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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 415 records · Page 23

Low-G Slosh Workshop Results From 2023: State of the Art, Gaps and Forward Work

The NASA Engineering and Safety Center (NESC) sponsored a workshop to dis-cuss low-g slosh. Over a dozen different NASA centers and industry partners participated in this workshop. The main topics were to identify the state of the art regarding test data, Computational Fluid Dynamics (CFD) analysis resources, and GN&C models that are available for this problem. The primary intent was to determine deficiencies in the collective knowledge base and to identify priorities that should be established for proactive work in the areas of model development, validation, and model integration. Recommendations from workshop participants include establishing an online slosh modeling resource, conducting ground/flight testing, developing surrogate models, and establishing co-simulation techniques. This paper summarizes the workshop findings and recommendations for the larger community.

Lattice-Boltzmann↗

A three-year dataset supporting research on building energy management and occupancy analytics

Abstract This paper presents the curation of a monitored dataset from an office building constructed in 2015 in Berkeley, California. The dataset includes whole-building and end-use energy consumption, HVAC system operating conditions, indoor and outdoor environmental parameters, as well as occupant counts. The data were collected during a period of three years from more than 300 sensors and meters on two office floors (each 2,325 m 2 ) of the building. A three-step data curation strategy is applied to transform the raw data into research-grade data: (1) cleaning the raw data to detect and adjust the outlier values and fill the data gaps; (2) creating the metadata model of the building systems and data points using the Brick schema; and (3) representing the metadata of the dataset using a semantic JSON schema. This dataset can be used in various applications—building energy benchmarking, load shape analysis, energy prediction, occupancy prediction and analytics, and HVAC controls—to improve the understanding and efficiency of building operations for reducing energy use, energy costs, and carbon emissions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Spaceborne synthetic aperture radar: Current status and future directions. A report to the Committee on Earth Sciences, Space Studies Board, National Research Council

This report provides a context in which questions put forth by NASA's Office of Mission to Planet Earth (OMPTE) regarding the next steps in spaceborne synthetic aperture radar (SAR) science and technology can be addressed. It summarizes the state-of-the-art in theory, experimental design, technology, data analysis, and utilization of SAR data for studies of the Earth, and describes potential new applications. The report is divided into five science chapters and a technology assessment. The chapters summarize the value of existing SAR data and currently planned SAR systems, and identify gaps in observational capabilities needing to be filled to address the scientific questions. Cases where SAR provides complementary data to other (non-SAR) measurement techniques are also described. The chapter on technology assessment outlines SAR technology development which is critical not only to NASA's providing societally relevant geophysical parameters but to maintaining competitiveness in SAR technology, and promoting economic development.

Evans, D. L.↗

How Can NASA Science Benefit Solar Energy Development and Assessment?

This is a keynote presentation for a workshop highlighting the use of remote sensing and modeling products derived with NASA missions and Earth system modeling for solar energy system development. We broadly introduce NASA's fleet of satellite producing publicly available data products that would be useful for the information needed solar energy development. We also introduce the work in Earth system science modeling that provides additional global gridded data products that are also relevant. We identify that one issue is obtaining and using this data is the level of expertise needed to find it. NASA has developed a new Earth Action program to address this gap and bring the data closer to the user. Now under the Energy Resources element, the NASA LaRC's POWER (Prediction of Worldwide Renewable Energy) project has developed a web services platform that provides key information needed for solar energy development as analysis-ready. This means that the data for particular locations are immediately useful for help provide the information needed by engineers and architects to plan for solar systems. Thus, the presentation shows why NASA products would be relevant and then shows examples of finding the needed data through the POWER web portal.

remote sensing↗

Synthetic Data Generation Using Machine Learning

Robust machine learning techniques for image analysis require a substantial amount of data to yield confident results. In the nuclear domain, data scarcity is a substantial challenge because there are so few facilities worldwide. This research focuses on being able alleviate the data scarcity problem by generating synthetic data to bridge the gap between large and small datasets. This work achieves that goal using a Generative Adversarial Network (GAN) architectural approach, by training a model on real-world data and expands that small dataset through synthetic data amendments. Model performance is impacted by the size of the real-world dataset and the number of training epochs utilized. This means that 1) It is important to develop your GAN to be optimized with the specific data type, and 2) approaches taken when training the GAN should be specialized to encompass important aspects of the dataset that it is generating. By taking a step to improve dataset sizes in this way, the gap between models trained by parties with significant amount of data and those without access to large data, closes, allowing for robust analyses of satellite imagery for nuclear domain applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Machine-Learning-aided Approach for Predicting the Thermal Expansion Behaviors in Advanced Test Reactor Capsules (NURETH-20 full paper)

