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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 289 records · Page 16

Interpreting the electron EDM constraint

The ACME collaboration has recently announced a new constraint on the electron EDM, |d e | < 1.1 × 10 -29 e cm, from measurements of the ThO molecule. This is a powerful constraint on CP-violating new physics: even new physics generating the EDM at two loops is constrained at the multi-TeV scale. We interpret the bound in the context of different scenarios for new physics: a general order-of-magnitude analysis for both the electron EDM and the CP-odd electron-nucleon coupling; 1-loop SUSY, probing sleptons above 10 TeV; 2-loop SUSY, probing multi-TeV charginos or stops; and finally, new physics that generates the EDM via the charm quark or top quark Yukawa couplings. In the last scenario, new physics generates a “QULE operator” ($q_{ƒ}\overline{σ}^{μν}\overline{u}_{ƒ}$)&middot;($ℓ\overline{σ}_{μν}\overline{e}$), which in turn generates the EDM through RG evolution. If the QULE operator is generated at tree level, this corresponds to a previously studied leptoquark model. For the first time, we also classify scenarios in which the QULE operator is generated at one loop through a box diagram, which include (among others) SUSY and leptoquark models. The electron EDM bound is the leading constraint on a wide variety of theories of CP-violating new physics interacting with the Higgs boson or the top quark. We argue that any future nonzero measurement of an electron EDM will provide a strong motivation for constructing new colliders at the highest feasible energies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Boundary to Constructive Solid Geometry Mappings: a Focus on 2-D Issues

The problem of converting boundary representation (B-rep) to constructive solid geometry representation (CSG-rep) (and vice versa) is discussed in two phases. The first phase entails finding a CSG-rep that defines the region bounded by a polygonal profile curve. The second phase utilizes the results of the first phase to find a CSG-rep for many non-polygonal profile curves. A mathematically concise representation of a region bounded by a polygonal is presented. Namely, any polygonal region bounded by an n sided polygon may be represented by a binary tree which has at most n planar halfspaces as leaves. A structure for this representation and an algorithm for calculating is discussed.

Peterson, D. P.↗

Woody Plant Decline in the Sahel of Western Niger (1996-2017): Is it Driven by Climate or Land Use Changes?

Although a recovery of woody vegetation has been observed throughout the Sahel, western Niger has not followed the overall satellite-derived greening trend. While satellite imagery can be used to study overall patterns and trends, only field observations can provide insights in the dynamics of woody plant populations. Here we used field data from 29 sites in the Dantiandou district in Niger to study woody species composition, plant density, crown cover, basal area, foliage and wood mass from 1996 to 2017. All sites show a decrease in woody plant parameters with a faster decrease in rangeland than in agricultural land. Most of the decrease is due to the loss of shrubs, while trees do not change significantly. When field observations were scaled up to the district level using land use maps, shrub density decreased from 342 to 155 ha-1in agricultural land, and from 1567 to 250 ha-1in rangeland. Trends in annual rainfall and soil moisture during the study period were not significant and cannot explain the decrease of woody vegetation. Instead, the expansion of cropped areas, shortened crop-fallow cycles and the increasing pressure on wood resources to satisfy demand for fuel and construction materials may have contributed to the decline.

Pierre Hiernaux↗

Odyssey personal communications satellite system

The spectacular growth of cellular telephone networks has proved the demand for personal communications. Large regions of the world are too sparsely populated to be economically served by terrestrial cellular communications. Since satellites are well suited to this application, TRW filed with the FCC on May 31, 1993 for the Odyssey construction permit. Odyssey will provide high quality wireless communication services worldwide from satellites. These services will include: voice, data, paging, and messaging. Odyssey will be an economical approach to providing communications. A constellation of 12 satellites will be orbited in three, 55 deg. inclined planes at an altitude of 10,354 km to provide continuous coverage of designated regions. Two satellites will be visible anywhere in the world at all times. This dual visibility leads to high line-of-sight elevation angles, minimizing obstructions by terrain, trees and buildings. Each satellite generates a multibeam antenna pattern that divides its coverage area into a set of contiguous cells. The communications system employs spread spectrum CDMA on both the uplinks and downlinks. This signaling method permits band sharing with other systems and applications. Signal processing is accomplished on the ground at the satellite's 'Gateway' stations. The 'bent pipe' transponders accommodates different regional standards, as well as signaling changes over time. The low power Odyssey handset will be cellular compatible. Multipath fade protection is provided in the handset.

