Distributed Turbulence Model with Rigorous Spatial Cross-Correlation for Simulation of Helicopter Flight in Atmospheric Turbulence

2019 ◽  
Vol 64 (4) ◽  
pp. 1-13
Author(s):  
Honglei Ji ◽  
Renliang Chen ◽  
Pan Li
Keyword(s):  
Atmospheric Turbulence ◽  
Turbulence Model ◽  
Cross Correlation ◽  
Turbulence Models ◽  
Flight Test ◽  
Longitudinal Direction ◽  
Flight Simulation ◽  
Quality Analysis ◽  
Frequency Range ◽  
Helicopter Flight

This paper presents a distributed turbulence model with rigorous spatial cross-correlation for helicopter flight simulation in atmospheric turbulence and for future handling-quality analysis. First, digital filters with longitudinal correlations of the von Kármán turbulence are developed to generate discrete turbulence velocity components. Meanwhile, transverse turbulence correlations are considered by relating the filters in different positions with mathematically rigorous spatial cross-correlation. Then, the distributions of the related filters on the transverse plane in front of helicopter and their velocity components in the longitudinal direction of airspeed, as well as turbulence models of helicopter aerodynamic surfaces, are established. Finally, a flight dynamics model coupled with the turbulence model is developed and validated against the flight-test data. The proposed model can achieve accurate real-time simulations of helicopter response to atmospheric turbulence in the frequency range of interest of handling qualities. The effect of transverse turbulence correlations on helicopter frequency response is also analyzed. The results show that the simulation model regardless of transverse turbulence correlations would aggravate the "rotor-to-body attenuation" effect of the main rotor and therefore underpredict the helicopter roll, pitch, and heave rate responses to atmospheric turbulence in the frequency range of interest.

Helicopter flight simulation trim in the coordinated turn with the hybrid genetic algorithm

2017 ◽  
Vol 233 (3) ◽  
pp. 1159-1168 ◽  
Author(s):  
Wei Wang ◽  
Dongsheng Li ◽  
Chun Liu
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Flight Test ◽  
Flight Simulation ◽  
Control Vector ◽  
Experimental Platform ◽  
Helicopter Flight ◽  
Quasi Newton ◽  
General Method ◽  
Good Agreement

Helicopter trim models are multivariate nonlinear equations and it is difficult to determine these initial trim points comparable to flight conditions. To solve this question, a hybrid genetic algorithm is presented in this paper, that combines the quick convergence ability of the quasi-Newton method and the advantages of genetic algorithm, such as global convergence. The trim control vector and the constraint conditions were established in the coordinated-turn based on the helicopter flight dynamic model. The coordinated turn flight of a UH-60 A helicopter was taken as an example to simulate on the experimental platform. Comparisons were made between the trim results and flight test data and there is a good agreement among them, and the efficiency of the algorithm presented is verified. It is a general method that can be applied to trim the helicopter of different flight conditions.

Understanding the Effect of Rotor-to-Rotor Interference on CH-47D Helicopter Dynamics

2021 ◽  
Author(s):  
Feyyaz Guner ◽  
David G. Miller ◽  
J. V. R. Prasad
Keyword(s):  
Flight Control ◽  
Influence Factors ◽  
Flight Test ◽  
Flight Simulation ◽  
Flight Control System ◽  
Pressure Potential ◽  
Handling Qualities ◽  
Helicopter Flight ◽  
Lateral Inflow ◽  
Lateral Axis

During the development of the Boeing CH-47D helicopter flight simulation model, test pilots reported mismatch between the flight simulator results and flight test data of the hover and low-speed lateral axis handling qualities, especially for the case without the automatic flight control system. In addressing the observed mismatch, the gains of the longitudinal and lateral components of the inflow model were selected to be significantly higher than their theoretical values. In this study, a detailed understanding of the rotor-to-rotor inflow interference is pursued using a recently developed multi-rotor pressure potential superposition inflow model. It is shown that the coupling between the inflow gradients of individual rotors exists in a tandem rotor, which can be approximated by using higher values for the longitudinal and lateral inflow gains of individual rotors. Further, it is shown that the need for empirical tuning of aerodynamic hub moment influence factors can be eliminated by properly accounting for the rotor-to-rotor interference in the inflow model.

scholarly journals Analysis of Flow Characteristics and Effects of Turbulence Models for the Butterfly Valve

