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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 1,801 records · Page 100
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A graph theoretic framework for representation, exploration and analysis on computed states of physical systems

A graph theoretic perspective is taken for a range of phenomena in continuum physics in order to develop representations for analysis of large scale, high-fidelity solutions to these problems. Of interest are phenomena described by partial differential equations, with solutions being obtained by computation. The motivation is to gain insight that may otherwise be difficult to attain because of the high dimensionality of computed solutions. We consider graph theoretic representations that are made possible by low-dimensional states defined on the systems. These states are typically functionals of the high-dimensional solutions, and therefore retain important aspects of the high-fidelity information present in the original, computed solutions. Our method is rooted in regarding each state as a vertex on a graph and identifying edges via processes that are induced either by numerical solution strategies, or by the physics. Correspondences are drawn between the sampling of stationary states, or the time evolution of dynamic phenomena, and the analytic machinery of graph theory. A collection of computations is examined in this framework and new insights to them are presented through analysis of the corresponding graphs.

42 ENGINEERING↗
DOE OSTI2019

Diesel Engine Characterization and Performance Scaling Via Brake Specific Fuel Consumption Map Dimensional Analysis

The goal of this work is to develop easily generalized models of heavy duty truck engine maps that allow for approximate comparisons of engine performance, thus enabling fuel efficient matching of engines to a set of corresponding loads and routes. This is achieved by applying dimensional analysis to create a uniformly applicable, dimensionless Brake Specific Fuel Consumption (BSFC) map that fits the behavior of a wide range of diesel engines. Here, a commonality between maps was found to occur when engine data is scaled by specific dimensional parameters that target data consistency among the primary operating points across engines. This common map highlights observable trends in engine performance based on the influence of these same parameters being scaled across engines. The resulting dimensionless engine map fits the minimum BSFC regions of four diesel engines to within 2.5 percent.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Scaled Wind Farm Technology (SWiFT) Facility (Safety Assessment, Rev. 0)

This Safety Assessment (SA) documents the hazard analysis conducted for the Scaled Wind Farm Technology (SWiFT) Facility. The Sandia National Laboratories (SNL) Authorization Basis process requires Safety Assessment documents for all moderate-hazard industrial facilities. Together with the Primary Hazard Screening (PHS) Document [SNL11A00204), the SA documents the SWiFT safety basis, which is defined as the safety analysis and hazard controls that provide reasonable assurance that a DOE facility can be operated in a manner that adequately protects the workers, collocated/onsite workers, the public, and the environment. The SA specifically addresses the potential impact of hazards on the worker, collocated worker, and public.

17 WIND ENERGY↗
DOE OSTI2022

Application of the metabolic modeling pipeline in KBase to categorize reactions, predict essential genes, and predict pathways in an isolate genome

The DOE Systems Biology Knowledgebase (KBase) platform offers a range of powerful tools for the reconstruction, refinement, and analysis of genome-scale metabolic models built from microbial isolate genomes. In this chapter, we describe and demonstrate these tools in action with an analysis of isoprene production in the Bacillus subtilis DSM genome. Two different methods are applied to build initial metabolic models for the DSM genome, then the models are gapfilled in three different growth conditions. Next, flux balance analysis (FBA) and flux variability analysis (FVA) techniques are applied to both study the growth of these models in minimal media and classify reactions within each model based on essentiality and functionality. The models are applied with the FBA method to predict essential genes, which are then compared to an updated list of essential genes obtained for B. subtilis 168, a very similar strain to the DSM isolate. The models are also applied to simulate Biolog growth conditions, and these results are compared with Biolog data collected for B. subtilis 168. Finally, the DSM metabolic models are applied to explore the pathways and genes responsible for producing isoprene in this strain. These studies demonstrate the accuracy and utility of models generated from the KBase pipelines, as well as exploring the tools available for analyzing these models.

