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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 55 records · Page 3

Monitoring Biomarkers for Muscular Atrophy using an Electronic Chip for Astronaut Health

Skeletal muscle atrophy is a serious health problem for astronauts in long-duration space flight under microgravity conditions. Preventative measures against muscle atrophy require specific exercise and dietary regimens. Preemptive measurements to improve treatment have the potential to streamline these regimens, decreasing their daily footprint and increasing astronaut quality of life. The objective of our proposed project is to (1) develop a fully integrated disposable microelectrode array chip (with the size of a stamp) that can be interfaced with a handheld electronic system for simultaneous detection of the a panel of biomarkers to monitor the progression of skeletal muscle atrophy due to disuse under microgravity in long-duration spaceflights; and (2) use such quantitative information to guide the combined countermeasures of physical exercise and pharmaceuticals (i.e. specific protease inhibitors) so that the intensity, duration and frequency of exercise can be reduced.

Biosensing↗

Porous carbon from lignocellulosic biomass with emphasis on corn plant waste residue for energy storage

The rising global demand for sustainable energy storage materials has driven the search for environmentally friendly and cost-effective electrode options. Hydrothermal conversion of lignocellulosic biomass has gained attention due to its low energy requirements and operation at relatively low temperatures, presenting a green alternative to traditional thermochemical methods. The resulting solid product, hydrochar, has been used as an adsorbent and soil amendment; however, chemical/thermal treatment significantly enhances its physical properties. These structural modifications transform hydrochar into an effective porous carbon electrode, offering abundant sites for electrolyte ion transport, critical for high-performance devices like supercapacitors and batteries. This review first discusses various waste biomass and sustainable feedstocks available globally. It compares two primary thermochemical conversion techniques, pyrolysis and hydrothermal carbonization/liquefaction, and examines their respective solid products, biochar and hydrochar, analyzing differences in their physical and chemical characteristics. The focus is placed on hydrochar, summarizing activation methods to produce porous carbon suitable for energy storage applications. Additionally, this review will include a dedicated section on the application of porous carbon derived from corn plant waste residue, considering that corn is one of the most abundant crops grown worldwide, which makes it an important and promising source for sustainable porous carbon production. The role of machine learning models in optimizing hydrothermal processes to produce high-quality hydrochar is also discussed, emphasizing how data-driven approaches can streamline process development. Finally, the review identifies the current challenges and prospects for lignocellulosic biomass-derived porous carbon as a sustainable electrode material in next-generation energy storage technologies.

25 ENERGY STORAGE↗

In-Plane Liftout and Push-to-Pull for In Situ Mechanical Testing of Irradiated Inconel X-750

A streamlined sample preparation method for nanomechanical testing is needed to improve the quality of specimens, reduce the cost, and increase the versatility of specimen fabrication. This work outlines an in-plane liftout focused ion beam (FIB) fabrication procedure to prepare electron-transparent specimens for in situ transmission electron microscopy (TEM) nanomechanical testing. Ion etching and electron backscatter diffraction (EBSD) techniques were used to lift out a [110] oriented grain from a neutron-irradiated bulk X-750 alloy. Careful control of voltages and currents ensured precision. Top surface thinning sweeps prevented resurfacing and redeposition while dog-bone geometries were shaped with a 1:4 gauge width-to-milling pattern diameter ratio. Nanotensile testing in the TEM with a picoindenter allowed for the estimation of an ultimate tensile strength of 2.41 GPa, and inspection revealed a high density of bubbles in the X-750 matrix. The proposed fabrication procedure is significant for preparing samples from radioactive materials, studying complex structures that are orientation-dependent, and analyzing desired planar areas.

