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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Machine Learning for Turbulence Modeling

This work was conducted as part of a Harry S. Truman Fellowship Laboratory Directed Research and Development project. The goal was to use machine learning methods to provide uncertainty quantification and model improvements for Reynolds Averaged Navier Stokes (RANS) turbulence models. For applications of interest in energy, safety, and security, it is critical to be able to model turbulence accurately. Current RANS models are unreliable for many flows of engineering relevance. Machine learning provides an avenue for developing improved models based on the data generated by high fidelity simulations. In this project, machine learning methods were used to predict when current RANS models would fail. They were also used to develop improved RANS closure models. A key aim was developing a tight feedback loop between scientific domain knowledge and data driven methods. To this end, a methodology for incorporating known invariance constraints into the machine learning models was proposed and evaluated. This work demonstrated that incorporating known constraints into the data driven models provided improved performance and reduced computational cost. This research represents one of the first applications of deep learning to turbulence modeling.

42 ENGINEERING↗
DOE OSTI2016

Knowledge management: Role of the the Radiation Safety Information Computational Center (RSICC)

The Radiation Safety Information Computational Center (RSICC) at Oak Ridge National Laboratory (ORNL) is an information analysis center that collects, archives, evaluates, synthesizes and distributes information, data and codes that are used in various nuclear technology applications. RSICC retains more than 2,000 software packages that have been provided by code developers from various federal and international agencies. RSICC’s customers (scientists, engineers, and students from around the world) obtain access to such computing codes (source and/or executable versions) and processed nuclear data files to promote on-going research, to ensure nuclear and radiological safety, and to advance nuclear technology. The role of such information analysis centers is critical for supporting and sustaining nuclear education and training programs both domestically and internationally, as the majority of RSICC’s customers are students attending U.S. universities. Additionally, RSICC operates a secure CLOUD computing system to provide access to sensitive export-controlled modeling and simulation (M&S) tools that support both domestic and international activities. This presentation will provide a general review of RSICC’s activities, services, and systems that support knowledge management and education and training in the nuclear field.

Valentine, Timothy↗
DOE OSTI2018

UNC-5 netrin receptor B mediates osteogenic differentiation by modulating bone morphogenetic protein signaling in human adipose-derived stem cells

Highlights: • UNC5B facilitates osteogenic differentiation of human adipose-derived stem cells. • It does so by modulation bone morphogenetic protein signaling. • UNC5B may be useful for bone tissue engineering and therapy for bone defects. UNC-5 netrin receptor B (UNC5B) is a dependence receptor of netrin-1 that plays an essential role in mediating angiogenesis and tumorigenesis. Despite its significant roles, there is limited knowledge about the role played by UNC5B in osteogenesis. In the present study, we first demonstrated that UNC5B was required for osteogenic differentiation of human adipose-derived stem cells (hASCs), both in vitro and in vivo. We also found that mechanistically, UNC5B promotes osteogenic differentiation by activating bone morphogenetic protein signaling. These findings point to a new important function of UNC5B and provide a potential basis for hASCs-mediated bone regeneration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Giant energy storage and power density negative capacitance superlattices

Dielectric electrostatic capacitors, because of their ultrafast charge-discharge, are desirable for high-power energy storage applications. Along with ultrafast operation, on-chip integration can enable miniaturized energy storage devices for emerging autonomous microelectronics and microsystems. Moreover, state-of-the-art miniaturized electrochemical energy storage systems-microsupercapacitors and microbatteries-currently face safety, packaging, materials and microfabrication challenges preventing on-chip technological readiness, leaving an opportunity for electrostatic microcapacitors. Here, in this study, we report record-high electrostatic energy storage density (ESD) and power density, to our knowledge, in HfO 2 -ZrO 2 -based thin film microcapacitors integrated into silicon, through a three-pronged approach. First, to increase intrinsic energy storage, atomic-layer-deposited antiferroelectric HfO 2 -ZrO 2 films are engineered near a field-driven ferroelectric phase transition to exhibit amplified charge storage by the negative capacitance effect, which enhances volumetric ESD beyond the best-known back-end-of-the-line-compatible dielectrics (115 J cm -3 ). Second, to increase total energy storage, antiferroelectric superlattice engineering scales the energy storage performance beyond the conventional thickness limitations of HfO 2 -ZrO 2 -based (anti)ferroelectricity (100-nm regime). Third, to increase the storage per footprint, the superlattices are conformally integrated into three-dimensional capacitors, which boosts the areal ESD nine times and the areal power density 170 times that of the best-known electrostatic capacitors: 80 mJ cm -2 and 300 kW cm -2 , respectively. This simultaneous demonstration of ultrahigh energy density and power density overcomes the traditional capacity-speed trade-off across the electrostatic-electrochemical energy storage hierarchy. Furthermore, the integration of ultrahigh-density and ultrafast-charging thin films within a back-end-of-the-line-compatible process enables monolithic integration of on-chip microcapacitors, which can unlock substantial energy storage and power delivery performance for electronic microsystems.

