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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hybrid particle-spectral method for kinetic plasma simulations

A hybrid model for numerical solutions of the Vlasov–Poisson equations is presented, which blends spectral and particle approaches. The model splits the distribution function for plasma species into both spectral and particle representations in the velocity space to combine the advantages of each approach. The spectral representation leverages asymmetrically weighted Hermite basis, whereas the particle representation leverages the particle-in-cell method. Configuration phase space is decomposed with the Fourier method, which is well suited for periodic problems. We derive conservation equations for mass, momentum, and energy for the proposed combined method. It is shown that the coupling error between the two methods is absent in the semi-discrete setting (not taking into account time discretization). Finally, numerical test cases are presented simulating a weak electron beam interaction with plasma, leading to beam–plasma instability. The initially localized electron beam evolved into a highly non-equilibrium distribution function in the velocity space. A small growth rate and the resonance nature of instability make it difficult to obtain accurate solutions for purely particle methods due to noise, which falls as ~1/$\sqrt{N_p}$ with a number of particles. At the same time, purely spectral methods may require a large number of modes to capture the highly nonequilibrium state of the evolved beam. We show that the hybrid method is well suited for such problems: it reproduces the linear stage as well as nonlinear dynamics with sufficient accuracy using a highly non-equilibrium distribution function.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

NMF-Based Anomaly Detection in CMS 2D Tracking Occupancy Histograms

The CMS experiment relies on Data Quality Monitoring (DQM) to ensure that recorded collision data are suitable for physics analysis. During LHC Run 3, each run contains many lumisections and tracking monitoring elements, making offline inspection challenging, especially for localized detector effects that may appear only for short periods of time. This poster presents an unsupervised machine-learning approach to identify anomalous lumisections in CMS tracking occupancy histograms using Non-Negative Matrix Factorization (NMF). The workflow uses offline CMS DQMIO tracking histograms retrieved with the CMS DIALS API and organized as two-dimensional occupancy maps for each lumisection. After selecting stable lumisections, the occupancy maps are normalized and arranged into a non-negative data matrix. The NMF model learns a compact set of basis patterns describing normal tracking occupancy. Each lumisection is then reconstructed from these learned components, and the reconstruction error is used as an anomaly score. Large residuals indicate occupancy patterns that deviate from normal detector behavior and are flagged for further inspection. This NMF-based approach provides a fast and interpretable way to flag lumisections whose tracking occupancy patterns differ from normal detector behavior. Preliminary studies show sensitivity to known tracking anomalies, and ongoing work is focused on validating the method across additional Run 3 Pixel and Strip detector issues.

Rodríguez Ramos, Iliomar [Puerto Rico U., Mayaguez↗
DOE OSTI2026

Bond Dissociation Energies of the Actinide Halides AnX, An = Ac–Lr and X = F–I, Utilizing Relativistic Composite Coupled Cluster Approaches

Bond dissociation energies (BDEs) have been calculated for the set of actinide halides AnX with An=Ac, Pa, and Np-Lr and X=F-I. Two composite thermochemistry methods based on the Feller-Peterson-Dixon (FPD) approach have been utilized, one involving spinor-based relativistic CCSD(T) calculations where spin-orbit (SO) was included at the orbital level and another using scalar relativistic CCSD(T) with a posteriori SO contributions based on 2-component multireference configuration interaction calculations. The method that was chosen for a given actinide halide was based on which representation yielded the best single determinant reference determinant for the coupled cluster calculation. The spinor-based method was chosen for all cases except for AmX, CmX, and BkX. Both composite approaches included contributions accounting for basis set truncation, outer-core correlation, the Gaunt interaction, and QED. The scalar FPD results, as well as the spinor-based calculations for AcF, also included higher order electron correlation up through CCSDT(Q). In addition to BDEs, CCSD(T) equilibrium bond lengths, harmonic frequencies, and vibrational anharmonicity constants are reported for all species. Last, the FPD BDEs for the fluorides were used to confirm the trend across the actinide series previously predicted by Gibson using bonding models based atomic promotion energies that provide a single 6d electron for bonding. In particular the local minimum in the BDEs at AmF is confirmed in the present calculations. Furthermore, the BDEs for LrX are predicted to be slightly larger than those of AcX, making them the largest in the actinide halide series.

