Basic Science Simulations Provide New Insights to Aid Hydrogen Gas Turbine Development
Massive first-principles simulation provides insight into flame anchoring in a hydrogen-rich jet in cross-flow.
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SEARCH · Engineering Papers
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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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Technetium Sorption by Cementitious Materials Under Reducing Conditions
The objective of this study was to measure Tc sorption to cementitious materials under reducing conditions to simulate Saltstone Disposal Facility conditions. Earlier studies were conducted and the experimental conditions were found not to simulate those of the facility. Through a five month subcontract with Clemson University, sorption of 99 Tc to four cementitious materials was examined within an anaerobic glovebag targeting a 0.1% H 2 (g)/ 99.9% N 2 (g) atmosphere. Early experiments based on Tc sorption and Eh indicated that 0.1% H 2 (g) (a reductant) was necessary to preclude experimental impacts from O 2 (g) diffusion into the glovebag. Preliminary data to date (up to 56 days) indicates that sorption of 99 Tc to cementitious materials increased with increasing slag content for simulated saltstone samples. This is consistent with the conceptual model that redox active sulfide groups within the reducing slag facilitate reduction of Tc(VII) to Tc(IV). These experiments differ from previous experiments where a 2% H 2 (g) atmosphere was maintained (Kaplan et al., 2011 (SRNL-STI-2010-00668)). The impact of the 2% H 2 (g) reducing atmosphere on this data was examined and determined to cause the reduction of Tc in experimental samples without slag. In the present ongoing study, after 56 days, Tc sorption by the 50-year old cement samples (no slag) was undetectable, whereas Tc sorption in the cementitious materials containing slag continues to increase with contact time (measured after 1, 4, 8, 19 and 56 days). Sorption was not consistent with spike concentrations and steady state has not been demonstrated after 56 days. The average conditional K d value for the Vault 2 cementitious material was 6,362 mL/g (17% slag), for the TR547 Saltstone (45% slag) the conditional K d was 1258 mL/g, and for TR545 (90% slag) the conditional K d was 12,112 mL/g. It is anticipated that additional samples will be collected until steady state conditions are established to permit measuring more representative K d and solubility values under these experimental conditions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Literature Review on the Sorption of Plutonium, Uranium, Neptunium, Americium and Technetium to Corrosion Products on Waste Tank Liners
The Savannah River Site (SRS) has conducted performance assessment (PA) calculations to determine the risk associated with closing liquid waste tanks. The PA estimates the risk associated with a number of scenarios, making various assumptions. Throughout all of these scenarios, it is assumed that the carbon-steel tank liners holding the liquid waste do not sorb the radionuclides. Tank liners have been shown to form corrosion products, such as Fe-oxyhydroxides (Wiersma and Subramanian 2002). Many corrosion products, including Fe-oxyhydroxides, at the high pH values of tank effluent, take on a very strong negative charge. Given that many radionuclides may have net positive charges, either as free ions or complexed species, it is expected that many radionuclides will sorb to corrosion products associated with tank liners.
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Advanced Anchoring Technology (Final Technical Report)
It is generally conceded that the costs associated with current practices for the mooring, anchoring, or foundation systems of Marine HydroKinetic (MHK) and Deepwater Floating Wind systems are a disproportionate portion of the total cost of an installed system. Reducing the cost of the mooring and anchoring components for MHK systems can contribute substantially to reducing the levelized cost of electricity (LCOE).
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Review of Concrete Biodeterioration in Relation to Buried Nuclear Waste
Long-term storage of low level radioactive material in below ground concrete disposal units (DUs) (Saltstone Disposal Facility) is a means of depositing wastes generated from nuclear operations of the U.S. Department of Energy. Based on the currently modeled degradation mechanisms, possible microbial induced effects on the structural integrity of buried low level wastes must be addressed. Previous international efforts related to microbial impacts on concrete structures that house low level radioactive waste showed that microbial activity can play a significant role in the process of concrete degradation and ultimately structural deterioration.
