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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Influence of plateau, slope, and valley on soil hydrology during the dry season in a Central Amazon old‐growth forest

Soil moisture regulates plant water supply and drought sensitivity in tropical forests, yet its vertical and topographic variation remains poorly characterized. We combined high-frequency time-domain reflectometry measurements from 5 to 100 cm across plateau, slope, and valley landforms at the Zona Florestal 2 research site north of Manaus, Central Amazonia, to quantify how soil moisture memory, timing of responses to rainfall, dry-down rates (τ), and soil–water depletion vary across these contrasting landforms. Landform-specific soil moisture calibration curves ensured accurate volumetric water content estimates in these highly weathered soils. During the 2023 dry-to-wet transition (August–November), soil moisture memory showed strong topographic contrasts, with valley profiles increasing from ∼47 h at 5 cm to ∼154 h at 100 cm, while plateaus exhibited higher near-surface persistence (∼124 h at 5 cm) but weaker memory at depth. Dry-down behavior reinforced these differences as valley soils exhibited τ values exceeding ∼200 h, more than double the characteristic τ of plateau soils (∼90 h). Rainfall–soil moisture correlations indicated immediate responses at shallow depths in valleys and progressively longer lags with depth on plateaus and slopes. These hydrologic patterns were mirrored in depletion profiles, which declined sharply below 30 cm on plateaus but remained high and sustained throughout the upper meter in slopes and valleys. Together, these findings provide the first depth-resolved field measurements of soil moisture memory, rainfall coupling, dry-down constants, and depletion dynamics across major upland landforms in Central Amazonia and offer clear observational benchmarks for improving land-surface and ecosystem model representations of soil–water processes.

Hillslope↗
DOE OSTI2020

Knocking Out the Wall: Revised Protocols for Gene Targeting in Physcomitrella patens

The moss Physcomitrella patens has become established as a model for investigating plant gene function due to the feasibility of gene targeting. The chemical composition of the P. patens cell wall is similar to that of vascular plants and phylogenetic analyses of glycosyltransferase sequences from the P. patens genome have identified genes that putatively encode cell wall biosynthetic enzymes, providing a basis for investigating the evolution of cell wall polysaccharides and the enzymes that synthesize them. Here, the protocols described in this chapter provide methods for targeted gene knockout in P. patens, from constructing vectors and maintaining cultures to transforming protoplasts and analysing the genotypes and phenotypes of the resulting transformed lines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Search for charged-lepton flavor violation in Υ(2S) → ℓ∓τ± (ℓ = e, μ) decays at Belle

Abstract We report a search for the charged-lepton flavor violation in Υ(2S) →ℓ ∓ τ ± (ℓ=e, μ) decays using a 25 fb −1 Υ(2S) sample collected by the Belle detector at the KEKBe + e − asymmetric-energy collider. We find no evidence for a signal and set upper limits on the branching fractions ($$ \mathcal{B} $$ B ) at 90% confidence level. We obtain the most stringent upper limits:$$ \mathcal{B} $$ B (Υ(2S)→ μ ∓ τ ± )<0.23×10 −6 and$$ \mathcal{B} $$ B (Υ(2S)→ e ∓ τ ± )<1.12×10 −6 .

Physics↗
DOE OSTI2022

High-dimensional anomaly detection with radiative return in $\mathcal{e}$⁺$\mathcal{e}$⁻ collisions

Experiments at a future $\mathcal{e}$⁺$\mathcal{e}$⁻ collider will be able to search for new particles with masses below the nominal centre-of-mass energy by analyzing collisions with initial-state radiation (radiative return). We show that machine learning methods that use imperfect or missing training labels can achieve sensitivity to generic new particle production in radiative return events. In addition to presenting an application of the classification without labels (CWoLa) search method in $\mathcal{e}$⁺$\mathcal{e}$⁻ collisions, our study combines weak supervision with variable-dimensional information by deploying a deep sets neural network architecture. We have also investigated some of the experimental aspects of anomaly detection in radiative return events and discuss these in the context of future detector design.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

