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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Millennial Time Capsules as a Promising Means for Preserving Records for Future Generations - 16542

When we deal with preservation of Records, Knowledge and Memory (RK and M) for any long-term, non-inspected facility such a deep geological repository, there is no single technical or cultural provision that can be relied upon to do alone the preservation job 100%. Rather we should increase our chances by implementing a combination of approaches based on different components that provide redundancy and/or pointers to one another. Time capsules are no exception. However, they seem well suited to support national archives and other preservation elements, in order to preserve RK and M as long as possible or interesting. Time capsules are a ready to go, workable concept, with many examples of implementation of large-size, millennial time capsules at small depths based on science and lessons to be learned. A proposal is also made for considering and developing small-size time capsules placed strategically deep underground at repository level. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Nuclear, Land marker for a Waste Isolation Site: International Architecture Competition - 18240

The design and construction of a nuclear waste marker must include many architectural considerations. Very little research has been conducted by architects to address this issue to date. Historically, the task of designating a nuclear waste site has been a discussion predominantly contained within the scientific and engineering communities. In an effort to engage architects within this dialogue, arch out loud hosted the NUCLEAR competition as an international, architectural investigation into the design of a nuclear waste site marker. The NUCLEAR competition asks participants to design a marker to designate the site of the Waste Isolation Pilot Plant (WIPP) located near Carlsbad, New Mexico. The marker will be meant to be a means of passive institutional controls (PICs) to deter inadvertent human intrusion upon the site and should last 10,000 years. The NUCLEAR competition defined the purpose of the nuclear waste site marker as a means to communicate the danger of inadvertent intrusion from future generations. The competition requires that entries must be both legible in communication and durable in their construction. The competition brief challenged participants to consider how customs and languages will evolve over time and to predict what motivations future generations might have for digging at the site. Other background information was provided about the site such as how waste was stored and how the unique geology of the site seals the waste. The 1993 Sandia National Laboratories report titled Expert Judgment on Markers to Deter Inadvertent Human Intrusion into the Waste Isolation Pilot Plant [1] was referenced along with the 1992 WIPP Land Withdrawal Act [2], interviews with WIPP scientists [3] involved with the WIPP PICs program and the Nuclear Energy Agency Records Knowledge and Memory working group. Competition participants were given digital 3-D Computer-Aided Design models for reference that included the underground storage portion of the site, existing buildings and the 16-square-mile site boundary identified in the 1992 WIPP Land Withdrawal Act [2]. This paper will: - Provide a detailed description of the submitted proposals including graphic analysis of the visualizations, diagrams, technical drawings, jury comments and statements. - Catalogue and identify the consistent themes within all submissions with possible categories including: 1) overall architectural form and language, 2) integration of written language and symbols within architecture, 3) use of technology and robotics, 4) construction methods and materials. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

The OECD-NEA RK and M Initiative (2011-2018) - a 7-year step in a 10,000-year journey: What next? - 19432

The OECD Nuclear Energy Agency (NEA) has coordinated an international initiative to develop understanding and guidelines related to the long-term preservation of records, knowledge and memory (RK and M) for radioactive waste repositories. After seven years of work, it has come to a close in 2018. Currently, the 'Final Report of the RK and M Initiative' is in the final process of publication [the status/sentence will be updated in early 2019]. It includes a historical review, sets out the RK and M fundamentals, presents a menu of approaches and mechanisms of RK and M preservation, and finally provides suggestions on how to develop a systemic strategy aimed at embedding radioactive waste repositories in society over extended periods of time. This paper highlights the 'multi-dimensionality' of RK and M preservation: Multiple time frames need to be considered, multiple transmission modes explored, and multiple actors brought together. The latter seems to be the primary aspect to be considered in the discussion about future (international) cooperation in the RK and M preservation field. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Long-Term Surveillance and Maintenance Records: Maintaining Access to the Knowledge - 13122

The U.S. Department of Energy (DOE) Office of Legacy Management (LM) is an integral part of DOE's strategy to ensure that legacy liabilities of former nuclear weapons production sites are properly managed following the completion of environmental cleanup activities. In the area of environmental legacy management, records management is crucial to the protection of health, environmental, and legal interests of the Department and the public. LM is responsible for maintaining long-term surveillance and maintenance (LTS and M) records in performance of its mission. Maintaining access to the knowledge contained in these record collections is one of LM's primary responsibilities. To fulfill this responsibility, LM established a consolidated records management facility, the LM Business Center (LMBC), to house physical media records and electronic records. A new electronic record keeping system (ERKS) was needed to replace an obsolete system while helping to ensure LM is able to meet ongoing responsibilities to maintain access to knowledge and control the life cycle management of records. (authors)

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗
NASA NTRSDate not supplied

