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NASA NTRSDate not supplied

Lunar Payloads to Constrain Exospheric Water through the NASA M-STAR program

Our understanding of water cycles on the Moon has significantly enhanced recent observations by Chang E-5, Lunar Prospector, and Chandrayaan-1 missions indicating the existence of an active water cycle on the Moon. In a new partnership between Delaware State University (DSU) and NASA Goddard Space Flight Center, enabled through the NASA’s M-STAR (MUREP Space Technology Artemis Research) program, we are developing low mass and power lunar rover payloads to enable long-duration human exploration missions. Payload technologies include wavelength modulation absorption spectroscopy to simultaneously detect water (H16OH) and isotopes (H16OD) in the (6700 nm) mid-infrared region using a closed path in compact Herriot cell optical design and wavelength modulation spectroscopy, and (2) Laser-induced breakdown spectroscopy (LIBS) to simultaneously detect and correlate water isotopes with characteristics elemental composition of lunar regolith. Due to the airless atmosphere of the Moon, we will utilize Artificial intelligence (AI) and Machine learning (ML) approaches to discriminate spectral interference with instrument drifts and correlate mid-IR trace gas profile with LIBS spectral information. This partnership will initiate a STEM engagement space program, e.g., Lander and CubeSat payload technology development for students and the next-generation NASA workforce for future lunar and Mars missions. DSU, a Historically Black University, prides itself in its proven excellence in teaching and research. It enrolls a diverse population of students (~5000) traditionally underrepresented in STEM disciplines. DSU has established itself at the forefront of optics and photonics research that transcends multidisciplinary fields of earth sciences, environmental, defense, and biomedical sensing applications.

water cycles↗

NASA NTRSDate not supplied

Conceptual Design of the Hybrid-Electric Subsonic Single Aft Engine (SUSAN) Electrofan Transport Aircraft

This paper presents an update to the conceptual design of NASA’s Subsonic Single Aft Engine (SUSAN) Electrofan transport aircraft—a 180 passenger, Mach 0.785 hybrid-electric regional jet with an economy range of 750 nmi and a design range of 2,500 nmi. The concept employs a series hybrid-electric powertrain driven by a fuel-burning aft fuselage propulsor that is connected to Megawatt-class power generators to convert additional mechanical shaft power to electric power. This electric power is used to support wing-mounted electric propulsors. The aft fuselage turbofan leverages boundary layer ingestion (BLI) and is designed to deliver 35% of the total aircraft thrust, while the wing propulsors assume underwing distributed electric propulsion (DEP) arrangements and are responsible for the remaining 65% thrust. Investigated in this work is the fuel burn performance of the SUSAN Electrofan when incorporating new weight and efficiency estimates for the power, battery, and thermal systems. An updated unified engine deck is also included, which accounts for the high effective bypass ratio made possible by the DEP systems and turbofan BLI effects to first order. Multidisciplinary design analysis and optimization (MDAO) is performed through an updated conceptual design environment, and comparisons are made to a Boeing 737 MAX 8-like reference aircraft performing similar missions, as well as a variant resized for 2,500 nmi.

CAS↗

NASA NTRS2023

Observing Ocean Ecosystem Responses to Volcanic Ash

Volcanic eruptions can be catastrophic events, particularly when they occur in inhabited coastal environments. They also play important roles in climate and biogeochemical cycles, including through nutrient deposition in the ocean. Volcanic ash studies in the ocean have focused on the phytoplankton response, generally quantifying changes in chlorophyll-a concentration. Many gaps remain in addressing fundamental questions regarding why volcanic ash deposition may enhance or limit both phytoplankton growth and/or drive community composition shifts. Here we outline a wide, multidisciplinary vision for monitoring volcanic eruptions near ocean ecosystems from satellites, including considerations for characteristics of airborne volcanic ash and ash geochemistry in seawater. Ultimately, observations beyond chlorophyll-a are needed to quantify phytoplankton communities (including harmful algal blooms) and possible impacts across higher trophic levels. We synthesize relevant research from volcanic studies as well as atmospheric and ocean sciences to identify the ‘known unknowns’ in ash-ecosystem studies. Our goal is to move toward an improved understanding of how real-time and near-real-time monitoring of volcanic eruptions can help address societally relevant questions.

volcano↗

NASA NTRSDate not supplied

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗

NASA NTRSDate not supplied

Statistical Practice and Research at NASA

The discipline of statistics has gained recognition within NASA by spurring innovation and efficiency, and it has demonstrated significant impact and value. In aerospace research and development, it accelerates learning, maximizes knowledge, ensures strategic resource investment, and informs rigorous data-driven decisions. In practice, it requires immersive multidisciplinary collaboration to develop solution strategies that integrate statistical methods with subject-matter expertise to address challenging research objectives. This presentation provides an overview of statistical case studies in aeronautics, space exploration, and atmospheric science, and it highlights statistical research motivated by NASA’s challenging applications.

