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NASA NTRSDate not supplied

Internal Layout of a Lunar Surface Habitat

NASA is currently developing concepts for sustained crewed missions to the lunar surface. Sustained missions will occur on annual basis for durations of 30 days or more. To house and support the crew, NASA is exploring the use of a lunar Surface Habitat. NASA relies on conceptual spacecraft design to assist in planning and mission analysis. A crucial component of this habitation design is the internal layout: the interior location of systems, workstations, crew quarters, etc. The purpose of this paper is to describe the process and resulting layout of a specific Surface Habitat design. This paper describes the SH’s hybrid inflatable structure then details the habitat’s interior layout. The proposed SH’s internal layout is depicted inside a hybrid inflatable structure using a low-fidelity CAD model. Multiple NASA references were consulted to determine the SH’s required functionality, minimal Net Habitable Volume, and minimal functional dimensions. These functions and volumes contribute to the placement and location of systems and spaces inside the habitat. In addition to functional volume, the layout includes systems and logistics placement. The resulting design will aid NASA in mission planning and further systems analysis.

Callie Burke↗

NASA NTRS2023

Low-Cost Testing in Representative Lunar Regolith Environment

Rapid prototyping and testing are key enablers of iterative designs common in early technology research and development. Testing in a dusty environment is critical to prepare the Cryogenic Magnetic Coupler for lunar operations. To enable early and iterative testing of dust mitigation concepts, a low-cost, low-fidelity representative lunar regolith environment was developed at the National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center (Edwards, California). Based on preliminary testing with this test setup, a similar setup may be of interest to universities and other entities looking to develop the capability to safely test relatively small-scale components with lunar regolith simulant. The development of this lunar regolith test chamber and results from preliminary testing are presented in this paper. Also discussed are further development strategies for the potential improvement of this setup.

Scott Stebbins↗

NASA NTRSDate not supplied

Propulsion-Airframe Integration for Conceptual Redesign of a Low-Boom Supersonic Transport

A low-boom supersonic transport was designed for a cruise Mach of 1.7 and 40 passengers. This low-boom aircraft, referred to as the Mach 1.7 40-PAX concept, was generated using computational fluid dynamics (CFD) based sonic boom analysis at the start of overland cruise (SOC). The engine for the Mach 1.7 40-PAX concept was designed using the Numerical Propulsion System Simulation (NPSS) and modeled as a flow-through nacelle for CFD analysis. To understand how the engine plume affects the undertrack ground signature, the Mach 1.7 40-PAX concept is redesigned using an aeropropulsive CFD simulation. A process is developed for approximation of the NPSS engine at SOC by a CFD engine for aeropropulsive CFD simulation. The generated CFD engine has the identical nozzle boundary conditions and approximately the same mass flow and thrust as those of the NPSS engine at SOC. Then, the configuration with the CFD engines is optimized to approximately restore the low-boom characteristics of the Mach 1.7 40-PAX concept. Finally, the CFD simulation data for the optimized concept with the CFD engines is used to calibrate the low-fidelity aerodynamic analyses for mission analysis of this concept. The cyclic dependency of the involved disciplinary analyses is resolved using an iteration method for a consistent coupling of the mission analysis, NPSS engine analysis, and low-boom redesign using the aeropropulsive CFD simulation. This low-boom redesign study is used as an example to demonstrate how the propulsion-airframe integration could be implemented for conceptual design of low-boom supersonic transports.

Low-boom supersonic transport↗

NASA NTRSDate not supplied

Propulsion-Airframe Integration for Conceptual Redesign of a Low-Boom Supersonic Transport