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Technetium Sorption by Cementitious Materials Under Reducing Conditions
The objective of this study was to measure technetium ( 99 Tc) sorption to cementitious materials under reducing conditions to simulate Saltstone Disposal Facility conditions. 99 Tc(VII) batch sorption experiments were conducted for 319 days in an inert glovebag with a variety of cementitious materials (aged cement, Vault 2, TR545, and TR547) containing varying amounts of blast furnace slag. Between 154 and 319 days, the 99 Tc aqueous concentrations tended to remain constant and samples amended with different initial 99 Tc concentrations, tended to merge at about 10 -9 M for Vault 2 (17% slag) and TR545 (90% slag) and 10 -8 M for TR547 (45% slag). This data provided strong evidence that solubility, and not adsorption (K{sub d} values), was controlling aqueous 99 Tc concentrations.
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Technetium Sorption By Cementitious Materials Under Reducing Conditions
The objective of this study was to measure Tc sorption to cementitious materials under reducing conditions to simulate Saltstone Disposal Facility conditions. Earlier studies were conducted and the experimental conditions were found not to simulate those of the facility. Through a five month subcontract with Clemson University, sorption of 99Tc to four cementitious materials was examined within an anaerobic glovebag targeting a 0.1% H 2 (g)/ 99.9% N 2 (g) atmosphere. Early experiments based on Tc sorption and Eh indicated that 0.1% H 2 (g) (a reductant) was necessary to preclude experimental impacts from O 2 (g) diffusion into the glovebag. Preliminary data to date (up to 56 days) indicates that sorption of 99 Tc to cementitious materials increased with increasing slag content for simulated saltstone samples. This is consistent with the conceptual model that redox active sulfide groups within the reducing slag facilitate reduction of Tc(VII) to Tc(IV).
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IHT: Tools for Computing Insolation Absorption by Particle Laden Flows
This report describes IHT, a toolkit for computing radiative heat exchange between particles. Well suited for insolation absorption computations, it is also has potential applications in combustion (sooting flames), biomass gasification processes and similar processes. The algorithm is based on the 'Photon Monte Carlo' approach and implemented in a library that can be interfaced with a variety of computational fluid dynamics codes to analyze radiative heat transfer in particle-laden flows. The emphasis in this report is on the data structures and organization of IHT for developers seeking to use the IHT toolkit to add Photon Monte Carlo capabilities to their own codes.
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Comprehensive Benchmark Suite for Simulation of Particle Laden Flows Using the Discrete Element Method with Performance Profiles from the Multiphase Flow with Interface eXchanges (MFiX) Code
Five benchmark problems are developed and simulated with the computational fluid dynamics and discrete element model code MFiX. The benchmark problems span dilute and dense regimes, consider statistically homogeneous and inhomogeneous (both clusters and bubbles) particle concentrations and a range of particle and fluid dynamic computational loads. Several variations of the benchmark problems are also discussed to extend the computational phase space to cover granular (particles only), bidisperse and heat transfer cases. A weak scaling analysis is performed for each benchmark problem and, in most cases, the scalability of the code appears reasonable up to approx. 103 cores. Profiling of the benchmark problems indicate that the most substantial computational time is being spent on particle-particle force calculations, drag force calculations and interpolating between discrete particle and continuum fields. Hardware performance analysis was also carried out showing significant Level 2 cache miss ratios and a rather low degree of vectorization. These results are intended to serve as a baseline for future developments to the code as well as a preliminary indicator of where to best focus performance optimizations.
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Waste Form Release Calculations for the 2005 Integrated Disposal Facility Performance Assessment. Erratum
This report refers to or contains K g values for glasses LAWA44, LAWB45 and LAWC22 affected by calculations errors as identified by Papathanassiu et al. (2011). The corrected K g values are reported in an erratum included in the revised version of the original report. The revised report can be referenced as follows: Pierce E. M. et al. (2004) Waste Form Release Data Package for the 2005 Integrated Disposal Facility Performance Assessment. PNNL-14805 Rev. 0 Erratum. Pacific Northwest National Laboratory, Richland, WA, USA.
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Turbulent Flow Simulation at the Exascale: Opportunities and Challenges Workshop: August 4-5, 2015, Washington, D.C.
This report details the impact exascale will bring to turbulent-flow simulations in applied science and technology. The need for accurate simulation of turbulent flows is evident across the DOE applied-science and engineering portfolios, including combustion, plasma physics, nuclear-reactor physics, wind energy, and atmospheric science. The workshop brought together experts in turbulent-flow simulation, computational mathematics, and high-performance computing. Building upon previous ASCR workshops on exascale computing, participants defined a research agenda and path forward that will enable scientists and engineers to continually leverage, engage, and direct advances in computational systems on the path to exascale computing.
