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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DiffLense: a conditional diffusion model for super-resolution of gravitational lensing data

Abstract Gravitational lensing data is frequently collected at low resolution due to instrumental limitations and observing conditions. Machine learning-based super-resolution techniques offer a method to enhance the resolution of these images, enabling more precise measurements of lensing effects and a better understanding of the matter distribution in the lensing system. This enhancement can significantly improve our knowledge of the distribution of mass within the lensing galaxy and its environment, as well as the properties of the background source being lensed. Traditional super-resolution techniques typically learn a mapping function from lower-resolution to higher-resolution samples. However, these methods are often constrained by their dependence on optimizing a fixed distance function, which can result in the loss of intricate details crucial for astrophysical analysis. In this work, we introduce DiffLense , a novel super-resolution pipeline based on a conditional diffusion model specifically designed to enhance the resolution of gravitational lensing images obtained from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). Our approach adopts a generative model, leveraging the detailed structural information present in Hubble space telescope (HST) counterparts. The diffusion model, trained to generate HST data, is conditioned on HSC data pre-processed with denoising techniques and thresholding to significantly reduce noise and background interference. This process leads to a more distinct and less overlapping conditional distribution during the model’s training phase. We demonstrate that DiffLense outperforms existing state-of-the-art single-image super-resolution techniques, particularly in retaining the fine details necessary for astrophysical analyses.

Computer Science↗
DOE OSTI2023

Gene Expression Programming for Quantum Computing

Here, we introduce QuantumGEP, a scientific computer program that uses gene expression programming (GEP) to find a quantum circuit that either (1) maps a given set of input states to a given set of output states or (2) transforms a fixed initial state to minimize a given physical quantity of the output state. QuantumGEP is a driver program that uses evendim, a generic computational engine for GEP, both of which are free and open source. We apply QuantumGEP as a powerful solver for MaxCut in graphs and for condensed matter quantum many-body Hamiltonians.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Modulation of polar auxin transport identifies the molecular determinants of source–sink carbon relationships and sink strength in poplar

Abstract Source-to-sink carbon (C) allocation driven by the sink strength, i.e., the ability of a sink organ to import C, plays a central role in tissue growth and biomass productivity. However, molecular drivers of sink strength have not been thoroughly characterized in trees. Auxin, as a major plant phytohormone, regulates the mobilization of photoassimilates in source tissues and elevates the translocation of carbohydrates toward sink organs, including roots. In this study, we used an ‘auxin-stimulated carbon sink’ approach to understand the molecular processes involved in the long-distance source–sink C allocation in poplar. Poplar cuttings were foliar sprayed with polar auxin transport modulators, including auxin enhancers (AE) (i.e., IBA and IAA) and auxin inhibitor (AI) (i.e., NPA), followed by a comprehensive analysis of leaf, stem and root tissues using biomass evaluation, phenotyping, C isotope labeling, metabolomics and transcriptomics approaches. Auxin modulators altered root dry weight and branching pattern, and AE increased photosynthetically fixed C allocation from leaf to root tissues. The transcriptome analysis identified highly expressed genes in root tissue under AE condition including transcripts encoding polygalacturonase and β-amylase that could increase the sink size and activity. Metabolic analyses showed a shift in overall metabolism including an altered relative abundance levels of galactinol, and an opposite trend in citrate levels in root tissue under AE and AI conditions. In conclusion, we postulate a model suggesting that the source–sink C relationships in poplar could be fueled by mobile sugar alcohols, starch metabolism-derived sugars and TCA-cycle intermediates as key molecular drivers of sink strength.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Quantifying Burst Repeatability for Godiva IV