Spitzer, Christopher J.↗

The matrix product approximation for the dynamic cavity method

Stochastic dynamics of classical degrees of freedom, defined on vertices of locally tree-like graphs, can be studied in the framework of the dynamic cavity method which is exact for tree graphs. Such models correspond for example to spin-glass systems, Boolean networks, neural networks, and other technical, biological, and social networks. The central objects in the cavity method are edge messages—conditional probabilities of two vertex variable trajectories. In this paper, we discuss a rather pedagogical derivation for the dynamic cavity method, give a detailed account of the novel matrix product edge message (MPEM) algorithm for the solution of the dynamic cavity equation as introduced, and present optimizations and extensions. Matrix product approximations of the edge messages are constructed recursively in an iteration over time. Computation costs and precision can be tuned by controlling the matrix dimensions of the MPEM in truncations. Without truncations, the dynamics is exact. Data for Glauber–Ising dynamics shows a linear growth of computation costs in time. In contrast to Monte Carlo simulations, the approach has a much better error scaling. Hence, it gives for example access to low probability events and decaying observables like temporal correlations. Here, we discuss optimized truncation schemes and an extension that allows to capture models which have a continuum time limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Reduced-Order Modeling of Multigroup Neutron Cross Sections for High-Temperature Gas-cooled Reactors

Abstract – Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

42 - ENGINEERING↗

Advanced Cross Section Library Generation using Reduced Order Models

Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

42 - ENGINEERING↗

Reduce-Order Modeling of Multigroup Neutron Cross Sections for High-Temperature Gas-cooled Reactors

Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which usually consists of a database of tabulated values, used to calculate the cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of micro cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. To address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multi-group cross section data across isotopes, reaction types and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs for have been trained for all isotopes in this work and systematic Griffin testing is ongoing at this moment to ensure the feasibility of this ROM technique for cross section predictions.

42 - ENGINEERING↗

The plant cell wall—dynamic, strong, and adaptable—is a natural shapeshifter

Mythology is replete with good and evil shapeshifters, who, by definition, display great adaptability and assume many different forms—with several even turning themselves into trees. Cell walls certainly fit this definition as they can undergo subtle or dramatic changes in structure, assume many shapes, and perform many functions. In this review, we cover the evolution of knowledge of the structures, biosynthesis, and functions of the 5 major cell wall polymer types that range from deceptively simple to fiendishly complex. Along the way, we recognize some of the colorful historical figures who shaped cell wall research over the past 100 years. The shapeshifter analogy emerges more clearly as we examine the evolving proposals for how cell walls are constructed to allow growth while remaining strong, the complex signaling involved in maintaining cell wall integrity and defense against disease, and the ways cell walls adapt as they progress from birth, through growth to maturation, and in the end, often function long after cell death. We predict the next century of progress will include deciphering cell type–specific wall polymers; regulation at all levels of polymer production, crosslinks, and architecture; and how walls respond to developmental and environmental signals to drive plant success in diverse environments.