36 MATERIALS SCIENCE↗

pyQuARC: Open Source Library for Earth Observation Metadata Quality Assessment

Metadata quality is essential to effective data discovery and has become increasingly vital as more Earth Science data sets become available. The Common Metadata Repository (CMR) hosts metadata describing NASA’s Earth Observation data products, which are archived across 12 Distributed Active Archive Centers (DAACs). The Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, conducts metadata quality assessments to ensure that these data products are discoverable, accessible, and usable. To achieve these goals, the ARC team has developed a metadata quality assessment framework to evaluate metadata completeness, correctness, and consistency. ARC uses a combination of manual and automated methods to assess these three components and identify areas of improvement; the team then collaborates with the DAACs to resolve any findings. To streamline this process, ARC is currently developing a host of scripts, known as pyQuARC, to automate metadata quality assessments as much as possible. pyQuARC is an open source library for Earth Observation Metadata Quality Assessment, and the tool utilizes ARC’s metadata quality assessment framework to make basic validation checks, pinpoint inconsistencies between dataset-level (i.e. collection) and file-level (i.e. granule) metadata, and identify opportunities for more descriptive and robust information. Since pyQuARC is also customizable, other users can make modifications as needed, and future metadata standards can also be implemented. Once pyQuARC is fully developed, it will support multiple schema types to serve the broader EOSDIS metadata community. This presentation will provide an overview of pyQuARC and its process of development while showcasing the tool’s valuable features and uses.

Jenny Wood↗

An experimental investigation of the flow physics of high-lift systems

This progress report is a series of overviews outlining experiments on the flow physics of confluent boundary layers for high-lift systems. The research objectives include establishing the role of confluent boundary layer flow physics in high-lift production; contrasting confluent boundary layer structures for optimum and non-optimum C(sub L) cases; forming a high quality, detailed archival data base for CFD/modelling; and examining the role of relaminarization and streamline curvature. Goals of this research include completing LDV study of an optimum C(sub L) case; performing detailed LDV confluent boundary layer surveys for multiple non-optimum C(sub L) cases; obtaining skin friction distributions for both optimum and non-optimum C(sub L) cases for scaling purposes; data analysis and inner and outer variable scaling; setting-up and performing relaminarization experiments; and a final report establishing the role of leading edge confluent boundary layer flow physics on high-lift performance.

Thomas, Flint O.↗

Shuttle Repair Tools Automate Vehicle Maintenance

Successfully building, flying, and maintaining the space shuttles was an immensely complex job that required a high level of detailed, precise engineering. After each shuttle landed, it entered a maintenance, repair, and overhaul (MRO) phase. Each system was thoroughly checked and tested, and worn or damaged parts replaced, before the shuttle was rolled out for its next mission. During the MRO period, workers needed to record exactly what needed replacing and why, as well as follow precise guidelines and procedures in making their repairs. That meant traceability, and with it lots of paperwork. In 2007, the number of reports generated during electrical system repairs was getting out of hand-placing among the top three systems in terms of paperwork volume. Repair specialists at Kennedy Space Center were unhappy spending so much time at a desk and so little time actually working on the shuttle. "Engineers weren't spending their time doing technical work," says Joseph Schuh, an electrical engineer at Kennedy. "Instead, they were busy with repetitive, time-consuming processes that, while important in their own right, provided a low return on time invested." The strain of such inefficiency was bad enough that slow electrical repairs jeopardized rollout on several occasions. Knowing there had to be a way to streamline operations, Kennedy asked Martin Belson, a project manager with 30 years experience as an aerospace contractor, to co-lead a team in developing software that would reduce the effort required to document shuttle repairs. The result was System Maintenance Automated Repair Tasks (SMART) software. SMART is a tool for aggregating and applying information on every aspect of repairs, from procedures and instructions to a vehicle s troubleshooting history. Drawing on that data, SMART largely automates the processes of generating repair instructions and post-repair paperwork. In the case of the space shuttle, this meant that SMART had 30 years worth of operations that it could apply to ongoing maintenance work. According to Schuh, "SMART standardized and streamlined many shuttle repair processes, saving time and money while increasing safety and the quality of repairs." Maintenance technicians and engineers now had a tool that kept them in the field, and because SMART is capable of continually evolving, each time an engineer put it to use, it would enrich the Agency-wide knowledge base. "If an engineer sees something in the work environment that they could improve, a repair process or a procedure, SMART can incorporate that data for use in future operations," says Belson.

Source record↗

Cartographic products in Space Shuttle earth observations operations

A description is given of the Automated Planning Mission Planning System (AMPS), a computer cartographic system developed by NASA in response to the need to streamline support for an increasing number and frequency of Shuttle missions and to enhance the quality of products produced for mission support. AMPS is menu driven and can plot orbit tracks and revolution times and site boundaries on Mercator projection maps. As an overall site selection process approaches, AMPS reduces the possibility of errors, is time effective, improves SSEOP products, and is adaptable for other related applications.

