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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Temperature dependence of nitrate-reducing Fe(II) oxidation by Acidovorax strain BoFeN1 – evaluating the role of enzymatic vs. abiotic Fe(II) oxidation by nitrite

ABSTRACT Fe(II) oxidation coupled to nitrate reduction is a widely observed metabolism. However, to what extent the observed Fe(II) oxidation is driven enzymatically or abiotically by metabolically produced nitrite remains puzzling. To distinguish between biotic and abiotic reactions, we cultivated the mixotrophic nitrate-reducing Fe(II)-oxidizing Acidovorax strain BoFeN1 over a wide range of temperatures and compared it to abiotic Fe(II) oxidation by nitrite at temperatures up to 60°C. The collected experimental data were subsequently analyzed through biogeochemical modeling. At 5°C, BoFeN1 cultures consumed acetate and reduced nitrate but did not significantly oxidize Fe(II). Abiotic Fe(II) oxidation by nitrite at different temperatures showed an Arrhenius-type behavior with an activation energy of 80±7 kJ/mol. Above 40°C, the kinetics of Fe(II) oxidation were abiotically driven, whereas at 30°C, where BoFeN1 can actively metabolize, the model-based interpretation strongly suggested that an enzymatic pathway was responsible for a large fraction (ca. 62%) of the oxidation. This result was reproduced even when no additional carbon source was present. Our results show that at below 30°C, i.e. at temperatures representing most natural environments, biological Fe(II) oxidation was largely responsible for overall Fe(II) oxidation, while abiotic Fe(II) oxidation by nitrite played a less important role.

Microbiology↗
DOE OSTI2023

Deep Reinforcement Learning Based HVAC Control for Reducing Carbon Footprint of Buildings

In this paper, we present our work on deep reinforcement learning (DRL) based intelligent control of Heating, Ventilation, and Air Conditioning (HVAC) with the goal of reducing carbon emission. We performed this task using 1) Marginal Operating Emission Rates (MOER), where the objective was to shift the demand to the low emission period of the day and 2) Time-Of-Use (TOU) demand-response price where the objective was to shift the demand to low price period of the day. This was achieved by learning an optimal pre-cooing strategy. We found the carbon emission reduction in the range of 6%-16% depending on the opportunity presented by the MOER signal. Similarly, we observed the carbon emission reduction in the range of 23%-29% during the peak price period when TOU price was used. The results clearly demonstrated the applicability of our approach in reducing the carbon footprint of the building.

carbon emission↗
DOE OSTI2019

Can I/O Variability Be Reduced on QoS-Less HPC Storage Systems?

For a production high-performance computing (HPC) system, where storage devices are shared between multiple applications and managed in a best effort manner, I/O contention is often a major problem. In this paper, we propose a balanced messaging-based re-routing in conjunction with throttling at the middleware level. This work tackles two key challenges that have not been fully resolved in the past: whether I/O variability can be reduced on a QoS-less HPC storage system, and how to design a runtime scheduling system that can scale up to a large amount of cores. The proposed scheme uses a two-level messaging system to re-route I/O requests to a less congested storage location so that write performance is improved, while limiting the impact on read by throttling re-routing. An analytical model is derived to guide the setup of optimal throttling factor. We thoroughly analyze the virtual messaging layer overhead and explore whether the in-transit buffering is effective in managing I/O variability. Contrary to the intuition, in-transit buffer cannot completely solve the problem. It can reduce the absolute variability but not the relative variability. The proposed scheme is verified against a synthetic benchmark as well as being used by production applications.

Huang, Dan↗
DOE OSTI2024

Using Median Point in Keeling Plot to Reduce the Uncertainty of the Isotopic Composition of Evapotranspiration