Peter A. Parker↗

NASA NTRS2024

Earth-Independent Medical Operations (EIMO) Concept of Operations (ConOps)

Compared to the current paradigm for crew health in low-Earth orbit and Lunar missions that rely on constant communication with Mission Control, there is an anticipated shift in medical operations for deep-space exploration missions. This shift stems from mission constraints imposed by the considerable distance from Earth, which include resource limitations due to a lack of resupply, mass, power, volume, and data limitations, challenges imposed by communication latency and the inability to evacuate in case of emergencies. To transition towards a more self-reliant medical approach, a comprehensive strategy is essential to progressively enable crew autonomy and mitigate mission success risks in the challenging environment of space. This transformative shift is collectively referred to as "Earth-Independent Medical Operations" (EIMO), signifying the gradual transfer of medical care and decision-making from terrestrial resources to space-based assets. This transition is aimed at bolstering astronaut health and performance while simultaneously reducing the overall risks associated with space missions. The constraints related to EIMO necessitate an integrated development of medical systems, featuring interoperability with mission planning, vehicle design, spacesuit design, and data architecture. This integration is vital in establishing a robust medical infrastructure that not only supports the well-being of astronauts but also ensures the success of the mission as a whole. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a model-based Concept of Operations (ConOps) outlining an initial vision for EIMO. Within this ConOps, a comprehensive view is presented, encompassing stakeholder needs, system objectives, and system goals associated with EIMO. Additionally, it provides illustrative examples of the various activities (scenarios) for which the system will be employed during missions. The selection of these activities has been meticulous, aiming to encompass a wide spectrum of medical conditions, including those falling under different risk categories, such as low-likelihood-low-consequence, low-likelihood-high-consequence, and high-likelihood-low-consequence. The selection of these activities (scenarios) effectively encompasses the wide range of medical events situated within an assumed probability-consequence bell curve. In each scenario, at least one of the five main EIMO components identified is captured. Those EIMO components are: Pre-mission Planning, Acute and Emergent Management Decision Making, Prolonged Medical Management Decision Making, Supplies and Resource Management, and Task Load Management. The ConOps was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA and aims to serve as an initial recommendation to gradually and safely enabling crew autonomy for Mars missions and beyond.