Instrumented experiments at test reactors are essential to deploying new advanced reactor systems. Designing new experiments and generating data on specific conditions require both time and cost investment. A high-fidelity model of the experiment environment can be created using finite element analysis software to support the actual experiments, but computation time is still a concern in applying outcomes to real-time usage (e.g., a digital twin). This research proposes a machine-learning-aided approach to temperature and displacement predictions, based on the thickness of the outer gas gap on the experimental capsule used for the in-pile demonstration of a novel thermal conductivity probe in the Advanced Test Reactor. The capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. There were gas gaps between the fuel and rodlet and between the inner and outer capsule. The learning data consisted of an experimental capsule’s radial distributions of temperature and displacement, as obtained from Abaqus and the physical features. For the first step, temperature was predicted using three positional parameters. Then the displacement was predicted using six different positional parameters. Each physical feature was normalized to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement in all cases involving interpolation and extrapolation. Also, data similarity enhancement increased the similarity between training and target data increasing the predictive accuracy of machine-learning models. In some cases of extrapolation, the accuracy of the machine-learning model showed limited performance, but still data similarity enhancement improved the accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Building a landslide hazard indicator with machine learning and land surface models

The U.S. Pacific Northwest has a history of frequent and occasionally deadly landslides caused by various factors. Using a multivariate, machine-learning approach, we combined a Pacific Northwest Landslide Inventory with a 36-year gridded hydrologic dataset from the National Climate Assessment – Land Data Assimilation System to produce a landslide hazard indicator (LHI) on a daily 0.125-degree grid. The LHI identified where and when landslides were most probable over the years 1979–2016, addressing issues of bias and completeness that muddy the analysis of multi-decadal landslide inventories. The seasonal cycle was strong along the west coast, with a peak in the winter, but weaker east of the Cascade Range. This lagging indicator can fill gaps in the observational record to identify the seasonality of landslides over a large spatiotemporal domain and show how landslide hazard has responded to a changing climate.

XGBoost↗

Life Cycle Cost Analysis of Prestressed Concrete Poles Subjected to Wind, Surges, and Waves

Prestressed concrete (PC) poles are becoming popular choices to support coastal power transmission systems. However, the existing literature does not offer a detailed analysis of the effectiveness of PC poles in terms of long-term vulnerabilities and the direct and indirect costs. This is due to (1) lack of fragility models for PC poles and (2) lack of probabilistic wind, storm surge, and wave models in coastal settings. In this study, we address these gaps through a series of Monte Carlo simulations to estimate fragility of PC poles as a function of age and hazard (wind, surges, and waves) intensity, and the development of a probabilistic hazard model based on 10,000 years of synthetic tropical cyclone data. The probabilistic hazard model is used in conjunction with high-resolution hydrodynamic models to generate realizations of coastal wind, storm surges, and waves for the Louisiana and Mississippi coasts. A comprehensive life cycle cost analysis for a service life of 70 years considering direct and indirect losses is conducted to compare the performance of a transmission line located in Pascagoula, Mississippi, when wood poles are replaced by PC poles. Results showed that aging has a minor effect on the reliability of PC poles, highlighting the advantages of replacing wood poles with PC poles, especially in coastal areas. In addition, PC poles are significantly more cost-effective compared with wood poles over their life cycle, leading to an estimated saving of $11.55 million (68.17% reduction). The results of this study provide key insight to inform decision-making processes to keep the coastal power grids resilient and cost-effective against future storm hazards.

natural disasters↗

Model form and sensitivity analysis of CALPHAD-based nucleation models in b-stabilized Ti alloys

