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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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At least 433 records · Page 24

Consolidating NASA's Arc Jets

The paper describes the consolidation of NASA's high powered arc-jet testing at a single location. The existing plasma arc-jet wind tunnels located at the Johnson Space Center were relocated to Ames Research Center while maintaining NASA's technical capability to ground-test thermal protection system materials under simulated atmospheric entry convective heating. The testing conditions at JSC were reproduced and successfully demonstrated at ARC through close collaboration between the two centers. New equipment was installed at Ames to provide test gases of pure nitrogen mixed with pure oxygen, and for future nitrogen-carbon dioxide mixtures. A new control system was custom designed, installed and tested. Tests demonstrated the capability of the 10 MW constricted-segmented arc heater at Ames meets the requirements of the major customer, NASA's Orion program. Solutions from an advanced computational fluid dynamics code were used to aid in characterizing the properties of the plasma stream and the surface environment on the calorimeters in the supersonic flow stream produced by the arc heater.

Consolidation↗

The OpenSSP Snow Particle and Scattering Property Database: Current Status and Future Plans

Understanding the connection between microphysical properties of falling snow and remote sensing observations requires detailed models of snow particles and the related electromagnetic scattering properties. To this end, we have created a database of synthetically-grown snow particles along with electromagnetic scattering properties calculated using advanced computational methods. We showcase the breadth of the catalog, current work, applications of the catalog, and future plans.

Adams, Ian S.↗

Toward Coupled Data Assimilation in NASA’s GEOS: Developments in the Ocean Context

The Global Modeling & Assimilation Office (GMAO) at NASA GSFC produces analyses and predictions of the Earth system using various configurations of the Goddard Earth Observing System (GEOS) model and assimilation system. The current sub-seasonal-to-seasonal prediction system (GEOS-S2S) is based on a coupled atmosphere-ocean-land-ice configuration of GEOS which includes the Modular Ocean Model version 5 (MOM5) run at approximately 50-km resolution and a de-coupled OI-based ocean analysis that uses an initialization of MOM5 forced by the MERRA-2 reanalysis. GMAO will soon implement an updated GEOS-S2S system that will run at 25-km resolution and adopt aspects of the hybrid four-dimensional ensemble-variational (H4DEnVar) system already running in the production-version atmospheric analysis system, including a Local Ensemble Transform Kalman Filter (LETKF) to provide initial conditions for the oceanic state. This presentation will focus on developments to sustain the GMAO's systems on longer time horizons, where more radical transformations will be required to adapt to advanced computing environments, higher resolution and more diverse model components, and new observations for the Earth system. Results will describe progress toward a version of the GEOS coupled system that will be based around the Joint Effort for Data assimilation Integration (JEDI) framework being developed within Joint Center for Satellite Data Assimilation (JCSDA) and include an updated ocean model, MOM6. Discussion will focus specifically on the use of a Unified Forward Operator (UFO) for simulating observations and the Object Oriented Prediction System (OOPS) for providing the state estimate. These features are being developed as a multi-agency effort under the auspices of the JCSDA and are being adopted in the GMAO for all its applications of coupled data assimilation including S2S, numerical weather prediction, and reanalysis.

Mahajan, Rahul↗

Mars Ascent Vehicle Hybrid Propulsion Configuration

As part of a Mars Sample Return (MSR) campaign, two Mars Ascent Vehicle (MAV) configurations have been designed in parallel. Each ascent vehicle configuration has a different propulsion system which ultimately leads to two unique vehicle designs. As part of a Preliminary Architecture Assessment (PAA), these vehicle designs were developed to the same level of maturity in order to inform the selection of one of the vehicles as the point of departure design for the campaign. The selection will be made in November 2019. The initial MSR architecture called for a hybrid-based propulsion MAV. This type of propulsion system calls for a solid wax motor that would utilize liquid MON-25 as an oxidizer. Hybrid rocket propulsion allows for more flexibility than traditional solid or liquid propulsion options, and typically benefits from the advantages of both. A hybrid motor can be throttled and shut down easily, and avoids significant risk in manufacturing and handling. On a theoretical level, hybrid motors perform at a higher specific impulse (Isp) than solid motors. The primary disadvantage of hybrid motors comes from additional complexity and significantly less flight heritage and low Technology Readiness Level (TRL). This paper describes the design of the hybrid propulsion configuration. An additional paper will be published describing the design of the solid propulsion configuration1. The hybrid propulsion configuration MAV was developed in 2019 by NASA Marshall Space Flight Center (MSFC) in association with NASA Jet Propulsion Laboratory (JPL). It features a Single Stage to Orbit (SSTO) design with an SP7A solid wax fuel and MON-25 liquid oxidizer. The liquid portion of the vehicle allows for a Liquid Injection Thrust Vector Controller (LITVC) as well as hypergolic propellant additives for ignition. The vehicle was designed to deliver approximately 0.31kg of Martian geological samples to a circular orbit at Mars of 343km at a 25o inclination. Although hybrid propulsion in general has been used on launch vehicles in the past, the integrated vehicle subsystems that operate in conjunction with these propulsion elements do not typically operate in a Martian environment, which in this application can get as cold as -40oC. The PAA advanced the maturity of these subsystems by performing detailed design and analysis on the vehicle with respect to structures and mechanisms, Guidance/Navigation/Control (GNC) systems, avionics, Reaction Control System (RCS), LITVC, thermal environments, and advanced Computational Fluid Dynamics (CFD). This paper will summarize the results of these studies.