The constructive method for massive particles in QED

The constructive method of determining amplitudes from on-shell pole structure has been shown to be promising for calculating amplitudes in a more efficient way. However, challenges have been encountered when a massless internal photon is involved in the gluing of three-point amplitudes with massive external particles. In this paper, we use the original on-shell method, old-fashioned perturbation theory, to shed light on the constructive method, and show that one can derive the Feynman amplitude by correctly identifying the residue even when there is an internal photon involved.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurement of the e + e - → $ {B}_s^0{\overline{B}}_s^0X $ cross section in the energy range from 10.63 to 11.02 GeV using inclusive $ {D}_s^{+} $ and D 0 production

We report the first measurement of the inclusive e + e - → $b\bar{b}$ → D$^±_s$ X and e + e - → $b\bar{b}$ → D 0 / $\overline{D}^0$ X cross sections in the energy range from 10.63 to 11.02 GeV. Based on these results, we determine σ(e + e - → ${B}_s^0{\overline{B}}_s^0$ X) and σ(e + e - → $B\overline{B}$ X) in the same energy range. We measure the fraction of ${B}_s^0$ events at Υ(10860) to be f s = (${22.0}_{-2.1}^{+2.0}$)%. We determine also the ratio of the ${B}_s^0$ inclusive branching fractions $\mathcal{B}$(${B}_s^0$ → D 0 / $\overline{D}^0$X)/$\mathcal{B}$(${B}_s^0$ → ${D}_s^{\pm }$X) = 0.416 ± 0.018 ± 0.092. The results are obtained using the data collected with the Belle detector at the KEKB asymmetric-energy e + e - collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Search for lepton-flavor-violating tau-lepton decays to ℓγ at Belle

Charged lepton flavor violation is forbidden in the Standard Model but possible in several new physics scenarios. In many of these models, the radiative decays τ ± → ℓ ± γ (ℓ = e, μ) are predicted to have a sizeable probability, making them particularly interesting channels to search at various experiments. An updated search via τ ± → ℓ ± γ using full data of the Belle experiment, corresponding to an integrated luminosity of 988 fb –1 , is reported for charged lepton flavor violation. No significant excess over background predictions from the Standard Model is observed, and the upper limits on the branching fractions, B(τ ± → μ ± γ) ≤ 4.2 × 10 –8 and B(τ ± → e ± γ) ≤ 5.6 × 10 –8 , are set at 90% confidence level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

The information content of jet quenching and machine learning assisted observable design

Jets produced in high-energy heavy-ion collisions are modified compared to those in proton-proton collisions due to their interaction with the deconfined, strongly-coupled quark-gluon plasma (QGP). In this work, we employ machine learning techniques to identify important features that distinguish jets produced in heavy-ion collisions from jets produced in proton-proton collisions. We formulate the problem using binary classification and focus on leveraging machine learning in ways that inform theoretical calculations of jet modification: (i) we quantify the information content in terms of Infrared Collinear (IRC)-safety and in terms of hard vs. soft emissions, (ii) we identify optimally discriminating observables that are in principle calculable in perturbative QCD, and (iii) we assess the information loss due to the heavy-ion underlying event and background subtraction algorithms. We illustrate our methodology using Monte Carlo event generators, where we find that important information about jet quenching is contained not only in hard splittings but also in soft emissions and IRC-unsafe physics inside the jet. This information appears to be significantly reduced by the presence of the underlying event. We discuss the implications of this for the prospect of using jet quenching to extract properties of the QGP. Since the training labels are exactly known, this methodology can be used directly on experimental data without reliance on modeling. We outline a proposal for how such an experimental analysis can be carried out, and how it can guide future measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable‑density and shear flows