Actinides↗
DOE OSTI2022

Mechanisms of Complete Dissociation of CO 2 on Iron Clusters

Dissociation of CO 2 on iron clusters was studied by using semilocal density functional theory and basis sets of triple-zeta quality. Fe 2 , Fe 4 , and Fe 16 clusters were selected as the representative host clusters. When searching for isomers of Fe n CO 2 , n=2, 4 and 16 corresponding to carbon dioxide attachment to the host clusters, its reduction to O and CO, and to the complete dissociation, it was found that the total spin magnetic moments of the lowest energy states of the isomers are often quenched with respect to those of initial reagents Fe n +CO 2 . Dissociation pathways of the Fe 2 +CO 2 , Fe 4 +CO 2 , and Fe 16 +CO 2 reactions contain several transition states separated by the local minima states; therefore, a natural question is where do the spin flips occur? Since lifetimes of magnetically excited states were shown to be of the order of 100 fs, the search for the CO 2 dissociation pathways was performed under the assumption that magnetic deexcitation may occur at the intermediate local minima. Two dissociation pathways were obtained for each Fe n +CO 2 reaction using the gradient-based methods. It was found that the Fe 2 +CO 2 reaction is endothermic with respect to both reduction and complete dissociation of CO 2 , whereas the Fe 4 +CO 2 and Fe 16 +CO 2 reactions are exothermic to both reduction and complete dissociation of carbon dioxide. Finally, the CO 2 reduction was found to be more favorable than its complete dissociation in the Fe 4 case.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

How Does HF-DFT Achieve Chemical Accuracy for Water Clusters?

Bolstered by recent calculations of exact functional-driven errors (FEs) and density-driven errors (DEs) of semilocal density functionals in the water dimer binding energy , we investigate approximate FEs and DEs in neutral water clusters containing up to 20 monomers, charged water clusters, and alkali- and halide-water clusters. Our proxy for the exact density is r 2 SCAN 50, a 50% global hybrid of exact exchange with r 2 SCAN, which may be less correct than r 2 SCAN for the compact water monomer but importantly more correct for long-range electron transfers in the noncompact water clusters. We show that SCAN makes substantially larger FEs for neutral water clusters than r 2 SCAN, while both make essentially the same DEs. Unlike the case for barrier heights, these FEs are small in a relative sense and become large in an absolute sense only due to an increase in cluster size. SCAN@HF, short for SCAN evaluated on the Hartree–Fock (HF) density, produces a cancellation of errors that makes it chemically accurate for predicting the absolute binding energies of water clusters. Likewise, adding a long-range dispersion correction to r 2 SCAN@HF, as in the composite method HF-r 2 SCAN-DC4, makes its FE more negative than in r 2 SCAN@HF, permitting a near-perfect cancellation of FE and DE. r 2 SCAN by itself (and even more so, r 2 SCAN evaluated on the r 2 SCAN 50 density), is almost perfect for the energy differences between water hexamers, and thus probably also for liquid water away from the boiling point. Thus, the accuracy of composite methods like SCAN@HF and HF-r 2 SCAN-DC4 is not due to the HF density being closer to the exact density, but to a compensation of errors from its greater degree of localization. We also give an argument for the approximate reliability of this unconventional error cancellation for diverse molecular properties. Lastly, we confirm this unconventional error cancellation for the SCAN description of the water trimer via Kohn–Sham inversion of the CCSD(T) density.

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

Automated Scoring of Morphological Changes in Images of Pentaerythritol Tetranitrate

Recent advances in characterization techniques that generate large datasets of material microstructure images require robust, automated image-processing. We applied an unsupervised anomaly detection method called feature anomaly detection system (FADS) to automatically detect and quantify microstructure changes in images of the explosive pentaerythritol tetranitrate (PETN) aged at various temperatures. We demonstrated the FADS approach on two-dimensional images extracted from computed tomography scans, but the same technique can be readily applied to other imaging modalities. FADS calculates anomaly scores on the basis of differences in filter activations of nominal and test data in pretrained convolutional neural networks. The FADS scores successfully differentiated between pristine PETN and PETN aged at a temperature where material coarsening occurred. Morphological metric analysis of segmented images verified observed trends in FADS scores as a function of aging temperature and aging time, specifically by calculating volume fractions, specific boundary lengths, two-point correlation functions, and local thicknesses. Here, the FADS technique has two important advantages compared to traditional morphological analysis: First, it uses grayscale images as input, rather than images that are segmented to separate the appropriate phases; and second, FADS scores capture any type of changes among image sets, rather than requiring prior knowledge or selection of a relevant set of metrics.

