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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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DOE OSTI2021

Instruction Roofline: An insightful visual performance model for GPUs

The Roofline performance model provides an intuitive approach to identify performance bottlenecks and guide performance optimization. However, the classic FLOP-centric approach is inappropriate for the emerging applications that perform more integer operations than floating point operations. In this article, we reintroduce our Instruction Roofline Model on NVIDIA GPUs and expand our evaluation of it. The Instruction Roofline incorporates instructions and memory transactions across all memory hierarchies together, and provides more performance insights than the FLOP-oriented Roofline Model, that is, instruction throughput, stride memory access patterns, bank conflicts, and thread predication. We use our Instruction Roofline methodology to analyze eight proxy applications: HPGMG from AMReX, Matrix Transpose benchmarks, ADEPT from MetaHipMer's sequence alignment phase, EXTENSION from MetaHipMer's local assembly phase, CUSP, cuSPARSE, cudaTensorCoreGemm, and cuBLAS. We demonstrate the ability of our methodology to understand various aspects of performance and performance bottlenecks on NVIDIA GPUs and motivate code optimizations.

Ding, N↗

DOE OSTI2024

Self‐Consistent Convolutional Density Functional Approximations: Application to Adsorption at Metal Surfaces

The exchange-correlation (XC) functional in density functional theory is used to approximate multi-electron interactions. A plethora of different functionals are available, but nearly all are based on the hierarchy of inputs commonly referred to as “Jacob's ladder.” This paper introduces an approach to construct XC functionals with inputs from convolutions of arbitrary kernels with the electron density, providing a route to move beyond Jacob's ladder. We derive the variational derivative of these functionals, showing consistency with the generalized gradient approximation (GGA), and provide equations for variational derivatives based on multipole features from convolutional kernels. A proof-of-concept functional, PBEq, which generalizes the PBEα framework with mathematical equation being a spatially-resolved function of the monopole of the electron density, is presented and implemented. It allows a single functional to use different GGAs at different spatial points in a system, while obeying PBE constraints. Analysis of the results underlines the importance of error cancellation and the XC potential in data-driven functional design. After testing on small molecules, bulk metals, and surface catalysts, the results indicate that this approach is a promising route to simultaneously optimize multiple properties of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis

The leaf economic spectrum is a widely-studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of PFTs. We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (SLA, N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (R_d, V_{c,max}, J_max) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, these covariance were an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.

biodiversity, ecological modeling, ecology, leaf b↗

DOE OSTI2020

Systems Theory Principles and Complex Systems Engineering Concepts for Protection and Resilience in Critical Infrastructure: Lessons from the Nuclear Sector

Part of the Presidential Policy Directive 21 (PPD-21) (PPD 2013) mandate includes evaluating safety, security, and safeguards (or nonproliferation) mechanisms traditionally implemented within the nuclear reactors, materials, and waste sector of critical infrastructure—including a complex, dynamic set of risks and threats within an all-hazards approach. In response, research out of Sandia National Laboratories (Sandia) explores the ability of systems theory principles (hierarchy and emergence) and complex systems engineering concepts (multidomain interdependence) to better understand and address these risks and threats. Herein, this Sandia research explores the safety, safeguards, and security risks of three different nuclear sector-related activities—spent nuclear fuel transportation, small modular reactors, and portable nuclear power reactors—to investigate the complex and dynamic risk related to the PPD-21-mandated all-hazards approach. This research showed that a systems-theoretic approach can better identify inter-dependencies, conflicts, gaps, and leverage points across traditional safety, security, and safeguards hazard mitigation strategies in the nuclear reactors, materials, and waste sector. Resulting from this, mitigation strategies from applying systems theoretic principles and complex systems engineering concepts can be (1) designed to better capture interdependencies, (2) implemented to better align with real-world operational uncertainties, and (3) evaluated as a systems-level whole to better identify, characterize, and manage PPD-21's all hazards strategies.

42 ENGINEERING↗

DOE OSTI2023

Enhancing Early Systems R&D Capabilities with Systems —Theoretic Process Analysis

