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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Nuclear data covariances are critical input to determine upper sub-critical limits and to design experiments to increase it [Slides]

This presentation discusses how Upper Subcritical Limits (USL) are key parameters to determine operational limits in nuclear criticality safety evaluations. It also discusses an example of plutonium casting operation using tantalum at LANL PF-4. The Whisper tool at Los Alamos relies on many inputs, including covariance data, leading the presentation to ask if an existing benchmark data be used in Whisper to adjust nuclear data and covariances to justify a higher USL. If not, Whisper can be used to help design an optimal new benchmark experiment. The presentation also seeks to determine what the possible impacts are on USL and operational limits for plutonium casting. In conclusion, nuclear data covariances are used for by Whisper for: GSSL adjustment of nuclear data and covariances, identification of most similar existing benchmark experiments to application, simulation of Upper Subcritical Limit of application, and input to optimization techniques for designing most appropriate new benchmark experiment(s) to meet requirements. This requires a complete set of nuclear data covariances, benchmarks and k-effective sensitivity profiles (for both benchmarks and applications). The presentation concludes by asking if end users should trust results that depend on current covariance data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Critical Minerals Leadership Academy: Building a Cross-Disciplinary Workforce for the Evolving Critical Minerals Sector

This presentation was submitted to the Society for Mining, Metallurgy, and Exploration (SME) MineXchange annual conference in Salt Lake City, Utah. This abstract and subsequent presentation provide an overview of the Critical Minerals Leadership Academy (CMLA) that took place in Laramie, Wyoming in August of 2025. The presentation includes information regarding the development of the CMLA, a review of the event, and information regarding participants, their backgrounds and future intentions.

58 GEOSCIENCES↗
DOE OSTI2021

A Critical Review of Challenges Faced by Converting Food Waste to Bioenergy Through Anaerobic Digestion and Hydrothermal Liquefaction

Here, the conventional approaches for handling food waste has been incineration, composting, landfilling, and anaerobic digestion for producing biogas. In light of organic waste bans and newly discovered presence of per- and polyfluorinated substances (PFAS) in food, food packaging materials, and compost, this review provides a critical summary of what has been investigated and reported and what needs to be considered when choosing suitable pathways for food waste. In addition to the fundamental principles inherent to anaerobic digestion and hydrothermal liquefaction, challenges for each process are identified followed by discussion of potential solutions to resolve the bottlenecks.

09 BIOMASS FUELS↗
DOE OSTI2024

Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics

The importance of data curation has been recognized in multiple areas of research; however, the discussion of this important issue is only beginning to emerge in materials science. In this Perspective, we highlight the benefits of using the standardized data curation protocols in materials science and discuss current gaps in accurate and reproducible data reporting using case studies drawn from high-impact materials science papers and well-known databases such as the Crystallography Open Database (COD) and the Cambridge Structural Database (CSD). We argue that both experimental and computational materials scientists need to embrace a culture of rigorous data curation as part of modern research data management. We propose a sample data curation pipeline for materials chemistry and illustrate its use by creating two new materials chemistry databases. Here, we hope that this perspective will serve to catalyze further discussion and promote the continuous development of rigorous data curation practices within the materials science research community. We posit that adherence to best practices of data curation will promote and enhance the reliability, reproducibility, and integrity of materials research and enable the development of reliable AI and machine learning models that critically depend on the use of quality data.

Chemical structure↗
DOE OSTI2021

A critical review on the progress and challenges to a more sustainable, cost competitive synthesis of adipic acid

Adipic acid is a key organic diacid intermediate used in nylon manufacturing. It is primarily produced by an industrial process that can form nitrous oxide as a byproduct. Nitrous oxide has a 300-fold higher global warming potential than carbon dioxide, and an estimated 10% of its annual global emissions are a result of adipic acid production. These concerns have led to significant efforts for the development of nitrous oxide mitigation technologies as well as more environmentally friendly routes for adipic acid production. New processes include both advanced chemical and biotechnological routes. Here in this review, we discuss key recent developments in mitigation as well as new technologies. We also provide a critical look at the potential of new technologies to compete with the incumbent process and highlight key remaining technical challenges to the development of greener (environmentally sustainable) and cost competitive (commercially sustainable) processes for adipic acid manufacture.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Arctic Critical Infrastructure: Assessing and Predicting the Risk to Critical Permafrost Infrastructure from Climate Change: A New Thermomechanical Approach

This study presents the development of a computational framework designed to predict the interaction between permafrost and infrastructure, addressing potential failure modes and mitigation strategies in the context of climate change. The framework, rooted in advanced modeling and simulation (mod/sim) techniques, integrates thermomechanical coupling to account for the complex interplay between heat flow, ice content, and mechanical behavior in permafrost. Existing models fail to fully capture these dynamics, particularly as they relate to the effects of ice saturation on structural integrity. Our innovative Arctic Coastal Erosion (ACE) framework fills this gap by coupling thermal and mechanical models to accurately simulate subsidence and deformation in permafrost environments. We applied the ACE framework to a representative runway, demonstrating its capability to predict settlement due to rising temperatures and subsequent permafrost thaw. This proof-of-concept showcases the potential of the framework to evaluate risks to Arctic infrastructure, which supports over four million people and 70% of existing permafrost-based structures. By simulating various infrastructure types and environmental conditions, our research offers insights into failure mechanisms and evaluates structural solutions to mitigate risk. The anticipated deliverables, including a prototype runway exemplar, position this project as a critical advancement in permafrost infrastructure modeling, with applications in national security and resilience planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

