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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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Global gross primary production simulated by three terrestrial biosphere models to analyse smoothing of limiting rates
Processed global terrestrial gross primary production (GPP) from three terrestrial biosphere models (TBMs). Two simulations were run with each model, one that selects the rate limiting process of photosynthesis based on the minimum of the potential rates (following Farquhar et al. 1980) and the other that uses quadratic smoothing between the potential rates (following Collatz et al. 1991). The three TBMs are: 1) the Energy Exascale Earth System Model (E3SM) land model (ELM) (release: v1.1.0) (Burrows et al., 2020), a coupled carbon, nitrogen, and phosphorus model with sun/shade big-leaf canopy photosynthesis scaling. 2) The Functionally Assembled Terrestrial Ecosystem Simulator (FATES, tag: sci.1.30.0_api.8.0.0) (Koven et al., 2019), coupled with the Community Land Model (CLM, version 5; Lawrence et al., 2019), a carbon-only vegetation demography model with multi-leaf and multi-canopy layers for scaling photosynthesis, and with a leaf area index (LAI) optimisation scheme. 3) The Sheffield Dynamic Global Vegetation Model (SDGVM, tag: Walkeretal2020_GCB), a carbon-only model with multi-leaf-layer canopy photosynthesis scaling and also with an LAI optimisation scheme (Walker et al., 2017; Woodward & Lomas, 2004). These data were generated to evaluate the effect of Collatz smoothing of limiting rates on simulated GPP across a range of terrestrial biosphere models. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures and .RDS files, a binary format specific to R and read with the 'readRDS' function.
Development of an Extensible Computational Framework for Centralized Storage and Distributed Curation and Analysis of Genomic Data Genome-scale Metabolic Models
The DOE funded KBase project of the Stevens group at the University of Chicago was focused on four high-level goals: (i) improve extensibility, accessibility, and scalability of the SEED framework for genome annotation, curation, and analysis; (ii) extend the SEED infrastructure to support transcription regulatory network reconstructions (2.1), metabolic model reconstruction and analysis (2.2), assertions linked to data (2.3), eukaryotic annotation (2.4), and growth phenotype prediction (2.5); (iii) develop a web-API for programmatic remote access to SEED data and services; and (iv) application of all tools to bioenergy-related genomes and organisms. In response to these goals, we enhanced and improved the ModelSEED resource within the SEED to enable new modeling analyses, including improved model reconstruction and phenotype simulation. We also constructed a new website and web-API for the ModelSEED. Further, we constructed a comprehensive web-API for the SEED as a whole. We also made significant strides in building infrastructure in the SEED to support the reconstruction of transcriptional regulatory networks by developing a pipeline to identify sets of consistently expressed genes based on gene expression data. We applied this pipeline to 29 organisms, computing regulons which were subsequently stored in the SEED database and made available on the SEED website (http://pubseed.theseed.org). We developed a new pipeline and database for the use of kmers, or short 8-residue oligomer sequences, to annotate genomes at high speed. Finally, we developed the PlantSEED, or a new pipeline for annotating primary metabolism in plant genomes. All of the work performed within this project formed the early building blocks for the current DOE Knowledgebase system, and the kmer annotation pipeline, plant annotation pipeline, and modeling tools are all still in use in KBase today.
Bottom Fixed Platform Dynamics Models Assessing Surface Ice Interactions for Transitional Depth Structures in the Great Lakes: FAST8 – IceDyn
To create long-term solutions for offshore wind turbines in a variety of environmental conditions, CAE tools are needed to model the design-driving loads that interact with an offshore wind turbine system during operation. This report describes our efforts in augmenting existing CAE tools used for offshore wind turbine analysis with a new module that can provide simulation capabilities for ice loading on the system. This augmentation was accomplished by creating an ice-loading module coupled to FAST8, the CAE tool maintained by the NREL for simulating land-based and offshore wind turbine dynamics. The new module includes both static and dynamic ice loading that can be applied during a dynamic simulation of the response of an offshore wind turbine. The ice forces can be prescribed, or influenced by the structure’s compliant response, or by the dynamics of both the structure and the ice floe. The new module covers ice failure modes of spalling, buckling, crushing, splitting, and bending. The supporting structure of wind turbines can be modeled as a vertical or sloping form at the waterline. The Inward Battered Guide Structure (IBGS) foundation designed by Keystone Engineering for the Great Lakes was used to study the ice models coupled to FAST8. The IBGS foundation ice loading simulations in FAST8 were compared to the baseline simulation case without ice loading. The ice conditions reflecting those from Lake Huron at Port Huron and Lake Michigan at North Manitou were studied under near rated wind speed of 12 m/s for the NREL 5-MW reference turbine. Simulations were performed on ice loading models 1 through 4 and ice model 6 with their respective sub-models. The purpose of ice model 5 is to investigate ice loading on sloping structures such as ice-cones on a monopile and is not suitable for multi-membered jacketed structures like the IBGS foundation. The key response parameters from the simulations, shear forces and moments from the tower base and IBGS foundation base, were compared. Ice models 1 and 6 do not significantly affect the tower fore-aft shear and moment. However, ice model 2 (dynamic analyses), model 3 (random ice loading), and model 4 (multiple ice failure zone loading) show increased effect on the tower fore-aft shear and moment with significant effect from ice model 3.1. In general ice loading creates large reaction forces and moments at the base of the IBGS foundation; the largest occurred in model 1.1 (steady creep ice indentation loading) followed by model 3.1 (random creep ice indentation loading). In general the power production from the ice loading cases had little deviation from the baseline case without ice loading. For ultimate limit state (ULS), ice model 1.1 ice and 3.1 appear to be the ice most critical models to consider at an early stage of design. Ice model 4 is an important tool for assessing structural fatigue.