Accelerated aging↗
DOE OSTI2025

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗
DOE OSTI2024

Kohn–Sham Density in a Slater Orbital Basis Set

Finite, atom-centered Slater basis sets are used to determine approximate Kohn–Sham molecular orbitals. This is achieved by minimizing the kinetic energy plus the sum-squared difference between the Kohn–Sham density and the full configuration interaction density. As a result of the finite basis, a weight factor is introduced to balance the two minimization components. Results herein show that this can be done systematically, without sensitive dependence on the choice of scaling factor. In addition, the algorithm is applied to the LiH diatomic for fractional electron counts, where stretching the bond introduces significant reorganization of the electron density. As a result, the analysis will show the correct KS orbital structure and reveal the effects of correlation and electron locality on the KS solutions.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Architectures and random properties of symplectic quantum circuits

Parametrized and random unitary (or orthogonal) n-qubit circuits play a central role in quantum information. As such, one could naturally assume that circuits implementing symplectic transformations would attract similar attention. However, this is not the case, as $\mathbb{SP}(d/2)$—the group of d × d unitary symplectic matrices—has thus far been overlooked. In this work, we aim at starting to fill this gap. We begin by presenting a universal set of generators $\mathcal{G}$ for the symplectic algebra $\mathfrak{sp}(d/2)$, consisting of one- and two-qubit Pauli operators acting on neighboring sites in a one-dimensional lattice. Here, we uncover two critical differences between such set, and equivalent ones for unitary and orthogonal circuits. Namely, we find that the operators in $\mathcal{G}$ cannot generate arbitrary local symplectic unitaries and that they are not translationally invariant. We then review the Schur–Weyl duality between the symplectic group and the Brauer algebra, and use tools from Weingarten calculus to prove that Pauli measurements at the output of Haar random symplectic circuits can converge to Gaussian processes. As a by-product, such analysis provides us with concentration bounds for Pauli measurements in circuits that form t-designs over $\mathbb{SP}(d/2)$. To finish, we present tensor-network tools to analyze shallow random symplectic circuits, and we use these to numerically show that computational-basis measurements anti-concentrate at logarithmic depth.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Implement and Test 3D Mortar Contact in BISON

We leverage the extension of the generation of mortar segment meshes to three dimensions in MOOSE’s framework to extend thermomechanical modeling capabilities to problems with three dimensions. A modular approach to gap heat transfer physics using the mortar finite element method was created and documented, mechanical contact was extended to three dimensions—including frictional behavior, performance and ease of use were improved, and steps towards scalability of solid mechanics problems involving contact were taken. Many of these new developments are demonstrated in the simulation of 3D light-water reactor (LWR) problems, where the thermomechanical interface problem is solved using the mortar finite element method. Usage of the mortar framework has improved convergence in 2D problems and has enabled employing friction in 3D problems, of which we show results of a short, local stack of 3D pellets. Consequently, the benefits of mortar in terms of solution convergence and quality are extended to three dimensions. Section 2 discusses fundamental developments that enabled the simulation of practical mortar problems in three dimensions and other general improvements, including the reduction of the derivative container size, the modification of dual basis computations when edge dropping (lack of secondary element projection) takes place, the improvement of conditioning when employing the VCP in-edge dropping conditions, and code usability and quality improvements. These latter code enhancements include the migration of tests using “old” mortar contact constraints to using dual mortar with a semi-smooth Newton solution strategy and the reuse of lower dimensional domains for straightforwardly setting up a mortar thermomechanical LWR problem, i.e. the MOOSE action is employed for mechanical contact and the thermal LWR action is employed to capture the gas conductance, contact, and radiation components of gap heat transfer physics. Independently of the mortar LWR thermal action, we developed a modular approach to gap heat transfer that resides in MOOSE and can be leveraged, e.g., in metallic fuel problems. This approach, whose code design based on MOOSE’s user objects to model specific physics was proposed by the maintenance activity, is detailed in Section 3. Based on the dual mortar finite element method, the frictional contact constraints were extended to three dimensions. A block sheared in two directions in and out of contact with a rigid plane is employed in Section 4 to show the way the approach handles changes in frictional states (e.g. stick to slip) within a competitive number of Newton iterations. Equations and numerical results on the use of the VCP with Cartesian Lagrange multipliers, whose combination enables their direct condensation, are described in Section 5.3. Two-dimensional and three-dimensional BISON LWR simulations are discussed in Section 6. Particularly, a stack of five eccentric pellets with a surface defect is simulated and the effect of pellet-cladding friction is assessed. Finally, conclusions are outlined in Section 7.

