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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 OSTI2024

Embedded symmetric positive semi-definite machine-learned elements for reduced-order modeling in finite-element simulations with application to threaded fasteners

Here, we present a machine-learning strategy for finite element analysis of solid mechanics wherein we replace complex portions of a computational domain with a data-driven surrogate. In the proposed strategy, we decompose a computational domain into an “outer” coarse-scale domain that we resolve using a finite element method (FEM) and an “inner” fine-scale domain. We then develop a machine-learned (ML) model for the impact of the inner domain on the outer domain. In essence, for solid mechanics, our machine-learned surrogate performs static condensation of the inner domain degrees of freedom. This is achieved by learning the map from displacements on the inner-outer domain interface boundary to forces contributed by the inner domain to the outer domain on the same interface boundary. We consider two such mappings, one that directly maps from displacements to forces without constraints, and one that maps from displacements to forces by virtue of learning a symmetric positive semi-definite (SPSD) stiffness matrix. We demonstrate, in a simplified setting, that learning an SPSD stiffness matrix results in a coarse-scale problem that is well-posed with a unique solution. We present numerical experiments on several exemplars, ranging from finite deformations of a cube to finite deformations with contact of a fastener-bushing geometry. We demonstrate that enforcing an SPSD stiffness matrix drastically improves the robustness and accuracy of FEM–ML coupled simulations, and that the resulting methods can accurately characterize out-of-sample loading configurations with significant speedups over the standard FEM simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Temporal Patterns in Soil Redox Potential Vary Across a Freshwater Coastal Delta

Widespread and persistent flooding is submerging coastal ecosystems, particularly along the Louisiana Gulf coast, where flooding results from the compounding effects of ground subsidence and rising sea level. Restoration projects aim to mitigate land loss by diverting sediment loads from rivers into degraded areas to increase ground elevation. To predict how coastal ecosystems will change over time in response to projected changes in relative sea level and restoration, it is necessary to understand how subsurface biogeochemical processes respond to dynamic hydrologic forcings. Here, this study evaluates how environmental parameters that integrate biogeochemical processes vary with water table fluctuations in the freshwater Wax Lake Delta (WLD) in Louisiana, USA, where water diversions have formed one of the only active deltas along the coast. High‐frequency observations of water level, soil redox potential, specific conductance and pH were made for 1 year along elevation transects located on the older, proximal and younger, distal ends of a deltaic island. Redox responded rapidly to changing water tables, with fluctuations occurring primarily in shallow soils (< 20 cm) and at higher elevations. Deeper soils and those at lower elevation remained inundated and reduced. Semi‐diurnal tidal fluctuations were pronounced in younger, distal soils, presumably due to rapid groundwater exchange with the river channel. Tidal signals were muted in older soils that instead exhibited seasonal variability associated with river discharge and evapotranspiration. Although much of the delta sediments are persistently reducing and anoxic, redox fluctuations in the natural levees that border the deltaic islands likely drive high rates of biogeochemical activity. Evaluating how hydrology drives the frequency and duration of redox fluctuations provides a basis for understanding how biogeochemical processes might vary with complex hydrological interactions in coastal systems.

Herndon, Elizabeth [Oak Ridge National Laboratory ↗
DOE OSTI2022

Designing Ceria/Alumina for Efficient Trapping of Platinum Single Atoms

Cerium oxide (ceria) has been shown to be very effective at trapping platinum atoms, due to formation of stable surface complexes at step edges, where coordinatively unsaturated cerium cations are present. But ceria loses its effectiveness when heated to high temperatures, due to loss of surface area and growth in particle size associated with sintering of the oxide. Being a rare-earth, and with limited supplies worldwide, it is important to develop methods to improve the effectiveness of ceria as a catalyst support. Here we explore the performance for trapping Pt atoms when the ceria is supported on a high surface area alumina carrier. This helps create a more sustainable catalyst formulation, especially if we can retain the high dispersion of Pt seen on ceria supports. For this work, we studied the atom trapping efficacy of ceria/alumina samples with increasing ceria content (8 wt% - 50%) and contrasted the behavior with pure ceria. Electron microscopy reveals that when dispersed on alumina, ceria is present in the form of crystalline nanoparticles as well as isolated cerium ions. These two forms of ceria differ markedly in their ability to trap Pt atoms. Atomically dispersed cerium is present in the form of Ce 3+ cations on alumina, however this form of ceria is not effective for trapping Pt atoms. Our results show that the atom trapped Pt resides primarily on crystalline ceria nanoparticles. CO oxidation was used as a probe reaction to evaluate the performance of these Pt AT /ceria-alumina catalysts. As a result, we conclude that over the range of ceria loadings we investigated, 50% ceria/alumina represents the optimal catalyst support for achieving high surface area and atom trapping efficiency while helping reduce the total ceria content in this catalyst system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Design of Multi-Stage Solvent Extraction Process for Separation of Rare Earth Elements