Systems engineering today faces a wide array of challenges, ranging from new operational environments to disruptive technological — necessitating approaches to improve research and development (R&D) efforts. Yet, emphasizing the Aristotelian argument that the “whole is greater than the sum of its parts” seems to offer a conceptual foundation creating new R&D solutions. Invoking systems theoretic concepts of emergence and hierarchy and analytic characteristics of traceability, rigor, and comprehensiveness is potentially beneficial for guiding R&D strategy and development to bridge the gap between theoretical problem spaces and engineering-based solutions. In response, this article describes systems–theoretic process analysis (STPA) as an example of one such approach to aid in early-systems R&D discussions. STPA—a ‘top-down’ process that abstracts real complex system operations into hierarchical control structures, functional control loops, and control actions—uses control loop logic to analyze how control actions (designed for desired system behaviors) may become violated and drive the complex system toward states of higher risk. By analyzing how needed controls are not provided (or out of sequence or stopped too soon) and unneeded controls are provided (or engaged too long), STPA can help early-system R&D discussions by exploring how requirements and desired actions interact to either mitigate or potentially increase states of risk that can lead to unacceptable losses. This article will demonstrate STPA's benefit for early-system R&D strategy and development discussion by describing such diverse use cases as cyber security, nuclear fuel transportation, and US electric grid performance. Together, the traceability, rigor, and comprehensiveness of STPA serve as useful tools for improving R&D strategy and development discussions. In conclusion, leveraging STPA as well as related systems engineering techniques can be helpful in early R&D planning and strategy development to better triangulate deeper theoretical meaning or evaluate empirical results to better inform systems engineering solutions.

42 ENGINEERING↗

DOE OSTI2023

Gender gap in perspectives of the impacts of degradation and restoration on ecosystem services in Ethiopia

Abstract The importance of land restoration has garnered increasing attention on the global stage through large‐scale initiatives such as the Bonn Challenge. However, policies and strategies are often gender‐blind and designed in compliance with entrenched social hierarchies, exacerbating pre‐existing social inequalities that affect restoration initiatives. The challenge of developing gender‐responsive policies and initiatives is accentuated by a persistent lack of sex‐disaggregated data concerning men's and women's differing perceptions and experiences. This study aims to help fill this gap by capturing the differences in men and women's perceptions of ecosystem services before and after restoration interventions in Ethiopia. Towards that end, in October 2021, we collected data from fifty‐nine (59) paired husband‐wife households and six gender‐segregated focus group discussions in two regions of Ethiopia: Amhara and Southern Nations, and Nationalities and Peoples (SNNP). Kendall's concordance analysis established a strong degree of disagreement between men's and women's ratings of restoration outcomes for most indicators. Men attributed degradation to landscape conditions and natural forces, while women considered the lack of appropriate restoration strategies as a precursor for accelerated degradation. The study also reveals that men tended to benefit more than women from enhanced ecosystem services post‐restoration, with increased labour and land management burdens often falling on the shoulders of women. Based on these findings, we argue that including men's and women's perspectives from the earliest planning phases of restoration initiatives is essential to ensure greater equity in benefit‐sharing, mitigate trade‐offs for women, and build more nuanced, just and successful approaches to restoration.

Mponela, Powell↗

DOE OSTI2020

Estimating posterior quantity of interest expectations in a multilevel scalable framework

Scalable approaches for uncertainty quantification are necessary for characterizing prediction confidence in large-scale subsurface flow simulations with uncertain permeability. To this end we explore a multilevel Monte Carlo approach for estimating posterior moments of a particular quantity of interest, where we employ an element-agglomerated algebraic multigrid (AMG) technique to generate the hierarchy of coarse spaces with guaranteed approximation properties for both the generation of spatially correlated random fields and the forward simulation of Darcy's law to model subsurface flow. In both these components (sampling and forward solves), we exploit solvers that rely on state-of-the-art scalable AMG. To illustrate the applicability of this approach, numerical tests are performed on two 3D examples-a unit cube and an egg-shaped domain with an irregular boundary-where the scalability of each simulation as well as the scalability of the overall algorithm are demonstrated.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Multilevel-in-width training for deep neural network regression

A common challenge in regression is that for many problems, the degrees of freedom required for a high-quality solution also allows for overfitting. Regularization is a class of strategies that seek to restrict the range of possible solutions so as to discourage overfitting while still enabling good solutions, and different regularization strategies impose different types of restrictions. In this paper, we present a multilevel regularization strategy that constructs and trains a hierarchy of neural networks, each of which has layers that are wider versions of the previous network's layers. Here, we draw intuition and techniques from the field of Algebraic Multigrid (AMG), traditionally used for solving linear and nonlinear systems of equations, and specifically adapt the Full Approximation Scheme (FAS) for nonlinear systems of equations to the problem of deep learning. Training through V-cycles then encourage the neural networks to build a hierarchical understanding of the problem. We refer to this approach as multilevel-in-width to distinguish from prior multilevel works which hierarchically alter the depth of neural networks. The resulting approach is a highly flexible framework that can be applied to a variety of layer types, which we demonstrate with both fully connected and convolutional layers. We experimentally show with PDE regression problems that our multilevel training approach is an effective regularizer, improving the generalize performance of the neural networks studied.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Imaging a solvent-swollen polymer gel network by open liquid transmission electron microscopy

