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DOE OSTI2025

Simulating regional workforce impacts of decarbonizing integrated steelmaking

Global efforts to mitigate climate change are increasing pressure on heavy manufacturing industries to decarbonize production. The iron and steel industry is responsible for 7% of CO 2 emissions globally (2% in the United States) and is often a major employer in the regions where iron and steel is produced. Understanding the future prospects for workers in regions with high CO 2 emitting industries—including impacts of phasing out or evolving such industries—will be critical for informing regional economic and clean energy strategies. We simulate the impact of an “in-place” transition that replaces today’s integrated production with direct reduced iron (DRI) used in electric arc furnaces (EAFs), using Southwest Pennsylvania as an application of our generalizable approach. Our results suggest that the integrated steelmaking workforce today has the skills, knowledge, and abilities (SKAs) to fill over 95% of all jobs required by DRI/EAF facilities, but the number of jobs is only 25% of those at integrated plants. We also find that some occupational groups have greater general transferability into the broader job market, while other groups, such as production workers, are ill-equipped today based on current SKAs to transition out of the iron and steel industry. Our methodology further suggests factors that limit transitions: Around 85% of occupations are more limited by missing skills, while 15% are more limited by insufficient wages. These results may help to improve the design of social policy and the targeting of retraining programs, while the simulation approach can be readily adapted for other regions and industries.

decarbonization↗

DOE OSTI2022

Combustion Kinetics Model Development & Fluid Property Experimental Investigation For Improved Design Of Supercritical CO 2 Power Cycle Components

Supercritical carbon dioxide (sCO 2 ) cycles are being investigated for the future of power generation and will contribute to a carbon-neutral future to combat the effects of climate change. These direct-fired closed cycles will produce power without adding significant pollutants to the atmosphere. For such cycles to be efficient, they will need to operate at significantly higher pressures (e.g., 300 atm for Allam Cycle) than existing systems (typically less than 40 atm). There is limited knowledge on combustion at these high pressures and with a high dilution of carbon dioxide. Also, various experimental and computational investigations and model developments have been performed by the University of Central Florida (UCF), Embry-Riddle Aeronautical University (ERAU), and Stanford University (S.U.) to improve the current knowledge base and support the design and development of sCO 2 combustors. This project's technical aspects include chemical kinetics development, fundamental sCO 2 combustion, combustion model and sub-model development, supercritical fluid injection characterization, and heat transfer characterization.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS2007

The Effects of Rainfall Inhomogeneity on Climate Variability of Rainfall Estimated from Passive Microwave Sensors

Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (T(sub b)) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the oblique incidence of current radiometers. Because of the horizontal averaging that occurs away from the nadir direction, the beam-filling error is found to be only a fraction of what has been reported previously in the literature based upon plane-parallel calculations. For a FOV representative of the 19-GHz radiometer channel (18 km X 28 km) aboard the Tropical Rainfall Measuring Mission (TRMM), the mean beam-filling correction computed in this study for tropical atmospheres is 1.26 instead of 1.52 computed from plane-parallel techniques. The slant-path solution is also less sensitive to finescale rainfall inhomogeneity and is, thus, able to make use of 4-km radar data from the TRMM Precipitation Radar (PR) in order to map regional and seasonal distributions of observed rainfall inhomogeneity in the Tropics. The data are examined to assess the expected errors introduced into climate rainfall records by unresolved changes in rainfall inhomogeneity. Results show that global mean monthly errors introduced by not explicitly accounting for rainfall inhomogeneity do not exceed 0.5% if the beam-filling error is allowed to be a function of rainfall rate and freezing level and does not exceed 2% if a universal beam-filling correction is applied that depends only upon the freezing level. Monthly regional errors can be significantly larger. Over the Indian Ocean, errors as large as 8% were found if the beam-filling correction is allowed to vary with rainfall rate and freezing level while errors of 15% were found if a universal correction is used.