Accurate prediction of α-phase nucleation and growth in β-stabilized titanium alloys is crucial for designing heat treatments to optimize mechanical properties in additively manufactured lightweight components. Ideally, predictions of nucleation and growth would incorporate both top-down observations of past experimental heat treatments and bottom-up modeling of phase transformations; however, the appropriate method of combining these information sources is not self-evident. Combining top-down and bottom-up information requires a unified form of model that can connect between spatiotemporal scales, as well as sets of fitting parameters that can be identified by each data source. The selection of which parameters to fit to which data source can be made based on expert opinion, or by performing a sensitivity analysis. In solid-solid nucleation, direct observation of the nucleation and growth process is challenging. Most data on the heat treatment-controlled phase transformations are not in-situ. To predict the process and outcome of the nucleation, growth and coarsening of precipitates, theoretical models of the nucleation pathway are used to bridge the gap. Many sources of uncertainty affect the modeling of this nucleation process. It can be influenced by small variations in the thermomechanical processing history, chemical composition, and initial microstructure. If molecular dynamics (MD) simulations are used to determine thermodynamic quantities and inform CALPHAD modeling, additional uncertainty can be introduced and accounted for using Bayesian methods. Top-down uncertainties require additional steps to quantify. The influence of nucleation model form on the sensitivity of predictions to input parameters and physical conditions is the focus of this study. Classical nucleation theory (CNT) allows modeling to formulate the nucleation as homogeneous or, more commonly, heterogeneous. Non-classical nucleation models are also increasingly explored as a means of reconciling top-down and bottom-up data. In this study, the sensitivity of the intragranular nucleation of α in a β-annealed, slow-cooled aging (BASCA) heat treatment of β-stabilized Ti5553 alloy is explored using CNT and both heterogeneous and homogeneous assumptions. The Kampmann-Wagner Numerical model of precipitate nucleation and growth is employed. Using open-source tools (pyCalphad and thermodynamic modeling of TiMo as a surrogate system, a sensitivity analysis is performed to measure variations in key parameters, including chemical driving force, interfacial energy, and diffusivity, as they relate to predictions of precipitate number density. The inclusion of top-down and bottom-up data in selection of nucleation model form is discussed.

Rodriguez Negron, A. M.↗

REGAL International Program: Analysis of experimental data for depletion code validation

The Rod-Extremity and Gadolinia AnaLysis (REGAL) Program is a joint international effort to expand the nuclide inventory experimental data for irradiated nuclear fuel, with a specific focus on addressing two challenging needs associated with the characterization of modern, high duty, nuclear fuel. The first challenge is filling the gaps in experimental nuclide inventory data for gadolinia (UO 2 –Gd 2 O 3 ) fuel rods. The huge absorption cross sections of Gd-155 and Gd-157 in the Gd dopant in these rods lead to atypical spatial self-shielding patterns and have an impact on the neutronic environment within the fuel assembly compared to regular UO 2 fuel rods. Additionally, the second challenge is investigating the impact of burnup gradients at rod extremities on fuel composition and neutron leakage, to provide relevant experimental data for assessing computational capabilities to model such impact. A benchmark has been defined as a first step in the development of best-estimate models in the preliminary phase of the experimental data evaluation. Comparison of experimental results obtained in Phase I of the program for two measured pressurized water reactor (PWR) samples, one UO 2 and one UO 2 –Gd 2 O 3 sample, with calculated results obtained with different computational tools based on the defined benchmark are presented and discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Chemical control of competing electron transfer pathways in iron tetracyano-polypyridyl photosensitizers