25 ENERGY STORAGE↗
DOE OSTI2022

Forward-Looking State-of-the-Art Review on Earned Value Management Systems: The Disconnect between Academia and Industry

Earned value management (EVM) is a project management approach that can enhance the probability of project success. It is applied widely across different industry sectors (e.g., energy, aerospace, construction, defense, and manufacturing), generally through the use of an earned value management system (EVMS). A holistic and up-to-date literature review on EVM and EVMS does not exist. A literature review can provide a comprehensive perspective on the topic, identifying and summarizing the existing body of knowledge, as a foundation to advance the state of practice of EVM/EVMS. Therefore, the objective of this paper is to investigate the EVM/EVMS state of the art by critically reviewing academic and industry publications, with a specific focus on the maturity of EVMS and the environment surrounding its implementation. By performing a systematic literature review, the authors identified 600 publications since the inception of the EVM concept in 1962, and then narrowed down this list to 160 relevant publications from the last decade for closer review. The findings include the discovery of eight emergent themes. Of these themes, “forecasting/prediction” constitutes the largest portion of the recent literature, followed by “application of EVMS.” One interesting finding is that EVMS maturity, although being a critical topic, is only discussed in one publication. Publications focused on EVM/EVMS have increased in the last decade and significant differences were found between academia and industry literature in terms of the limitations and extensions of EVM/EVMS, EVMS environment, and compliance. A key finding is that designing a reliable EVMS should combine both technical and social aspects of implementation. This forward-looking paper provides a state-of-the-art review while highlighting gaps in the existing EVM/EVMS body of knowledge and introducing new perspectives to support EVMS research and application.

42 ENGINEERING↗
DOE OSTI2020

Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences

Data science has primarily focused on big data, but for many physics, chemistry, and engineering applications, data are often small, correlated and, thus, low dimensional, and sourced from both computations and experiments with various levels of noise. Typical statistics and machine learning methods do not work for these cases. Expert knowledge is essential, but a systematic framework for incorporating it into physics-based models under uncertainty is lacking. Here, we develop a mathematical and computational framework for probabilistic artificial intelligence (AI)–based predictive modeling combining data, expert knowledge, multiscale models, and information theory through uncertainty quantification and probabilistic graphical models (PGMs). We apply PGMs to chemistry specifically and develop predictive guarantees for PGMs generally. Our proposed framework, combining AI and uncertainty quantification, provides explainable results leading to correctable and, eventually, trustworthy models. The proposed framework is demonstrated on a microkinetic model of the oxygen reduction reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Bulk Electrical Cable Non-Destructive Examination Methods for Nuclear Power Plant Cable Aging Management Programs

