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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

On efficient Hessian computation using the edge pushing algorithm in Julia

Evaluating the Hessian matrix of second-order derivatives at a sequence of points can be costly when applying second-order methods for nonlinear optimization. In this work, we discuss our experiences implementing the recently proposed Edge Pushing (EP) method in Julia as an experimental replacement for the current colouring-based methods used by JuMP, an open-source algebraic modelling language. We propose an alternative data structure for sparse Hessians to avoid the use of hash tables and analyse the space and time complexity of EP method. In our benchmarks, we find that EP is very competitive in terms of both preprocessing time and Hessian evaluation time. As a result, we identify cases where EP closes the performance gap between JuMP's previous implementation and the implementation in AMPL, a commercial software package with similar functionality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

E-beam manipulation of Si atoms on graphene edges with an aberration-corrected scanning transmission electron microscope

The burgeoning field of atomic-level material control holds great promise for future breakthroughs in quantum and memristive device manufacture and fundamental studies of atomic-scale chemistry. Realization of atom-by-atom control of matter represents a complex and ongoing challenge. Here, we explore the feasibility of controllable motion of dopant Si atoms at the edges of graphene via the sub-atomically focused electron beam in a scanning transmission electron microscope. Furthermore, we demonstrate that the graphene edges can be cleaned of Si atoms and then subsequently replenished from nearby source material. It is also shown how Si edge atoms may be “pushed” from the edge of a small hole into the bulk of the graphene lattice and from the bulk of the lattice back to the edge. This is accomplished through sputtering of the edge of the graphene lattice to bury or uncover Si dopant atoms. Finally, we demonstrate e-beam mediated hole healing and incorporation of dopant atoms. These experiments form an initial step toward general atomic-scale material control.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Smart sensors using artificial intelligence for on-detector electronics and ASICs

Cutting edge detectors push sensing technology by further improving spatial and temporal resolution, increasing detector area and volume, and generally reducing backgrounds and noise. This has led to a explosion of more and more data being generated in next-generation experiments. Therefore, the need for near-sensor, at the data source, processing with more powerful algorithms is becoming increasingly important to more efficiently capture the right experimental data, reduce downstream system complexity, and enable faster and lower-power feedback loops. In this paper, we discuss the motivations and potential applications for on-detector AI. Furthermore, the unique requirements of particle physics can uniquely drive the development of novel AI hardware and design tools. We describe existing modern work for particle physics in this area. Finally, we outline a number of areas of opportunity where we can advance machine learning techniques, codesign workflows, and future microelectronics technologies which will accelerate design, performance, and implementations for next generation experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Evaluating Support for OpenMP Offload Features

The OpenMP language features have been evolving to meet the rapid development in hardware platforms. DOE applications tend to push the bleeding edge of features ratified in the OpenMP specification and tend to expose the rough edges of the features' implementations. The software harness on DOE supercomputers such as Titan and (upcoming) Summit include Cray, Clang, Flang, XL and GCC compilers. It is critical, especially for Summit, that the compilers support OpenMP offloading features. This paper focuses on evaluating support for OpenMP 4.5 target offload directives across compiler implementations on Titan and Summitdev, an early access system, which is one generation removed from Summit's architecture enabling application teams to test the systems' architecture. Our tests not only evaluate the OpenMP implementations but also expose ambiguities in the OpenMP 4.5 specification. We also evaluate compiler implementations using kernels extracted from production DOE applications. This helps in assessing the interaction of different OpenMP directives independent of other application artifacts. We are aware that the implementations are constantly evolving and are advertised as having only partial OpenMP 4.x support. We see this as a synergistic effort to help identify and correct features that are required by DOE applications and prevent deployment delays later on. Going forward, we also plan to interact with standard benchmarking bodies like SPEC/HPG to donate our tests and mini-apps/kernels for potential inclusion in the next release versions of SPEC OMP and SPEC ACCEL benchmark suites.

