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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 1,153 records · Page 64
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NASA NTRS2018

Autonomous Small Body Mapping and Spacecraft Navigation

Current methods for pose and shape estimation of small bodies, such as comets and asteroids, rely on extensive ground support and significant use of radiometric measurements using the Deep Space Network. The Stereo-Photoclinometry (SPC) technique is currently used to provide detailed topological information about a small body as well as its absolute orientation and position. While this technique has produced very accurate estimates, the core algorithm cannot be run in real-time and requires a team of scientists on the ground who must communicate with the spacecraft in order to oversee SPC operations. Autonomous onboard navigation addresses these limitations by eliminating the need for human oversight. In this paper, we present an optimization-based estimation algorithm for navigation that allows the spacecraft to autonomously approach and maneuver around an unknown small body by mapping its geometric shape, estimating its orientation, and simultaneously determining the trajectory of the center of mass of the small body. We show the effectiveness of the proposed algorithm using simulated data from a previous flight mission to Comet 67P.

Bhaskaran, Shyamkumar↗
DOE OSTI2021

REopt Lite User Manual

REopt Lite evaluates the economic viability of grid-connected solar photovoltaics, wind, combined heat and power, and electric and thermal storage at commercial and small industrial sites. It allows building owners to identify the system sizes and dispatch strategies that minimize the site’s life cycle cost of energy. REopt Lite also estimates the amount of time on-site generation and storage can sustain the site's critical load during a grid outage and allows the user the choice of optimizing for energy resilience. It is primarily used to inform project development decisions and to support research on the factors that drive project feasibility for market development and policy analysis. It is available through a web interface, application programing interface, and open-source code. This user manual provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Abiotic Stresses Shift Belowground Populus-Associated Bacteria Toward a Core Stress Microbiome

The identification of a common “stress microbiome” indicates tightly controlled relationships between the plant host and bacterial associates and a conserved structure in bacterial communities associated with poplar trees under different growth conditions. The ability of the microbiome to buffer the plant from extreme environmental conditions coupled with the conserved stress microbiome observed in this study suggests an opportunity for future efforts aimed at predictably modulating the microbiome to optimize plant growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Hierarchical Task Scheduler for Heterogeneous Computing

Heterogeneous computing is one of the future directions of HPC. Task scheduling in heterogeneous computing must balance the challenge of optimizing the application performance and the need for an intuitive interface with the programming run-time to maintain programming portability. The challenge is further compounded by the varying data communication time between tasks. This paper proposes RANGER, a hardware-assisted task-scheduling framework. By integrating RISC-V cores with accelerators, the RANGER scheduling framework divides scheduling into global and local levels. At the local level, RANGER further partitions each task into fine-grained subtasks to reduce the overall makespan. At the global level, RANGER maintains the coarse granularity of the task specification, thereby maintaining programming portability. The extensive experimental results demonstrate that RANGER achieves a 12.7× performance improvement on average, while only requires 2.7% of area overhead.

Miniskar, Narasinga Rao↗
DOE OSTI2017

Molten salt reactor neutronics and fuel cycle modeling and simulation with SCALE

Current interest in advanced nuclear energy and molten salt reactor (MSR) concepts has enhanced interest in building the tools necessary to analyze these systems. A Python script known as ChemTriton has been developed to simulate equilibrium MSR fuel cycle performance by modeling the changing isotopic composition of an irradiated fuel salt using SCALE for neutron transport and depletion calculations. Some capabilities in ChemTriton that have improved, include a generic geometry capable of modeling multi-zone and multi-fluid systems, enhanced time-dependent feed and separations, and a critical concentration search. Although more generally applicable, the capabilities developed to date are illustrated in this paper in three applied problems: (1) simulating the startup of a thorium-based MSR fuel cycle (a likely scenario requires the first of these MSRs to be started without available 233U); (2) determining the effect of the removal of different fission products on MSR operations; and (3) obtaining the equilibrium concentration of a mixed-oxide light-water reactor fuel in a two-stage fuel cycle with a sodium fast reactor. Moreover, the third problem is chosen to demonstrate versatility in an application to analyze the fuel cycle of a non-MSR system. During the first application, the initial fuel salt compositions fueled with different sources of fissile material are made feasible after (1) removing the associated nonfissile actinides after much of the initial fissile isotopes have burned and (2) optimizing the thorium concentration to maintain a critical configuration without significantly reducing breeding capability. In the second application, noble metal, volatile gas, and rare earth element fission products are shown to have a strong negative effect on criticality in a uranium-fueled thermal-spectrum MSR; their removal significantly increases core lifetime (by 30%) and fuel utilization. In the third application, the fuel of a mixed-oxide light-water reactor approaches an equilibrium composition after 20 depletion steps, demonstrating the potential for the longer time scales required to achieve equilibrium for solid-fueled systems over liquid fuel systems. This time to equilibrium can be reduced by starting with an initial fuel composition closer to that of the equilibrium fuel, reducing the need to handle time-dependent fuel compositions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