This Pacific Northwest National Laboratory milestone report describes progress to date on the investigation of nondestructive test methods focusing particularly on bulk electrical test methods that provide key indicators of cable aging and damage. The work includes a review of relevant literature as well as hands-on experimental verification of inspection capabilities. As nuclear power plants consider applying for second, or subsequent, license renewal to extend their operating period from 60 years to 80 years, it is important to understand how the materials installed in plant systems and components will age during that time and develop aging management programs to assure continued safe operation under normal and design basis events (DBE). Normal component and system tests typically confirm the cables can perform their normal operational function. The focus of the cable test program, however, is directed toward the more demanding challenge of assuring the cable function under accident or DBE. The industry has adopted 50% elongation at break (EAB) relative to the un-aged cable condition as the acceptability standard. All tests are benchmarked against the cable EAB test. EAB, however, is a destructive test so the test programs must apply an array of other nondestructive examination (NDE) tests to assure or infer the overall set of cable’s system integrity. Assessment of cable integrity is further complicated in many cases by vendor’s use of dissimilar material for jacket and insulation. Frequently the jacket will degrade more rapidly than the underlying insulation. Although this can serve as an early alert to cable damage, direct test of the cable insulation without violating the protective jacket becomes problematic. This report addresses the range of bulk electrical NDE cable tests that are or could be practically implemented in a field-test situation with a particular focus on frequency domain reflectometry (FDR). The FDR test method offers numerous advantages over many other bulk electrical tests. Two commercial FDR systems plus a laboratory vector network analyzer are used to test an array of aged and un-aged cables under identical conditions. Several conclusions are set forth, and a number of knowledge gaps are identified.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

NLC ZDR: Zero Order Design Report for the NEXT Linear Collider (Volume 1)

This “Zeroth-Order Design Report” (ZDR) for the Next Linear Collider (NLC) is being created at a time of both great opportunity and uncertainty in the future directions that will be taken by the world-wide community of high-energy physics. There is exciting news that the Large Hadron Collider project has been approved for construction at CERN, and the planned involvement by physicists and engineers from countries around the globe will make this the first accelerator to be designed and built by a truly world-wide collaboration. By contrast, the cancellation of the SSC has demonstrated the necessity of international collaboration on such large scientific projects. The community of scientists and engineers at work on the accelerator physics and technologies of high-energy electron-positron colliders has recognized this need, and has made concerted effort to coordinate research activities to optimize our combined understanding and knowledge. This ZDR is one further step in this process.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

NLC ZDR: Zero Order Design Report for the NEXT Linear Collider (Volume 2)

This “Zeroth-Order Design Report” (ZDR) for the Next Linear Collider (NLC) is being created at a time of both great opportunity and uncertainty in the future directions that will be taken by the world-wide community of high- energy physics. There is exciting news that the Large Hadron Collider project has been approved for construction at CERN, and the planned involvement by physicists and engineers from countries around the globe will make this the first accelerator to be designed and built by a truly world-wide collaboration. By contrast, the cancellation of the SSC has demonstrated the necessity of international collaboration on such large scientific projects. The community of scientists and engineers at work on the accelerator physics and technologies of high-energy electron-positron colliders has recognized this need, and has made concerted effort to coordinate research activities to optimize our combined understanding and knowledge. This ZDR is one further step in this process.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Justice Underpinning Science and Technology Research (JUST-R) Offline Tool: A Tool for Guiding Researchers in Addressing Energy Justice Considerations in Early-Stage Research

The Justice Underpinning Science and Technology Research (JUST-R) Metrics Framework is a set of metrics for assessing the energy justice implications of technologies that are currently under research and development (R&D). The JUST-R Metrics Framework guides researchers through an analysis of the many facets of their research processes, from material inputs to knowledge sources, that may contribute to energy injustice both during the research period and when the technology is scaled. This JUST-R Offline Tool consists of an Excel file and PDF guide to aid researchers, engineers, and project managers in their application of the JUST-R Metrics Framework. This tool enables researchers to 1) evaluate the baseline energy justice implications of their research; 2) develop justice-oriented changes to the research process; and 3) track the implementation of proposed changes. The metrics included in the framework are sorted into five aspects of research: Team Dynamics, Sources & Inputs, Processes & Protocols, Waste & Hazards, and Results & Dissemination. The JUST-R Tool can be found here: https://www.nrel.gov/analysis/just-r.html.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Development of a High Throughput Platform for Screening Glycoside Hydrolases Based on Oxime-NIMS