Yaghoubi, Darius↗

Mars Ascent Vehicle Solid Propulsion Configuration

As part of a Mars Sample Return (MSR) campaign, two Mars Ascent Vehicle (MAV) configurations have been designed in parallel. Each ascent vehicle configuration has a different propulsion system, which ultimately leads to two unique vehicle designs. As part of a Preliminary Architecture Assessment (PAA), these vehicle designs were developed to the same level of maturity in order to inform the selection of one of the vehicles as the point of departure design for the campaign. The selection will be made in November 2019. Although the initial MSR architecture called for a hybrid-based propulsion MAV featuring solid wax fuel with liquid oxidizer, a configuration using more traditional solid propulsion was developed as an additional risk mitigation option. Though lacking in the single stage to orbit (SSTO) and throttle flexibility of a hybrid configuration, a solid configuration vehicle allows a simpler design with significantly longer flight heritage and higher Technology Readiness Level (TRL). This paper describes the design of the solid propulsion configuration. An additional paper will be published describing the design of the hybrid propulsion configuration. The solid propulsion configuration MAV was developed in 2019 by NASA Marshall Space Flight Center (MSFC) in association with NASA Jet Propulsion Laboratory (JPL). It features two stages with a modified STAR-17 motor for the second stage and a traditional electromechanical actuator Thrust Vector Controller (TVC). The vehicle was designed to deliver approximately 0.47kg of Martian geological samples to a circular orbit at Mars of 343km at a 25° inclination. Although solid motor designs in general are at a relatively high TRL, the integrated vehicle subsystems that operate in conjunction with these propulsion elements do not typically operate in a Martian environment, which in this application can get as cold as -40°C. The PAA advanced the maturity of these subsystems by performing detailed design and analysis on the vehicle with respect to structures and mechanisms, Guidance/Navigation/Control (GNC) systems, avionics, Reaction Control System (RCS), TVC, thermal environments, and advanced Computational Fluid Dynamics (CFD). This paper will summarize the results of these studies.

Yaghoubi, Darius↗

Mars Ascent Vehicle Solid Propulsion Configuration

As part of a Mars Sample Return (MSR) campaign, two Mars Ascent Vehicle (MAV) configurations have been designed in parallel. Each ascent vehicle configuration has a different propulsion system, which ultimately leads to two unique vehicle designs. As part of a Preliminary Architecture Assessment (PAA), these vehicle designs were developed to the same level of maturity in order to inform the selection of one of the vehicles as the point of departure design for the campaign. The selection will be made in November 2019. Although the initial MSR architecture called for a hybrid-based propulsion MAV featuring solid wax fuel with liquid oxidizer, a configuration using more traditional solid propulsion was developed as an additional risk mitigation option. Though lacking in the single stage to orbit (SSTO) and throttle flexibility of a hybrid configuration, a solid configuration vehicle allows a simpler design with significantly longer flight heritage and higher Technology Readiness Level (TRL). This paper describes the design of the solid propulsion configuration. An additional paper will be published describing the design of the hybrid propulsion configuration. The solid propulsion configuration MAV was developed in 2019 by NASA Marshall Space Flight Center (MSFC) in association with NASA Jet Propulsion Laboratory (JPL). It features two stages with a modified STAR-17 motor for the second stage and a traditional electromechanical actuator Thrust Vector Controller (TVC). The vehicle was designed to deliver approximately 0.47kg of Martian geological samples to a circular orbit at Mars of 343km at a 25° inclination. Although solid motor designs in general are at a relatively high TRL, the integrated vehicle subsystems that operate in conjunction with these propulsion elements do not typically operate in a Martian environment, which in this application can get as cold as -40°C. The PAA advanced the maturity of these subsystems by performing detailed design and analysis on the vehicle with respect to structures and mechanisms, Guidance/Navigation/Control (GNC) systems, avionics, Reaction Control System (RCS), TVC, thermal environments, and advanced Computational Fluid Dynamics (CFD). This paper will summarize the results of these studies.