Earth Independent Medical Operations↗

NASA NTRS2024

3D Printed Materials Characterization for Rapid Prototyping and Plant Growth

Through KSC IRTD funding in 2022, this project brought a list of 18, 3D printed filaments into formal characterization testing to provide a reference for their behaviors under relevant applications. The project format set up a series of tests to expose 3D printed specimens. A total of 1,989 individual 3D printed test specimens were sent across KSC to be scrutinized by three laboratories to fulfill a multidisciplinary assessment of each material TRL. Testing started with 18 materials. Initially, seed germination assays in the PPA, sample materials were enclosed in petri dishes with lettuce seeds on damp germination paper. No significant impacts on lettuce seed germination were observed in this testing. Next, sample coupons were printed and sent for materials testing to the KSC Analysis/Mechanical and Environmental Testing Laboratory, where they were subjected to 14- and 30-day soak periods in solutions used to provide nutrients to plants or to sanitize hardware before and after use. Following a long soak typical of a 30-day plant growout in Hoagland’s solution, 14 materials gained more than 10% of their own mass. This indicated an increased potential for leaching or providing conditions that are not food safe. Materials that exceeded 15% absorption by mass were eliminated from further testing. Based off this result, the team continued with a core list of nine filaments to fulfill Tensile, Flexural, Biofilm formation, and plant growth testing. Those materials were PLA (Raise3D), ABS (Raise3D), PETG (PolyethyleneTerephthalate Glycol) (Raise3D), ASA (Acrylonitrile Styrene Acrylate) (Raise3D), PC (Polycarbonate) (Raise3D), TPU (Thermoplastic polyurethane)-95 (Raise3D), PLA Copper (Gizmodorks), PP (Polypropylene) (Braskem), and HIPS (High Impact Polystyrene) (Gizmodorks). Testing also quantified the spectral impact of using different color 3D printed surfaces in a growth chamber. The material used for spectral testing was PLA. Printing employed a standard surface texture representative of all materials. It was shown through Tensile Testing (ASTM D638-22) that the breaking force of a 3D printed part greatly varied depending on layer orientation. This is common through all materials, and demonstrates that the strength of a 3D printed component can be maximized by layering the material normal to the primary force on the part. Four-point flexural testing (ASTM D790) provided quantities of interest, Flexural modulus, Flexural strength, Flexural stress, and strain at break within a 5% strain limit from each of nine materials. Biofilm formation testing was conducted in the Molecular and Microbiological Laboratory. Testing completed on specimens from each material showed equal formation on the surface. Additional plant growth testing was conducted in the PPA beyond the initial germination testing. The final assessment documents that three materials (PLA, ABS, and PC) have reached TRL 6 through extensive testing, and ultimate end-to-end applied use in experimental or testing conditions (flight and ground). TRL 5 materials (ASA, TPU-95, PLA Copper, PP, PETG, and HIPS) have all been successfully applied in Research and Development for crop growth applications and are ready to be applied in formal testing. TRL 4 materials Nylon910, PLA Carbon Fiber, PPA CF, PPA Glass Fiber (GF), NinjaFlex, and P-filament 721 are materials that were able to be printed and tested, but have yet to show data meeting applied requirements. TRL 3 NylonX, Flex TPE-185, and Nylon were unable to be reliably printed to fulfill testing. These results provide researchers with reference for materials to use during plant growth experimentation, and also set a standard for future characterization work applying 3D printing and materials to testing, research, and experimentation.

Gioia Massa↗

NASA NTRSDate not supplied

Aviary: Open-Source Software Tool for Optimizing Next-Generation Aircraft Designs

Existing aircraft design tools are limited in their ability to provide meaningful trends for hybrid-electric & all-electric aircraft. Aviary is an open-source software tool that modernizes legacy design tools and enables multidisciplinary analysis and optimization of unconventional vehicles like X-66A. Aviary has the potential to revolutionize aircraft analysis by making aircraft conceptual designs more efficient.

Jennifer Gratz↗

NASA NTRSDate not supplied

Overview of the Subscale RAVEN Flight Controls and Modeling Testbed

The Research Aircraft for eVTOL Enabling TechNologies (RAVEN) Subscale Wind-Tunnel and Flight Test (SWFT) model is a subscale aircraft built for flight dynamics and controls research demonstrated in wind-tunnel and flight-test experiments. The intent of this paper is to provide a summary of past, current, and future efforts being pursued by the RAVEN-SWFT project. Initially, vehicle development guidelines were crafted by a multidisciplinary team to ensure that the RAVEN-SWFT vehicle was well suited for research in multiple areas, including aero-propulsive modeling, flight controls, and autonomy, among others. The vehicle has been used to obtain extensive wind-tunnel data, enabling aero-propulsive model development across the transition flight envelope and validation of computational tools. The vehicle will be used to conduct flight testing in order to evaluate modeling strategies and flight control logic. The RAVEN-SWFT model also serves as a risk reduction activity for a conceptual, full-scale vehicle in the 1000-lb class. The next steps in the project are to successfully demonstrate free flight in hover, transition, forward flight, and the reverse thereof, utilizing custom control laws integrated onto the RAVEN-SWFT avionics hardware. The project intends to publicize all of the geometry, data, and methods in future reports.

eVTOL↗

NASA NTRSDate not supplied

Outfitting the In-Space Manufacturing Advancement Center (ISMAC)

Marshall Space Flight Center has begun investment into a new collaborative workspace where ISM technologies can be advanced utilizing multidisciplinary teams. Equipment has been commissioned to explore ISM technologies related to electronics, welding, additive manufacturing, recycling, and metal extraction from Lunar or Martian regolith. This is an overview of the latest capabilities outfit to the new In-Space Manufacturing Advancement Center.

