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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate

Abstract Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Advancing South American Water and Climate Science Through Multi-Decadal Convection-Permitting Modeling

The South America Affinity Group (SAAG) was established in early 2019 by the National Center for Atmospheric Research (NCAR) Water Systems Program as a community effort focused on improving hydroclimate science over South America. SAAG supports large research efforts such as the ANDEX Regional Hydroclimate Program as well as individual research groups. The group started with a dozen members and quickly grew to over 100 participants from more than ten countries. For the past four years, the SAAG has been meeting online every two weeks and has organized sessions at international conferences such as the American Geophysical Union Fall Meeting and the Convection-Permitting Climate Workshop. At the core of the SAAG effort are two multi-decadal convection permitting (CP) model simulations with 4-km grid spacing for historical and future climates over the South American continent. Additionally, a major observational data collection effort has been undertaken, including in-situ station data from South American meteorological and water services, gridded products, satellite-based observations, and field campaign data. In conclusion, this article discusses the research needs and scientific goals that drive this community of scientists with diverse backgrounds and interests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Will There Be a Significant Change to El Niño in the Twenty-First Century?

The El Niño–Southern Oscillation (ENSO) response to anthropogenic climate change is assessed in the following 1° nominal resolution Community Climate System Model, version 4 (CCSM4) Coupled Model Intercomparison Project phase 5 (CMIP5) simulations: twentieth-century ensemble, preindustrial control, twenty-first-century projections, and stabilized 2100–2300 “extension runs.” ENSO variability weakens slightly with CO 2 ; however, various significance tests reveal that changes are insignificant at all but the highest CO 2 levels. Comparison with the 1850 control simulation suggests that ENSO changes may become significant on centennial time scales; the lack of signal in the twentieth- versus twenty-first-century ensembles is due to their limited duration. Changes to the mean state are consistent with previous studies: a weakening of the subtropical wind stress curl, an eastward shift of the tropical convective cells, a reduction in the zonal SST gradient, and an increase in vertical thermal stratification take place as CO 2 increases. The extratropical thermocline deepens throughout the twenty-first century, with the tropical thermocline changing slowly in response. The adjustment time scale is set by the relevant ocean dynamics, and the delay in its effect on ENSO variability is not diminished by increasing ensemble size. The CCSM4 results imply that twenty-first-century simulations may simply be too short for identification of significant tropical variability response to climate change. An examination of atmospheric teleconnections, in contrast, shows that the remote influences of ENSO do respond rapidly to climate change in some regions, particularly during boreal winter. Finally, this suggests that changes to ENSO impacts may take place well before changes to oceanic tropical variability itself become significant.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

AMIP Simulation with the CAM4 Spectral Element Dynamical Core

We evaluate the climate produced by the Community Earth System Model, version 1, running with the new spectral-element atmospheric dynamical core option. The spectral-element method is congured to use a cubed-sphere grid, providing quasi-uniform resolution over the sphere, increased parallel scalability and removing the need for polar filters. It uses a fourth order accurate spatial discretization which locally conserves mass and moist total energy. Using the Atmosphere Model Intercomparison Project protocol, we compare the results from the spectral-element dy- namical core with those produced by the default nite-volume dynamical core and with observations.

CAM-SE↗
DOE OSTI2013

The Mean Climate of the Community Atmosphere Model (CAM4) in Forced SST and Fully Coupled Experiments

