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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 OSTI2024

Space-Time Structured Plasma Waves

Electrostatic waves play a critical role in nearly every branch of plasma physics from fusion to advanced accelerators, to astro, solar, and ionospheric physics. The properties of planar electrostatic waves are fully determined by the plasma conditions, such as density, temperature, ionization state, or details of the distribution functions. Furthermore we demonstrate that electrostatic wave packets structured with space-time correlations can have properties that are independent of the plasma conditions. For instance, an appropriately structured electrostatic wave packet can travel at any group velocity, even backward with respect to its phase fronts, while maintaining a localized energy density. These linear, propagation-invariant wave packets can be constructed with or without orbital angular momentum by superposing natural modes of the plasma and can be ponderomotively excited by space-time structured laser pulses like the flying focus.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗
DOE OSTI2022

Vapor-Phase Aggregation of Cerium Oxide Nanoparticles in a Rapidly Cooling Plasma

Local conditions, such as temperature and oxygen availability, have a pronounced effect on the formation and evolution of fallout following a nuclear explosion. While the behavior of nuclear-relevant materials such as uranium has begun to be explored under a wider range of environments, little is known about the behavior of plutonium. Here, using cerium as a surrogate, we track the vapor-phase aggregation of cerium oxide nanoparticles created in a plasma flow reactor under conditions of controlled temperature at two different oxygen fugacities. In situ optical emission spectroscopy is used to measure the variations in the spectral intensity of atomic and molecular species with temperature and oxygen content. We find that the relative rate of gas-phase oxidation of cerium is highly dependent on both temperature and local redox conditions within the flow reactor, to the extent that doubling the oxygen availability effectively doubles the amount of vapor-phase cerium monoxide at high temperatures (>2000 K). Condensed cerium oxide nanoparticles are also collected and analyzed ex situ via transmission electron microscopy and grazing-incidence small-angle X-ray scattering to determine their elemental composition, crystal structure, and size distribution. The size and morphology of the condensed nanoparticles are independent of local redox conditions, forming the same crystal type with the same size distribution regardless of oxygen availability. Postcondensation particle evolution, however, is found to be predominantly driven by temperature, with the average particle size increasing as particles cool and subsequently aggregate. These results expand our understanding of the chemical and physical behavior of refractory oxides that form during the early stages of fallout formation.

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

Protective effects of non–catalytic proteins on endoglucanase activity at air and lignin interfaces

The manner in which added non-catalytic proteins during enzymatic hydrolysis of lignocellulosic substrates enhances hydrolysis mechanisms is not completely understood. Prior research has indicated that a reduction in the non-specific adsorption of enzymes on lignin, and deactivation of enzymes exposed to air–liquid interface provide rationale. This work investigated root causes including effects of the air–liquid interface on non-catalytic proteins, and effects of lignin on endoglucanase. Three different experimental designs and three variables (air–liquid interfacial area, the types of lignin (acid or enzymatic lignin), and the presence of non-enzymatic protein (bovine serum albumin [BSA] or soy proteins ) were used. The results showed that acid isolated lignin adsorbed almost all endoglucanase activity initially present in supernatant, independent of air interface conditions (25 or 250 ml flasks) with the presence of BSA preventing this effect. Endoglucanase lost 30%–50% of its activity due to an air–liquid interface in the presence of lignin while addition of non-enzymatic protein helped to preserve this enzyme's activity. Langmuir and Freundlich models applied to experimental data indicated that the adsorption increases with increasing temperature for both endoglucanase and BSA. Adsorption of the enzyme and protein were endothermic with an increase in entropy. Finally, these results, combined, show that hydrophobicity plays a strong role in the adsorption of both endoglucanase and BSA on lignin.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Data-driven analysis and prediction of wastewater treatment plant performance: Insights and forecasting for sustainable operations