59 BASIC BIOLOGICAL SCIENCES↗

Global bases for nonplanar loop integrands, generalized unitarity, and the double copy to all loop orders

We introduce a constructive method for defining a global loop-integrand basis for scattering amplitudes, encompassing both planar and nonplanar contributions. Our approach utilizes a graph-based framework to establish a well-defined, non-redundant basis of integrands. This basis, constructed from a chosen set of non-redundant graphs together with a selection of irreducible scalar products, provides clear insights into various physical properties of scattering amplitudes and proves useful in multiple contexts, such as on-shell Ward identities and manifesting gauge-choice independence. A key advantage of our integrand basis is its ability to streamline the generalized unitarity method. Specifically, we can directly read off the coefficients of basis elements without resorting to ansätze or solving linear equations. This novel approach allows us to lift generalized unitarity cuts — expressed as products of tree amplitudes — to loop-level integrands, facilitating the use of the tree-level double copy to generate complete gravitational integrands at any loop order. This method circumvents the difficulties in identifying complete higher-loop-order gauge-theory integrands that adhere to the color-kinematics duality. Additionally, our cut-based organization is well-suited for expansion in hard or soft limits, aiding in the exploration of ultraviolet or classical limits of scattering amplitudes.

Effective Field Theories↗

Southern Indiana Ecological Conservation: Assessing Canopy Cover Dynamics and Forest Type Groupings in Southern Indiana to Inform Restoration Activities

As human influence continues to negatively impact natural habitats, timely assessment of ecosystem changes and restoration is critical to protect forest health and biodiversity. In our study, we focused on oak-hickory forests in southern Indiana. Oak-hickory forests were the dominant ecosystem dynamic in present-day Indiana for centuries until European colonization, which brought about fire suppression and, eventually, fire exclusion. Anthropogenic fire exclusion in this fire-adapted habitat led to the encroachment of mesic species, such as beech and maple trees. This process, commonly referred to as mesophication, was the focus of our study. Our team performed a feasibility study in using NASA Earth observations to support our end-user partners, Let the Sun Shine In and the US Forest Service, Hoosier National Forest, in their selection of oak-hickory restoration sites. To aid in our analysis of the forest dynamics of southern Indiana, our team used Landsat 5, 8, and 9 imageries, along with other ancillary datasets to create maps to illustrate areas that would most benefit from partners’ forest restoration and management practices. By constructing a Green Vegetation Fraction change map across our 39-year study period (1984-2023) to visualize the change in forest cover and creating a restoration suitability assessment map to reveal sites that met requirements for oak-hickory growth, we provided our partners with suitable site selection for restorative management and found that 3.3% of our entire study area and 4.4% of the Hoosier National Forest were deemed suitable. Our feasibility study benefits southern Indiana restoration by aiding our partners in efficiently selecting sites for prescribed burning, forest thinning, and other restoration management practices.

restoration↗

Growing Insulation in Alaska

Buildings produce 40% of all carbon emissions in the U.S. This includes the energy needed to heat, cool, and power the nation's buildings and the energy used to manufacture, ship, and assemble the construction materials. In extreme climates and remote regions, buildings use even more energy, as building materials must be produced and shipped farther to the site, increasing the greenhouse gas emissions embodied in the buildings. The U.S. National Renewable Energy Laboratory (NREL) is developing technologies that reduce how much energy our buildings use and how much carbon goes into them in the first place. NREL researchers teamed up with the Biomaterials Laboratory at the University of Alaska, U.S. Forest Service Forest Products Lab, and the VTT Centre of Finland on a three-year project to "grow" insulation using trees in Alaska - improving the efficiency of buildings by providing envelope retrofit options using local resources.

carbon negative building↗

Substructure in the stellar halo near the Sun: I. Data-driven clustering in integrals-of-motion space

