SEARCH · Engineering Papers

Results for “link resolvers”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Development of Automated Pipeline for Time-Resolved Link-Wise Vehicular Energy Consumption in the Chattanooga, TN Road Network

The Department of Energy (DOE) has shown strong interest in detecting energy inefficiencies in regional road networks, so as to derive energy consumed at a high spatial temporal resolution. We have developed a workflow to automate the estimation of time-resolved vehicular energy consumption over each link in a road network of interest. The road network used in the current work is centered around the city of Chattanooga, Tennessee and its bordering regions. Utilizing the most mature road network for the Chattanooga, TN region, vehicle speed & count data from TomTom in conjunction with machine learning methods, we have developed an automated pipeline to estimate energy consumption for every link in the network. The first step in the pipeline is ingesting vehicle probe counts and speed estimates from TomTom API. In the next step, the probe counts, speed profiles and other exogenous data (i.e. road types, weather data, ground-truth volume counts and more) were used as input to a supervised learning algorithm to estimate the number of vehicles throughout the entire region for each road segment. These volume estimates were then mapped to a unified road network that contained additional important information such as percentage change in gradient across a link, number of lanes and link lengths that are features in pre-trained single vehicle energy-consumption models available with the RouteE software developed at NREL. The per vehicle energy consumption on each road link predicted using appropriate RouteE vehicular models were multiplied by the volume estimate for the corresponding link over a given time period to predict energy consumed per link for the time interval of interest. Currently, work is underway to improve both the RouteE per vehicle energy estimate and the volume estimates derived from TomTom probe counts. We have also explored the correlation of the link-wise energy estimates with the features of the pre-trained RouteE machine learning model in order to gain insight into what factors contribute most to the link-wise energy consumption.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗

DOE OSTI2021

Employing Weibull Analysis and Weakest Link Theory to Resolve Crystalline Silicon PV Cell Strength Between Bare Cells and Reduced- and Full-Sized Modules

Weibull analysis and weakest link theory are employed to resolve the probability of crystalline silicon PV cell fracture when measured as bare cells and when stressed in reduced- and full-sized modules. Experimental results indicated that the characteristic cell strength is reduced by ~20% once packaged into the laminate of a one-cell module and loaded in four-point flexure (4PF). This experimental observation was shown consistent with a weakest link theory prediction that the strength limiting flaws reside on the surface of the cell's edge. Here, the analysis is ultimately extended to present the equivalent loading of four-cell modules by uniform pressure and 4PF and a uniformly loaded full-sized module and demonstrates that smaller, representative, modules must be loaded to a much higher level than their parent full-sized modules to achieve an equivalent probability for cell fracture.

14 SOLAR ENERGY↗

DOE OSTI2023

Genome-resolved correlation mapping links microbial community structure to metabolic interactions driving methane production from wastewater

Anaerobic digestion of municipal mixed sludge produces methane that can be converted into renewable natural gas. To improve economics of this microbial mediated process, metabolic interactions catalyzing biomass conversion to energy need to be identified. Here, we present a two-year time series associating microbial metabolism and physicochemistry in a full-scale wastewater treatment plant. By creating a co-occurrence network with thousands of time-resolved microbial populations from over 100 samples spanning four operating configurations, known and novel microbial consortia with potential to drive methane production were identified. Interactions between these populations were further resolved in relation to specific process configurations by mapping metagenome assembled genomes and cognate gene expression data onto the network. Prominent interactions included transcriptionally active Methanolinea methanogens and syntrophic benzoate oxidizing Syntrophorhabdus , as well as a Methanoregulaceae population and putative syntrophic acetate oxidizing bacteria affiliated with Bateroidetes (Tenuifilaceae) expressing the glycine cleavage bypass of the Wood–Ljungdahl pathway.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Elucidating Syntrophic Butyrate-Degrading Populations in Anaerobic Digesters Using Stable-Isotope-Informed Genome-Resolved Metagenomics

