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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5

Cost-Reduction Roadmap for Residential Solar Photovoltaics (PV), 2017-2030

The installed cost of solar photovoltaics (PV) has fallen rapidly in recent years and is expected to continue declining in the future. In this report, we focus on the potential for continued PV cost reductions in the residential market. From 2010 to 2017, the levelized cost of energy (LCOE) for residential PV declined from 52 cents per kilowatt-hour (cents/kWh) to 16 cents/kWh (Fu et al. 2017). The U.S. Department of Energy's (DOE's) Solar Energy Technologies Office (SETO) recently set new LCOE targets for 2030, including a target of 5 cents/kWh for residential PV. We present a roadmap for achieving the SETO 2030 residential PV target. Because the 2030 target likely will not be achieved under business-as-usual trends (NREL 2017), we examine two key market segments that demonstrate significant opportunities for cost savings and market growth: installing PV at the time of roof replacement and installing PV as part of the new home construction process. Within both market segments, we identify four key cost-reduction opportunities: market maturation, business model integration, product innovation, and economies of scale. To assess the potential impact of these cost reductions, we compare modeled residential PV system prices in 2030 to the National Renewable Energy Laboratory's (NREL's) quarter one 2017 (Q1 2017) residential PV system price benchmark (Fu et al. 2017). We use a bottom-up accounting framework to model all component and project-development costs incurred when installing a PV system. The result is a granular accounting for 11 direct and indirect costs associated with installing a residential PV system in 2030. All four modeled pathways demonstrate significant installed-system price savings over the Q1 2017 benchmark, with the visionary pathways yielding the greatest price benefits. The largest modeled cost savings are in the supply chain, sales and marketing, overhead, and installation labor cost categories. When we translate these installed-system costs into LCOE, we find that the less-aggressive pathways achieve significant cost reductions, but may not achieve the 2030 LCOE target. On the other hand, both visionary pathways could get very close to (for roof replacement) or achieve (for new construction) the 2030 target. Our analysis has two key implications. First, because installed-system soft cost reductions account for about 65 percent of the LCOE reductions in 2030 for both visionary pathways, residential PV stakeholders may need to emphasize these soft cost reductions to achieve the 2030 target. Second, capturing these savings will likely require considerable innovation in the technologies and business practices employed by the PV industry.

14 SOLAR ENERGY↗

Ex Situ Catalytic Fast Pyrolysis of Lignocellulosic Biomass to Hydrocarbon Fuels: 2020 State of Technology

Biomass catalytic fast pyrolysis (CFP) research was funded by the Bioenergy Technologies Office (BETO) of the U.S. Department of Energy (DOE) to enable technical breakthroughs to help reduce the cost of conversion of biomass to liquid hydrocarbon fuels. The key goals were to achieve a mature plant modeled Minimum Fuel Selling Price of $3/GGE, with greater than 60% greenhouse gas (GHG) reduction over petroleum derived gasoline by 2022. Experimental results at NREL and PNNL, along with lifecycle analysis by ANL show that we achieved these goals based on performance at the bench scale. A Pt/TiO2 catalyst was used in a fixed bed reactor for upgrading pyrolysis vapors from an upstream fast pyrolysis reactor (ex-situ configuration) to produce CFP oil with 16.5% oxygen content. Subsequent co-hydrotreating of 10 vol% of CFP oil with 90 vol% straight run diesel (SRD) at the bench scale yielded greater than 95% carbon efficiency for the CFP oil portion of the feed. Light oxygenated coproducts were recovered from the off gases from the CFP process via adsorption and subsequent desorption. Aspen Plus modeling of purification of the desorbed stream using the UNIFAC property method showed that acetone and methyl-ethyl-ketone can be purified to chemicals grade and sold as coproducts to benefit the economics and reduce GHG emissions attributed to the fuel product. Some of the key risks and uncertainties associated with this process, and potential future work are mentioned in this report.

