Crosswind Shear Gradient Affect on Wake Vortices

Parametric simulations with a Large Eddy Simulation (LES) model are used to explore the influence of crosswind shear on aircraft wake vortices. Previous studies based on field measurements, laboratory experiments, as well as LES, have shown that the vertical gradient of crosswind shear, i.e. the second vertical derivative of the environmental crosswind, can influence wake vortex transport. The presence of nonlinear vertical shear of the crosswind velocity can reduce the descent rate, causing a wake vortex pair to tilt and change in its lateral separation. The LES parametric studies confirm that the vertical gradient of crosswind shear does influence vortex trajectories. The parametric results also show that vortex decay from the effects of shear are complex since the crosswind shear, along with the vertical gradient of crosswind shear, can affect whether the lateral separation between wake vortices is increased or decreased. If the separation is decreased, the vortex linking time is decreased, and a more rapid decay of wake vortex circulation occurs. If the separation is increased, the time to link is increased, and at least one of the vortices of the vortex pair may have a longer life time than in the case without shear. In some cases, the wake vortices may never link

Advection of Microphysical Scalars in Terminal Area Simulation System (TASS)

The Terminal Area Simulation System (TASS) is a large eddy scale atmospheric flow model with extensive turbulence and microphysics packages. It has been applied successfully in the past to a diverse set of problems ranging from prediction of severe convective events (Proctor et al. 2002), tracking storms and for simulating weapons effects such as the dispersion and fallout of fission debris (Bacon and Sarma 1991), etc. More recently, TASS has been used for predicting the transport and decay of wake vortices behind aircraft (Proctor 2009). An essential part of the TASS model is its comprehensive microphysics package, which relies on the accurate computation of microphysical scalar transport. This paper describes an evaluation of the Leonard scheme implemented in the TASS model for transporting microphysical scalars. The scheme is validated against benchmark cases with exact solutions and compared with two other schemes - a Monotone Upstream-centered Scheme for Conservation Laws (MUSCL)-type scheme after van Leer and LeVeque's high-resolution wave propagation method. Finally, a comparison between the schemes is made against an incident of severe tornadic super-cell convection near Del City, Oklahoma

Simulation of Benchmark Cases with the Terminal Area Simulation System (TASS)

The hydrodynamic core of the Terminal Area Simulation System (TASS) is evaluated against different benchmark cases. In the absence of closed form solutions for the equations governing atmospheric flows, the models are usually evaluated against idealized test cases. Over the years, various authors have suggested a suite of these idealized cases which have become standards for testing and evaluating the dynamics and thermodynamics of atmospheric flow models. In this paper, simulations of three such cases are described. In addition, the TASS model is evaluated against a test case that uses an exact solution of the Navier-Stokes equations. The TASS results are compared against previously reported simulations of these benchmark cases in the literature. It is demonstrated that the TASS model is highly accurate, stable and robust

Estimation of Eddy Dissipation Rates from Mesoscale Model Simulations

The Eddy Dissipation Rate is an important metric for representing the intensity of atmospheric turbulence and is used as an input parameter for predicting the decay of aircraft wake vortices. In this study, the forecasts of eddy dissipation rates obtained from the current state-of-the-art mesoscale model are evaluated for terminal area applications. The Weather Research and Forecast mesoscale model is used to simulate the planetary boundary layer at high horizontal and vertical mesh resolutions. The Bougeault-Lacarrer and the Mellor-Yamada-Janji schemes implemented in the Weather Research and Forecast model are evaluated against data collected during the National Aeronautics and Space Administration s Memphis Wake Vortex Field Experiment. Comparisons with other observations are included as well

Bowles-Tatnall Wake Vortex Encounter Hazard Metric

Wake vortex spacing standards constrict the terminal area throughput and impose severe constraints on the overall capacity and efficiency of the National Airspace System. For more than two decades starting in the early 1990s, the National Aeronautics and Space Administration conducted extensive research on characterizing the formation and evolution of aircraft wakes. This multidisciplinary work included comprehensive field experiments (Pruis et al. 2016), flight tests (Vicroy et al. 1998), and wind tunnel tests (Rossow 1994; Chow et al. 1997). Parametric studies using large eddy simulations (Proctor 1998; Proctor et al. 2006) were conducted in order to develop fast-time models for the prediction of wake transport and decay (Ahmad et al. 2016). Substantial effort was spent on the formulation of acceptable vortex hazard metrics (Tatnall 1995; Hinton and Tatnall 1997). Several wake encounter severity metrics have been suggested in the past, which include the wake circulation strength, vortex-induced rolling moment coefficient (Clv), bank angle, and the roll control ratio (Tatnall 1995; Hinton and Tatnall 1997; Van der Geest 2012). The vortex-induced rolling moment coefficient introduced by Bowles and Tatnall (Tatnall 1995; Gloudemans et al. 2016) has been used extensively for risk and safety analysis of newly proposed air traffic management concepts and procedures. The original method of Bowles and Tatnall assumed a constant wing loading (the wing lift-curve slope, CL is constant), which resulted in an overestimation of the vortexinduced rolling moment coefficient. Bowles (2014) suggested a correction to the original method that provides more accurate values of Clv and which is also consistent with the underlying physics of the problem. The overestimation of Clv in the original method can be corrected by assuming an elliptical lift distribution. Figure 1.1 illustrates the correction in Clv achieved by the modified method