Flowsheet design and stage determination for the separation of rare earth elements (REEs) using solvent extraction (SX) is a challenging task because of the chemical similarity of the REEs. Low separation factors between the elements and complex equilibrium chemistry provide unique challenges to designing an efficient flowsheet for the separation of elements. The multi-stage nature of the SX process adds further complexity, making the assessment of products for a proposed design and stage combination difficult. Therefore, to develop a SX flowsheet, it is essential to quantify the performance for various design and separation conditions. This paper attempts to address the challenge by utilizing an equilibrium and process modeling approach. Results from a bench-scale study performed on a 10 g/L rare earth salt mixture were used in studying the extraction/stripping behavior and developing equilibrium models. DEHPA with TBP as a phase modifier was used as an extractant, while hydrochloric acid was utilized as a stripping agent. The results obtained were used in developing extraction/stripping models, which were integrated into a process framework of a SX train in a Matlab/Simulink environment. The models were programmed as a function block routine and used for developing a flowsheet, which was simulated for differing separation and design conditions. To identify optimum stage combinations, a particle swarm optimization (PSO) routine was developed and implemented for each SX train. Recovery and purity of elements of interest were used as objective function criteria. The stage combination leading to the minimization of the objective function was used to identify the optimum stage combination for a series of SX trains to attempt a balance of purity and recovery. The models and optimization method were implemented to separate a feed mixture containing REEs, which indicated that 99.52 and 85.41 percent purity is achievable for Yttrium and Lanthanum separation using 8-12-3 and 10-3-5 stage combination for loading, scrubbing, and striping. The model also indicated difficult separability between neodymium, praseodymium, and cerium.

Srivastava, Vaibhav (ORCID:0000000212645987)↗
DOE OSTI2020

COVID-19 biomarkers based on respiratory microbiome content

COVID-19 patient care management would greatly benefit from new tools that enable accurate assessment of disease severity and stage, potentially enabling a personalized medicine approach. Detection of the SARS-CoV-2 virus itself, or even quantitation of viral loads, is not sufficient for accurate assessment of disease state beyond diagnosis of infection [eg, doi:10.1093/cid/ciaa344]. Levels of usual suspect protein biomarkers associated with host response to infection [eg, C-reactive protein (CRP); cytokines like IL-6, TNF-alpha, and IL-10; complement proteins like C3a and C5a], and of individual blood cell types (eg, leukocytes, lymphocytes, and subsets thereof), show limited correlation with disease severity and stage, with high patient-to-patient and study-to-study variability [eg, doi:10.1093/cid/ciaa248]. High-dimensional panels of biomarkers should have greater predictive power and resilience to unavoidable sources of variability; however, their assembly from proteins and cell types is extremely difficult, due to technical limitations in analyte measurement, especially with regard to starting material requirements and detection sensitivity. Host response profiling through Next Generation Sequencing (NGS) of gene expression patterns (ie, RNA-Seq) is a promising approach, but at the time of this project there were only two publicly available datasets of relevance [doi:10.1093/cid/ciaa203, doi:10.1080/22221751.2020.1747363], and close inspection of them revealed that each had at least one major flaw that severely undermined its value in supporting robust analysis of host response to SARS-CoV- 2 infection. However, the first of these studies [doi:10.1093/cid/ciaa203] fortuitously collected NGS data not only from host cells, but also from bacteria present in bronchoalveolar lavage fluid (BALF) recovered from COVID-19 patients; and because the respiratory microbiome (in terms of bacterial species content) is far less complex than the human transcriptome, the NGS data collected were sufficient to provide coverage depth supporting robust analysis. Surprisingly, the authors of the study did not carry out a detailed analysis of these data and their potential for revealing important new information about COVID-19. Therefore, we carried out a meta-analysis of the dataset as a first step in evaluating the potential for profiling of respiratory microbiome dynamics as a means of accurately assessing COVID-19 disease state.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Printable Fiber Reinforced Cement Composites – Feasibility Study