09 BIOMASS FUELS↗

Particle Energization via Tearing Instability with Global Self-Organization Constraints

The presentation reviews how tearing magnetic reconnection leads to powerful ion energization in reversed field pinch (RFP) plasmas. A mature MHD model for tearing instability has been developed that captures key nonlinear dynamics from the global to intermediate spatial scales. A turbulent cascade is also present that extends to at least the ion gyroradius scale, within which important particle energization mechanisms are anticipated. In summary, Ion heating and acceleration associated with magnetic reconnection from tearing instability is a powerful process in the RFP laboratory plasma (gyro-resonant and stochastic processes are likely candidates to support the observed rapid heating and other features, reconnection-driven electron heating appears weaker or even absent, energetic tail formation for ions and electrons). Global self-organization strongly impacts particle energization (tearing interactions that span to core to edge, global magnetic flux change produces a larger electric field and runaway, correlations in electric and magnetic field fluctuations needed for dynamo feedback, impact of transport processes (which can be quite different for ions and electrons), inhomogeneity on the system scale, e.g., strong edge gradients).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cogeneration of electricity and liquid fuels using an HTGR as the heat source - 18698

A high temperature gas-cooled reactor (HTGR) used for cogeneration of electricity and liquid transportation fuels was modeled. The model consisted of two HTGRs, each transferring heat through: - a steam generator (SG) to a supercritical Rankine Cycle (SCRC) producing electricity, and - an intermediate heat exchanger (IHX) to a biomass gasifier and Fischer-Tropsch (FT) process producing gasoline, jet fuel, diesel, liquefied petroleum gas (LPG) and/or naphtha. The individual systems and components in the cogeneration model are mature technologies and commercially available, because minimizing the need for additional innovation increases the overall probability of success for a new and unique hybrid system. Technical evaluations of cogeneration on the island of Oahu in the State of Hawaii, using eucalyptus and sugarcane as the biomass feedstock, indicated that high thermal efficiency was achievable and that the concept is technically viable. Economic evaluations of cogeneration, based on construction and finance costs and current electricity and liquid fuel prices, indicated that the cogeneration plant is economically viable. Additional analyses quantified the potential number of jobs created in the state and the reduction in carbon emissions. Further analyses indicated that cogeneration would significantly enhance Hawaii's energy security. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Cybersecurity Education, Training, and WFD

Availability of skilled workforce in sufficient number is one of the most often cited barriers to improving cybersecurity. INL's research has determined that this is not a cybersecurity problem but rather a strategic business imperative; in response INL created the Cyber Competency Health and Maturity Progression Model (Cyber-CHAMP) to help organizations learn the realities of their cyber workforce and their development needs. The presentation starts with an overview of Cyber-CHAMP as a unifying theme for workforce development and then provides brief introductions to selected DHS (ICS cybersecurity hands-on training), DOE (CyberStrike, OT Defender Fellowship, Liberty Eclipse), and INL (Cybercore Summer Camp, University Collaboration Laboratory) programs. Cyber-Informed Engineering discussion concludes the presentation, with an update on activities conducted by the CIE Education Working Group to further the second pillar of the National CIE Strategy, Education.

42 ENGINEERING↗

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported programming models, including (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). We use the GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code as of April 2023 to generate a vast amount of implementations given simple + + prompt variants. To quantify and compare the results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. Results suggest that the OpenAI Codex 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 code keywords, while Julia prompts perform acceptably well for its mature programming models (e.g., Threads and CUDA.jl). We expect for these benchmarks to provide a point of reference for each programming model's community. Overall, understanding the convergence of large language models, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.