With the increasing digitalization of processes throughout the lifecycle of buildings, data exchanged between stakeholders and between building systems has grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent, hindering the development of applications that can be reused across buildings and limiting the scalability of innovative solutions. Semantics refers to the description of the meaning of the data in a way that can be consistently understood by applications. Recently, several competing initiatives have been developing metadata schemas and ontologies to express this semantic information for different applications in the building domain. This paper systematically reviews these schemas and conducts an analysis of five of them to evaluate their applicability to three high-value use cases for building operations: energy audits, automated fault detection and diagnostics and optimal control. The survey finds 40 schemas published in the last 10 years but but their actual use in industry is difficult to estimate. Among the five selected ontologies, several gaps are highlighted in relation to the three use cases. Recommendations for the future include better harmonization of these initiatives, more centralized repositories and search engines for these schemas as well as better industry engagement to facilitate their adoption.

Smart Building, Sematic, Metadata, Ontology, Data ↗
DOE OSTI2021

Criticality Accident Alarm System Shielding Benchmark: Integral Experiment Request 498, Critical Engineering Decision 2 Report

A workable design to perform a CAAS benchmark experiment is detailed herein. Key dimensions, materials, source intensity levels, and detectors are listed in this report. Sensitivity to 21 perturbations was determined to be acceptable. The next step will be for NCSP management to determine whether procurement should occur and if the experiment should proceed. The perturbation study suggests that the room return shield cavity radius and runout should be maintained to within a millimeter, the room return shield should be positioned carefully (perhaps with a laser range finder), and that the detectors should be mounted in a lightweight fixture such as aluminum, so their positioning is assured. Using a 3D scanner or photogrammetry to record part shapes may be beneficial. Further work is also needed to verify source reproducibility.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Current Status of the DOE/NNSA Nuclear Criticality Safety Program Hands-on Criticality Safety Training Courses [Slides]

The NCSP training and education program has been conducted since 2011 and has trained over 591 students. 388 students have been trained in the 2-week hands-on course for practitioners and 203 students have been trained in the 1-week manager courses. The course is continuously improved using lessons-learned from the prior year, and new course content is added as necessary. Special courses are developed and offered periodically at the discretion of the NCSP manager. The updated manager course for CSOs was successfully piloted at NCERC in June 2020 and was successfully piloted at Sandia in April 2022. Students interested in taking the courses should visit the DOE NCSP website for additional information about all course offerings and for information about course registration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives

Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit about one-third of greenhouse gases. In the last few years, machine learning has achieved a notable momentum that, if properly harnessed, may unleash its potential for advanced analytics and control of smart buildings, enabling the technique to scale up for supporting the decarbonization of the building sector. In this perspective, transfer learning aims to improve the performance of a target learner exploiting knowledge in related environments. The present work provides a comprehensive overview of transfer learning applications in smart buildings, classifying and analyzing 77 papers according to their applications, algorithms, and adopted metrics. The study identified four main application areas of transfer learning: (1) building load prediction, (2) occupancy detection and activity recognition, (3) building dynamics modeling, and (4) energy systems control. Furthermore, the review highlighted the role of deep learning in transfer learning applications that has been used in more than half of the analyzed studies. The paper also discusses how to integrate transfer learning in a smart building's ecosystem, identifying, for each application area, the research gaps and guidelines for future research directions.

Pinto, G↗
DOE OSTI2021

Grey-box modeling and application for building energy simulations - A critical review

Grey-box modeling, as one of the three fundamental modeling techniques for building energy models, has many advantages compared with black-box modeling and white-box modeling. Additionally, it has been widely applied to solve problems of building technologies, such as building load estimation, control and optimization, and building-grid integration. However, a thorough review of grey-box modeling is not available. This review study systematically investigated various aspects of grey-box modeling for buildings. First, the fundamental aspects of grey-box modeling are presented, including the theoretical background, modeling of building elements, modeling order, modeling diagram, and order reduction. Second, the detailed modeling approaches are discussed. Third, multiple applications of grey-box modeling are investigated for building energy domain, which are categorized into the following groups: heat dynamics analysis, thermal load estimation, building control and optimization, district/urban scale energy modeling, and building-grid integration. Finally, the available software packages for grey-box modeling are compared. Overall, the challenges of using grey-box modeling can be summarized as follows: (1) the theoretical limitations and assumptions of grey-box modeling are unclear; (2) grey-box model naming convention and structure are confusing; (3) grey-box model creation is vague; (4) suitable applications of grey-box models are unknown; and (5) grey-box models lack unified software solutions for wider adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