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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

2024 Nasa Lunabotics University Competition: Site Preparation With Bulk Regolith

Lunabotics provides accredited in-stitutions of higher learning students (vocational-technical, college, university) an opportunity to apply the NASA systems engineering process to design and build a prototype robot. This robot would be capable of performing the proposed operations on the Lunar sur-face in support of future Artemis mission goals. Lunabotics features a systems engineering design challenge to engage students in the next phase of hu-man space exploration supporting the Artemis missions. This two-semester event encourages students to design and build an autonomous or telerobotic robot designed to traverse the simulated Lunar surface and complete the assigned construction tasks. The number of teams accepted into this challenge is not predetermined but is based on the scores and overall quality of the Project Management Plans received and other factors.

Lunabotics↗
NASA NTRSDate not supplied

2024 Nasa Lunabotics University Competition: Site Preparation With Bulk Regolith

Introduction: Lunabotics provides accredited institutions of higher learning students (vocational-technical, college, university) an opportunity to apply the NASA systems engineering process to design and build a prototype robot. This robot would be capable of performing the proposed operations on the Lunar surface in support of future Artemis mission goals. Lunabotics features a systems engineering design challenge to engage students in the next phase of hu-man space exploration supporting the Artemis missions. This two-semester event encourages students to design and build an autonomous or telerobotic robot designed to traverse the simulated Lunar surface and complete the assigned construction tasks. The number of teams accepted into this challenge is not predetermined but is based on the scores and overall quality of the Project Management Plans received and other factors. The culmination of the Lunabotics virtual challenge will be the design, build and operation of a functional prototype Lunar robot. Teams are required to submit the following: (1) Project Management Plan, (2) Systems Engineering Paper, a (3) STEM Engage-ment Report, and a (4) Proof of Life Video. This is an optional item, but to qualify for the grand prize a team must also submit a: (5) Presentation and Demonstration. Background: The NASA Lunabotics University Competition was first held in 2010 as a follow on to the NASA Regolith Excavation Challenge [1]. The high level of interest and participation from over 50 universities each year has led to a sustained annual competi-ion cadence: it has been held every May for the past 14 years [2,3]. Over 6,000 students have participated and been inspired to pursue Science, Technology, En-gineering and Mathematics careers (STEM). 2024 Competition: The necessary lunar surface tasks are evolving to meet the NASA Artemis Mission requirements. In the past Lunabotics challenges we gathered data to support Lunar mining for consuma-bles in the Lunar regolith. Now, in 2024, the task is to gather data on Lunar site preparation and construction by designing and building a robot that will traverse the chaotic Lunar terrain and construct a regolith-based berm. The goal is to build a berm structure which would be useful to the Artemis Mission for blast and ejecta protection during lunar landings and launches, shading cryogenic propellant tank farms, providing radiation protection around a nuclear power plant and other mission critical uses. Lunabotics will consist of three separate events this year. The first event is NASA’s Lunabotics Project Development Challenge, where teams submit various deliverables to be scored by judges. The second event will be the University of Central Florida (UCF) Lunabotics Qualification challenge, in the Exolith laboratory, where teams will put their de-signs to the test. The top ten scoring teams from the Qualification challenge are then invited to the third and final event, NASA’s Lunabotics On-Site Challenge at Kennedy Space Center in Florida. This presentation will summarize the results and lessons learned from the NASA Lunabotics University Competition held in May 2024.