Monsalve Diaz, Jose↗
DOE OSTI2018

Examination of Shipping Package 9975-04194

In December 2017, K-Area personnel attempted to open package 9975-04194 to remove its contents. The upper fiberboard assembly could not be initially removed due to an interference fit that had developed against the lead shield. Corrosion of the shield created two specific conditions that caused this interference. First, there was widespread heavy blisters over the shield surface. Corrosion of the lead under the surface (associated with porosity in the as-cast shield which is open to the surface) appears to have caused the blisters to form. Second, corrosion also formed in a gap between the lead shield and the internal stainless steel liner, pushing the top edge of the shield outward into the upper fiberboard assembly. In both cases, portions of the shield are pushed outward since the corrosion product occupies a greater volume than the metallic lead it replaced.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

A Multidimensional Operando Study Showing the Importance of the Electrode Macrostructure in Lithium Sulfur Batteries

Lithium sulfur batteries are one of the most promising next-generation energy storage technologies, because of their impressive theoretical energy density, low materials cost, and relative safety. However, incomplete understanding of their underlying operation mechanisms has hindered their further development and commercialization. In this work, to gain a better understanding of the operation mechanisms in the lithium sulfur battery, three macroscopically different (woven and nonwoven) and microscopically similar (made from the same carbon fibers) free-standing carbon felts are used as the conductive matrices to show how the macrostructure influences the redox reactions and the electrochemical performance. Additionally, an operando radiography and simultaneous in situ electrochemical impedance spectroscopy study are performed to highlight the differences of the carbon hosts and how they compare electrochemically in a lithium sulfur battery. The electrochemical results show that the carbon host with a more open structure results in increased capacity as well as a higher diffusion coefficient. The operando radiography shows that the open structures are more conducive to efficient redox reactivity in forming solid sulfur species, mostly in the form of elongated needlelike structures identified as β-S8, near the end of charge, which is corroborated by the impedance data. The data also reveal a “breathing” mechanism, where the polysulfides are pushed to the edges during discharge and pulled back during charge. Furthermore, it is also revealed that the “breathing” process is a limiting factor in the high rate performance. Overall, this study shows that there is a close relationship between the macrostructure of the carbon matrix and the electrochemical performance of the sulfur cathode.

25 ENERGY STORAGE↗
DOE OSTI2023

Layered metals as polarized transparent conductors

The quest to improve transparent conductors balances two key goals: increasing electrical conductivity and increasing optical transparency. To improve both simultaneously is hindered by the physical limitation that good metals with high electrical conductivity have large carrier densities that push the plasma edge into the ultra-violet range. Technological solutions reflect this trade-off, achieving the desired transparencies only by reducing the conductor thickness or carrier density at the expense of a lower conductance. Here we demonstrate that highly anisotropic crystalline conductors offer an alternative solution, avoiding this compromise by separating the directions of conduction and transmission. We demonstrate that slabs of the layered oxides Sr 2 RuO 4 and Tl 2 Ba 2 CuO 6+δ are optically transparent even at macroscopic thicknesses >2 μm for c-axis polarized light. Underlying this observation is the fabrication of out-of-plane slabs by focused ion beam milling. This work provides a glimpse into future technologies, such as highly polarized and addressable optical screens.

36 MATERIALS SCIENCE↗
DOE OSTI2022

In situ detection of RF breakdown on microfabricated surface ion traps

We report microfabricated surface ion traps are a principal component of many ion-based quantum information science platforms. The operational parameters of these devices are pushed to the edge of their physical capabilities as the experiments strive for increasing performance. When the applied radio-frequency (RF) voltage is increased excessively, the devices can experience damaging electric discharge events known as RF breakdown. We introduce two novel techniques for in situ detection of RF breakdown, which we implemented while characterizing the breakdown threshold of surface ion traps produced at Sandia National Laboratories. In these traps, breakdown did not always occur immediately after increasing the RF voltage, but often minutes or even hours later. This result is surprising in the context of the suggested mechanisms for RF breakdown in vacuum. Additionally, the extent of visible damage caused by breakdown events increased with the applied voltage. To minimize the probability for damage when RF power is first applied to a device, our results strongly suggest that the voltage should be ramped up over the course of several hours and monitored for breakdown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Self-consistent dispersal puts tight constraints on the spatiotemporal organization of species-rich metacommunities

