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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Extension of the ADAPT Framework for Multiple Simulators

Probabilistic Risk Assessment (PRA) uses fault tree/event tree analysis to evaluate the environmental impacts of nuclear power plants due to internal or external initiating events. In a fault tree, basic failure events are assembled using primarily And/Or logic to determine the combinations of failures that lead to failure of the system as a whole. An event tree is forward-facing, and begins with a single initiating event. From there the analysis considers what event may occur next, and branches out among the possible configurations of occurrence and non-occurrence of that event. This branching continues until end states are reached. End states may include a safe and stable configuration of the plant, or any number of differing failure states. Both fault and event trees require basic event probabilities as inputs to provide insight on the likelihood of different outcomes. PRA has been applied to nuclear power plants as an analysis tool since the 1975 Reactor Safety Study. In a traditional PRA, the order of events is prescribed by the analyst and each event is typically a binary aleatory uncertainty: occurrence or non-occurrence. Discrete dynamic event tree (DDET) analysis eliminates this subjectivity in ordering of events by using the output of a dynamic system model (simulator) to inform the branching. Branching conditions are triggered by the existence of a relevant plant state in the code, and therefore only occur as physically appropriate. The DDET approach also allows consideration of both epistemic and aleatory uncertainties on a phenomenologically and stochastically consistent platform. One limitation of the DDET driver codes developed to date (namely ADAPT, ADS, and MCDET ) is that the tree is driven by a single simulator. The goal of this work is a general multi-simulator driver. This limits the parameter space that may be explored in a single DDET to that which may be covered by a single simulator. In this work, the Analysis of Dynamic Accident Progression Trees (ADAPT) code is extended to support multiple arbitrary simulators. This capability will increase the depth and breadth of phenomena that may be analyzed in a single DDET. For example, a large-scale system code may pass the analysis to a more detailed code if certain conditions are met, in order to capture relevant phenomena that would be lost if only the system code were to be used. In addition, the time required to cover a given uncertainty space may be reduced by dynamically identifying and running only the situations that are appropriate given the plant conditions in each simulator. The use of multiple simulators is expected to further reduce subjectivity in PRA by enabling high fidelity modeling of reality. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Dynamic Importance Measures in the ADAPT Framework

Probabilistic Risk Assessment (PRA) uses fault tree/event tree analysis to evaluate the environmental impacts of nuclear power plants due to internal or external initiating events. In a fault tree, basic failure events are assembled using primarily And/Or logic to determine the combinations of failures that lead to failure of the system as a whole. An event tree is forward-facing, and begins with a single initiating event. From there the analysis considers what event may occur next, and branches out among the possible configurations of occurrence and non-occurrence of that event. This branching continues until user-defined end states are reached. End states may include a safe and stable configuration of the plant, or any number of differing failure states. Both fault and event trees require basic event probabilities as inputs to provide insight on the likelihood of different outcomes. PRA has been applied to nuclear power plants as an analysis tool since the 1975 Reactor Safety Study. In a traditional PRA, the order of events is prescribed by the analyst and each event is typically a binary aleatory uncertainty: occurrence or non-occurrence. Discrete dynamic event tree (DDET) analysis eliminates this subjectivity in ordering of events by using the output of a dynamic system model (simulator) to inform the branching. Branching conditions are triggered by the existence of a relevant plant state in the code, and therefore only occur as physically appropriate. The DDET approach also allows consideration of both epistemic and aleatory uncertainties on a phenomenologically and stochastically consistent platform. One current limitation of DDETs is the assessment of results, which is not as well developed as in traditional PRA. A concept that is used in PRA to assess the significance of a basic event is the concept of importance measures (IMs). In traditional PRA, IMs only consider the likelihood of occurrence of non-occurrence of a basic event. The application of importance measures to DDETs must take into consideration not only the occurrence and non-occurrence of an event, but also uncertain timing or severity. This work describes three general dynamic importance measures (DIMs) as implemented in the Analysis of Dynamic Accident Progression Trees (ADAPT) DDET driver code. The measures account for the change in progression of the DDET resulting from the different values of each uncertain variable under investigation. The DIMs are applied to a sample DDET to demonstrate the type of insights that may be gained from each one. These measures will facilitate comparison of the impact of dynamic branching events on a consequence of interest, which also allow DDETs to be used in prioritizing plant investments. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Absorption/Desorption based high efficiency Supercritical Carbon Dioxide Power Cycles - Final Scientific/Technical Report

