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Justin S Gray

Publications and source records attributed to Justin S Gray.

7 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Multidisciplinary Optimization of an Electric Quadrotor Urban Air Mobility Aircraft

Urban Air Mobility (UAM) vehicles have the potential to augment urban transportation systems, allowing passengers to skip the traffic below for a fee. This emerging market is opening up the design space for a new class of Urban Air Mobility (UAM) vehicles which could be powered by electric propulsion systems to be economical and environmentally friendly. However, development of these UAM concepts presents several additional challenges in the design process. First, these concept designs require including new disciplinary models for subsystems including the electric motors, cables, batteries and thermal management systems. Second, correctly designing and evaluating these various subsystems requires tight coupling between the discipline models to capture interactions. This paper presents the continued development of a multidisciplinary design optimization environment to aid in the development of these vehicle concepts. The multidisciplinary environment fully couples the various subsystem models allowing for the full vehicle to be designed and optimized simultaneously. In this research, the developed modeling approach is demonstrated in the analysis of a small, all-electric quadrotor UAM concept. Results from these studies show that numerous disciplines can be tightly coupled and producing improved overall vehicle designs.

Multidisciplinary Optimization↗
NASA NTRSDate not supplied

Performance Analysis of Optimized STARC-ABL Designs Across the Entire Mission Profile

Boundary layer ingestion (BLI) offers the potential for significant fuel burn reduction by exploiting strong aeropropulsive interactions. NASA’s STARC–ABL concept uses an electri- cally powered BLI tail cone thruster on what is otherwise a traditional airframe. Despite the traditional airframe of this configuration, aeropropulsive integration is critical to the perfor- mance of the BLI propulsor. Furthermore, due to being electrically powered, the fan pressure ratio and efficiency of the BLI tail cone thruster vary widely across the flight envelope, and this variation in fan performance must be accounted for with the aeropropulsive integration of the BLI system. Thus, accurate performance prediction for this novel propulsion configu- ration requires the use of a coupled aeropropulsive model across the flight envelope. In this work, we analyze the off-design performance of 18 optimized designs using an aeropropulsive model that is built with the OpenMDAO framework to couple 3-D RANS CFD simulations to 1-D thermodynamic cycle analyses. The designs are created via high-fidelity aeropropulsive design optimizations that span a range of fan pressure ratio and thrust values at the cruise conditions for the STARC-ABL concept, which was chosen as the aerodynamic design point for the propulsor. Performance analyses we present herein are then performed at a range of off-design flight conditions that span the flight envelope, including low-speed and low-altitude flight conditions. This study provides the first set of high-fidelity data for the STARC–ABL configuration at off-design conditions, and the results quantify the power savings through BLI compared to a traditional propulsion system across the entire mission profile.

optimization↗
NASA NTRSDate not supplied

Battery Cell-to-Pack Scaling Trends for Electric Aircraft

Battery pack gravimetric energy density is one of the most important, yet often miss- estimated design parameters for sizing all-electric aircraft. Proper accounting for thermal, structural, and operational safety margins are frequently lost when extrapolating performance from the cell level to the aircraft level. This paper summarizes the relevant engineering and certification details needed to better account for the penalties associated when assembling battery packs. The relationship between the cell and pack energy density is not linear, as is often assumed. Furthermore, the relationship varies depending on pack requirements, cell chemistry, and architecture. Parametric, high-fidelity models are used to determine optimal battery pack sizes over a range of conditions to better quantify technology scaling effects.

Battery Electric Aircraft↗
NASA NTRSDate not supplied

A Nonlinear Schur Complement Solver for CFD-Based Multidisciplinary Models

CFD-based multidisciplinary models are the fundamental building blocks of multidis- ciplinary design optimization frameworks. Linear and nonlinear solutions of these coupled models are difficult, especially when the Jacobian matrices represent a saddle point problem, where a block-diagonal corresponding to a discipline is non-invertible. These scenarios necessitate the use of a coupled solver algorithm such as the Newton’s method instead of the popular block Gauss– Seidel-based methods because of this non-invertible block. To address this challenge, we introduce a nonlinear Schur complement solver suitable for CFD-based multidisciplinary models. The solver leverages the specialized linear and nonlinear solvers of the CFD code, and therefore, does not require the solution of a large coupled linear system as the coupled Newton’s method. Further- more, because the solver primarily uses the specialized linear and nonlinear solvers of the CFD code, it does not suffer from the same robustness limitations as the coupled Newton’s method. In this work, we will implement this solver in NASA’s OpenMDAO framework and demonstrate its effectiveness using a CFD-based aeropropulsive model. The solver will contribute to the develop- ment of aeropropulsive design optimization and CFD-based design optimization methods with the ultimate goal of accelerating the design and integration of advanced propulsion systems.

Nonlinear Solvers↗