A low-boom supersonic transport was designed for a cruise Mach of 1.7 and 40 passengers. This low-boom aircraft, referred to as the Mach 1.7 40-PAX concept, was generated using computational fluid dynamics (CFD) based sonic boom analysis at the start of overland cruise (SOC). The engine for the Mach 1.7 40-PAX concept was designed using the Numerical Propulsion System Simulation (NPSS) and modeled as a flow-through nacelle for CFD analysis. To understand how the engine plume affects the undertrack ground signature, the Mach 1.7 40-PAX concept is redesigned using an aeropropulsive CFD simulation. A process for approximation of the NPSS engine at SOC by a CFD engine is developed. The generated CFD engine has the identical nozzle boundary conditions and approximately the same mass flow and thrust as those of the NPSS engine at SOC. Then, the configuration with the CFD engines is optimized to approximately restore the low-boom characteristics of the Mach 1.7 40-PAX concept. Finally, the CFD simulation data for the optimized concept with the CFD engines is used to calibrate the low-fidelity aerodynamic analyses for mission analysis of this concept. The cyclic dependency of the involved disciplinary analyses is resolved using an iteration method for a consistent coupling of the mission analysis, NPSS engine analysis, and low-boom redesign using the aeropropulsive CFD simulation. This low-boom redesign study is used as an example to demonstrate how the propulsion-airframe integration could be implemented for conceptual design of low-boom supersonic transports.

Low-boom supersonic transport↗

NASA NTRSDate not supplied

RApid Blade and Blade-Vortex InTeraction (RABBIT) GUI implementation via MATLAB Application Designer

Rotorcraft noise source identification and reduction is crucial to the emergence of the Urban Air Mobility (UAM) market. One key rotor noise source is Blade Vortex Interaction (BVI), caused by the rotor wake interacting with the rotor blades. The low-fidelity RApid Blade and Blade-Vortex InTeraction (RABBIT) tool was created to predict the location and characteristics of Blade-Vortex Interaction (BVI) noise. RABBIT enables engineers to quickly locate and understand designs or configurations that cause significant BVI noise. Furthermore, RABBIT can identify the time and location of blade overlap for coaxial rotors. RABBIT is not a general acoustic prediction tool, but instead utilizes vortex and wake parameters to visualize and predict only BVI noise. To date, RABBIT has been validated against CAMRAD II and ANOPP2/AARON for three NASA Revolutionary Vertical Lift Technology (RVLT) concept vehicles: the Quiet Single Main Rotor (QSMR), Side-by-Side, and Quadrotor. RABBIT has been shown to be a useful BVI prediction tool capable of visualizing BVI as a function of various parameters. Impulse factor and time rate of change of loading allows for a unique BVI prediction technique that provides information on impulse strength, location, and frequency. This presentation will highlight how MATLAB’s App Designer was utilized to enable users to navigate RABBIT easily and efficiently without prior experience with MATLAB or rotorcraft acoustics. RABBIT users can build and view rotors in real time with options to control blade chord, radius, phasing, and airfoil geometry. Furthermore, multiple rotors can be combined to create state-of-the-art multi-rotor vehicles or fleets. Editable tables, sliding bars, and push buttons were implemented within MATLAB’s App Designer for RABBIT’s GUI to allow engineers and designers to predict low order acoustic impact of BVI occurrences.

Natasha Lydia Schatzman↗

NASA NTRS2023

NDARC - NASA Design and Analysis of Rotorcraft: Theory - Appendix A

The NASA Design and Analysis of Rotorcraft (NDARC) software is an aircraft system analysis tool that supports both conceptual design efforts and technology impact assessments. The principal tasks are to design (or size) a rotorcraft to meet specified requirements, including vertical takeoff and landing(VTOL) operation, and then analyze the performance of the aircraft for a set of conditions. For broad and lasting utility, it is important that the code have the capability to model general rotorcraft configurations, and estimate the performance and weights of advanced rotor concepts. The architecture of the NDARC code accommodates configuration flexibility, a hierarchy of models, and ultimately multidisciplinary design, analysis, and optimization. Initially the software is implemented with low-fidelity models, typically appropriate for the conceptual design environment. An NDARC job consists of one or more cases, each case optionally performing design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance calculation, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. For analysis tasks, the aircraft description can come from the sizing task, from a previous case or a previous NDARC job, or be independently generated (typically the description of an existing aircraft). The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. For each component, attributes such as performance, drag, and weight can be calculated; and the aircraft attributes are obtained from the sum of the component attributes. Description and analysis of conventional rotorcraft configurations is facilitated, while retaining the capability to model novel and advanced concepts. Specific rotorcraft configurations considered are single-main-rotor and tail-rotor helicopter, tandem helicopter, coaxial helicopter, and tiltrotor. The architecture of the code accommodates addition of new or higher-fidelity attribute models for a component, as well as addition of new components.