Abstract This work presents a novel numerical procedure for reconstructing volumetric density and velocity fields from planar laser-induced fluorescence (PLIF) and stereoscopic particle image velocimetry (SPIV) data. This new method is theoretically and practically demonstrated to provide more accurate 3D vortical structures and density fields in high shear flows than reconstruction methods based on the mean convective velocity. While Taylor’s hypothesis of frozen turbulence is commonly applied by using the local mean streamwise velocity, the proposed algorithm uses the measured local instantaneous velocity for data convection. It consists of a step-by-step reconstruction based on a mixed Lagrangian–Eulerian solver that includes the 3D interpolation of scattered flow data and that relaxes the Taylor’s hypothesis by iterative enforcement of the incompressibility constraint on the velocity field. This methodology provides 3D fields with temporal resolution, spatial resolution, and accuracy comparable to that of real 3D snapshots, thus providing a practical alternative to tomographic measurements. The procedure is validated using numerical data of the constant-density channel flow available on the Johns Hopkins University Turbulence Database (JHTDB), showing the accurate reconstruction of the 3D velocity field. The algorithm is applied to an experimental dataset of PLIF and SPIV measurements of a variable-density jet flow, demonstrating its capability to provide 3D velocity and density fields that are more consistent with the Navier–Stokes equations compared to the mean flow convective method. Graphic abstract

42 ENGINEERING↗
DOE OSTI2024

The first ensemble of kilometer-scale simulations of a hydrological year over the third pole

An accurate understanding of the current and future water cycle over the Third Pole is of great societal importance, given the role this region plays as a water tower for densely populated areas downstream. An emerging and promising approach for skillful climate assessments over regions of complex terrain is kilometer-scale climate modeling. As a foundational step towards such simulations over the Third Pole, we present a multi-model and multi-physics ensemble of kilometer-scale regional simulations for the hydrological year of October 2019 to September 2020. The ensemble consists of 13 simulations performed by an international consortium of 10 research groups, configured with a horizontal grid spacing ranging from 2.2 to 4 km covering all of the Third Pole region. These simulations are driven by ERA5 and are part of a Coordinated Regional Climate Downscaling EXperiment Flagship Pilot Study on Convection-Permitting Third Pole. The simulations are compared against available gridded and in-situ observations and remote-sensing data, to assess the performance and spread of the model ensemble compared to the driving reanalysis during the cold and warm seasons. Although ensemble evaluation is hindered by large differences between the gridded precipitation datasets used as a reference over this region, we show that the ensemble improves on many warm-season precipitation metrics compared with ERA5, including most wet-day and hour statistics, and also adds value in the representation of wet spells in both seasons. As such, the ensemble will provide an invaluable resource for future improvements in the process understanding of the hydroclimate of this remote but important region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Symmetry-breaking-induced rare fluctuations in a time-delay dynamic system

Inspired by the experimental and numerical findings, we study the dynamic instabilities of two coupled nonlinear delay differential equations that are used to describe the coherent oscillations between the top and bottom boundary layers in turbulent Rayleigh–Bénard convection. By introducing two sensitivity parameters for the instabilities of the top and bottom boundary layers, we find three different types of solutions, namely in-phase single-period oscillations, multi-period oscillations and chaos. The chaos solution contains rare but large amplitude fluctuations. The statistical properties of these fluctuations are consistent with those observed in the experiment for the massive eruption of thermal plumes, which causes random reversals of the large-scale circulation in turbulent Rayleigh–Bénard convection. Finally, our study thus provides new insights into the origin of rare massive eruptions and sudden changes of large-scale flow pattern that are often observed in convection systems of geophysical and astrophysical scales.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

CO 2 supplementation eliminates sugar-rich media requirement for plant propagation using a simple inexpensive temporary immersion photobioreactor