Abstract The isotopic composition of evapotranspirationδ ET is a crucial parameter in isotope-based evapotranspiration (ET) partitioning and moisture recycling studies. The Keeling plot method is the most prevalent method to calculateδ ET , though it contains large extrapolated uncertainties from the least squares regression. Traditional Keeling regression uses the mean point of individual measurements. Here, a modified Keeling plot framework was proposed using the median point of individual measurements. We tested theδ ET uncertainty using the mean point [σ ET (mean)] and median point [σ ET (median)]. Multiple resolutions of input and output data from six independent sites were used to test the performance of the two methods. Theσ ET (mean) would be greater thanσ ET (median) when the mean value of inverse vapor concentration () is greater than the median value of inverse vapor concentration []. When applying the filter ofr 2 > 0.8, around 70% ofσ ET (mean) was greater thanσ ET (median). This phenomenon might be due to the normality of the vapor concentrationC υ producing the asymmetric distribution of 1/C υ . The median method could perform significantly better than the mean method when inputting high-resolution measurements (e.g., 1 Hz) and when the water vapor concentrationC υ is relatively low. Compared to the mean method, applying the median method could on average reduce 6.88% of ET partitioning uncertainties and could on average reduce 9.00% of moisture recycling uncertainties. This study provided a new insight of the Keeling plot method and emphasized handling model output uncertainty from multiple perspectives instead of only from input parameters.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Reducing communication in algebraic multigrid with multi-step node aware communication

Algebraic multigrid (AMG) is often viewed as a scalable [Formula: see text] solver for sparse linear systems. Yet, AMG lacks parallel scalability due to increasingly large costs associated with communication, both in the initial construction of a multigrid hierarchy and in the iterative solve phase. This work introduces a parallel implementation of AMG that reduces the cost of communication, yielding improved parallel scalability. It is common in Message Passing Interface (MPI), particularly in the MPI-everywhere approach, to arrange inter-process communication, so that communication is transported regardless of the location of the send and receive processes. Performance tests show notable differences in the cost of intra- and internode communication, motivating a restructuring of communication. In this case, the communication schedule takes advantage of the less costly intra-node communication, reducing both the number and the size of internode messages. Node-centric communication extends to the range of components in both the setup and solve phase of AMG, yielding an increase in the weak and strong scaling of the entire method.

Computer Science↗
DOE OSTI2015

Downregulation of GAUT12 in Populus deltoides by RNA silencing results in reduced recalcitrance, increased growth and reduced xylan and pectin in a woody biofuel feedstock

The inherent recalcitrance of woody bioenergy feedstocks is a major challenge for their use as a source of second-generation biofuel. Secondary cell walls that constitute the majority of hardwood biomass are rich in cellulose, xylan, and lignin. The interactions among these polymers prevent facile accessibility and deconstruction by enzymes and chemicals. Plant biomass that can with minimal pretreatment be degraded into sugars is required to produce renewable biofuels in a cost-effective manner. The following are the results: GAUT12/IRX8 is a putative glycosyltransferase proposed to be involved in secondary cell wall glucuronoxylan and/or pectin biosynthesis based on concomitant reductions of both xylan and the pectin homogalacturonan (HG) in Arabidopsis irx8 mutants. Two GAUT12 homologs exist in Populus trichocarpa, PtGAUT12.1 and PtGAUT12.2. Knockdown expression of both genes simultaneously has been shown to reduce xylan content in Populus wood. We tested the proposition that RNA interference (RNAi) downregulation of GAUT12.1 alone would lead to increased sugar release in Populus wood, that is, reduced recalcitrance, based on the hypothesis that GAUT12 synthesizes a wall structure required for deposition of xylan and that cell walls with less xylan and/or modified cell wall architecture would have reduced recalcitrance. Using an RNAi approach, we generated 11 Populus deltoides transgenic lines with 50 to 67% reduced PdGAUT12.1 transcript expression compared to wild type (WT) and vector controls. Ten of the eleven RNAi lines yielded 4 to 8% greater glucose release upon enzymatic saccharification than the controls. The PdGAUT12.1 knockdown (PdGAUT12.1-KD) lines also displayed 12 to 52% and 12 to 44% increased plant height and radial stem diameter, respectively, compared to the controls. Knockdown of PdGAUT12.1 resulted in a 25 to 47% reduction in galacturonic acid and 17 to 30% reduction in xylose without affecting total lignin content, revealing that in Populus wood as in Arabidopsis, GAUT12 affects both pectin and xylan formation. Finally, analyses of the sugars present in sequential cell wall extracts revealed a reduction of glucuronoxylan and pectic HG and rhamnogalacturonan in extracts from PdGAUT12.1-KD lines.