Kummerow, Christian↗

NASA NTRS2007

Spinoff 2007

In accordance with congressional mandates cited in the National Aeronautics and Space Act of 1958 and the Technology Utilization Act of 1962, NASA was directed to encourage greater use of the Agency's knowledge by providing a link between the NASA research community and those who might use the research for commercial or industrial products. For more than 40 years, NASA has nurtured partnerships with the private sector to facilitate the transfer of NASA-developed technologies. The benefits of these partnerships have reached throughout the economy and around the globe, as the resulting commercial products contributed to the development of services and technologies in the fields of health and medicine, transportation, public safety, consumer goods, environmental resources, computer technology, and industry. Since 1976, NASA Spinoff has profiled more than 1,500 of the most compelling of these technologies, annually highlighting the best and brightest of partnerships and innovations. Building on this dynamic history, NASA partnerships with the private sector continue to seek avenues by which technological achievements and innovations gleaned among the stars can be brought down to benefit our lives on Earth. NASA Spinoff highlights the Agency's most significant research and development activities and the successful transfer of NASA technology, showcasing the cutting-edge research being done by the Nation's top technologies and the practical benefits that come back down to Earth in the form of tangible products that make our lives better.

Source record↗

NASA NTRSDate not supplied

Language Model For Earth Science: Exploring Potential Downstream Applications As Well As Current Challenges

The use of deep learning techniques to build transformer language models such as SciBERT and GPT3 have transformed the natural language technology (NLT) landscape. These new NLTs are being used in speech to text and vice versa, auto-mated text classification, sentiment analysis, topic modeling, text summarization, and cognitive assistants. While Earth science has no shortage of unstructured data such as journal and conference papers, little efforts have focused on harnessing NLTs for knowledge extraction and supporting the scientific process. This paper surveys the use of language models in different science. BERT-E, a new Earth science-specific language model, is presented. BERT-E is generated using a transfer learning solution. A language model that has already been trained for general Science (SciBERT) is fine-tuned using abstracts and full text extracted from various Earth science-related articles. A downstream keywords classification application is used for evaluation, and the use of BERT-E shows improved performance. The need to develop a robust set of benchmarks in evaluating the language model such as BERT-E is discussed. Finally, example applications are presented to inspire additional ideas for applications using domain-specific language models.

R Ramachandran↗

DOE OSTI2016

Computational Fluid Dynamics Modeling of Bubbling in a Viscous Fluid for Validation of Waste Glass Melter Modeling

At the Hanford site, radioactive waste stored in underground tanks is slated for vitrification for final disposal. A comprehensive knowledge of the glass batch melting process will be useful in optimizing the process, which could potentially reduce the cost and duration of this multi-billion dollar cleanup effort. We are developing a high-fidelity heat transfer model of a Joule-heated ceramic lined melter to improve the understanding of the complex, inter-related processes occurring with the melter. The glass conversion rates in the cold cap layer are dependent on promoting efficient heat transfer. In practice, heat transfer is augmented by inserting air bubblers into the molten glass. However, the computational simulations must be validated to provide confidence in the solutions. As part of a larger validation procedure, it is beneficial to split the physics of the melter into smaller systems to validate individually. The substitution of molten glass for a simulant liquid with similar density and viscosity at room temperature provides a way to study mixing through bubbling as an isolated effect without considering the heat transfer dynamics. The simulation results are compared to experimental data obtained by the Vitreous State Laboratory at the Catholic University of America using bubblers placed within a large acrylic tank that is similar in scale to a pilot glass waste melter. Comparisons are made for surface area of the rising air bubbles between experiments and CFD simulations for a variety of air flow rates and bubble injection depths. Also, computed bubble rise velocity is compared to a well-accepted expression for bubble terminal velocity.

bubbling↗

DOE OSTI2016

Computational Fluid Dynamics Modeling of Bubbling in a Viscous Fluid for Validation of Waste Glass Melter Modeling

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Undercooling minimization in ultrasound coupled DTA measurements of molten salts