Photoinduced intramolecular electron transfer dynamics following metal-to-ligand charge-transfer (MLCT) excitation of [Fe(CN) 4 (2,2'-bipyridine)] 2- (1), [Fe(CN) 4 (2,3-bis(2-pyridyl)pyrazine)] 2- (2) and [Fe(CN) 4 (2,2'-bipyrimidine)] 2- (3) were investigated in various solvents with static and time-resolved UV-Visible absorption spectroscopy and Fe 2p3d resonant inelastic X-ray scattering (RIXS). This series of polypyridyl ligands, combined with the strong solvatochromism of the complexes, enables the 1 MLCT vertical energy to be varied from 1.64 eV to 2.64 eV and the 3 MLCT lifetime to range from 180 fs to 67 ps. The 3 MLCT lifetimes in 1 and 2 decrease exponentially as the MLCT energy increases, consistent with electron transfer to the lowest energy triplet metal-centred ( 3 MC) excited state, as established by the Tanabe–Sugano analysis of the Fe 2p3d RIXS data. In contrast, the 3 MLCT lifetime in 3 changes non-monotonically with MLCT energy, exhibiting a maximum. This qualitatively distinct behaviour results from a competing 3 MLCT → ground state (GS) electron transfer pathway that exhibits energy gap law behaviour. The 3 MLCT → GS pathway involves nuclear tunnelling for the high-frequency polypyridyl breathing mode (hν = 1530 cm -1 ), which is most displaced for complex 3, making this pathway significantly more efficient. Our study demonstrates that the excited state relaxation mechanism of Fe polypyridyl photosensitizers can be readily tuned by ligand and solvent environment. Furthermore, our study reveals that extending charge transfer lifetimes requires control of the relative energies of the 3 MLCT and the 3 MC states and suppression of the intramolecular distortion of the acceptor ligand in the 3 MLCT excited state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reliability Assessment of Cooling Fans for PV Inverters: Testing, Modeling, and Case Studies

The reliability of photovoltaic (PV) inverters is critical for long-term solar system performance, with cooling fan failures frequently leading to costly downtime. While much research exists on general cooling fan reliability, little attention has been given to fans operating within PV inverters and their unique environmental challenges. Here, this article proposes a comprehensive methodology to address this gap. First, a failure mode and effects analysis is performed on fans to identify the key failure mechanisms in PV applications, their corresponding stressors, and the models necessary for lifetime prediction. Second, an accelerated life test is designed and conducted to collect valuable experimental data for PV inverter fans in a reasonable amount of time. Third, a mathematical conversion of dynamic mission profiles into effective constant stress levels is derived. Fourth, case studies are given, showcasing lifetime estimates that account for geographic variations in mission profile data. The results demonstrate that this integrated approach leads to an accurate reliability assessment for PV inverter cooling fans.

accelerated life testing (ALT)↗

Second Cancers After Fractionated Radiotherapy: Stochastic Population Dynamics Effects

When ionizing radiation is used in cancer therapy it can induce second cancers in nearby organs. Mainly due to longer patient survival times, these second cancers have become of increasing concern. Estimating the risk of solid second cancers involves modeling: because of long latency times, available data is usually for older, obsolescent treatment regimens. Moreover, modeling second cancers gives unique insights into human carcinogenesis, since the therapy involves administering well characterized doses of a well studied carcinogen, followed by long-term monitoring. In addition to putative radiation initiation that produces pre-malignant cells, inactivation (i.e. cell killing), and subsequent cell repopulation by proliferation can be important at the doses relevant to second cancer situations. A recent initiation/inactivation/proliferation (IIP) model characterized quantitatively the observed occurrence of second breast and lung cancers, using a deterministic cell population dynamics approach. To analyze ifradiation-initiated pre-malignant clones become extinct before full repopulation can occur, we here give a stochastic version of this I I model. Combining Monte Carlo simulations with standard solutions for time-inhomogeneous birth-death equations, we show that repeated cycles of inactivation and repopulation, as occur during fractionated radiation therapy, can lead to distributions of pre-malignant cells per patient with variance >> mean, even when pre-malignant clones are Poisson-distributed. Thus fewer patients would be affected, but with a higher probability, than a deterministic model, tracking average pre-malignant cell numbers, would predict. Our results are applied to data on breast cancers after radiotherapy for Hodgkin disease. The stochastic IIP analysis, unlike the deterministic one, indicates: a) initiated, pre-malignant cells can have a growth advantage during repopulation, not just during the longer tumor latency period that follows; b) weekend treatment gaps during radiotherapy, apart from decreasing the probability of eradicating the primary cancer, substantially increase the risk of later second cancers.