Here this study presents a comprehensive performance and forecasting analysis of the As-Samra wastewater treatment plant (WWTP) in Jordan, with two main objectives. Firstly, a thorough evaluation of the plant's performance is conducted. The analysis involves independently assessing historical operational conditions, plant production, and their statistical correlations using various statistical techniques. The second objective focuses on developing a data-driven forecasting approach to predict the plant's production one month in advance, using multiple machine learning models. The results highlight the effectiveness of principal component analysis (PCA) in simplifying operational data, revealing distinct operational clusters, and identifying seasonal production patterns while showing correlations between operational conditions and overall power production. The support vector machine (SVM) forecasting model emerged as the top performer, showcasing the potential of a hybrid forecasting approach. The findings offer valuable perspectives for enhancing operational efficiency, refining production planning, and ultimately improving the environmental impact of the plant.

42 ENGINEERING↗
DOE OSTI2020

Anomalous Anisotropic Nanoparticle Aggregation in Cu 2 (OH) 3 Br Gels

Aerogels are of interest for their ability to uniformly incorporate nanoscale features into macroscopic assemblies, which enabled applications that require low density, high surface area, and/or bicontinuous networks. The structure of the nanoporous network is intrinsically linked to the macroscopic properties of aerogels. Hence, control of this structure is of paramount importance. Small-angle X-ray scattering (SAXS) is used here to monitor nanoparticle aggregation in situ in Cu 2 (OH) 3 Br aerogels formed via epoxide-assisted gelation. Anomalous anisotropic aggregation is observed in the absence of templating agents and is attributed to the molecular structure of the inorganic nanoparticles themselves. This is a fundamental departure from the models currently used to describe traditional inorganic sol–gel chemistry where nanoparticles are believed to undergo isotropic diffusion- and/or kinetically limited aggregation. Time-resolved SAXS indicates that Cu 2 (OH) 3 Br nanoparticles nucleate rapidly from solution to form unbranched chain-like aggregates rather than branched mass-fractal aggregates. Sizes of primary particles (~1.5 nm) and the chain-like structure of their aggregates are independent of particle concentration (gel density), while rates of particle aggregation, gelation time, and aggregate size are strongly dependent upon particle concentration, which implies that the chemistry of particle formation and the physics of particle aggregation are independent processes. Because the conditions necessary for creating anisotropic structures are not unique to Cu 2 (OH) 3 Br, these results could provide insight into the structure and gelation mechanisms of other inorganic aerogels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Design of Twisted Two-Dimensional Heterostructures and Performance Regulation Descriptor for Electrocatalytic Ammonia Production from Nitric Oxide

The electrocatalytic reduction of nitric oxide (NO) to ammonia (NH 3 ) represents an attractive alternative for valorizing waste NO streams (NORR). However, discovering efficient catalysts for NO-to-NH 3 conversion remains challenging. We have designed metal-intercalated twisted graphene-BN heterostructures, in which metal atoms act as electron-transfer bridges. The twisted configuration facilitates cross-interface charge transfer, redistributing electrons from the graphene–metal interface to the metal–BN interface and BN surface. This electronic modulation enables boron atom adjacent to the metal center in BN to serve as active sites, promoting strong chemisorption and enhanced activation of NO. After high-throughput screening of the stability and NO capture ability of various transition metal-intercalated twisted heterostructures, we have investigated systematically the NORR pathways across 30 candidates. The results show that the rBN-Ti-Gθ and rBN-V-Gθ heterostructures exhibit exceptional NO-to-NH 3 catalytic performance under optimized twisting conditions. Additionally, using sure independence screening and sparsifying operator (SISSO) for model training, we propose a descriptor and establish a relationship between the twist angle and catalytic activity. This study bridges the gap in applying twisted heterostructures to NORR electrocatalysis and provides new insights and strategies for designing high-performance NORR catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Violation of energy conditions and the gravitational radius of the proton