Additive manufacturing is enabling the manufacturability of structures with previously unattainable complexity or functionality, and there is growing interest in additive manufacturing of “printed” concrete structures. The focus of this Phase 1 Technical Collaboration (TC) project was to evaluate feasibility of printing hybrid cement composite structures reinforced with textile carbon fibers (tCF). This project leverages other (non-IACMI) projects on cement formulation and printing process development, as well as on the production process for tCF. This project’s primary focus was to explore cement composite mix design with textile carbon fibers to be manufactured by MonteFibre (TC partner) and evaluate suitable fiber-matrix interface or sizing for cement composites working with Michelman (TC Partner). This project supports IACMI’s goal of reducing the cost and embodied energy of carbon fiber composites. Cost is one of the fundamental challenges to carbon fiber reinforced cement composites. Cement is an extremely inexpensive material (approximately $\$$0.05/lb). Adding 1 wt% of conventional carbon fiber to cement quadruples its cost. Therefore, the need to use low-cost carbon fiber and ensure that the additional cost of the carbon fiber has a greater cost benefit to the final product. This was the first preliminary evaluation to integrate tCF reinforcement in cement composites, and such potential tCF utilization should significantly reduce materials cost. Cement composite production is energy and emissions intensive, thus by strengthening it less material will be required. Hence, the embodied energy and production time of the resulting structures will be reduced. Additionally, integrating these new materials into additive processes can enable selective use of the material in high load or stress areas. It is noteworthy that past work in this field of fiber reinforced cement composites did not consider the optimization of fiber-matrix interface using suitable sizing. Carbon fiber reinforcement offers potential added benefits of thermal conductivity (which affects cure rate) and flow behavior that could provide opportunities for site specific utilization of carbon fiber on hybrid cement structures (e.g. use the fiber reinforcement on outer surfaces to enhance strength and modulus and then infiltrating the internal structures with conventional concrete). MonteFibre was the industry lead and planned on supplying the tCF for this project. However, during the short Phase-1 duration of this project, MonteFibre was unable to produce tCF for this project due to manufacturing plant being off-line throughout the course of the project. The project team decided to pursue an alternate option which involved demonstrating printable concrete with steel fibers by the ORNL lead, Dr. Brian Post. The University of Tennessee collaboration team focused on evaluating the suitable chemical sizing for carbon fibers working with Michelman and also developed methods for material characterization of cement-based composites to evaluate the material response for compression, shear, flexure, and tension. The two milestones for University of Tennessee, Knoxville were realized related to identification of one sizing suitable for carbon fiber reinforced cement composite and developing data associated with mechanical behavior of unreinforced (neat) and carbon fiber reinforced cement composites. ORNL could not complete the task of carbon fiber reinforced printed cement composites due to the reasons mentioned earlier, but was able to replace tCF with steel fibers to demonstrate the feasibility of printing with fiber reinforced cement composites. The Project team reviewed possible sizing chemistry available in collaboration with Michelman for use on carbon fiber reinforcement in cement composites and concrete applications. Our initial goal was to identify a sizing most promising for formulation with textile carbon fibers (tCF) to deliver excellent mechanical properties in composite material state. Since tCF was not available for this project as originally envisioned, the team continued this task to identify a suitable sizing for carbon fiber applications by applying such sizing to lower cost carbon fibers currently available commercially from Zoltek called Panex fibers. At a future time this can be optimized for textile carbon fibers from Montefibre. The bulk of previous work on carbon fiber reinforced cement has neglected the importance of fiber-matrix adhesion on mechanical properties of the cement composite and identifying this missing link was an important accomplishment for future research. Tensile behavior of fiber reinforced concrete is important to evaluate in order to realize the dream of concrete products that do not need reinforcing steel. Important sample preparation and testing procedures were addressed in this study and it was concluded that substantial improvements in tensile behavior, without compromising compressive strength, and improved ductility can result from the use of carbon fiber reinforcement.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles

Off-road vehicles, such as wheel loaders, excavators, and harvesters, are extensively utilized across a wide range of industries, including construction, agriculture, and mining. These machines have become indispensable in supporting the day-to-day operational needs of a nation, playing a critical role in various sectors' infrastructure and productivity. However, despite their utility, off-road vehicles are significant consumers of fossil fuels, resulting in substantial emissions that contribute to environmental degradation. This highlights the pressing need for research and technological advancements aimed at improving their energy efficiency and reducing their carbon footprint. There are, however, two primary challenges that must be addressed to achieve these goals. First, off-road vehicles typically perform both driving and working tasks simultaneously, which introduces a high level of complexity into their overall dynamic systems. Analysis the interactions between these functions is challenging. Second, research into off-road vehicles is inherently interdisciplinary, demanding expertise across several domains such as fluid power systems, vehicle dynamics, control theory, optimization techniques, and real-world implementation. Recognizing these challenges, we proposed the project titled "Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles" as a comprehensive solution to enhance fuel efficiency while simultaneously improving productivity. This project specifically focuses on autonomous off-road vehicles, with particular attention to wheel loaders, and seeks to develop novel methods to optimize energy consumption without sacrificing operational performance. The project integrates real-time control algorithms, vehicle dynamics modeling, and co-optimization of powertrain system and vehicle system to achieve these goals. Our optimization strategy dynamically co-optimizes critical parameters at both the powertrain and vehicle levels, including vehicle speed, working tool movements, powertrain dynamics, and engine operations in real-time. To streamline this optimization process, we developed a vehicle model that captures the key dynamics while significantly enhancing computational efficiency. This allows the system to intelligently minimize fuel consumption, all while maintaining or even improving productivity through real-time calculations during various off-road operations. To validate the effectiveness of this energy optimization method, we introduced a state-of-the-art Hardware-in-the-Loop (HIL) testbed. This reconfigurable testbed seamlessly integrates the actual engine with virtual models of the wheel loader's subsystems, allowing for accurate emulation of real-world operational loads and environments. By simulating these conditions, the HIL testbed enables us to evaluate the wheel loader’s performance under diverse working scenarios, ensuring the developed solution is applicable in real-world operations. This testbed proved to be instrumental in validating the optimization algorithms and demonstrating the system's practical effectiveness. During the evaluation and testing phase, we employed the HIL testbed to rigorously assess the energy savings and productivity improvements generated by the optimized system. The results were highly encouraging, revealing that the automated wheel loader achieved over 30% fuel savings compared to traditional, human-operated cycles, with comparable or even enhanced levels of productivity. The insights gained from this HIL-based testing provided critical validation of our approach and highlighted the potential for deploying these optimized autonomous technologies in real-world off-road vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2023

Local Power Impact Experiment Design for a New Fuel Type for use in the Advanced Test Reactor