Molten salts are ionic liquids that are used for the electrolytic pyroprocessing of metals and as heat transfer fluids in very high temperature processes. Recently, halide-based molten salt reactors (MSR) have gained momentum for high density and environmentally responsible electricity generation. The function of these reactors and their fuel cycle depend on a knowledge of the halide salt’s thermodynamic properties [1]. Therefore, high accuracy phase equilibria of MSR relevant base halide and actinide containing salts are needed. Modern thermal analysis of the phase transitions of halide salts is usually done during heating at relatively high scan rates with commercial devices. Normally such measurements are adequate for pure or pseudo-binary salts. However, as the number of components in the mixture increases, accurately resolving the liquidus becomes increasingly difficult. Reversing the scanning mode greatly increases the sensitivity of phase transition measurements but can decrease accuracy due to undercooling [2] — a common occurrence in molten halide systems [3]. This work presents the development of a differential thermal analysis (DTA) cell intended for use in radiological gloveboxes. Non-contact ultrasonic agitation of the halide salt is implemented to limit kinetic limitations on crystallization during cooling to minimize undercooling [4]. Measurements on halide salts are also presented to elucidate the effect of non-contact mixing on undercooling. Reference [1] S. Boyd and C. Taylor, “3 - Chemical fundamentals and applications of molten salts,” in Molten Salt Reactors and Thorium Energy, T. J. Dolan, Ed., Woodhead Publishing, 2017, pp. 29–91. doi: 10.1016/B978-0-08-101126-3.00003-8. [2] K. Nitsch, A. Cihlár, and M. Rodová, “Molten state and supercooling of lead halides,” J. Cryst. Growth, vol. 264, no. 1, pp. 492–498, Mar. 2004, doi: 10.1016/j.jcrysgro.2004.01.011. [3] L. Rycerz, “Practical remarks concerning phase diagrams determination on the basis of differential scanning calorimetry measurements,” J. Therm. Anal. Calorim., vol. 113, no. 1, pp. 231–238, Jul. 2013, doi: 10.1007/s10973-013-3097-0. [4] Md. H. Zahir, S. A. Mohamed, R. Saidur, and F. A. Al-Sulaiman, “Supercooling of phase-change materials and the techniques used to mitigate the phenomenon,” Appl. Energy, vol. 240, pp. 793–817, Apr. 2019, doi: 10.1016/j.apenergy.2019.02.045.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1992

The development and technology transfer of software engineering technology at NASA. Johnson Space Center

The United State's big space projects of the next decades, such as Space Station and the Human Exploration Initiative, will need the development of many millions of lines of mission critical software. NASA-Johnson (JSC) is identifying and developing some of the Computer Aided Software Engineering (CASE) technology that NASA will need to build these future software systems. The goal is to improve the quality and the productivity of large software development projects. New trends are outlined in CASE technology and how the Software Technology Branch (STB) at JSC is endeavoring to provide some of these CASE solutions for NASA is described. Key software technology components include knowledge-based systems, software reusability, user interface technology, reengineering environments, management systems for the software development process, software cost models, repository technology, and open, integrated CASE environment frameworks. The paper presents the status and long-term expectations for CASE products. The STB's Reengineering Application Project (REAP), Advanced Software Development Workstation (ASDW) project, and software development cost model (COSTMODL) project are then discussed. Some of the general difficulties of technology transfer are introduced, and a process developed by STB for CASE technology insertion is described.

Pitman, C. L.↗

DOE OSTI2024

Mo than meets the eye: genomic insights into molybdoenzyme diversity of Seleniivibrio woodruffii strain S4T

Abstract Seleniivibrio woodruffii strain S4T is an obligate anaerobe belonging to the phylum Deferribacterota. It was isolated for its ability to respire selenate and was also found to respire arsenate. The high-quality draft genome of this bacterium is 2.9 Mbp, has a G+C content of 48%, 2762 predicted genes of which 2709 are protein-coding, and 53 RNA genes. An analysis of the genome focusing on the genes encoding for molybdenum-containing enzymes (molybdoenzymes) uncovered a remarkable number of genes encoding for members of the dimethylsulfoxide reductase family of proteins (DMSOR), including putative reductases for selenate and arsenate respiration, as well as genes for nitrogen fixation. Respiratory molybdoenzymes catalyze redox reactions that transfer electrons to a variety of substrates that can act as terminal electron acceptors for energy generation. Seleniivibrio woodruffii strain S4T also has essential genes for molybdate transporters and the biosynthesis of the molybdopterin guanine dinucleotide cofactors characteristic of the active centers of DMSORs. Phylogenetic analysis revealed candidate respiratory DMSORs spanning nine subfamilies encoded within the genome. Our analysis revealed the untapped potential of this interesting microorganism and expanded our knowledge of molybdoenzyme co-occurrence.