Lunabotics↗
NASA NTRS2012

Smart Cameras for Remote Science Survey

Communication with remote exploration spacecraft is often intermittent and bandwidth is highly constrained. Future missions could use onboard science data understanding to prioritize downlink of critical features [1], draft summary maps of visited terrain [2], or identify targets of opportunity for followup measurements [3]. We describe a generic approach to classify geologic surfaces for autonomous science operations, suitable for parallelized implementations in FPGA hardware. We map these surfaces with texture channels - distinctive numerical signatures that differentiate properties such as roughness, pavement coatings, regolith characteristics, sedimentary fabrics and differential outcrop weathering. This work describes our basic image analysis approach and reports an initial performance evaluation using surface images from the Mars Exploration Rovers. Future work will incorporate these methods into camera hardware for real-time processing.

robotics↗
DOE OSTI2023

Minimizing exposure to legacy wells and avoiding conflict between storage projects: Exploring area of review as a screening tool

Elevated pressure from large-volume injection is a key driver of risk and project cost. If transmissive features (e.g., non-isolating wells or fracture systems) are present, increased injection-zone pressure can drive fluids from depth toward protected freshwater resources. In US Carbon Capture and Storage (CCS) law, the area at risk is known as the Area of Review (AoR). The size and number of potentially transmissive features to be evaluated and possibly remediated or managed is a function of the size and location of the AoR. The size of the AoR depends on several variables, including properties of the injection zone, properties of protected resources, and injection rate and duration. Evaluation of the intersection of these variables across a portfolio of sites highlights the injection zone depth and boundary conditions as top-level controls. Deep injection, use of multiple stacked injection zones, reduced injection rate and choice of injection well location can all be used to minimize AoR and the number of potentially transmissive features within it. Here, we introduce the concept of pressure space (defined as connected pore volume times pressure) as the key subsurface commodity for CO 2 storage and we suggest that it forms a more robust basis for leasing and regulation than pore space alone.

58 GEOSCIENCES↗
NASA NTRS2001

Geophysical Exploration of Asteroids: The Deep Interior Mission Concept

We describe a possible international multiple-rendezvous mission to probe the interiors representative near-Earth objects. Features include SEP, autonomous navigation, stereo imaging, radio tomography, anchored seismology stations and explosive signal sources. Additional information is contained in the original extended abstract.

Asphaug, E.↗
NASA NTRS2013

Functional Performance of an Enabling Atmosphere Revitalization Subsystem Architecture for Deep Space Exploration Missions

A subsystem architecture derived from the International Space Station's (ISS) Atmosphere Revitalization Subsystem (ARS) has been functionally demonstrated. This ISS-derived architecture features re-arranged unit operations for trace contaminant control and carbon dioxide removal functions, a methane purification component as a precursor to enhance resource recovery over ISS capability, operational modifications to a water electrolysis-based oxygen generation assembly, and an alternative major atmospheric constituent monitoring concept. Results from this functional demonstration are summarized and compared to the performance observed during ground-based testing conducted on an ISS-like subsystem architecture. Considerations for further subsystem architecture and process technology development are discussed.

Perry, Jay L.↗
NASA NTRSDate not supplied

NASA Extreme Environment Mission Operations (NEEMO)