The energy-momentum tensor (EMT) of the proton encodes fundamental information about its mass, pressure, and shear distributions. Using recent lattice QCD data for the gravitational form factors, we show that the Breit-frame Wigner EMT may be of Hawking-Ellis type IV in the proton’s core. Such EMT violates all pointwise energy conditions and lacks a causal rest frame so that the usual mechanical picture fails at short distances. We define the —a new hadronic observable—marking the scale where the EMT becomes ordinary (type I) and the classical interpretation is restored. We also derive from the averaged null energy condition nonperturbative, model-independent quantum field theory constraints on gravitational form factors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches

Abstract. Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable and has to be inferred from models instead, such as semi-empirical bookkeeping models and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an important example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called loss of additional sink capacity (LASC). The LASC results from the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation and accumulates over time, which is not captured in bookkeeping models. The fLULCC from transient DGVM simulations, thus, strongly depends on the timing of land use and land cover changes mainly because LASC accumulation is cut off at the end of the simulated period. To estimate the LASC, the fLULCC from pre-industrial DGVM simulations, which is independent of changing environmental conditions, can be used. Additionally, DGVMs using constant present-day environmental forcing enable an approximation of bookkeeping estimates. Here, we analyse these three DGVM-derived fLULCC estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO2-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0±0.6 PgC yr−1 for 2009–2018, of which ∼40 % are attributable to the LASC (0.8±0.3 PgC yr−1). From 1850 onward, the fLULCC accumulated to 189±56 PgC with 40±15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient fLULCC estimates to exceed estimates under present-day conditions, despite generally increased carbon stocks in the latter. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, equatorial Africa, and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of fLULCC estimates on the time a certain land use and land cover change event happened to occur and on the chosen time period for the forcing of environmental conditions in the underlying simulations. We argue for an approach that provides an accounting of the fLULCC that is more robust against these choices, for example by estimating a mean DGVM ensemble fLULCC and LASC for a defined reference period and homogeneous environmental changes (CO2 only).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Foreign Entity of Concern Requirements in the One Big Beautiful Bill Act

The One Big Beautiful Bill Act (OBBB), enacted July 4, 2025, makes billions of dollars in federal energy tax credits conditional on supply chain independence from China and other foreign entities of concern. The OBBB simultaneously creates powerful economic incentives to reshore energy supply chains to the United States and allied nations. Through such incentives, the OBBB elevates digital assurance and supply chain verification from voluntary best practices into critical capabilities for demonstrating tax credit eligibility. The OBBB uses tax credit eligibility requirements to simultaneously address national security concerns regarding foreign supply chain dependencies and incentivize domestic energy manufacturing. This brief details how organizations should operationalize these requirements through baseline compliance audits, interim documentation systems, supply chain diversification strategies, and long-term institutional integration of digital assurance capabilities that turn compliance burdens into competitive advantages

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2025

A Scalable Interior‐Point Gauss–Newton Method for PDE‐Constrained Optimization With Bound Constraints

Here, we present a scalable approach to solve a class of partial differential equation (PDE)‐constrained optimization problems with bound constraints. This approach utilizes a robust full‐space interior‐point (IP)‐Gauss–Newton optimization method. To cope with the poorly‐conditioned IP‐Gauss–Newton saddle‐point linear systems that need to be solved approximately, once per optimization step, we propose two spectrally related preconditioners. These preconditioners leverage the limited informativeness of data in regularized PDE‐constrained optimization problems. A block Gauss–Seidel preconditioner is proposed for the GMRES‐based solution of the IP‐Gauss–Newton linear systems. It is shown, for a large‐class of PDE‐ and bound‐constrained optimization problems, that the spectrum of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix is asymptotically independent of discretization and is not impacted by the ill‐conditioning that notoriously plagues interior‐point methods. We exploit symmetry of the IP‐Gauss–Newton linear systems and propose a regularization and log‐barrier Hessian preconditioner for the preconditioned conjugate gradient (PCG)‐based solution of the equivalent IP‐Gauss–Newton–Schur complement linear systems. The eigenvalues of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix, that are not equal to one, are identical to the eigenvalues of the regularization and log‐barrier Hessian preconditioned Schur complement matrix. The scalability of the approach is demonstrated on two example problems. The numerical solution of these optimization problems is shown to require a discretization independent number of IP‐Gauss–Newton linear solves. Furthermore, the linear systems are solved in a discretization and IP ill‐conditioning independent number of preconditioned Krylov subspace iterations. The parallel scalability of the preconditioner, achieved via algebraic multigrid component solvers when applicable, and the aforementioned algorithmic scalability permits a parallel scalable means to compute solutions of a large class of PDE‐ and bound‐constrained problems.