The minimum resolvable relative change in the neutron source emission of Godiva IV between bursts, i.e., burst repeatability, was quantified using a combination of activation monitors and a resistance temperature detector (RTD). Measurements support changes in the neutron source emission between bursts can be determined with a precision of 2.7%. The measurements were performed during a series of twelve Godiva IV bursts and were a collaborative effort between Los Alamos National Laboratory, Sandia National Laboratories, and Pacific Northwest National Laboratory. Gold, iron, nickel, and sulfur activation monitors were positioned in a sample holder in the central cavity of Godiva IV for each burst. The RTD is part of the Godiva burst diagnostic system and is in a fixed location in the safety block of Godiva IV. It is used to determine the temperature rise of the burst, i.e., the difference between the maximum temperature recorded during the burst and the initial temperature prior to the burst. Differences in either the specific activity of the activation monitor reactions, or the temperature rise can be used to determine the relative change in the neutron source emission for separate bursts, but historic results have proven that each method is susceptible to various sources of biases which generally cannot be isolated using a single method. We address this issue by applying both measurement methods and analyzing the correlation between them. The results presented in this work will be used to support future experiments with Godiva IV at the National Criticality Experiments Research Center (NCERC).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Acclimation of Phytoplankton Fe:C Ratios Dampens the Biogeochemical Response to Varying Atmospheric Deposition of Soluble Iron

Abstract Dissolved iron (dFe) plays an important role in regulating marine productivity. In high nutrient, low chlorophyll regions (>33% of the global ocean), iron is the primary growth limiting nutrient, and elsewhere iron can regulate nitrogen fixation by diazotrophs. The link between iron availability and carbon export is strongly dependent on the phytoplankton iron quotas or cellular Fe:C ratios. This ratio varies by more than an order of magnitude in the open ocean and is positively correlated with ambient dFe concentrations in field observations. Representing Fe:C ratios within models is necessary to investigate how ocean carbon cycling will interact with perturbations to iron cycling in a changing climate. The Community Earth System Model ocean component was modified to simulate dynamic, group‐specific, phytoplankton Fe:C that varies as a function of ambient iron concentration. The simulated Fe:C ratios improve the representation of the spatial trends in the observed Fe:C ratios. The acclimation of phytoplankton Fe:C ratios dampens the biogeochemical response to varying atmospheric deposition of soluble iron, compared to a fixed Fe:C ratio. However, varying atmospheric soluble iron supply has first order impacts on global carbon and nitrogen fluxes and on nutrient limitation spatial patterns. Our results suggest that pyrogenic Fe is a significant dFe source that rivals mineral dust inputs in some regions. Changes in dust flux and iron combustion sources (anthropogenic and wildfires) will modify atmospheric Fe inputs in the future. Accounting for dynamic phytoplankton iron quotas is critical for understanding ocean biogeochemistry and projecting its response to variations in atmospheric deposition.

Environmental Sciences & Ecology↗
DOE OSTI2019

Experimental Validation of Model Predictive Control Applied to the Azura Wave Energy Converter

Ocean wave energy is a promising area of renewable energy development. However, there are unique operational challenges, particularly with regards to modeling, estimation, and control. Model Predictive Control (MPC) is a widely studied control approach that has strong potential for successful application to ocean wave energy conversion. It combines a predictive element, which is necessary for optimal wave energy conversion, along with consideration of system limitations, which is extremely important when operating within the very large forces present in ocean hydrodynamics. This paper presents MPC formulation and experimental testing, applied to the 1/15th scale Azura wave energy converter developed and tested by Northwest Energy Innovations (NWEI). Here, the results demonstrate successful prototype testing, with MPC providing an average increase in power production of 36% over standard fixed damping for six cases of sea states.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Global terrestrial nitrogen fixation and its modification by agriculture

Biological nitrogen fixation (BNF) is the largest natural source of new nitrogen (N) that supports terrestrial productivity, yet estimates of global terrestrial BNF remain highly uncertain. Here, in this study, we show that this uncertainty is partly because of sampling bias, as field BNF measurements in natural terrestrial ecosystems occur where N fixers are 17 times more prevalent than their mean abundances worldwide. To correct this bias, we develop new estimates of global terrestrial BNF by upscaling field BNF measurements using spatially explicit abundances of all major biogeochemical N-fixing niches. We find that natural biomes sustain lower BNF, 65 (52–77) Tg N yr −1 , than previous empirical bottom-up estimates, with most BNF occurring in tropical forests and drylands. We also find high agricultural BNF in croplands and cultivated pastures, 56 (54–58) Tg N yr −1 . Agricultural BNF has increased terrestrial BNF by 64% and total terrestrial N inputs from all sources by 60% over pre-industrial levels. Our results indicate that BNF may impose stronger constraints on the carbon sink in natural terrestrial biomes and represent a larger source of agricultural N than is generally considered in analyses of the global N cycle, with implications for proposed safe operating limits for N use.

