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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Distributed Rules-Based Deconfliction of ADMS Applications: Part 1: Requirements & Decomposition

This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. This first document introduces the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem is decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. Selection of the optimal number of decompositions of the deconfliction problem should be made based on a tradeoff analysis between computational speed and global optimality. This second document will define an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Catalytic Site Requirements for N2O Decomposition on Cu-, Co-, and Fe-SSZ-13 Zeolites

N2O decomposition is investigated on Cu, Co and Fe-exchanged SSZ-13 zeolite catalysts at relatively low metal loadings. The catalysts are synthesized by solution ion exchange, and subjected to X-ray diffraction (XRD), temperature-programed-reduction by H2 (H2-TPR), temperature-programed-reaction of N2O (N2O-TPR) coupled with in-situ transmission FTIR, and finally steady-state flow reaction tests. At low N2O pressures (< 0.05 kPa), all catalysts display pseudo first-order kinetics. From Arrhenius analysis, Cu and Fe-SSZ-13 display very different apparent activation energies but similar pre-exponential factors, suggesting their similar reaction mechanisms. N2O decomposition follows a dual-site mechanism, occurring on dimeric M-O-M sites in these catalysts, and O2 is formed by the combination of two O ad-atoms from two vicinal metal sites. Under low N2O pressure (0.05 kPa) and first-order kinetic regime, the reaction is limited by N-O cleavage on bare metal active sites. In comparison to Cu-SSZ-13, the much higher N2O decomposition rate over Fe-SSZ-13 is attributed to the much lower activation barriers for the N-O cleavage step. N2O decomposition occurs on isolated Co2+ ions in Co-SSZ-13. The rate-limiting step is N-O cleavage on an O-occupied Co site in the low-pressure first order kinetic regime. This single-site mechanism leads to much higher pre-exponential factors as compared to the dual-site mechanism. This beneficial factor for reaction rate enhancement, however, is compromised by the much higher activation barriers over this catalyst.

Lin, Fan↗
DOE OSTI2025

SNoGloDe: A Structured Nonlinear Global Decomposition Solver

Large-scale optimization problems often require decomposition strategies and customized algorithms to achieve optimal solutions within a reasonable time. Building on the work of Cao and Zavala (2019) for solving nonlinear two-stage stochastic programs to global optimality, we implement and extend their approach. We generalize to optimization problems reformulated with a block-angular constraint structure (e.g., temporal decomposition). Our framework, written in Python using Pyomo, is highly customizable and enables parallel execution of the decomposition. SNoGloDe allows tailored branching strategies, lower bounding problems, and candidate generators to leverage problem-specific knowledge. To demonstrate effectiveness, we compare SNoGloDe’s performance with Gurobi on a temporally decomposed produced water case study.

algorithms↗
DOE OSTI2014

The chemical instability of Na{sub 2}IrO{sub 3} in air

Highlights: • Na{sub 2}IrO{sub 3} decomposes rapidly in laboratory air. • The decomposition requires the simultaneous presence of CO{sub 2} and H{sub 2}O. • Decomposition results in a dramatic change in the magnetic properties. • Second 5 K feature in magnetic susceptibility not previously reported. - Abstract: We report that Na{sub 2}IrO{sub 3}, which has a layered honeycomb iridium oxide sublattice interleaved by Na planes, decomposes in laboratory air while maintaining the same basic crystal structure. The decomposition reaction was monitored by time-dependent powder X-ray diffraction under different ambient atmospheres, through which it was determined that it occurs only in the simultaneous presence of both CO{sub 2} and H{sub 2}O. A hydrated sodium carbonate is the primary decomposition product along with altered Na{sub 2}IrO{sub 3}. The diffraction signature of the altered Na{sub 2}IrO{sub 3} is quite similar to that of the pristine material, which makes the detection of decomposition difficult in a sample handled under ordinary laboratory conditions. The decomposed samples show a significantly decreased magnetic susceptibility and the disappearance of the low temperature antiferromagnetic transition considered to be characteristic of the phase. Samples that have never been exposed to air after synthesis display a previously unreported magnetic transition at 5 K.

