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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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DOE SMART Mobility Urban Science Efforts are helping use/develop key data sets, models, and roles for DOE in engaging across seven Smart City Finalists as well as for ensuring useful/useable insights. Austin, Texas, was targeted for analyses of opportunity (model and data maturity). Other Urban Science/broader SMART initiatives were also helped by this research.
This document describes a standard library plant controller model to interface with the grid-forming hybrid control inverter-based resource (IBR) model. The initial version of model specification was jointly developed by Pacific Northwest National Laboratory (PNNL), Tesla Energy, and EPRI, and it was revised multiple times later to incorporate suggestions from WECC MVS members. Tesla Energy provided main control algorithms to support the development of this model specification. This standard library model is developed to help the utility industry better understand the GFM technology. The model could be used to represent equipment for long-term planning studies where vendor-specific models are not available. As equipment matures and improves, standard library models will be updated to capture the new functionalities of GFMs. It is not intended that these models will always remain representative of all future GFM technologies.
This document describes a standard library grid-forming (GFM) hybrid control inverter-based resource (IBR) model. The GFM hybrid control approach implements both a typical GFM control and a typical grid-following (GFL) control inside one single inverter simultaneously, so that it can take advantage of both methods without comprising the benefits of a typical GFM. The initial version of model specification was jointly developed by Pacific Northwest National Laboratory (PNNL), Tesla Energy, and EPRI, and it was revised multiple times later to incorporate suggestions from WECC MVS members. Tesla Energy provided main control blocks to support the development of this model specification. This standard library model is developed to help the utility industry better understand the GFM technology. The model could be used to represent equipment for long-term planning studies where vendor-specific models are not available. As equipment matures and improves, standard library models will be updated to capture the new functionalities of GFMs. It is not intended that these models will always remain representative of all future GFM technologies.
Engineered monoclonal antibodies have proven to be highly effective therapeutics in recent viral outbreaks. However, despite technical advancements, an ability to rapidly adapt or increase antibody affinity and by extension, therapeutic efficacy, has yet to be fully realized. We endeavored to stand-up such a pipeline using molecular modeling combined with experimental library screening to increase the affinity of F5, a monoclonal antibody with potent neutralizing activity against Venezuelan Equine Encephalitis Virus (VEEV), to recombinant VEEV (IAB) E1E2 antigen. We modeled the F5/E1E2 binding interface and generated predictions for mutations to improve binding using a Rosetta-based approach and dTERMen, an informatics approach. The modeling was complicated by the fact that a high-resolution structure of F5 is not available and the H3 loop of F5 exceeds the length for which current modeling approaches can determine a unique structure. A subset of the predicted mutations from both methods were incorporated into a phage display library of scFvs. This library and a library generated by error-prone PCR were screened for binding affinity to the recombinant antigen. Results from the screens identified favorable mutations which were incorporated into 12 human-IgG1 variants. The best variant, containing eight mutations, improved KD from 0.63 nM (parental) to 0.01 nM. While this did not improve neutralization or therapeutic potency of F5 against IAB, it did increase cross-reactivity to other closely related VEEV epizootic and enzootic strains, demonstrating the potential of this method to rapidly adapt existing therapeutics to emerging viral strains.
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To maintain immunological balance the organism has to be tolerant to self while remaining competent to mount an effective immune response against third-party antigens. An important mechanism of this immune regulation involves the action of regulatory T-cell (Tregs). In this mini-review, we discuss some of the known and proposed mechanisms by which Tregs exert their influence in the context of immune regulation, and the contribution of mathematical modeling for these mechanistic studies. These models explore the mechanisms of action of regulatory T cells, and include hypotheses of multiple signals, delivered through simultaneous antigen-presenting cell (APC) conjugation; interaction of feedback loops between APC, Tregs, and effector cells; or production of specific cytokines that act on effector cells. As the field matures, and competing models are winnowed out, it is likely that we will be able to quantify how tolerance-inducing strategies, such as CD4-blockade, affect T-cell dynamics and what mechanisms explain the observed behavior of T-cell based tolerance.