Louie, Tiffany S.↗

DOE OSTI2017

Mechanisms and Rates of U(VI) Reduction by Fe(II) in Homogeneous Aqueous Solution and the Role of U(V) Disproportionation

Molecular-level pathways in the aqueous redox transformation of uranium by iron remain unclear, despite the importance of this knowledge for predicting uranium transport and distribution in natural and engineered environments. As the relative importance of homogeneous versus heterogeneous pathways is difficult to probe experimentally, here we apply computational molecular simulation to isolate rates of key one electron transfer reactions in the homogeneous pathway. By comparison to experimental observations the role of the heterogeneous pathway also becomes clear. Density functional theory (DFT) and Marcus theory calculations for all primary monomeric species at pH values ≤7 show for UO22+ and its hydrolysis species UO2OH+ and UO2(OH)20 that reduction by Fe2+ is thermodynamically favorable, though kinetically limited for UO22+. An inner-sphere encounter complex between UO2OH+ and Fe2+ was the most stable for the first hydrolysis species and displayed an electron transfer rate constant ket = 4.3 × 103 s-1. Three stable inner- and outer-sphere encounter complexes between UO2(OH)20 and Fe2+ were found, with electron transfer rate constants ranging from ket = 7.6 × 102 to 7.2 × 104 s-1. Homogeneous reduction of these U(VI) hydrolysis species to U(V) is, therefore, predicted to be facile. In contrast, homogeneous reduction of UO2+ by Fe2+ was found to be thermodynamically unfavorable, suggesting the possible importance of U(V)-U(V) disproportionation as a route to U(IV). Calculations on homogeneous disproportionation, however, while yielding a stable outer-sphere U(V)-U(V) encounter complex, indicate that this electron transfer reaction is not feasible at circumneutral pH. Protonation of both axial O atoms of acceptor U(V) (i.e., by H3O+) was found to be a prerequisite to stabilize U(IV), consistent with the experimental observation that the rate of this reaction is inversely correlated with pH. Thus, despite prevailing notions that U(V) is rapidly eliminated by homogeneous disproportionation, this pathway is irrelevant at environmental conditions.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2021

Materials representation and transfer learning for multi-property prediction

The adoption of machine learning in materials science has rapidly transformed materials property prediction. Hurdles limiting full capitalization of recent advancements in machine learning include the limited development of methods to learn the underlying interactions of multiple elements as well as the relationships among multiple properties to facilitate property prediction in new composition spaces. To address these issues, we introduce the Hierarchical Correlation Learning for Multi-property Prediction (H-CLMP) framework that seamlessly integrates: (i) prediction using only a material's composition, (ii) learning and exploitation of correlations among target properties in multi-target regression, and (iii) leveraging training data from tangential domains via generative transfer learning. The model is demonstrated for prediction of spectral optical absorption of complex metal oxides spanning 69 three-cation metal oxide composition spaces. H-CLMP accurately predicts non-linear composition-property relationships in composition spaces for which no training data are available, which broadens the purview of machine learning to the discovery of materials with exceptional properties. This achievement results from the principled integration of latent embedding learning, property correlation learning, generative transfer learning, and attention models. The best performance is obtained using H-CLMP with transfer learning [H-CLMP(T)] wherein a generative adversarial network is trained on computational density of states data and deployed in the target domain to augment prediction of optical absorption from composition. H-CLMP(T) aggregates multiple knowledge sources with a framework that is well suited for multi-target regression across the physical sciences.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Exploring DataVortex Systems for Irregular Applications

