Nicholas Peters | Search NASA

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VTOL Analysis for Emergency Response Applications (VAERA) - Identifying Technology Gaps for Wildfire Relief Rotorcraft Missions

The mission of VAERA (VTOL Analysis for Emergency Response Applications) is to enable the design, development, and analysis of emergency response rotorcraft for different disaster scenarios. The project’s current focus is on improving crewed and uncrewed rotorcraft for wildfire relief efforts. This paper presents background information on the current state of the art for wildfire-fighting crewed and uncrewed rotorcraft, current wildfire operations, handling and flying qualities considerations of similar vehicles, and the limitations of uncrewed sub-1000 lb commercial off the shelf (COTS) rotorcraft that could be (and sometimes are) used for different wildfire missions. Technology gaps that are currently limiting rotorcraft firefighting capabilities are identified using the background information, and a plan of how to address each of the identified technology gaps is presented. In this paper, the key technology gaps identified for rotorcraft in the wildfire environment include: poor performance and handling/flying qualities, inadequate or nonexistent categorization of handling qualities, unvalidated flight dynamics turbulence modeling approaches, and inadequate subsystems for wildfire missions. While numerous concerns for rotorcraft operating in the wildfire environment exist, this paper focuses on those issues that are either not being addressed by others, or that require more attention. The goals of this paper are to both educate the public on critical technology gaps for wildfire-fighting rotorcraft that have not gained significant traction in the public domain, and to explain the work required to address those technology gaps.

VTOL↗

NASA NTRSDate not supplied

Utilizing Advanced Air Mobility Rotorcraft Tools for Wildfire Applications

Over the past decade, due in large part to heavy investment in the field of Advanced Air Mobility (AAM), significant progress in rotorcraft-focused modeling tools has been made. Such progress has notably increased AAM rotorcraft modeling capabilities in the topics of conceptual design, preliminary design, and more recently flight dynamics. Yet, due to recent and persistent increases in extreme weather events, an emerging interest has been raised in utilizing such modeling capabilities for aiding in emergency relief efforts and other public good missions. This paper uses wildfire fighting as a representative public good mission and demonstrates the relevance of the NASA Revolutionary Vertical Lift Technology (RVLT) rotorcraft toolchain to such missions. An emphasis is placed on flight dynamics modeling and control because of the hazards and challenges associated with the atmospheric environment of wildfires. In this work, the NASA FlightCODE tool was used to analyze both a UH-60 and the NASA six-passenger quadcopter reference model hovering in an experimentally informed wildfire turbulent environment. Preliminary results of this study estimate actuator usage exceedances and disturbance rejection capabilities of the vehicles’ translational rate command systems. Leveraging the RVLT toolchain, refinement and expansion of this work could lead to handling qualities envelope estimation and design optimization for wildfire turbulent environments. This would provide pilots with additional information to make real-time decisions in high-risk scenarios and begins preparations for simulating these dangerous environments for pilot training and experimentation.

Rotorcraft↗

NASA NTRSDate not supplied

Utilizing Advanced Air Mobility Rotorcraft Tools for Wildfire Applications

Over the past decade, due in large part to heavy investment in the field of Advanced Air Mobility (AAM), significant progress in rotorcraft-focused modeling tools has been made. Such progress has notably increased AAM rotorcraft modeling capabilities in the topics of conceptual design, preliminary design, and more recently flight dynamics. Yet, due to recent and persistent increases in extreme weather events, an emerging interest has been raised in utilizing such modeling capabilities for aiding in emergency relief efforts and other public good missions. This paper uses wildfire fighting as a representative public good mission and demonstrates the relevance of the NASA Revolutionary Vertical Lift Technology (RVLT) rotorcraft toolchain to such missions. An emphasis is placed on flight dynamics modeling and control because of the hazards and challenges associated with the atmospheric environment of wildfires. In this work, the NASA FlightCODE tool was used to analyze both a UH-60 and the NASA six-passenger quadcopter reference model hovering in an experimentally informed wildfire turbulent environment. Preliminary results of this study estimate actuator usage exceedances and disturbance rejection capabilities of the vehicles’ translational rate command systems. Leveraging the RVLT toolchain, refinement and expansion of this work could lead to handling qualities envelope estimation and design optimization for wildfire turbulent environments. This would provide pilots with additional information to make real-time decisions in high-risk scenarios and begins preparations for simulating these dangerous environments for pilot training and experimentation.

