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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 487 records · Page 27

Sensitivity of LDEF foil analyses using ultra-low background germanium versus large NaI(T1) multidimensional spectrometers

Cobalt samples were analyzed for cosmic ray induced Co-60 with both an ultralow background germanium gamma ray spectrometer and with a large NaI(T1) multidimensional spectrometer using electronic anticoincidence shielding. Aluminum samples were analyzed for Na-22. The results are presented along with the relative sensitivities and precision afforded by the two methods.

Reeves, James H.↗

Sensitivity of LDEF foil analyses using ultra-low background germanium vs. large NaI(Tl) multidimensional spectrometers

Cobalt foils and stainless steel samples were analyzed for induced Co-60 activity with both an ultra-low background germanium gamma-ray spectrometer and with a large NaI(Tl) multidimensional spectrometer, both of which use electronic anticoincidence shielding to reduce background counts resulting from cosmic rays. Aluminum samples were analyzed for Na-22. The results, in addition to the relative sensitivities and precisions afforded by the two methods, are presented.

Reeves, James H.↗

Impact of Increased Latent Generations on Sensitivity Calculations with SCALE

Analyses of cross section sensitivity data from systems with fissile material allow analysts to associate an importance for each material, nuclide, reaction, and neutron energy by simulating real world criticality scenarios. Although criticality safety validation efforts can be guided by the cross-section sensitivity and uncertainty data generated for a particular system, these calculations can often be computationally expensive and sometimes cumbersome without proper guidance. The TSUNAMI suite within the SCALE code package has several methods for generating sensitivity data, including multigroup and continuous energy (CE) capabilities. The release of SCALE 6.3 has three different CE methods for generating cross section sensitivity data: (1) the Iterated Fission Probability (IFP) method with the KENO Monte Carlo transport solver, (2) the IFP method with the Shift Monte Carlo transport solver, and (3) the Contributon-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method with the KENO Monte Carlo transport solver. Although the CLUTCH method has additional parameters for generating sensitivity data files relative to the IFP method, all three methods use latent generations, which are the generations between an event (i.e., fission) and the assessment of importance based on the asymptotic population of progeny neutrons. Increasing the number of latent generations in a calculation leads to increased discrimination of the sensitivity coefficients but at the cost of the increased uncertainty associated with those generated values. Analysts must balance the accuracy of the sensitivity calculations and its uncertainty with the associated computational cost involved in generating the values. This paper discusses the impact of adjusting the latent generation parameter for a range of sensitivity values and how these changes compare with the direct perturbation values obtained from a change of ±0.5% Δ k in both benchmark and safety application models. Two benchmarks from the International Handbook of Evaluated Criticality Safety Benchmark Experiments and the MPC-32 dual purpose canister for spent nuclear fuel are used for analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Investigation of Navier-Stokes Code Verification and Design Optimization

With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization study is carried out using a geometric mean approach. Following this, sensitivity analyses with the aid of variance-based non-parametric approach and partial correlation coefficients are conducted using data available from surrogate models of the objectives and the multi-objective optima to identify the contribution of the design variables to the objective variability and to analyze the variability of the design variables and the objectives. In summary the present dissertation offers insight into an improved coarse to fine grid extrapolation technique for Navier-Stokes computations and also suggests tools for a designer to conduct design optimization study and related sensitivity analyses for a given design problem.

Vaidyanathan, Rajkumar↗

State-of-the-Art Reactor Consequence Analysis Project: Sensitivity Analysis Using Dakota

The State-of-the-Art Reactor Consequence Analyses (SOARCA) project has focused on best estimate analyses and uncertainty analysis for postulated accidents at specific nuclear power plants. The consequences of these accidents are estimated using the simulation tools MELCOR and MACCS. To understand which uncertain input variables are important to determining these consequences, analysts have performed sensitivity analyses. The tool used to perform these sensitivity analyses in previous SOARCA work, CompModSA, is no longer supported. Therefore, the current work focuses on migrating these analyses to another tool and evaluating its performance. Dakota, which is a tool developed at Sandia National Laboratories, is used in this work. Sensitivity results are created for three analyses from the SOARCA Surry UA. Though CompModSA and Dakota vary slightly in their algorithms and implementation, their sensitivity results generally agree, which gives confidence in the Dakota approach and increases confidence in the original analyses. It is likely that this methodology is extendable to the rest of SOARCA analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