PDE-constrained optimization↗
DOE OSTI2024

FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization

Annual energy production (AEP) is commonly used in objective functions for wind farm layout optimization. AEP is proportional to wind farm power production integrated over an annual distribution of free-stream wind conditions. Physics-based estimates of wind farm power production typically rely on low-fidelity engineering wake models that approximate the steady-state wind farm flow field. AEP estimates are then obtained by performing independent simulations for discrete wind conditions and using rectangular quadrature to account for each condition's expected frequency of occurrence. Depending on the number of simulated discrete wind conditions, this numerical integral could be hampered by poor accuracy or high computational costs. The FLOWERS AEP model instead poses an analytical integral of the engineering wake model over the variable wind conditions, yielding a closed-form, analytical function for wind farm AEP. This paper derives the analytical functions for FLOWERS AEP and its derivatives with respect to turbine position, which are useful for gradient-based wind farm layout optimization, in nondimensional form. We then analyze the benefits of the FLOWERS AEP model over conventional reference models, focusing on its low cost, adequate wake loss predictions, and smooth design space. Although the FLOWERS approach is found to predict the exact value of AEP with some error relative to the reference model (within 14% on average), it dramatically reduces computation time by an order of magnitude, produces a qualitatively similar design space at relatively low resolution, and yields comparable optimal layouts. This significant speed improvement is critical in layout optimization applications, where determining an optimal layout in an efficient manner is more important than precise AEP prediction.

17 WIND ENERGY↗
DOE OSTI2025

First measurement of symmetric cumulants of hexagonal flow harmonics in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

Correlations between event-by-event fluctuations of anisotropic flow harmonics are measured in Pb-Pb collisions at a center-of-mass energy per nucleon pair of 5.02 TeV, as recorded by the ALICE detector at the LHC. This study presents correlations up to the hexagonal flow harmonic 𝑣 6 , which was measured for the first time. The magnitudes of these higher-order correlations are found to vary as a function of collision centrality and harmonic order. These measurements are compared to viscous hydrodynamic model calculations with EKRT initial conditions and to the iEBE-VISHNU model with T R ⁢ENTo initial conditions. The observed discrepancies between the data and the model calculations vary depending on the harmonic combinations. Due to the sensitivity of model parameters estimated with Bayesian analyses to these higher-order observables, the results presented in this work provide new and independent constraints on the initial conditions and transport properties in theoretical models used to describe the system created in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Etching of Si 3 N 4 induced by electron beam plasma from hollow cathode plasma in a downstream reactive environment

