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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 19 records

4BMS-X Design and Test Activation

In support of the NASA goals to reduce power, volume and mass requirements on future CO2 (Carbon Dioxide) removal systems for exploration missions, a 4BMS (Four Bed Molecular Sieve) test bed was fabricated and activated at the NASA Marshall Space Flight Center. The 4BMS-X (Four Bed Molecular Sieve-Exploration) test bed used components similar in size, spacing, and function to those on the flight ISS flight CDRA system, but were assembled in an open framework. This open framework allows for quick integration of changes to components, beds and material systems. The test stand is highly instrumented to provide data necessary to anchor predictive modeling efforts occurring in parallel to testing. System architecture and test data collected on the initial configurations will be presented.

Peters, Warren T.↗

DELTA: An Open-Source Framework to Simplify Deep Learning with Satellite Imagery

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA for deep learning on satellite imagery based on tensorflow. It helps simplify data engineering and preprocessing steps and reduces the need for a lot of the boilerplate code that needs written to make datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the grunt work. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping.

Michael von Pohle↗

DELTA: An Open-Source Framework to Simplify Machine Learning with Satellite Imagery

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA to simplify running and training machine learning (ML) models on satellite imagery. Users new to machine learning can run existing ML models on satellite imagery with minimal setup and configuration. For experienced ML users, DELTA helps simplify data engineering, preprocessing steps, and reduces the need for boilerplate code that needs written to make satellite imagery datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the imagery manipulation. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping using imagery from multiple satellite sources

Michael von Pohle↗

DELTA: An Open-Source Framework to Simplify Machine Learning with Satellite Imagery

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA to simplify running and training machine learning (ML) models on satellite imagery. Users new to machine learning can run existing ML models on satellite imagery with minimal setup and configuration. For experienced ML users, DELTA helps simplify data engineering, preprocessing steps, and reduces the need for boilerplate code that needs written to make satellite imagery datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the imagery manipulation. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping using imagery from multiple satellite sources.

deep learning↗

F Prime: An Open-Source Framework for Small-Scale Flight Software Systems

Developing flight software for small-scale missions such as CubeSats and SmallSats is challenging. These missions typically have ambitious goals, modest budgets, and tight schedules. To meet these challenges, a good flight software framework is essential. Frameworks can provide an architecture, infrastructure, tools, and reusable software components, all of which can help developers deliver their code on time and on budget. In this paper we present F Prime, a free, open-source flight software framework developed at JPL and tailored to small-scale systems such as CubeSats, SmallSats, and instruments. F Prime comprises several elements: (1) an architecture that decomposes flight software into discrete components with well-defined interfaces; (2) a C++ framework that provides core capabilities such as message queues and threads; (3) tools for specifying components and connections and automatically generating code; (4) a growing collection of ready-to-use components; and (5) tools for testing flight software at the unit and integration levels.We describe the F Prime framework and tools and present our experience using them. We describe several enhancements to the framework currently underway in the areas of software design, software verification, and ground data systems for testing.

Levison, Jeffrey W.↗

Openet: Applications of Satellite-Based Evapotranspiration Data for Water Resources Management in the Western United States

Advancing water security in overallocated river basins globally requires consistent and reproducible information on consumptive use of water that can anchor the development of data-driven solutions to the challenge of balancing water supply and demand. OpenET is a fully automated system for field-scale (30 m), satellite-based mapping of evapotranspiration (ET) at daily, monthly and annual timesteps. OpenET currently provides spatially contiguous data throughout the 23 westernmost states in the continental US, and includes both current information as well as multi-year timeseries of ET. The OpenET consortium has implemented an ensemble of satellite-based ET models (ALEXI/DisALEXI, eeMETRIC, PT-JPL, geeSEBAL, SIMS and SSEBop) on Google Earth Engine, which provides a shared computing platform for collaboration on processing of data from Landsat and other satellites, land cover and meteorological inputs, leading to increased consistency and accuracy across the ensemble of models. Earth Engine also facilitates hosting and distribution of data via open data collections and an application programming interface. We provide updates on the OpenET framework, open data services and data access tools, approach to geographic expansion, recent accuracy assessments, and describe how a user-driven design approach has facilitated successful applications of OpenET data for a wide range of water resource management activities. Applications to date include: use of ET data to improve quantification of ET and consumptive use in Oregon, Utah and the Upper Colorado River Basin; streamlining of water use reporting requirements in the California Delta; support for calculation of water budgets for the implementation of the Sustainable Groundwater Management Act in California; and integration into decision support tools for irrigation management. The use cases demonstrate how satellite-derived ET data that are easily accessed and seen as broadly accepted can accelerate adoption of innovative water management practices at scale, and support advances in the sustainability of water supplies. Uptake and use of data by the OpenET science community has also led to advances in our understanding of the impacts of landcover change, irrigation intensification and wildfire events on hydrology and the water security.