We apply AI-assisted large language model (LLM) capabilities of GPT-3 targeting high-performance computing (HPC) kernels for (i) code generation, and (ii) auto-parallelization of serial code in C ++, Fortran, Python and Julia. Our scope includes the following fundamental numerical kernels: AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG, and language/programming models: (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). Kernel implementations are generated using GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code given simple + + prompt variants. To quantify and compare the generated results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. For auto-parallelization, we use ChatGPT interactively giving simple prompts as in a dialogue with another human including simple “prompt engineering” follow ups. Results suggest that correct outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general-purpose Python can benefit from adding language keywords, while Julia prompts perform acceptably well for its Threads and CUDA.jl programming models. Finally, we expect to provide an initial quantifiable point of reference for code generation in each programming model using a state-of-the-art LLM. Overall, understanding the convergence of LLMs, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.
This study uses modeling and simulation approaches to investigate the impacts on injectivity of trace amounts of mercury (Hg) in a carbon dioxide (CO 2 ) stream injected for geologic carbon sequestration in a sandstone reservoir at ~2.5 km depth. At the range of Hg concentrations expected (7-190 ppbV, or ~ 0.06-1.6 mg/std.m 3 CO 2 ), the total volumetric plugging that could occur due to complete condensation of Hg, or due to complete precipitation of Hg as cinnabar, results in a very small porosity change. In addition, Hg concentration much higher than the concentrations considered here would be required for Hg condensation to even occur. Concentration of aqueous Hg by water evaporation into CO 2 is also unlikely because the higher volatility of Hg relative to H 2 O at reservoir conditions prevents the Hg concentration from increasing in groundwater as dry CO 2 sweeps through, volatilizing both H 2 O and Hg. Using a model-derived aqueous solution to represent the formation water, batch reactive geochemical modeling show that the reaction of the formation water with the CO 2 -Hg mixture causes the pH to drop to about 4.7 and then become buffered near 5.2 upon reaction with the sediments, with a negligible net volume change from mineral dissolution and precipitation. Cinnabar (HgS(s)) is found to be thermodynamically stable as soon as the Hg-bearing CO 2 reacts with the formation water which contains small amounts of dissolved sulfide. Liquid mercury (Hg(l)) is not found to be thermodynamically stable at any point during the simulation. Two-dimensional radial reactive transport simulations of CO 2 injection at a rate of 14.8 kg/s into a 400 m-thick formation at isothermal conditions of 106°C and average pressure near 215 bar, with varying amounts of Hg and H 2 S trace gases, show generally that porosity changes only by about ±0.05% (absolute, i.e., new porosity = initial porosity ±0.0005) with Hg predicted to readily precipitate from the CO 2 as cinnabar in a zone mostly matching the single-phase CO 2 plume. The precipitation of minerals other than cinnabar, however, dominates the evolution of porosity. Main reactions include the replacement of primarily Fe-chlorite by siderite, of calcite by dolomite, and of K-feldspar by muscovite. Chalcedony is also predicted to precipitate from the dissolution of feldspars and quartz. Although the range of predicted porosity change is quite small, the amount of dissolution and precipitation predicted for these individual minerals is not negligible. These reactive transport simulations assume that Hg gas behaves ideally. To examine effects of non-ideality on these simulations, approximate calculations of the fugacity coefficient of Hg in CO 2 were made. Results suggest that Hg condensation could be significantly overestimated when assuming ideal gas behavior, making our simulation results conservative with respect to impacts on injectivity. The effect of pressure on Henry’s constant for Hg is estimated to yield Hg solubilities about 10% lower than when this effect is not considered, a change that is considered too small to affect the conclusions of this report. Although all results in this study are based on relatively mature data and modeling approaches, in the absence of experimental data and more detailed site-specific information, it is not possible to fully validate the results and conclusions.