Reis Ely, Carla R. [Oregon State Univ., Corvallis,↗
DOE OSTI2022

Soil and soil fraction radiocarbon, C and N from the Enriched Background Isotope Study, Oak Ridge National Laboratory, Tennessee, USA

A large accidental 14CO2 release at the Oak Ridge Reservation in Tennessee, USA provided a strong label pulse into adjacent, well-studied oak forests, resulting in highly elevated Δ14C values in leaf litter (~1000‰) and roots (~260–450‰). A four-year manipulative study was conducted to provide insight into mechanisms underlying soil Organic matter dynamics, specifically to determine the relative contribution of litter versus roots to the bulk mineral soil C pool, as well as to free light, occluded light and heavy fractions. The heavy fraction was further split into fractions with densities of 1.7–2.4 g cm-3 and >2.4 g cm-3 to test the homogeneity of the mineral-associated fraction of C. Substantial concentrations of label were detected in all soil fractions within a year of the 14CO2 release, indicating rapid incorporation of newly fixed photosynthates in all fractions of soil organic C, regardless of differences in stability inferred by previous work. This rapid incorporation of label occurred only in treatments where roots were labeled, indicating that roots are the major source of inputs to mineral soil C stocks at these sites. Separation of the heavy fraction into subfractions of intermediate (1.7–2.4 g cm -3) and high (>2.4 g cm-3) density indicated that both subfractions incorporated label at similar rates, despite significant differences in degree of microbial processing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Stochastic Adaptive Droop Control in Frequency Regulation of Power Systems With Intermittent Generators

Modern power systems (MPSs), including microgrids (MGs), are increasingly incorporating multiple renewable energy sources (RESs) such as wind and solar power, as well as battery storage and controllable loads. While environmentally beneficial, these sources pose challenges for control and management due to their intermittent and stochastic nature, especially in maintaining frequency stability with multiple interconnected generators of varying capacities. Traditional droop control methods are effective in systems with generators that are dispatchable and have fixed generation capacities, but they fall short when applied to systems with RESs, where generation capacities are dynamic and affected by unpredictable environmental conditions. To address these challenges, this paper introduces a novel stochastic adaptive droop control (SADC) method for load frequency control (LFC). The proposed method adapts droop coefficients in real time, based on the measured stochastic data of power generation capacities, enabling more effective frequency regulation in systems with variable and intermittent power generation. Unlike traditional adaptive control methods, which assume constant or slowly-varying system parameters, this approach accounts for stochastic processes by modeling them as Markov chains, enabling robust performance under highly dynamic and unpredictable conditions. The key contributions of this work include the development of real-time droop coefficient adaptation algorithms, derivation of their stability and convergence properties, and the demonstration of the advantages of the method through simulations. Case studies highlight the improved performance of frequency regulation, particularly in addressing the impact of stochastic weather conditions and the benefits of reducing dependence on battery reserves in dealing with intermittency of RESs. Finally, this paper provides a comprehensive analysis of the theoretical foundations of the method, as well as practical implementation insights for future power systems with high penetration of RESs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Detecting the full photoemission cone from laser-based ARPES experiments by leveraging deflector technology

Angle-resolved photoemission spectroscopy (ARPES) provides a direct access to the electronic band structure of solid and molecular systems. The momentum range accessible by this technique depends directly on the photon energy used, and low-photon-energy sources are insufficient to photoemit electrons over the full Brillouin zone of most quantum materials. In addition, while electrons are emitted over a 2π solid angle, conventional hemispherical analyzers only collect a small subset of those electrons. A previous work [Gauthier et al., Rev. Sci. Instrum. 92, 123907 (2021)] demonstrated that electrons emitted over a larger field-of-view can be acquired in one fixed configuration by accelerating them toward the analyzer with a bias voltage. Here, in this study, we extend this work by leveraging the deflector technology of novel ARPES hemispherical analyzers. We demonstrate the ability to detect all 2π photoemitted electrons in a fixed configuration for various materials, such as gold, cuprates, and transition-metal dichalcogenides. This approach is especially advantageous for time-resolved ARPES, as electron dynamics over a large momentum range can be accessed with identical measurement conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Nitrogen derived from Combined Algal Processing supports algae cultivation for biofuels