The Advanced Test Reactor (ATR), and complimentary zero-power ATR Critical (ATRC) reactor, located at Idaho National Labs (INL), are undergoing conversion from Highly Enriched Uranium (HEU) to Low Enriched Uranium (LEU). Both have a variety of testing locations that can receive large variations in flux due to its unique serpentine design, consisting of five lobes (see Figure 1). Initial criticality and power distribution throughout the core are controlled by core-external outer shim control cylinders (OSCCs). Distinct test loops allow for testing at specific temperatures, pressures, and irradiation conditions. The ATR is one of the key nuclear engineering research and testing facilities within the DOE National Laboratory Complex, and the ATRC supports its operation [1]. Currently, the Office of Material Management and Minimization (M3) within the National Nuclear Security Administration of the DOE is working to convert the remaining research reactors, including the ATR, from 93% HEU fuel to 19.75% LEU fuel (LEU) to support non-proliferation [2]. Extensive materials testing at INL and internationally has demonstrated that a high-density uranium molybdenum (U 10Mo) alloy can meet the performance requirements of the remaining high powered research reactors. However, there are many technical challenges to address before the conversion to LEU can be successful, including the accurate characterization of the reactor core physics with LEU fuel. Reactor physics safety evaluations currently use Monte Carlo for the 21st Century (MC21), a continuous-energy Monte Carlo radiation transport code [3]. Existing MC21 models of the ATR and ATRC cores have a validation basis for use in neutronics analyses with HEU fuel. The models are used to support safety analyses that include comparisons to the safety requirements for the reactors. However, the use of the LOWE element in the ATR and ATRC is not currently covered by the current model validation basis. To deploy the new fuel type, extensive computational reactor physics support is necessary to support the use of LOWE in the ATR and ATRC. Therefore, LOWE requires a rigorous validation basis, aligned with that of HEU fuel, that takes advantage of the existing software tools and processes currently used for the ATR and ATRC. The experiment to validate of the MC21 models for determining power, the Power Impact Validation Experiment, will consist of two flux runs in the ATRC, one with fully HEU loading and one with a single LOWE element. Both flux runs will be instrumented with 20 sets of azimuthal fission wires and 3 sets of axial fission wires, as shown in Figure 4. Standard flux run methodology will be used [4]. Power Impact Validation Experiment data will be compared against MC21 calculated data, both for absolute fission rate accuracy and to determine the relative change in fission rates between the two runs. The results of the Power Impact Validation Experiment and subsequent evaluations will provide the validation basis for MC21 for use with LOWE elements. Key features of the Power Impact Validation Experiment include: (1) Two flux runs to allow for LOWE perturbed measurements to be compared to already validated measurements taken from a full core of HEU fuel, (2) Optimization of instrumentation to balance analytical needs with practical considerations (e.g., limited time window to count beta particles from fission products), and (3) Standard ATRC core loading, including both driver positions and flux traps, to minimize cost while remaining representative of typical ATR core loading.

42 ENGINEERING↗
DOE OSTI2026

Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials

Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.

Puga, Christina L.↗
DOE OSTI2022

A New Method to Overcome Carboxyamide Formation During AFEX Pretreatment of Lignocellulosic Biomass

Lignin-carbohydrate complexes (LCCs) in the plant cell wall are responsible for providing resistance against biomass-degrading enzymes produced by microorganisms. Four major types of lignin-carbohydrate bonds are reported in the literature, namely, benzyl ethers, benzyl esters, phenyl glycosides, and acetyl ester linkages. Ester’s linkages in the plant cell wall are labile to alkaline pretreatments, such as ammonia fiber expansion (AFEX), which uses liquid or gaseous ammonia to cleave those linkages in the plant cell wall and reduce biomass recalcitrance. Two competing reactions, notably hydrolysis and ammonolysis, take place during AFEX pretreatment process, producing different aliphatic and aromatic acids, as well as their amide counterparts. AFEX pretreated grasses and agricultural residues are known to increase conversion of biomass to sugars by four- to five-fold when subjected to commercial enzyme hydrolysis, yielding a sustainable feedstock for producing biofuels, biomaterials, and animal feed. Animal feed trials on dairy cows have demonstrated a 27% increase in milk production when compared to a control feedstock. However, the presence of carboxamides in feedstocks could promote neurotoxicity in animals if consumed beyond a certain concentration. Thus, there is the need to overcome regulatory hurdles associated with commercializing AFEX pretreated biomass as animal feed in the United States. This manuscript demonstrates a modified pretreatment for increasing the digestibility of industrial byproducts such as Brewer’s spent grains (BSG) and high-fiber meal (HFM) produced from BSG and dry distillers grains with soluble (DDGS), while avoiding the production of carboxamides. The three industrial byproducts were first treated with calculated amounts of alkali such as NaOH, Ca(OH) 2 , or KOH followed by AFEX pretreatment. We found that 4% alkali was able to de-esterify BSG and DDGS more efficiently than using 2% alkali at both 10 and 20% solids loading. AFEX pretreatment of de-esterified BSG, HFM, and DDGS produced twofold higher glucan conversion than respective untreated biomass. This new discovery can help overcome potential regulatory issues associated with the presence of carboxamides in ammonia-pretreated animal feeds and is expected to benefit several farmers around the world.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Software For Advanced Large-scale Analysis Of Magnetic Confinement For Numerical Design, Engineering & Research (salamander)