Linking the genomic content of uncultivated microbes to their metabolic functions remains a critical challenge in microbial ecology. Resolving this challenge has implications for improving our management of key microbial interactions in biotechnologies such as anaerobic digestion, which relies on slow-growing syntrophic and methanogenic communities to produce renewable methane from organic waste. In this study, we combined DNA stable-isotope probing (SIP) with genome-centric metagenomics to recover the genomes of populations enriched in 13 C after growing on [ 13 C]butyrate. Differential abundance analysis of recovered genomic bins across the SIP metagenomes identified two metagenome-assembled genomes (MAGs) that were significantly enriched in heavy [ 13 C]DNA. Phylogenomic analysis assigned one MAG to the genus Syntrophomonas and the other MAG to the genus Methanothrix. Metabolic reconstruction of the annotated genomes showed that the Syntrophomonas genome encoded all the enzymes for beta-oxidizing butyrate, as well as several mechanisms for interspecies electron transfer via electron transfer flavoproteins, hydrogenases, and formate dehydrogenases. The Syntrophomonas genome shared low average nucleotide identity (<95%) with any cultured representative species, indicating that it is a novel species that plays a significant role in syntrophic butyrate degradation within anaerobic digesters. The Methanothrix genome contained the complete pathway for acetoclastic methanogenesis, indicating that it was enriched in 13 C from syntrophic acetate transfer. This study demonstrates the potential of stable-isotope-informed genome-resolved metagenomics to identify in situ interspecies metabolic cooperation within syntrophic consortia important to anaerobic waste treatment as well as global carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Thermal cycling-driven microstructural changes of eutectic Al–Si phase change materials in SS304 containers revealed by multi-modal imaging

Aluminum-based Al–Si alloys are widely used as phase change materials (PCMs) in thermal energy storage (TES) systems owing to their high volumetric latent heat and superior thermal conductivity. However, their long-term reliability is limited by degradation processes that remain insufficiently understood. In this work, we employ a multimodal, correlative characterization framework to systematically resolve the degradation behavior of eutectic Al–Si PCMs in contact with SS304 containers under repeated thermal cycling. By integrating high-resolution electron microscopy, three-dimensional X-ray fluorescence (3D XRF) imaging, and differential scanning calorimetry (DSC), we directly link spatially resolved compositional and microstructural evolution to changes in thermophysical properties. The correlative analysis reveals that elemental leaching of Fe, Cr, and Ni from the stainless-steel container into the PCM drives the formation of intermetallic compounds (IMCs) both at the interface and within the bulk PCM, leading to pronounced compositional heterogeneity. These interfacial reactions and diffusion-induced transformations progressively destabilize the Al–Si eutectic, reducing the effective phase-transforming fraction. Consistent with these observations, DSC measurements show a decrease in melting temperature and latent heat of fusion with thermal cycling. These results underscore the critical influence of interfacial reactions and material compatibility on the stability, durability, and overall performance of Al–Si-based TES systems.

25 ENERGY STORAGE↗

DOE OSTI2024

A Vertically Resolved Canopy Improves Chemical Transport Model Predictions of Ozone Deposition to North Temperate Forests

Abstract Dry deposition is the second largest tropospheric ozone (O 3 ) sink and occurs through stomatal and nonstomatal pathways. Current O 3 uptake predictions are limited by the simplistic big‐leaf schemes commonly used in chemical transport models (CTMs) to parameterize deposition. Such schemes fail to reproduce observed O 3 fluxes over terrestrial ecosystems, highlighting the need for more realistic treatment of surface‐atmosphere exchange in CTMs. We address this need by linking a resolved canopy model (1D Multi‐Layer Canopy CHemistry and Exchange Model, MLC‐CHEM) to the GEOS‐Chem CTM and use this new framework to simulate O 3 fluxes over three north temperate forests. We compare results with in situ measurements from four field studies and with standalone, observationally constrained MLC‐CHEM runs to test current knowledge of O 3 deposition and its drivers. We show that GEOS‐Chem overpredicts observed O 3 fluxes across all four studies by up to 2×, whereas the resolved‐canopy models capture observed diel profiles of O 3 deposition and in‐canopy concentrations to within 10%. Relative humidity and solar irradiance are strong O 3 flux drivers over these forests, and uncertainties in those fields provide the largest remaining source of model deposition biases. Flux partitioning analysis shows that: (a) nonstomatal loss accounts for 60% of O 3 deposition on average; (b) in‐canopy chemistry makes only a small contribution to total O 3 fluxes; and (c) the CTM big‐leaf treatment overestimates O 3 ‐driven stomatal loss and plant phytotoxicity in these temperate forests by up to 7×. Results motivate the application of fully online vertically explicit canopy schemes in CTMs for improved O 3 predictions.