Context. Merger debris is expected to populate the stellar haloes of galaxies. In the case of the Milky Way, this debris should be apparent as clumps in a space defined by the orbital integrals of motion of the stars. Aims. Our aim is to develop a data-driven and statistics-based method for finding these clumps in integrals-of-motion space for nearby halo stars and to evaluate their significance robustly. Methods. We used data from Gaia EDR3, extended with radial velocities from ground-based spectroscopic surveys, to construct a sample of halo stars within 2.5 kpc from the Sun. We applied a hierarchical clustering method that makes exhaustive use of the single linkage algorithm in three-dimensional space defined by the commonly used integrals of motion energy E, together with two components of the angular momentum, L z and L ⊥ . To evaluate the statistical significance of the clusters, we compared the density within an ellipsoidal region centred on the cluster to that of random sets with similar global dynamical properties. By selecting the signal at the location of their maximum statistical significance in the hierarchical tree, we extracted a set of significant unique clusters. By describing these clusters with ellipsoids, we estimated the proximity of a star to the cluster centre using the Mahalanobis distance. Additionally, we applied the HDBSCAN clustering algorithm in velocity space to each cluster to extract subgroups representing debris with different orbital phases. Results. Our procedure identifies 67 highly significant clusters (> 3σ), containing 12% of the sources in our halo set, and 232 subgroups or individual streams in velocity space. In total, 13.8% of the stars in our data set can be confidently associated with a significant cluster based on their Mahalanobis distance. Inspection of the hierarchical tree describing our data set reveals a complex web of relations between the significant clusters, suggesting that they can be tentatively grouped into at least six main large structures, many of which can be associated with previously identified halo substructures, and a number of independent substructures. This preliminary conclusion is further explored in a companion paper, in which we also characterise the substructures in terms of their stellar populations. Conclusions. Our method allows us to systematically detect kinematic substructures in the Galactic stellar halo with a data-driven and interpretable algorithm. The list of the clusters and the associated star catalogue are provided in two tables available at the CDS.

79 ASTRONOMY AND ASTROPHYSICS↗

RSRM Nozzle Anomalous Throat Erosion Investigation Overview

In September, 1996, anomalous pocketing erosion was observed in the aft end of the throat ring of the nozzle of one of the reusable solid rocket motors (RSRM 56B) used on NASA's space transportation system (STS) mission 79. The RSRM throat ring is constructed of bias tape-wrapped carbon cloth/ phenolic (CCP) ablative material. A comprehensive investigation revealed necessary and sufficient conditions for occurrence of the pocketing event and provided rationale that the solid rocket motors for the subsequent mission, STS-80, were safe to fly. The nozzles of both of these motors also exhibited anomalous erosion similar to, but less extensive than that observed on STS-79. Subsequent to this flight, the investigation to identify both the specific causes and the corrective actions for elimination of the necessary and sufficient conditions for the pocketing erosion was intensified. A detailed fault tree approach was utilized to examine potential material and process contributors to the anomalous performance. The investigation involved extensive constituent and component material property testing, pedigree assessments, supplier audits, process audits, full scale processing test article fabrication and evaluation, thermal and thermostructural analyses, nondestructive evaluation, and material performance tests conducted using hot fire simulation in laboratory test beds and subscale and full scale solid rocket motor static test firings. This presentation will provide an over-view of the observed anomalous nozzle erosion and the comprehensive, fault-tree based investigation conducted to resolve this issue.

Clinton, R. G., Jr.↗

Effects of random forest modeling decisions on biogeochemical time series predictions

Abstract Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important parameterization decisions for appropriate use and optimal model fit. We explored the role that parameter decisions, including training/testing data splitting strategies, variable selection, and hyperparameters play on RF goodness‐of‐fit by constructing models using 1296 unique parameter combinations to predict concentrations of nitrate, a key nutrient for biogeochemical cycling in aquatic ecosystems. Models were built on long‐term, publicly available water quality and meteorology time series collected by the National Estuarine Research Reserve monitoring network for two contrasting ecosystems representing freshwater and brackish estuaries. We found that accounting for temporal dependence when splitting data into training and testing subsets was key for avoiding over‐estimation of model predictive power. In addition, variable selection, the ratio of training to testing data, and to a lesser degree, variables per split and number of trees, were significant parameters for optimizing RF goodness‐of‐fit. We also explored how model parameter decisions influenced interpretation of the relative importance of predictors to the model, and model predictor‐dependent variable relationships, with results suggesting that both data structure and model parameterization influence these factors. Because much of the current RF literature is written for the computational and statistical science communities, the primary goal of this study is to provide guidelines for aquatic scientists new to machine learning to apply RF techniques appropriately to aquatic biogeochemical datasets.