Dispersal can be critical to the maintenance of ecosystems as it allows local communities to be recolonized after extinction. However, it remains unclear whether the extinction-mitigating effect of dispersal persists when the number of competing species is large. Based on a spatially explicit mathematical description of metacommunities, we show that when many species coexist, each species operates near its extinction threshold, barely surviving due to dispersal. This has general consequences for spatiotemporal abundance patterns. For short-range dispersal, species organize into fractal spatiotemporal extinction patterns characteristic of a directed percolation phase transition. As species approach their extinction threshold, biodiversity is very sensitive to perturbation, suggesting that dispersal within a metacommunity puts tight constraints on the robustness and evolution of species-rich metacommunities. Biodiversity is often attributed to a dynamic equilibrium between the immigration and extinction of species. This equilibrium forms a common basis for studying ecosystem assembly from a static reservoir of migrants—the mainland. Yet, natural ecosystems often consist of many coupled communities (i.e., metacommunities), and migration occurs between these communities. The pool of migrants then depends on what is sustained in the ecosystem, which, in turn, depends on the dynamic migrant pool. This chicken-and-egg problem of survival and dispersal is poorly understood in communities of many competing species, except for the neutral case—the “unified neutral theory of biodiversity.” Employing spatiotemporal simulations and mean-field analyses, we show that self-consistent dispersal puts rather tight constraints on the dynamic migration–extinction equilibrium. When the number of species is large, species are pushed to the edge of their global extinction, even when competition is weak. As a consequence, the overall diversity is highly sensitive to perturbations in demographic parameters, including growth and dispersal rates. When dispersal is short range, the resulting spatiotemporal abundance patterns follow broad scale-free distributions that correspond to a directed percolation phase transition. The qualitative agreement of our results for short-range and long-range dispersal suggests that this self-organization process is a general property of species-rich metacommunities. Our study shows that self-sustaining metacommunities are highly sensitive to environmental change and provides insights into how biodiversity can be rescued and maintained.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Development of Integrated Biomimetic Framework with Intelligent Monitoring, Cognition and Decision Capabilities for Control of Advanced Energy Plants

The objective of the project entitled “Development of Integrated Biomimetic Framework with Intelligent Monitoring, Cognition, and Decision Capabilities for Control of Advanced Energy Plants” is to develop algorithms and methodologies for designing a biomimetic control system for optimal control of advanced energy plants. Traditionally, control systems have been designed based on assumed a priori knowledge of the process system. A number of variables are manipulated to accomplish disturbance rejection and/or servo control performance. While it is possible to adapt the process model based on available data, the control structure and the controllers rarely change. Thus, the knowledge learnt during process operation is lost or remains underutilized. In addition, the business models of today, especially for power plants, are rapidly changing. The power plant operators are being pushed to the edge due to the penetration of renewable energy derived power to the grid, the demand for high efficiency, ever-tightening environmental regulations, and requirements for increased plant availability. Thus, power plant operations need to be agile and should adapt quickly to the dynamic requirements. A number of characteristics distinguish biological systems from the traditional process control systems. Self-organization, distributed intelligence, adaptability, intelligent monitoring, cognition, and decision capabilities are some of the powerful characteristics of the biological world that can be effectively utilized in process control. At the top, the central nervous system (CNS) integrates the information from and coordinates the activities of all parts of the bodies (for bilaterian animals). Inspired by these distinct characteristics, this project seeks to develop methodologies and algorithms to accomplish: (i) self-organization of the control structure for maximizing the plant’s operating profit by mimicking the function of the cortical areas in the human brain, (ii) distributed and adaptive controllers that mimic the rule of pursuit present in ants, (iii) intelligent monitoring of the controllers powered with cognition and decision capabilities that mimic the artificial immune systems, and (iv) seamless coordination and integration in the control system that mimics the CNS.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Data Fusion to Enhance Quality Control and Analysis with Instruments at the Marine and Coastal Research Laboratory

Deploying environmental monitoring instruments in the marine environment can be challenging, facing challenges around device survivability, biofouling and corrosion, and consistent data collection. This project explores the use of data fusion – the process of integrating multiple data sources to produce more consistent, accurate, and useful information – to build a consistent long-term monitoring system at the Marine and Coastal Research Laboratory (MCRL) in Sequim, Washington. Unused instruments that had been acquired from past projects were inventoried and deployments planned on the MCRL pier and floating dock. A total of 8 instruments were deployed including a tide gauge, hydrophone, acoustic Doppler current profiler (ADCP), photosynthetically active radiation (PAR) sensors, meteorological station, and three water quality sensors. Deployments were planned to be well-protected around the pier structure and a maintenance schedule was created for cleaning and recalibration. An automated data pipeline was created to aggregate data on edge computers that push data to Amazon Web Services (AWS) cloud storage every 15 minutes, performing automated quality control and data transformations using the Time Series Data Analytical Toolkit (TSDAT). Continued efforts are underway to maintain this system into the future, take a data-driven approach to maintenance scheduling, improve the reliability of the system, and share the data with a variety of end-users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Using Thermosyphon Hybrid Cooling System to Optimize Data Center Water Efficiency