Visualizing the network of a solvent-swollen polymer gel remains problematic. To address this challenge, open transmission electron microscopy (TEM) was applied to thin gel films permeated by a nonvolatile ionic liquid. The targeted physical gels were prepared by cooling concentrated solutions of poly(ethylene glycol) in 1-ethyl-3-methyl imidazolium ethyl sulfate [EMIM][EtSO 4 ]. During the cooling, gelation occurred by a frustrated crystallization of the dissolved polymer, leading to a percolated, solvent-permeated semicrystalline network in which nanoscale polymer crystals acted as crosslinks. Crystalline features ranging from ~5 to ~200 nm were observed, with the visible network strands dominantly consisting of long curvilinear crystallites of ~15–20 nm diameter. Nascent spherulites irregularly decorated the network, creating a complex structural hierarchy that complicated analyses. Lacking diffraction contrast, TEM did not visualize the many disordered, fully solvated PEG chains present in the voids between crystals. Finally, recognizing that a network's three dimensionality is ambiguous when assessed through two-dimensional microscopy projections, a small gel region was studied by TEM tomography, revealing a nearly isotropic three-dimensional arrangement of the curvilinear crystallites, which displayed remarkably uniform cylindrical cross sections.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Spatial analysis of cell patterning to aid genetic and phenotypic understanding of grass stomatal density: A case study in maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Higgs Inflation and the Electroweak Gauge Sector

Abstract We introduce a method that allows the Higgs to be the inflaton. The Higgs is considered as a pseudo‐Nambu‐Goldstone (pNG) boson of a global coset symmetry , which is spontaneously breaks at an energy scale . A suitable Chern−Simons (CS) interaction is given to it, with representing the dimensionless CS coupling strength and an decay constant. As a result, slow‐roll inflation occurs via ‐induced friction down a steep sinusoidal potential. To obey electroweak symmetry, the lowest‐order CS interaction is required to be quadratic in the Higgs, with the coupling strength . Higher‐order interaction terms keep the full Lagrangian nearly invariant under the approximate pNG shift symmetry. Employing the simplest symmetry coset , ‐folds of inflation occur when . Successfully explaining inflation necessitates small values of the decay constant, ; this in turn requires large , which is ruled out by electric dipole measurements. Although the electroweak hierarchy problem while achieving successful inflation, the real benefit is found in providing a different path to identifying the Higgs as the inflaton, outside the standard modified‐gravity framework.

Alexander, Stephon [Brown Center for Theoretical P↗

DOE OSTI2023

Diurnal cycle of precipitation over the tropics and central United States: intercomparison of general circulation models

Diurnal precipitation is a fundamental mode of variability that climate models have difficulty in accurately simulating. Here, in this work, the diurnal cycle of precipitation (DCP) in participating climate models from the Global Energy and Water Exchanges' DCP project is evaluated over the tropics and central United States. Common model biases such as excessive precipitation over the tropics, too frequent light-to-moderate rain, and the failure to capture propagating convection in the central United States still exist. Over the central United States, the issues of too weak rainfall intensity in climate runs is well improved in their hindcast runs with initial conditions from numerical weather prediction analyses. But the improvement is minimal over the central Amazon. Incorporating the role of the large-scale environment in convective triggering processes helps resolve the phase-locking issue in many models where precipitation often incorrectly peaks near noon due to maximum insolation over land. Allowing air parcels to be lifted above the boundary layer improves the simulation of nocturnal precipitation which is often associated with the propagation of mesoscale systems. Including convective memory in cumulus parameterizations acts to suppress light-to-moderate rain and promote intense rainfall; however, it also weakens the diurnal variability. Simply increasing model resolution (with cumulus parameterizations still used) cannot fully resolve the biases of low-resolution climate models in DCP. The hierarchy modeling framework from this study is useful for identifying the missing physics in models and testing new development of model convective processes over different convective regimes.

58 GEOSCIENCES↗

DOE OSTI2022

libwfa: Wavefunction analysis tools for excited and open‐shell electronic states

Abstract An open‐source software library for wavefunction analysis, libwfa, provides a comprehensive and flexible toolbox for post‐processing excited‐state calculations, featuring a hierarchy of interconnected visual and quantitative analysis methods. These tools afford compact graphical representations of various excited‐state processes, provide detailed insight into electronic structure, and are suitable for automated processing of large data sets. The analysis is based on reduced quantities, such as state and transition density matrices (DMs), and allows one to distill simple molecular orbital pictures of physical phenomena from intricate correlated wavefunctions. The implemented descriptors provide a rigorous link between many‐body wavefunctions and intuitive physical and chemical models, for example, exciton binding, double excitations, orbital relaxation, and polyradical character. A broad range of quantum‐chemical methods is interfaced with libwfa via a uniform interface layer in the form of DMs. This contribution reviews the structure of libwfa and highlights its capabilities by several representative use cases. This article is categorized under: Software > Quantum Chemistry Theoretical and Physical Chemistry > Spectroscopy

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Sterile neutrino dark matter and leptogenesis in Left-Right Higgs Parity