Halo modelling in chameleon theories
We analyse modelling techniques for the large-scale structure formed in scalar-tensor theories of constant Brans-Dicke parameter which match the concordance model background expansion history and produce a chameleon suppression of the gravitational modification in high-density regions. Thereby, we use a mass and environment dependent chameleon spherical collapse model, the Sheth-Tormen halo mass function and linear halo bias, the Navarro-Frenk-White halo density profile, and the halo model. Furthermore, using the spherical collapse model, we extrapolate a chameleon mass-concentration scaling relation from a ΛCDM prescription calibrated to N-body simulations. We also provide constraints on the model parameters to ensure viability on local scales. We test our description of the halo mass function and nonlinear matter power spectrum against the respective observables extracted from large-volume and high-resolution N-body simulations in the limiting case of f(R) gravity, corresponding to a vanishing Brans-Dicke parameter. We find good agreement between the two; the halo model provides a good qualitative description of the shape of the relative enhancement of the f(R) matter power spectrum with respect to ΛCDM caused by the extra attractive gravitational force but fails to recover the correct amplitude. Introducing an effective linear power spectrum in the computation of the two-halo term to account for an underestimation of the chameleon suppression at intermediate scales in our approach, we accurately reproduce the measurements from the N-body simulations.
Neutron spectroscopic factors of {sup 34}Ar and {sup 46}Ar from (p,d) transfer reactions
Single-neutron-transfer measurements using (p,d) reactions have been performed at 33 MeV per nucleon with proton-rich {sup 34}Ar and neutron-rich {sup 46}Ar beams in inverse kinematics. The extracted spectroscopic factors are compared to the large-basis shell-model calculations. Relatively weak quenching of the spectroscopic factors is observed between {sup 34}Ar and {sup 46}Ar. The experimental results suggest that neutron correlations have a weak dependence on the asymmetry of the nucleus over this isotopic region. The present results are consistent with the systematics established from extensive studies of spectroscopic factors and dispersive optical-model analyses of {sup 40-49}Ca isotopes. They are, however, inconsistent with the trends obtained in knockout-reaction measurements.
The Coupled Influence of Thermal Physiology and Biotic Interactions on the Distribution and Density of Ant Species along an Elevational Gradient
A fundamental tenet of biogeography is that abiotic and biotic factors interact to shape the distributions of species and the organization of communities, with interactions being more important in benign environments, and environmental filtering more important in stressful environments. This pattern is often inferred using large databases or phylogenetic signal, but physiological mechanisms underlying such patterns are rarely examined. We focused on 18 ant species at 29 sites along an extensive elevational gradient, coupling experimental data on critical thermal limits, null model analyses, and observational data of density and abundance to elucidate factors governing species’ elevational range limits. Thermal tolerance data showed that environmental conditions were likely to be more important in colder, more stressful environments, where physiology was the most important constraint on the distribution and density of ant species. Conversely, the evidence for species interactions was strongest in warmer, more benign conditions, as indicated by our observational data and null model analyses. Our results provide a strong test that biotic interactions drive the distributions and density of species in warm climates, but that environmental filtering predominates at colder, high-elevation sites. Such a pattern suggests that the responses of species to climate change are likely to be context-dependent and more specifically, geographically-dependent.