The role of the metal core in the performance of WO x inverse catalysts

In this study, metal-metal oxide inverse catalysts are valuable in diverse applications but selecting pairs is challenging. Here we investigate the role of metal cores (Pt, Ru, Rh, Pd, Ni) in the formation and dynamics of Brønsted acid sites on WO x overlayer on carbon. By in situ/ex situ characterizations, probe chemistry kinetics, and DFT calculations, we demonstrate that metals with varying work functions promote the WO x dispersion, enhancing the Brønsted acidity than the 3D crystallites on carbon at submonolayer coverages by tuning the oxidation state of WO x . The metal core impacts the water splitting and hydroxylation of WO x . Water splitting on Ru-WO x is thermodynamically favorable compared to Ni-WO x and increases the dehydration rate on the former, leading to an activity enhancement by increasing the H 2 pulsing frequency. This study provides insights into optimizing inverse catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Exact Gaussian processes for massive datasets via non-stationary sparsity-discovering kernels

Abstract A Gaussian Process (GP) is a prominent mathematical framework for stochastic function approximation in science and engineering applications. Its success is largely attributed to the GP’s analytical tractability, robustness, and natural inclusion of uncertainty quantification. Unfortunately, the use of exact GPs is prohibitively expensive for large datasets due to their unfavorable numerical complexity of $$O(N^3)$$ O ( N 3 ) in computation and $$O(N^2)$$ O ( N 2 ) in storage. All existing methods addressing this issue utilize some form of approximation—usually considering subsets of the full dataset or finding representative pseudo-points that render the covariance matrix well-structured and sparse. These approximate methods can lead to inaccuracies in function approximations and often limit the user’s flexibility in designing expressive kernels. Instead of inducing sparsity via data-point geometry and structure, we propose to take advantage of naturally-occurring sparsity by allowing the kernel to discover—instead of induce—sparse structure. The premise of this paper is that the data sets and physical processes modeled by GPs often exhibit natural or implicit sparsities, but commonly-used kernels do not allow us to exploit such sparsity. The core concept of exact, and at the same time sparse GPs relies on kernel definitions that provide enough flexibility to learn and encode not only non-zero but also zero covariances. This principle of ultra-flexible, compactly-supported, and non-stationary kernels, combined with HPC and constrained optimization, lets us scale exact GPs well beyond 5 million data points.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Genotype to ecotype in niche environments: adaptation of Arthrobacter to carbon availability and environmental conditions

Niche environmental conditions influence both the structure and function of microbial communities and the cellular function of individual strains. The terrestrial subsurface is a dynamic and diverse environment that exhibits specific biogeochemical conditions associated with depth, resulting in distinct environmental niches. Here, we present the characterization of seven distinct strains belonging to the genus Arthrobacter isolated from varying depths of a single sediment core and associated groundwater from an adjacent well. We characterized genotype and phenotype of each isolate to connect specific cellular functions and metabolisms to ecotype. Arthrobacter isolates from each ecotype demonstrated functional and genomic capacities specific to their biogeochemical conditions of origin, including laboratory-demonstrated characterization of salinity tolerance and optimal pH, and genes for utilization of carbohydrates and other carbon substrates. Analysis of the Arthrobacter pangenome revealed that it is notably open with a volatile accessory genome compared to previous pangenome studies on other genera, suggesting a high potential for adaptability to environmental niches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Confinement in Wendelstein 7-X Limiter Plasmas