Model-Specific Metadata for Enhancing Space Science Models

The Space Weather and Heliophysics modeling community, supported by the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov), provides a collaborative platform for space weather models and data. Flexible metadata is vital for advancing scientific research and fostering collaboration. Our work in expressing complex simulations of the Space Weather Modeling Framework (SWMF), particularly Global Magnetosphere (GM) grid components, in terms of simple metadata records shows great promise in creating searchable and reusable units of knowledge. Such records can be readily utilized to support the process of scientific discovery, closely aligning with the goals outlined in the Open Science initiative. Our primary goal is to show the scalability and benefits of metadata-focused methodologies. This presentation highlights the potential for applying metadata methodologies to other complex models, improving usability, supplying efficient documentation and fostering interdisciplinary research.

space weather↗
NASA NTRS1993

Neural network applications

A design procedure is suggested for neural networks which accommodates the inclusion of such knowledge-based systems techniques as fuzzy logic and pairwise comparisons. The use of these procedures in the design of applications combines qualitative and quantitative factors with empirical data to yield a model with justifiable design and parameter selection procedures. The procedure is especially relevant to areas of back-propagation neural network design which are highly responsive to the use of precisely recorded expert knowledge.

Padgett, Mary L.↗
NASA NTRS1996

Knowledge Engineering for Preservation and Future use of Institutional Knowledge

This Project has two main thrusts-preservation of special knowledge and its useful representation via computers. NASA is losing the expertise of its engineers and scientists who put together the great missions of the past. We no longer are landing men on the moon. Some of the equipment still used today (such as the RL-10 rocket) was designed decades ago by people who are now retiring. Furthermore, there has been a lack, in some areas of technology, of new projects that overlap with the old and that would have provided opportunities for monitoring by senior engineers of the young ones. We are studying this problem and trying out a couple of methods of soliciting and recording rare knowledge from experts. One method is that of Concept Maps which produces a graphical interface to knowledge even as it helps solicit that knowledge. We arranged for experienced help in this method from John Coffey of the Institute of Human and Machine Technology at the University of West Florida. A second method which we plan to try out in May, is a video-taped review of selected failed missions (e.g., the craft tumbled and blew up). Five senior engineers (most already retired from NASA) will, as a team, analyze available data, illustrating their thought processes as they try to solve the problem of why a space craft failed to complete its mission. The session will be captured in high quality audio and with at least two video cameras. The video can later be used to plan future concept mapping interviews and, in edited form, be a product in itself. Our computer representations of the amassed knowledge may eventually, via the methods of expert systems, be joined with other software being prepared as a suite of tools to aid future engineers designing rocket engines. In addition to representation by multimedia concept maps, we plan to consider linking vast bodies of text (and other media) by hypertexting methods.

Moreman, Douglas↗
DOE OSTI2014

Determination of elastic properties of a MnO{sub 2} coating by surface acoustic wave velocity dispersion analysis

MnO{sub 2} is a material of interest in the development of high energy-density batteries, specifically as a coating material for internal 3D structures, thus ensuring rapid energy deployment. Its electrochemical properties have been mapped extensively, but there are, to the best of the authors' knowledge, no records of the elastic properties of thin film MnO{sub 2}. Impulsive stimulated thermal scattering (ISTS), also known as the heterodyne diffraction or transient grating technique, was used to determine the Young's modulus (E) and porosity (ψ) of a 500 nm thick MnO{sub 2} coating on a Si(001) substrate. ISTS is an all optical method that is able to excite and detect surface acoustic waves (SAWs) on opaque samples. From the measured SAW velocity dispersion, the Young's modulus and porosity were determined to be E = 25 ± 1 GPa and ψ=42±1%, respectively. These values were confirmed by independent techniques and determined by a most-squares analysis of the carefully fitted SAW velocity dispersion. This study demonstrates the ability of the presented technique to determine the elastic parameters of a thin, porous film on an anisotropic substrate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1989

Artificial Intelligence Controls Tape-Recording Sequence

Developmental expert-system computer program intended to schedule recording of large amounts of data on limited amount of magnetic tape. Schedules recording using two sets of rules. First set incorporates knowledge of locations for recording of new data. Second set incorporates knowledge about issuing commands to recorder. Designed primarily for use on Voyager Spacecraft, also applicable to planning and sequencing in industry.