Cost-effective hydrolysis of biomass into sugars for biofuel production requires high-performance low-cost glycoside hydrolase (GH) cocktails that are active under demanding process conditions. Improving the performance of GH cocktails depends on knowledge of many critical parameters, including individual enzyme stabilities, optimal reaction conditions, kinetics, and specificity of reaction. With this information, rate- and/or yield-limiting reactions can be potentially improved through substitution, synergistic complementation, or protein engineering. Given the wide range of substrates and methods used for GH characterization, it is difficult to compare results across a myriad of approaches to identify high performance and synergistic combinations of enzymes. Here, we describe a platform for systematic screening of GH activities using automatic biomass handling, bioconjugate chemistry, robotic liquid handling, and nanostructure-initiator mass spectrometry (NIMS). Twelve well-characterized substrates spanning the types of glycosidic linkages found in plant cell walls are included in the experimental workflow. To test the application of this platform and substrate panel, we studied the reactivity of three engineered cellulases and their synergy of combination across a range of reaction conditions and enzyme concentrations. We anticipate that large-scale screening using the standardized platform and substrates will generate critical datasets to enable direct comparison of enzyme activities for cocktail design.

09 BIOMASS FUELS↗
DOE OSTI2020

On the Convergence of Physics Informed Neural Networks for Linear Second-Order Elliptic and Parabolic Type PDEs

Physics informed neural networks (PINNs) are deep learning based techniques for solving partial differential equations (PDEs) encountered in computational science and engineering. Guided by data and physical laws, PINNs find a neural network that approximates the solution to a system of PDEs. Such a neural network is obtained by minimizing a loss function in which any prior knowledge of PDEs and data are encoded. Despite its remarkable empirical success in one, two or three dimensional problems, there is little theoretical justification for PINNs. As the number of data grows, PINNs generate a sequence of minimizers which correspond to a sequence of neural networks. We want to answer the question: Does the sequence of minimizers converge to the solution to the PDE? We consider two classes of PDEs: linear second-order elliptic and parabolic. By adapting the Schauder approach and the maximum principle, we show that the sequence of minimizers strongly converges to the PDE solution in C 0 . Furthermore, we show that if each minimizer satisfies the initial/boundary conditions, the convergence mode becomes H 1 . Computational examples are provided to illustrate our theoretical findings. To the best of our knowledge, this is the first theoretical work that shows the consistency of PINNs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Department of Energy/IDEA: More best-practices research

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.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Addressing Human and Organizational Factors in Nuclear Industry Modernization: A Sociotechnically Based Strategic Framework

The modernization of nuclear power plants will require an advanced concept of operations, involving an integrated set of tightly coupled systems in which all stakeholders act in a coordinated manner. For this modernization effort to be enabled, we developed a human and organizational factors approach based on a broad sociotechnical framework. Starting from core human factors principles, we conducted a literature review of the methods and approaches relevant to the modernization problem. These included not only core disciplines such as cognitive systems engineering, systems theoretic accident modeling and processes, human systems integration, resilience engineering, and macroergonomics but also related topics of safety culture and organizational change. From this literature, we developed a conceptual framework centered around the work system with its four interacting components: people, technology, process, and governance. In an effective work system, these four components are jointly optimized according to three systems criteria: efficiency, effectiveness, and safety. System failure may result from excessive emphasis on any one criterion. The actual work of attaining joint optimization in a given work system can be accomplished by utilizing three high-level functions: knowledge elicitation, knowledge representation, and cross-functional integration. Finally, we illustrated the utility of this approach by applying it to practical problems and case studies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Governance and Resilience: A Holistic Approach to Systems Security in Complex and Chaotic Environments

Here, a systems governance approach emphasizes a holistic perspective that identifies and navigates the interdependencies and conflicts between security and operational needs. Governance is defined as a collection of metasystems that provide the necessary constraints and processes to support, steer, adapt, transform, and sustain a system (Keating et al. 2022). Utilizing the Cynefin framework, which distinguishes between simple, complicated, complex, and chaotic environments (Snowden and Boone 2007), the article highlights the challenges faced by nuclear power plants in predatory contexts and the importance of integrating security objectives into governance frameworks. By incorporating security as a fundamental aspect of governance, the article underscores its significance for persistence, adaptation, and transformation in the face of uncertainty. Additionally, it introduces key heuristics of systems security, such as the importance of context, knowledge‐based decision‐making, and organization‐specific sociological factors (Williams and Caskey 2024). Ultimately, this work provides valuable insights into enhancing resilient operations in complex environments by reinforcing the connection between effective governance and security in systems engineering.