As magnetic confinement fusion energy gains traction internationally to enable abundant energy production, designing components for fusion systems is a pressing challenge. During the planned lifetime of a fusion device, components evolve in extreme environments and must withstand large, repeated thermal loads and bombardment by 14 MeV neutrons, plasma ions, and neutral particles (deuterium, tritium, and helium), corrosive conditions, etc. All these physical processes take place simultaneously, interact in intricate ways, and impose important constraints that can affect performance. Experimental data is rare and costly to obtain, making design particularly challenging. Predictive computational frameworks must be an integral part of an accelerated and cost-effective design process by modeling fusion system performance in simulated environments. To better understand component degradation and operational impacts on their performance, the Software for Advanced Large-scale Analysis of MAgnetic confinement for Numerical Design, Engineering & Research (SALAMANDER) is designed as an open-source, fully integrated, multiphysics, multiscale, NQA-1 compliant framework facilitating 3D, high-fidelity fusion system modeling. To that end, SALAMANDER is a MOOSE-based framework, and therefore leverages MOOSE upstream libraries such as PETSc and libMesh to deliver sophisticated finite element, finite volume, and nonlinear solver technology for fusion energy simulations. SALAMANDER couples MOOSE physics module capabilities—such as thermal hydraulics, heat conduction, Navier-Stokes, and thermomechanics—with tritium transport via TMAP8, neutronics via Cardinal, and nascent particle-in-cell capabilities. Direct simulation Monte Carlo methods will be used to address neutral transport near the walls. By coupling all these physics in an integrated application, SALAMANDER will enable high-fidelity modeling of irradiation levels and plasma exposure conditions of plasma facing components and their impact on heat and tritium distributions, as well as the resulting mechanical constraints experienced by the plasma facing components and performance of blanket systems. Furthermore, SALAMANDER will be particularly suited for engineering studies thanks to the stochastic tool module readily available in MOOSE, allowing for extended uncertainty quantification and risk analysis studies. It is also able to use computer-aided design (CAD) meshes to model complex geometries, which is indispensable for fusion systems. SALAMANDER therefore supports design, safety, engineering, and research projects for magnetic confinement fusion systems

Simon, Pierre-Clement [Idaho National Laboratory (↗
DOE OSTI2022

Microbial Tracking-2, a metagenomics analysis of bacteria and fungi onboard the International Space Station

The International Space Station (ISS) is a unique and complex built environment with the ISS surface microbiome originating from crew and cargo or from life support recirculation in an almost entirely closed system. The Microbial Tracking 1 (MT-1) project was the first ISS environmental surface study to report on the metagenome profiles without using whole-genome amplification. The study surveyed the microbial communities from eight surfaces over a 14-month period. The Microbial Tracking 2 (MT-2) project aimed to continue the work of MT-1, sampling an additional four flights from the same locations, over another 14 months. Eight surfaces across the ISS were sampled with sterile wipes and processed upon return to Earth. DNA extracted from the processed samples (and controls) were treated with propidium monoazide (PMA) to detect intact/viable cells or left untreated and to detect the total DNA population (free DNA/compromised cells/intact cells/viable cells). DNA extracted from PMA-treated and untreated samples were analyzed using shotgun metagenomics. Samples were cultured for bacteria and fungi to supplement the above results. Staphylococcus sp. and Malassezia sp. were the most represented bacterial and fungal species, respectively, on the ISS. Overall, the ISS surface microbiome was dominated by organisms associated with the human skin. Multi-dimensional scaling and differential abundance analysis showed significant temporal changes in the microbial population but no spatial differences. The ISS antimicrobial resistance gene profiles were however more stable over time, with no differences over the 5-year span of the MT-1 and MT-2 studies. Twenty-nine antimicrobial resistance genes were detected across all samples, with macrolide/lincosamide/streptogramin resistance being the most widespread. Metagenomic assembled genomes were reconstructed from the dataset, resulting in 82 MAGs. Functional assessment of the collective MAGs showed a propensity for amino acid utilization over carbohydrate metabolism. Co-occurrence analyses showed strong associations between bacterial and fungal genera. Culture analysis showed the microbial load to be on average 3.0 × 10 5 cfu/m 2 . Utilizing various metagenomics analyses and culture methods, we provided a comprehensive analysis of the ISS surface microbiome, showing microbial burden, bacterial and fungal species prevalence, changes in the microbiome, and resistome over time and space, as well as the functional capabilities and microbial interactions of this unique built microbiome. Data from this study may help to inform policies for future space missions to ensure an ISS surface microbiome that promotes astronaut health and spacecraft integrity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Heat Integration Optimization and Dynamic Modeling Investigation for Advancing the Coal-Direct Chemical Looping Process