DOE knowledgebase↗
DOE OSTI2014

Uncertainty and sensitivity analysis of fission gas behavior in engineering-scale fuel modeling

The role of uncertainties in fission gas behavior calculations as part of engineering-scale nuclear fuel modeling is investigated using the BISON fuel performance code and a recently implemented physics-based model for the coupled fission gas release and swelling. Through the integration of BISON with the DAKOTA software, a sensitivity analysis of the results to selected model parameters is carried out based on UO2 single-pellet simulations covering different power regimes. The parameters are varied within ranges representative of the relative uncertainties and consistent with the information from the open literature. The study leads to an initial quantitative assessment of the uncertainty in fission gas behavior modeling with the parameter characterization presently available. Also, the relative importance of the single parameters is evaluated. Moreover, a sensitivity analysis is carried out based on simulations of a fuel rod irradiation experiment, pointing out a significant impact of the considered uncertainties on the calculated fission gas release and cladding diametral strain. The results of the study indicate that the commonly accepted deviation between calculated and measured fission gas release by a factor of 2 approximately corresponds to the inherent modeling uncertainty at high fission gas release. Nevertheless, higher deviations may be expected for values around 10% and lower. Implications are discussed in terms of directions of research for the improved modeling of fission gas behavior for engineering purposes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2010

Variations of Cloud and Radiative Properties of Boundary-layer and Deep Convective Systems with Sea Surface Temperature Anomalies

Gridded monthly-mean satellite data contain compositing information from different cloud system types and clear-sky environments. To isolate the variations of cloud physical properties of an individual cloud system type with its environment, orbital data are needed. In this study, we will analyze the variations of cloud and radiative properties of boundary-layer clouds and deep convective cloud systems with sea surface temperature (SST) anomalies. We use Terra-CERES (Clouds and the Earth s Radiant Energy System) Level 2 data to classify distinct cloud objects defined by cloud-system types (deep convection, boundary-layer cumulus, stratocumulus and overcast clouds), sizes, geographic locations, and matched large-scale environments. This analysis method identifies a cloud object as a contiguous region of the Earth with a single dominant cloud-system type. It determines the shape and size of the cloud object from the satellite data and the cloud-system selection criteria. The statistical properties of the identified cloud objects are analyzed in terms of probability density functions (PDFs) of a single property or joint PDFs between two properties. The SST anomalies are defined as the differences from five-year annual-cycle means. Individual cloud objects are sorted into one of five equal size subsets, with the matched SST anomalies ranging from the most negative to the most positive values, for a given size category of deep convective cloud objects, boundary-layer cumulus, stratocumulus and overcast cloud objects. The PDFs of cloud and radiative properties for deep convective cloud objects (between 30 S and 30 N) are found to largely similar among the five SST anomaly subsets except for the lowest SST anomaly subset. The different characteristics from this SST anomaly subset may be related to some cloud objects resulting from equatorward movement of extratropical cloud systems. This result holds true for all three different size categories (measured by equivalent diameters of 100-150, 150-300 and > 300 km). The PDFs of cloud and radiative properties for boundary-layer cloud types are more variable for macrophysical properties than for microphysical properties, due probably to different large-scale environments where these cloud objects are formed. Implications of these results for the cloud feedback will also be discussed.

Xu, Kuan-Man↗
DOE OSTI2021

Comparative analysis of various pretreatments to mitigate fouling and scaling in membrane distillation

Membrane distillation (MD) has shown strong promise for treating hypersaline produced water (PW) streams. Scaling and fouling on the membrane surface, however, have been identified as major challenges for commercialization and widespread application. The focus of this study was to first identify the nature of foulants and scalants on the membrane surface and then investigate the pretreatment strategies that mitigate the extent of fouling and scaling on the membrane surface. Vacuum MD (VMD) was selected for this study because of its higher flux at more moderate feed temperatures that eventually leads better assessment of fouling and scaling on the membrane surface. VMD flux tests were carried out with three different real PW samples at total dissolved solids concentrations in the range of 120-160 g/L. It was found that an efficient pretreatment prior to MD is required to mitigate the fouling potential of the organic matter, mostly suspended constituents, in PW samples. Suspended organics fouled and quickly wetted the MD membrane. Major conventional treatments, including filtration, oxidation, coagulation, air floatation, and aeration were investigated to pretreat the PW before VMD tests. A comprehensive comparative analysis is presented showing that the ultrafiltration and coagulation pretreatments displayed the best performance in mitigating the fouling and scaling, while oxidative pretreatment was found to be effective in reducing the iron concentration to less than 5 ppm. The surface of scaled membranes was carefully characterized to further evaluate the performance of each pretreatment. The components that had the highest tendency to precipitate on the membrane surface were identified as strontium sulfate, calcium carbonate, sodium chloride, iron oxide, and silica. In closing, these findings are supported by thermodynamic estimation of the saturation index.