36 MATERIALS SCIENCE↗
DOE OSTI2014

On computing stress in polymer systems involving multi-body potentials from molecular dynamics simulation

Hardy stress definition has been restricted to pair potentials and embedded-atom method potentials due to the basic assumptions in the derivation of a symmetric microscopic stress tensor. Force decomposition required in the Hardy stress expression becomes obscure for multi-body potentials. In this work, we demonstrate the invariance of the Hardy stress expression for a polymer system modeled with multi-body interatomic potentials including up to four atoms interaction, by applying central force decomposition of the atomic force. The balance of momentum has been demonstrated to be valid theoretically and tested under various numerical simulation conditions. The validity of momentum conservation justifies the extension of Hardy stress expression to multi-body potential systems. Computed Hardy stress has been observed to converge to the virial stress of the system with increasing spatial averaging volume. This work provides a feasible and reliable linkage between the atomistic and continuum scales for multi-body potential systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

3D And 4D Cloud Lifecycle Investigations Using Innovative Scanning Radar Analysis Methods. Final report

With the vast upgrades to the ARM program radar measurement capabilities in 2010 and beyond, our ability to probe the 3D structure of clouds and associated precipitation has increased dramatically. This project build on the PI's and co-I's expertisein the analysis of radar observations. The first research thrust aims to document the 3D morphological (as depicted by the radar reflectivity structure) and 3D dynamical (cloud$-$scale eddies) structure of boundary layer clouds. Unraveling the 3D dynamical structure of stratocumulus and shallow cumulus clouds requires decomposition of the environmental wind contribution and particle sedimentation velocity from the observed radial Doppler velocity. The second thrust proposes to unravel the mechanism of cumulus entrainment (location, scales) and its impact on microphysics utilizing radar measurements from the vertically pointing and new scanning radars at the ARM sites. The third research thrust requires the development of a cloud$-$tracking algorithm that monitors the properties of cloud.

3D structure↗
DOE OSTI2024

Modeling Interactive Effects of Manganese Bioavailability, Nitrogen Deposition, and Warming on Soil Carbon Storage

Manganese (Mn) is a redox–active micronutrient that has been shown to accelerate plant litter decomposition; however, the effect of Mn–promoted decomposition on soil C storage is unclear. We present a novel biogeochemical model simulating how Mn bioavailability influences soil organic C (SOC) stocks in a soil profile (<50 cm) within a temperate forest. In our model, foliar Mn increased in response to increasing soluble Mn released through Mn–oxide (birnessite) dissolution in mineral soil layers. The ensuing Mn enrichment in leaf litter redistributed Mn to the surface forest floor layer, promoted enzymatic oxidation of lignin, and decreased SOC stocks. Total SOC loss was partially mitigated by accumulation of lignin–oxidation products as mineral–associated organic C. We also explored how Mn–driven changes to C storage interacted with effects of N deposition and warming. Nitrogen enrichment inhibited Mn–dependent lignin degradation, increasing SOC stocks and weakening their dependence on Mn bioavailability. Warming stimulated decomposition and reduced C stocks but was less effective at low Mn bioavailability. Our model results suggest that SOC stocks are sensitive to Mn bioavailability because increased plant uptake redistributes Mn to surface soils where it can enhance litter decomposition. Finally, based on our simulations, we predict that Mn becomes limiting to litter decomposition where Mn is poorly soluble. Depletion of bioavailable Mn or other cofactors that are critical to decomposition could limit the response of organic C stocks to warming over time, but quantitative projections of the role of Mn bioavailability in regulating decomposition requires additional measurements to constrain model uncertainties.

58 GEOSCIENCES↗
DOE OSTI2019

Exploring redshift-space distortions in large-scale structure

We explore and compare different ways large-scale structure observables in redshift-space and real space can be connected. These include direct computation in Lagrangian space, moment expansions and two formulations of the streaming model. Here we derive for the first time a Fourier space version of the streaming model, which yields an algebraic relation between the real- and redshift-space power spectra which can be compared to earlier, phenomenological models. By considering the redshift-space 2-point function in both configuration and Fourier space, we show how to generalize the Gaussian streaming model to higher orders in a systematic and computationally tractable way. We present a closed-form solution to the Zeldovich power spectrum in redshift space and use this as a framework for exploring convergence properties of different expansion approaches. While we use the Zeldovich approximation to illustrate these results, much of the formalism and many of the relations we derive hold beyond perturbation theory, and could be used with ingredients measured from N-body simulations or in other areas requiring decomposition of Cartesian tensors times plane waves. Lastly, we finish with a discussion of the redshift-space bispectrum, bias and stochasticity and terms in Lagrangian perturbation theory up to 1-loop order.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Permeable Membrane Reactor for Ammonia Decomposition - RUPS