Driven by a mission to push the leading edge for data center sustainability, NREL recognized the need to make its data center not just energy efficient, but water efficient, too. So, in 2016, NREL, with partners Johnson Controls and Sandia National Laboratories, deployed an innovative thermosyphon cooler (TSC) as a test bed on the roof of the NREL's Energy Systems Integration Facility (ESIF). In combination with existing evaporative towers, the TSC forms an extremely water-and cost-efficient hybrid cooling system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Measurement and applications: Exploring the challenges and opportunities of hierarchical federated learning in sensor applications

Sensor applications have become ubiquitous in modern society as the digital age continues to advance. AI-based techniques (e.g., machine learning) are effective at extracting actionable information from large amounts of data. An example would be an automated water irrigation system that uses AI-based techniques on soil quality data to decide how to best distribute water. However, these AI-based techniques are costly in terms of hardware resources, and Internet-of-Things (IoT) sensors are resource-constrained with respect to processing power, energy, and storage capacity. These limitations can compromise the security, performance, and reliability of sensor-driven applications. To address these concerns, cloud computing services can be used by sensor applications for data storage and processing. Unfortunately, cloud-based sensor applications that require real-time processing, such as medical applications (e.g., fall detection and stroke prediction), are vulnerable to issues such as network latency due to the sparse and unreliable networks between the sensor nodes and the cloud server [1]. As users approach the edge of the communications network, latency issues become more severe and frequent. A promising alternative is edge computing, which provides cloud-like capabilities at the edge of the network by pushing storage and processing capabilities from centralized nodes to edge devices that are closer to where the data are gathered, resulting in reduced network delays [2], [3].

Po-Leen Ooi, Melanie↗
DOE OSTI2022

The leaf economics spectrum of triploid and tetraploid C 4 grass Miscanthus x giganteus

Abstract The leaf economics spectrum (LES) describes multivariate correlations in leaf structural, physiological and chemical traits, originally based on diverse C 3 species grown under natural ecosystems. However, the specific contribution of C 4 species to the global LES is studied less widely. C 4 species have a CO 2 concentrating mechanism which drives high rates of photosynthesis and improves resource use efficiency, thus potentially pushing them towards the edge of the LES. Here, we measured foliage morphology, structure, photosynthesis, and nutrient content for hundreds of genotypes of the C 4 grass Miscanthus × giganteus grown in two common gardens over two seasons. We show substantial trait variations across M .× giganteus genotypes and robust genotypic trait relationships. Compared to the global LES, M .× giganteus genotypes had higher photosynthetic rates, lower stomatal conductance, and less nitrogen content, indicating greater water and photosynthetic nitrogen use efficiency in the C 4 species. Additionally, tetraploid genotypes produced thicker leaves with greater leaf mass per area and lower leaf density than triploid genotypes. By expanding the LES relationships across C 3 species to include C 4 crops, these findings highlight that M .× giganteus occupies the boundary of the global LES and suggest the potential for ploidy to alter LES traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Data for The Leaf Economics Spectrum of Triploid and Tetraploid C4 Grass Miscanthus x giganteus

The leaf economics spectrum (LES) describes multivariate correlations in leaf structural, physiological and chemical traits, originally based on diverse C3 species grown under natural ecosystems. However, the specific contribution of C4 species to the global LES is studied less widely. C4 species have a CO2 concentrating mechanism which drives high rates of photosynthesis and improves resource use efficiency, thus potentially pushing them towards the edge of the LES. Here, we measured foliage morphology, structure, photosynthesis, and nutrient content for hundreds of genotypes of the C4 grass Miscanthus × giganteus grown in two common gardens over two seasons. We show substantial trait variations across M. × giganteus genotypes and robust genotypic trait relationships. Compared to the global LES, M. × giganteus genotypes had higher photosynthetic rates, lower stomatal conductance, and less nitrogen content, indicating greater water and photosynthetic nitrogen use efficiency in the C4 species. Additionally, tetraploid genotypes produced thicker leaves with greater leaf mass per area and lower leaf density than triploid genotypes. By expanding the LES relationships across C3 species to include C4 crops, these findings highlight that M. × giganteus occupies the boundary of the global LES and suggest the potential for ploidy to alter LES traits.