42 ENGINEERING↗
DOE OSTI2023

Hydrogen in disordered titania: connecting local chemistry, structure, and stoichiometry through accelerated exploration

Hydrogen incorporation in native surface oxides of metal alloys often controls the onset of metal hydriding, with implications for materials corrosion and hydrogen storage. A key representative example is titania, which forms as a passivating layer on a variety of titanium alloys for structural and functional applications. These oxides tend to be structurally diverse, featuring polymorphic phases, grain boundaries, and amorphous regions that generate a disparate set of unique local environments for hydrogen. Here, we introduce a workflow that can efficiently and accurately navigate this complexity. First, a machine learning force field, trained on ab initio molecular dynamics simulations, was used to generate amorphous configurations. Density functional theory calculations were then performed on these structures to identify local oxygen environments, which were compared against experimental observations. Second, to classify subtle differences across the disordered configuration space, we employ a graph-based sampling procedure. Finally, local hydrogen binding energies and hopping kinetics are computed using exhaustive density functional theory calculations on representative configurations. Here, we leverage this methodology to show that hydrogen binding energetics are described by local oxygen coordination, which in turn is affected by stoichiometry, and form the basis of hopping kinetics and diffusion. Together these results imply that hydrogen incorporation and transport in TiO x can be tailored through compositional engineering, with implications for improving the performance and durability of titanium-derived alloys in hydrogen environments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Impacts of a Prescribed Fire on Air Quality in Central New Mexico

A short-duration but high-impact air quality event occurred on 28 November 2018 along the Rio Grande Valley of New Mexico. This fire occurred outside the typical wildfire season, and greatly impacted the air quality in Socorro, NM, and the surroundings. Measurements were taken during the event using an aerosol light scattering technique (integrating nephelometer) and a particulate mass concentration monitor (DustTrak PM optical monitor). The instruments sampled the ambient air during the event on the campus of the New Mexico Institute of Mining and Technology in Socorro, New Mexico. The peak values on a 5-min basis of light scattering and the PM mass concentration reached 470 Mm -1 and 270 µg/m 3 , respectively. We examined the meteorological context of the event using local meteorological data and back trajectories using the NOAA HYSPLIT model to determine atmospheric transport and possible sources. Several fires, both prescribed and wildfires, occurred in the region including a prescribed burn at Bosque del Apache National Wildlife Refuge (17 km south-southeast of the receptor site). The data suggest that the prescribed burn at Bosque del Apache was the dominant contributor due to transport evidence and the event’s narrow spatiotemporal extent. The increasing importance of restoring ecosystem function using prescribed fire in wildland fire management will likely lead to more frequent air quality impacts and sets up policy tradeoffs that require a balance between these public goals. This study examines the evidence of the effects of a prescribed fire in a protected wildland area impacting the air quality in a nearby populated area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

3D Source Reconstruction Using Coded Aperture Gamma-Ray Imaging

Recent measurements with coded-aperture imagers demonstrate material mass determination in a holdup setting to an accuracy within a few percent. This capability is of particular interest to the Surplus Plutonium Disposition (SPD) project, which aims to dilute and dispose of surplus plutonium oxide. Gamma-ray imagers can be used to determine holdup without interrupting normal operations. In this work, we examine techniques for 3D source localization and mass determination using gamma-ray imagers. Coded-aperture imagers provide excellent source localization within the 2D image plane; however, multiple imagers operating in tandem are necessary to identify source location in 3D space. A Maximum Likelihood Expectation-Maximization (MLEM) method for fitting detector mappings is a powerful tool for accomplishing this task. MLEM allows 3D source localization to be simultaneously constrained using multiple gamma-ray imagers by constructing the basis for the MLEM fit using detector mappings from different detector locations stitched together. Each of these basis points represents a singular response from a source in 3D space and is generated using Monte Carlo simulations of sources placed individually at different locations throughout the imager’s field of view. Additionally, implementing knowledge of the physical equipment in the simulations of the glovebox used for the SPD project incorporates attenuation effects that are needed to calculate material holdup.