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Determining the Release of Radionuclides from SRS Tank 12H Waste Residual Solids Following Tank Closure
Eight High Level Waste (HLW) tanks used to store radioactive waste slurries have been emptied and closed at the Savannah River Site (SRS). Performance Analyses (PA) modeling of the release of radionuclides from residual waste solids in these tanks into the environment over extended time periods indicated the most likely risk drivers for environmental contamination. Radionuclide leaching studies were desired to provide additional information regarding the residual waste solubility assumptions used in the models.
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MFIX DEM Enhancement for Industry-Relevant Flows (Final Report)
The overall goal of this two-phase project is to implement performance improvements of the Multiphase Flow with Interphase Exchanges (MFIX) Discrete Element Model (DEM) code that enable a transformative shift for industrial use. Prior to this effort, the largest simulations performed using MFIX are O(10 7 ) particles. This falls short of the O(10 9 ) particle simulations that must be completed on a timescale of days or weeks (vs. months or years) to enable simulations with physically-relevant domain sizes to be incorporated into industrial design cycles within five years. This was accomplished by tailoring best-in-class practices to bear on the unique challenges posed by the MFIX-DEM algorithm and code base. Scientific simulations (e.g., in cosmology, turbulent combustion) routinely use massively parallel computing to update far more particles in short wall clock times. Results from Phase 1 (1.5 years in duration) indicated significant gains in speed were possible for a wide range of benchmark cases. Moreover, a survey sent to >35 companies indicates that the timing is ideal for such an enhanced tool, with >80% of the respondents indicating that DEM is already value-added or will be within the next 5 years, and >70% of the respondents indicating that improved speed is the top computational priority. In Phase 2 (3.5 years in duration), the two major barriers that hinder industry from effectively using multiphase Computational Fluid Dynamics (CFD) to cut costs and improve performance, namely computational overhead and confidence in predictions, continued to be addressed. Regarding the former, the results from Phase 1 to guide the effort, with enhancements focused on an improved time-stepping algorithm and particle sorting. Four target problems of 1 billion particles each and increasing complexity were identified: homogeneous cooling, tumbler with continuous particle size distribution, discharge from a rectangular hopper and a cylindrical riser. Each of these were successfully simulated for relevant time scales (on order of seconds) using less than 24 hours of wall clock time. These represent the first 1-billion particle DEM simulations performed with MFIX, namely using the MFIX-Exa code. This code is currently under development at NETL in collaboration with Lawrence Berkeley National Laboratory. Regarding the second barrier on predictive uncertainty, experiments from Phase 1 (interacting nozzles - hydrodynamics only) and Phase 2 (very small-scale segregation experiments) were used to demonstrate the ability of two simplified approaches to uncertainty quantification (UQ). By limiting the number of particles, UQ based on the simplified treatment was compared to standard UQ, which was shown to have much higher computational demands. Experiments were also performed on a pilot-scale stripper unit to provide validation data for future CFD-DEM simulations and UQ.
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AI@DOE Interim Executive Report
Interim executive report for DOE’s Office of Science, NNSA, and Applied Energy Offices, in collaboration with the Artificial Intelligence and Technology Office, DOE AI roundtable workshops (December 2021 through February 2022) (“AI@DOE”). These workshops were used to help identify AI research requirements and priorities for the next decade for Department of Energy in developing machine-learning-based prediction and decision-support capabilities that address and anticipate DOE mission challenges. These missions’ challenges for AI include: AI to advance scientific discovery and technological innovation AI to support high consequence decisions while managing risk AI to improve DOE’s responsiveness to national & global issues AI to assist stewardship of the environment and national critical infrastructure These will be addressed in large part through the development and application of new and powerful artificial intelligence and/or machine learning algorithms and strategies. https://web.cvent.com/event/fc3922f8-fc75-4041-a317-f13a1da44f7c/summary?locale=en-US&i=2Wx2tjbStkydRFq_N2whPw
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Tools for Design and Scale-Up of Solar Thermochemical Reactors: Cooperative Research and Development Final Report, CRADA Number CRD-13-00530