Biomass Analytics↗
DOE OSTI2020

The performance evaluation of direct detection electron energy-loss spectroscopy at 200 kV and 80 kV accelerating voltages

Direct electron detectors (DeDs) have been widely used for imaging studies because of their higher beam sensitivity, lower noise, improved pixel resolution, etc. However, there have been limited studies related to the performance in spectroscopic applications for the direct electron detection. Hereby, taking the advantage of the DeD installed on a high-performance electron energy-loss spectrometer, we systematically studied the performance of a DeD (Gatan's K2 IS) fitted on an aberration-corrected transmission electron microscope (TEM) equipped with an electron monochromator. Using SrTiO3 as the model system, the point spread function in the zero-loss region of the spectrum and the performance for core loss spectroscopy have been investigated under both 200 kV and 80 kV operating conditions. We demonstrate that the K2 detector can achieve an overall better performance at 200 kV than a charge coupled device (CCD) detector. At 80 kV, the K2 DeD is still better than a CCD, except for the relative broad tails of the zero-loss peak. The signal-to-noise ratio is very close for DeD and CCD under 80 kV. Based on our data obtained at different operating voltages, it is clear that DeD will benefit the microscopy community and boost the development of cutting-edge materials science studies by pushing the frontiers in electron energy-loss spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Gyrokinetic GENE simulations of DIII-D near-edge L-mode plasmas

We present gyrokinetic simulations with the GENE code addressing the near-edge region of an L-mode plasma in the DIII-D tokamak. At radial position ρ = 0.80, simulations with the ion temperature gradient (ITG) increased by 40% above the nominal value give electron and ion heat fluxes that are in simultaneous agreement with the experiment. This gradient increase is consistent with the combined statistical and systematic uncertainty σ of the charge exchange recombination spectroscopy measurements at the 1.6σ level. Multiscale simulations are carried out with a realistic mass ratio and geometry for the first time in the near-edge. These multiscale simulations suggest that the highly unstable ion temperature gradient (ITG) modes of the flux-matched ion-scale simulations suppress electron-scale transport, such that ion-scale simulations are sufficient at this location. At radial position ρ = 0.90, nonlinear simulations show a hybrid state of ITG and trapped electron modes, which was not expected from linear simulations. The nonlinear simulations reproduce the total experimental heat flux with the inclusion of E × B shear effects and an increase in the electron temperature gradient by ∼23%. This gradient increase is compatible with the combined statistical and systematic uncertainty of the Thomson scattering data at the 1.3σ level. These results are consistent with previous findings that gyrokinetic simulations are able to reproduce the experimental heat fluxes by varying input parameters close to their experimental uncertainties, pushing the validation frontier closer to the edge region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Tightest Mixed-Integer Programming Formulations for Quadratic SCUC Optimization

In this project, we developed new, tighter Mixed-Integer Programming (MIP) formulations for the combined Alternating Current (AC) Security-Constrained Unit Commitment (SCUC) and Security-Constrained Optimal Power Flow (SCOPF). The work addresses a critical challenge in power system operations: efficiently determining which generation units to commit and how to optimally dispatch them while maintaining network reliability constraints for both normal and contingency scenarios. Our efforts: 1. Advance the Understanding of SCUC/SCOPF Modeling: By introducing tighter MIP formulations and leveraging cutting-edge optimization tools (Julia/JuMP, PowerModels.jl), this project has pushed forward the state of the art in efficient power systems scheduling. 2. Enhance Technical and Economic Feasibility: The methods developed provide more accurate and potentially faster solutions to large-scale, realistic scheduling and dispatch problems in electric power systems, which can translate into improved reliability and potentially lower costs for grid operations. 3. Benefit to the Public: Greater efficiency in power system operations leads to cost savings for utilities and end-users. Improved reliability and integration of advanced modeling approaches can facilitate the adoption of clean energy resources and better accommodate uncertainties in renewable generation. Because this technology could impact bulk power markets and reliability, these innovations have far-reaching public benefits in terms of cost savings, reliability, and sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