Laminack, Alex↗
DOE OSTI2023

A Pulse Generation Framework with Augmented Program-aware Basis Gates and Criticality Analysis

Near-term intermediate scale quantum (NISQ) de- vices are subject to considerable noise and short coherence time. Consequently, it is critical to minimize circuit execution latency. Traditionally, each basis gate of a transpiled circuit is decoded into a fixed episode of the device control pulses. Recently, people started to investigate merged pulse generation for customized gates through quantum optimal control (QOC). However, existing QOC approaches face the challenges of (i) restricted search space due to prohibitive compilation overhead; (ii) suboptimal end-to-end performance due to aggressive local optimization and falsely introduced dependency among the customized gates; (iii) inadequate adaptivity towards system calibration, which is critical for NISQ devices. In this work, we propose PAQOC, a novel QOC framework that can (i) automatically detect frequently encountered gate patterns in the logical circuit by modeling the problem as a subgraph mining process and reuse these patterns to enable much larger search space exploration (i.e., program aware); (ii) systemically construct customized gate-set based on the impact to the overall program latency (i.e., criticality-aware); and (iii) quickly adapt to system re-calibration thanks to the small-scale pattern-based gate generation (i.e., adaptivity-aware). PAQOC achieves a good tradeoff between circuit performance and compilation time, allowing fully automatic, single stop, ad- hoc customized pulse generation for more efficient execution of user programs on NISQ devices. Evaluations using fifteen applications show that PAQOC can achieve on average 1.95× speedup of the circuit latency and achieve on average 36.7% reduction in compilation overhead. With PAQOC, circuits can run faster with reduced noise, allowing deeper circuits to be tested within the coherence time of present NISQ platforms.

Chen, Yanhao↗
DOE OSTI2023

Quantitative Characterization of Hyper-Local Atmospheric Greenhouse Gas Sources

Atmospheric greenhouse gas (GHG) emissions are often characterized using stationary, tower-based sensors. Ground based sensors reside in the turbulent boundary layer and are subject to intense concentration impulses from hyper-local (<100m) point sources of emissions. These high frequency spikes are often filtered out in broader emission flux studies, losing valuable information about how hyper-local sources influence receptors. In this study, we investigated how empirical atmospheric data can be used to locate and quantify a concurrently measured hyper-local point source in a dense urban setting. An eddy covariance style tower and a low-cost sensor tower were deployed in various locations around an urban, hyper-local CO2/CH4 emissions source (a continuously measured restaurant exhaust vent). A model using different processing and statistical techniques was built to examine the most effective procedures for source isolation, directional location, and emission quantification. Using excess concentrations above a minimum baseline, we identify the source using bivariate polar plots and quantify the relationship between source size, receptor distance, and statistical proxies. Furthermore, we find that varying statistical thresholds allows for identification of less influential sources which are drowned out by larger or closer sources. Finally, we show that large sources can be effectively characterized using low-cost sensors, a valuable outcome informing how networks for monitoring larger areas could be implemented. This work may provide a basis for source identification and monitoring protocols for networks that feature sensors influenced by hyper-local point sources, subject to site-specific assumptions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