Vermeuel, Michael P. [Department of Soil, Water, a↗

DOE OSTI2022

Wildfire-dependent changes in soil microbiome diversity and function

Abstract Forest soil microbiomes have crucial roles in carbon storage, biogeochemical cycling and rhizosphere processes. Wildfire season length, and the frequency and size of severe fires have increased owing to climate change. Fires affect ecosystem recovery and modify soil microbiomes and microbially mediated biogeochemical processes. To study wildfire-dependent changes in soil microbiomes, we characterized functional shifts in the soil microbiota (bacteria, fungi and viruses) across burn severity gradients (low, moderate and high severity) 1 yr post fire in coniferous forests in Colorado and Wyoming, USA. We found severity-dependent increases of Actinobacteria encoding genes for heat resistance, fast growth, and pyrogenic carbon utilization that might enhance post-fire survival. We report that increased burn severity led to the loss of ectomycorrhizal fungi and less tolerant microbial taxa. Viruses remained active in post-fire soils and probably influenced carbon cycling and biogeochemistry via turnover of biomass and ecosystem-relevant auxiliary metabolic genes. Our genome-resolved analyses link post-fire soil microbial taxonomy to functions and reveal the complexity of post-fire soil microbiome activity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Linking Transient Voltage to Spatially-Resolved Luminescence Imaging to Understand Reliability of Perovskite Photovoltaics

In this work, we present a methodology to separate effects of perovskite device metastability from irreversible degradation, using stress/rest cycling under constant current bias while collecting a series of electroluminescence images and continuously monitoring voltage. We develop a simulation model and procedures for image processing to better understand the effects of ion parameters on the transient nature of voltage and evolving electroluminescence images.

electroluminescence↗

DOE OSTI2021

Linking Transient Voltage to Spatially-Resolved Luminescence Imaging to Understand Reliability of Perovskite Photovoltaics: Preprint

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2017

A compendium of multi-omic sequence information from the Saanich Inlet water column

Marine oxygen minimum zones (OMZs) are widespread regions of the ocean that are currently expanding due to global warming. While inhospitable to most metazoans, OMZs are hotspots for microbial mediated biogeochemical cycling of carbon, nitrogen and sulphur, contributing disproportionately to marine nitrogen loss and climate active trace gas production. Our current understanding of microbial community responses to OMZ expansion is limited by a lack of time-resolved data sets linking multi-omic sequence information (DNA, RNA, protein) to geochemical parameters and process rates. Here, we present six years of time-resolved multi-omic observations in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia, Canada that undergoes recurring changes in water column oxygenation status. This compendium provides a unique multi-omic framework for studying microbial community responses to ocean deoxygenation along defined geochemical gradients in OMZ waters.

Hawley, Alyse K. (ORCID:0000000235164043)↗

DOE OSTI2021

Finite-temperature many-body perturbation theory for electrons: Algebraic recursive definitions, second-quantized derivation, linked-diagram theorem, general-order algorithms, and grand canonical and canonical ensembles

A comprehensive and detailed account is presented for the finite-temperature many-body perturbation theory for electrons that expands in power series all thermodynamic functions on an equal footing. Algebraic recursions in the style of the Rayleigh–Schrödinger perturbation theory are derived for the grand potential, chemical potential, internal energy, and entropy in the grand canonical ensemble and for the Helmholtz energy, internal energy, and entropy in the canonical ensemble, leading to their sum-over-states analytical formulas at any arbitrary order. For the grand canonical ensemble, these sum-over-states formulas are systematically transformed to sum-over-orbitals reduced analytical formulas by the quantum-field-theoretical techniques of normal-ordered second quantization and Feynman diagrams extended to finite temperature. It is found that the perturbation corrections to energies entering the recursions have to be treated as a nondiagonal matrix, whose off-diagonal elements are generally nonzero within a subspace spanned by degenerate Slater determinants. They give rise to a unique set of linked diagrams—renormalization diagrams—whose resolvent lines are displaced upward, which are distinct from the well-known anomalous diagrams of which one or more resolvent lines are erased. A linked-diagram theorem is introduced that proves the size-consistency of the finite-temperature many-body perturbation theory at any order. General-order algorithms implementing the recursions establish the convergence of the perturbation series toward the finite-temperature full-configuration-interaction limit unless the series diverges. As a result, the normal-ordered Hamiltonian at finite temperature sheds light on the relationship between the finite-temperature Hartree–Fock and first-order many-body perturbation theories.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