Caskey, Susan A. [Sandia National Laboratories (SN↗
DOE OSTI2017

Aeration costs in stirred-tank and bubble column bioreactors

To overcome knowledge gaps in the economics of large-scale aeration for production of commodity products, Aspen Plus is used to simulate steady-state oxygen delivery in both stirred-tank and bubble column bioreactors, using published engineering correlations for oxygen mass transfer as a function of aeration rate and power input, coupled with new equipment cost estimates developed in Aspen Capital Cost Estimator and validated against vendor quotations. Here, these simulations describe the cost efficiency of oxygen delivery as a function of oxygen uptake rate and vessel size, and show that capital and operating costs for oxygen delivery drop considerably moving from standard-size (200 m 3 ) to world-class size (500 m 3 ) reactors, but only marginally in further scaling up to hypothetically large (1000 m 3 ) reactors. Finally, this analysis suggests bubble-column reactor systems can reduce overall costs for oxygen delivery by 10-20% relative to stirred tanks at low to moderate oxygen transfer rates up to 150 mmol/L-h.

09 BIOMASS FUELS↗
DOE OSTI2018

Fuel Testing for Sylvatex: Cooperative Research and Development Final Report, CRADA Number CRD-16-636

Sylvatex is a green nano-chemistry company that has developed a platform technology utilizing renewable, non-toxic inputs to create a stable nanoparticle that can be used in multiple applications. Their mission is to increase the use of renewables globally, to empower a cleaner and healthier future. The main application is a fuel technology product - MicroX - that utilizes proprietary knowledge to scale low-cost, cleaner-burning renewable diesel fuel and additives by using a co-location commercial model. The aspects of this project will include testing of two Sylvatex MicroX fuels on an engine dynamometer platform. Industry standard ultra-low sulfur diesel (ULSD) B3 fuel and a ULSD B20 will both be used for comparison of the Sylvatex fuels (U.S. standard diesel fuel at the pump contains an average of approximately 3% biodiesel; this is why B3 would be used as a baseline comparison). Sylvatex is currently using a prototype formulation (MicroX 1) that applies a high cost surfactant. An experimental formulation (MicroX 2) that uses lower cost materials is under development. The MicroX 1 will be blended at a 10% level into the B3 ULSD fuel and the MicroX 2 will be blended at a 10% level into both the B3 and the B20 ULSD fuels for study on the engine dynamometer test platform. All fuel blends will be tested over the FTP transient engine test cycle and a steady state ramped modal engine test cycle. Each test cycle will be performed a minimum of 3 times for each fuel. Tailpipe and/or engine out gaseous exhaust emissions (CO2, CO, NOx, THC, O2,), engine out PM emissions, and brake-specific fuel consumption rates will be evaluated for all test cycles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

FY21 Report on Activities for EBS International

This report summarizes the FY21 Activities for EBS International Collaborations Work Package. The international collaborations work packages aim to leverage knowledge, expertise, and tools from the international nuclear waste community, as deemed relevant according to SFWST “roadmap” priorities. This report describes research and development (R&D) activities conducted during fiscal year 2021(FY21) specifically related to the Engineered Barrier System (EBS) R&D Work Package in the Spent Fuel and Waste Science and Technology (SFWST) Campaign supported by the United States (U.S.) Department of Energy (DOE). It fulfills the SFWST Campaign deliverable M4SF- 21SN010308062. The R&D activities described in this report focus on understanding EBS component evolution and interactions within the EBS, as well as interactions between the host media and the EBS. A primary goal is to advance the development of process models that can be implemented directly within the Generic Disposal System Analysis (GDSA) platform or that can contribute to the safety case in some manner such as building confidence, providing further insight into the processes being modeled, establishing better constraints on barrier performance, etc. Sandia National Laboratories is participating in THM modeling in the international projects EBS Task Force and DECOVALEX 2023. EBS Task Force, Task 11 is on modeling of laboratory-scale High Temperature Column Test conducted at Lawrence Berkeley National Laboratory. DECOVALEX 2023, Task C is on THM modeling of the full-scale emplacement experiment (FE experiment) at the Mont Terri Underground Rock Laboratory, Switzerland. This report summarizes Sandia’s progress in the modeling studies of DECOVALEX 2023, Task C. Modeling studies related to the High Temperature Column Test will be documented in future reports.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