Godoy, William↗

A Metallic Fuel Performance Benchmark Problem Based on the IFR-1 Experiment

Metallic nuclear fuels are an active area of research and development for use in advanced reactors. Robust and accurate metallic fuel performance models are necessary for the design, safety analysis, and licensing of such reactors. However, metallic fuel performance models are not as mature as ceramic fuel performance models and require additional development. In order to better gauge the accuracy of existing models, identify high-priority models for development, and quantify the improvements made by future model development, ORNL has developed a benchmark problem based on the IFR-1 experiment. This work gathers all relevant information on the IFR-1 experiment and uses it to develop the benchmark problem. It simulates the problem using the fuel performance code BISON and compare the results to post-irradiation examination data from the experiment. Then a sensitivity analysis is performed on the BISON model to determine the benchmark problem’s sensitivity to uncertainty in the input parameters. The results suggest that BISON’s mechanical models require additional development. Plastic deformation is under-predicted in the cladding and axial swelling is over-predicted in the fuel. These problems may be related. Additionally, there is a bias in the temperature which may be a result of uncertainty in the input parameters rather than an issue with the fuel performance models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations

The association between spectral reflectance and canopy processes remains challenging for quantifying large-scale canopy phenological cycles in tropical forests. In this paper, we used a tower-mounted hyperspectral camera in an eastern Amazon forest to assess how canopy spectral signals of three species are linked with phenological processes in the 2012 dry season. We explored different approaches to disentangle the spectral components of canopy phenology processes and analyze their variations over time using 17 images acquired by the camera. The methods included linear spectral mixture analysis (SMA); principal component analysis (PCA); continuum removal (CR); and first-order derivative analysis. In addition, three vegetation indices potentially sensitive to leaf flushing, leaf loss and leaf area index (LAI) were calculated: the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI) and the entitled Green-Red Normalized Difference (GRND) index. We inspected also the consistency of the camera observations using Moderate Resolution Imaging Spectroradiometer (MODIS) and available phenological data on new leaf production and LAI of young, mature and old leaves simulated by a leaf demography-ontogeny model. The results showed a diversity of phenological responses during the 2012 dry season with related changes in canopy structure and greenness values. Because of the differences in timing and intensity of leaf flushing and leaf shedding, Erisma uncinatum, Manilkara huberi and Chamaecrista xinguensis presented different green vegetation (GV) and non-photosynthetic vegetation (NPV) SMA fractions; distinct PCA scores; changes in depth, width and area of the 681-nm chlorophyll absorption band; and variations over time in the EVI, GRND and NDVI. At the end of dry season, GV increased for Erisma uncinatum, while NPV increased for Chamaecrista xinguensis. For Manilkara huberi, the NPV first increased in the beginning of August and then decreased toward September with new foliage. Variations in red-edge position were not statistically significant between the species and across dates at the 95% confidence level. The camera data were affected by view-illumination effects, which reduced the SMA shade fraction over time. When MODIS data were corrected for these effects using the Multi-Angle Implementation of Atmospheric Correction Algorithm (MAIAC), we observed an EVI increase toward September that closely tracked the modeled LAI of mature leaves (3–5 months). Compared to the EVI, the GRND was a better indicator of leaf flushing because the modeled production of new leaves peaked in August and then declined in September following the GRND closely. Finally, while the EVI was more related to changes in mature leaf area, the GRND was more associated with new leaf flushing.

54 ENVIRONMENTAL SCIENCES↗

Individual Load Model Parameter Estimation in Distribution Systems Using Load Switching Events

There currently exists a mature literature on modeling the aggregate load of a distribution feeder by making use of measurements at its feeder-head at substation. The primary application of such feeder-aggregated load models is in sub-transmission or transmission system analysis. However, there is a growing need in practice also to model each individual load across the feeder. If available, such individual load models have applications in power distribution system analysis, e.g., to better integrate distributed energy resources or to improve power quality and reliability. Motivated by this observation, in this paper, we propose a new method for individual load modeling in power distribution systems. It works by using the measurements only at the feeder-head. It takes an innovative approach to analyzing the load switching events across the distribution feeder itself, instead of or in addition to relying on upstream voltage events that are commonly used in feeder-aggregated load modeling. By tracking the downstream load switching events, the proposed method can make a robust estimation of the ZIP load model parameters for all individual loads. The proposed method is examined on small illustrative test-feeders as well as the IEEE 33-bus test system under various operating scenarios. The adverse impact of errors in measurements and system parameters are also investigated on the performance of the developed load modeling method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Factors circulating in the blood of type 2 diabetes mellitus patients affect osteoblast maturation – Description of a novel in vitro model