2021 ◽  
Vol 11 (14) ◽  
pp. 6319
Author(s):  
Sung-Woong Choi ◽  
Hyoung-Seock Seo ◽  
Han-Sang Kim
Keyword(s):  
Turbulence Model ◽  
Dissipation Rate ◽  
Flow Characteristics ◽  
Turbulence Models ◽  
Flow Properties ◽  
Nominal Diameter ◽  
Large Pressure ◽  
Sst Model ◽  
Turbulence Effect ◽  
Valve Opening

In the present study, the flow characteristics of butterfly valves with different sizes DN 80 (nominal diameter: 76.2 mm), DN 262 (nominal diameter: 254 mm), DN 400 (nominal diameter: 406 mm) were numerically investigated under different valve opening percentages. Representative two-equation turbulence models of two-equation k-epsilon model of Launder and Sharma, two-equation k-omega model of Wilcox, and two-equation k-omega SST model of Menter were selected. Flow characteristics of butterfly valves were examined to determine turbulence model effects. It was determined that increasing turbulence effect could cause many discrepancies between turbulence models, especially in areas with large pressure drop and velocity increase. In addition, sensitivity analysis of flow properties was conducted to determine the effect of constants used in each turbulence model. It was observed that the most sensitive flow properties were turbulence dissipation rate (Epsilon) for the k-epsilon turbulence model and turbulence specific dissipation rate (Omega) for the k-omega turbulence model.

scholarly journals Turbulence model performance for ventilation components pressure losses

2021 ◽  
Author(s):  
Karsten Tawackolian ◽  
Martin Kriegel
Keyword(s):  
Reynolds Number ◽  
Turbulence Model ◽  
Pressure Loss ◽  
Low Reynolds Number ◽  
Turbulence Models ◽  
Reynolds Numbers ◽  
Test Case ◽  
Pressure Losses ◽  
Loss Coefficients ◽  
Near Wall

AbstractThis study looks to find a suitable turbulence model for calculating pressure losses of ventilation components. In building ventilation, the most relevant Reynolds number range is between 3×104 and 6×105, depending on the duct dimensions and airflow rates. Pressure loss coefficients can increase considerably for some components at Reynolds numbers below 2×105. An initial survey of popular turbulence models was conducted for a selected test case of a bend with such a strong Reynolds number dependence. Most of the turbulence models failed in reproducing this dependence and predicted curve progressions that were too flat and only applicable for higher Reynolds numbers. Viscous effects near walls played an important role in the present simulations. In turbulence modelling, near-wall damping functions are used to account for this influence. A model that implements near-wall modelling is the lag elliptic blending k-ε model. This model gave reasonable predictions for pressure loss coefficients at lower Reynolds numbers. Another example is the low Reynolds number k-ε turbulence model of Wilcox (LRN). The modification uses damping functions and was initially developed for simulating profiles such as aircraft wings. It has not been widely used for internal flows such as air duct flows. Based on selected reference cases, the three closure coefficients of the LRN model were adapted in this work to simulate ventilation components. Improved predictions were obtained with new coefficients (LRNM model). This underlined that low Reynolds number effects are relevant in ventilation ductworks and give first insights for suitable turbulence models for this application. Both the lag elliptic blending model and the modified LRNM model predicted the pressure losses relatively well for the test case where the other tested models failed.

scholarly journals Method for Measuring the Second-Order Moment of Atmospheric Turbulence

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 564
Author(s):  
Hong Shen ◽  
Longkun Yu ◽  
Xu Jing ◽  
Fengfu Tan
Keyword(s):  
Atmospheric Turbulence ◽  
Weighting Function ◽  
Structure Constant ◽  
Turbulence Models ◽  
Second Order ◽  
Index Structure ◽  
Order Moment ◽  
Site Testing ◽  
Optical Effects ◽  
Novel Method

The turbulence moment of order m (μm) is defined as the refractive index structure constant Cn2 integrated over the whole path z with path-weighting function zm. Optical effects of atmospheric turbulence are directly related to turbulence moments. To evaluate the optical effects of atmospheric turbulence, it is necessary to measure the turbulence moment. It is well known that zero-order moments of turbulence (μ0) and five-thirds-order moments of turbulence (μ5/3), which correspond to the seeing and the isoplanatic angles, respectively, have been monitored as routine parameters in astronomical site testing. However, the direct measurement of second-order moments of turbulence (μ2) of the whole layer atmosphere has not been reported. Using a star as the light source, it has been found that μ2 can be measured through the covariance of the irradiance in two receiver apertures with suitable aperture size and aperture separation. Numerical results show that the theoretical error of this novel method is negligible in all the typical turbulence models. This method enabled us to monitor μ2 as a routine parameter in astronomical site testing, which is helpful to understand the characteristics of atmospheric turbulence better combined with μ0 and μ5/3.