The purpose of the project is to address the optimization and startup operation of a modular coal direct chemical looping (CDCL) combustion system integrated with a steam cycle for power generation to reduce the risks involved in further scale-up of the technology. The modular reactor design of the CDCL process provides flexibility in the fabrication of the reactor and in its operating capacity (i.e. turndown ratio) at the cost of a more complex heat exchange network (HEN) design and integration. To address the technology gaps and advance the efficiency and economic feasibility of the CDCL technology, the project will perform a detailed and comprehensive analysis of the integration of a modular CDCL reactor system and a steam cycle system under both static and transient conditions via HEN process performance simulations and system dynamic modeling, respectively. The scope of work consists of 1) Experimental and computational studies of the CDCL combustor reactor 2) Comprehensive static (i.e. steady-state) system HEN design analysis in CDCL 550 MWe commercial unit for power generation and 3) Dynamic modeling of site specific design of 10MWe CDCL large pilot plant. The project team has successfully developed and validated a kinetic model for the oxidation of oxygen carriers in the combustor using the unreacted shrinking core model (UCSM). The model is capable of capturing the oxidation kinetics of fully or partially reduced oxygen carrier particles. A computational fluid dynamics (CFD) model is developed to simulate the hydrodynamics, heat transfer, and chemical reaction occurring in the CDCL combustor. The model is developed in MFIX and ANSYS Fluent. Key aspects of CDCL combustor operation, including heat transfer, oxygen carrier oxidation, and the transport of oxygen carrier particles, are simulated using this CFD model. The HEN for a commercial scale 550 MWe CDCL power plant is simulated and optimized using ASPEN Plus. Practical design considerations are incorporated based on industrial experiences. The performance and cost for the commercial CDCL plant is updated based on these analyses. A dynamic model for the 10 MWe CDCL pilot plant is developed in ProTRAX simulation software. The model is based on the pilot plant design developed in project DE-FE0027654 “10 MWe CDCL Large Pilot Plang – Pre-FEED Study” and the steam cycle data obtained from Dover Light & Power plant. The transient behaviors during pilot plant load variation are simulated using the dynamic model.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Plasma Wall Interaction with 3-D Plasma Boundaries

The interaction of the edge plasma and the material surfaces is one of the most critical challenges on the path to harness fusion power as new, fundamental energy source. This challenge typically combines the thrust to reach high density, low temperature (detached) plasmas in front of the divertor target plates as well as understanding the plasma material interaction (PMI) in particular in this regime. The combination of both research thrusts represents an extraordinarily challenging subject encompassing spatial scales spanning nanometers to meters in all states of matter and across a broad energy range. Modeling capabilities, which help to interpret data from nowadays experiments and enable extrapolation to future devices are urgently required. This is in particular true for toroidal magnetic confinement devices with three-dimensional (3D) plasma boundaries. Such plasma boundary geometries occur in tokamaks, when small amplitude magnetic perturbations are used to stabilize the unruly edge plasma or in stellarators, that are inherently 3D plasma confinement devices. In this project, the impact of 3D plasma boundaries on the plasma material interaction (PMI) was assessed. This work focused on plasma boundary conditions, in which high-density conditions at the material surfaces yield mitigation of the otherwise immense heat and particle loads that these materials would see. These so-called high recycling and eventually detached plasma regimes are of great interest for future reactor operation. In the project, key features that are unique to 3D boundaries were explored in comparison to canonically assumed axisymmetric plasma edge situations in tokamaks. In particular, the relevance of the 3D boundary situation in the extrapolation to the plasma boundary solution at ITER, the next step fusion energy experiment under construction as a multi-national, world-wide large-science experiment in southern France, has been explored. The EMC3-EIRENE plasma edge fluid and kinetic neutral transport code has been advanced to cope with the challenging and unprecedented conditions in the ITER boundary plasma including 3D fields that are planned to be used to suppress harmful edge instabilities, the so-called edge localized modes. This is a vital integration challenge for ITER and the results from this grant have provide a leading capability for this assessment. It was shown that the detachment process in a 3D edge solution for ITER follows the recycling regimes that are known from axisymmetric solutions, but that multiple plasma exhaust channels connected to the material surfaces are established which feature individual recycling characteristics. Because these channels touch the material surfaces in the divertor in a 3D geometry, the compatibility with the plasma material interaction (PMI), including erosion and impurity generation has been found to be an important part of the integration challenge. To address this, the fully 3D plasma material interaction code ERO2 has been adapted to these ITER specific geometries and a homogeneous mixing model was implemented, that allows to consider the mixing of Be and Was used at ITER in the PMI modeling. This model enhancement has been used to study non-local migration of Be in the JET ITER like wall configuration and it has been shown that with this model such complex migration processes in ITER relevant plasma shapes and with ITER relevant plasma boundary conditions can be addressed. The combined modeling approach using EMC3-EIRENE as a plasma boundary transport code and the ERO2 specialized PMI model will be an asset for the continued preparations of ITER operation as well as for Fusion Pilot Plant efforts that have emerged in the U.S. during the evolution of this grant. The predictive capability of this numerical tool has been validated at the DIII-D US national fusion facility. Here, dedicated plasma edge diagnostics were implemented to measure the impurity household around a 3D edge plasma during ELM suppression by 3D fields. Dedicated experiments with local material probes using these diagnostics and the state-of-the-art suite of boundary measurements at DIII-D have shown that the 3D perturbation of the plasma edge that is excreted by such 3D control fields yield a perturbation of the plasma boundary flux structure and hence also of the resulting PMI. The 3D boundary plasma is composed out of helical magnetic flux channels that intersect the divertor targets at an angle relative to the main guiding field, i.e., the toroidal magnetic field component of the tokamak. A similar effect has been measured as well on limiter surfaces during the startup campaign at the new stellarator experiment Wendelstein 7-X. These experiments ad initial analysis with the ERO plasma material interaction model, suggested that the place of erosion for a given particle from the surface and its re-deposition can be different in such 3D field geometries yielding potentially a significant level of net-erosion. This is not the case for axisymmetric solutions, where it was shown in the past that the eroded particles are effectively re-deposited into gaps produced by erosion at the same position and hence the net-erosion levels are small. For ITER, the quest to suppress the ELMs and at the same time maintain the integrity of the divertor is an issue, which these fundamental findings will help to resolve. The coupling of this work to the extrapolation in the ITER program has been addressed by both the PI and the lead numerical scientist being ITER Science Fellows in the duration of the contract and forward. A second focus in the exploration of 3D boundary effects on tokamaks and stellarators has been set on the measurement of helium exhaust features with such 3D fields. This is important because He represents the ash of the fusion process and needs to be exhausted. It was shown that 3D field application compatible with suppression of ELMs yields an increase of the helium exhaust performance. The ratio of the effective helium confinement time over the energy confinement time was reduced by almost 50% which demonstrated that the impact of helium accumulation in the plasma core with respect to the confinement of energy to sustain the fusion reaction is significantly improved with such 3D control fields. It was shown that this is the case for tokamaks as well as stellarators. At the Large helical Device in Japan, a similar enhancement of the helium exhaust features when small amplitude additional 3D fields were applied was measured. This is an important additional function of 3D field application and its impact on ITER is presently being studied in combination with investigations of helium exhaust in 3D field geometries of stellarator devices.