On the Network Topology of Cross-Linked Acrylate Photopolymers: A Molecular Dynamics Case Study

A reactive molecular dynamics approach is used to simulate cross-linking of acrylate polymer networks. By employing the same force field and reactive scheme and studying three representative multifunctional acrylate monomers, we isolate the importance of the nonreactive moieties within these model monomers. Analyses of reactive trajectories benchmark the estimated gel points, cyclomatic character, and spatially resolved cross-linking tendencies of the acrylates as a function of conversion. The insights into the similarities and differences of the polymerization and resulting networks presented here suggest molecular mechanics as a useful tool in the rational design of photopolymerization resins.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Characteristics of Wetting-Induced Bacteriophage Blooms in Biological Soil Crust

Biological soil crusts (biocrusts) are photosynthetic “hot spots” in deserts and cover ~12% of the Earth’s terrestrial surface, and yet they face an uncertain future given expected shifts in rainfall events. Laboratory wetting of biocrust communities is known to cause a bloom of Firmicutes which rapidly become dominant community members within 2 days after emerging from a sporulated state. We hypothesized that their bacteriophages (phages) would respond to such a dramatic increase in their host’s abundance. In our experiment, wetting caused Firmicutes to bloom and triggered a significant depletion of cyanobacterial diversity. We used genome-resolved metagenomics to link phage to their hosts and found that the bloom of the genus Bacillus correlated with a dramatic increase in the number of Caudovirales phages targeting these diverse spore-formers ( r = 0.762). After 2 days, we observed dramatic reductions in the relative abundances of Bacillus , while the number of Bacillus phages continued to increase, suggestive of a predator-prey relationship. We found predicted auxiliary metabolic genes (AMGs) associated with sporulation in several Caudovirales genomes, suggesting that phages may influence and even benefit from sporulation dynamics in biocrusts. Prophage elements and CRISPR-Cas repeats in Firmicutes metagenome-assembled genomes (MAGs) provide evidence of recent infection events by phages, which were corroborated by mapping viral contigs to their host MAGs. Combined, these findings suggest that the blooming Firmicutes become primary targets for biocrust Caudovirales phages, consistent with the classical “kill-the-winner” hypothesis. This work forms part of an overarching research theme studying the effects of a changing climate on biological soil crust (biocrust) in the Southwestern United States. To our knowledge, this study was the first to characterize bacteriophages in biocrust and offers a view into the ecology of phages in response to a laboratory wetting experiment. The phages identified here represent lineages of Caudovirales , and we found that the dynamics of their interactions with their Firmicutes hosts explain the collapse of a bacterial bloom that was induced by wetting. Moreover, we show that phages carried host-altering metabolic genes and found evidence of proviral infection and CRISPR-Cas repeats within host genomes. Our results suggest that phages exert controls on population density by lysing dominant bacterial hosts and that they further impact biocrust by acquiring host genes for sporulation. Future research should explore how dominant these phages are in other biocrust communities and quantify how much the control and lysis of blooming populations contributes to nutrient cycling in biocrusts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

A Co-Simulation Framework to Study Future Energy-Economy Interactions

Energy-economy interactions are often studied using top-down integrated assessment or economy models that have broad scope but lack the resolution and process detail to consider complex emerging trends across the energy sector. This presentation describes an approach to maintain both detail and scope by linking NREL's highly resolved models of the electricity, transportation, and buildings sectors with a MIT's USREP computable general equilibrium model of the U.S. economy. We will discuss strategies for linking across disparate models along with preliminary results describing the economy-wide impacts of future energy technology innovation.

ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Time-Resolved Structural Kinetics of an Organic Mixed Ionic–Electronic Conductor

The structure and packing of organic mixed ionic–electronic conductors have an especially significant effect on transport properties. In operating devices, this structure is not fixed but is responsive to changes in electrochemical potential, ion intercalation, and solvent swelling. Toward this end, the steady-state and transient structure of the model organic mixed conductor, poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), is characterized using multimodal time-resolved operando techniques. Steady-state operando X-ray scattering reveals a doping-induced lamellar expansion of 1.6 Å followed by 0.4 Å relaxation at high doping levels. Time-resolved operando X-ray scattering reveals asymmetric rates of lamellar structural change during doping and dedoping that do not directly depend on potential or charging transients. Further, time-resolved spectroscopy establishes a link between structural transients and the complex kinetics of electronic charge carrier subpopulations, in particular the polaron–bipolaron equilibrium. These findings provide insight into the factors limiting the response time of organic mixed-conductor-based devices, and present the first real-time observation of the structural changes during doping and dedoping of a conjugated polymer system via X-ray scattering.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Mediterranean grassland soil C–N compound turnover is dependent on rainfall and depth, and is mediated by genomically divergent microorganisms

Soil microbial activity drives the carbon and nitrogen cycles and is an important determinant of atmospheric trace gas turnover, yet most soils are dominated by microorganisms with unknown metabolic capacities. Even Acidobacteria, among the most abundant bacteria in soil, remain poorly characterized, and functions across groups such as Verrucomicrobia, Gemmatimonadetes, Chloroflexi and Rokubacteria are understudied. Here, we have resolved 60 metagenomic and 20 proteomic data sets from a Mediterranean grassland soil ecosystem and recovered 793 near-complete microbial genomes from 18 phyla, representing around one-third of all microorganisms detected. Importantly, this enabled extensive genomics-based metabolic predictions for these communities. Acidobacteria from multiple previously unstudied classes have genomes that encode large enzyme complements for complex carbohydrate degradation. In contrast, most microorganisms encode carbohydrate esterases that strip readily accessible methyl and acetyl groups from polymers like pectin and xylan, forming methanol and acetate, the availability of which could explain the high prevalence of C 1 metabolism and acetate utilization in genomes. Microorganism abundances among samples collected at three soil depths and under natural and amended rainfall regimes indicate statistically higher associations of inorganic nitrogen metabolism and carbon degradation in deep and shallow soils, respectively. This partitioning decreased in samples under extended spring rainfall, indicating that long-term climate alteration can affect both carbon and nitrogen cycling. As a whole, by leveraging natural and experimental gradients with genome-resolved metabolic profiles, we link microorganisms lacking prior genomic characterization to specific roles in complex carbon, C 1 , nitrate and ammonia transformations, and constrain factors that impact their distributions in soil.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

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

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

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2021

Alignment of the magnetic field in star-forming regions and why it might be difficult to observe

ABSTRACT Magnetic fields are an important component of the interstellar medium (ISM) and exhibit strongly varying field strengths and a non-trivial correlation with the gas density. Its dynamical impact varies between individual regions of the ISM and correlates with the orientation of the field with respect to the gas structures. Using high-resolution magneto-hydrodynamical simulations of the ISM, we explore the connection between the orientation of the field and the dynamical state of the gas. We find that the onset of gravitational instability in molecular gas above a density of $\rho \sim 10^{-21}\, \mathrm{g\, cm}^{-3}$$(n\sim 400\, \mathrm{cm}^{-3})$ coincides with an alignment of the magnetic field lines and the gas flow. At this transition, the gradient of the density changes from mainly perpendicular to preferentially parallel to the field lines. A connection between the three-dimensional alignment and projected two-dimensional observables is non-trivial, because of a large dispersion of the magnetic field orientation along the line of sight. The turbulent correlation lengths can be small compared to the typical integration lengths. As a consequence, the small-scale signal of the orientation can sensitively depend on the line of sight or the dynamical state of the cloud can fluctuate stochastically or be completely averaged out. With higher spatial resolution more small-scale structures are resolved, which aggravates the link between magneto-hydrodynamical quantities and projected observables.

Girichidis, Philipp (ORCID:0000000293009914)↗