09 BIOMASS FUELS↗
DOE OSTI2015

The reduced genomes of Parcubacteria (OD1) contain signatures of a symbiotic lifestyle

Candidate phylum OD1 bacteria (also referred to as Parcubacteria) have been identified in broad range of anoxic environments through community survey analysis. Although none of these species have been isolated in the laboratory, several genome sequences have been reconstructed from metagenomic sequence data and single-cell sequencing. The organisms have small (generally <1 Mb) genomes with severely reduced metabolic capabilities. We have reconstructed 8 partial to near-complete OD1 genomes from oxic groundwater samples, and compared them against existing genomic data. The conserved core gene set comprises 202 genes, or ~28% of the genomic complement. ‘Housekeeping’ genes and genes for biosynthesis of peptidoglycan and Type IV pilus production are conserved. Gene sets for biosynthesis of cofactors, amino acids, nucleotides and fatty acids are absent entirely or greatly reduced. The only aspects of energy metabolism conserved are the non-oxidative branch of the pentose-phosphate shunt and central glycolysis. These organisms also lack some activities conserved in almost all other known bacterial genomes, including signal recognition particle, pseudouridine synthase A, and FAD synthase. Pan-genome analysis indicates a broad genotypic diversity and perhaps a highly fluid gene complement, indicating historical adaptation to a wide range of growth environments and a high degree of specialization. The genomes were examined for signatures suggesting either a free-living, streamlined lifestyle or a symbiotic lifestyle. The lack of biosynthetic capabilities and DNA repair, along with the presence of potential attachment and adhesion proteins suggest the Parcubacteria are ectosymbionts or parasites of other organisms. The wide diversity of genes that potentially mediate cell-cell contact suggests a broad range of partner/prey organisms across the phylum.

candidate phyla↗
DOE OSTI2021

Reducing Ground-based Astrometric Errors with Gaia and Gaussian Processes

Stochastic field distortions caused by atmospheric turbulence are a fundamental limitation to the astrometric accuracy of ground-based imaging. This distortion field is measurable at the locations of stars with accurate positions provided by the Gaia DR2 catalog; we develop the use of Gaussian process regression (GPR) to interpolate the distortion field to arbitrary locations in each exposure. We introduce an extension to standard GPR techniques that exploits the knowledge that the 2D distortion field is curl-free. Applied to several hundred 90 s exposures from the Dark Energy Survey as a test bed, we find that the GPR correction reduces the variance of the turbulent astrometric distortions ≈12× , on average, with better performance in denser regions of the Gaia catalog. The rms per-coordinate distortion in the riz bands is typically ≈7 mas before any correction and ≈2 mas after application of the GPR model. The GPR astrometric corrections are validated by the observation that their use reduces, from 10 to 5 mas rms, the residuals to an orbit fit to riz-band observations over 5 yr of the r = 18.5 trans-Neptunian object Eris. We also propose a GPR method, not yet implemented, for simultaneously estimating the turbulence fields and the 5D stellar solutions in a stack of overlapping exposures, which should yield further turbulence reductions in future deep surveys.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

The Reduced Effectiveness of EGR to Mitigate Knock at High Loads in Boosted SI Engines

Numerous studies have demonstrated that exhaust gas recirculation (EGR) can attenuate knock propensity in spark ignition (SI) engines at naturally aspirated or lightly boosted conditions. In this paper, we investigate the role of cooled EGR under higher load conditions with multiple fuel compositions, where highly retarded combustion phasing typical of modern SI engines was used. It was found that under these conditions, EGR attenuation of knock is greatly reduced, where EGR doesn’t allow significant combustion phasing advance as it does under lighter load conditions. Detailed combustion analysis shows that when EGR is added, the polytropic coefficient increases causing the compressive pressure and temperature to increase. At sufficiently highly boosted conditions, the increase in polytropic coefficient and additional trapped mass from EGR can sufficiently reduce fuel ignition delay to overcome knock attenuation effects. Kinetic modeling demonstrates that the effectiveness of EGR to mitigate knock is highly dependent on the pressure-temperature condition. Experiments at 2000 rpm have confirmed reduced fuel ignition delay under highly boosted conditions relevant to modern downsized boosted SI engines, where in-cylinder pressure is higher and the temperature is cooler. Finally, at these conditions, charge reactivity increases compared to naturally aspirated conditions, and attenuation of knock by EGR is reduced.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Dimensionality reducibility for multi-physics reduced order modeling