42 ENGINEERING↗
DOE OSTI2016

Shielding analysis of TN-32 spent fuel dry cask with SCALE

The objective of the University of Florida Non Destructive Evaluation (NDE) team is to use Emission Source Tomography to determine and verify the spent fuel location and condition in TN-32 dry casks. In order to investigate this technique, a radiation analysis of TN-32 cask will be performed with MAVRIC control module of SCALE 6.1 and MCNP6 code. The radiation source term from active fuel regions and fuel assembly structure components is calculated, and the MAVRIC geometry model is demonstrated in this paper. Finally, the procedure and future work is listed in this paper. And the shielding analysis result will be presented in ANS winter conference. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2022

Desert Locust Cropland Damage Differentiated from Drought, with Multi-Source Remote Sensing in Ethiopia

In 2020, Ethiopia had the worst desert locust outbreak in 25 years, leading to food insecurity. Locust research has typically focused on predicting the paths and breeding grounds based on ground surveys and remote sensing of outbreak factors. In this study, we hypothesized that it is possible to detect desert locust cropland damage through the analysis of fine-scale (5–10 m) resolution satellite remote sensing datasets. We performed our analysis on 121 swarm point locations on croplands derived from the Food and Agriculture Organization (FAO) of the United Nations, and 94 ‘non-affected’ random cropland sample points generated for this study that are distributed within 20–25 km from the ‘center’ of swarm affected sample locations. Integrated Drought Condition Indices (IDCIs) and Vegetation Health Indices (VHIs) calculated for the affected sample locations for 2000–2020 were strongly correlated (R(exp 2) > 0.90) with that of the corresponding non-affected group of sample sites. Drought indices were strongly correlated with the evaluation Standardized Precipitation Evapotranspiration Indices (SPEIs) and showed that 2020 was the wettest year since 2000. In 2020, the NDVI and backscatter coefficient of cropland phenologies from the affected versus non-affected cropland sample sites showed a slightly wider, but significant gap in March (short growing season) and August-October (long growing season). Thus, slightly wider gaps in cropland phenologies between the affected and non-affected sites were likely induced from the locust damage, not drought, with fine scale data representing a larger gap.

Desert locust↗
DOE OSTI2017

Influences of drizzle on stratocumulus cloudiness and organization [Influences of drizzle on cloudiness and stratocumulus organization]

Large-eddy simulations are used to study the influence of drizzle on stratocumulus organization, based on measurements made as part of the Second Dynamics and Chemistry of the Marine Stratocumulus field study-II. Cloud droplet number concentration ( N c ) is prescribed and considered as the proxy for different aerosol loadings. Our study shows that the amount of cloudiness does not decrease linearly with precipitation rate. An N c threshold is observed below which the removal of cloud water via precipitation efficiently reduces cloud depth, allowing evaporation to become efficient and quickly remove the remaining thin clouds, facilitating a fast transition from closed cells to open cells. Using Fourier analysis, stratocumulus length scales are found to increase with drizzle rates. Raindrop evaporation below 300 m lowers the cloud bases and amplifies moisture variances in the subcloud layer, while it does not alter the horizontal scales in the cloud layer, suggesting that moist cold pool dynamic forcings are not essential for mesoscale organization of stratocumulus. Furthermore, the cloud scales are greatly increased when the boundary layer is too deep to maintain well mixed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Trends in extreme temperature over Nigeria from percentile‐based threshold indices

