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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Stomatal behaviour moderates the water cost of CO 2 acquisition for 21 boreal and temperate species under experimental climate change

Abstract The linkage of stomatal behaviour with photosynthesis is critical to understanding water and carbon cycles under global change. The relationship of stomatal conductance (g s ) and CO 2 assimilation (A net ) across a range of environmental contexts, as represented in the model parameter (g 1 ), has served as a proxy of the marginal water cost of carbon acquisition. We useg 1 to assess species differences in stomatal behaviour to a decade of open‐air experimental climate change manipulations, asking whether generalisable patterns exist across species and climate contexts.A net ‐g s measurements (17 727) for 21 boreal and temperate tree species under ambient and +3.3°C warming, and ambient and ~40% summer rainfall reduction, provided >2700 estimates ofg 1 . Warming and/or reduced rainfall treatments both loweredg 1 because those treatments resulted in lower soil moisture and because stomatal behaviour changed more in warming when soil moisture was low. Species tended to respond similarly, although, in species from warmer and drier habitats, g 1 tended to be slightly higher and to be the least sensitive to the decrease in soil water. Overall, both warming and rainfall reduction consistently made stomatal behaviour more conservative in terms of water loss per unit carbon gain across 21 species and a decade of experimental observation.

Plant Sciences↗
DOE OSTI2017

1:52 Scale Testing of the First US Commercial Scale Floating Wind Turbine, VolturnUS: Testing Overview and the Evolution of Scale Model Testing Methods

Over the past 6 years, the University of Maine (UMaine) has been an active contributor in research and scale-model testing of floating offshore wind turbines (FOWTs). This paper serves to share the evolution of UMaine’s scale-model testing pedigree by exploring the various test campaigns at a high level, culminating with the design validation of the VolturnUS floating platform. These model test campaigns have each provided key insights into the behavior of FOWT platforms as well as improving the ability to perform model tests of FOWTs. In 2011, the UMaine-led DeepCwind Consortium carried out 1/50-scale model tests of a generic tension leg platform (TLP), a semi-submersible (semi), and a spar-buoy (spar) floating platform at the Maritime Research Institute Netherlands (MARIN) test facility. The designs were Froude-scaled and supported a scaled version of the 5-MW National Renewable Energy Laboratory (NREL) offshore research turbine. Data from these tests has been used extensively for numerical simulation validation efforts using NREL’s computer-aided engineering software FAST and laid the foundation for UMaine’s design efforts on VolturnUS. In 2013, UMaine conducted another test campaign at MARIN using the original semi-submersible from 2011 with an improved turbine as well as a 1:50-scale model of the VolturnUS concrete semi-submersible design. The improved DeepCwind semi-submersible data is currently being utilized in the validation of a large number of other analysis codes as part of the International Energy Agency’s OC5 project. In 2015, UMaine opened its own Wind/Wave test facility, the Alfond Wind/Wave Ocean Engineering Laboratory (W2). Utilizing this new facility, UMaine tested the 1:50-scale model DeepCwind semi-submersible, repeating the tests from MARIN, to validate the experimental equipment and procedures as well as demonstrate the capability of the W2. In 2016 UMaine carried out testing of a 1:52-scale model of the 100% design of the VolturnUS with a 6-MW topside as a final design validation to support the US Department of Energy-supported, full-scale Aqua Ventus demonstration project scheduled to be connected to the grid in 2019. A newly designed 6-MW scale model turbine was used in this test and the performance-matched turbine design methodology is described. Selected results from the test campaign and preliminary numerical comparisons are discussed as well as key lessons learned from the model test campaigns are presented.

17 WIND ENERGY↗
DOE OSTI2019

How heteroepitaxy occurs on strontium titanate

In traditional models of heteroepitaxy, the substrate serves mainly as a crystalline template for the thin-film lattice, dictating the initial roughness of the film and the degree of coherent strain. Here, performing in situ surface x-ray diffraction during the heteroepitaxial growth of LaTiO 3 on SrTiO 3 (001), we find that a TiO 2 adlayer composed of the ( 13 × 13 ) R 33.7° and ( 2 × 2 ) R 45.0° reconstructions is a highly active participant in the growth process, continually diffusing to the surface throughout deposition. The effects of the TiO 2 adlayer on layer-by-layer growth are investigated using different deposition sequences and anomalous x-ray scattering, both of which permit detailed insight into the dynamic layer rearrangements that take place. Our work challenges commonly held assumptions regarding growth on TiO 2 -terminated SrTiO 3 (001) and demonstrates the critical role of excess TiO 2 surface stoichiometry on the initial stages of heteroepitaxial growth on this important perovskite oxide substrate material.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations

The U.S. Department of Energy has identified exascale-class wind farm simulation as critical to wind energy scientific discovery. A primary objective of the ExaWind project is to build high-performance, predictive computational fluid dynamics (CFD) tools that satisfy these modeling needs. GPU accelerators will serve as the computational thoroughbreds of next-generation, exascale-class supercomputers. Here, we report on our efforts in preparing the ExaWind unstructured mesh solver, Nalu-Wind, for exascale-class machines. For computing at this scale, a simple port of the incompressible-flow algorithms to GPUs is insufficient. To achieve high performance, one needs novel algorithms that are application aware, memory efficient, and optimized for the latest-generation GPU devices. The result of our efforts are unstructured-mesh simulations of wind turbines that can effectively leverage thousands of GPUs. In particular, we demonstrate a first-of-its-kind, incompressible-flow simulation using Algebraic Multigrid solvers that strong scales to more than 4000 GPUs on the Summit supercomputer.

algebraic multigrid↗
DOE OSTI2022

RAFT (Response Amplitudes of Floating Turbines) [SWR-22-40]

RAFT is a Python code for frequency-domain analysis of floating wind turbines. RAFT works in the frequency domain to provide efficient computations of a floating wind system's response spectra accounting for platform hydrodynamics, quasi-static mooring reactions, rotor aerodynamics, and linearized control. It can be used to calculate response amplitude operators (RAO's), power spectral densities, mean/static properties, and response metrics based on mean and root-mean-square values of each output. RAFT serves as the Level 1 model in the WEIS (Wind Energy with Integrated Servo-control) toolkit, and features an OpenMDAO wrapper.

Hall, Matthew↗
DOE OSTI2012

Exploring the Switchgrass Transcriptome Using Second-Generation Sequencing Technology

Switchgrass (Panicum virgatum L.) is a C4 perennial grass and widely popular as an important bioenergy crop. To accelerate the pace of developing high yielding switchgrass cultivars adapted to diverse environmental niches, the generation of genomic resources for this plant is necessary. The large genome size and polyploid nature of switchgrass makes whole genome sequencing a daunting task even with current technologies. Exploring the transcriptional landscape using next generation sequencing technologies provides a viable alternative to whole genome sequencing in switchgrass. Switchgrass cDNA libraries from germinating seedlings, emerging tillers, flowers, and dormant seeds were sequenced using Roche 454 GS-FLX Titanium technology, generating 980,000 reads with an average read length of 367 bp. De novo assembly generated 243,600 contigs with an average length of 535 bp. Using the foxtail millet genome as a reference greatly improved the assembly and annotation of switchgrass ESTs. Comparative analysis of the 454-derived switchgrass EST reads with other sequenced monocots including Brachypodium, sorghum, rice and maize indicated a 70– 80% overlap. RPKM analysis demonstrated unique transcriptional signatures of the four tissues analyzed in this study. More than 24,000 ESTs were identified in the dormant seed library. In silico analysis indicated that there are more than 2000 ESTSSRs in this collection. Expression of several orphan ESTs was confirmed by RT-PCR. We estimate that about 90% of the switchgrass gene space has been covered in this analysis. This study nearly doubles the amount of EST information for switchgrass currently in the public domain. The celerity and economical nature of second-generation sequencing technologies provide an in-depth view of the gene space of complex genomes like switchgrass. Sequence analysis of closely related members of the NAD + -malic enzyme type C4 grasses such as the model system Setaria viridis can serve as a viable proxy for the switchgrass genome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Model-ready benchmarks for NPP, ANPP, litter fluxes, and recruitment into the 1 cm dbh size class

The intended use of this dataset is to serve as an observational benchmark to evaluate model predictions of NPP, ANPP, litter fluxes, and recruitment at Barro Colorado Island, Panama. This dataset contains four CSV files and one text file. “Benchmarks-NPP-ANPP-R-L.csv” provides estimates of annual ecosystem-level reproductive litter flux (R), leaf litter flux (L), aboveground net primary productivity (ANPP), and net primary productivity (NPP) for 61 field plots throughout tropical, temperate, and boreal forest biomes. An additional 499 plots (n = 550) include estimates of just R, L, and R/L. Each row reports a distinct set of estimates for one sampling interval at one plot. “Metadata-Benchmarks-NPP-ANPP-R-L.csv” contains field descriptions for all data fields in “Benchmarks-NPP-ANPP-R-L.csv”. “References-Benchmarks-NPP-ANPP-R-L.txt” contains full references to the original studies used to produce the observations at each plot included in the data. “Benchmarks-Recruitment.csv” provides estimates of species-level recruitment rates into the 1 cm dbh size class at four CTFS-ForestGeo sites using methods that account for unobserved mortality of new recruits between census intervals (Kohyama et al., 2018). “Metadata-Benchmarks-Recruitment.csv” contains field descriptions for all data fields in “Benchmarks-Recruitment.csv”.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Regulatory Incentives and Disincentives for Utility Investments in Grid Modernization