Schwuttke, Ursula M.↗
DOE OSTI2011

Office of Nuclear Energy Knowledge Management Program Situational Analysis Report

Knowledge management (KM) has been a high priority for the Department of Energy (DOE) Office of Nuclear Energy (NE) for the past several years. NE Programs are moving toward well-established knowledge management practices and a formal knowledge management program has been established. Knowledge management is being practiced to some level within each of the NE programs. Although it continues to evolve as NE programs evolve, a formal strategic plan that guides the implementation of KM has been developed. Despite the acceptance of KM within DOE NE, more work is necessary before the NE KM program can be considered fully successful. Per Dr. David J. Skyrme[1], an organization typically moves through the following evolutionary phases: (1) Ad-hoc - KM is being practiced to some level in some parts of the organization; (2) Formal - KM is established as a formal project or program; (3) Expanding - the use of KM as a discipline grows in practice across different parts of the organization; (4) Cohesive - there is a degree of coordination of KM; (5) Integrated - there are formal standards and approaches that give every individual access to most organizational knowledge through common interfaces; and (6) Embedded - KM is part-and-parcel of everyday tasks; it blends seamlessly into the background. According to the evolutionary phases, the NE KM program is operating at the two lower levels, Ad-hoc and Formal. Although KM is being practiced to some level, it is not being practiced in a consistent manner across the NE programs. To be fully successful, more emphasis must be placed on establishing KM standards and processes for collecting, organizing, sharing and accessing NE knowledge. Existing knowledge needs to be prioritized and gathered on a routine basis, its existence formally recorded in a knowledge inventory. Governance to ensure the quality of the knowledge being used must also be considered. For easy retrieval, knowledge must be organized according to a taxonomy that mimics nuclear energy programs. Technologies need to be established to make accessing the knowledge easier for the user. Finally, knowledge needs to be used as part of a well defined work process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

River Deltas and Sea-Level Rise

Future sea-level rise poses an existential threat for many river deltas, yet quantifying the effect of sea-level changes on these coastal landforms remains a challenge. Sea-level changes have been slow compared to other coastal processes during the instrumental record, such that our knowledge comes primarily from models, experiments, and the geologic record. Here we review the current state of science on river delta response to sea-level change, including models and observations from the Holocene until 2300 CE. We report on improvements in the detection and modeling of past and future regional sea-level change, including a better understanding of the underlying processes and sources of uncertainty. We also see significant improvements in morphodynamic delta models. Still, substantial uncertainties remain, notably on present and future subsidence rates in and near deltas. Observations of delta submergence and land loss due to modern sea-level rise also remain elusive, posing major challenges to model validation. There are large differences in the initiation time and subsequent delta progradation during the Holocene, likely from different sea-level and sediment supply histories. Modern deltas are larger and will face faster sea-level rise than during their Holocene growth, making them susceptible to forced transgression. Regional sea-level projections have been much improved in the past decade and now also isolate dominant sources of uncertainty, such as the Antarctic ice sheet. Vertical land motion in deltas can be the dominant source of relative sea-level change and the dominant source of uncertainty; limited observations complicate projections. River deltas globally might lose 5% (~35,000 km 2 ) of their surface area by 2100 and 50% by 2300 due to relative sea-level rise under a high-emission scenario.

58 GEOSCIENCES↗
NASA NTRS2002

NASA Materials Related Lessons Learned

Lessons Learned have been the basis for our accomplishments throughout the ages. They have been passed down from father to son, mother to daughter, teacher to pupil, and older to younger worker. Lessons Learned have also been the basis for the nation's accomplishments for more than 200 years. Both government and industry have long recognized the need to systematically document and utilize the knowledge gained from past experiences in order to avoid the repetition of failures and mishaps. Through the knowledge captured and recorded in Lessons Learned from more than 80 years of flight in the Earth's atmosphere, NASA's materials researchers are constantly working to develop stronger, lighter, and more durable materials that can withstand the challenges of space. The Agency's talented materials engineers and scientists continue to build on that rich tradition by using the knowledge and wisdom gained from past experiences to create futurist materials and technologies that will be used in the next generation of advanced spacecraft and satellites that may one day enable mankind to land men on another planet or explore our nearest star. These same materials may also have application here on Earth to make commercial aircraft more economical to build and fly. With the explosion in technical accomplishments over the last decade, the ability to capture knowledge and have the capability to rapidly communicate this knowledge at lightning speed throughout an organization like NASA has become critical. Use of Lessons Learned is a principal component of an organizational culture committed to continuous improvement.

Garcia, Danny↗
NASA NTRS2003

NASA Materials Related Lessons Learned

Lessons Learned have been the basis for our accomplishments throughout the ages. They have been passed down from father to son, mother to daughter, teacher to pupil, and older to younger worker. Lessons Learned have also been the basis for the nation s accomplishments for more than 200 years. Both government and industry have long recognized the need to systematically document and utilize the knowledge gained from past experiences in order to avoid the repetition of failures and mishaps. Through the knowledge captured and recorded in Lessons Learned from more than 80 years of flight in the Earth s atmosphere, NASA s materials researchers are constantly working to develop stronger, lighter, and more durable materials that can withstand the challenges of space. The Agency s talented materials engineers and scientists continue to build on that rich tradition by using the knowledge and wisdom gained from past experiences to create futuristic materials and technologies that will be used in the next generation of advanced spacecraft and satellites that may one day enable mankind to land men on another planet or explore our nearest star. These same materials may also have application here on Earth to make commercial aircraft more economical to build and fly. With the explosion in technical accomplishments over the last decade, the ability to capture knowledge and have the capability to rapidly communicate this knowledge at lightning speed throughout an organization like NASA has become critical. Use of Lessons Learned is a principal component of an organizational culture committed to continuous improvement.