The standard model Higgs quartic coupling vanishes at (10 9 – 10 13 ) GeV. We study SU(2) L × SU(2) R × U(1) B–L theories that incorporate the Higgs Parity mechanism, where this becomes the scale of Left-Right symmetry breaking, $v_R$. Furthermore, these theories solve the strong CP problem and predict three right-handed neutrinos. We introduce cosmologies where SU(2) R × U(1) B–L gauge interactions produce right-handed neutrinos via the freeze-out or freeze-in mechanisms. In both cases, we find the parameter space where the lightest right-handed neutrino is dark matter and the decay of a heavier one creates the baryon asymmetry of the universe via leptogenesis. A theory of flavor is constructed that naturally accounts for the lightness and stability of the right-handed neutrino dark matter, while maintaining sufficient baryon asymmetry. The dark matter abundance and successful natural leptogenesis require vR to be in the range (10 10 – 10 13 ) GeV for freeze-out, in remarkable agreement with the scale where the Higgs quartic coupling vanishes, whereas freeze-in requires $v_R$ ≳ 109 GeV. The allowed parameter space can be probed by the warmness of dark matter, precise determinations of the top quark mass and QCD coupling by future colliders and lattice computations, and measurement of the neutrino mass hierarchy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Joint statistics of cosmological constant and SUSY breaking in flux vacua with nilpotent Goldstino

We obtain the joint distribution of the gravitino mass and the cosmological constant in KKLT and LVS models with anti-D3 brane uplifting described via the nilpotent goldstino formalism. Moduli stabilisation (of both complex structure and Kähler moduli) is incorporated so that we sample only over points corresponding to vacua. Our key inputs are the distributions of the flux superpotential, the string coupling and the hierarchies of warped throats. In the limit of zero cosmological constant, we find that both in KKLT and LVS the distributions are tilted favourably towards lower scales of supersymmetry breaking.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Axion dark matter from frictional misalignment

We study the impact of sphaleron-induced thermal friction on the axion dark-matter abundance due to the interaction of an axion-like particle (ALP) with a dark non-abelian gauge sector in a secluded thermal bath. Thermal friction can either enhance the axion relic density by delaying the onset of oscillations or suppress it by damping them. We derive an analytical formula for the frictional adiabatic invariant, which remains constant along the axion evolution and which allows us to compute the axion relic density in a general set-up. Even in the most minimal scenario, in which a single gauge group is responsible for both the generation of the ALP mass and the friction force, we find that the resulting dark-matter abundance from the misalignment mechanism deviates from the standard scenario for axion masses m a ≳ 100 eV. We also generalize our analysis to the case where the gauge field that induces friction and the gauge sector responsible for the ALP mass are distinct and their couplings to the axion have a large hierarchy as can be justified by means of alignment or clockwork scenarios. We find that it is easy to open up the ALP parameter space where the resulting axion abundance matches the observed dark-matter relic density both in the traditionally over- and underabundant regimes. This conclusion also holds for the QCD axion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Gravitational Waves from Nnaturalness

Abstract We study the prospects for probing the Nnaturalness solution to the electroweak hierarchy problem with future gravitational wave observatories. Nnaturalness, in its simplest incarnation, predictsNcopies of the Standard Model with varying Higgs mass parameters. We show that in certain parameter regions the scalar reheaton transfers a substantial energy density to the sector with the smallest positive Higgs squared mass while remaining consistent with bounds on additional effective relativistic species. In this sector, all six quarks are much lighter than the corresponding QCD confinement scale, allowing for the possibility of a first-order chiral symmetry-breaking phase transition and an associated stochastic gravitational wave signal. We consider several scenarios characterizing the strongly-coupled phase transition dynamics and estimate the gravitational wave spectrum for each. Pulsar timing arrays (SKA), spaced-based interferometers (BBO, Ultimate-DECIGO,μAres, asteroid ranging), and astrometric measurements (THEIA) all have the potential to explore new regions of Nnaturalness parameter space, complementing probes from next generation cosmic microwave background radiation experiments.

Physics↗

DOE OSTI2025

Grand unification at the cosmological collider with chemical potential

We introduce a tree-level chemical potential mechanism for spin-1 particles within cosmological collider physics, allowing them to be detected in primordial non-Gaussianities for masses above the inflationary Hubble scale. We apply this mechanism to orbifold grand unification and the massive unification partners of the standard model gauge bosons. Our mechanism requires at least a pair of massive vector fields which are singlets of the standard model, a condition which is satisfied in the classic “trinification” scenario. Assuming that the gauge hierarchy problem is solved by supersymmetry, gauge coupling running points to unification partners at ~ 10$^{15}$ GeV. We show that, within high-scale inflation, chemical potential enhancement can lead to observably strong signals for trinification partners in future cosmological surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