Observations on confinement in the first experimental campaign on the optimized Stellarator Wendelstein 7-X are summarized. In this phase W7-X was equipped with five inboard limiters only and thus the discharge length restricted to avoid local overheating. Stationary plasmas are limited to low densities <2–3 centerdot 10 19 m -3 . With the available 4.3 MW ECR Heating core T e ~ 8 keV, T i ~ 1–2 keV are achieved routinely resulting in energy confinement time τ E between 80 ms to 150 ms. For these conditions the plasmas show characteristics of core electron root confinement with peaked T e -profiles and positive E r up to about half of the minor radius. Lastly, profiles and plasma currents respond to on- and off-axis heating and co- and counter ECCD respectively.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Exploiting Vector and Multicore Parallelsim for Recursive, Data- and Task-Parallel Programs

Modern hardware contains parallel execution resources that are well-suited for data-parallelism-vector units-and task parallelism-multicores. However, most work on parallel scheduling focuses on one type of hardware or the other. In this work, we present a scheduling framework that allows for a unified treatment of task- and data-parallelism. Our key insight is an abstraction, task blocks, that uniformly handles data-parallel iterations and task-parallel tasks, allowing them to be scheduled on vector units or executed independently as multicores. Our framework allows us to define schedulers that can dynamically select between executing task- blocks on vector units or multicores. We show that these schedulers are asymptotically optimal, and deliver the maximum amount of parallelism available in computation trees. To evaluate our schedulers, we develop program transformations that can convert mixed data- and task-parallel pro- grams into task block-based programs. Using a prototype instantiation of our scheduling framework, we show that, on an 8-core system, we can simultaneously exploit vector and multicore parallelism to achieve 14×-108× speedup over sequential baselines.

Ren, Bin↗
DOE OSTI2020

Parallel-in-Time Simulation of Lindblad's Equation

Constructing fast quantum logic gates is critical to building a scalable quantum computer. We consider a qudit, a quantum version of a bit that can take an arbitrary number of states, coupled with a cavity. In this project, we wish to force the qudit to reach the 0-state, for any possible initial state. The coupled system changes in time according to Lindblad’s equation, an ordinary differential equation on the density matrix of the quantum system. Lindblad’s equation contains some parameters that we can control, so-called control functions. We seek control functions which force the qudit to the 0-state within 2 microseconds, which is much faster than what is currently done in practice. The search method is gradient descent, a numerical optimization method that uses gradient information to iteratively improve the control parameters. My contribution to this project is an attempt to speed up the computation of the gradient. It currently takes about 40 seconds to compute the gradient which involves solving a set of ODEs sequentially. Current supercomputers have thousands of cores, but sequential computations can only make use of 1 core at a time. We wish to divide up the work better, so that we can use many more cores at once. To this end, we have implemented the Multigrid Reduction in Time (MGRIT) algorithm. We perform a systematic parameter search on how to best apply this algorithm. Results indicate a 25 percent speed up for solving Lindblad’s equation and determining how close the final state is the 0-state.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Aerolastic tailoring and integrated wing design

Much has been learned from the TSO optimization code over the years in determining aeroelastic tailoring's place in the integrated design process. Indeed, it has become apparent that aeroelastic tailoring is and should be deeply embedded in design. Aeroelastic tailoring can have tremendous effects on the design loads, and design loads affect every aspect of the design process. While optimization enables the evaluation of design sensitivities, valid computational simulations are required to make these sensitivities valid. Aircraft maneuvers simulated must adequately cover the plane's intended flight envelope, realistic design criteria must be included, and models among the various disciplines must be calibrated among themselves and with any hard-core (e.g., wind tunnel) data available. The information gained and benefits derived from aeroelastic tailoring provide a focal point for the various disciplines to become involved and communicate with one another to reach the best design possible.

Love, Mike H.↗
DOE OSTI2017

Liquid-Rich Shale Potential of Utah’s Uinta and Paradox Basins: Reservoir Characterization and Development Optimization

