and propulsive performance (i.e., lift, drag, thrust and fuel flow) of the Cessna Citation X were generated in-house by the LARCASE team based on the data encoded in the RAFS [41,42], and have the same mathematical structure as those presented in Sections II.B.2 and II.B.3. ...
This paper presents a practical method to compute the four-dimensional flight trajectories of aircraft in the presence of winds. The proposed method consisted of numerically integrating the aircraft equations of motion over different segments that compose a typical commercial flight profile. For this purpose, the aircraft vertical trajectory was divided into seven typical flight segments: unrestricted climb at constant airspeed, restricted climb at constant airspeed, climb/level-off acceleration, level flight at constant airspeed, unrestricted descent at constant airspeed, restricted descent at constant airspeed, and descent/level-off deceleration. For each segment, detailed algorithms were designed to solve and then integrate the equations of motion using an Euler scheme. The lateral trajectory, on the other hand, was constructed by connecting a series of waypoints with straight and turn segments. The method was applied and validated on the well-known Cessna Citation X business jet, for which a qualified research aircraft flight simulator (RAFS) was available. A total of 130 tests were carried out with the RAFS over a wide range of operational conditions. The comparison results showed that the trajectory data predicted by the algorithms matched the trajectory data obtained from the RAFS with less than 5% relative errors.
... In the same way as for the aerodynamic coefficients, the engine model is also composed of a set of fourdimensional lookup tables describing the variation of the thrust and fuel flow as function of the altitude ℎ, the Mach number , and temperature conditions. These lookup tables were developed and validated by the authors in a previous study using data from the RAFS [46,47]. Mathematically, the thrust and fuel flow are expressed as follows, ...
... Eq. (46) can be rewritten in a more compact form as follows: ...
The objective of this paper is to present a practical method developed at the Laboratory of Applied Research in Actives Controls, Avionics, and AeroServoElasticity (LARCASE) for calculating takeoff and departure trajectories of a Cessna Citation X. The method consisted in numerically integrating the aircraft equations of motion for each segment that composed a typical takeoff and departure profile. For this purpose, the complete aircraft trajectory was divided into five typical segments, including ground acceleration, rotation, transition, climb at constant speed, and climb acceleration. For each segment, detailed algorithms to solve and integrate the equations of motion using an Euler scheme were designed. The complete aircraft trajectory was obtained by combining these segments in a specified order depending on the departure procedure profile. The validation of the methodology was evaluated with a qualified Research Aircraft flight Simulator (RAFS) of the Cessna Citation X. A total of 38 tests were carried out with the RAFS over a wide range of operational conditions. Comparison results showed that the trajectory data predicted by the different algorithms matched the trajectory data obtained from the RAFS with less than 5% of relative error.
... In the field of aircraft model development, the focus is on methodologies that can identify high fidelity engine [6] and aircraft [7] performance models from flight data. These models are intended for use as research tools, for aircraft performance evaluation, and in flight trajectory optimization algorithms. ...
... In the second method, the atmospheric parameters for the time domain were computed through 4D linear interpolation: the atmosphere parameters were computed for each routing grid waypoint and time domain limit value, and then the D coefficients were computed for each time domain using Eq. (6). The results of the comparisons for the time necessary to create the ADM and the model precision are presented in Table 6. ...
This article presents a new method for storing and computing the atmospheric data used in time-critical flight trajectory performance prediction calculations, such as flight performance prediction calculations in flight management systems and/or flight trajectory optimization, of constant altitude cruise segments. The proposed model is constructed based on the forecast data provided by Meteorological Service Agencies, in a GRIB2 data file format, and the set of waypoints that define the lateral component of the evaluated flight profile(s). The atmospheric data model can be constructed/updated in the background or off-line, when new atmospheric prediction data are available, and subsequently used in the flight performance computations. The results obtained using the proposed model show that, on average, the atmospheric parameter values are computed six times faster than through 4D linear interpolations, while yielding identical results (value differences of the order of 10e−14). When used in flight trajectory performance calculations, the obtained results show that the proposed model conducts to significant computation time improvements. The proposed model can be extended to define the atmospheric data for a set of cruise levels (usually multiple of 1000 ft).
... Similarly, Bartel and Young [32] investigated previously published empirical models to predict the thrust and fuel consumption of a modern turbofan during takeoff, climb and cruise. Ghazi et al. [33] and Botez et al. [34] used different empirical equations to model the engine thrust and fuel flow of a Cessna Citation X. Camilleri et al. [35] designed a lift and drag models for an Airbus A320 based on equations provided by Ojha [28] and Asselin [36]. Researchers have also considered the possibility of combining empirical equations with open source data such as the Jane's all the Word's Aircraft Database [37] or the ICAO Engine Emission Databank [38] to design performance models as proposed by Metz et al. in [39] and Sun et al. in [40]. ...
This paper presents the validation results of a study conducted at the Laboratory of Applied Research in Actives Controls, Avionics, and Aeroservoelasticity to develop a modeling technique for determining a performance model of a particular aircraft using a limited amount of data. This technique was applied to the well-known business jet aircraft, Cessna Citation X. All the reference data used to design the model were generated using an in-house in-flight performance program. These data were subsequently combined with simplified flight mechanics equations in order to estimate various performance and aero-propulsive characteristics of the aircraft. An original identification algorithm was next developed in order to determine a mathematical model describing the fuel flow, as well as the aircraft thrust and drag aerodynamic coefficients. Validation of the study was accomplished by comparing trajectory data predicted by the model with trajectory data measured with a research aircraft flight simulator (RAFS) of the Cessna Citation X. The results show a very good agreement for the flight time, the ground distance traveled, and fuel consumption.