Lulla, Kamlesh↗

An experimental investigation of the flow physics of high-lift systems

This progress report, a series of viewgraphs, outlines experiments on the flow physics of confluent boundary layers for high lift systems. The design objective is to design high lift systems with improved C(sub Lmax) for landing approach and improved take-off L/D and simultaneously reduce acquisition and maintenance costs. In effect, achieve improved performance with simpler designs. The research objectives include: establish the role of confluent boundary layer flow physics in high-lift production; contrast confluent boundary layer structure for optimum and non-optimum C(sub L) cases; formation of a high quality, detailed archival data base for CFD/modeling; and examination of the role of relaminarization and streamline curvature.

Thomas, Flint O.↗

Data Curation for Machine Learning Applied to Geothermal Power Plant Operational Data for GOOML: Geothermal Operational Optimization with Machine Learning: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach to physics-guided, data-centric machine learning. This framework has been used to develop digital twins that provide steamfield operators with operational environments to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management in real world applications. To create, test, and apply the GOOML framework, diverse time-series datasets spanning multiple years were sourced from various geothermal power plant components within several complex real-world geothermal operations. These operations are based in the United States and New Zealand and include a variety of technologies, end-uses and configurations, collectively covering nearly all relevant operating conditions for modern geothermal fields. Datasets were acquired from multiple sources to ensure that machine learning experiments generalized properly to various operating conditions. It was found that the data varied in quality, format, and completeness. To ensure consistency between the various datasets, a standardized data curation process was developed to reliably streamline data preparation. This paper will discuss best practices as learned from the GOOML data curation process which takes the following steps: 1) acquisition of large quantities of data from power plant operators, 2) digestion of data to gain an initial understanding of what is included, 3) data transformation, which includes converting the data into a standardized machine-readable format so that they can be visualized, quality checked, and cleaned, 4) quality assurance and quality control, involving identification of significant data gaps and apparent anomalies through mapping of data features to real world componentry via the GOOML historical model, followed by discussion with modelers and power plant operators to identify additional data needs and to resolve issues, 5) use in machine learning algorithms, and 6) repetition of steps one through five until all data needs are met and data are deemed suitable for producing trustworthy modeling results which may be disseminated, ideally along with the curated dataset. This iterative process is focused on improving the quality of the data rather than tuning machine learning model parameters and supports a shift towards data-centric AI as a means to improving real-world applicability of geothermal machine learning projects.

access↗

Use of Open Networks and Delay-Tolerant Protocol to Decrease WAN Latency of EOS near Real-Time Data

Since 1999, NASA's Earth Observing System Data Operations System (EDOS) project at Goddard Space Flight Center (GSFC) has provided high-rate data capture, level zero processing, and product distribution services for a majority of NASA's EOS (Earth Observing System) high-rate missions, including Terra, Aqua, Aura, ICESat, EO-1, SMAP, and OCO-2. EDOS high-rate science and engineering (150-300 Mbps) data-driven capture systems are deployed at 7 worldwide ground stations which are connected via both private (closed) and public (open) wide area networks (WANs) to the centralized EDOS Level Zero Processing Facility (LZPF) located at GSFC, where the data is processed and Level 0 products are distributed to users worldwide. All data transferred over the open networks to GSFC traverse an IPSec tunnel, providing the same level of security as a VPN connection. EDOS produces both time-based and near real-time products (session-based). Near real-time data products are produced from a single ground station contact; time-based products are produced from multiple ground station contacts. EDOS is the primary supplier of EOS Level 0 data to the NASA near real-time user community known as the Land, Atmosphere Near real-time Capability for EOS (LANCE). For the past few years, EDOS has streamlined its systems to reduce WAN latency for near real-time data delivery, including implementing Quality of Service (QoS), expanding closed network bandwidth, adding open network connections with more bandwidth, and implementing a delay-tolerant protocol to mitigate long round-trip times to remote ground stations.