Type 2 diabetes mellitus (T2DM) is one of the most frequent metabolic disorders in industrialized countries. Among other complications, T2DM patients have an increased fracture risk and delayed fracture healing. We have demonstrated that supraphysiological glucose and insulin levels inhibit primary human osteoblasts' maturation. We aimed at developing a more physiologically relevant in vitro model to analyze T2DM-mediated osteoblast changes. Therefore, SCP-1-immortalized pre-osteoblasts were differentiated with T2DM or control (non-obese and obese) sera. Between both control groups, no significant changes were observed. Proliferation was significantly increased (1.69-fold), while AP activity and matrix mineralization was significantly reduced in the T2DM group. Expression levels of osteogenic marker genes and transcription factors were altered, e.g. down-regulation of RUNX2 and SP-7 or up-regulation of STAT1, in the T2DM group. Active TGF-β levels were significantly increased (1.46-fold) in T2DM patients' sera. SCP-1 cells treated with these sera showed significantly increased TGF-β signaling (2.47-fold). Signaling inhibition effectively restored osteoblast maturation in the T2DM group. Summarizing our data, SCP-1 cells differentiated in the presence of T2DM patients' serum exhibit reduced osteoblast function. Thus, this model has a high physiological impact, as it can identify circulating factors in T2DM patients' blood that may affect bone function, e.g. TGF-β. - Highlights: • We present here a physiologically relevant in vitro model for diabetic osteopathy. • Blood of T2DM patients contains factors that affect osteoblasts' function. • The model developed here can be used to identify these factors, e.g. TGF-β. • Blocking TGF-β signaling partly rescues the osteoblasts' function in the T2DM group. • The model is useful to demonstrate the role of single factors in diabetic osteopathy.

60 APPLIED LIFE SCIENCES↗

Virtual Synchronous Machine Grid-Forming Inverter Model Specification (REGFM_B1)

This report describes a generic virtual synchronous machine (VSM) grid-forming inverter (GFM) model - REGFM_B1. The initial model specification was proposed by Pacific Northwest National Laboratory (PNNL), General Electric (GE), and Electric Power Research Institute (EPRI). Siemens Gamesa Renewable Energy (SGRE) also provided inputs to the specification. The model specification has been revised multiple times based on the discussions between all the contributors listed in this report. This work was funded by the Universal Interoperability for Grid-Forming Inverters (UNIFI) Consortium. This generic model is developed to help the utility industry understand the concept of VSM GFMs. The model could be used to represent equipment for long-term planning studies where vendor-specific models are not available. As equipment mature and improve, generic 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.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Recent Updates to the System Advisor Model (SAM)

The System Advisor Model (SAM) is a mature suite of techno-economic models for many renewable energy technologies that can be downloaded for free as a desktop application or software development kit. SAM is used for system-level modeling, including generating performance pro the release of the code as an open source project on GitHub. Other additions that will be covered include the ability to download data directly into SAM from the National Solar Radiation Database (NSRDB) and up- dates to a user-interface macro that assists with PV system sizing. A brief update on SAM's battery model and its integration with the detailed photovoltaic model will also be discussed. Finally, an outline of planned work for the next year will be presented, including the addition of a bifacial model, support for multiple MPPT inputs for detailed inverter modeling, and the addition of a model for inverter thermal behavior.

14 SOLAR ENERGY↗

Carbon-phosphorus cycle models overestimate CO 2 enrichment response in a mature Eucalyptus forest

The importance of phosphorus (P) in regulating ecosystem responses to climate change has fostered P-cycle implementation in land surface models, but their CO 2 effects predictions have not been evaluated against measurements. Here, we perform a data-driven model evaluation where simulations of eight widely used P-enabled models were confronted with observations from a long-term free-air CO 2 enrichment experiment in a mature, P-limited Eucalyptus forest. We show that most models predicted the correct sign and magnitude of the CO 2 effect on ecosystem carbon (C) sequestration, but they generally overestimated the effects on plant C uptake and growth. We identify leaf-to-canopy scaling of photosynthesis, plant tissue stoichiometry, plant belowground C allocation, and the subsequent consequences for plant-microbial interaction as key areas in which models of ecosystem C-P interaction can be improved. Together, this data-model intercomparison reveals data-driven insights into the performance and functionality of P-enabled models and adds to the existing evidence that the global CO 2 -driven carbon sink is overestimated by models.

