Search NASA⌕ Search

SEARCH · Search NASA

Results for “three component”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Simultaneous Separation of Protactinium-230 and Uranium-230 Isotopes from a Proton-Irradiated Thorium Matrix

The use of radioisotopes in cancer therapy is becoming increasingly important. As a potential candidate for targeted alpha therapy, 230 U (t 1/2 = 20.8 d), the decay daughter of 230 Pa (t 1/2 = 17.4 d) is currently being investigated for cancer treatment. For radioisotopes to be used in biomedicine, they must be radiochemically pure and free from carrier interference. This can be challenging given their short half-life. Thus, in this study, radiological separation methods for harvesting isotopes for use in biomedicine must be simple, fast, and capable of obtaining the required purity levels. Herein, we demonstrate a new rapid method for the separation of 230 U and 230 Pa from a proton-irradiated 232 Th metal target and from coproduced fission products with high recovery and purity. A dual-column approach was used, in which the first column was an anion exchange (AX) column and the second column was a DGA column. The MP-1 AX resin was used for the primary separation of the three major components (U, Pa, and Th, as well as fission products), and the DGA column was used for further purification of the separated 230 U. The method is simple and allows for straightforward separation of U, Pa, Th, and fission products; also, the entire process from target dissolution to shipment of 230 U could be completed in 3 days with an overall 230 U recovery yield of 96 ± 3%. Additionally, separated 230 Pa fractions can be used to harvest ingrown 230 U after initial separation.

DGA resin↗
DOE OSTI2021

Local and Global Sensitivity Analysis of a Reactive Transport Model Simulating Floodplain Redox Cycling

Reactive transport models (RTMs) are essential tools that simulate the coupling of advective, diffusive, and reactive processes in the subsurface, but their complexity makes them difficult to understand, develop and improve without accompanying statistical analyses. Although global sensitivity analysis (SA) can address these issues, the computational cost associated with most global SA techniques limits their use with RTMs. In this study, we apply distance-based generalized sensitivity analysis (DGSA), a novel and computationally efficient method of global SA, to a floodplain-scale RTM and compare DGSA results to those from local SA. Our test case focuses on the impact of 17 uncertain environmental parameters on spatially and temporally variable redox conditions within a floodplain aquifer. The input parameters considered include flow and diffusion rates, geochemical reaction rates, and the spatial distribution of sediment facies. Sensitivity was evaluated for three distinct components of the model response, encompassing both multidimensional and categorical output. Parameter rankings differ between local SA and DGSA, due to nonlinear effects of individual parameters and interaction effects between parameters. DGSA results show that fluid residence time, which is controlled by aquifer permeability, generally exerts a stronger control on redox conditions than do geochemical reaction rates. Sensitivity indices also demonstrate that sulfate reduction is key for establishing and maintaining reducing conditions throughout the aquifer. Furthermore, these results provide insights into the key drivers of heterogeneous redox processes within floodplain aquifers, as well as the main sources of uncertainty when modeling complex subsurface systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An Open‐Source, Physics‐Based, Tropical Cyclone Downscaling Model With Intensity‐Dependent Steering

Abstract An open‐source, physics‐based tropical cyclone (TC) downscaling model is developed, in order to generate a large climatology of TCs. The model is composed of three primary components: (a) a random seeding process that determines genesis, (b) an intensity‐dependent beta‐advection model that determines the track, and (c) a non‐linear differential equation set that determines the intensification rate. The model is entirely forced by the large‐scale environment. Downscaling ERA5 reanalysis data shows that the model is generally able to reproduce observed TC climatology, such as the global seasonal cycle, genesis locations, track density, and lifetime maximum intensity distributions. Inter‐annual variability in TC count and power‐dissipation is also well captured, on both basin‐wide and global scales. Regional TC hazard estimated by this model is also analyzed using return period maps and curves. In particular, the model is able to reasonably capture the observed return period curves of landfall intensity in various sub‐basins around the globe. The incorporation of an intensity‐dependent steering flow is shown to lead to regionally dependent changes in power dissipation and return periods. Advantages and disadvantages of this model, compared to other downscaling models, are also discussed.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Systematic characterization of gene function in the photosynthetic alga Chlamydomonas reinhardtii

Most genes in photosynthetic organisms remain functionally uncharacterized. Here, using a barcoded mutant library of the model eukaryotic alga Chlamydomonas reinhardtii, we determined the phenotypes of more than 58,000 mutants under more than 121 different environmental growth conditions and chemical treatments. A total of 59% of genes are represented by at least one mutant that showed a phenotype, providing clues to the functions of thousands of genes. Mutant phenotypic profiles place uncharacterized genes into functional pathways such as DNA repair, photosynthesis, the CO 2 -concentrating mechanism and ciliogenesis. We illustrate the value of this resource by validating phenotypes and gene functions, including three new components of an actin cytoskeleton defense pathway. The data also inform phenotype discovery in land plants; mutants in Arabidopsis thaliana genes exhibit phenotypes similar to those we observed in their Chlamydomonas homologs. We anticipate that this resource will guide the functional characterization of genes across the tree of life.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