ABSTRACT This study analyses spatial and temporal trends in extreme temperature indices over Nigeria. The percentile indices were calculated from newly homogenized daily minimum and maximum temperature data for the period 1971–2012 for 21 stations in Nigeria. Indices describing the characteristics of hot extremes and cold extremes are calculated with the RClimDex software. The annual and seasonal trends in these indices are obtained using the ordinary least square fit and the statistical significance tested using the R‐based modified Mann–Kendall test. We examine characteristics of these indices for the entire country and separately for the three geographical zones in Nigeria: Guinea, Savanna, and Sahel. The spatial and temporal patterns of trends in the indices indicate that Nigeria has experienced statistically significant increase in the frequency of hot extreme and decrease in cold extreme events. Although majority of the stations have significant trends in warm days and warm nights, the annual trend is greatest in warm nights. In addition, the rate of warming in minimum temperature (‘warm nights’) is stronger in June, July, August ( JJA ) and September, October, November ( SON ) compare with December, January, February ( DJF ) and March, April, May ( MAM ). As for the trends in cold days and cold nights, the trends in cold nights are larger than for cold days at both the annual and seasonal scales. The regional analysis indicates that trends in warm nights and cold nights are most pronounced in Guinea and Sahel regions.

Abatan, Abayomi A.↗
DOE OSTI2016

Parameterized complex dielectric functions of CuIn 1−x Ga x Se 2 : applications in optical characterization of compositional non‐uniformities and depth profiles in materials and solar cells

Abstract In‐situ spectroscopic ellipsometry (SE) was employed to extract the complex dielectric functions ε = ε 1 + iε 2 over the spectral range of 0.75–6.5 eV for a set of polycrystalline CuIn 1− x Ga x Se 2 (CIGS) thin films with different alloy compositions x = [Ga]/{[In] + [Ga]}. For highest possible accuracy in ε for each CIGS thin film, specialized SE procedures were adopted including (i) deposition to a thickness of ~600 Å on smooth native oxide covered crystal silicon wafers, which minimizes the surface roughness on the film and thus the required corrections in data analysis, and (ii) measurement in‐situ , which minimizes ambient contamination and oxidation of the film surface. Assuming an analytical form for each of the ε spectra for these CIGS films, oscillator parameters were obtained in best fits, and these parameters were fit in turn to polynomials in x . With the resulting database of polynomial coefficients, the ε spectra for any composition of CIGS can be generated from the single parameter, x . In addition to enabling accurate contactless determination of bulk and surface roughness layer thicknesses of CIGS films by high speed multichannel SE, the database enables characterization of the composition and its profile with depth into these films, and even how the depth profile varies spatially within the plane of the films. In this study, depth profile parameters were found to correlate spatially with solar cell performance parameters. As a result, SE provides the capability of contactless compositional analysis of production‐scale CIGS photovoltaic modules at high speed. Copyright © 2016 John Wiley & Sons, Ltd.

Aryal, Puruswottam↗
DOE OSTI2022

The SENSEI Generic In Situ Interface: Tool and Processing Portability at Scale [Book Chapter]

One key challenge when doing in situ processing is the investment required to add code to numerical simulations needed to take advantage of in situ processing. Such instrumentation code is often specialized, and tailored to a specific in situ method or infrastructure. Then, if a simulation wants to use other in situ tools, each of which has its own bespoke API [4], then the simulation code team will quickly become overwhelmed with having a different set of instrumentation APIs, one per in situ tool or method. In an ideal situation, such instrumentation need happen only once, and then the instrumentation API provides access to a large diversity of tools. In this way, a data producer’s instrumentation need not be modified if the user desires to take advantage of a different set of in situ tools. The SENSEI generic in situ interface addresses this challenge, which means that SENSEI-instrumented codes enjoy the benefit of being able to use a diversity of tools at scale, tools that include Libsim, Catalyst, Ascent, as well as user-defined methods written in C++ or Python. SENSEI has been shown to scale to greater than 1M-way concurrency on HPC platforms, and provides support for a rich and diverse collection of common scientific data models. Furthermore, this chapter presents the key design challenges that enable tool and processing portability at scale, some performance analysis, and example science applications of the methods.