Garcia, Danny↗
DOE OSTI2018

3D-Printed, Superelastic Polypyrrole–Graphene Electrodes with Ultrahigh Areal Capacitance for Electrochemical Energy Storage

Disruptive custom electronics require a transformation in energy storage systems from traditional thin-film units to shape conformable 3D components. However, current thick electrodes suffer from uncontrollable geometries and architectures, which lead to ion diffusion limitations, and poor mechanical properties. Here, designed, superelastic polypyrrole (PPy)-coated graphene aerogel (GA) electrodes are fabricated via 3D printing and polymer self-assembly methods. This resilient GA template (up to 90% compression) can be printed into any desired shape including engineered 3D architectures with periodic macropores, which promote the uniform deposition and adhesion of PPy onto the support. Additionally, the coated PPy thin film increases the specific gravimetric capacitance of the GA electrode from 14 to 395 F g -1 with 90% retention after 5000 charging–discharging cycles. The capacitance remains the same value after 100 times compression cycles. It also improves the compressive strength by one order of magnitude from 0.14 to 2.4 MPa. Areal capacitance and energy density of the PPy–GA electrode are 2 F cm -2 and 0.78 mWh cm -2 , respectively, which to the best of the knowledge break the record for compressible electrodes, respectively. This approach enables the fabrication of complex architectured energy storage modules with enhanced compressibility, ultrahigh areal electrochemical performance, and excellent cyclability.

25 ENERGY STORAGE↗
DOE OSTI2024

Mixed Self-Assembled Monolayers for High-Photovoltage Tin Perovskite Solar Cells

Self-assembled monolayers (SAMs) are used as potent hole transport layers (HTLs) in lead-based perovskite solar cells, enabling large quasi-Fermi level splitting for high photovoltage (>1.1 V) with a deficit of <0.5 V. However, tin-based perovskite solar cells (TPSCs) with SAM HTLs suffer from low photovoltage (<0.65 V) with a deficit of >0.7 V. Herein we employ a holistic approach to tackle this significant challenge by designing a mixed SAM, engineering a compatible tin perovskite thin film, and leveraging an efficient electron transport layer. Consequently, high photovoltage of 0.829 V is achieved with an efficiency of 9.4%, which is a record to our knowledge among TPSCs using SAMs as sole HTLs. Finally, while SAMs have been little used in TPSCs thus far, our holistic approach should catalyze their future advancements toward outperformance.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Situational Awareness in Distribution Grid Using Micro-PMU Data: A Machine Learning Approach

The recent development of distribution-level phasor measurement units, a.k.a. micro-PMUs, has been an important step towards achieving situational awareness in power distribution networks. The challenge however is to transform the large amount of data that is generated by micro-PMUs to actionable information and then match the information to use cases with practical value to system operators. This open problem is addressed in this paper. First, we introduce a novel data-driven event detection technique to pick out valuable portion of data from extremely large raw micro-PMU data. Subsequently, a datadriven event classifier is developed to effectively classify power quality events. Importantly, we use field expert knowledge and utility records to conduct an extensive data-driven event labeling. Moreover, certain aspects from event detection analysis are adopted as additional features to be fed into the classifier model. In this regard, a multi-class support vector machine (multi-SVM) classifier is trained and tested over 15 days of real-world data from two micro-PMUs on a distribution feeder in Riverside, CA. In total, we analyze 1.2 billion measurement points, and 10,700 events. Here, the effectiveness of the developed event classifier is compared with prevalent multi-class classification methods, including k-nearest neighbor method as well as decision-tree method. Importantly, two real-world use-cases are presented for the proposed data analytics tools, including remote asset monitoring and distribution-level oscillation analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Reweighting simulated events using machine-learning techniques in the CMS experiment

Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a GEANT -based simulation of the detectors are used to produce large samples of simulated events for analysis by the LHC experiments. These simulations come at a high computational cost, where the detector simulation and reconstruction algorithms have the largest CPU demands. This article describes how machine-learning (ML) techniques are used to reweight simulated samples obtained with a given set of parameters to samples with different parameters or samples obtained from entirely different simulation programs. The ML reweighting method avoids the need for simulating the detector response multiple times by incorporating the relevant information in a single sample through event weights. Results are presented for reweighting to model variations and higher-order calculations in simulated top quark pair production at the LHC. This ML-based reweighting is an important element of the future computing model of the CMS experiment and will facilitate precision measurements at the High-Luminosity LHC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