The team of Southwest Research Institute® (SwRI®) and Thar Energy LLC (Thar) are advancing the state of the art in fossil-fired closed Brayton supercritical carbon dioxide (sCO 2 ) power cycles. This current effort is focused on evaluating the integration of a fossil-based thermal system with closed Brayton sCO 2 power blocks to understand the impact of thermal integration on plant performance and identification of current technology gaps. This effort is extending the current understanding of how fossil-based thermal systems may best be integrated with recuperated closed Brayton cycles based on the overall impact on the integrated plant efficiency, cost, and operating characteristics. System Engineering Design and Thermodynamic Analysis is being utilized to (1) identify technical challenges impacting the integration of fossil-based thermal sources with highly recuperated closed Brayton sCO 2 power cycles, (2) evaluate the impact of boiler design and sCO 2 cycle configuration on integrated plant performance, cost, and operability, and (3) evaluate technology readiness of the integrated system and identify specific technologies requiring development of advanced fossil-based sCO 2 cycles. Engineering evaluation is being applied to coal- and natural gas-fired thermal systems for sCO 2 power cycles to evaluate current boiler technologies and challenges associated with adapting those to a sCO 2 based configuration. This includes technical evaluation of the sCO 2 heat exchanger design and anticipated performance impacts on the thermal system. In addition to the general evaluation of indirect fossil fires closed Brayton sCO 2 cycles, this effort is also evaluating a novel indirect sCO 2 power cycle that utilizes an absorption/desorption circuit to minimize compression work by 40% to 65%. This translates to a thermodynamic cycle efficiency improvement of 3.2 points for a simple recuperated cycle using a binary CO 2 + Acetone working fluid.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Chapter 2: Global Value Chain and Manufacturing Analysis on Geothermal Power Plant Turbines

The global geothermal power market has shown significant growth since the last decade and is expected to reach a total installed capacity of 18.4 gigawatts electric (GWe) by the end of 2021 (GEA, 2016). The global geothermal power plant turbine market is dominated by a small number of manufacturers. Between 2005 and 2015, 82% of the geothermal steam turbines were manufactured in Japan, and 74% of the geothermal binary cycle turboexpanders were manufactured in Israel. During this period, the United States played an important role in the global trade flow of fully assembled turbine units and turbine parts, with a high volume of imports and exports. Another significant growth area was in Italian turbine/turboexpander manufacturers, who have increased their market share in the last couple of years. One other important change in the manufacturing market was in Turkey, where the bonus on feed-in-tariff (FIT) for domestic hardware components boosted the national manufacturing sector between 2010 and 2020. When planning geothermal power projects, developers customize their power plant size to fit the available geothermal resource capacity. The turbine is designed and sized to optimize the efficiency and utilization of resource and revenue production. The rest of the power plant components such as heat exchangers (HX), water-cooled cooling towers (WCCT), or air-cooled condensers (ACC) are then chosen to complement the turbine size and design. These one-off manufacturing custom design turbines have relatively higher manufacturing set-up costs, longer lead times, and higher capital costs than the standard design turbines manufactured in larger volumes. However, turbines produced in standard increments and in larger manufacturing volumes could result in lower costs per turbine, but potentially lower efficiency. Based on pipeline projects and resource assessments, there is significant potential value in creating standard turbine sizes that could offer an economic advantage, as is done for modular microturbines.