Bethel, E. Wes↗
DOE OSTI2017

Evaluating opportunities to improve material and energy impacts in commodity supply chains

When evaluated at the scale of individual processes, next-generation technologies may be more energy and emissions intensive than current technology. Furthermore, many advanced technologies have the potential to reduce material and energy consumption in upstream or downstream processing stages. In order to fully understand the benefits and consequences of technology deployment, next-generation technologies should be evaluated in context, as part of a supply chain. This work presents the Materials Flow through Industry (MFI) supply chain modeling tool. The MFI tool is a cradle-to-gate linear network model of the US industrial sector that can model a wide range of manufacturing scenarios, including changes in production technology and increases in industrial energy efficiency. The MFI tool was developed to perform supply chain scale analyses in order to quantify the impacts and benefits of next-generation technologies and materials at that scale. For the analysis presented in this paper, the MFI tool is utilized to explore a case study comparing three lightweight vehicle supply chains to the supply chain of a conventional, standard weight vehicle. Several of the lightweight vehicle supply chains are evaluated under manufacturing scenarios that include next-generation production technologies and next-generation materials. Results indicate that producing lightweight vehicles is more energy and emission intensive than producing the non-lightweight vehicle, but the fuel saved during vehicle use offsets this increase. In this case study, greater reductions in supply chain energy and emissions were achieved through the application of the next-generation technologies than from application of energy efficiency increases.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗
DOE OSTI2013

Einstein–Cartan gravity, Asymptotic Safety, and the running Immirzi parameter

In this paper we analyze the functional renormalization group flow of quantum gravity on the Einstein–Cartan theory space. The latter consists of all action functionals depending on the spin connection and the vielbein field (co-frame) which are invariant under both spacetime diffeomorphisms and local frame rotations. In the first part of the paper we develop a general methodology and corresponding calculational tools which can be used to analyze the flow equation for the pertinent effective average action for any truncation of this theory space. In the second part we apply it to a specific three-dimensional truncated theory space which is parametrized by Newton’s constant, the cosmological constant, and the Immirzi parameter. A comprehensive analysis of their scale dependences is performed, and the possibility of defining an asymptotically safe theory on this hitherto unexplored theory space is investigated. In principle Asymptotic Safety of metric gravity (at least at the level of the effective average action) is neither necessary nor sufficient for Asymptotic Safety on the Einstein–Cartan theory space which might accommodate different “universality classes” of microscopic quantum gravity theories. Nevertheless, we do find evidence for the existence of at least one non-Gaussian renormalization group fixed point which seems suitable for the Asymptotic Safety construction in a setting where the spin connection and the vielbein are the fundamental field variables. -- Highlights: •A functional RG equation for a first order formulation of gravity is constructed. •The theory space constituted by tetrad and spin connection variables is explored. •The RG equation is solved in a 3 dimensional truncation of theory space. •The flow of Newton’s constant, the cosmological constant and the Immirzi parameter is analyzed. •Evidence for the nonperturbative renormalizability of the theory is found.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

An analytical phytoplankton model and its application in the tidal freshwater James River

Here, this study constructs an analytical model to understand the phytoplankton dynamics in a one-dimensional system by integrating physical and biological processes. We present an analytical solution of phytoplankton distribution along the longitudinal direction of a tidal river. The solution has two components: water age and accumulative growth. The water age represents the overall effect of physical transport due to advection, while the accumulative growth represents the accumulation of phytoplankton biomass due to biological processes during the transport. In addition, an alternative solution with nonlinear reaction term is given to account for the feedback mechanism of nonlinear processes that affect phytoplankton growth rate. The nonlinear reaction term can be also used to approximate the effect of physical mixing on phytoplankton distribution. The analytical solutions can be further used to predict the temporal variation and spatial distribution of phytoplankton along the tidal river. They also serve as a mathematical tool to unite different field phytoplankton observations. We applied the model in the Tidal Freshwater Region (TFR) of James River under different dynamic conditions and the model results match well with the observations, which validates the theory on different time scales. Furthermore, an analysis is conducted for the Local Chlorophyll-a Maximum (LCM) in the TFR. It shows that the condition for LCM is biologically controlled, but its location is regulated by river flow and river geomorphology.

54 ENVIRONMENTAL SCIENCES↗

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