An evaluation of global organic aerosol schemes using airborne observations

Chemical transport models have historically struggled to accurately simulate the magnitude and variability of observed organic aerosol (OA), with previous studies demonstrating that models significantly underestimate observed concentrations in the troposphere. In this study, we explore two different model OA schemes within the standard GEOS-Chem chemical transport model and evaluate the simulations against a suite of 15 globally distributed airborne campaigns from 2008 to 2017, primarily in the spring and summer seasons. These include the ATom, KORUS-AQ, GoAmazon,FRAPPE, SEAC4RS, SENEX, DC3, CalNex, OP3, EUCAARI, ARCTAS and ARCPAC campaigns and provide broad coverage over a diverse set of atmospheric composition regimes – anthropogenic, biogenic, pyrogenic and remote. The schemes include significant differences in their treatment of the primary and secondary components of OA – a “simple scheme” that models primary OA (POA) as non-volatile and takes a fixed-yield approach to secondary OA (SOA) formation and a “complex scheme” that simulates POA as semi-volatile and uses a more sophisticated volatility basis set approach for non-isoprene SOA, with an explicit aqueous uptake mechanism to model isoprene SOA. Despite these substantial differences, both the simple and complex schemes perform comparably across the aggregate dataset in their ability to capture the observed variability (with an R2 of 0.41 and 0.44, respectively). The simple scheme displays greater skill in minimizing the overall model bias (with a normalized mean bias of 0.04 compared to 0.30 for the complex scheme). Across both schemes, the model skill in reproducing observed OA is superior to previous model evaluations and approaches the fidelity of the sulfate simulation within the GEOS-Chem model. However,there are significant differences in model performance across different chemical source regimes, classified here into seven categories.Higher-resolution nested regional simulations indicate that model resolution is an important factor in capturing variability in highly localized campaigns, while also demonstrating the importance of well-constrained emissions inventories and local meteorology, particularly over Asia. Our analysis suggests that a semi-volatile treatment of POA is superior to anon-volatile treatment. It is also likely that the complex scheme parameterization overestimates biogenic SOA at the global scale. While this study identifies factors within the SOA schemes that likely contribute to OA model bias (such as a strong dependency of the bias in the complex scheme on relative humidity and sulfate concentrations), comparisons with the skill of the sulfate aerosol scheme in GEOS-Chem indicate the importance of other drivers of bias, such as emissions, transport and deposition, that are exogenous to the OA chemical scheme.

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

Test of model of equivalence of tree height growth and transpiration rates in percolation-based phenomenology for root-soil interaction

We recently introduced a phenomenological model to represent root-soil interactions that accounts for variability in tree growth on local scales and within species (Hunt et al., 2020). Here, using publicly available datasets, we examine the developed model to provide additional empirical evidence, which also gives novel insight into two particular tree species, Eucalyptus regnans and Eucalyptus sieberri. In particular, we discovered two novel aspects of the model: a power-law time dependence with a different power-law exponent than usually heretofore applied, and apparently a direct equivalence of results for transpiration and growth rates. Also, although our original expectation was that growth and transpiration were merely proportional, comparison of the entire BAAD data set (Falster et al., 2015) for tree height with our model (Hunt et al., 2020; Fig. 1) already suggested approximate equality of these disparate measurements (volume/area, height). In this present manuscript we find further evidence for equivalence of the two measurements and provide additional theoretical basis for a model assumption regarding constancy of sap flow rates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Time-series forecasting using manifold learning, radial basis function interpolation, and geometric harmonics

We address a three-tier numerical framework based on nonlinear manifold learning for the forecasting of high-dimensional time series, relaxing the “curse of dimensionality” related to the training phase of surrogate/machine learning models. At the first step, we embed the high-dimensional time series into a reduced low-dimensional space using nonlinear manifold learning (local linear embedding and parsimonious diffusion maps). Then, we construct reduced-order surrogate models on the manifold (here, for our illustrations, we used multivariate autoregressive and Gaussian process regression models) to forecast the embedded dynamics. Finally, we solve the pre-image problem, thus lifting the embedded time series back to the original high-dimensional space using radial basis function interpolation and geometric harmonics. The proposed numerical data-driven scheme can also be applied as a reduced-order model procedure for the numerical solution/propagation of the (transient) dynamics of partial differential equations (PDEs). In conclusion, we assess the performance of the proposed scheme via three different families of problems: (a) the forecasting of synthetic time series generated by three simplistic linear and weakly nonlinear stochastic models resembling electroencephalography signals, (b) the prediction/propagation of the solution profiles of a linear parabolic PDE and the Brusselator model (a set of two nonlinear parabolic PDEs), and (c) the forecasting of a real-world data set containing daily time series of ten key foreign exchange rates spanning the time period 3 September 2001–29 October 2020.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