BioSTEAMDevelopmentGroup/biosteam

BioSTEAM is a fast and flexible package for the design, simulation, and techno-economic analysis of biorefineries under uncertainty. BioSTEAM’s framework is built to streamline and automate early-stage technology evaluations and to enable rigorous sensitivity and uncertainty analyses. Complete biorefinery configurations are available at the Bioindustrial-Park GitHub repository, BioSTEAM’s premier repository for biorefinery models and results. The long-term growth and maintenance of BioSTEAM is supported through both community-led development and the research institutions invested in BioSTEAM. Through the open-source and community-lead platform, BioSTEAM aims to foster communication and transparency within the biorefinery research community for an integrated effort to expedite the evaluation of candidate biofuels and bioproducts. Additionally, an agile life cycle assessment (LCA) platform has been designed to interface with BioSTEAM, BioSTEAM-LCA. This open-source, installable package allows users to perform streamlined LCAs of biorefineries. The focus of BioSTEAM-LCA is to streamline and automate early-stage environmental impact analyses of processes and technologies, and to enable rigorous sensitivity and uncertainty analyses linking process design, performance, economics, and environmental impacts.

Cortes-Peña, Yoel↗

BioSTEAMDevelopmentGroup/thermosteam

BioSTEAM is a fast and flexible package for the design, simulation, and techno-economic analysis of biorefineries under uncertainty. BioSTEAM’s framework is built to streamline and automate early-stage technology evaluations and to enable rigorous sensitivity and uncertainty analyses. Complete biorefinery configurations are available at the Bioindustrial-Park GitHub repository, BioSTEAM’s premier repository for biorefinery models and results. The long-term growth and maintenance of BioSTEAM is supported through both community-led development and the research institutions invested in BioSTEAM. Through the open-source and community-lead platform, BioSTEAM aims to foster communication and transparency within the biorefinery research community for an integrated effort to expedite the evaluation of candidate biofuels and bioproducts. Additionally, an agile life cycle assessment (LCA) platform has been designed to interface with BioSTEAM, BioSTEAM-LCA. This open-source, installable package allows users to perform streamlined LCAs of biorefineries. The focus of BioSTEAM-LCA is to streamline and automate early-stage environmental impact analyses of processes and technologies, and to enable rigorous sensitivity and uncertainty analyses linking process design, performance, economics, and environmental impacts. ThermoSTEAM is a standalone thermodynamic engine capable of estimating mixture properties, solving thermodynamic phase equilibria, and modeling stoichiometric reactions. ThermoSTEAM builds upon chemicals, the chemical properties component of the Chemical Engineering Design Library, with a robust and flexible framework that facilitates the creation of property packages. The Biorefinery Simulation and Techno-Economic Analysis Modules (BioSTEAM) is dependent on ThermoSTEAM for the simulation of unit operations.

Cortes-Peña, Yoel↗

Sensitivity analysis of low bulk resistivity solar cells

In an effort to identify critical parameters of single-junction solar cells and to determine their relative sensitivity, parametric analyses have been conducted with a computer code SPCOLAY. A receipt for high-efficiency cells emerges from the analyses that requires the primary ingredients of low bulk resistivity (0.1-0.2 ohm-cm), a bulk diffusion length as large as attainable (greater than 100 microns), and a small front surface recombination velocity (about 100 cm/sec). Other parameters appear to play less sensitive roles.

Lin, E. I. H.↗

Wing-section optimization for supersonic viscous flow

To improve the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating thin-layer Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wind design task, the present investigation concentrated on testing the feasibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with similar features: slightly cambered, parabolic profiles with sharp leading- and trailing-edges. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for the problem formulations which should contribute to an effective wing shape optimization.

