Supersonic Technology Concept Aeroplanes for Environmental Studies

The International Civil Aviation Organization is considering new environmental standards for future supersonic civil aircraft. NASA is supporting this effort by analyzing several notional, near-term supersonic transports. NASAs performance, noise, and exhaust emission predictions for these transports are being used to inform a larger study that will determine the global environmental and economic impact of adding supersonic aircraft to the fleet beginning this decade. A supersonic business jet with a maximum takeoff gross weight of 55 tonnes is the focus of this paper. A smaller business jet weighing 45 tonnes is also discussed. Both airplanes use supersonic engines derived from a common contemporary commercial subsonic turbofan core. Aircraft performance, airport-vicinity noise, and exhaust emissions are predicted using NASA tools. Also investigated are some of the anticipated behaviors and requirements of these aircraft in the commercial airspace. The sensitivity of noise to system uncertainties is presented and alternative engine studies are discussed

In-stride Optimal Motion Planning/re-planning for MCM Missions using Optimization

NPS NRP Executive SummaryIn-stride Optimal Motion Planning/re-planning for MCM Missions using OptimizationN8 - Integration of Capabilities & ResourcesThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Forward Gradients for Data-Driven CFD Wall Modeling

Computational Fluid Dynamics (CFD) is used in the design and optimization of gas turbines and many other industrial/ scientific applications. However, the practical use is often limited by the high computational cost, and the accurate resolution of near-wall flow is a significant contributor to this cost. Machine learning (ML) and other data-driven methods can complement existing wall models. Nevertheless, training these models is bottlenecked by the large computational effort and memory footprint demanded by back-propagation. Recent work has presented alternatives for computing gradients of neural networks where a separate forward and backward sweep is not needed and storage of intermediate results between sweeps is not required because an unbiased estimator for the gradient is computed in a single forward sweep. In this paper, we discuss the application of this approach for training a subgrid wall model that could potentially be used as a surrogate in wall-bounded flow CFD simulations to reduce the computational overhead while preserving predictive accuracy

Far-Term Exploration of Advanced Single-Aisle Subsonic Transport Aircraft Concepts

Far-term single-aisle class aircraft concepts for potential entry-into-service of 2045 were investigated using an Interactive Reconfigurable Matrix of Alternatives (IRMA) approach. The configurations identified through this design space exploration were then distilled into three advanced aircraft concepts best characterizing the prominent features identified through the IRMA exploration. These three aircraft concepts were then configured and sized for a 150-passenger capacity and a 3,500 nautical mile design mission. Mission block fuel burn was estimated and compared to a far-term conventional configuration baseline concept and a 2005 l. These comparisons suggest considerable potential improvements in fuel efficiency from the investigated advanced concepts

Update on the Development of a Flutter Analysis Capability for Unconventional Aircraft Concepts Using HCDstruct

Following years of development, the Higher-fidelity Conceptual Design and structural optimization (HCDstruct) tool is being extended to support dynamic aeroservoelastic analysis and structural optimization for advanced aircraft concepts. These required enhancements include: the development of an aerodynamic matching routine for correcting Nastrans doublet-lattice method aerodynamics; the implementation of control surface structural models; and the implementation of support for Nastrans flutter solution sequence (SOL 145). This paper presents an update on the implementation of generalized control surface structural models and support for Nastran SOL 145

Aeroelastic Optimization of Generalized Tube and Wing Aircraft Concepts Using HCDstruct Version 2.0

Major enhancements were made to the Higher-fidelity Conceptual Design and structural optimization (HCDstruct) tool developed at NASA Langley Research Center (LaRC). Whereas previous versions were limited to hybrid wing body (HWB) configurations, the current version of HCDstruct now supports the analysis of generalized tube and wing (TW) aircraft concepts. Along with significantly enhanced user input options for all air- craft configurations, these enhancements represent HCDstruct version 2.0. Validation was performed using a Boeing 737-200 aircraft model, for which primary structure weight estimates agreed well with available data. Additionally, preliminary analysis of the NASA D8 (ND8) aircraft concept was performed, highlighting several new features of the tool