Yaghoubi, Darius↗

Do You See What I See? Interactive Visualization of Mission Design and Navigation

Mission Design and Navigation (MDNav) is an intensive process requiring advanced computational resources, expert human intuition, and many successive human-in-the-loop iterations to converge on acceptable trajectory designs or navigation solutions. The current bottleneck in MDNav is not the underlying computational algorithms but the human cognitive capacity to prune through a multitude of simulated results to select high-value candidates. One approach to alleviate this burden is through the judicious application of visualizations that allow humans to interactively filter data in multiple dimensions to reveal salient patterns and highlight divergences. When designed efficiently, such interactive visualizations should aid human operators to get familiar with data faster, visually observe correlations, and communicate findings more effortlessly. In this work, we present three visualization case studies that have the potential to increase human operator efficiency in MDNav. While identifying the most critical “pain points” that operators face, and also working on potential solutions, we followed a human-centered design approach. We started with a series of interviews with potential users, and then rapidly created prototypes for alternative solutions, validated outcomes with feedback from users through out development of these proof of concept visualizations. With this survey of our current efforts, we demonstrate the transformative capability of interactive data visualizations for improving mission development and operations, enabling operators to grow intuition, and communicating key concepts across diverse mission teams.

Arora, Nitin↗

Radiation Tolerance and Mitigation for Neuromorphic Processors

Neuromorphic processors are designed to execute Deep Neural Networks (DNNs) at very high speed using only a fraction of the electrical power needed to run a DNN on a traditional CPU or GPU. This unique capability makes Neuromorphic processors a prime candidate for space systems, where advanced computational tasks like image analysis, depth map reconstruction, or rover control need to be executed in a power-starved environment. In contrast to the growing number of applications of Neuromorphic processors in smart phones, the automotive and robotics domain, the space environment is unforgiving because of extreme temperatures and high levels of radiation. Any space system, operating beyond LEO requires computing hardware that is resilient against radiation effects. However, Neuromorphic processors have not yet been designed or tested for their radiation tolerance. In this report, we consider traditional methods of detection of radiation events and mitigation via redundancy and gauge their effectiveness on DNNs. In contrast to traditional flight software, however, neural networks represent a statistical algorithm, which might affect its resilience against radiation events. We will focus on the analysis of the tolerance of DNNs with respect to radiation events and discuss techniques to detect radiation hits using on-chip triple modular redundancy (TMR) on an Intel Loihi neuromorphic processor and to mitigate radiation damage. We describe an architecture for on-chip TMR for the Intel Loihi and present results of initial experiments.

Neural Networks↗

On the Role of Friction and Particle Size Distribution in Granular Packings

Packing of particles in a disordered arrangement has tremendous significance in both condensed matter physics and engineering applications. The last three decades have seen remarkable progress in our understanding of the physics of granular packings that has been largely facilitated by a rapid growth in the power of modern computers. Although granular packings are ubiquitous in diverse natural settings, from clogging of powders in hoppers to the crowding of living cells, a significant motivation for modeling granular packings has emerged from a proposal that the transition from a fluid-like state to a solid-like state of a granular material upon increasing volume fraction, called jamming, is intimately related to the origins of glass transition in thermal systems. As such, a majority of modeling efforts have focused on the jamming behavior of an idealized granular material: frictionless, monodisperse sphere. While such studies have illuminated the rich physics of jamming, granular materials in nature and engineering practice are rarely frictionless or monodisperse. The analogous research on the packing of these ‘real-world’ granular materials is still not fully developed. Besides requiring the exploration of a huge parameter space, three key computational considerations have inhibited their modeling: (i) traditional computational methods are not adept at simulating mechanically-stable packings of frictional particles near the jamming transition; (ii) standard algorithms of contact detection in discrete element methods are impractical to simulate granular packings with a wide distribution of particle sizes; (iii) a lack of well-established contact mechanics models of friction that can accurately reproduce experimental data. This chapter will review the latest computational advances to simulate the jamming of size-dispersed frictional particles, and describe the rich microstructural diversity that emerges in their packings.

granular↗

Somatic Mutation Analysis in Spaceflight: NASA Twins Genome Study

The NASA Twins Genome Study investigates the effects of spaceflight on somatic mutation accumulation by comparing genome-wide sequence data from a spaceflight astronaut and his Earth-bound twin. Utilizing advanced computational software on high performance computers, this study identifies and maps somatic mutations, with implications for understanding spaceflight-associated health risks, including cancer, neurodegeneration, and cardiovascular disease. The findings aim to bridge rodent and human space research, offering insights into tissue-specific pathophysiology, risk models, and potential therapeutic interventions.

somatic mutation↗

GASP Advancements With Symbolic Computations, Optimization, and Decoupled Numerical Methods