Sachs, Rainer K.↗

A CFD Database for Airfoils and Wings at Post-Stall Angles of Attack

This paper presents selected results from an ongoing effort to develop an aerodynamic database from Reynolds-Averaged Navier-Stokes (RANS) computational analysis of airfoils and wings at stall and post-stall angles of attack. The data obtained from this effort will be used for validation and refinement of a low-order post-stall prediction method developed at NCSU, and to fill existing gaps in high angle of attack data in the literature. Such data could have potential applications in post-stall flight dynamics, helicopter aerodynamics and wind turbine aerodynamics. An overview of the NASA TetrUSS CFD package used for the RANS computational approach is presented. Detailed results for three airfoils are presented to compare their stall and post-stall behavior. The results for finite wings at stall and post-stall conditions focus on the effects of taper-ratio and sweep angle, with particular attention to whether the sectional flows can be approximated using two-dimensional flow over a stalled airfoil. While this approximation seems reasonable for unswept wings even at post-stall conditions, significant spanwise flow on stalled swept wings preclude the use of two-dimensional data to model sectional flows on swept wings. Thus, further effort is needed in low-order aerodynamic modeling of swept wings at stalled conditions.

Petrilli, Justin↗

Probing rutile solid-phase crystallization of atomically mixed Mn-alloyed TiO 2 coatings through XANES analysis

Phase transformation via dopant introduction is an emerging strategy for tuning the electronic and catalytic properties of oxides. However, developing a general theory of ternary alloys and their microstructure evolution remains challenging due to the knowledge gaps in how point defects such as dopants lead to the formation of complex or metastable phases. We investigate the influence of Mn concentration and annealing temperature on the microstructure evolution of amorphous Mn-alloyed TiO 2 synthesized via Atomic Layer Deposition. In conclusion, our findings reveal a new crystallization pathway resulting in a direct amorphous TiO 2 to rutile transformation without an intermediate anatase phase and our multi-parameter thermal processing conditions show potential for AI-assisted data acquisition and analysis for studying complex oxide coatings.

36 MATERIALS SCIENCE↗

Systems Analysis Approach to Polyethylene Terephthalate and Olefin Plastics Supply Chains in the Circular Economy: A Review of Data Sets and Models

The environmental and economic impacts of implementing a circular economy in plastic waste supply chains are not well understood. The proposed systems analysis framework assesses environmental, social, and economic impacts of plastic waste supply chains in a circular economy. The first objective of this article is to identify datasets, models and knowledge gaps associated with waste plastic supply chain processes, mainly in the U.S. Our literature review indicated that the best datasets exist for virgin plastic resin production, mechanical recycling, landfilling, and incineration, with materials recovery facility being intermediate, and with chemical recycling the lowest. The second objective of this article is to develop an illustrative application of the framework by conducting a preliminary systems analysis of PET bottles with closed-loop recycling. Here, the preliminary systems analysis of PET bottles utilized a linear programming optimization method. Our optimization model indicated that both chemical and mechanical recycling processes are needed to achieve a true circular economy of PET bottles with the least greenhouse gas emissions, specifically reductions of 24% when compared with the linear economy. Good quality and standardized life cycle assessment and techno-economic analysis studies are needed to better understand the environmental, economic, and social impacts of advanced sorting and chemical recycling technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Comparison of Methods for Assessing Space Suit Joint Ranges of Motion

Through the Advanced Exploration Systems Program, NASA is attempting to use the vast collection of space suit mobility data from 50 years worth of space suit testing to build predictive analysis tools to aid in early architecture decisions for future missions and exploration programs. However, the design engineers must first understand if and how data generated by different methodologies can be compared directly and used in an essentially interchangeable manner. To address this question, the isolated joint range of motion data from two different test series were compared. Both data sets were generated from participants wearing the Mark III Space Suit Technology Demonstrator (MK-III), Waist Entry I-suit (WEI), and minimal clothing. Additionally the two tests shared a common test subject that allowed for within subject comparisons of the methods that greatly reduced the number of variables in play. The tests varied in their methodologies: the Space Suit Comparative Technologies Evaluation used 2D photogrammetry to analyze isolated ranges of motion while the Constellation space suit benchmarking and requirements development used 3D motion capture to evaluate both isolated and functional joint ranges of motion. The isolated data from both test series were compared graphically, as percent differences, and by simple statistical analysis. The results indicated that while the methods generate results that are statistically the same (significance level p= 0.01), the differences are significant enough in the practical sense to make direct comparisons ill advised. The concluding recommendations propose direction for how to bridge the data gaps and address future mobility data collection to allow for backward compatibility.

Aitchison, Lindsay↗