Applications of reduced order modeling (ROM) to support analysis of complex reactor behavior using high fidelity simulations have developed rapidly in recent years. Reduction implies any computational approach aiming to reduce the cost of the simulation, especially for situations involving repeated executions such as probabilistic risk assessment and uncertainty quantification applications. This article presents a novel non-intrusive methodology to render reduction for multi-physics models by taking advantage of the combined reduction introduced by each sub-physics in the simulation. Next, a surrogate model is constructed in terms of the reduced dimensions. A key component of the proposed methodology is to upper-bound the errors resulting from the reduction to ensure its reliability for subsequent engineering applications. To implement and demonstrate the proposed ROM algorithm, the INL’s MAMMOTH environment is employed to analyze the level of reduction in the coupled radiation-thermal transport modeling of a 2D quarter fuel pin in a light water reactor spectrum. MAMMOTH couples the neutronics model of Rattlesnake module and the fuel performance model of BISON module. Here, the results show that the reduction obtained with coupled physics is more significant than that with individual sub-physics models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Enhanced photocatalytic and photoelectrochemical activities of reduced TiO 2-x /BiOCl heterojunctions

A key issue to design highly efficient photoelectrodes for hydrogen production is how to prohibit the rapid carrier recombination. In order to use the visible light and reduce the recombination of electrons and holes, reduced TiO 2-x /BiOCl heterojunctions are successfully synthesized and the photoelectrodes are assembled in this work. The effects of various Bi/Ti molar ratios on the structural, morphological, optical, photoelectrochemical and photocatalytic activities of the resultant samples are investigated systematically. The TiO 2-x nanoparticles contain Ti 3+ , Ti 2+ , and oxygen vacancies (Ov), while the BiOCl nanosheets exposed {001} facet. Ultraviolet–visible diffuse reflectance spectroscopy (UV–vis DRS) results indicate that the existence of Ti 3+ , Ti 2+ and Ov expand the light-response range. Linear scan voltammetry and electrochemical impedance spectroscopy results indicate that more efficient electron transportation is presented in the heterojunctions with the appropriate Bi/Ti molar ratio. Consequently, the reduced TiO 2-x /BiOCl heterojunction with the most appropriate Bi/Ti molar ratio exhibits a high photocurrent density of 0.755 mA cm -2 with photoconversion efficiency up to 0.634%, 10.5 and 22.6 times larger than that of pure TiO 2 and BiOCl. Furthermore, this heterojunction exhibit 48.38 and 12.54 times enhancement for the visible-light decomposition of rhodamine B compared with pure TiO 2 and BiOCl.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Multifidelity Ensemble Kalman Filter with Reduced Order Control Variates

This work develops a new multi delity ensemble Kalman lter (MFEnKF) algorithm based on linear control variate framework. The approach allows for rigorous multi delity extensions of the EnKF, where the uncertainty in coarser delities in the hierarchy of models represent control variates for the uncertainty in ner delities. Small ensembles of high delity model runs are com- plemented by larger ensembles of cheaper, lower delity runs, to obtain much improved analyses at only small additional computational costs. We investigate the use of reduced order models as coarse delity control variates in the MFEnKF, and provide analyses to quantify the improvements over the traditional ensemble Kalman lters. We apply these ideas to perform data assimilation with a quasi-geostrophic test problem, using direct numerical simulation and a corresponding POD-Galerkin reduced order model. Numerical results show that the two- delity MFEnKF provides better analyses than existing EnKF algorithms at comparable or reduced computational costs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

An Adaptive Reduced Basis Collocation Method Based on PCM ANOVA Decomposition for Anisotropic Stochastic PDEs

The combination of reduced basis and collocation methods enables efficient and accurate evaluation of the solutions to parameterized PDEs. Here, we study the stochastic collocation methods that can be combined with reduced basis methods to solve high-dimensional parameterized stochastic PDEs. We also propose an adaptive algorithm using a probabilistic collocation method (PCM) and ANOVA decomposition. This procedure involves two stages. First, the method employs an ANOVA decomposition to identify the effective dimensions, i.e., subspaces of the parameter space in which the contributions to the solution are larger, and sort the reduced basis solution in a descending order of error.Then, the adaptive search refines the parametric space by increasing the order of polynomials until the algorithm is terminated by a saturation constraint. We demonstrate the effectiveness of the proposed algorithm for solving a stationary stochastic convection-diffusion equation, a benchmark problem chosen because solutions contain steep boundary layers and anisotropic features. Lastly, we show that two stages of adaptivity are critical in a benchmark problem with anisotropic stochasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