In vitro plant propagation systems such as temporary immersion bioreactors (TIBs) are valuable tools that enable production of disease-free plants with improved traits. However, TIB systems can be expensive, difficult to implement, and prone to contamination due to sugar rich propagation media. Using rapidly growing chicory root cultures to expedite design-build-test cycles, we report here an improved, low-cost version of a previously reported Hydrostatically-driven TIB (Hy-TIB) that facilitates economical use of gas mixtures. Bioreactor improvements include decreased material costs, expanded modes of operation, and a horizontal orientation of a plastic film plant growth chambers that increase propagule light exposure. To take advantage of these improvements, we describe here experiments that evaluate the impacts of elevated CO 2 on propagation of cacao (Theobroma cacao) secondary embryos and nodal cultures of yam (Dioscorea spp.) during both phototrophic and photomixotrophic growth. Our experiments show that elevated CO 2 during plant propagation significantly improved both cacao and yam propagule development and eliminated the need for supplemental sugars in tissue culture growth media. Thus, our improved Hy-TIB shows potential as a simple, low-cost, and scalable propagation platform with cost-effective gas composition control and reduced risk of contamination overgrowth. We provide detailed instructions for assembly of this Hy-TIB design and discuss the implications of its adoption in food-insecure regions of the world.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Deep nonparametric estimation of intrinsic data structures by chart autoencoders: Generalization error and robustness

Autoencoders have demonstrated remarkable success in learning low-dimensional latent features of high-dimensional data across various applications. Assuming that data are sampled near a low-dimensional manifold, we employ chart autoencoders, which encode data into low-dimensional latent features on a collection of charts, preserving the topology and geometry of the data manifold. Our paper establishes statistical guarantees on the generalization error of chart autoencoders, and we demonstrate their denoising capabilities by considering n noisy training samples, along with their noise-free counterparts, on a d-dimensional manifold. By training autoencoders, we show that chart autoencoders can effectively denoise the input data with normal noise. We prove that, under proper network architectures, chart autoencoders achieve a squared generalization error in the order of n–$\frac{2}{d+2}$log 4 n, which depends on the intrinsic dimension of the manifold and only weakly depends on the ambient dimension and noise level. We further extend our theory on data with noise containing both normal and tangential components, where chart autoencoders still exhibit a denoising effect for the normal component. As a special case, our theory also applies to classical autoencoders, as long as the data manifold has a global parametrization. Furthermore, our results provide a solid theoretical foundation for the effectiveness of autoencoders, which is further validated through several numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Generalization error guaranteed auto-encoder-based nonlinear model reduction for operator learning

Many physical processes in science and engineering are naturally represented by operators between infinite-dimensional function spaces. The problem of operator learning, in this context, seeks to extract these physical processes from empirical data, which is challenging due to the infinite or high dimensionality of data. An integral component in addressing this challenge is model reduction, which reduces both the data dimensionality and problem size. In this paper, we utilize low-dimensional nonlinear structures in model reduction by investigating Auto-Encoder-based Neural Network (AENet). AENet first learns the latent variables of the input data and then learns the transformation from these latent variables to corresponding output data. Our numerical experiments validate the ability of AENet to accurately learn the solution operator of nonlinear partial differential equations. Furthermore, we establish a mathematical and statistical estimation theory that analyzes the generalization error of AENet. Finally, our theoretical framework shows that the sample complexity of training AENet is intricately tied to the intrinsic dimension of the modeled process, while also demonstrating the robustness of AENet to noise.

Auto-encoder↗
DOE OSTI2022

Advances in hexagon mesh-based flow direction modeling

Watershed delineation and flow direction representation are the foundations of streamflow routing in spatially distributed hydrologic modeling. A recent study showed that hexagon-based watershed discretization has several advantages compared to the traditional Cartesian (latitude–longitude) discretization, such as uniform connectivity and compatibility with other Earth system model components based on unstructured mesh systems (e.g., oceanic models). Despite these advantages, hexagon-based discretization has not been widely adopted by the current generation of hydrologic models. One major reason is that there is no existing model that can delineate hexagon-based watersheds while maintaining accurate representations of flow direction across various spatial resolutions. In this study, we explored approaches such as spatial resampling and hybrid breaching-filling stream burning techniques to improve watershed delineation and flow direction representation using a newly developed hexagonal mesh watershed delineation model (HexWatershed). We applied these improvements to the Columbia River basin and performed 16 simulations with different configurations. The results show that (1) spatial resampling modulates flow direction around headwaters and provides an opportunity to extract subgrid information; and (2) stream burning corrects the flow directions in mountainous areas with complex terrain features.

58 GEOSCIENCES↗