Applications↗

Reverse Micelle Based Synthesis of Microporous Materials in Microgravity

Microporous materials include a large group of solids of varying chemical composition as well as porosity. These materials are characterized by channels and cavities of molecular dimensions. The framework structure is made up of interconnecting T-O-T' bonds, where T and T' can be Si, Al, P, Ga, Fe, Co, Zn, B and a host of other elements. Materials with Si-O-Al bonding in the framework are called zeolites and are extensively used in many applications. Ion-exchange properties of these materials are exploited in the consumer and environmental industries. Chemical and petroleum industries use zeolites as catalysts in hydrocarbon transform ations. Synthesis of new microporous frameworks has led to the development of new technologies, and thus considerable effort worldwide is expended in their discovery. Microporous materials are typically made under hydrothermal conditions. Influence of nature of starting reactants, structure directing agents, pH, temperature, and aging all have profound influence on the synthesis process. This is primarily because the most interesting open frameworks are not necessarily the stable structures in the reaction medium. Thus, the discovery of new frameworks is often tied to finding the right composition and synthesis conditions that allow for kinetic stabilization of the structure. This complexity of the synthesis process and limited understanding of it has made it difficult to develop directed is of microporous materials and most advances in this field have been made by trial and error. The basic issues in crystal growth of these materials include: (1) Nature of the nucleation process; (2) Molecular structure and assembly of nuclei; (3) Growth of nuclei into crystals; (4) Morphology control; and (5) Transformation of frameworks into other structures. The NASA-funded research described in this paper focuses on all the above issues and has been described in several publications. We present the highlights of our program, especially with the focus on possible experiments in microgravity.

Dutta, Prabir K.↗

Matrix characteristics and origin of lunar breccia samples no. 12034 and 12073

The transmission electron microscope was used to investigate the nature of the matrix in two samples of lunar breccia. This matrix is composed largely of tiny (0.5 microns) grains of unaltered glass which are plastically fitted against one another, and tightly welded to the clastic fragments with which they are in contact. The breccias have an open framework of angular clastic particles composed mainly of anorthositic, basaltic and glassy fragments. Most of the anorthositic fragments have been shock metamorphosed. Over half of the glassy clasts, and also the former diaplectic glass particles produced from shocked plagioclase, were partly or wholly devitrified before inclusion in the present breccias. It is concluded that each breccia was deposited from a hot basesurge cloud of impact debris, and the tiny bits of glass in the matrix condensed from rock that was volatilized by the heat of major meteorite impact.

Waters, A. C.↗

Preferential uptake of ammonium ions by zinc ferrocyanide

The concentration of ammonia from dilute aqueous solution could have facilitated many prebiotic reactions. This may be especially true if this concentration involves incorporation into an organized medium. We have shown that (unlike iron(III) ferrocyanide) zinc ferrocyanide,Zn2Fe(CN)6 xH2O, preferentially takes up ammonium ions from 0.01 M NH4Cl to give the known material Zn3(NH4)2[Fe(CN)6]2 xH2O, even in the presence of 0.01 M KCl. KCl alone gave Zn3K2[Fe(CN)6]2 xH2O. Products were characterized by elemental (CHN) analysis and powder X-ray diffraction (XRD). We attribute the remarkable specificity for the ammonium ion to the open framework of the product, which offers enough space for hydrogen-bonded ammonium ions, and infer that other inorganic materials with internal spaces rich in water may show a similar preference.

Non-NASA Center↗

Variable Sampling Mapping

The performance of an optical system (for example, a telescope) is limited by the misalignments and manufacturing imperfections of the optical elements in the system. The impact of these misalignments and imperfections can be quantified by the phase variations imparted on light traveling through the system. Phase retrieval is a methodology for determining these variations. Phase retrieval uses images taken with the optical system and using a light source of known shape and characteristics. Unlike interferometric methods, which require an optical reference for comparison, and unlike Shack-Hartmann wavefront sensors that require special optical hardware at the optical system's exit pupil, phase retrieval is an in situ, image-based method for determining the phase variations of light at the system s exit pupil. Phase retrieval can be used both as an optical metrology tool (during fabrication of optical surfaces and assembly of optical systems) and as a sensor used in active, closed-loop control of an optical system, to optimize performance. One class of phase-retrieval algorithms is the iterative transform algorithm (ITA). ITAs estimate the phase variations by iteratively enforcing known constraints in the exit pupil and at the detector, determined from modeled or measured data. The Variable Sampling Mapping (VSM) technique is a new method for enforcing these constraints in ITAs. VSM is an open framework for addressing a wide range of issues that have previously been considered detrimental to high-accuracy phase retrieval, including undersampled images, broadband illumination, images taken at or near best focus, chromatic aberrations, jitter or vibration of the optical system or detector, and dead or noisy detector pixels. The VSM is a model-to-data mapping procedure. In VSM, fully sampled electric fields at multiple wavelengths are modeled inside the phase-retrieval algorithm, and then these fields are mapped to intensities on the light detector, using the properties of the detector and optical system, for comparison with measured data. Ultimately, this model-to-data mapping procedure enables a more robust and accurate way of incorporating the exit-pupil and image detector constraints, which are fundamental to the general class of ITA phase retrieval algorithms.