Algae biomass, a biofuel feedstock with potential to reduce global CO 2 emissions, is currently too expensive Nitrogen, a significant input and life cycle cost, requires research on recycling and additional sources to reduce costs. Integral to nitrogen recycling is the knowledge of actual nitrogen requirements in outdoor ponds, thus data from the Unified Field Studies of the Algae Testbed Public-Private Partnership was analyzed. The data showed that Nannochloropsis oceanica used 14–24 mg/L NH 4 + per harvest cycle for robust growth. Nitrogen recycled directly from the algae conversion process will likely be the primary source of nitrogen for algae cultivation. Harvested algae can be fractionated via Combined Algal Processing (CAP), where algae are pretreated, fermented, and the fuel feedstocks (e. g. ethanol, lipids) are removed leaving a nitrogen rich slurry. Chlorella vulgaris grew robustly in nitrogen-free media supplemented with CAP residues through 4 harvest cycles with no inhibition. The amount of nitrogen as free ammonium available for recycling directly without further processing was insufficient (~4% of total needed), thus the nitrogen fixing bacteria, Azotobacter vinelandii, was investigated as a means for increasing ammonium concentration in CAP residues. This organism was shown to be proficient at growth on sugars liberated from algae biomass during pretreatment and sustained algae growth using A. vinelandii supernatants was also demonstrated. Using Azotobacter to increase ammonium concentrations on-site using an inexpensive biological process to generate the necessary ammonium for outdoor algae cultivation improves sustainability of algae biofuels by avoiding the energy intensive steps of typical ammonium production and transport. Furthermore, these results show that byproducts of algae conversion begin to close nitrogen demand and, with further supplementation by diazotrophic bacteria or protein hydrolysis, may completely replace current energyintensive and costly industrial nitrogen sources offering a path to increased economic feasibility and improved life cycle analysis of algae-based biofuels.

09 BIOMASS FUELS↗
DOE OSTI2022

Pyomo.DOE: An open-source package for model-based design of experiments in Python

Predictive mathematical models are a cornerstone of science and engineering. Yet selecting, calibrating, and validating said science-based models often remains an art in practice. Model-based design of experiments (MBDoE) provides a systematic framework to maximize information gain from experiments while minimizing time and resource costs. But MBDoE remains limited to niche application areas, in part because practitioners must integrate expertise in statistics, computational optimization, and modeling. To help reduce this barrier, we introduce Pyomo.DOE, an open-source package for MBDoE. Pyomo.DOE uses a nonlinear sensitivity analysis code k_aug to quickly approximate the Fisher information matrix and leverages a new stochastic programming abstraction. We demonstrate Pyomo.DOE with the first application of MBDoE to fixed-bed breakthrough experiments, which highlights the power of Pyomo.DOE to quantify the value of experimental modifications a priori for large-scale partial differential-algebraic equation (PDAE) models. Here we also provide a mathematical primer on MBDoE targeted at general chemical engineers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Ball Motion and Near-Field Spray Characteristics of a Gasoline Direct Injection Injector using an X-ray Phase-Contrast Imaging Technique under High-Injection Pressures

Here, the purpose of this study is to visualize the ball (needle) motion and near-field spray characteristics of a gasoline direct injection injector under different injection conditions and analyze the effect of the internal structure of the injector on the ball motion, near-field spray velocity, and post-injection process. The injection pressure is set to 10MPa, 20 MPa, and 30 MPa, and the energization duration is fixed at 1.5 ms. An advanced X-ray technique with high transmittance and low scattering, is used to visualize the internal structure and near-field spray characteristics of the injector, which is impossible with general light sources. The ball is found to tilt to the right in the Y-axial direction during stable motion because the driving force of fuel on the ball is larger on the left side owing to the larger distance of the ball from the left wall. In addition, during stable motion, the near-field velocity of a hole with a smaller inlet angle is significantly higher than that of a hole with a larger inlet angle. The hole with a smaller inlet angle display better atomization characteristics during the post-injection process under all values of injection pressure.

47 OTHER INSTRUMENTATION↗