NASA is exploring advancements in hybrid-electric propulsion concepts for aircraft design. A new analysis capability has been deployed at NASA’s Ames Research Center using a new mathematical modeling framework in Python that leverages symbolic representation of mathematical expressions, optimization-based problem formulations, and standalone numerical methods. This capability, called Gascon, has been verified against NASA’s General Aviation Synthesis Program (GASP) results for several vehicles that exercise the analysis capability for a variety of aircraft classes and engine models, including both turbofans and turboprops. We believe this capability will set the stage for more rapid development of novel aircraft models with more flexible design assessments using optimization, and more traceable analysis for reproducibility. Additionally, a novel Pareto optimization-based design space exploration that shows the trade between range flown and fuel burn by manipulating the thrust split during cruise for a true parallel hybrid aircraft was developed by leveraging the unique features of Gascon.

aircraft design↗

Future Computer Requirements for Computational Aerodynamics

Recent advances in computational aerodynamics are discussed as well as motivations for and potential benefits of a National Aerodynamic Simulation Facility having the capability to solve fluid dynamic equations at speeds two to three orders of magnitude faster than presently possible with general computers. Two contracted efforts to define processor architectures for such a facility are summarized.

Source record↗

Computational aerodynamics on large computers

Three examples of advances in computational aerodynamics; (1) three-dimensional inviscid transonic analysis, (2) design calculations for wings, and (3) the computation of viscous-induced aileron buzz, are reviewed. Attention is given to wing surface pressures, design optimization, computer memory, speed and advanced solution methods on parallel computer architecture. It is determined that many implicit approximate-factorization schemes, that have been developed for Navier-Stokes equations, can be coded to run efficiently on microprocessors.

Ballhaus, W. F.↗

A computational study of advanced exhaust system transition ducts with experimental validation

The current study is an application of CFD to a 'real' design and analysis environment. A subsonic, three-dimensional parabolized Navier-Stokes (PNS) code is used to construct stall margin design charts for optimum-length advanced exhaust systems' circular-to-rectangular transition ducts. Computer code validation has been conducted to examine the capability of wall static pressure predictions. The comparison of measured and computed wall static pressures indicates a reasonable accuracy of the PNS computer code results. Computations have also been conducted on 15 transition ducts, three area ratios, and five aspect ratios. The three area ratios investigated are constant area ratio of unity, moderate contracting area ratio of 0.8, and highly contracting area ratio of 0.5. The degree of mean flow acceleration is identified as a dominant parameter in establishing the minimum duct length requirement. The effect of increasing aspect ratio in the minimum length transition duct is to increase the length requirement, as well as to increase the mass-averaged total pressure losses. The design guidelines constructed from this investigation may aid in the design and manufacture of advanced exhaust systems for modern fighter aircraft.

Wu, C.↗

Assessing and Advancing the Potential of Quantum Computing: A NASA Case Study

Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum computing hardware has advanced rapidly, from tiny laboratory experiments to quantum chips that can outperform even the largest supercomputers on specialized computational tasks, these noisy- intermediate scale quantum (NISQ) processors are still too small and non-robust to be directly useful for any real-world applications. In this paper, we describe NASA’s work in assessing and advancing the potential of quantum computing. We discuss advances in algorithms, both near- and longer-term, and the results of our explorations on current hardware as well as with simulations, including illustrating the benefits of algorithm-hardware codesign in the NISQ era. This work also includes physics-inspired classical algorithms that can be used at application scale today. We discuss innovative tools supporting the assessment and advancement of quantum computing, and describe improved methods for simulating quantum systems of various types on high performance computing systems that incorporate realistic error models. We provide an overview of recent methods for benchmarking, evaluating, and characterizing quantum hardware for error mitigation, computational purposes.

quantum computing↗

Assessing and advancing the potential of quantum computing: A NASA case study

Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum computing hardware has advanced rapidly, from tiny laboratory experiments to quantum chips that can outperform even the largest supercomputers on specialized computational tasks, these noisy-intermediate scale quantum (NISQ) processors are still too small and non-robust to be directly useful for any real-world applications. In this paper, we describe NASA’s work in assessing and advancing the potential of quantum computing. We discuss advances in algorithms, both near- and longer-term, and the results of our explorations on current hardware as well as with simulations, including illustrating the benefits of algorithm-hardware co-design in the NISQ era. This work also includes physics-inspired classical algorithms that can be used at application scale today. We discuss innovative tools supporting the assessment and advancement of quantum computing and describe improved methods for simulating quantum systems of various types on high-performance computing systems that incorporate realistic error models. We provide an overview of recent methods for benchmarking, evaluating, and characterizing quantum hardware for error mitigation, as well as insights into fundamental quantum physics that can be harnessed for computational purposes.

Rieffel, Eleanor G.↗