Modeling and Analysing the Impact of Heat Pump Water Heaters on Distribution Systems Using GridLAB-D
With the constant increase in energy demand, finding ways to reduce peak load and the energy-costs factors has become more imperative. Domestic water heating showcases a significant opportunity for such applications. Water heating is the second-highest energy consumer in the residential sector across the United States. Electric Water Heaters (EWHs), in particular, constitute nearly 43% of American household water heating energy consumption. Heat Pump Water Heater (HPWH), on the other hand, are an advanced water heating technology that has recently emerged in the United States residential market. The objectives of this work are to develop a HPWH model and build a case study that evaluates various penetration levels of HPWH in providing reduced peak load and cost-effective energy savings for both utilities and customers. The HPWH model was developed and integrated within the GridLAB-D simulation environment. The model behavior was then validated against a real HPWH unit at Portland State University (PSU). The case studies incorporated five HPWH penetration levels, ranging from 20% to 100%. In each case, EWHs were replaced with HPWHs. The results showed that a high penetration level of HPWHs can reduce the energy consumption on a distribution system to 38%.
Spectrophotometric and model-atmosphere analyses of the hot DO and DAO white dwarfs from the Palomar-Green survey
Recent optical and spectrophotometric observations of all currently known DAO and DO hot white dwarf candidates from the Palomar-Green Survey are presented. The optical observations were carried out using the Kitt Peak National Observatory Intensified Image Dissector Scanner (IIDS) system, the Multiple Mirror Telescope (MMT), and two photon-counting Reticon systems. Ultraviolet spectrophotometry was obtained using the International Ultraviolet Explorer (IUE) short-wavelength and long-wavelength cameras. The following spectroscopic subgroups were identified in the observations: the cool DO stars with spectra showing H I features together with He II + H blends; the hot DO stars, with spectra exhibiting weak He II (+H) lines; and hydrogen-rich DAO stars with broad H lines and sharp H II lines at 4686 A. A fourth subgroup of stars resembling PG 1159 with He at He II lines at 4686, and a C, N ion blend in the optical spectrum were also found. The spectroscopic data were analyzed in terms of a grid of hot, high-gravity LTE model atmospheres composed of a mixture of hydrogen and helium, and atmospheric parameters are deduced for each class of objects. On the basis of the model atmosphere analysis, the local space density of the DO stars is estimated to be 1.9-3.0 x 10 to the -7th per cubic pc, depending on the scale height.
Characterization of the Triassic Newark Basin of New York and New Jersey for geologic storage of carbon dioxide
The Newark Basin is a Triassic-aged rift basin underlying densely populated, industrialized sections of New York, New Jersey and Pennsylvania. The Basin is an elongate half-graben encompassing an area of more than 7,510 square-kilometers (2,900 square-miles), and could represent a key storage component for commercial scale management of carbon dioxide emissions via geologic sequestration. The project team first acquired published reports, surface and subsurface maps, and seismic data, which formed the basis for a three-dimensional model framework for the northern end of the Basin incorporating stratigraphic, hydrologic, and water quality data. Field investigations included drilling, coring, and logging of two stratigraphic test borings in Clarkstown, NY (Exit 14 Tandem Lot Well No. 1), drilled to a depth of 2,099 meters (6,885 feet); and Palisades, NY (Lamont-Doherty Earth Observatory Test Well No. 4) drilled to a depth of 549 meters (1,802 feet). Two two-dimensional seismic reflection data lines arrayed perpendicularly were acquired by Schlumberger/WesternGeco to help characterize the structure and stratigraphy and as part of pre-drilling field screening activities for the deep stratigraphic borehole. A total of 47 meters (155 feet) of continuous whole core was recovered from the Tandem Lot boring from depths of 1,393 meters (4,570 feet) to 1,486 meters (4,877 feet). Twenty-five horizontal rotary cores were collected in mudstones and sandstones in the surface casing hole and fifty-two cores were taken in various lithologies in the deep borehole. Rotary core plugs were analyzed by Weatherford Laboratories for routine and advanced testing. Rotary core plug trim end thin sections were evaluated by the New York State Museum for mineralogical analysis and porosity estimation. Using core samples, Lawrence Berkley National Laboratory designed and completed laboratory experiments and numerical modeling analyses to characterize the dissolution and reaction of carbon dioxide with formation brine and minerals, and resulting effects on injection rate, pressure, effective storage volume, and carbon dioxide migration within a prospective sandstone reservoir. $$Three potential porous and permeable sandstone units were identified in the Passaic Formation at the New York State Thruway Exit 14 location. Potential Flow Unit 1, at a depth of 643 meters (2,110 feet) to 751 meters (2,465 feet); Potential Flow Unit 2 at a depth of 853 meters (2,798 feet) to 1,000 meters (3,280 feet); and Potential Flow Unit 3, at a depth of 1,114 meters (3,655 feet) to 1,294 meters (4,250 feet). Reactive transport simulations of interactions between carbon dioxide, brine and formation minerals were carried out to evaluate changes in formation water chemistry, mineral precipitation and dissolution reactions, and any potential