Comparisons of Crosswind Velocity Profile Estimates Used in Fast-Time Wake Vortex Prediction Models

Five methods for estimating crosswind profiles used in fast-time wake vortex prediction models are compared in this study. Previous investigations have shown that temporal and spatial variations in the crosswind vertical profile have a large impact on the transport and time evolution of the trailing vortex pair. The most important crosswind parameters are the magnitude of the crosswind and the gradient in the crosswind shear. It is known that pulsed and continuous wave lidar measurements can provide good estimates of the wind profile in the vicinity of airports. In this study comparisons are made between estimates of the crosswind profiles from a priori information on the trajectory of the vortex pair as well as crosswind profiles derived from different sensors and a regional numerical weather prediction model

Numerical Simulation of a Tornado Generating Supercell

The development of tornadoes from a tornado generating supercell is investigated with a large eddy simulation weather model. Numerical simulations are initialized with a sounding representing the environment of a tornado producing supercell that affected North Carolina and Virginia during the Spring of 2011. The structure of the simulated storm was very similar to that of a classic supercell, and compared favorably to the storm that affected the vicinity of Raleigh, North Carolina. The presence of mid-level moisture was found to be important in determining whether a supercell would generate tornadoes. The simulations generated multiple tornadoes, including cyclonic-anticyclonic pairs. The structure and the evolution of these tornadoes are examined during their lifecycle

Wind Information Uplink to Aircraft Performing Interval Management Operations

Interval Management (IM) is an ADS-B-enabled suite of applications that use ground and flight deck capabilities and procedures designed to support the relative spacing of aircraft (Barmore et al., 2004, Murdoch et al. 2009, Barmore 2009, Swieringa et al. 2011; Weitz et al. 2012). Relative spacing refers to managing the position of one aircraft to a time or distance relative to another aircraft, as opposed to a static reference point such as a point over the ground or clock time. This results in improved inter-aircraft spacing precision and is expected to allow aircraft to be spaced closer to the applicable separation standard than current operations. Consequently, if the reduced spacing is used in scheduling, IM can reduce the time interval between the first and last aircraft in an overall arrival flow, resulting in increased throughput. Because IM relies on speed changes to achieve precise spacing, it can reduce costly, low-altitude, vectoring, which increases both efficiency and throughput in capacity-constrained airspace without negatively impacting controller workload and task complexity. This is expected to increase overall system efficiency. The Flight Deck Interval Management (FIM) equipment provides speeds to the flight crew that will deliver them to the achieve-by point at the controller-specified time, i.e., assigned spacing goal, after the target aircraft crosses the achieve-by point (Figure 1.1). Since the IM and target aircraft may not be on the same arrival procedure, the FIM equipment predicts the estimated times of arrival (ETA) for both the IM and target aircraft to the achieve-by point. This involves generating an approximate four-dimensional trajectory for each aircraft. The accuracy of the wind data used to generate those trajectories is critical to the success of the IM operation. There are two main forms of uncertainty in the wind information used by the FIM equipment. The first is the accuracy of the forecast modeling done by the weather provider. This is generally a global environmental prediction obtained from a weather model such as the Rapid Refresh (RAP) from the National Centers for Environmental Prediction (NCEP). The weather forecast data will have errors relative to the actual, or truth, winds that the aircraft will encounter. The second source of uncertainty is that only a small subset of the forecast data can be uplinked to the aircraft for use by the FIM equipment. This results in loss of additional information. The Federal Aviation Administration (FAA) and RTCA are currently developing standards for the communication of wind and atmospheric data to the aircraft for use in NextGen operations. This study examines the impact of various wind forecast sampling methods on IM performance metrics to inform the standards development

Numerical Simulation of the Aircraft Wake Vortex Flowfield

The near wake vortex flowfield from a NACA0012 half-wing was simulated using a fully unstructured Navier-Stokes flow solver in three dimensions at a chord Reynolds number of 4.6 million and a Mach number of approximately 0.15. Several simulations were performed to examine the effect of boundary conditions, mesh resolution and turbulence scheme on the formation of wingtip vortex and its downstream propagation. The standard Spalart-Allmaras turbulence model was compared with the Dacles-Mariani and Spalart-Shur corrections for rotation and curvature effects. The simulation results were evaluated using the data from experiment performed at NASA Ames' 32in x 48in low speed wind tunnel

Flight Tests of the Turbulence Prediction and Warning System (TPAWS)

Flight tests of the National Aeronautics and Space Administration's Turbulence Prediction And Warning System (TPAWS) were conducted in the Fall of 2000 and Spring of 2002. TPAWS is a radar-based airborne turbulence detection system. During twelve flights, NASA's B-757 tallied 53 encounters with convectively induced turbulence. Analysis of data collected during 49 encounters in the Spring of 2002 showed that the TPAWS Airborne Turbulence Detection System (ATDS) successfully detected 80% of the events at least 30 seconds prior to the encounter, achieving FAA recommended performance criteria. Details of the flights, the prevailing weather conditions, and each of the turbulence events are presented in this report. Sensor and environmental characterizations are also provided