Introduction: NASA is preparing to land the first woman and first person of color on the Moon within the next decade, and ensuring the success of these missions will depend on our preparation on the ground in multiple ground-based lunar environment analogs. To achieve this, NASA has used full mission class analogs, of which NASA Extreme Environment Mission Operations (NEEMO) is the longest continuously running example. Discussion: NEEMO is NASA’s long-standing undersea high-fidelity spaceflight mission analog. It focuses on exploration science, EVA techniques and tools, and maturing ISS IVA flight hardware and operations concepts. NEEMO crews are composed of groups of US and International Partner (IP) astronauts, engineers and scientists who live, work and explore in a challenging environment analogous to the environment experienced currently on ISS and what is expected for future deep space exploration destinations. NEEMO missions are conducted at Aquarius Reef Base (ARB), which includes a shore base in Tavernier, FL, and the world's only undersea research station, the Aquarius habitat, which is located 5.4 miles (9 kilometers) off Key Largo in the Florida Keys National Marine Sanctuary. ARB is owned and operated by Florida International University (FIU). Aquarius was selected due to its remote and extreme location and its ability to provide the unique isolation and risk factors that spaceflight presents. NEEMO missions allow for evaluations of end-to-end EVA and Science exploration concepts of operations with a crew that is in situ in a true extreme environment. They also allow for evaluations of flight hardware and ops tools that are either pondered or destined for ISS or Gateway in the near future. NEEMO missions feature flight-like interactions between the crew and a Mission Control Center (MCC )and Science Team, which in turn allows evaluation of mission and science operations decision making and communications techniques. One reason NEEMO missions are of such high fidelity is that so many of the participants are experienced human space flight end operators. The majority of crewmembers are trained astronauts, and many of the MCC operators have credentials as current or former certified ISS MCC operators (e.g., CapCom, EVA Officer, etc.). Mission products are generated daily by the ground team and are modeled on ISS products (but modified as needed). A planning team manages the constantly evolving mission timelines in response to the ever-changing constraints and opportunities. During NEEMO missions, suited EVA crewmembers (using diving helmets) have clear voice communications with each other, the habitat, and the MCC and Science Team back on shore. Each EVA crewmember also sends helmet cam video to the habitat and MCC and Science Teams. Appropriate communications latencies are inserted for the destination being simulated as well. NEEMO missions are made possible by a broad collaboration of participants. Astronauts from all of the ISS partner agencies are eligible for crew assignment. Often the crew includes a NASA scientist, doctor or engineer with a particular skill to contribute. Sometimes crewmembers come from external entities–generally institutes or universities. Objectives come from a wide variety of sources as well, from within NASA, IPs, government agencies, academia, commercial companies and research institutes. A typical NEEMO mission is a collaboration between at least 5 NASA centers. To date, 23 NEEMO missions have been conducted since 2001, and NEEMO 24 is planned for 2022. Conclusion: NEEMO is a high-fidelity mission analog conducted in an extreme subsea environment. It features experienced end-operators in human spaceflight, from the astronaut crewmembers to key personnel staffing Mission Control. Acknowledgments: The authors wish to thank FIU and NASA’s HEO SEI/Strategic Analysis and Exploration Integration and Science Directorate organizations for the continued support that makes the NEEMO Project possible.

M L Reagan↗
NASA NTRS2022

Classifying Unidentified X-Ray Sources in the Chandra Source Catalog Using A Multiwavelength Machine-Learning Approach

The rapid increase in serendipitous X-ray source detections requires the development of novel approaches to efficiently explore the nature of X-ray sources. If even a fraction of these sources could be reliably classified, it would enable population studies for various astrophysical source types on a much larger scale than currently possible. Classification of large numbers of sources from multiple classes characterized by multiple properties (features) must be done automatically and supervised machine learning (ML) seems to provide the only feasible approach. We perform classification of Chandra Source Catalog version 2.0 (CSCv2) sources to explore the potential of the ML approach and identify various biases, limitations, and bottlenecks that present themselves in these kinds of studies. We establish the framework and present a flexible and expandable Python pipeline, which can be used and improved by others. We also release the training data set of 2941 X-ray sources with confidently established classes. In addition to providing probabilistic classifications of 66,369 CSCv2 sources (21% of the entire CSCv2 catalog), we perform several narrower-focused case studies (high-mass X-ray binary candidates and X-ray sources within the extent of the H.E.S.S. TeV sources) to demonstrate some possible applications of our ML approach. We also discuss future possible modifications of the presented pipeline, which are expected to lead to substantial improvements in classification confidences.