Smith, Jeffrey, S.↗

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

NASA’s Life Sciences Ports (NLSP) serves the scientific community by providing curated data from space life science experiment. The Human Research Program (HRP) with the help of NLSP is currently transforming their life sciences data archive systems and processes to improve compliance with the FAIR principles [1]. Some of these improvements will at the same time support the twin pillars of Open Science [2]: transparency of methods and reproducibility of results. Scientific transparency is marked by the easily intelligible communication of what has been investigated: what were the procedures for collecting sample and the characteristics of samples collected? what kinds of measurements were made, what were the environmental conditions of the measurements? What were the analysis techniques of the collected data? Reproducibility of the results and findings from the investigation requires a high level of transparency for all but the simplest investigations; the slightest deviation in communicating and replicating complex experimental procedures or data analyses can often yield quite different data and even findings, thwarting their validation. One of the ways the NLSP is aiming to improve the communication of scientific information is through the use of ontology-driven metadata. Ontologies are powerful, graph-based knowledge representation structures, which can be leveraged to increase data interoperability, the area of the FAIR principles in which many data systems most lack compliance. Over the past decade, there has been a concerted effort in the biomedical community to develop modular and narrowly focused domain and application-specific ontologies in a common, open-source framework, the Open Biological and Biomedical Ontology (OBO) Foundry [3]. The open sharing and modular nature of this effort promises huge increases in harmonized data sharing for systems that leverage these models. Which is in line with the FAIR Data Principles of Findability, Accessibility, Interoperability, and Reuse for scientific data management and stewardship. 1. Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. 2. National Academies of Sciences, E. and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. 2018, Washington, DC: The National Academies Press. 232. 3. Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5.

Life Sciences data↗

Rapid Lightweight Firmware Architecture of the Mobile Metamaterial Internal Co-Integrator Robot

The Mobile Metamaterial Internal Co-Integrator (MMIC-I) is a structure assembly and servicing robot for in-space servicing, assembly, and manufacturing of primary structures and infrastructure. MMIC-I is a battery-powered crawling robot that can travel through periodic structures such as trusses and open framework mechanical metamaterials. It does this through sequences of component extension, contraction, and gripping. This paper provides a detailed discussion of MMIC-I’s lightweight and rapidly developed firmware architecture, to enable demonstration of robot locomotion, secondary operations, and communications with a central command source. The rationale for the lightweight rapid development approach is to allow for assessment of long term system requirements in parallel with the mechatronics development, including optimization of system and subsystem power densities, to inform a future choice of flight ready software frameworks. MMIC-I system computing and I/O requirements are much lower than what is provided by proven baseline computing hardware for existing flight ready software frameworks such as the core Flight System, F prime, and the Robot Operating System. Development of earth gravity ground demonstration of the robotic systems is greatly benefited by limited power and mass factors for computing hardware. Here, we implement inter-process communication, commanding, and telemetry with the Espressif ESP32 module running the Arduino OS.

Damiana Catanoso↗

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

NASA’s Life Sciences Ports (NLSP) serves the scientific community by providing curated data from space life science experiment. The Human Research Program (HRP) with the help of NLSP is currently transforming their life sciences data archive systems and processes to improve compliance with the FAIR principles [1]. Some of these improvements will at the same time support the twin pillars of Open Science [2]: transparency of methods and reproducibility of results. Scientific transparency is marked by the easily intelligible communication of what has been investigated: what were the procedures for collecting sample and the characteristics of samples collected? what kinds of measurements were made, what were the environmental conditions of the measurements? What were the analysis techniques of the collected data? Reproducibility of the results and findings from the investigation requires a high level of transparency for all but the simplest investigations; the slightest deviation in communicating and replicating complex experimental procedures or data analyses can often yield quite different data and even findings, thwarting their validation. One of the ways the NLSP is aiming to improve the communication of scientific information is through the use of ontology-driven metadata. Ontologies are powerful, graph-based knowledge representation structures, which can be leveraged to increase data interoperability, the area of the FAIR principles in which many data systems most lack compliance. Over the past decade, there has been a concerted effort in the biomedical community to develop modular and narrowly focused domain and application-specific ontologies in a common, open-source framework, the Open Biological and Biomedical Ontology (OBO) Foundry [3]. The open sharing and modular nature of this effort promises huge increases in harmonized data sharing for systems that leverage these models. Which is in line with the FAIR Data Principles of Findability, Accessibility, Interoperability, and Reuse for scientific data management and stewardship.

Life Sciences data↗

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Greg Schuster↗

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Elisabeth Andrews↗

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Greg Schuster↗