resulting effects on formation permeability. The experimental and modeling analyses suggest that mineral precipitation and dissolution reactions (within the target formation) are not expected to lead to significant changes to the underground hydrologic system over time frames (~30 years) typically relevant for carbon dioxide injection operations. Key findings of this basin characterization study include an estimate of carbon dioxide storage capacity in the Newark Basin. Assuming an average porosity of twelve percent and an aquifer volume of 6.1E+12 meters3, calculated ranges of likely storage capacity range from 1.9 – 20.2 gigatonnes under high temperature (low carbon dioxide density) conditions; and 2.9 – 30.2 gigatonnes under low temperature (low carbon dioxide density) conditions. Intra-basin faulting, geometry of the Palisades Sill, and the presence of altered meta-sediments above and below the Sill, increase potential compartmentalization within the basin. A structural/stratigraphic trap type may occur where porous/permeable sediments are cross-cut by the Palisades Sill. Potential injection intervals are present within the Stockton Formation of the Newark Basin. Additional porous/permeable intervals may be present within sandstones of the Passaic Formation, increasing projected storage capacity. Deeper wedges of strata are likely present in the deeper portions of the basin in southern New York and into northern New Jersey. Abundant mudstones are present in the Passaic, Lockatong, and Stockton Formations. These intervals have the requisite petrophysical properties to form effective primary and secondary containment intervals to industrial-scale sequestration of carbon dioxide in the Newark Basin. Hydro-thermally altered meta-sediments in the region immediately surrounding the top and base of the Palisades Sill is devoid of porosity/permeability and forms an additional effective lateral/vertical sealing cap rock.
NASA Goddard Giovanni Support for YOTC
The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been twofold: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. In regards to the second challenge, it should be stressed that this problem will not be solved through the production and examination of one or a few high quality long-term records of fundamental quantities (e.g., SST, water vapor, cloud fraction). Rather, an alternative and more comprehensive paradigm is needed, one that integrates the multitude of applicable resources and measures of tropical convection in a manner that that can be better utilized by the diagnostic, modeling and forecasting communities to more completely and coherently focus on the problem.Because the goal of YOTC involves examining a scientifically complex, multi-scale process , rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO). The proposed dissemination framework for the YOTC satellite data archive is based on the Giovanni system. Giovanni is a web-based application developed by the NASA Goddard Earth Science (GES) Data and Information Service Center (DISC) that provides a simple and intuitive way to visualize, analyze, and access/download vast amounts of Earth science remote sensing data. A prototype YOTC Giovanni System (hereafter YOTC-GS) is in the process of being developed. YOTC-GS will provide access to level 2 (i.e. swath level data) and/or level 3 (i.e. gridded/mapped data) forms of satellite data, the choice or both depending on what is appropriate and relevant. The former is needed and better suited for detailed process examination, exploiting the highest temporal-spatial resolutions available and comparison to regional cloud-system resolving model / cloud resolving model (CSRM/CRM) model output. The latter is needed and more well suited for examination of phenomena, conditions and processes on large to global scales, and for comparisons to global model analyses, prediction and simulation output.
Elements of complexity in subsurface modeling, exemplified with three case studies
There are complexity elements to consider when applying subsurface flow and transport models to support environmental analyses. Modelers balance the benefits and costs of modeling along the spectrum of complexity, taking into account the attributes of more simple models (e.g., lower cost, faster execution, easier to explain, less mechanistic) and the attributes of more complex models (higher cost, slower execution, harder to explain, more mechanistic and technically defensible). In this paper, modeling complexity is examined with respect to considering this balance. The discussion of modeling complexity is organized into three primary elements: 1) modeling approach, 2) description of process, and 3) description of heterogeneity. Three examples are used to examine these complexity elements. Two of the examples use simulations generated from a complex model to develop simpler models for efficient use in model applications. The first example is designed to support performance evaluation of soil vapor extraction remediation in terms of groundwater protection. The second example investigates the importance of simulating different categories of geochemical reactions for carbon sequestration and selecting appropriate simplifications for use in evaluating sequestration scenarios. In the third example, the modeling history for a uranium-contaminated site demonstrates that conservative parameter estimates were inadequate surrogates for complex, critical processes and there is discussion on the selection of more appropriate model complexity for this application. All three examples highlight how complexity considerations are essential to create scientifically defensible models that achieve a balance between model simplification and complexity.