40 EE - Geothermal Technologies Office (EE-4G)↗
DOE OSTI2025

Quantitative dissection of Agrobacterium T-DNA expression in single plant cells reveals density-dependent synergy and antagonism

Agrobacterium pathogenesis, which involves transferring T-DNA into plant cells, is the cornerstone of plant genetic engineering. As the applications that rely on Agrobacterium increase in sophistication, it becomes critical to achieve a quantitative and predictive understanding of T-DNA expression at the level of single plant cells. Here we examine if a classic Poisson model of interactions between pathogens and host cells holds true for Agrobacterium infecting Nicotiana benthamiana. Systematically challenging this model revealed antagonistic and synergistic density-dependent interactions between bacteria that do not require quorum sensing. Using various approaches, we studied the molecular basis of these interactions. To overcome the engineering constraints imposed by antagonism, we created a dual binary vector system termed ‘BiBi’, which can improve the efficiency of a reconstituted complex metabolic pathway in a predictive fashion. Our findings illustrate how combining theoretical models with quantitative experiments can reveal new principles of bacterial pathogenesis, impacting both fundamental and applied plant biology.

Alamos, Simon↗
DOE OSTI2022

3-regular three-XORSAT planted solutions benchmark of classical and quantum heuristic optimizers

With current semiconductor technology reaching its physical limits, special-purpose hardware has emerged as an option to tackle specific computing-intensive challenges. Optimization in the form of solving quadratic unconstrained binary optimization problems, or equivalently Ising spin glasses, has been the focus of several new dedicated hardware platforms. These platforms come in many different flavors, from highly-efficient hardware implementations on digital-logic of established algorithms to proposals of analog hardware implementing new algorithms. In this work, we use a mapping of a specific class of linear equations whose solutions can be found efficiently, to a hard constraint satisfaction problem (three-regular three-XORSAT, or an Ising spin glass) with a 'golf-course' shaped energy landscape, to benchmark several of these different approaches. We perform a scaling and prefactor analysis of the performance of Fujitsu's digital annealer unit (DAU), the D-Wave advantage quantum annealer, a virtual MemComputing machine, Toshiba's simulated bifurcation machine (SBM), the SATonGPU algorithm from Bernaschi et al, and our implementation of parallel tempering. We identify the SATonGPU and DAU as currently having the smallest scaling exponent for this benchmark, with SATonGPU having a small scaling advantage and in addition having by far the smallest prefactor thanks to its use of massive parallelism. Furthermore, our work provides an objective assessment and a snapshot of the promise and limitations of dedicated optimization hardware relative to a particular class of optimization problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Elucidating the Transition of 3D Morphological Evolution of Binary Alloys in Molten Salts with Metal Ion Additives

Molten salts serve as effective high-temperature heat transfer fluids and thermal storage media used in a wide range of energy generation and storage facilities, including concentrated solar power plants, molten salt reactors and high-temperature batteries. However, at the salt–metal interfaces, a complex interplay of charge-transfer reactions involving various metal ions, generated either as fission products or through corrosion of structural materials, takes place. Simultaneously, there is a mass transport of ions or atoms within the molten salt and the parent alloys. The precise physical and chemical mechanisms leading to the diverse morphological changes in these materials remain unclear. Here, to address this knowledge gap, this work employed a combination of synchrotron X-ray nanotomography and electron microscopy to study the morphological and chemical evolution of Ni-20Cr in molten KCl-MgCl 2 , while considering the influence of metal ions (Ni 2+ , Ce 3+ , and Eu 3+ ) and variations in salt composition. Our research suggests that the interplay between interfacial diffusivity and reactivity determines the morphological evolution. The summary of the associated mass transport and reaction processes presented in this work is a step forward toward achieving a fundamental comprehension of the interactions between molten salts and alloys. Overall, the findings offer valuable insights for predicting the diverse chemical and structural alterations experienced by alloys in molten salt environments, thus aiding in the development of protective strategies for future applications involving molten salts.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Lignin with controlled structural properties by N-heterocycle-based deep eutectic solvent extraction