Item, Cem C.↗

Search for a heavy resonance decaying into a Z and a Higgs boson in events with an energetic jet and two electrons, two muons, or missing transverse momentum in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search is presented for a heavy resonance decaying into a Z boson and a Higgs (H) boson. The analysis is based on data from proton-proton collisions at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 138 fb$^{−1}$, recorded with the CMS experiment in the years 2016–2018. Resonance masses between 1.4 and 5 TeV are considered, resulting in large transverse momenta of the Z and H bosons. Final states that result from Z boson decays to pairs of electrons, muons, or neutrinos are considered. The H boson is reconstructed as a single large-radius jet, recoiling against the Z boson. Machine-learning flavour-tagging techniques are employed to identify decays of a Lorentz-boosted H boson into pairs of charm or bottom quarks, or into four quarks via the intermediate H → WW$^{*}$ and ZZ$^{*}$ decays. The analysis targets H boson decays that were not generally included in previous searches using the H → $ \textrm{b}\overline{\textrm{b}} $ channel. Compared with previous analyses, the sensitivity for high resonance masses is improved significantly in the channel where at most one b quark is tagged.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton–proton collisions at an energy of $\sqrt{s}=13\,\text {TeV} $ at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 $\,\text {fb}^{-1}$. A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to $\hbox {b}\bar{\hbox {b}}$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Benchmarking greenhouse gas emissions from US wastewater treatment for targeted reduction

Here, in this study, to assess the national climate impact of wastewater treatment and inform decarbonization, we assembled a comprehensive greenhouse gas inventory of 15,863 facilities in the contiguous USA. Considering location and treatment configurations, we modelled on-site CH 4 , N 2 O and CO 2 production and emissions associated with energy, chemical inputs and solids disposal. Using Monte Carlo simulations, we estimated median national emissions at 47 million tonnes of CO 2 equivalent per year, with on-site process CH 4 and N 2 O emissions exceeding current government estimates by 41%. Treatment configurations with anaerobic digesters are responsible for 16 million tonnes of CO 2 equivalent per year of fugitive methane, outweighing benefits achieved through on-site electricity generation. Systems designed for nutrient removal have the highest greenhouse gas emissions intensity, attributable to energy requirements and N 2 O production, demonstrating current trade-offs between meeting water quality and climate objectives. We analysed key sensitivities and included a geospatial analysis to highlight the scale and distribution of opportunities for reducing life cycle greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗

Correlation between oxygen evolution reaction activity and surface compositional evolution in epitaxial La 0.5 Sr 0.5 Ni 1– x Fe x O 3– δ thin films

Water electrolysis can use renewable electricity to produce green hydrogen, a portable fuel and sustainable chemical precursor. Improving electrolyzer efficiency hinges on the activity of the oxygen evolution reaction (OER) catalyst. Earth-abundant, ABO 3 -type perovskite oxides offer great compositional, structural, and electronic tunability, with previous studies showing compositional substitution can increase the OER activity drastically. However, the relationship between the tailored bulk composition and that of the surface, where OER occurs, remains unclear. Here, we study the effects of electrochemical cycling on the OER activity of La 0.5 Sr 0.5 Ni 1– x Fe x O 3– δ ( x = 0–0.5) epitaxial films grown by oxide molecular beam epitaxy as a model Sr-containing perovskite oxide. In this work, electrochemical testing and surface-sensitive spectroscopic analyses show Ni segregation, which is affected by electrochemical history, along with surface amorphization, coupled with changes in OER activity. Our findings highlight the importance of surface composition and electrochemical cycling conditions in understanding OER performance, suggesting common motifs of the active surface with high surface area systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Partial PdAu nanoparticle embedding into TiO 2 support accentuates catalytic contributions from the Au/TiO 2 interface