Hui Yang↗
NASA NTRS2008

The Supercritical Pile GRB Model: The Prompt to Afterglow Evolution

The 'Supercritical Pile' is a very economical gamma ray burst (GRB) model that provides for the efficient conversion of the energy stored in the protons of a Relativistic Blast Wave (RBW) into radiation and at the same time produces - in the prompt GRB phase, even in the absence of any particle acceleration - a spectral peak at an energy sim 1 MeV. We extend this model to include also the evolution of the RBW Lorentz factor Gamma and thus follow the spectral and temporal features of this model into the early GRB afterglow stage. One of the novel features of the present treatment is the inclusion of the feedback of the GRB produced radiation on the evolution of Gamma with radius. This feedback and the presence of kinematic and dynamic thresholds in the model can be the sources of rich time evolution which we have begun to explore. In particular, one can this way obtain afterglow light curves with steep decays followed by the more conventional flatter afterglow slopes, while at the same time preserving the desirable features of the model, i.e. the well defined relativistic electron source and radiative processes that produce the proper peak in the nu F spectra. Furthermore, the existence of a kinematic threshold in this model provides for a operational distinction of the prompt and afterglow GRB stages; in fact, the afterglow stage sets in when the RBW Lorentz factor cannot anymore fulfill the kinematic condition for pair formation in the photon - proton pair production reactions that constitute the fundamental process for the dissipation of the blast wave kinetic energy. We present the results of a specific set of parameters of this model with emphasis on the multiwavelength prompt emission and transition to the early afterglow.

Kazanas, Demosthenes↗
NASA NTRS2009

The Supercritical Pile GRB Model: The Prompt to Afterglow Evolution

The "Supercritical Pile" is a very economical GRB model that provides for the efficient conversion of the energy stored in the protons of a Relativistic Blast Wave (RBW) into radiation and at the same time produces - in the prompt GRB phase, even in the absence of any particle acceleration - a spectral peak at energy approx. 1 MeV. We extend this model to include the evolution of the RBW Lorentz factor Gamma and thus follow its spectral and temporal features into the early GRB afterglow stage. One of the novel features of the present treatment is the inclusion of the feedback of the GRB produced radiation on the evolution of Gamma with radius. This feedback and the presence of kinematic and dynamic thresholds in the model can be the sources of rich time evolution which we have began to explore. In particular. one can this may obtain afterglow light curves with steep decays followed by the more conventional flatter afterglow slopes, while at the same time preserving the desirable features of the model, i.e. the well defined relativistic electron source and radiative processes that produce the proper peak in the (nu)F(sub nu), spectra. In this note we present the results of a specific set of parameters of this model with emphasis on the multiwavelength prompt emission and transition to the early afterglow.

Mastichiadis, A.↗
NASA NTRS2010

A Bulk Comptonization Model for the Prompt GRM Emission

The "Supercritical Pile" is a very economical GRB model that provides for the efficient conversion of the energy stored in the protons of a Relativistic Blast Wave (RBW) into radiation and at the same time produces - in the prompt GRB phase, even in the absence of any particle acceleration - a spectral peak at energy approximately 1 MeV. We extend this model to include the evolution of the RBW Lorentz factor F and thus follow its spectral and temporal features into the early GRB afterglow stage. One of the novel features of the present treatment is the inclusion of the feedback of the GRB produced radiation on the evolution of Gamma with radius. This feedback and the presence of kinematic and dynamic thresholds in the model are sources of potentially very rich time evolution which we have began to explore. In particular, one can this way obtain afterglow light curves with steep decays followed by the more conventional flatter afterglow slopes, while at the same time preserving the desirable features of the model, i.e. the well defined relativistic electron source and radiative processes that produce the proper peak in the nu F(sub nu) spectra. In this note we present the results of a specific set of parameters of this model with emphasis on the multiwavelength prompt emission and transition to the early afterglow.

Kazanas, Demos↗
DOE OSTI2021

Two-dimensional electronic–vibrational spectroscopy: Exploring the interplay of electrons and nuclei in excited state molecular dynamics