The Community Atmosphere Model, version 4 (CAM4), was released as part of the Community Climate System Model, version 4 (CCSM4). The finite volume (FV) dynamical core is now the default because of its superior transport and conservation properties. Deep convection parameterization changes include a dilute plume calculation of convective available potential energy (CAPE) and the introduction of convective momentum transport (CMT). An additional cloud fraction calculation is now performed following macrophysical state updates to provide improved thermodynamic consistency. A freeze-drying modification is further made to the cloud fraction calculation in very dry environments (e.g., the Arctic), where cloud fraction and cloud water values were often inconsistent in CAM3. In CAM4 the FV dynamical core further degrades the excessive trade-wind simulation, but reduces zonal stress errors at higher latitudes. Plume dilution alleviates much of the midtropospheric tropical dry biases and reduces the persistent monsoon precipitation biases over the Arabian Peninsula and the southern Indian Ocean. CMT reduces much of the excessive trade-wind biases in eastern ocean basins. CAM4 shows a global reduction in cloud fraction compared to CAM3, primarily as a result of the freeze-drying and improved cloud fraction equilibrium modifications. Regional climate feature improvements include the propagation of stationary waves from the Pacific into midlatitudes and the seasonal frequency of Northern Hemisphere blocking events. A 1° versus 2° horizontal resolution of the FV dynamical core exhibits superior improvements in regional climate features of precipitation and surface stress. Finally, improvements in the fully coupled mean climate between CAM3 and CAM4 are also more substantial than in forced sea surface temperature (SST) simulations.

cloud fraction calculation↗
DOE OSTI2014

Exploratory High-Resolution Climate Simulations using the Community Atmosphere Model (CAM)

Extended, high-resolution (0.23° latitude × 0.31° longitude) simulations with Community Atmosphere Model versions 4 and 5 (CAM4 and CAM5) are examined and compared with results from climate simulations conducted at a more typical resolution of 0.9° latitude × 1.25° longitude. Overall, the simulated climate of the high-resolution experiments is not dramatically better than that of their low-resolution counterparts. Improvements appear primarily where topographic effects may be playing a role, including a substantially improved summertime Indian monsoon simulation in CAM4 at high resolution. Significant sensitivity to resolution is found in simulated precipitation over the southeast United States during winter. Some aspects of the simulated seasonal mean precipitation deteriorate notably at high resolution. Prominent among these is an exacerbated Pacific “double ITCZ” bias in both models. Nevertheless, while large-scale seasonal means are not dramatically better at high resolution, realistic tropical cyclone (TC) distributions are obtained. Some skill in reproducing interannual variability in TC statistics also appears.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

ENSO-Induced Teleconnection: Process-Oriented Diagnostics to Assess Rossby Wave Sources and Ambient Flow Properties in Climate Models

Climate model fidelity in representing ENSO-induced teleconnection is assessed with process-oriented diagnostics that examine a chain of processes, from equatorial Pacific precipitation to the midlatitude circulation pattern over the Pacific–North American regions. Such processes are rarely addressed during model development. Using an upper-tropospheric divergent level, local vorticity gradient of the ambient zonal flow (∂ 2 U¯/∂y 2 ) and a restoring force for Rossby waves (β * ) are estimated, the equivalent barotropic vorticity equation is solved, and an anomalous Rossby wave source (RWS') quantified. The analysis is applied to AMIP5 and AMIP6 simulations. For a realistic circulation response representation, the hypothesis that models accurately represent the strength and location of RWS', and spatial variations in β * is tested. Compared to AMIP5, in AMIP6 there are clear improvements in representing RWS' and β * . To validate the hypothesis, the analysis identifies two metrics: spatially coherent RWS' in the subtropical North Pacific, and longitudes of negative β * over the western-central North Pacific. By projecting these metrics in two and three-dimensional views, improvements or degradations in model versions are apparent. If a model’s fidelity in representing ∂ 2 U¯/∂y 2 and RWS' are compromised, then radiated Rossby waves are reflected more equatorward, resulting in zonally elongated circulation anomalies over the central North Pacific. Thus, during climate model development, applying this analysis frequently will keep a regular check on the fidelity of the modeled response to anomalous El Niño convection in conjunction with changing model ambient flow dependencies. As a result, this analysis is intended to form a process-oriented diagnostics package, a community contribution to the NOAA Model Diagnostics Task Force.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modes of Variability in E3SM and CESM Large Ensembles