scholarly journals Improving a real-time helicopter simulator model with linear input filters

2021 ◽  
Author(s):  
Pavle Šćepanović ◽  
Frederik A. Döring
Keyword(s):  
Feedback Control ◽  
Time Domain ◽  
Flight Test ◽  
Flight Mechanics ◽  
Mean Square ◽  
Qualification Test ◽  
Model Inversion ◽  
Helicopter Flight ◽  
The Time Domain ◽  
Mean Square Errors

AbstractFor a broad range of applications, flight mechanics simulator models have to accurately predict the aircraft dynamics. However, the development and improvement of such models is a difficult and time consuming process. This is especially true for helicopters. In this paper, two rapidly applicable and implementable methods to derive linear input filters that improve the simulator model are presented. The first method is based on model inversion, the second on feedback control. Both methods are evaluated in the time domain, compared to recorded helicopter flight test data, and assessed based on root mean square errors and the Qualification Test Guide bounds. The best results were achieved when using the first method.

Assessment of turbulence models for bubbly flows: Toward a five-equation turbulence model

2020 ◽  
Vol 220 ◽  
pp. 115425
Author(s):  
Ghazi Bellakhal ◽  
Fathia Chaibina ◽  
Jamel Chahed
Keyword(s):  
Turbulence Model ◽  
Turbulence Models ◽  
Bubbly Flows

Helicopter Rotor Blade Flexibility Simulation for Aeroelasticity and Flight Dynamics Applications

2014 ◽  
Vol 59 (4) ◽  
pp. 1-18 ◽  
Author(s):  
Ioannis Goulos ◽  
Vassilios Pachidis ◽  
Pericles Pilidis
Keyword(s):  
Real Time ◽  
Rotor Blade ◽  
Flight Dynamics ◽  
Integrated Approach ◽  
Flight Simulation ◽  
Response Characteristics ◽  
Helicopter Flight ◽  
Finite State ◽  
The Time Domain ◽  
Blade Loads

This paper presents a mathematical model for the simulation of rotor blade flexibility in real-time helicopter flight dynamics applications that also employs sufficient modeling fidelity for prediction of structural blade loads. A matrix/vector-based formulation is developed for the treatment of elastic blade kinematics in the time domain. A novel, second-order-accurate, finite-difference scheme is employed for the approximation of the blade motion derivatives. The proposed method is coupled with a finite-state induced-flow model, a dynamic wake distortion model, and an unsteady blade element aerodynamics model. The integrated approach is deployed to investigate trim controls, stability and control derivatives, nonlinear control response characteristics, and structural blade loads for a hingeless rotor helicopter. It is shown that the developed methodology exhibits modeling accuracy comparable to that of non-real-time comprehensive rotorcraft codes. The proposed method is suitable for real-time flight simulation, with sufficient fidelity for simultaneous prediction of oscillatory blade loads.

Rotorcraft Lateral-Directional Oscillations: The Anatomy of a Nuisance Mode

2021 ◽  
Author(s):  
Dheeraj Agarwal ◽  
Linghai Lu ◽  
Gareth D. Padfield ◽  
Mark D. White ◽  
Neil Cameron
Keyword(s):  
Simulation Model ◽  
Simulation Models ◽  
Flight Test ◽  
Flight Simulation ◽  
Stability And Control ◽  
Systems Research ◽  
Control Derivatives ◽  
Research Aircraft ◽  
Level Of Understanding ◽  
And Control

High-fidelity rotorcraft flight simulation relies on the availability of a quality flight model that further demands a good level of understanding of the complexities arising from aerodynamic couplings and interference effects. One such example is the difficulty in the prediction of the characteristics of the rotorcraft lateral-directional oscillation (LDO) mode in simulation. Achieving an acceptable level of the damping of this mode is a design challenge requiring simulation models with sufficient fidelity that reveal sources of destabilizing effects. This paper is focused on using System Identification to highlight such fidelity issues using Liverpool's FLIGHTLAB Bell 412 simulation model and in-flight LDO measurements from the bare airframe National Research Council's (Canada) Advanced Systems Research Aircraft. The simulation model was renovated to improve the fidelity of the model. The results show a close match between the identified models and flight test for the LDO mode frequency and damping. Comparison of identified stability and control derivatives with those predicted by the simulation model highlight areas of good and poor fidelity.

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