Emerging applications for data analytics and knowledge discovery typically have irregular or unpredictable communication patterns that do not scale well on parallel systems designed for traditional bulk-synchronous HPC applications. New network architectures that focus on minimizing (short) message latencies, rather than maximizing (large) transfer bandwidths, are emerging as possible alternatives to better support those applications with irregular communication patterns. We explore a system based upon one such novel network architecture, the Data Vortex interconnection network, and examine how this system performs by running benchmark code written for the Data Vortex network, as well as a reference MPI-over- Infiniband implementation, on the same cluster.

Data Vortex, High-Performance Computing, Networkin↗

DOE OSTI2022

Ecosystem consequences of introducing plant growth promoting rhizobacteria to managed systems and potential legacy effects

The rapidly growing industry of crop biostimulants leverages the application of plant growth promoting rhizobacteria (PGPR) to promote plant growth and health. However, introducing nonnative rhizobacteria may impact other aspects of ecosystem functioning and have legacy effects; these potential consequences are largely unexplored. Nontarget consequences of PGPR may include changes in resident microbiomes, nutrient cycling, pollinator services, functioning of other herbivores, disease suppression, and organic matter persistence. Importantly, we lack knowledge of whether these ecosystem effects may manifest in adjacent ecosystems. The introduced PGPR can leave a functional legacy whether they persist in the community or not. Legacy effects include shifts in resident microbiomes and their temporal dynamics, horizontal transfer of genes from the PGPR to resident taxa, and changes in resident functional groups and interaction networks. Ecosystem functions may be affected by legacies PGPR leave following niche construction, such as when PGPR alter soil pH that in turn alters biogeochemical cycling rates. Here, we highlight new research directions to elucidate how introduced PGPR impact resident microbiomes and ecosystem functions and their capacity for legacy effects.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

NESC GN&C TDT Workshop on 2D Image Motion Optical Transfer Functions, Pointing Performance Analysis, and Requirements

What You Will Learn: The focus is on payload imaging performance due to pointing motion. Some historical background on pointing performance analysis is given. The Optical Transfer Function (OTF) and Modulation Transfer Function (MTF) are defined. The imaging performance due to pointing motion is measured by image motion optical transfer functions (IM OTF). IM OTFs are defined for displacement, smear, and jitter motions, which are all rigorously defined. Deterministic and Statistical IM OTFs are briefly derived and graphically illustrated and compared. The IM OTFs are parameterized by pointing error metrics(PEM), which are means and covariances of displacement, smear, and jitter. Emphasis is on procedures and algorithms to evaluate the image motion optical transfer functions and pointing error metrics. Three procedures are covered, which depend on whether the pointing error data is from time-domain simulation, frequency-domain analysis, or stochastic modeling. A method to evaluate the relative contribution of disturbance sources and to identify the most significant contributors is presented. The presentation includes pertinent discussion of flexible structures and control-structure interaction. No single book can adequately cover this subject, so a book is not required for the course. A list of selected articles, reports, documents, and books is provided for reference and further study. Mathis kept to the minimum necessary to convey principles; lengthy derivations are left to the reference material. Graphics are used to illustrate concepts. As with any such learning endeavor, the knowledge gained will be retained and strengthened through actual practice.c©2019–2021 Mark E. Pittelkau— 5

NASA Engineering and Safety Center (NESC)↗

DOE OSTI2017

Knowledge Management in the Field of Nuclear Energy - How to Bridge the Gap between Retiring Workforce and Next Generations - 17101