An etching system based on the interaction of electrons extracted from a direct current (DC) hollow-cathode (HC) Ar plasma and injected towards a Si3N4 covered silicon substrate located in the downstream reactive environment created by an additional remote CF 4 /O 2 plasma source was developed and evaluated. By controlling the properties of the injected beam electrons, this approach allows to deliver energy to a surface functionalized by exposure to reactive species, and initiate surface etching. The energy of the primary beam electrons is controlled by the acceleration voltage relative to the HC discharge. Ar atoms flow from the high-pressure HC discharge into the low pressure downstream reactive environment in the process chamber. For an acceleration voltage greater than the ionization potential of Ar and/or process gas species, the energetic primary beam electrons produce a secondary plasma in the process chamber, and can also cause additional dissociation. We have characterized the properties of the secondary plasma and also surface etching of Si 3 N 4 as a function of process parameters, including acceleration voltage (0-80 V), discharge current of the HC discharge (1-2 A), pressure (3.5-20 mTorr), source to substrate distance (1.5 to 5 cm), and feed gas composition (20% and 80% O2 in CF 4 /O 2 ). The electron energy probability function (EEPF) measured with a Langmuir probe about 2.5 cm below the extraction ring suggests several major groups of electrons for this situation, including high energy primary beam electrons with an energy that varies as the acceleration voltage is changed and low energy electrons produced by beam electron-induced ionization of the Ar gas in the process chamber. When a remote CF 4 /O 2 plasma is additionally coupled to the process chamber, Si 3 N 4 surfaces can be functionalized, and by varying the energy of the beam electrons, Si 3 N 4 etching can be induced by electron-neutral synergy effect with plasma-surface interaction. For conditions without beam electron injection, the remote plasma etching rate (ER) of Si 3 N 4 depends strongly on the O 2 concentration in the CF 4 /O 2 processing gas mixture and can be suppressed for O 2 -rich process conditions by the formation of a SiONF passivation layer on the Si 3 N 4 surface. The combination of the HC electron beam source with the remote plasma source (HCEB-RP) makes it possible to induce Si 3 N 4 etching for O 2 -rich remote plasma conditions where remote plasma by itself produces negligible Si 3 N 4 etching. The electron enhanced etching of Si 3 N 4 depends strongly on O 2 /CF 4 mixing ratio reflecting changing arrival rates of O and F species at the surface. Optical emission spectroscopy was used to estimate the ratio of gas phase F and O densities and found to be controlled by the gas mixing ratio and independent of HC EB operating conditions. At this time the detailed sequence of events operative in the etching mechanism is unclear. While the increase of the electron energy is ultimately responsible for initiating surface etching, at present we cannot rule out a role of ions from the simultaneously produced secondary plasma in plasma surface interaction mechanisms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Melting rate correlation with batch properties and melter operating conditions during conversion of nuclear waste melter feeds to glasses

The rate of conversion of nuclear waste melter feed to glass is affected by the selection of melter feed materials and by melter design and operation. The melting rate correlation (MRC) is an equation that relates the glass production rate with two types of variables: (1) feed and melt properties: conversion heat, cold-cap bottom temperature, and glass melt viscosity; and (2) melter design and operation parameters: melter geometry, melter operating temperature, and gas bubbling rate. The MRC shows good agreement for an extended melting-rate data set of high-level waste (HLW) melter feeds and a data set generated for low-activity waste (LAW) melter feeds. Laboratory observation of heated melter feed samples is often used to assess the cold-cap bottom temperature of HLW melter feeds (moderately foaming feeds), but this technique appears inadequate for LAW melter feeds (vigorously foaming feeds). For LAW feeds, an adequate assessment of the cold-cap bottom temperature was achieved using evolved gas analysis, which allows identification of the collapse of primary foam for oxidized feeds. This assessment shows that the cold-cap bottom temperature for vigorously foaming LAW feeds is higher than that for moderately foaming HLW feeds. When the results of MRC are compared, LAW feeds are generally less sensitive to the bubbling rate and melt viscosity, and more sensitive to the cold-cap bottom temperature than HLW feeds. The MRC qualifies as a promising tool to support the selection of melter feed materials and melter operating conditions, which is determined from expensive independent scaled melter experiments, and sophisticated mathematical models.