The generation of impurities in gas processing facilities must be counteracted to minimize downstream impacts to process components and piping. Reservoir Unloading Purification System (RUPS) is an umbrella term describing research and development activities to remove impurities from current and future facility gases. As the application of developed RUPS technologies matures, the technologies will be verified in the Hydrogen Processing Demonstration System (HPDS) to provide a holistic view of the process before future implementation. By adding catalyst, it is possible to decrease the activation energy typically required for decomposition of ammonia. This allows a drastic decrease in required temperatures necessary for the reaction to take place in a permeable membrane reactor (PMR) (from > 650 deg. C to < 425 deg. C). A PMR was fabricated for scoping studies. The primary objective of this research is to determine whether the use of a PMR containing ruthenium catalyst can provide a favorable environment for maximum ammonia decomposition at moderate temperatures. Scoping studies will be performed to determine the catalytic capability of Ru-Al{sub 2}O{sub 3} or Ru-SiO{sub 2} to determine the effectiveness of ammonia decomposition with a PMR. Tests will evaluate effects of: gas composition/impurity concentration, catalyst loading, test cell space velocity, and various carrier gases of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Interaction of light with the ZnO surface: Photon induced oxygen “breathing,” oxygen vacancies, persistent photoconductivity, and persistent photovoltage

ZnO surfaces adsorb oxygen in the dark and emit CO{sub 2} when exposed to white light, reminiscent of the lungs of living creatures. We find that this exchange of oxygen with the ambient affects the integrity of the ZnO surface. Thus, it forms a basis for several interesting surface phenomena in ZnO, such as photoconductivity, photovoltage, and gas sensing, and has a role in ZnO electrical conduction. Using x-ray photoelectron spectroscopy on ZnO nanowires, we observed a decomposition of ZnO under white light and formation of oxygen-depleted surface, which explains photoconductivity by the electron donation of oxygen vacancies. Our findings suggest that the observed decomposition of the ZnO lattice may only take place due to photon-induced reduction of ZnO by carbon containing molecules (or carbo-photonic reduction), possibly from the ambient gas, accounting in a consistent way for both the reduced demands on the energy required for decomposition and for the observed emission of lattice oxygen in the form of CO{sub 2}. The formation of oxygen-vacancy rich surface is suggested to induce surface delta doping, causing accumulation of electrons at the surface, which accounts for both the increase in conductivity and the flattening of the energy bands. Using surface photovoltage spectroscopy in ultra high vacuum, we monitored changes in the deep level spectrum. We observe a wide optical transition from a deep acceptor to the conduction band, which energy position coincides with the position of the so called “green luminescence” in ZnO. This green transition disappears with the formation of surface oxygen vacancies. Since the oxygen vacancies are donors, while the green transition involves surface acceptors, the results suggest that the initial emission of oxygen originates at the defect sites of the latter, thereby eliminating each other. This suggests that the green transition originates at surface Zn vacancy acceptors. Removing an oxygen atom from a Zn vacancy completes the vacancy to become a full ZnO molecule vacancy, which does not produce deep levels. Our results explain why ZnO finds use as an electrical detector for oxygen and for carbon containing gas molecules. They may also shed new light on photocatalytic uses of ZnO. It is suggested that similar surface phenomena may affect other semiconducting oxides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Multi-Scale Modeling for Plasma-Enhanced Ammonia Decomposition over Carbides and Nitrides

Ammonia is a carbon-free hydrogen carrier, but its decomposition typically requires high temperatures over costly Ru-based catalysts due to the large barrier for N≡N bond formation. We develop a multiscale framework combining density functional theory, zero-dimensional plasma kinetics, and microkinetic modeling to elucidate how non-thermal plasma (NTP) enables low-temperature NH 3 decomposition over Co-based carbides and nitrides, benchmarked against Ru and Co. Under thermal conditions, all catalysts are limited by N≡N bond formation, with Co 3 C(001) most active owing to its negatively charged surface, strong N* binding, and low activation barriers of N≡N bond formation. Plasma-induced vibrational excitation of NH 3 and its reactive radicals promotes a radical-driven •NH 2 –N* coupling pathway that dominates on Co 3 C(001) and Co 3 N(001), shifting the rate-limiting step to NH 3 (v1) dissociation, increasing turnover frequencies by up to 6 orders of magnitude, and reducing the temperature needed to reach a turnover frequency of 5 s –1 from >680 °C (Ru and Co under thermal condition) to 267 °C (Co 3 C) and 415 °C (Co 3 N). These results identify Co-based carbides and nitrides as promising plasma-active catalysts for energy-efficient hydrogen production from ammonia.