The enclosed report is the culmination of a multi-year and multi-faceted research project investigating Utah’s unconventional tight oil potential. From the beginning, the project team focused efforts on two different plays: (1) the basal Green River Formation’s (GRF) Uteland Butte unconventional play in the Uinta Basin and (2) the more established but understudied Cane Creek shale play in the Paradox Basin. The 2009-2014 high price of crude oil, coupled with lower natural gas prices, generated renewed interest in exploration and development of liquid hydrocarbon reserves. Following the success of the mid-2000s shale gas boom and employing many of the same well completion techniques, petroleum companies started exploring for liquid petroleum in shale formations. In fact, many shales targeted for natural gas include areas in which the shale is more prone to liquid production. In Utah, organic-rich shales in the Uinta and Paradox Basins have been the source of significant hydrocarbon generation, with companies traditionally targeting the interbedded sands or carbonates for their conventional resource recovery. Because of the advances in horizontal drilling and hydraulic fracturing techniques, operators in these basins started to explore the petroleum production potential of the shale units themselves. The GRF in the Uinta Basin has been studied for over 50 years, since the first hydrocarbon discoveries. However, those studies focused on the many conventional sandstone reservoirs currently producing oil and gas. In contrast, less information was available about the more unconventional crude oil production potential of thinner carbonate/shale units, most notably the basal Uteland Butte member. The Cane Creek shale of the Paradox Basin has been a target for exploration periodically since the 1960s and produces oil from several small fields. The play generated much interest in the early 1990s with the successful use of horizontal drilling. Recently, the USGS assessed the undiscovered oil resource in the Cane Creek shale of the Paradox Basin at 103 million barrels at a 95 percent confidence level and 198 million barrels at a 50 percent confidence level. Nonetheless, limited research was available or published to further define the play and the reservoir characteristics. The specific objectives of the enclosed research were to (1) characterize geologic, geochemical, and geomechanical rock properties of target zones in the two designated basins by compiling data and by analyzing available cores, cuttings, and well logs; (2) describe outcrop reservoir analogs of GRF plays (Cane Creek shale is not exposed) and compare them to subsurface data; (3) map major regional trends for targeted intervals and identify “sweet spots” that have the greatest oil potential; (4) reduce exploration costs and drilling risks, especially in environmentally sensitive areas; (5) improve drilling and fracturing effectiveness by determining optimal well completion design; and (6) reduce field development costs, maximize oil recovery, and increase reserves. These objectives are all addressed in a series of nine publications that resulted from this extensive research project. Each publication is included in this report as an independent appendix.

02 PETROLEUM↗
DOE OSTI2022

Redox oxide@molten salt as a generalized catalyst design strategy for oxidative dehydrogenation of ethane via selective hydrogen combustion

Here, the current study demonstrates a redox oxide @ molten salt core-shell architecture as a generalized redox catalyst design strategy for chemical looping – oxidative dehydrogenation of ethane. 17 combinations of redox active oxides and molten salts were prepared, evaluated, and characterized. X-ray diffraction indicates that the redox oxides and molten salts are fully compatible, forming separate and stable phases. X-ray photoelectron spectroscopy demonstrates that the molten salts aggregate at the redox oxide surface, forming a core-shell structure to block the non-selective sites responsible for CO x formation. Up to ~74% single-pass olefin yields were achieved using the proposed redox catalyst design strategy. Statistical analyses of the performance data indicate the potential to achieve up to 86.7% single-pass yield by simply optimizing the operating conditions using the redox catalysts reported in this study. Meanwhile, the generalizability of the catalyst design strategy offers exciting opportunities to further optimize the composition and performance of the redox catalysts for ethane ODH under a chemical looping scheme with significantly reduced energy consumption and CO 2 emissions.

03 NATURAL GAS↗
DOE OSTI2017

Structural Evolution of Sub-10 nm Octahedral Platinum$-$Nickel Bimetallic Nanocrystals

Octahedral Pt alloy nanocrystals (NCs) have shown excellent activities as electrocatalysts toward oxygen reduction reaction (ORR). As the activity and stability of NCs are highly dependent on their structure and the elemental distribution, it is of great importance to understand the formation mechanism of octahedral NCs and to rationally synthesize shape-controlled alloy catalysts with optimized ORR activity and stability. However, the factors controlling the structural and compositional evolution during the synthesis have not been well understood yet. Here in this paper, we systematically investigated the structure and composition evolution pathways of Pt–Ni octahedra synthesized with the assistance of W(CO) 6 and revealed a unique core–shell structure consisting of a Pt core and a Pt–Ni alloy shell. Below 140 °C, sphere-like pure Pt NCs with the diameter of 3–4 nm first nucleated, followed by the isotropic growth of Pt–Ni alloy on the seeds at temperatures between 170 and 230 °C forming Pt@Pt–Ni core–shell octahedra with {111} facets. Owing to its unique structure, the Pt@Pt–Ni octahedra show an unparalleled stability during potential cycling, that is, no activity drop after 10 000 cycles between 0.6 and 1.0 V. This work proposes the Pt@Pt–Ni octahedra as a high profile electrocatalyst for ORR and reveals the structural and composition evolution pathways of Pt-based bimetallic NCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Design and optimization of nanoparticle-pigmented solar selective absorber coatings for high-temperature concentrating solar thermal systems