Lee, Seung Min↗
DOE OSTI2024

Coupled Experimental–Theoretical Characterization of a Carbon Electrode in Vanadium Redox Flow Batteries using X-ray Absorption Spectroscopy

Vanadium redox flow batteries (VRFBs) have emerged as promising solutions for stationary grid energy storage due to their high efficiency, scalability, safety, near room-temperature operation conditions, and the ability to independently size power and energy capacities. The performance of VRFBs heavily relies on the redox couple reactions of V 2+ /V 3+ and VO 2+ /VO 2 + on carbon electrodes. Therefore, a thorough understanding of the surface functionality of carbon electrodes and their propensity for degradation during electrochemical cycles is crucial for designing VRFBs with extended lifespans. In this study, we present a coupled experimental–theoretical approach based on carbon K edge X-ray absorption spectroscopy (XAS) to characterize carbon electrodes prepared under different conditions and identify relevant functional groups that contribute to unique spectroscopic features. Atomic models were created to represent functional groups, such as hydroxyl, carboxyl, methyl, and aldehyde, bonded to carbon atoms in either sp 2 or sp 3 environments. The interactions between functionalized carbon and various solvated vanadium complexes were modeled using density functional theory. A library of carbon K-edge XAS spectra was generated for distinct carbon atoms in different functional groups, both before and after interacting with solvated vanadium complexes. Here we demonstrate how these simulated spectra can be used to deconvolve ex situ experimental spectra measured from carbon electrodes and to track changes in the electrode composition following immersion in different electrolytes or extended cycling within a functional VRFB. By doing so, we identify the active species present on the carbon electrodes, which play a crucial role in determining their electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2024

A comparison of model validation approaches for echo state networks using climate model replicates

As global temperatures continue to rise, climate mitigation strategies such as stratospheric aerosol injections (SAI) are increasingly discussed, but the downstream effects of these strategies are not well understood. As such, there is interest in developing statistical methods to quantify the evolution of climate variable relationships during the time period surrounding an SAI. Feature importance applied to echo state network (ESN) models has been proposed as a way to understand the effects of SAI using a data-driven model. This approach depends on the ESN fitting the data well. If not, the feature importance may place importance on features that are not representative of the underlying relationships. Typically, time series prediction models such as ESNs are assessed using out-of-sample performance metrics that divide the times series into separate training and testing sets. However, this model assessment approach is geared towards forecasting applications and not scenarios such as the motivating SAI example where the objective is using a data driven model to capture variable relationships. Here, in this paper, we demonstrate a novel use of climate model replicates to investigate the applicability of the commonly used repeated hold-out model assessment approach for the SAI application. Simulations of an SAI are generated using a simplified climate model, and different initialization conditions are used to provide independent training and testing sets containing the same SAI event. The climate model replicates enable out-of-sample measures of model performance, which are compared to the single time series hold-out validation approach. For our case study, it is found that the repeated hold-out sample performance is comparable, but conservative, to the replicate out-of-sample performance when the training set contains enough time after the aerosol injection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Controlled photo-discharge of dust in a complex plasma

One of the limitations in studying dusty plasmas is that many of the important properties of the dust (like the charge) are directly coupled to the surrounding plasma conditions rather than being determined independently. The application of high-intensity ultraviolet (UV) sources to generate discharging photoelectric currents may provide an avenue for developing methods of controlling dust charge. Careful selection of the parameters of the UV source and dust material may even allow for this to be accomplished with minimal perturbation of the background plasma. The Auburn Magnetized Plasma Research Laboratory (MPRL) has developed a ‘proof-of-concept’ experiment for this controlled photo-discharging of dust; a high-intensity, near-UV source was used to produce large changes in the equilibrium positions of lanthanum hexaboride ( $\textrm {LaB}_6$ ) particles suspended in an argon DC glow discharge with negligible changes in the potential, density and temperature profiles of the background plasma. The shifts in equilibrium position of the dust are consistent with a reduction in dust charge. Video analysis is used to quantify the changes in position, velocity and acceleration of a test particle under the influence of the UV and Langmuir probes are used to measure the effects on the plasma.

Physics↗