The complex and heterogeneous nature of the lignin macromolecule has presented a lasting barrier to its utilization. To achieve high lignin yield, the technical lignin extraction process usually severely modifies and condenses the native structure of lignin, which is a critical drawback for its utilization in conversion processes. In addition, there is no method capable of separating lignin from plant biomass with controlled structural properties. Here, we developed an N-heterocycle-based deep eutectic solvent formed between lactic acid and pyrazole (La–Py DES) with a binary hydrogen bonding functionality resulting in a high affinity toward lignin. In this study, up to 93.7% of lignin was extracted from wheat straw biomass at varying conditions from 90 °C to 145 °C. Through careful selection of treatment conditions as well as lactic acid to pyrazole ratios, lignin with controlled levels of ether linkage content, hydroxyl group content, and average molecular weight can be generated. Under mild extraction conditions (90 °C to 120 °C), light-colored native-like lignin can be produced with up to 80% yield, whereas ether linkage–free lignin with low polydispersity can be obtained at 145 °C. Overall, this study offers a new strategy for native lignin extraction and generating lignin with controlled structural properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2000

BOREAS RSS-7 Regional LAI and FPAR Images From 10-Day AVHRR-LAC Composites

The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team collected various data sets to develop and validate an algorithm to allow the retrieval of the spatial distribution of Leaf Area Index (LAI) from remotely sensed images. Advanced Very High Resolution Radiometer (AVHRR) level-4c 10-day composite Normalized Difference Vegetation Index (NDVI) images produced at CCRS were used to produce images of LAI and the Fraction of Photosynthetically Active Radiation (FPAR) absorbed by plant canopies for the three summer IFCs in 1994 across the BOREAS region. The algorithms were developed based on ground measurements and Landsat Thematic Mapper (TM) images. The data are stored in binary image format files.

Hall, Forrest G.↗
DOE OSTI2016

BdCESA7 , BdCESA8 , and BdPMT utility promoter constructs for targeted expression to secondary cell-wall-forming cells of grasses

Utility vectors with promoters that confer desired spatial and temporal expression patterns are useful tools for studying gene and cellular function and for industrial applications. To target the expression of DNA sequences of interest to cells forming plant secondary cell walls, which generate most of the vegetative biomass, upstream regulatory sequences of the Brachypodium distachyon lignin biosynthetic gene BdPMT and the cellulose synthase genes BdCESA7 and BdCESA8 were isolated and cloned into binary vectors designed for Agrobacterium -mediated transformation of monocots. Expression patterns were assessed using the β-glucuronidase gene GUSPlus and X-glucuronide staining. All three promoters showed strong expression levels in stem tissue at the base of internodes where cell wall deposition is most active, in both vascular bundle xylem vessels and tracheids, and in interfascicular tissues, with expression less pronounced in developmentally older tissues. In leaves, BdCESA7 and BdCESA8 promoter-driven expression was strongest in leaf veins, leaf margins, and trichomes; relatively weaker and patchy expression was observed in the epidermis. BdPMT promoter-driven expression was similar to the BdCESA promoters expression patterns, including strong expression in trichomes. The intensity and extent of GUS staining varied considerably between transgenic lines, suggesting that positional effects influenced promoter activity. Introducing the BdPMT and BdCESA8 Open Reading Frames into BdPMT and BdCESA8 utility promoter binary vectors, respectively, and transforming those constructs into Brachypodium pmt and cesa8 loss-of-function mutants resulted in rescue of the corresponding mutant phenotypes. This work therefore validates the functionality of these utility promoter binary vectors for use in Brachypodium and likely other grass species. Lastly, the identification, in Bdcesa8-1 T-DNA mutant stems, of an 80% reduction in crystalline cellulose levels confirms that the BdCESA8 gene is a secondary-cell-wall-forming cellulose synthase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Vapor liquid equilibrium of pure and aqueous Methyl diethanolamine (MDEA), 2-Dimethylmonoethanolamine (DMMEA), N-Methylmonoethanolamine (MMEA) and 1-(2-Aminoethyl)piperazine (AEP): Experimental results and modeling