Electric power is America's most capital-intensive industry, with more than $100 billion invested each year in energy infrastructure. Investment needs are likely to grow as electric utilities make power systems more reliable and resilient, deploy advanced digital technologies, and facilitate new services to meet some consumers' expectations for greater choice and control. But do current regulatory approaches provide the appropriate incentives for grid modernization investments? This report presents three perspectives: -Financial analyst Steve Kihm begins by explaining that any major investor-owned electric utility that wants to raise capital today can do so at a reasonable cost. The question is whether utility managers want to raise capital for grid modernization. Specifically, they look for investments that create the most value for their existing shareholders. In cases where grid modernization investments are not the best choice in terms of shareholder value, Kihm describes shareholder incentive mechanisms that regulators could consider to encourage such investments when they are in the public interest. -From an institutional perspective, Dr. Janice Beecher finds that the traditional rate-base/rate of return regulatory model provides powerful incentives for utilities to pursue investments, cost control, efficiency and even innovation, and it is well suited to the policy objectives of grid modernization. Prudence of grid modernization investments (fair returns) depends on careful evaluation of the specific asset, and any special incentives (bonus returns) should be used only if they promote economic efficiency consistent with the core goals of economic regulation. According to Beecher, realizing the promises of grid modernization depends on effective implementation of the traditional regulatory model and ratemaking tools to serve the public interest. -Conversely, former commissioner and clean energy consultant Ron Lehr says that rapid electric industry changes require a better alignment of utility investment incentives with changes challenging the electricity sector, emerging grid modernization options and benefits, and public policies. For example, investor-owned utilities typically have an incentive to make capital investments, but rarely to employ expense-based solutions, since utilities do not earn profits on expenses. Further, Lehr cites a variety of factors that stand in the way of creating well targeted and well aligned utility incentives, including litigated regulatory processes. These may be a poor choice for finding the right balance among competing interests, establishing rules of prospective application, justifying demonstrations of new technologies and approaches to meeting emerging consumer demands, and keeping pace with rapid change.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Universal Design Curves for Elastomeric Direct Ink-Writing Architectures

Direct ink writing of silicone elastomers enables printing with precise control of porosity and mechan- ical properties of ordered cellular solids, suitable for shock absorption and stress mitigation applications. With the ability to manipulate structure and feedstock stiffness, the design space becomes challenging to parse to obtain a solution producing a desired mechanical response. Here we derive an analytical design approach for a specific architecture. Results from finite element simulations and quasi-static mechanical tests of two different parallel strand architectures were analyzed to understand the structure-property relationships under compressive strain. Combining effective stiffness-density scaling with least squares optimization of the stress responses yielded general response curves parameterized by resin modulus and strand spacing. An analytical expression of these curves serves as a reduced order model, which, when optimized, provides a rapid design capability for filament-based 3D printed structures. As a demonstration, the optimal design of a face-centered tetragonal architecture is computed that satisfies prescribed minimum and maximum load constraints.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Connections between nonlocal operators: From vector calculus identities to a fractional Helmholtz decomposition

Nonlocal vector calculus, which is based on the nonlocal forms of gradient, divergence, and Laplace operators in multiple dimensions, has shown promising applications in fields such as hydrology, mechanics, and image processing. In this work, we study the analytical underpinnings of these operators. We rigorously treat compositions of nonlocal operators, prove nonlocal vector calculus identities, and connect weighted and unweighted variational frameworks. We combine these results to obtain a weighted fractional Helmholtz decomposition which is valid for sufficiently smooth vector fields. Our approach identifies the function spaces in which the stated identities and decompositions hold, providing a rigorous foundation to the nonlocal vector calculus identities that can serve as tools for nonlocal modeling in higher dimensions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴ speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously previously impossible with conventional tools while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗
DOE OSTI2022

Cooperative Research and Infectious Disease Surveillance: A 2021 Epilogue

As the world looks forward to turning a corner in the face of the COVID-19 pandemic, it becomes increasingly evident that international research cooperation and dialogue is necessary to end this global catastrophe. Last year, we initiated a research topic: “Infectious Disease Surveillance: Cooperative Research in Response to Recent Outbreaks, Including COVID-19,” which aimed at featuring manuscripts focused on the essential link between surveillance and cooperative research for emerging and endemic diseases, and highlighting scientific partnerships in countries under-represented in the scientific literature. Here we recognize the body of work published from our manuscript call that resulted in over 50 published papers. This current analysis describes articles and authors from a variety of funded and unfunded international sources. The work exemplifies successful research and publications which are frequently cooperative, and may serve as a basis to model further global scientific engagements.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

EPIC 219388192b—An Inhabitant of the Brown Dwarf Desert in the Ruprecht 147 Open Cluster