In-Space Manufacturing↗

NASA NTRSDate not supplied

Aerodynamic Design Optimization for Natural Laminar Flow Airfoils

Natural laminar flow technology is a passive laminar flow control (LFC) strategy that seeks to delay the onset of boundary-layer transition (BLT) through shape optimization to reduce the drag of the aerodynamic vehicle. Adjoint-based design optimization for LFC is proposed in an integrated multidisciplinary framework, which includes the computational fluid dynamics (CFD), geometry and grid deformation, and linear stability analysis (LSA) for transition prediction. In particular, the BLT location is predicted using the dual N-factor method that is based on a linear stability theory (LST) eigenvalue problem. The dual N-factor criterion accounts for the amplification of planar Tollmien-Schlichting (TS) and stationary crossflow (CF) boundary-layer instabilities to predict the transition location in three-dimensional boundary-layer flows. The adjoint-based shape optimization procedure is based on an iteratively coupled CFD and LSA methodology to converge the transition location and flow solutions, as well as to calculate the sensitivities of the aerodynamic metrics of interest with respect to the flow and shape design parameters. The RAE 2822 airfoil at 0 and 30 degrees yaw angles, an angle of attack of 0.72 degrees, and subsonic conditions (M∞ = 0.19, Rec = 5.6 × 106 ) are used as baseline configurations for design optimization. The angle of attack and the vertical displacement of free-form-deformation control points are used as design variables to reduce the drag coefficient while reaching a specified lift coefficient. The optimized unswept airfoil designs achieve a 30% drag reduction accompanied by a downstream shift of the transition locations over both suction and pressure sides of the airfoil. The initial design iterations for the swept case also show a favorable trend in the drag reduction with transition delay over both sides.

Transition↗

NASA NTRSDate not supplied

Commercially-viable Hydrogen Aircraft for Reduction of Greenhouse Emissions

NASA assembled a cross-organizational multidisciplinary “radical” project team combining a diverse set of skills including aircraft architecture modelling and optimization, advanced material science, and engineering of high performance cryogenic, thermal management and fuel cell systems components and subsystems to tackle the challenging problem of development of commercially viable mid-size aircraft that would radically transform air transportation. Our team is developing an integrated conceptual and experimental methodology to realize a medium-range hydrogen aircraft design based on fuel cells, hydrogen burning engines, advanced power management and distribution, cryogenic hydrogen storage systems, and novel thermal management systems combined with an integrated aircraft concept of operations both during the flight and at the airports. The resulting analyses suggested the aircraft architecture options, sizes and layouts for the propulsion subsystem and cryogenic liquid hydrogen (LH2) tankage to verify the weight-scaling relationships for a medium-range aircraft carrying 100-200 passengers flying 1000 - 5000 km. Hydrogen - based distributed electric propulsion and cryogenic systems were further analysed, and more detailed study identified systems goals for a viable overall system weight for missions of various lengths. The developed aircraft architecture is being optimized by total specific energy density, specific power, size and mission profiles.

aircraft architecture↗

NASA NTRSDate not supplied

Commercially-viable Hydrogen Aircraft for Reduction of Greenhouse Emissions

aircraft architecture↗

NASA NTRSDate not supplied

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

The purpose of this paper is to extend previously demonstrated methodologies for design under uncertainty, leveraging analytical gradients to higher fidelity analysis for use in conceptual aircraft design. Previous work developed methods to generate analytical derivatives through polynomial chaos expansion, eliminating the need to estimate derivatives via complex step or finite difference. In this research, the authors build upon the methods to include physics-based aircraft design codes for aircraft design under uncertainty. This extends the previous work’s case study, which employed analytical aerodynamics and Breguet range estimations for wing design, to a higher fidelity level. In addition, this work extends previous work on interface development between the Uncertainty Quantification with Polynomial Chaos Expansion (UQPCE) software and Model-Based Systems Analysis and Engineering (MBSA&E) frameworks. This paper will discuss the development work necessary to perform multidisciplinary design under uncertainty as well as demonstrate the mechanics of interfacing UQPCE and conceptual aircraft design tools such as NASA’s Aviary code. In a case study, a conceptual aircraft design under uncertainty was conducted and compared against a traditional deterministic design. When given information about the uncertainty space from UQPCE, the optimizer was able to shape the output distribution and produce a more robust design

UQ↗

NASA NTRSDate not supplied

The Satellite Needs Working Group (SNWG) Biennial Survey: Analyzing Satellite Earth Observation Needs Across U.S. Federal Civilian Agencies