54 ENVIRONMENTAL SCIENCES↗

Role of Cell Wall Polysaccharides in Water Distribution During Seed Imbibition of Hymenaea courbaril L.

Seed water imbibition is critical to seedling establishment in tropical forests. The seeds of the neotropical tree Hymenaea courbaril have no oil reserves and have been used as a model to study storage cell wall polysaccharide (xyloglucan - XyG) mobilization.We studied pathways of water imbibition in Hymenaea seeds. To understand seed features, we performed carbohydrate analysis and scanning electron microscopy. We found that the seed coat comprises a palisade of lignified cells, below which are several cell layers with cell walls rich in pectin. The cotyledons are composed mainly of storage XyG. From a single point of scarification on the seed surface, we followed water imbibition pathways in the entire seed using fluorescent dye and NMRi spectroscopy. We constructed composites of cellulose with Hymenaea pectin or XyG. In vitro experiments demonstrated cell wall polymer capacity to imbibe water, with XyG imbibition much slower than the pectin-rich layer of the seed coat.We found that water rapidly crosses the lignified layer and reaches the pectin-rich palisade layer so that water rapidly surrounds the whole seed. Water travels very slowly in cotyledons (most of the seed mass) because it is imbibed in the XyG-rich storage walls. However, there are channels among the cotyledon cells through which water travels rapidly, so the primary cell walls containing pectins will retain water around each storage cell.The different seed tissue dynamic interactions between water and wall polysaccharides (pectins and XyG) are essential to determining water distribution and preparing the seed for germination.

arabinoxylan↗

Three-Dimensional Modeling of the Solar Wind: From the Coronal Base to the Outer Heliosphere

We have developed a global fully three-dimensional magnetohydrodynamic solar wind model for the region that extends from the coronal base to 100 AU. The simulation domain consists of tree spherical shell subdomains with computational boundaries between them placed at 20 solar radii and 0.3 AU. The location of the first boundary ensures that the flow at the boundary is both supersonic and super-Alfvenic. A steady-state solution in the innermost (coronal) region is obtained by the time-relaxation method. The solution uses a tilted dipole model or solar magnetograms as the boundary condition at the coronal base and includes a flux of Alfven waves in the WKB approximation which provide additional acceleration for the coronal outflow in the open field regions. The intermediate region solution is constructed by the integration of steady-state equations along radius using a marching scheme. The outer region solution (0.3-100 AU) is obtained again by the time relaxation and takes into account turbulence transport and heating as well as heating, flow deceleration, and other effects due to the interstellar pickup protons treated as a separate fluid. We use the model to simulate the global steady-state structure of the solar wind from the coronal base to the heliospheric boundary and compare the results with Ulysses and Voyager observations.

Usmanov, A. V↗

Sequential Testing Algorithms for Multiple Fault Diagnosis

In this paper, we consider the problem of constructing optimal and near-optimal test sequencing algorithms for multiple fault diagnosis. The computational complexity of solving the optimal multiple-fault isolation problem is super-exponential, that is, it is much more difficult than the single-fault isolation problem, which, by itself, is NP-hard. By employing concepts from information theory and AND/OR graph search, we present several test sequencing algorithms for the multiple fault isolation problem. These algorithms provide a trade-off between the degree of suboptimality and computational complexity. Furthermore, we present novel diagnostic strategies that generate a diagnostic directed graph (digraph), instead of a diagnostic tree, for multiple fault diagnosis. Using this approach, the storage complexity of the overall diagnostic strategy reduces substantially. The algorithms developed herein have been successfully applied to several real-world systems. Computational results indicate that the size of a multiple fault strategy is strictly related to the structure of the system.

Shakeri, Mojdeh↗