The current phase-out decision of the German Federal Government and the 'Energiewende' - resulting from the Fukushima Daiichi Accident in 2011 - changed the nuclear market significantly. Together with the change in political and social attitude towards nuclear energy since 2002 it has contributed to a decline in technical expertise. This as well as the generation change in the nuclear technology lead to the risk of losing accumulated knowledge and experience which still are essential for the future - not only in Germany but in other countries - even though the focus in Germany will shift from operating to decommissioning, dismantling and radioactive waste management. A long-term strategy in order to preserve technical expertise to solve the forthcoming tasks in Germany was required. This strategy should include e.g. the implementation of technical programs not only for internal training of the staff but also for authorities. Together with authorities TUV NORD developed individual training concepts for a broad range of customers to preserve a transfer of know-how with the state-of-the-art in science and technology and even support international projects, especially in countries with less experience in the nuclear fields. Additionally, special data bases were developed in order to ensure the accessibility of long-term nuclear data storage. Furthermore technical conferences in different fields like decommissioning and radioactive waste disposal were established as an opportunity for knowledge exchange. Based on given examples it is being demonstrated how technical expertise can be preserved even though the field of nuclear energy in Germany has changed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Nuclear Data Sheets for A=189

Evaluated experimental data are presented for 13 known mass 189 nuclides (Hf, Ta, W, Re, Os, Ir, Pt, Au, Hg, Tl, Pb, Bi, Po). Since the 2003Wu02 publication, structure and decay data from 25 new and primary publications have been incorporated in the current work, while adding a new 189 Hf nuclide. New data have been added for all nuclides except 189 Au and 189 Hg. Moreover, several previous datasets were modified for β-decay Q values and conversion coefficients even when no new publications appeared since 2003Wu02. In spite of large amounts of data available for A=189 nuclides, several deficiencies remain, which are pointed out below in the hope that further experimental work may improve our knowledge of structure of these nuclides. For 189 Hf and 189 Ta, ground-state half-lives, and their decay schemes are unknown. An isomer in 189 Ta has recently been established but its decay characteristics are unknown, even though several gamma rays were connected with its decay. No excited states are known in 189 W and only one in 189 Po. The decay scheme of 189 W is known poorly with most gamma rays left as unassigned. The decay schemes of 189 Au and 189 Pb g.s. suffer from incompleteness, while those for the g.s. and isomer of 189 Tl are almost absent. The decay schemes of g.s. and isomer of 189 Hg are very complex as apparent from the study by 1996Wo04. Evaluators feel that these two decay schemes could be improved with modern gamma-ray detector arrays. While several isomers are known in many of the A=189 nuclides, there is in general lack of information of level half-lives, thus limiting the knowledge of transition probabilities. High-spin structures, including SD bands in 189 Hg and 189 Tl, are known in 189 Re, 189 Ir, 189 Pt, 189 Au, 189 Hg, 189 Tl, 189 Pb and 189 Bi. Single-particle transfer data are available for 189 Re, 189 Os, and 189 Pt; and two-neutron transfer data for 189 Ir.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

A Biophysical Perspective on Enzyme Catalysis

According to the article, even after a century of investigation, our understanding of how enzymes work remains far from complete. In particular, several factors that enable enzymes to achieve high catalytic efficiencies remain only poorly understood. A number of theories have been developed, which propose or reaffirm that enzymes work as structural scaffolds, serving to bring together and properly orient the participants so that the reaction can proceed; therefore, leading to enzymes being viewed as only passive participants in the catalyzed reaction. A growing body of evidence shows that enzymes are not rigid structures but are constantly undergoing a wide range of internal motions and conformational fluctuations. In this Perspective, on the basis of studies from our group, we discuss the emerging biophysical model of enzyme catalysis that provides a detailed understanding of the interconnection among internal protein motions, conformational substates, enzyme mechanisms, and the catalytic efficiency of enzymes. For a number of enzymes, networks of conserved residues that extend from the surface of the enzyme all the way to the active site have been discovered. These networks are hypothesized to serve as pathways of energy transfer that enables thermodynamical coupling of the surrounding solvent with enzyme catalysis and play a role in promoting enzyme function. Additionally, the role of enzyme structure and electrostatic effects has been well acknowledged for quite some time. Collectively, the recent knowledge gained about enzyme mechanisms suggests that the conventional paradigm of enzyme structure encoding function is incomplete and needs to be extended to structure encodes dynamics, and together these enzyme features encode function including catalytic rate acceleration.

Biochemistry & Molecular Biology↗