An adequate characterization of internal modes of climate variability (MoV) is a prerequisite for both accurate seasonal predictions and climate change detection and attribution. Assessing the fidelity of climate models in simulating MoV is therefore essential; however, doing so is complicated by the large intrinsic variations in MoV and the limited span of the observational record. Large ensembles (LEs) provide a unique opportunity to assess model fidelity in simulating MoV and quantify intermodel contrasts. Here, in this work, these goals are pursued in four recently produced LEs: the Energy Exascale Earth System Model (E3SM) versions 1 and 2 LEs, and the Community Earth System Model (CESM) versions 1 and 2 LEs. In general, the representation of global coupled modes is found to improve across successive E3SM and CESM versions in conjunction with the fidelity of the base state climate while the patterns of extratropical modes are well simulated across the ensembles. Various persistent shortcomings for all MoV are however identified and discussed. The results both demonstrate the successes of these recent model versions and suggest the potential for continued improvement in the representation of MoV with advances in model physics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Identification of Uranium Minerals in Natural U-Bearing Rocks Using Infrared Reflectance Spectroscopy

The identification of minerals, including uranium-bearing minerals, is traditionally a labor-intensive-process using x-ray diffraction (XRD), fluorescence, or other solid-phase and wet chemical techniques. While handheld XRD and fluorescence instruments can aid in field identification, handheld infrared reflectance spectrometers can also be used in industrial or field environments, with rapid, non-destructive identification possible via spectral analysis of the solid’s reflectance spectrum. We have recently developed standard laboratory measurement methods for the infrared (IR) reflectance of solids and have investigated using these techniques for the identification of uranium-bearing minerals, using XRD methods for ground-truth. Due to the rich colors of such species, including distinctive spectroscopic signatures in the infrared, identification is facile and specific, both for samples that are pure or are partially composed of uranium (e.g. boltwoodite, schoepite, tyuyamunite, carnotite, etc.) or non-uranium minerals. The method can be used to detect not only pure and partial minerals, but is quite sensitive to chemical change such as hydration (e.g. schoepite). We have further applied statistical methods, in particular classical least squares (CLS) and multivariate curve resolution (MCR) for discrimination of such uranium minerals and two uranium pure chemicals (U3O8 and UO2) against common background materials (e.g. silica sand, asphalt, calcite, K-feldspar) with good success. Each mineral contains unique infrared spectral features; some of the IR features are similar or common to entire classes of minerals, typically arising from similar chemical moieties or functional groups in the minerals: phosphates, sulfates, carbonates, etc. These characteristic 2 infrared bands generate the unique (or class-specific) bands that distinguish the mineral from the interferents or backgrounds. We have observed several cases where the chemical moieties that provide the spectral discrimination in the longwave IR do so by generating upward-going reststrahlen bands in the reflectance data, but the same minerals have other weaker (overtone) bands, sometimes from the same chemical groups, that are manifest as downward-going transmission-type features in the midwave and shortwave infrared.

Beiswenger, Toya N.↗
DOE OSTI2023

An Interactive Spectral Analysis Tool for Chemical Identification and Quantification of Gas-Phase Species in Complex Spectra

A spectral analysis tool has been developed to interactively identify and quantify individual gas-phase species from complex infrared absorbance spectra obtained from laboratory or field data. The SpecQuant program has an intuitive graphical interface that accommodates both reference and experimental data with varying resolution and instrumental lineshape, as well as algorithms to readily align the wavenumber axis of a sample spectrum with the raster of a reference spectrum. Using a classical least squares model in conjunction with reference spectra such as those from the Pacific Northwest National Laboratory (PNNL) gas-phase infrared database or simulated spectra derived from the HITRAN line-by-line database, the mixing ratio of each identified species is determined along with its associated estimation error. After correcting the wavelength and intensity of the field data, SpecQuant displays the calculated mixing ratio versus the experimental data for each analyte along with the residual spectrum with any or all analyte fits subtracted for visual inspection of the fit and residuals. The software performance for multianalyte quantification was demonstrated using moderate resolution (0.5 cm –1 ) infrared spectra that were collected during the time-resolved infrared photolysis of methyl iodide.

