NASA Spacecraft Conjunction Assessment and Collision Avoidance Best Practices Handbook
Explore the source record for details and available documents.
SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
Some of the Earth system data products such as those from NASA airborne and field investigations (a.k.a. campaigns), are highly heterogeneous and cross-disciplinary, making the data extremely challenging to manage. For example, airborne and field campaign measurements tend to be sporadic over a period of time, with large gaps. Data products generated are of various processing levels and utilized for a wide range of inter- and cross-disciplinary research and applications. Data and derived products have been historically stored in a variety of domain-specific standard (and some non-standard) formats and in various locations such as NASA Distributed Active Archive Centers (DAACs), NASA airborne science facilities, field archives, or even individual scientists’ computer hard drives. As a result, airborne and field campaign data products have often been managed and represented differently, making it onerous for data users to find, access, and utilize campaign data. Some difficulties in discovering and accessing the campaign data originate from the incomplete data product and contextual metadata that may contain details relevant to the campaign (e.g. campaign acronym and instrument deployment locations), but tend to lack other significant information needed to understand conditions surrounding the data. Such details can be burdensome to locate after the conclusion of a campaign. Utilizing consistent terminology, essential for improved discovery and reuse, is also challenging due to the variety of involved disciplines. To help address the aforementioned challenges faced by many repositories and data managers handling airborne and field data, this presentation will describe stewardship practices developed by the Airborne Data Management Group (ADMG) within the Interagency Implementation and Advanced Concepts Team (IMPACT) under the NASA’s Earth Science Data systems (ESDS) Program.
Explore the source record for details and available documents.
This is the first revision by the Office of the Chief Engineer of the 2020 Handbook updated to reflect the release of NPR 8079.1, NASA Spacecraft Conjunction Analysis and Collision Avoidance for Space Environment Protection.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Material degradation during the fabrication of microelectronic devices has plagued the space industry for many years owing to the layering of many dissimilar metals to create these devices. Often, commonly used materials and systems are overlooked as potential sources of material degradation. This technical bulletin highlights extensive research to isolate probable causes of this degradation.
This article continues the overview of the U.S. Department of Energy and IDEA collaboration by highlighting additional case studies that demonstrate innovative engineering approaches in district energy systems. It focuses on how campuses are improving efficiency, integrating advanced technologies, and reducing energy use and emissions through data-driven strategies. The University of Cincinnati is featured for its highly efficient chilled water system, using advanced algorithms and upgraded “smart chillers” to optimize performance, reduce energy consumption, and lower costs. Wake Forest University emphasizes a data-informed modernization process, using system optimization and targeted building improvements to significantly boost efficiency and reduce overall energy use. Arizona Western College showcases creative solutions to extreme cooling demands, including system redesign, smart controls, and thermal storage to improve reliability and cut peak energy costs. Overall, the article demonstrates that combining innovative engineering, real-time data analysis, and system optimization can significantly enhance performance, reduce emissions, and deliver cost savings in district energy systems.
This article, the fourth and final installment in the DOE–IDEA series, focuses on organizational execution and how strong management practices, teamwork, and preparedness contribute to successful district energy systems. It highlights case studies from Ashley Energy and Cornell University to illustrate effective operational strategies. Ashley Energy demonstrates the importance of emergency preparedness and rapid response. After a major flood disrupted its plant, the organization restored service in under 72 hours by relying on pre-established plans, vendor relationships, and trained staff. The case emphasizes proactive contingency planning, understanding insurance processes, and empowering skilled personnel to improvise during crises. Cornell University’s example highlights the role of collaboration and transparency in long-term success. Its district energy system benefits from strong data sharing, real-time energy monitoring, and active involvement of faculty and students in system planning and innovation. This culture of teamwork and data-driven decision-making supports sustainability goals and continuous system improvement. Overall, the article shows that effective organizational execution—through preparedness, collaboration, and data transparency—is essential for maintaining reliable, efficient, and sustainable district energy systems.
An ideal chelator for f-elements features rapid kinetics of complexation, high thermodynamic stability, and slow kinetics of dissociation. Here we present the facile synthesis of a macrocyclic ligand bearing four 1-hydroxy-2-pyridinone units linked to a cyclen scaffold that rapidly forms thermodynamically stable complexes with lanthanides (Sm 3+ , Eu 3+ , Tb 3+ , Dy 3+ ) and a representative late actinide (Cm 3+ ) in aqueous media and concurrently sensitizes them. Extended X-ray absorption fine structure (EXAFS) spectroscopy revealed an increase in the Ln/An-O bond lengths following the trend Cm>Eu>Tb and EXAFS data were compatible with time-resolved luminescence studies, which indicated one to two water molecules in the inner metal coordination sphere of Eu(III) and two water molecules for the Cm(III) complex. Spectrofluorimetric ligand competition titrations against DTPA confirmed the high thermodynamic stability of DOTHOPO complexes, with pM values between 19.9(1) and 21.9(2).
This manuscript explores six controversial topics regarding LCA of emerging technologies: (1) appropriate use of LCA, (2) uncertainty assessment, (3) comparison with incumbents, (4) adopting standards, (5) system scale-up, and (6) stakeholder engagement. These topics encompass key issues vigorously debated during a series of workshop-style discussions convened by the LCA of Emerging Technologies Research Network (currently hosted by ACLCA). This paper represents the main points of support and opposition for a declarative resolution representing each topic, along with points of consensus, held amongst research network of LCA practitioners and experts. These debates and associated open questions are intended to build awareness amongst practitioners and decision-makers of the common challenges associated with assessing emerging technologies, while fostering evidence-based and context-informed discussions that are both transparent and impactful for the broader community.
The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.
Buildings are responsible for 38% of global greenhouse gas (GHG) emissions and, therefore, pathways to reduce their impact are crucial to achieve climate targets. Building stock energy models (BSEMs) have long been used as a tool to assess the current and future energy demand and environmental impact of building stocks. BSEMs have become more and more complex and are often tailored to case-specific datasets, which results in a high degree of heterogeneity among models. This heterogeneity, together with a lack of consistency in the reporting hinders the understanding of these models and, thereby, an accurate interpretation and comparison of results. In this paper we present a reporting guideline in order to improve reporting practices of BSEMs. The guideline was developed by experts as part of the IEA's Annex 70 and builds upon reporting guidelines from other fields. It consists of five topics (Overview, Model Components, Input and Output, Quality Assurance and Additional Information), which are further subdivided into subtopics. We explain which model aspects should be described in each subtopic, and provide illustrative examples on how to apply the guideline. In closing, the reporting guideline is consistent with the model classification framework and online model registry also developed in the Annex.
Solid oxide electrolyzer (SOE) technology is an emerging method for hydrogen production, noted for its superior electrical efficiency. Despite the significant progress made in recent years, the broad development of SOE technology is often constrained by the necessary and extensive "skill of the craft" required to successfully test simple single cell test articles. This may be linked to the dearth of practical and pragmatic guidance within the literature for safe, reliable, and performant test equipment and test procedures. Researchers at the Idaho National Laboratory (INL) have been actively testing SOEs ranging from button cells to stacks up to 500 kW, in collaboration with industry and other national laboratories. Based on operational experience, INL has developed system design procedures that ensure safe and reliable operation of SOE systems with the level of support required for each test. This paper presents key aspects of SOE stack and system testing, including safe design procedures, balance of plant components design, and specific implementations at INL. Practical design details of reactants, heat, and power management are presented along with lessons learned from the SOE test facility operations at INL.