In ovoid-shaped, Gram-positive bacteria, MapZ guides FtsZ-ring positioning at cell equators. The cell wall of the ovococcus Streptococcus mutans contains peptidoglycan decorated with serotype c carbohydrates (SCCs). In the present study, we identify the major cell separation autolysin AtlA as an SCC-binding protein. AtlA binding to SCC is attenuated by the glycerol phosphate (GroP) modification. Using fluorescently labeled AtlA constructs, we mapped SCC distribution on the streptococcal surface, revealing enrichment of GroP-deficient immature SCCs at the cell poles and equators. The immature SCCs co-localize with MapZ at the equatorial rings throughout the cell cycle. In GroP-deficient mutants, AtlA is mislocalized, resulting in dysregulated cellular autolysis. These mutants display morphological abnormalities associated with MapZ mislocalization, leading to FtsZ-ring misplacement. Altogether, our data support a model in which maturation of a cell wall polysaccharide provides the molecular cues for the recruitment of cell division machinery, ensuring proper daughter cell separation and FtsZ-ring positioning.
The team of Southwest Research Institute® (SwRI®), ITEA, Electric Power Research Institute, Inc. (EPRI), GE Global Research (GE), Jacobs Engineering (Jacobs), and Peter Reineck Associates (PRA) are advancing Flameless Pressurized Oxy-Combustion (FPO), a novel coal technology. This effort seeks to complete the preliminary engineering and planning of a 50-MWth Pilot Plant that produces electricity and steam for district heating. The technology, pioneered by ITEA at the 5-MWth scale, must be brought to a higher technology readiness level (TRL) to be viable at the commercial scale. This project builds upon extensive evaluation of the techno-economic performance of the FPO technology already performed by ITEA. This includes system improvements, such as the addition of a turbo-expander to the flue gas stream. Some of the performance-enhancing components are not as well defined as others. The primary goal of this project was to bring all of the core cycle components to the same level of design maturity. Extensive cycle modeling and evaluation explored various configurations of the process. Different coals, operating conditions, and heat recovery devices were considered and modeled using Aspen Plus. The results of the cycle modeling informed the pilot plant configuration and the planned configuration at the commercial scale. The system pressurization is maintained in the flue gas clean-up and water removal. This allows for efficient and cost-effective carbon dioxide compression and sequestration package. Once the cycle was optimized, preliminary drawings, layouts, and plans defined the pilot facility. Process flow diagrams (PFD) were used to describe the pilot configuration in greater detail. A heat and mass balance with stream data was created. A master equipment list specified the operating conditions for major pieces of equipment within the pilot using this heat and mass balance. A detailed cost estimate for the planned configuration was completed with an Association for the Advancement of Cost Engineering (AACE) Class IV level of cost analysis. A site selection effort evaluated a variety of potential candidate sites. The selection effort focused on three sites for an in-depth evaluation of the merits and viability of hosting a pilot demonstration. The ability of the host site to support the project with cost sharing was also assessed. The selection process chose the University of Wyoming (UW) as the host site, and cost estimates for the pilot capital estimate were made using local data. A preliminary test plan and operation plan, which creates figures of merit, control, and instrumentation was produced. An effort that outlines methods of pilot cost reduction was completed near the end of the project. A techno-economic assessment (TEA) evaluated the FPO technology at the commercial scale in comparison to the NETL baseline cases. The reference plants were used in combination with proprietary equipment estimates to build a plant capital cost and cost of electricity evaluation. FPO performed better than the sub-bituminous post-combustion capture cases. Further preliminary estimates of improvements to the FPO cycle show even further gains when compared to conventional carbon capture methods.
Eliciting antibodies that are cross reactive with surface proteins of diverse strains of highly mutable pathogens (e.g., HIV, influenza) could be key for developing effective universal vaccines. Mutations in the framework regions of such broadly neutralizing antibodies (bnAbs) have been reported to play a role in determining their properties. We used molecular dynamics simulations and models of affinity maturation to study specific bnAbs against HIV. Our results suggest that there are different classes of evolutionary lineages for the bnAbs. If germline B cells that initiate affinity maturation have high affinity for the conserved residues of the targeted epitope, framework mutations increase antibody rigidity as affinity maturation progresses to evolve bnAbs. If the germline B cells exhibit weak/moderate affinity for conserved residues, an initial increase in flexibility via framework mutations may be required for the evolution of bnAbs. Subsequent mutations that increase rigidity result in highly potent bnAbs. Implications of our results for immunogen design are discussed.