Thompson, Christopher J.↗
DOE OSTI2021

Exascale models of stellar explosions: Quintessential multi-physics simulation

The ExaStar project aims to deliver an efficient, versatile, and portable software ecosystem for multi-physics astrophysics simulations run on exascale machines. The code suite is a component-based multi-physics toolkit, built on the capabilities of current simulation codes (in particular Flash-X and Castro), and based on the massively parallel adaptive mesh refinement framework AMReX. It includes modules for hydrodynamics, advanced radiation transport, thermonuclear kinetics, and nuclear microphysics. The code will reach exascale efficiency by building upon current multi- and many-core packages integrated into an orchestration system that uses a combination of configuration tools, code translators, and a domain-specific asynchronous runtime to manage performance across a range of platform architectures. The target science includes multi-physics simulations of astrophysical explosions (such as supernovae and neutron star mergers) to understand the cosmic origin of the elements and the fundamental physics of matter and neutrinos under extreme conditions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

ORCHA: A performance portability system for extreme heterogeneity

Heterogeneity is the prevalent trend in the rapidly evolving high-performance computing (HPC) landscape in both hardware and application software. The diversity in hardware platforms, currently comprising various accelerators and a future possibility of specializable chiplets, poses a significant challenge for scientific software developers aiming to harness optimal performance across different computing platforms while maintaining the quality of solutions when their applications are simultaneously growing more complex. Code synthesis and code generation can provide mechanisms to mitigate this challenge. We have developed a divide and conquer approach where different aspects of performance are handled by different stand-alone tools that are interfaced with the application through generated code. This portability system, ORCHA, enables users to configure and orchestrate their computations among available resources on a platform by specifying a high-level recipe, thereby permitting a many-to-many paradigm where each recipe results in a different variant of the application. The core design goal is to let users decide the application’s hardware mapping and orchestration by editing only the high-level recipe—without modifying the maintained source code or binding the application to a particular runtime system. Tools in ORCHA distribution are: CG-Kit for translating the recipe into an execution graph; Milhoja to execute the graph by orchestrating data and task movement among hardware resources; and Macroprocessor that enables users to define their own code-shorthand for higher composability and easier management of code variants. Additionally, the design of ORCHA permits tools to work in a plug-and-play mode where the application can build and run without CG-Kit and Milhoja, and either tool can be swapped out for other tools with similar capabilities by modifying the code generation portion of ORCHA. In this paper, we describe the design of ORCHA and the role that code-generation plays in isolating applications from tools. We demonstrate the breadth of configurations ORCHA enables with a case study in which an application configuration is realized on three distinct hardware mappings—a GPU-centric, a CPU/GPU balanced, and a CPU/GPU concurrent layouts by using different recipes.

Lee, Youngjun↗
DOE OSTI2020

Vibro-acoustic modulation and data fusion for localizing alkali–silica reaction–induced damage in concrete

This article investigates the application of vibro-acoustic modulation testing for diagnosing damage in concrete structures. The vibro-acoustic modulation technique employs two excitation frequencies on a structure. The interaction of these excitations in the measured response indicates damage through the presence of sidebands in the frequency spectra. Past studies using this technique have mostly focused on metals and composites (thin plates or laminates). Our research focuses on concrete, which is a highly heterogeneous material susceptible to a variety of chemical, physical, and mechanical damage processes. In particular, this article investigates diagnosing cracking in concrete from an expansive gel produced by an alkali–silica reaction in the presence of moisture. Past studies have been limited to damage detection using vibro-acoustic modulation testing, whereas this article extends the technique to damage localization. A cement slab with pockets of reactive aggregate is used to investigate the diagnosis technique. The effects of different testing parameters, such as locations, magnitudes, and frequencies of the two excitations, are analyzed and incorporated in the damage localization methodology. A Bayesian probabilistic methodology is developed to fuse the information from multiple test configurations in order to construct damage probability maps for the test specimen. The results of vibro-acoustic modulation–based damage localization are validated by petrographic study of cores taken from the slab.