3D plasma edge transport↗
DOE OSTI2022

Development of Numerical Model of Metal Foam with PCM for the Estimation of Effective Thermal Conductivity

Global warming due to climate change is a threat to humankind. Nuclear energy is one of the promising solutions to reduce fossil fuel usage. Nuclear energy can handle the base load, compensating for the volatility of renewable energy. If nuclear energy could achieve load following capability, the combination with renewable energy would be more suitable. Thermal energy storage (TES) is one of the options for enabling load following of nuclear reactors. The TES makes it possible to store surplus nuclear thermal energy and release it later as needed. In Idaho National Laboratory (INL), a new concept of latent heat TES integrated with high-temperature heat pipe has been proposed and is under development, which is called Heat pipe-Integrated Thermal Battery (HITB). HITB exchanges thermal energy between the reactor system and TES via heat pipe. The heat transferred to TES medium, made of phase change material (PCM), stores energy as sensible heat and/or latent heat. As PCM typically has poor thermal conductivity, however, various heat transfer enhancement techniques are required to achieve a rapid charging cycle. There are many techniques to enhance the heat transfer ability of TES medium such as disk, fin, and metal foam. Among them, metal foam is an appropriate option to enhance the heat transfer because it maximizes the heat transfer area through metal wicks. Metal foam is a lightweight metal structure that has a high porosity of over 0.9. The typical materials for metal foam are Aluminum, Copper, Nickel, and Silicon Carbide (SiC). Metal foam not only enhances heat transfer via conduction but also increases contact surface area. In the HITB design , the metal foam is being considered as one of the options to enhance the heat transfer of TES medium (PCM) [1]. To predict the enhanced thermal performance of TES, one should properly estimate the effective thermal conductivity of metal foam combined with PCM material or calculate heat transfer in distributed model. There are many experimental works that provides effective thermal conductivity of metal foam with various PCM [2,3]. Also, many theoretical models were developed based on the unit cell model of metal foam [4,5]. With a distributed model, on the other hand, detail heat transfer characteristics between metal foam and PCM material can be analyzed considering the geometry or buoyancy effect. However, due to the complex geometry of metal foam pores, the computational cost for three-dimensional modeling highly increases. Therefore, if metal foam structure can be modeled in simple and repetitive design, the computational cost would decrease Among the various metal foam models [2], lattice model is one of the simple and extendable design. The porosity and pores per inch (PPI) can be characterized by the size and spatial distance of lattice structure. If the three-dimensional metal foam model consists of lattice structure could properly estimate the heat transfer, which is characterized by effective thermal conductivity, it would be a good option to assess the thermal performance of metal foam with PCM. In this study, a three-dimensional numerical model was developed to simulate conductive heat transfer between metal foam and PCM. The three-dimensional lattice structure of square pillars was selected as a basic structure of the metal foam. The calculation result was characterized by the effective thermal conductivity of the whole domain. A sensitivity study was conducted for mesh size, domain size, and PPI to check whether the calculation result gives a converged result or not. Lastly, the effective thermal conductivity from the lattice model was compared with existing experimental data to validate the model result

25 ENERGY STORAGE↗
DOE OSTI2025

Application of a temporal multiscale method for efficient simulation of degradation in PEM Water Electrolysis under dynamic operating conditions

