Engineering topics

Christopher Eggert

Publications and source records attributed to Christopher Eggert.

3 records

NASA NTRS2025

Optimal Mission Profile for Low-Boom Supersonic Aircraft

An optimal mission profile, called the low-boom mission profile, is proposed for low-boom supersonic aircraft. The low-boom mission profile uses a fixed AoA for the cruise segment until reaching the cruise ceiling. The fixed AoA is determined by the cruise condition for the low-boom shaping of the aircraft. The derived CL trajectory is not necessarily the optimal trajectory for the cruise range when unrestricted supersonic flight is allowed. The undertrack sonic boom ground noise level is reduced during the cruise because of the increasing altitude from the fixed AoA trajectory and the approximate invariance of nondimensional overpressure at 3BL below a supersonic aircraft with respect to cruise altitude change when the AoA and cruise Mach are fixed. The approximate invariance of nondimensional overpressure at 3BL below a supersonic aircraft is verified using both Euler and Reynolds-averaged Navier-Stokes CFD solvers. A low-boom supersonic transport concept is used to illustrate that, compared to the fixed cruise altitude trajectory, the low-boom mission profile can increase the cruise range of a low-boom aircraft and reduce the undertrack sonic boom ground noise levels for the entire cruise segment. One significant contribution of this paper is the implication that an aircraft OML satisfying a sonic boom ground noise level constraint at SOC will satisfy the same noise level constraint over the entire cruise segment, as long as a fixed AoA trajectory is flown.

Low-boom characteristics↗

NASA NTRSDate not supplied

Multidisciplinary Optimization of A Transonic Truss-Braced Wing Aircraft Using Aviary

The continuous push to decrease fuel burn of single-aisle commercial aircraft has led to interest in a Transonic Truss-Braced Wing (TTBW) concept vehicle. Sporting high-slung wings that are long and slender to increase aerodynamic efficiency, a TTBW can also accommodate higher-bypass turbine engines. The combination of these two changes potentially leads to an overall decrease in fuel consumption. In this paper, a TTBW concept vehicle is assembled in the Aviary open-source tool for conceptual aircraft design. The conceptual-level aerodynamics and propulsion systems that come prepackaged with Aviary are replaced with higher-fidelity vortex lattice method for aerodynamics (VSPAERO) and a one-dimensional cycle analysis tool for propulsion (pyCycle). The vehicle is then optimized to minimize fuel burn for a representative commercial mission. Design parameters for the vehicle include the electrified turbine size, the size of the electric motors which are used for takeoff and climb assist, and battery capacity. The TTBW concept vehicle presented in this paper represents the first application of Aviary to an aircraft design problem.

Optimization↗

NASA NTRSDate not supplied

Method for System-Level Multidisciplinary Uncertainty Analysis of Low-Boom Flight Vehicles

Current research supporting NASA’s Commercial Supersonic Technology project is focused on the efficient prediction of uncertainty in sonic boom loudness generated by low-boom aircraft concepts. This paper focuses on research incorporating aircraft trim and aerostructural analysis into a multidisciplinary system-level uncertainty analysis. This enables the modeling of a steady-state representation of a point in the uncertainty space, simulating the vehicle as it would be flown. This approach also enables multiple uncertain parameters defining the configuration of the vehicle to be reduced to three: Mach number, altitude, and aircraft weight. To demonstrate this methodology, a case study exploring a conceptual low-boom supersonic aircraft is performed. Two different approaches are used to model the interactions between nearfield pressure signature analysis and sonic boom propagation, and their performance is evaluated in terms of accuracy and computational expense. One method uses a set of local surrogate models to generate a large number of nearfield signatures and perform Monte Carlo analysis. This method is found to produce, at a lower expense, uncertainty metrics that are comparable to the second method, in which uncertainty metrics are computed based on loudness metric values obtained directly from simulated nearfield signatures.

Supersonics↗