NREL will be collaborating with the Participant on a United States - Australia Solar Energy Collaboration (USASEC) Project Number 1-USO034 "Tools for design and scale-up of solar thermochemical reactors." The grant funds for the Participant's 3.5 year project number 1-US034 commencing on 1 February 2013 have been awarded to the Participant by the Australian Renewable Energy Agency and NREL will be collaborating with the Participant during the final 28 months of this project. This project seeks to provide basic knowledge required to design solar thermochemical reactors able to perform the required energy conversions. In several proposed and demonstrated reactors, concentrated sunlight directly irradiates small solid particles suspended in fluid, enabling very high heat transfer rates to the particles which are the sites of chemical reaction. The reactors, therefore, involve the complex and couple dynamics of turbulent, chemically reacting, particle-laden flows and their interaction with concentrating solar radiation. A strong understanding of these coupled interactions will be crucial important in predicting and optimizing the performance of prototype reactors, but this understanding does not yet exist, since they have never been studied in any fundamental way. The project has a assembled an internationally leading team from The University of New South Wales (UNSW) and the University of Adelaide in Australia and the NREL in the United States to address this key gap in available know-how. The project will use U.S. Dept. of Energy (DOE) supercomputers, among the most powerful available worldwide, with cutting-edge software tools to perform first-principles simulations of the relevant interactions. These studies will be combined with detailed laser-based measurements in Australia to provide the first comprehensive databases concerning the governing phenomena in directly irradiated solar-thermochemical reactors. The outcomes will be the basic scientific knowledge, engineering knowhow and modeling tools necessary to design new reactor concepts and then scale up from the laboratory bench to practical size systems.
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Follow-on Report of Analysis of Approaches to Supplemental Treatment of Low–Activity Waste at the Hanford Nuclear Reservation (Volumes I & II)
The Hanford Site, in southeast Washington State, is preparing to disposition approximately 56,000,000 gallons (56 Mgal) of radioactive and chemically hazardous wastes currently stored in underground tanks at the site. Tank wastes will be divided into a high-activity fraction and a low-activity fraction for subsequent treatment and disposition. A waste processing and treatment facility, the Waste Treatment and Immobilization Plant (WTP), will include the high-level waste (HLW) vitrification facility (WTP HLW Vitrification Facility) for immobilizing the high-activity fraction and a low-activity waste (LAW) vitrification facility (WTP LAW Vitrification Facility) for immobilizing the low-activity fraction. Both facilities will use vitrification technology to immobilize the Hanford tank wastes in a glass waste form.
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Advanced Research Directions on AI for Science, Energy, and Security: Report on Summer 2022 Workshops
Over the past decade, fundamental changes in artificial intelligence (AI)—from foundational to applied—have delivered dramatic insights across a wide breadth of U.S. Department of Energy (DOE) mission space. AI is helping to augment and improve scientific and engineering workflows (e.g., for control, design, and dramatic performance gains through surrogate models) in national security, the Office of Science, and DOE’s applied energy programs. The progress and potential for AI in DOE science was captured in the 2020 “AI for Science” report from the DOE laboratory community in collaboration with academia and industry. Specific scientific areas ready to further leverage the power of AI ranged from the scale and performance of computational models to data analysis to creating new classes of observations using computer vision. Since that report, the scale and scope of scientific AI have accelerated, revealing new, emergent properties that yield insights that go beyond enabling opportunities to being potentially transformative in the way that scientific problems are posed and solved. Thus, under the guidance of both the Office of Science (SC) and the National Nuclear Security Administration (NNSA), the DOE national laboratories organized a series of workshops in 2022 to gather input on new and rapidly emerging opportunities and challenges of scientific AI. This 2023 report is a synthesis of those workshops. The scientific community believes AI can have a foundational impact on a broad range of DOE missions, including science, energy, and national security. Further, DOE has unique capabilities that enable the community to drive progress in scientific use of AI, building on long-standing DOE strengths and investments in computation, data, and communications infrastructure, spanning the Energy Sciences Network (ESnet), the Exascale Computing Project (ECP), and integrative programs such as the NNSA Office of Defense Programs Advanced Simulation and Computing (ASC) and the SC Scientific Discovery through Advanced Computing (SciDAC) programs.
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Language Model Inventory v1.0 [Slides]
This presentation is an inventory of the latest large language model (LLM) offerings. It lists some of the most prominent open- and closed-source LLMs. Given the rapid pace of progress in this space, it is not guaranteed to be a comprehensive list. This resource is intended to help inform decision-making about LLM capabilities at NREL.
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