Karve, Pranav↗
DOE OSTI2016

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

Here, gene fusions are the most powerful type of in silico -derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli ; (ii) 131 fusions found in B vitamin metabolism. These sets were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Modeling central metabolism and energy biosynthesis across microbial life

Here, automatically generated bacterial metabolic models, and even some curated models, lack accuracy in predicting energy yields due to poor representation of key pathways in energy biosynthesis and the electron transport chain (ETC). Further compounding the problem, complex interlinking pathways in genome-scale metabolic models, and the need for extensive gapfilling to support complex biomass reactions, often results in predicting unrealistic yields or unrealistic physiological flux profiles. As a result, to overcome this challenge, we developed methods and tools to build high quality core metabolic models (CMM) representing accurate energy biosynthesis based on a well studied, phylogenetically diverse set of model organisms. We compare these models to explore the variability of core pathways across all microbial life, and by analyzing the ability of our core models to synthesize ATP and essential biomass precursors, we evaluate the extent to which the core metabolic pathways and functional ETCs are known for all microbes. 6,600 (80 %) of our models were found to have some type of aerobic ETC, whereas 5,100 (62 %) have an anaerobic ETC, and 1,279 (15 %) do not have any ETC. Using our manually curated ETC and energy biosynthesis pathways with no gapfilling at all, we predict accurate ATP yields for nearly 5586 (70 %) of the models under aerobic and anaerobic growth conditions. This study revealed gaps in our knowledge of the central pathways that result in 2,495 (30 %) CMMs being unable to produce ATP under any of the tested conditions. We then established a methodology for the systematic identification and correction of inconsistent annotations using core metabolic models coupled with phylogenetic analysis. In conclusion, we predict accurate energy yields based on our improved annotations in energy biosynthesis pathways and the implementation of diverse ETC reactions across the microbial tree of life. We highlighted missing annotations that were essential to energy biosynthesis in our models. We examine the diversity of these pathways across all microbial life and enable the scientific community to explore the analyses generated from this large-scale analysis of over 8000 microbial genomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Exome resequencing and GWAS for growth, ecophysiology, and chemical and metabolomic composition of wood of Populus trichocarpa

Populus trichocarpa is an important forest tree species for the generation of lignocellulosic ethanol. Understanding the genomic basis of biomass production and chemical composition of wood is fundamental in supporting genetic improvement programs. Considerable variation has been observed in this species for complex traits related to growth, phenology, ecophysiology and wood chemistry. Those traits are influenced by both polygenic control and environmental effects, and their genome architecture and regulation are only partially understood. Genome wide association studies (GWAS) represent an approach to advance that aim using thousands of single nucleotide polymorphisms (SNPs). Genotyping using exome capture methodologies represent an efficient approach to identify specific functional regions of genomes underlying phenotypic variation. We identified 813 K SNPs, which were utilized for genotyping 461 P. trichocarpa clones, representing 101 provenances collected from Oregon and Washington, and established in California. A GWAS performed on 20 traits, considering single SNP-marker tests identified a variable number of significant SNPs ( p -value < 6.1479E-8) in association with diameter, height, leaf carbon and nitrogen contents, and δ 15 N. The number of significant SNPs ranged from 2 to 220 per trait. Additionally, multiple-marker analyses by sliding-windows tests detected between 6 and 192 significant windows for the analyzed traits. The significant SNPs resided within genes that encode proteins belonging to different functional classes as such protein synthesis, energy/metabolism and DNA/RNA metabolism, among others. SNP-markers within genes associated with traits of importance for biomass production were detected. They contribute to characterize the genomic architecture of P. trichocarpa biomass required to support the development and application of marker breeding technologies.

09 BIOMASS FUELS↗