In the last three decades, there has been an exponential growth in the area of information technology providing the information processing needs of data-driven businesses in government, science, and private industry in the form of capturing, staging, integrating, conveying, analyzing, and transferring data that will help knowledge workers and decision makers make sound business decisions. Data integration across enterprise warehouses is one of the most challenging steps in the big data analytics strategy. Several levels of data integration have been identified across enterprise warehouses: data accessibility, common data platform, and consolidated data model. Each level of integration has its own set of complexities that requires a certain amount of time, budget, and resources to implement. Such levels of integration are designed to address the technical challenges inherent in consolidating the disparate data sources. In this paper, we present a methodology based on industry best practices to measure the readiness of an organization and its data sets against the different levels of data integration. We introduce a new Integration Level Model (ILM) tool, which is used for quantifying an organization and data system s readiness to share data at a certain level of data integration. It is based largely on the established and accepted framework provided in the Data Management Association (DAMA-DMBOK). It comprises several key data management functions and supporting activities, together with several environmental elements that describe and apply to each function. The proposed model scores the maturity of a system s data governance processes and provides a pragmatic methodology for evaluating integration risks. The higher the computed scores, the better managed the source data system and the greater the likelihood that the data system can be brought in at a higher level of integration.
High-fidelity aerodynamic analysis has been demonstrated for mean performance and unsteady dynamics in a sCO2 compressor designed by Hanwha Power Systems Americas for a 10 MWe Concentrating Solar Power plant. Simulations were performed with CRUNCH CFD® software tool that was matured to accurately model near critical real fluid effects in sCO2. Pre-test predictions for mean performance were validated with test data collected later. Performance predictions were accurate and captured sensitivity of the efficiency to inlet temperature of CO2 as well as steep drop-off at high flow rates due to condensation in the inlet throat. Detailed analysis was performed to understand the source of these performance losses at near critical conditions. Unsteady dynamic effects in the compressor at off-design conditions were also identified and quantified. In particular a system wide “condensation surge” condition was detected at high flow coefficients that results in large amplitude pulsations with accompanying mass flow fluctuations at low frequencies and has potential to cause damage in closed loop systems.
The primary treatment of the tank waste at the DOE Hanford site will be done in the Waste Treatment and Immobilization Plant (WTP) that is currently under construction. The baseline plan for this facility is to treat the waste, splitting it into High Level Waste (HLW) and Low Activity Waste (LAW). Both waste streams are then separately vitrified as glass and poured into canisters for disposition. The LAW glass will be disposed onsite in the Integrated Disposal Facility (IDF). There are currently no plans to treat the waste to remove technetium, so its disposition path is the LAW glass. Due to the water solubility properties of pertechnetate and long half-life of 99 Tc, effective management of 99 Tc is important to the overall success of the Hanford River Protection Project mission. To achieve the full target WTP throughput, additional LAW immobilization capacity is needed, and options are being explored to immobilize the supplemental LAW portion of the tank waste. Removal of 99 Tc, followed by off-site disposal, would eliminate a key risk contributor for the IDF Performance Assessment (PA) for supplemental waste forms, and has potential to reduce treatment and disposal costs. Washington River Protection Solutions (WRPS) is developing some conceptual flow sheets for supplemental LAW treatment and disposal that could benefit from technetium removal. One of these flowsheets will specifically examine removing 99 Tc from the LAW feed stream to supplemental immobilization. To enable an informed decision regarding the viability of technetium removal, further maturation of available technologies is being performed. This report contains results of experimental ion exchange distribution coefficient testing and computer modeling using the resin SuperLig ® 639 a to selectively remove perrhenate from high ionic strength simulated LAW. It is advantageous to operate at higher concentration in order to treat the waste stream without dilution and to minimize the volume of the final wasteform. This work examined the impact of high ionic strength, high density, and high viscosity if higher concentration LAW feed solution is used. Perrhenate (ReO 4 - ) has been shown to be a good nonradioactive surrogate for pertechnetate in laboratory testing for this ion exchange resin, and the performance bias is well established. Equilibrium contact testing with 7.8 M [Na + ] average simulant concentrations indicated that the SuperLig ® 639 resin average perrhenate distribution coefficient was 368 mL/g at a 100:1 phase ratio. Although this indicates good performance at high ionic strength, an equilibrium test cannot examine the impact of liquid viscosity, which impacts the diffusivity of ions and therefore the loading kinetics. To get an understanding of the effect of diffusivity, modeling was performed, which will be followed up with column tests in the future.