Two-dimensional electronic-vibrational spectroscopy (2DEVS) is an emerging spectroscopic technique which exploits two different frequency ranges for the excitation (visible) and detection (infrared) axes of a 2D spectrum. In contrast to degenerate 2D techniques, such as 2D electronic or 2D infrared spectroscopy, the spectral features of a 2DEV spectrum report cross correlations between fluctuating electronic and vibrational energy gaps rather than autocorrelations as in the degenerate spectroscopies. The center line slope of the spectral features reports on this cross correlation function directly and can reveal specific electronic-vibrational couplings and rapid changes in the electronic structure, for example. The involvement of the two types of transition moments, visible and infrared, makes 2DEVS very sensitive to electronic and vibronic mixing. 2DEV spectra also feature improved spectral resolution, making the method valuable for unraveling the highly congested spectra of molecular complexes. The unique features of 2DEVS are illustrated in this paper with specific examples and their origin described at an intuitive level with references to formal derivations provided. Although early in its development and far from fully explored, 2DEVS has already proven to be a valuable addition to the tool box of ultrafast nonlinear optical spectroscopy and is of promising potential in future efforts to explore the intricate connection between electronic and vibrational nuclear degrees of freedom in energy and charge transport applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Advancing GRCop-based Bimetallic Additive Manufacturing to Optimize Component Design and Applications for Liquid Rocket Engines

Additive manufacturing (AM) is advancing many applications of component design for liquid rocket engines. The ability to rapidly design and manufacture components has provided significant opportunities for development and flight programs across the propulsion industry. AM has demonstrated significant advantages that include cost and schedule savings in addition to performance improvements through new design opportunities. While these performance advantages can be in the characteristics of complex design features, they can also be in the form of new materials. AM has been demonstrated in these various component applications using a variety of metal alloys, many of which are traditional alloys for extreme environments. Additional developments were completed using AM to provide new alloys and maturing these material uses for high performance applications. Almost all of the prior developments across component applications have focused on single-alloys in these AM processes. NASA and industry partners have focused in recent years to advance processing to create bimetallic and multicomponent AM processes and materials. The role of multi-alloy AM offers advantages since it can further optimize weight, optimize reliability and performance by increasing the strength to weight ratio of a component, and can optimize materials for various engineering requirements. This is particularly important in liquid rocket engine combustion devices that must reject heat in high heat flux environments yet maintain adequate structural margins under high operational pressure. NASA has been exploring several AM processes, materials, and applications for combustion devices, specifically combustion chambers, injectors, nozzles, and ignition systems. These components require fine geometric features for internal flow or cooling functionality. They experience high thermal gradients across thin-walls and must survive high pressures and temperatures from propellants and the combustion process. A copper-based alloy is normally used to provide high thermal conductivity, but at the detriment of increased weight if used as a single alloy in an AM chamber. Various AM processes were demonstrated on these components using a copper-based alloy/superalloy bimetallic solution. The AM processes being explored individually and in combination for bimetallic applications include Laser Powder Bed Fusion (L-PBF), Laser Powder Directed Energy Deposition (LP-DED), and cold spray. The combination of bimetallic material combinations explored in this research include copper-based material primarily and superalloys, Inconel 625 or NASA HR-1. The various aspects of the additive manufacturing processes and challenges, materials characterization, and the testing of bimetallic components in a relevant environment will be discussed.

Additive Manufacturing↗
NASA NTRSDate not supplied

Advancing GRCop-based Bimetallic Additive Manufacturing to Optimize Component Design and Applications for Liquid Rocket Engines