ammonia decomposition↗
DOE OSTI2023

An Infinite Domain 3D Poisson Solver Based on the Barnes-Hut Algorithm

We present a domain decomposition method for the solution of the 3D Poisson equation with infinite domain boundary conditions. The method is based on an application of the Barnes-Hut tree particle scheme adapted to gridded data. Long range interactions are computed using the first two terms in the Cartesian multipole expansion of Green’s function convoluted with the charge while short range computations are performed using Hockney’s domain doubling algorithm. A standard domain decomposition strategy requires O(N 2 ) applications of Hockney’s algorithm, where N is the number of subdomains that intersect that charge support, while in the present approach only O(Nlog 2 N) such computations suffice. The discretization scheme employed is a sixth order Mehrstellen approximation of the 3D Laplace opera tor. The method exhibits satisfactory accuracy at a substantially reduced computational cost compared to the full domain decomposition Hockney’s algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems

The Koopman operator has recently garnered much attention for its value in dynamical systems analysis and data-driven model discovery. However, its application has been hindered by the computational complexity of extended dynamic mode decomposition; this requires a combinatorially large basis set to adequately describe many nonlinear systems of interest, e.g. cyber-physical infrastructure systems, biological networks, social systems, and fluid dynamics. Often the dictionaries generated for these problems are manually curated, requiring domain-specific knowledge and painstaking tuning. In this paper we introduce a deep learning framework for learning Koopman operators of nonlinear dynamical systems. We show that this novel method automatically selects efficient deep dictionaries, outperforming state-of-the-art methods. We benchmark this method on partially observed nonlinear systems, including the glycolytic oscillator and show it is able to predict quantitatively 100 steps into the future, using only a single timepoint, and qualitative oscillatory behavior 400 steps into the future.

koopman operators, machine learning, deep learning↗
DOE OSTI2019

Method to Extract System-Independent Material Properties From Dual-Energy X-Ray CT

In 2016, we published a method for processing dual-energy computed tomography (DECT) data called system-independent rho-e/Z-e (ρ e /Z e ) or SIRZ. Using data from multiple DECT systems and spectra, SIRZ estimated the electron density ρ e and effective atomic number Z e (based on published X-ray cross sections), for a set of known specimens. However, the decomposition process required complex spectral modeling of the DECT system, which made SIRZ difficult to implement and automate. This paper describes the subsequent work on “SIRZ-2” to simplify the spectral modeling, automate the process, and improve its range and versatility. The SIRZ-2 basis functions are more accurate for the X-ray energy range (<;200 keV) and materials that are common to DECT applications in security and nondestructive characterization. To evaluate the SIRZ-2 performance, eight well-characterized specimens (with Z e of 6-20) were scanned with multiple spectral pairs (up to 200 keV) on seven different DECT systems, including a commercial airport luggage scanner. For these varied tests, the average SIRZ-2 relative errors for ρ e estimates were four times lower (0.7% compared to 3.0% for SIRZ), while average Z e relative errors were comparably low for both methods (<;1.5%). Average precision errors were also low (<;2.3% for both). SIRZ-2 produces accurate, repeatable, and system-independent material property estimates of (ρ e , Z e ) that can be directly compared across DECT systems and over time.

42 ENGINEERING↗
DOE OSTI2019

An Efficient Mixed-Mode Representation of Sparse Tensors

The Compressed Sparse Fiber (CSF) representation for sparse tensors is a generalization of the Compressed Sparse Row (CSR) format for sparse matrices. For a tensor with d modes, typical tensor methods such as CANDECOMP/PARAFAC decomposition (CPD) require a sequence of d tensor computations, where efficient memory access with respect to different modes is required for each of them.The straightforward solution is to use d distinct representations of the tensor, with each one being efficient for one of the d computations. However, a d-fold space overhead is often unacceptable in practice, especially with memory-constrained GPUs. In this paper, we present a mixed-mode tensor representation that partitions the tensor’s nonzero elements into disjoint sections, each of which is compressed to create fibers along a different mode. Experimental results on the latest generation of GPU device demonstrate that better performance can be achieved by using the mixed-mode representation, while utilizing only a small fraction of the space required to keep d distinct CSF representations.

Nisa, Israt↗
DOE OSTI2019

Systems Engineering Project - Tritium

The purpose of this project is to apply a systems engineering method to a programmatic improvement or implementation of a system found within the Weapons and Complex Integration (WCI) Nuclear Materials Technology Program (NMTP) at Lawrence Livermore National Laboratory (LLNL). This project identifies an opportunity for improvement of the Tritium Processing Station (TPS) based on key stakeholder requirements. This document will cover the generation of the selected concept, system operational context and use cases, the production of verifiable engineering requirements, functional decomposition, and an assessment of risk via a failure mode and effect analysis (FMEA).

42 ENGINEERING↗