Many cities across the United States seek to understand the maturity of data and models that are available to help manage challenges, opportunities, and uncertainties associated with the shifts in technologies, human behaviors and sustainable urban mobility strategies. One key question identified for smart city action planning includes how to best shape continuous improvements for urban populations at the intersection of mobility, energy, and quality of life? With the emerging megatrends of urbanization (more than 70% of world population in cities by 2050), on-demand shared mobility, vehicle electrification, and automated vehicles, initial 'urban science' studies to date have demonstrated the potential and need for maturing the related data and model ecosystems and on-going performance measurement across multiple urban system goals: e.g., from more mobility, clean and efficient energy use, accessibility and safety to less air pollution, traffic, and resource-intensive urban sprawl. To build on emerging literature and understand city responses to disruptive change, this initial study engages researchers and practitioners across four smart city finalists (Columbus, Denver, Austin and Portland) that competed in the U.S. Department of Transportation (DOT) Smart City Challenge. The initial results emphasize the need for a suite of datasets and diverse analytical approaches that support U.S. Department of Energy (DOE) relevant research with cities. Considering desirable energy and mobility outcomes as a first step to advancing smart city solutions strategies, we systematically review approaches of and shortcomings in four U.S. cities, and suggest improvements in three areas: measurement, modeling effectiveness of new mobility technologies, and data-driven governance.
This report is prepared to fulfill a Level 2 milestone for CASL on “deliver and document RIA fuel performance modeling using Bison fuel performance code.” The work performed is focused on modeling the full length commercial fuel rod response under a design basis Reactivity Initiated Accident (RIA), in particular, a hypothetical Control Rod Ejection Accident (CREA) in a Pressurized Water Reactor (PWR). Fuel rods with different burnups, 0 (fresh fuel), 20, 40, and 60 GWd/tU have been modeled with a reactivity worth insertion of $1.24 at Hot Zero Power (HZP) condition. Bison failure modeling method, and a brief summary of validations on selected RIA cases from CABRI and NSRR testing facilities are also described. The work performed has demonstrated the successful application of Bison code in the modeling of thermal and mechanical responses in RIAs for PWRs. In particular, Bison code has a more mature capability in the modeling of the frictional contact between pellet and cladding of the high burnup fuels, which is critical for modeling the Pellet Clad Mechanical Interaction (PCMI). The modeling of RIA using Bison code shows fuels in PWR environment could have different responses than in the simulated RIA tests, and results indicate that a transition from PCMI to Departure from Nucleate Boiling (DNB) could happen at relatively lower enthalpies: a better heat transfer from the fuel to coolant could increase cladding temperature and ductility, but at the same time also reduces the margin to DNB, which could cause high temperature oxidation and ballooning type of failures. The precise determination of the transition into DNB may rely on a more accurate input of the power histories in the simulated RIAs from VERA, the core simulator of CASL. The limiting conditions in PWRs could be quite different than those tests with non-typical testing conditions, and the improvement of the modeling of thermal responses, such as, clad coolant heat transfer, gap heat transfer, clad thermal inertia, and radial power profiles could be important considerations of the RIAs. In modeling the fuel responses in a fast transient, a number of variables could affect the initial burnup states, and some material models, e.g., fuel mechanical models, fission gas release, and corrosion models, and parameters can affect modeling results as well. Those uncertainties and advanced modeling capabilities need to be investigated in the future study of RIAs.
The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project demonstrate significant advances in all six research areas. The major conclusions are that statically-adaptive variable-resolution modeling is currently becoming mature in the climate sciences, and that AMR holds outstanding promise for future-generation weather and climate models on high-performance computing architectures.