NDARC↗

NASA NTRS2023

Computational Study of Vortex-Induced Separation for a 5-Bladed Rotor

This work computationally investigated the rotor blade vortex-induced separation recently observed during an aerodynamic rotor test campaign in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel. Two separate approaches (i.e., airfoil modification and blade tip modification) were studied to mitigate the vortex-induced separation. Low-fidelity tools based on blade element momentum theory were shown to mispredict the rotor inflow and were also shown to not capture the vortex-induced separation caused by perpendicular blade-vortex interaction. This misprediction was exploited to isolate the aerodynamic thrust deficit caused by the vortex-induced separation (i.e., 20%) from the thrust deficit due to inflow variation (i.e., 31%). High-fidelity tools were shown to reasonably predict aerodynamic forces within 13% and flow separation when compared to experimental results. The modified airfoil variant of the baseline rotor effectively mitigated the vortex-induced separation while the blade tip modified variant still showed separation, though the size and strength of the vortex was reduced. Acoustic predictions were underpredicted by 10 dB from preliminary measurements taken in the untreated wind tunnel. Broadband noise contributions from different rotor blade sections showed that self-noise due to flow separation and other turbulent boundary layer mechanisms was the dominant noise source for all three rotor cases, followed by blade-wake interaction noise caused by perpendicular blade-vortex interactions.

aerodynamics↗

NASA NTRSDate not supplied

The Containment Assurance Risk Framework of the Mars Sample Return Program

The Mars Sample Return campaign aims at bringing rock and atmospheric samples from Mars to Earth through a series of robotic missions. These missions would collect the samples being cached and deposited on Martian soil by the Perseverance rover, place them in a container, and launch them into Martian orbit for subsequent capture by an orbiter that would bring them back. Given there exists a non-zero probability that the samples contain biological material, precautions are being taken to design systems that would break the chain of contact between Mars and Earth. These include techniques such as sterilization of Martian particles, redundant containment vessels, and a robust reentry capsule capable of accurate landings without a parachute. Requirements exist that the probability of containment not assured of Martian-contaminated material into Earth’s biosphere be less than one in a million. To demonstrate compliance with this strict requirement, a statistical framework was developed to assess the likelihood of containment loss during each sample return phase and make a statement about the total combined mission probability of containment not assured. The work presented here describes this framework, which considers failure modes or fault conditions that can initiate failure sequences ultimately leading to containment not assured. Reliability estimates are generated from databases, design heritage, component specifications, or expert opinion in the form of probability density functions or point estimates and provided as inputs to the mathematical models that simulate the different failure sequences. The probabilistic outputs are then combined following the logic of several fault trees to compute the ultimate probability of containment not assured. Given the multidisciplinary nature of the problem and the different types of mathematical models used, the statistical tools needed for analysis are required to be computationally efficient. While standard Monte Carlo approaches are used for fast models, a multi-fidelity approach to rare event probabilities is proposed for expensive models. In this paradigm, inexpensive low-fidelity models are developed for computational acceleration purposes while the expensive high-fidelity model is kept in the loop to retain accuracy in the results. This work presents an example of end-to-end application of this framework highlighting the computational benefits of a multi-fidelity approach.

Giuseppe Cataldo↗

NASA NTRS2013

X-HAB: Vertical Habitability Layout and Fabrication Studies - Voronoi Algorithmic Space Transport (VAST)

The final presentation of the California Polytechnic State University's Vertical Habitability Layout and Fabrication Studies, a vertical habitat. The goals of the project are: - Design the interior of a vertical habitat, with a well-documented link back to the process of design (continuing the work completed the first quarter, with parametrically-derived volumes, internal layout, etc.). - A full-size low-fidelity 3-D spatial (mockup of the vertical habitat.