54 ENVIRONMENTAL SCIENCES↗

Comprehensive, Quantitative Risk Assessment of CO 2 Geologic Sequestration (Final Technical Report)

A Quantitative Failure Modes and Effects Analysis (QFMEA) was developed to conduct comprehensive, quantitative risk assessments on CO 2 capture, transportation, and sequestration or use in deep saline aquifers, enhanced oil recovery operations, or enhanced coal bed methane operations. The model identifies and characterizes potential risks; identifies the likely failure modes, causes, effects and methods of detection; lists possible risk prevention and risk mitigation steps; estimates potential damage recovery costs, mitigation costs and costs savings resulting from mitigation; and ranks (prioritizes) risks according to the probability of failure, the severity of failure, the difficulty of early failure detection and the potential for fatalities. The QFMEA model generates the necessary information needed for effective project risk management. Diverse project information can be integrated into a concise, common format that allows comprehensive, quantitative analysis, by a cross-functional team of experts, to determine: What can possibly go wrong? How much will damage recovery cost? How can it be prevented or mitigated? What is the cost savings or benefit of prevention or mitigation? Which risks should be given highest priority for resolution? The QFMEA model can be tailored to specific projects and is applicable to new projects as well as mature projects. The model can be revised and updated as new information comes available. It accepts input from multiple sources, such as literature searches, site characterization, field data, computer simulations, analogues, process influence diagrams, probability density functions, financial analysis models, cost factors, and heuristic best practices manuals, and converts the information into a standardized format in an Excel spreadsheet. Process influence diagrams, geologic models, financial models, cost factors and an insurance schedule were developed to support the QFMEA model. Comprehensive, quantitative risk assessments were conducted on three (3) sites using the QFMEA model: (1) SACROC Northern Platform CO 2 -EOR Site in the Permian Basin, Scurry County, TX, (2) Pump Canyon CO 2 -ECBM Site in the San Juan Basin, San Juan County, NM, and (3) Farnsworth Unit CO 2 -EOR Site in the Anadarko Basin, Ochiltree County, TX. The sites were sufficiently different from each other to test the robustness of the QFMEA model.

54 ENVIRONMENTAL SCIENCES↗

BUQEYE guide to projection-based emulators in nuclear physics

The BUQEYE collaboration (Bayesian Uncertainty Quantification: Errors in Your effective field theory) presents a pedagogical introduction to projection-based, reduced-order emulators for applications in low-energy nuclear physics. The term emulator refers here to a fast surrogate model capable of reliably approximating high-fidelity models. As the general tools employed by these emulators are not yet well-known in the nuclear physics community, we discuss variational and Galerkin projection methods, emphasize the benefits of offline-online decompositions, and explore how these concepts lead to emulators for bound and scattering systems that enable fast and accurate calculations using many different model parameter sets. We also point to future extensions and applications of these emulators for nuclear physics, guided by the mature field of model (order) reduction. All examples discussed here and more are available as interactive, open-source Python code so that practitioners can readily adapt projection-based emulators for their own work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Mobility Data and Models Informing Smart Cities

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.

33 ADVANCED PROPULSION SYSTEMS↗

Standard Library Plant Controller Model Specification for a Grid-Forming Hybrid Control Inverter-Based Resource (REPCGFM_C1)

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.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Standard Library Grid-Forming Hybrid Control Inverter-Based Resource Model Specification (REGFM_C1)

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.

24 POWER TRANSMISSION AND DISTRIBUTION↗