We report the discovery of EPIC 219388192b, a transiting brown dwarf in a 5.3 day orbit around a member star of Ruprecht 147, the oldest nearby open cluster association, which was photometrically monitored by K2 during its Campaign 7. We combine the K2 time-series data with ground-based adaptive optics imaging and high-resolution spectroscopy to rule out false positive scenarios and determine the main parameters of the system. EPIC 219388192b has a radius of R{sub b}=0.937±0.032 R {sub Jup} and mass of M{sub b}=36.84±0.97 M {sub Jup}, yielding a mean density of 59.6±7.6 g cm{sup −3}. The host star is nearly a solar twin with mass M{sub ⋆}=1.01±0.04 M {sub ⊙}, radius R{sub ⋆}=1.01±0.03 R {sub ⊙}, effective temperature T {sub eff} = 5850 ± 85 K, and iron abundance [Fe/H] = 0.03 ± 0.08 dex. Its age, spectroscopic distance, and reddening are consistent with those of Ruprecht 147, corroborating its cluster membership. EPIC 219388192b is the first mature brown dwarf with precise determinations of mass, radius, and age, and serves as benchmark for evolutionary models in the substellar regime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Developing a Validation Methodology for Expert-Informed Bayesian Network Models Supporting Nuclear Nonproliferation Analysis

Under the auspices of Pacific Northwest National Laboratory’s Signature Discovery Initiative (SDI), the research team developed a series of Bayesian Network models to assess multi-source signatures of nuclear programs. A Bayesian network is a mathematical model that can be used to marshal evidence to assess competing hypotheses. The purpose of the models was to allow non-expert analysts to benefit from the use of expert-informed mathematical models to assess nuclear programs, because such assessments require significant technical expertise ranging from the nuclear fuel cycle, construction and engineering, imagery analysis, and so forth. One such model developed under this research was aimed at assessing the consistency of open-source information about a nuclear facility with the facility’s declared use. The model incorporates factors such as location, security and safety features among others identified by subject matter experts as crucial to their assessments. The model includes key features, observables and their relationships. The model also provides documentation, which serves as training materials for the non-experts.

White, Amanda M.↗
DOE OSTI2016

On the short-term uncertainty in performance f a point absorber wave energy converter

Of interest, in this study, is the quantification of uncertainty in the performance of a two-body wave point absorber (Reference Model 3 or RM3), which serves as a wave energy converter (WEC). We demonstrate how simulation tools may be used to establish short-term relationships between any performance parameter of the WEC device and wave height in individual sea states. We demonstrate this methodology for two sea states. Efficient structural reliability methods, validated using more expensive Monte Carlo sampling, allow the estimation of uncertainty in performance of the device. Such methods, when combined with metocean data quantifying the likelihood of different sea states, can be useful in long-term studies and in reliability-based design.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

Stochastic Molecular Dynamics

I can not pass up the opportunity to honor Graeme Bird, a true gentleman and a real scholar, if there ever was one. When we first met at a rarefied gas dynamics conference, it was instant mutual admiration. Furthermore, we met rarely thereafter at subsequent rarefied gas meetings since I attended them infrequently as a physicist interested in hydrodynamics, where often even a rarefied gas without deterministic collisions can serve as a simple fluid model but Graeme attended them regularly. In that rst meeting I became aware of DSMC, read Graeme paper and found to my astonishment that the only reference in that paper was to my molecular dynamics work2. Indeed DSMC is computationally faster competitor to molecular dynamics and it is this feature that I would like to emphasize in this brief note. It is for this reason that I entitled this contribution \stochastic molecular dynamics". I once told Graeme that that would have been a more descriptive name to his method than DSMC. DSMC is also a good demonstration that an algorithm developed for an entirely different purposes can also be very useful for other applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations: Preprint

The US Department of Energy has identified Exascale-Class wind farm simulation tools as critical to wind energy scientific discovery. A primary objective of the Exawind project is to build high-performance, predictive Computational Fluid Dynamics tools that satisfy these modeling needs. GPU accelerators will serve as the computational thoroughbreds of next generation, Exascale-Class, platforms. Here, we report on our efforts for preparing the Exawind unstructured mesh solver, Nalu-Wind, for Exascale-Class machines. For computing at this scale, a simple port of the incompressible-flow algorithms to GPUs is not sufficient. One needs novel algorithms that are application aware, memory efficient, and optimized for latest generation GPU devices to get high-performance. The result of our efforts are unstructured mesh simulations of wind turbines that use 1/6 the compute resources of Summit supercomputer at Oak Ridge National Lab. In particular, we demonstrate a first-of-its-kind, simulation using Algebraic Multigrid solvers on over 4000 GPUs.

algebraic multigrid↗
DOE OSTI2025

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴× speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously—previously impossible with conventional tools—while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