Additive manufacturing (AM) is advancing many applications of component design for liquid rocket engines. The ability to rapidly design and manufacture components has provided significant opportunities for development and flight programs across the propulsion industry. AM has demonstrated significant advantages that include cost and schedule savings in addition to performance improvements through new design opportunities. While these performance advantages can be in the characteristics of complex design features, they can also be in the form of new materials. AM has been demonstrated in these various component applications using a variety of metal alloys, many of which are traditional alloys for extreme environments. Additional developments were completed using AM to provide new alloys and maturing these material uses for high performance applications. Almost all of the prior developments across component applications have focused on single-alloys in these AM processes. NASA and industry partners have focused in recent years to advance processing to create bimetallic and multicomponent AM processes and materials. The role of multi-alloy AM offers advantages since it can further optimize weight, optimize reliability and performance by increasing the strength to weight ratio of a component, and can optimize materials for various engineering requirements. This is particularly important in liquid rocket engine combustion devices that must reject heat in high heat flux environments yet maintain adequate structural margins under high operational pressure. NASA has been exploring several AM processes, materials, and applications for combustion devices, specifically combustion chambers, injectors, nozzles, and ignition systems. These components require fine geometric features for internal flow or cooling functionality. They experience high thermal gradients across thin-walls and must survive high pressures and temperatures from propellants and the combustion process. A copper-based alloy is normally used to provide high thermal conductivity, but at the detriment of increased weight if used as a single alloy in an AM chamber. Various AM processes were demonstrated on these components using a copper-based alloy/superalloy bimetallic solution. The AM processes being explored individually and in combination for bimetallic applications include Laser Powder Bed Fusion (L-PBF), Laser Powder Directed Energy Deposition (LP-DED), and cold spray. The combination of bimetallic material combinations explored in this research include copper-based material primarily and superalloys, Inconel 625 or NASA HR-1. The various aspects of the additive manufacturing processes and challenges, materials characterization, and the testing of bimetallic components in a relevant environment will be discussed.

Additive Manufacturing↗
DOE OSTI2025

Announcing the Biomedical Data Translator: Initial Public Release

ABSTRACT The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open‐source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. We announce here Translator's initial public release and provide an overview of its architecture, standards, user interface, and core features. Translator employs a scalable, federated, knowledge graph framework for the integration of clinical, genomic, pharmacological, and other biomedical knowledge sources, enabling query retrieval, inference, and hypothesis generation. Translator's user interface is designed to support the exploration of knowledge relationships and the generation of insights, without requiring deep technical expertise and gradually revealing more detailed evidence, provenance, and confidence information, as needed by a given user. To demonstrate Translator's application and impact, we highlight features of the user interface in the context of three real‐world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism. We discuss strengths and limitations of reasoning within a largely federated system and the need for rich concept modeling and deep provenance tracking. Finally, we outline future directions for enhancing Translator's functionality and expanding its data sources. Translator represents a significant step forward in making complex biomedical knowledge more accessible and actionable, aiming to accelerate translational research and improve patient care.

Research & Experimental Medicine↗
NASA NTRS2004

A Preliminary Relationship Between the Depth of Martian Gullies and the Abundance of Hydrogen on Near-Surface Mars

Recent compelling evidence has been presented to suggest the presence of near-surface water or water ice on Mars. The Mars Orbiter Camera (MOC) has photographed relatively young fluvial features in the form of gullies which have been attributed to groundwater seepage. The Gamma Ray Spectrometer (GRS) from the Mars Odyssey spacecraft has detected large amounts of hydrogen in the Martian soil, inferred to come from water or water ice within the upper meter of the surface. We explore the model of groundwater seepage as the mechanism of gully formation as opposed to other mechanisms. We investigate the abundance of hydrogen to the depth at which gully-like features form. We see a positive correlation, which implies the presence of a groundwater system for Mars.

Frey, E. L.↗
DOE OSTI2023

Protein model quality assessment using rotation–equivariant transformations on point clouds

Machine learning research concerning protein structure has seen a surge in popularity over the last years with promising advances for basic science and drug discovery. Working with macromolecular structure in a machine learning context requires an adequate numerical representation, and researchers have extensively studied representations such as graphs, discretized 3D grids, and distance maps. As part of CASP14, we explored a new and conceptually simple representation in a blind experiment: atoms as points in 3D, each with associated features. These features—initially just the basic element type of each atom—are updated through a series of neural network layers featuring rotation-equivariant convolutions. Starting from all atoms, we further aggregate information at the level of alpha carbons before making a prediction at the level of the entire protein structure. We find that this approach yields competitive results in protein model quality assessment despite its simplicity and despite the fact that it incorporates minimal prior information and is trained on relatively little data. As a result, its performance and generality are particularly noteworthy in an era where highly complex, customized machine learning methods such as AlphaFold 2 have come to dominate protein structure prediction.

59 BASIC BIOLOGICAL SCIENCES↗