Despite the broad catalytic relevance of metal–support interfaces, controlling their chemical nature, the interfacial contact perimeter (exposed to reactants), and consequently, their contributions to overall catalytic reactivity, remains challenging, as the nanoparticle and support characteristics are interdependent when catalysts are prepared by impregnation. Here, we decoupled both characteristics by using a raspberry-colloid-templating strategy that yields partially embedded PdAu nanoparticles within well-defined SiO 2 or TiO 2 supports, thereby increasing the metal–support interfacial contact compared to nonembedded catalysts that we prepared by attaching the same nanoparticles onto support surfaces. Between nonembedded PdAu/SiO 2 and PdAu/TiO 2 , we identified a support effect resulting in a 1.4-fold higher activity of PdAu/TiO 2 than PdAu/SiO 2 for benzaldehyde hydrogenation. Notably, partial nanoparticle embedding in the TiO 2 raspberry-colloid-templated support increased the metal–support interfacial perimeter and consequently, the number of Au/TiO 2 interfacial sites by 5.4-fold, which further enhanced the activity of PdAu/TiO 2 by an additional 4.1-fold. Theoretical calculations and in situ surface-sensitive desorption analyses reveal facile benzaldehyde binding at the Au/TiO 2 interface and at Pd ensembles on the nanoparticle surface, explaining the connection between the number of Au/TiO 2 interfacial sites (via the metal–support interfacial perimeter) and catalytic activity. Our results demonstrate partial nanoparticle embedding as a synthetic strategy to produce thermocatalytically stable catalysts and increase the number of catalytically active Au/TiO 2 interfacial sites to augment catalytic contributions arising from metal–support interfaces.

Lim, Kang Rui Garrick (ORCID:0000000321599844)↗

Optimal 1D Ly α forest power spectrum estimation – II. KODIAQ, SQUAD, and XQ-100

ABSTRACT We measure the 1D Ly α power spectrum P1D from Keck Observatory Database of Ionized Absorption toward Quasars (KODIAQ), The Spectral Quasar Absorption Database (SQUAD), and XQ-100 quasars using the optimal quadratic estimator. We combine KODIAQ and SQUAD at the spectrum level, but perform a separate XQ-100 estimation to control its large resolution corrections in check. Our final analysis measures P1D at scales k < 0.1 s km−1 between redshifts $z$ = 2.0–4.6 using 538 quasars. This sample provides the largest number of high-resolution, high-S/N observations; and combined with the power of optimal estimator it provides exceptional precision at small scales. These small-scale modes (k ≳ 0.02 s km−1), unavailable in Sloan Digital Sky Survey and Dark Energy Spectroscopic Instrument analyses, are sensitive to the thermal state and reionization history of the intergalactic medium, as well as the nature of dark matter. As an example, a simple Fisher forecast analysis estimates that our results can improve small-scale cut-off sensitivity by more than a factor of 2.

79 ASTRONOMY AND ASTROPHYSICS↗

Probabilistic Risk Assessment of a Light-Water Reactor Coupled with a High-Temperature Electrolysis Hydrogen Production Plant

This report details an expansion of the original two generic probabilistic risk assessments (PRAs) for the addition of a heat extraction system (HES) to a light-water reactor, one for a pressurized-water reactor and one for a boiling-water reactor. The new material in this revision includes a new HES design, direct electrical coupling of the nuclear power plant to the High-Temperature Electrolysis Facility (HTEF), and a smaller 100-MWt HTEF analysis. The results investigate the applicability of the potential licensing approaches, which do not require a full United States Nuclear Regulatory Commission licensing review. The PRAs are generic and include some assumptions. We eliminated many conservative assumptions from the preliminary pressurized-water reactor PRA report using design data for both the HES and HTEF. The PRA results indicate that the 10 CFR 50.59 licensing approach is justified due to the minimal increase in initiating event frequencies for all design basis accidents, with none exceeding 5.6%. The PRA results for core damage frequency and large early release frequency support the use of RG 1.174 as further risk information that supports a change without a full licensing amendment review. Further insights provided through hazard analyses and sensitivity studies confirm with high confidence that the safety case for licensing an HES addition and an HTEF sited 1.0 km from the nuclear power plant is strong and that the placement of a HTEF at 0.5 km is also a viable case. Site-specific information can alter these conclusions.

08 HYDROGEN↗

Measurement techniques for trace metals in coal-plant effluents: A brief review

The strong features and limitations of techniques for determining trace elements in aerosols emitted from coal plants are discussed. Techniques reviewed include atomic absorption spectroscopy, charged particle scattering and activation, instrumental neutron activation analysis, gas/liquid chromatography, gas chromatographic/mass spectrometric methods, X-ray fluorescence, and charged-particle-induced X-ray emission. The latter two methods are emphasized. They provide simultaneous, sensitive multielement analyses and lend themselves readily to depth profiling. It is recommended that whenever feasible, two or more complementary techniques should be used for analyzing environmental samples.

Singh, J. J.↗