Exploring parallel coordinates plots in virtual reality

Parallel Coordinates Plots (PCP) are a widely used approach to interactively visualize and analyze multidimensional scientific data in a 2D environment. In this paper, we explore the use of Parallel Coordinates in an immersive Virtual Reality (VR) 3D visualization environment as a means to support the decision-making process in engineering design processes. We evaluate the potential of VR PCP using a formative qualitative study with seven participants. In a task involving 54 points with 29 dimensions per point, we found that participants were able to detect patterns in the dataset compared with a previously published study with two expert users using traditional 2D PCP, which acts as the gold standard for the dataset. The dataset describes the Pareto front for a three-objective aerodynamic design optimization study in turbomachinery.Cambridge European & Trinity Hall Scholarshi

Artificial Neural Network-Based Flight Control Using Distributed Sensors on Fixed-Wing Unmanned Aerial Vehicles

Conventional control systems for autonomous aircraft use a small number of precise sensors in combination with classical control laws to maintain flight. The sensing systems encode center of mass motion and generally are set-up for flight regimes where rigid body assumptions and linear flight dynamics models are valid. Gain scheduling is used to overcome some of the limitations from these assumptions, taking advantage of well-tuned controllers over a range of design points. In contrast, flying animals achieve efficient and robust flight control by taking advantage of highly non-linear structural dynamics and aerodynamics. It has been suggested that the distributed arrays of flow and force sensors found in flying animals could be behind their remarkable flight control. Using a wind tunnel aircraft model instrumented with distributed arrays of load and flow sensors, we developed Artificial Neural Network flight control algorithms that use signals from the sensing array as well as the signals available in conventional sensing suites to control angle-of-attack. These controllers were trained to match the response from a conventional controller, achieving a level of performance similar to the conventional controller over a wide range of angle-of-attack and wind speed values. Wind tunnel testing showed that by using an ANN-based controller in combination with signals from a distributed array of pressure and strain sensors on a wing, it was possible to control angle-of-attack. The End-to-End learning approach used here was able to control angle-of-attack by directly learning the mapping between control inputs and system outputs without explicitly estimating or being given the angle-of-attack.</p

Fan-Intake interaction under high incidence

In this paper, we present an extensive numerical study on the interaction between the downstream fan and the flow separating over an intake under high incidence. The objectives of this investigation are twofold: (a) to gain qualitative insight into the mechanism of fan–intake interaction and (b) to quantitatively examine the effect of the proximity of the fan on the inlet distortion. The fan proximity is altered using the key design parameter, L/D, where D is the diameter of the intake, and L is the distance of the fan from the intake lip. Both steady and unsteady Reynolds-averaged numerical simulations (RANS) were carried out. For the steady calculations, a low-order fan model has been used, while a full 3D geometry has been used for the unsteady RANS. The numerical methodology is also thoroughly validated against the measurements for the intake-only and fan-only configurations on a high bypass ratio turbofan intake and fan, respectively. To systematically study the effect of fan on the intake separation and explore the design criteria, a simplified intake–fan configuration has been considered. In this fan–intake model, the proximity of the fan to the intake separation (L/D) can be conveniently altered without affecting other parameters. The key results indicate that, depending on L/D, the fan has either suppressed the level of the postseparation distortion or increased the separation-free operating range. At the lowest L/D (∼0.17), around a 5 deg increase in the separation-free angle of incidence was achieved. This delay in the separation-free angle of incidence decreased with increasing L/D. At the largest L/D (∼0.44), the fan was effective in suppressing the postseparation distortion rather than entirely eliminating the separation. Isentropic Mach number distribution over the intake lip for different L/D's revealed that the fan accelerates the flow near the casing upstream of the fan face, thereby decreasing the distortion level in the immediate vicinity. However, this acceleration effect decayed rapidly with increasing upstream distance from the fan-face.</jats:p