The Satellite Needs Working Group (SNWG) is part of the U.S. Group on Earth Observations (USGEO) and was established to identify high-priority Earth observation satellite needs across U.S. federal civilian agencies. Federal agencies often rely on Earth observation data to fulfill multidisciplinary agency responsibilities such as assessing agricultural crop conditions, detecting wildfires, and monitoring water quality; however, the data sets and tools required to meet these needs are not always readily available or accessible to agency personnel. SNWG conducts a biennial survey of federal satellite needs in order to bridge the gap between Earth observation data providers and their government stakeholders and users. The SNWG Management Office completes an analysis of these survey submissions to gain insight into the types of satellite needs that exist across the government. Within the survey, agencies provide details on how satellite data are used to meet their objectives, measurement requirements needed for their use cases, and gaps that exist in currently available satellite data products and services. For the SNWG 2024 cycle, there were 125 surveys submitted from 25 different agencies. This presentation will discuss findings from the statistical analysis of the SNWG 2024 survey responses and highlight the diverse nature of the needs, common themes in agency requests, and differences in the responses compared to previous cycles. The presentation will also discuss the newly approved SNWG Aggregate Statistics Report that will make these analysis results available to the public and help inform what’s next for science.

Essence Raphael↗

NASA NTRSDate not supplied

Sonic Boom Ground Noise Minimization Via the Adjoint Method

A multidisciplinary design optimization methodology to directly minimize the ground-level noise generated by the sonic boom of a high altitude supersonic body is presented. A Cartesian Euler flow solver is coupled with an atmospheric propagation tool to create a ground-noise analysis capability for supersonic bodies. Adjoint formulations for both the flow solver and propagation tool are also coupled to compute sensitivities of shape variations in the body in a highly efficient manner. A gradient-based optimizer is then introduced to forge a valuable design capability. Output-based mesh adaptation that is driven directly by ground-level noise is employed to increase accuracy and provide error estimation. The design method is demonstrated first on a simple axisymmetric body with few design variables to evaluate the efficacy of the optimization scheme. Guided by the results of this initial case, the problem is then repeated with somewhat different design variables to further demonstrate the capabilities of the design method. Finally, the method is applied to a real-world problem by optimizing control surface deflection settings of a low-boom aircraft to minimize ground noise while maintaining trimmed, level flight.

ARMD↗

NASA NTRSDate not supplied

Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients

UQ↗

NASA NTRSDate not supplied

Earth-Independent Medical Operations (EIMO) Concept of Operations

In contrast to the current crew health paradigm for low-Earth orbit and Lunar missions, which depends on real-time communication with Mission Control, deep-space exploration missions will require a significant shift in medical operations. This shift is driven by the constraints of operating at a considerable distance from Earth, such as resource limitations—lack of resupply, restricted mass, power, volume, and data—as well as communication delays and the inability to evacuate back to Earth during emergencies. To move toward a more self-reliant medical model, a strategy is needed to gradually increase space-based crew autonomy and reduce risks to mission success in the challenging environment of deep space. This transformative change, known as "Earth-Independent Medical Operations" (EIMO), explores the gradual transfer of medical care and decision-making from Earth-based support to space-based systems. The goal of this transition is to enhance astronaut health and performance while minimizing mission risks. EIMO requires the development of a medical system that integrates seamlessly with mission planning, vehicle and spacesuit design, and data architecture. This integration is crucial for building a robust medical infrastructure that not only safeguards astronaut well-being but also ensures overall mission success. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has revised the EIMO model-based Concept of Operations (ConOps) which outlines an initial vision for EIMO. The ConOps, which is built on the stakeholders’ need, system goals, and objectives (NGOs), presents an array of in-mission scenarios that span a wide range of medical conditions demonstrating the system’s capabilities from basic to complex events. Developed by a multidisciplinary team of systems engineers, scientists, and clinicians within ExMC, the ConOps revision includes two new scenarios(Barotrauma and Self-Medical Management and Behavioral Health and Chronic Medical Care), and implementation of findings from EIMO technical interchange meetings that focused on data and training. The envisioned EIMO Medical System (MS) operates as a system of systems, gathering data from various sources such as reference databases, real-time wearable sensors, point-of-care diagnostics, and environmental controls. The MS also incorporates advanced training tools to support autonomous medical care, assisting the Crew Medical Officer (CMO) during medical events where Ground Support is either unavailable or communication-delayed beyond practicality. Furthermore, MS functions and capabilities were decomposed from the scenarios to establish foundational requirements for EIMO and traced to the NASA Spaceflight Human-System Standard(NASA-STD-3001, Volumes 1 and 2). These traces were performed to gain insights on the alignment of EIMO requirements with the NASA standard. This work serves as an initial recommendation to increase crew autonomy gradually and safely for Mars missions and future deep-space exploration.

medical system↗