In this paper, we present a systematic approach for the design and optimization of nanoparticle-pigmented solar selective absorbers for operation at 750 °C. Using the scattering and absorption cross-sections calculated by Lorenz-Mie scattering theory as input, we employ a four-flux radiative transfer method to investigate the solar selectivity mechanism and optimize the optical-to-thermal conversion efficiency (η therm ) as a function of the metallic nanoparticle material, the nanoparticle diameter, the volume fraction, and the coating thickness. Among the nanoparticle material candidates in this study, C54-TiSi 2 is the best option with an optimized η therm = 87.0% for a solar concentration ratio of C = 100 and η therm = 94.4% for C = 1000 at 750 °C. NiSi is also a promising candidate comparable to TiSi 2 in thermal efficiency, Experimentally, an un-optimized 200 nm-diameter TiSi 2 nanoparticle-silicone solar selective coating has already achieved η therm = 89.8% for C = 1000 at 750 °C. This performance is consistent with the theoretical model and close to the thermal efficiency of the commercial Pyromark 2500 coatings (90.1%). We also demonstrate that Ni/NiSi core-shell structures embedded in the SiO 1.5 matrix is thermally stable at 750 °C for 1000 h in air. Lastly, these results indicate that silicide cermet coatings are promising to achieve high optical performance and high temperature thermal stability simultaneously.

14 SOLAR ENERGY↗
DOE OSTI2018

Attacking the Opioid Epidemic: Determining the Epistatic and Pleiotropic Genetic Architectures for Chronic Pain and Opioid Addiction

We describe the CoMet application for large-scale epistatic Genome-Wide Association Studies (eGWAS) and pleiotropy studies. High performance is attained by transforming the underlying vector comparison methods into highly performant generalized distributed dense linear algebra operations. The 2-way and 3-way Proportional Similarity metric and Custom Correlation Coefficient are implemented using native or adapted GEMM kernels optimized for GPU architectures. By aggressive overlapping of communications, transfers and computations, high efficiency with respect to single GPU kernel performance is maintained up to the full Titan and Summit systems. Nearly 300 quadrillion element comparisons per second and over 2.3 mixed precision ExaOps are reached on Summit by use of Tensor Core hardware on the Nvidia Volta GPUs. Performance is four to five orders of magnitude beyond comparable state of the art. CoMet is currently being used in projects ranging from bioenergy to clinical genomics, including for the genetics of chronic pain and opioid addiction.

Joubert, Wayne↗
DOE OSTI2022

Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints

Vast volumes of data are produced by today's scientific simulations and advanced instruments. These data cannot be stored and transferred efficiently because of limited I/O bandwidth, network speed, and storage capacity. Error-bounded lossy compression can be an effective method for addressing these issues: not only can it significantly reduce data size, but it can also control the data distortion based on user-defined error bounds. In practice, many scientific applications have specific requirements or constraints for lossy compression, in order to guarantee that the reconstructed data are valid for post hoc analysis. For example, some datasets contain irrelevant data that should be isolated in particular and users often have intuition regarding value ranges, geospatial regions, and other data subsets that are crucial for subsequent analysis. Existing state-of-the-art error-bounded lossy compressors, however, do not consider these constraints during compression, resulting in inferior compression ratios with respect to user's post hoc analysis, due to the fact that the data itself provides little or no value for post hoc analysis. In this work we address this issue by proposing an optimized framework that can preserve diverse constraints during the error-bounded lossy compression, e.g., cleaning the irrelevant data, efficiently preserving different precision for multiple value intervals, and allowing users to set diverse precision over both regular and irregular regions. We perform our evaluation on a supercomputer with up to 2,100 cores. Experiments with six real-world applications show that our proposed diverse constraints based error-bounded lossy compressor can obtain a higher visual quality or data fidelity on reconstructed data with the same or even higher compression ratios compared with the traditional state-of-the-art compressor SZ. Furthermore, our experiments also demonstrate very good scalability in compression performance compared with the I/O throughput of the parallel file system.

97 MATHEMATICS AND COMPUTING↗