Michael Fox↗

NASA NTRS2023

Python Based Plume Dynamics Estimation Tool (PyPDET) Rapid Plume Strike Analysis for RPOD Maneuvers in Deep Space Operations

I worked as a NASA Intern during the Summer 2023 term in the DS-00 division under the supervision of my mentor, Dr. Jonathan Pitt. Our goal was to build on our previous work from 2022 to develop a plume strike estimation tool using a prescribed physics methodology and model plume impingement effects while considering the dynamics of a rendezvous, operations, proximity, and docking (RPOD) maneuver. This tool supports previously configured CFD-DSMC calculations by allowing for rapid analysis of initial designs using a low-fidelity source flow model. Engineers can then use the high-fidelity CFD-DSMC tool to consolidate results as they work towards finalizing a design. This year’s project was focused on developing a software application that other engineers would be using in their analysis. Thus, the user’s experience was considered in the development of this application. Proper documentation, testability, and modularity of the codebase was our priority. For example, the project included auto documentation procedures to start building towards a User Manual, while also including dedicated demonstration cases for more explicit communication of functionality. Also, this project included a framework for testing the source code for future developments. Additionally, care was taken to develop the code using an Object-Oriented Programming approach. Thus, allowing for a modular extensibility of functionality in anticipation of future developments. The core work of this project was developing an algorithm that would transform the visiting vehicle and associated thruster data according to the kinematics described in the jet firing history. It would then calculate the estimated plume strikes on two of the target vehicles and write data accordingly into a VTK file. Summer work is to conclude by developing and presenting a PowerPoint slide deck at the intern exit briefing on August 11 th , 2023. Once the model for simple plume strike calculations is developed and tested there are several avenues to explore to continue development of this tool. These are also discussed in this report.

Plume Impingement↗

NASA NTRSDate not supplied

Aerodynamic Implications of Aerocapture Systems for Uranus Orbiters

Exploration of the Ice Giants, Uranus in particular, has been indicated as the highest priority new flagship-class mission by the 2022 Planetary Science Decadal Survey. However, due to it’s location in the solar system, extensive travel time and resources are required for a mission to reach Uranus. Aerocapture offers shorter interplanetary transit times and reduced propellant requirements for such a mission when compared to a traditional propulsive-capture orbiter. Considerations for the aerodynamics of an aerocapture system enabling flagship-class science mission to Uranus are presented. The applicability of a low lift-to-drag entry vehicle aeroshell with flight heritage to a new planet and atmosphere is evaluated. A preliminary aerodatabase is formulated from low-fidelity methods and heritage flight mission data to provide initial estimates of trajectory space to be considered for inserting a spacecraft into orbit at Uranus using aerocapture. Computational fluid dynamics calculations in the free molecular, transitional, and continuum regimes using Direct Simulation Monte Carlo and Navier-Stokes solutions are used to assess the validity of this preliminary aerodatabase. The considered entry vehicle is found to varying levels of agreement with work done by previous flight missions when evaluated for flight in Uranus’ atmosphere. Implications for the aerodynamics of this vehicle as applied in an aerocapture system in flight at Uranus as found by the current work are discussed.

Eli R. Shellabarger↗

NASA NTRSDate not supplied

Aerodynamic Implications of Aerocapture Systems for Uranus Orbiters

Exploration of the Ice Giants, Uranus in particular, has been indicated as the highest priority new flagship-class mission by the 2022 Planetary Science Decadal Survey. However, due to it's location in the solar system, extensive travel time and resources are required for a mission to reach Uranus. Aerocapture offers shorter interplanetary transit times and reduced propellant requirements for such a mission when compared to a traditional propulsive-capture orbiter. Considerations for the aerodynamics of an aerocapture system enabling flagship-class science mission to Uranus are presented. The applicability of a low lift-to-drag entry vehicle aeroshell with flight heritage to a new planet and atmosphere is evaluated. A preliminary aerodatabase is formulated from low-fidelity methods and heritage flight mission data to provide initial estimates of trajectory space to be considered for inserting a spacecraft into orbit at Uranus using aerocapture. Computational fluid dynamics calculations in the free molecular, transitional, and continuum regimes using Direct Simulation Monte Carlo and Navier-Stokes solutions are used to assess the validity of this preliminary aerodatabase. The considered entry vehicle is found to varying levels of agreement with work done by previous flight missions when evaluated for flight in Uranus' atmosphere. Implications for the aerodynamics of this vehicle as applied in an aerocapture system in flight at Uranus as found by the current work are discussed.