Monte Carlo modeling and analyses of YALINA booster subcritical assembly, Part III : low enriched uranium conversion analyses.
This study investigates the performance of the YALINA Booster subcritical assembly, located in Belarus, during operation with high (90%), medium (36%), and low (21%) enriched uranium fuels in the assembly's fast zone. The YALINA Booster is a zero-power, subcritical assembly driven by a conventional neutron generator. It was constructed for the purpose of investigating the static and dynamic neutronics properties of accelerator driven subcritical systems, and to serve as a fast neutron source for investigating the properties of nuclear reactions, in particular transmutation reactions involving minor-actinides. The first part of this study analyzes the assembly's performance with several fuel types. The MCNPX and MONK Monte Carlo codes were used to determine effective and source neutron multiplication factors, effective delayed neutron fraction, prompt neutron lifetime, neutron flux profiles and spectra, and neutron reaction rates produced from the use of three neutron sources: californium, deuterium-deuterium, and deuterium-tritium. In the latter two cases, the external neutron source operates in pulsed mode. The results discussed in the first part of this report show that the use of low enriched fuel in the fast zone of the assembly diminishes neutron multiplication. Therefore, the discussion in the second part of the report focuses on finding alternative fuel loading configurations that enhance neutron multiplication while using low enriched uranium fuel. It was found that arranging the interface absorber between the fast and the thermal zones in a circular rather than a square array is an effective method of operating the YALINA Booster subcritical assembly without downgrading neutron multiplication relative to the original value obtained with the use of the high enriched uranium fuels in the fast zone.
Deterministic and Monte Carlo modeling and analyses of YALINA-THERMAL subcritical assembly.
Abstract not provided
THERMAL-FLUIDS ANALYSES OF MODEL 9977 AND 9975 SHIPPING PACKAGES UNDER NORMAL AND HAZARD ANALYSIS CONDITIONS
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Nonnegative tensor factorization for contaminant source identification
Unsupervised Machine Learning (ML) is becoming increasingly popular for solving various types of data analytics problems including feature extraction, blind source separation, exploratory analyses, model diagnostics, etc. In this work, we have developed a new unsupervised ML method based on Nonnegative Tensor Factorization (NTF) for identification of the original groundwater types (including contaminant sources) present in geochemical mixtures observed in an aquifer. Frequently, groundwater types with different geochemical signatures are related to different background and/or contamination sources. The characterization of groundwater mixing processes is a challenging but very important task critical for any environmental management project aiming to characterize the fate and transport of contaminants in the subsurface and perform contaminant remediation. This task typically requires solving complex inverse models representing groundwater flow and geochemical transport in the aquifer, where the inverse analysis accounts for available site data. Usually, the model is calibrated against the available data characterizing the spatial and temporal distribution of the observed geochemical types. Numerous different geochemical constituents and processes may need to be simulated in these models which further complicates the analyses. Additionally, the application of inverse methods may introduce biases in the analyses through the assumptions made in the model development process. Here, we substitute the model inversion with unsupervised ML analysis. The ML analysis does not make any assumptions about underlying physical and geochemical processes occurring in the aquifer. Our ML methodology, called NTFk, is capable of identifying (1) the unknown number of groundwater types (contaminant sources) present in the aquifer, (2) the original geochemical concentrations (signatures) of these groundwater types and (3) spatial and temporal dynamics in the mixing of these groundwater types. These results are obtained only from the measured geochemical data without any additional site information. In general, the NTFk methodology allows for interpretation of large high-dimensional datasets representing diverse spatial and temporal components such as state variables and velocities. NTFk has been tested on synthetic and real-world site three-dimensional datasets. Finally, the NTFk algorithm is designed to work with geochemical data represented in the form of concentrations, ratios (of two constituents; for example, isotope ratios), and delta notations (standard normalized stable isotope ratios).
LDEF geometry/mass model for radiation analyses
A three-dimensional geometry/mass model of LDEF is under development for ionizing radiation analyses. This model, together with ray tracing algorithms, is being programmed for use both as a stand alone code in determining three-dimensional shielding distributions at dosimetry locations and as a geometry module that can be interfaced with radiation transport codes.