This work presents new vapor-liquid data for the pure components 2-dimethylmonoethanolamine (DMMEA) and N-methylethanolamine (MMEA) and for the binary systems of aqueous methyldiethanolamine (MDEA), DMMEA, MMEA, and 1-(2-aminoethyl)piperazine (AEP). New Antoine models are developed for the pure component systems, and new and improved NRTL models for the binary systems. In the model development, together with new data from this work, all available data on VLE, excess heat of mixing, H E , freezing point depression, and specific heat were gathered, evaluated and used selectively for parameter optimization. Emphasis has been put on a best possible representation of amine volatility to enable reasonable predictions of amine emissions from absorption plants and to form a basis for subsequent models of ternary systems with CO 2 . In conclusion, model predictions are compared with experimental results and other models, source by source, and the overall results are satisfactory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

RUNAWAY DWARF CARBON STARS AS CANDIDATE SUPERNOVA EJECTA

The dwarf carbon (dC) star SDSS J112801.67+004034.6 has an unusually high radial velocity, 531 ± 4 km s{sup −1}. We present proper motion and new spectroscopic observations which imply a large Galactic rest frame velocity, 425 ± 9 km s{sup −1}. Several other SDSS dC stars are also inferred to have very high galactocentric velocities, again each based on both high heliocentric radial velocity and also confidently detected proper motions. Extreme velocities and the presence of C {sub 2} bands in the spectra of dwarf stars are both rare. Passage near the Galactic center can accelerate stars to such extreme velocities, but the large orbital angular momentum of SDSS J1128 precludes this explanation. Ejection from a supernova in a binary system or disruption of a binary by other stars are possibilities, particularly as dC stars are thought to obtain their photospheric C {sub 2} via mass transfer from an evolved companion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

DOE-GTO Low Temperature Project Case Study

The US Department of Energy (DOE), Geothermal Technologies Office (GTO) has funded low temperature projects to demonstrate the technical and economic feasibility of power generation from geothermal resources at temperatures of 150 degrees C and lower. To date three of the funded projects have completed their two year operation phase during which they supplied operating data to the GTO. This paper discusses the operation of two of these plants while they were providing data, including a review of facility performance, as well as an initial economic assessment of each.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Methane production and emissions in trees and forests

Forest ecosystem methane (CH 4 ) research has focused on soils, but trees are also important sources and sinks in forest CH 4 budgets. Living and dead trees transport and emit CH 4 produced in soils; living trees and dead wood emit CH 4 produced inside trees by microorganisms; and trees produce CH 4 through an abiotic photochemical process. Here, we review the state of the science on the production, consumption, transport, and emission of CH 4 by living and dead trees, and the spatial and temporal dynamics of these processes across hydrologic gradients inclusive of wetland and upland ecosystems. Emerging research demonstrates that tree CH 4 emissions can significantly increase the source strength of wetland forests, and modestly decrease the sink strength of upland forests. Scaling from stem or leaf measurements to trees or forests is limited by knowledge of the mechanisms by which trees transport soil-produced CH 4 , microbial processes produce and oxidize CH 4 inside trees, a lack of mechanistic models, the diffuse nature of forest CH 4 fluxes, complex overlap between sources and sinks, and extreme variation across individuals. Understanding the complex processes that regulate CH 4 source–sink dynamics in trees and forests requires cross-disciplinary research and new conceptual models that transcend the traditional binary classification of wetland vs upland forest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Experimental investigation on the binary/ternary fluidization behavior of Geldart D type spherical LDPE, Geldart D type cylindrical wood and Geldart B type sand particles

The series of experiments have been performed on a 2.5-inch cylindrical bed made of acrylic with full optical access and multiple pressure ports at various heights of the bed. The material of interest includes in the investigation include Geldart type D cylindrical hardwood pellets, Geldart type D spherical LDPE, and Geldart type B sand particles. The wood particles have a diameter of around 6.6 mm and a length of 13.2 mm, corresponding to an aspect ratio of 1:2. The spherical LDPE particles and the sand particles have a Sauter Mean Diameter of 3.75 mm, and 0.5 mm, respectively. The experiment series involved the fluidization of the above-mentioned single particle type, as well as the fluidization of binary and ternary mixtures with varying superficial velocities.

20 FOSSIL-FUELED POWER PLANTS↗