Hydrogen is emerging as a vital energy carrier, driven by the need to reduce carbon emissions. Proton Electrolyte Membrane Water Electrolysis (PEMWE) enables hydrogen production under fluctuating renewable power conditions but requires improved understanding and stability of the anode catalyst layer under dynamic operating conditions, especially with low noble metal loadings. Long-term degradation experiments are both time-consuming and costly; therefore, a systematic, model-aided approach is essential. In the present work, a temporal multiscale method is applied to reduce the computational effort of simulating long-term degradation processes in PEMWE, with an exemplary focus on catalyst dissolution. A mechanistic model incorporating the oxygen evolution reaction, catalyst dissolution, and hydrogen permeation from the cathode to the anode was hypothesized and implemented. In this way, the local periodicity of transport and reaction processes in dynamic PEMWE operation, which influence the gradual degradation of the catalyst layer, is captured. The temporal multiscale method significantly reduces the computational effort of simulation, decreasing processing time from hours to mere minutes. This efficiency gain is attributed to the limited evolution of Slow-Scale variables during each period of time P of the Fast-Scale variables. Consequently, simulation is required only until local periodicity is achieved within each Slow-Scale time step. Hence, the fully resolved dynamic problem is decoupled into these two scales, employing a heterogeneous multiscale technique. The developed approach effectively accelerates parameter estimation and predictive simulations, supporting systematic modeling of PEMWE degradation under dynamic conditions.

08 HYDROGEN↗
DOE OSTI2020

Opportunities to Implement Solutions to Achieve Remedial Action Objectives in Consideration of Stakeholder Interests - 20365

A case study in the implementation of a soils excavation and removal project conducted at a Formerly Utilized Sites Remedial Action Program (FUSRAP) Maywood Superfund Site (FMSS) vicinity property; an active commercial business, in a densely populated area, with significant operational, technical and, logistical constraints that were expected to limit areas that could be remediated. The United States Army Corps of Engineers-led (USACE) team successfully navigated complex overlapping stakeholder interests to achieve a more efficient and complete removal of contaminated soils and debris while minimizing unnecessary excess costs to the Government. This paper centers on FUSRAP activities at the FMSS vicinity property located at 149-151 Maywood Avenue, Maywood, Bergen County, New Jersey. For most of its FUSRAP history, this ∼109,000 square meter (27-acre) property housed a now-demolished ∼26,000 square meter (6.5-acre) warehouse operated by Sears Logistics Services, a unit of the Sears Roebuck Company (Figure 2). Sears ended its property lease and vacated the warehouse in December 2016. Given that long history and for the purposes of this paper, the property will be referred to as the 'Sears property' or simply 'the property.' The Sears property is approximately 109,000 square meters (27-acres) and is currently zoned for commercial use. The property is bound to the north and northwest by 100 West Hunter Avenue (the Stepan Company), to the northeast by 205 Maywood Avenue, to the east by Maywood Avenue, to the south by 23 West Howcroft Road, and to the west by businesses on NJ Route 17 and the NJ Route 17 roadway. Until December 2016, the property housed a warehouse and distribution center operated by Sears Logistical Services. On-site structures were demolished by the property owner in 2017. The warehouse covered the north section of the property along the Stepan Company property line. A railroad spur from the adjacent property now known as the Maywood Interim Storage Site (MISS) ended at the northeast corner of the warehouse. Wetlands were located east of the warehouse; the rest of the property was covered with paved parking lots and grassed areas. During remediation at the property, opportunities frequently arose where the project team was able to coordinate effectively with stakeholders to sequence remediation activities to facilitate removal of otherwise inaccessible soils and identify opportunities for materials reuse when supported by residual radiological and chemical levels. Some specific opportunities include: - remediating individual truck loading dock bays to maintain tenant operations; - working along a busy highway and in a utility corridor containing a 30-inch high pressure gas main; - remediating Lodi Brook and associated wetlands requiring bypass pumping and other diversionary structures to maintain local community stormwater drainage; - protecting during remediation and supporting access to facilitate tenant/owner maintenance of critical fire protection and water supply system service lines buried in contaminated soils and necessary for safe warehouse operations; and - coordinating with stakeholders to ensure non-radiological contaminants of concern for the site (unaffiliated with FUSRAP) were addressed by the responsible party in a manner that maximized benefit to all parties while supporting an efficient overall site remediation program. Once the property was vacant and the warehouse structure and radiologically non-impacted above-grade structures were demolished, the project identified an opportunity to significantly reduce the volume of waste associated with the foundation of the former warehouse, a foundation suspected of being partially constructed in radiologically contaminated soils. The project developed and implemented supplemental radiological verification survey and sampling strategies based on radiological cross-contamination risk potential with process flow-charts and screening-level based decision points; a program that classified saw-cut sections of concrete based on observed residual surface radioactivity conditions using a combination of gamma sensitive sodium-iodide scans and beta sensitive Geiger-Muller direct measurements. The proposed approach was reviewed with stakeholders with feedback, including consideration of applicable State of New Jersey Site Remediation Program criteria and guidance before implementation. Once classified, additional sampling was performed at frequencies driven by screening. The sampling methods, stockpile sampling frequencies, criteria and, approach to data evaluation were developed in consideration of existing site cleanup standards, regional background ranges, State of New Jersey radiological remediation program guidance, and specific stakeholder input With the property remediation and survey efforts nearly completed, it is relevant to examine retrospectively the objectives, assumptions and limitations in the remedial design (i.e., what was planned) versus what was able to be accomplished through effective teaming. Benefits to other environmental remediation site programs include better understanding of how to work effectively with stakeholders to achieve win-win outcomes, and approaches to site remediation, waste minimization and materials reuse that were successful in their overall outcomes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