Rotorcraft↗

NASA NTRSDate not supplied

On the Application of an Actuator Line Model for Rotorcraft Outwash Predictions

As the next generation of Vertical Take-Off and Landing (VTOL) vehicles develops and the VTOL industry makes significant progress in utilizing them for public transportation, it is crucial to have validated and cost-effective computational models accessible to both industry professionals and academics in the rotorcraft community. This study investigates the implementation of a new actuator line model within NASA’s OVERFLOW computational fluid dynamics (CFD) solver, with a focus on predicting rotorcraft outwash. This reduced-order rotor model was developed to provide reasonably accurate outwash predictions while reducing computational costs compared to traditional blade-resolved CFD simulations. To validate the actuator line model for outwash predictions, the model was compared against existing experimental data across three validation cases: single rotor Out-of-Ground Effect (OGE), single rotor In-Ground Effect (IGE), and tandem rotor IGE. All three cases were based on the rotor geometry and configuration of the CH-47D. To evaluate the feasibility and advantages of using an actuator line model for outwash predictions the results were compared to a series of high-fidelity blade-resolved CFD simulations as well as comprehensive analyses simulations based on CHARM predictions. The results of this study demonstrate the feasibility of leveraging this new actuator line model for reasonably accurate outwash predictions. The outwash results obtained from the actuator line model closely matched those from high-fidelity blade-resolved simulations while significantly reducing the overall computational costs of the simulations. Results from this study further demonstrated the feasibility of using CHARM for efficient, and reasonably accurate time-averaged outwash predictions for multi-rotor configurations.

CFD↗

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PALMO: An OVERFLOW Machine Learning Airfoil Performance Database

The OVERFLOW Machine Learning Airfoil Performance (PALMO) database has been created to enable robust modeling of airfoil performance in a variety of applications. The PALMO database uses OVERFLOW simulation data second-order accurate in time and fourth-order accurate in space with Spalart-Allmaras turbulence closure. The foundation of the in-development PALMO database is the airfoil base cube. Each base cube includes simulation data parametrized over a range of Mach numbers, Reynolds numbers, and angles-of-attack. This database includes the NACA 4-series airfoils, with parametrization in airfoil thickness and camber from an NACA 0006 to an NACA 4424. In total, 52,480 NACA 4-series OVERFLOW calculations were run on the NASA High-End Compute Capability (HECC) supercomputer. This provides high-order-accurate simulation data covering a wide range of aerospace design applications, which enables users to develop accurate airfoil performance look-up tables without additional high-performance computing. In addition to engineering design and analysis of aerospace vehicles, PALMO is well suited to be a benchmark dataset for the development and testing of machine learning methods in aerospace engineering. This work presents an example PALMO surrogate model that enables accurate airfoil performance predictions for any arbitrary combination of camber, thickness, Mach number, Reynolds number, and angle of attack within the bounds of the database. Airfoil performance tables predicted for an airfoil not used in training the model are used in three-dimensional OVERFLOW simulations to quantify the downstream accuracy on aggregate rotor performance metrics. For the NACA 3415 airfoil, which had no common thickness or camber with the training data, the surrogate predicted and CFD generated tables were within 2.1% of each other in the forward flight lift to drag metric. This suggests that performance tables generated for airfoils within the bounds of the PALMO database will yield aggregate rotor performance predictions on par with tables generated from directly running OVERFLOW airfoil calculations. The PALMO airfoil performance coefficients are available publicly.

Database↗