Uranus↗

NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗

NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Ben Phillips↗

NASA NTRSDate not supplied

RApid Blade and Blade-Vortex InTeraction (RABBIT) Reimagined: Algorithm Improvement and User-Friendly Interface Implementation

Rotorcraft noise source identification and reduction is crucial to the emergence of the Urban Air Mobility (UAM) market. One key rotor noise source is Blade Vortex Interaction (BVI), caused by the rotor blades interacting with the rotor wake. The low-fidelity RApid Blade and Blade-Vortex InTeraction (RABBIT) tool was created to predict the location and characteristics of BVI noise. RABBIT enables engineers to quickly design and simulate UAM configurations and understand BVI occurrences for a desired flight condition. Furthermore, RABBIT can also identify the time and location of blade overlap for coaxial rotors. RABBIT is not a general acoustic prediction tool, but instead utilizes vortex and wake parameters to visualize and predict BVI aerodynamics. RABBIT algorithm has been further developed including reduction of computational time, accounting for BVI source time arrival, improved vortex strength modeling, and BVI impulse factor. A user-friendly app is presented with the intent of bringing RABBIT to the masses to allow engineers from various educational backgrounds to design and begin to understand BVI. Furthermore, RABBIT capabilities are highlighted by a parameter study highlighting key parameters that impact BVIalong with highlighting RABBIT’s ability to identify BVI occurrences from other rotors.

RApid↗

NASA NTRS2024

Design of an In-Slot Cooled Air-Core Flux-Focusing Permanent Magnet Synchronous Machine for Electric Aircraft Applications

High performance and reliable permanent magnet synchronous machines are potentially a key technology for enabling reduced emissions in future generations of sustainable aircraft. In this paper, a novel air-core flux focusing permanent magnet synchronous machine with carbon fiber shafting for aviation applications is presented. A low-fidelity analytical sizing tool is detailed for the motor topology. The sizing tool is used to explore design trades and create an example 100 kW flux-focusing motor for eVTOL applications. Higher fidelity finite element analysis was used to validate the predicted performance of the motor. The selected design is able to achieve roughly 97 percent efficiency and 6 kW/kg at a continuous operating power of 100 kW.

Jonathan Gutknecht↗

NASA NTRSDate not supplied

Global Sensitivity Analyses for Test Planning with Black-Box Models for Mars Sample Return

This work describes sensitivity analyses performed on complex black-box models used to support experimental test planning under limited resources in the context of the Mars Sample Return program, which aims at bringing to Earth rock and atmospheric samples from Mars. We develop a systematic workflow that allows the analysts to simultaneously obtain quantitative insights on key drivers of uncertainty, on the direction of impact, and the presence of interactions. We apply novel optimal transport-based global sensitivity measures to tackle the multivariate nature of the output. On the modeling side, we apply multi-fidelity techniques that leverage low-fidelity models to speed up the calculations and make up for the limited amount of high-fidelity samples, while keeping these in the loop for accuracy guarantees. The sensitivity analysis reveals insights useful for the analysts to understand the model's behavior and identify the factors to focus on during testing in order to maximize the value of information extracted from them to ensure mission success when limited resources are available.

Giuseppe Cataldo↗

DOE OSTI2024

Multi-Fidelity Modeling and Control for Building Temperature Control

The ability to control energy loads such as a building's heating, ventilation, and air conditioning (HVAC) system can help facilitate increased penetration of variable renewable energy sources into the electric grid. To be able to control these HVAC systems more effectively, detailed simulations of the corresponding building physics is becoming increasingly important. These detailed simulations can be complex, nonlinear, and can require immense computational power when used in an advanced control method such as model predictive control (MPC), prompting the need to explore less computationally intensive strategies. In this work, a multi-fidelity approach is proposed to combine samples from a complex, high-fidelity model with a simple, low-fidelity model within the MPC control loop. More specifically, the parameters of a reduced-order, linear building model are periodically updated with knowledge from its high-fidelity counterpart - an EnergyPlus model - in an online fashion using a Gaussian Process surrogate model. Hence, highly accurate predictions of current and future conditions in a building are maintained with a substantially reduced computational burden compared to using the high-fidelity models alone. In other words, this linear parameter varying model preserves the low computational requirements of a low-order linear model while accurately modeling a building's dynamics. This allows a building controller to take highly informed actions without requiring a large computational budget.

building modeling↗