Delay-Tolerant Protocol↗

Harmonization of experimental approach and data collection to streamline analysis of biomass composition from algae in an inter-laboratory setting

In order to establish and design long-term algae cultivation experiments, inter-laboratory projects need to harmonize the requirements of techno-economic and life-cycle analysis models, with standardized data inputs. In order to provide a consistent foundation and allow for integration and analysis of the results in computational technical and resource analysis models, we implemented closely coordinated, harmonized and objective analytical protocols along with a common language for measuring growth and productivity for the major algal components. We describe here the process by which we developed a harmonization framework for analysis across five geographically diverse testbed sites. Our goal was to align analytical procedures to ensure consistent reporting on biomass and lipid content, quality and yields to eliminate measurement variability as a source of uncertainty in production data. Developing standards for analysis that streamline reporting on composition and expected fuel yields from biomass is one of the major outcomes of this work and this provides a starting place for further advanced characterization of algae to support the techno-economical process analyses and account for the mass balance accounting of algal biomass. In conclusion, initial analysis of data obtained from field studies shows trends in compositional shifts of lipid and protein content of the biomass that are in support of the physiological experiments demonstrated in the first geographically distributed unified outdoor cultivation trials.

09 BIOMASS FUELS↗

The HL-20 Personnel Launch System

A lifting-body approach to the design of a personnel launch system spacecraft for Space Station crew rotation missions is presented. Recent study findings in the areas of wind tunnel tests, landing dynamics, handling qualities, and abort are summarized. HL-20, which is designed for safe and reliable operations, has improved operability, maintainability, and affordability as compared to current manned transportation operations. The high lift-to-drag ratio of the HL-20 provides significant advantages in reduced g-loads during entry, high crossrange capability, ability to fly to landing sites over an extensive part of the earth, and multiple landing opportunities per day at specific landing sites. Pilot ratings of the flying qualities are at level 1 on the Cooper-Harper scale. Attention is also given to a streamlined management approach to HL-20 PLS development and operations which are presently under study.

Talay, Theodore A.↗

Systems Maintenance Automated Repair Tasks (SMART)

SMART is an interactive decision analysis and refinement software system that uses evaluation criteria for discrepant conditions to automatically provide and populate a document/procedure with predefined steps necessary to repair a discrepancy safely, effectively, and efficiently. SMART can store the tacit (corporate) knowledge merging the hardware specification requirements with the actual "how to" repair methods, sequences, and required equipment, all within a user-friendly interface. Besides helping organizations retain repair knowledge in streamlined procedures and sequences, SMART can also help them in saving processing time and expense, increasing productivity, improving quality, and adhering more closely to safety and other guidelines. Though SMART was developed for Space Shuttle applications, its interface is easily adaptable to any hardware that can be broken down by component, subcomponent, discrepancy, and repair.

Source record↗

Towards Streamlining Auditing for Compliance With Requirements in Open-Source Software at NASA

Context: NASA requires all software to meet several requirements (NPR 7150.2) depending on software criticality. The instantiation of these requirements may vary per project; however, once decided upon, projects must undergo audits to evaluate compliance with these requirements. Aim: We propose that audit effort can be reduced when requirements are realized by leveraging commonly used open-source infrastructure for version control, issue tracking and continuous integration, and the generated records are analyzed using a repository mining software tool to quantify process compliance. Method: We perform a case study in the NASA-funded Copilot project, utilizing Kaiaulu, a repository mining software tool. We define four software compliance metrics based on the Copilot’s requirements, and analyze their impact on source code quality. Results: Our work demonstrates how it is possible to leverage existing open source tools and platforms to facilitate software certification and qualification, and to streamline the auditing process required even when stringent requirements must be enforced. Conclusion: Together, both project and tool can be utilized to visualize project compliance, and metrics can be defined to more easily identify process irregularities to minimize auditing efforts. Project Repository: github.com/Copilot-Language/copilot Tool Repository: github.com/sailuh/kaiaulu

code-quality↗

WREF Halo Streamline scanning lidar / Derived data / RHI

This dataset contains streamwise velocity retrieved from the Range Height Indicator (RHI) scans done by the UC Davis scanning Lidar. The quality control of the radial wind speed is performed following the algorithm of Beck & Kuhn (2017). Instantaneous realizations characterized by wind misalignment greater than 60 degrees (based on the closest VAD scan in time) are discarded.

17 WIND ENERGY↗