What we know and what we don’t know about the proton spin after 30 years

More than three decades ago, the European Muon Collaboration published a surprising result on the spin structure of the proton: the spins of its three quark components account for only a small part of the spin of the proton. Furthermore, ever since, theoretical and experimental progress has been made in understanding the origins of the proton spin. In this review, we discuss what has been learned so far, what is still missing and what could be learned from the upcoming experiments, including the Jefferson Lab 12GeV upgrade and the proposed Electron-Ion Collider. In particular, we focus on first-principles calculations and experimental measurements of the total gluon helicity ΔG, and the quark and gluon orbital angular momenta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Turbulence-driven flow dynamics in general axisymmetric toroidal geometry

The present work gives the equations governing the generation of toroidally axisymmetric flows by turbulent Reynolds and Maxwell stresses in finite aspect ratio, general cross section tokamak plasmas. Inclusion of the divergence-free flow constraint in lowest order changes the time scale for evolution of the poloidal flows driven by turbulence by substantial factors. In the pedestal region for present day machines, comparing to earlier cylindrical models, the time scale evaluated using a large aspect ratio circular cross section model can be two orders of magnitude longer while the present, general geometry result can be about one order of magnitude longer. Inclusion of gyroviscosity in the calculation shows that the only lowest order radial velocity fluctuations that enter the problem are those due to fluctuating E×B flows. Toroidal and poloidal flow effects on the toroidally axisymmetric flows are inextricably coupled due to the neoclassical poloidal viscosity. Accordingly, the physics is inherently three dimensional and measurements of all three velocity components are required to obtain the information needed to quantitatively test the theory. The parallel and angular momentum equations for the lowest order, toroidally axisymmetric flows look like radial transport equations when the turbulence is included. The turbulence terms provide the radial transport fluxes. In standard neoclassical theory, the parallel flow equation is local on each flux surface; there is no radial derivative term. However, adding turbulence gives a way, in principle, for radial transport to lead to poloidal flows that deviate from the neoclassical prediction. As a result, the inclusion of the Maxwell stress provides a mechanism for MHD fluctuations to alter the toroidally axisymmetric flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Technoeconomic Cost Analysis of NREL Concentrating Solar Power Gen3 Liquid Pathway

The National Renewable Energy Laboratory is leading the liquid (molten salt) power tower pathway for the U.S. Department of Energy's concentrating solar power Gen3 initiative. The Gen3 liquid pathway required updated designs to three major components: the tower and receiver, the thermal energy storage tanks, and the power cycle. We assume a 100 MWe net system output and used the System Advisor Model (SAM) to complete a technoeconomic cost analysis of the Gen3 liquid pathway design and estimate its levelized cost of electricity. This paper summarizes the methodology and results of that analysis.

chloride salt↗
DOE OSTI2022

Ten years of Gulf Coast ecosystem restoration projects since the Deepwater Horizon oil spill

A decade since coastal restoration began across U.S. Gulf of Mexico states after the Deepwater Horizon oil spill, it is timely to examine its collective effects relative to intended outcomes. Through 2021, allocated funds for 570 projects by state, federal, non-profit, and other entities approached half the unprecedented recovery settlements. The need for synthesis of restoration results to inform further expenditures is urgent. Yet, unlike the western and eastern U.S. coasts, this region lacks an entity charged with conducting environmental synthesis. Synthesis of the cumulative effects of large-scale restoration will encompass three challenging components: (1) understanding and accounting for synergistic and antagonistic effects; (2) incorporating long-term environmental trends and acute events; and (3) addressing the relative scale of restoration effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advanced Characterization in Advanced Manufacturing Workshop

The Advanced Manufacturing (AM) Work shop successfully convened experts from government, academia, and industry to address pressing scientific challenges and strengthen the AM user community. The workshop was held at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory during the National Synchrotron Light Source II (NSLS-II) and Center for Functional Nanomaterials (CFN) Users’ Meeting. Participation included researchers from Stony Brook University, Massachusetts Institute of Technology, Yale University, Harvard University, Columbia University, and several other institutions across the United States and the world. In conclusion, the program featured three complementary components—oral presentations, a facility tour, and a brainstorming session— that together fostered collaboration and high lighted the transformative role of synchrotron based characterization in AM.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantitative analysis of cost savings and occupants’ preferences in grid-interactive smart home operation

Many utility companies in the United States have introduced time-of-use (TOU) rates for homeowners with the goal of regulating electricity consumption during peak hours. The electrical appliances in homes include various thermostatically controlled devices, such as air conditioners (AC) for thermal comfort, and nonthermostatically controlled devices such as clothes washers. As a result, homeowners face the complicated challenge of economically operating multiple electrical appliances in their homes while maintaining comfort and convenience. This is usually due to the lack of an explicit understanding of the correlation between cost saving and the users’ comfort. To understand the correlation, this article is designed to construct a framework by integrating three major components: a multi-objective optimization method accommodating multiple competing goals with different weights, a learning-based system modeling approach describing the dynamics and thermal coupling effects of appliances, and a novel comfort index method differentiating preferred and acceptable thermal comfort. Our proposed framework can allow the indoor air temperature to fall into the "preferred" range with a marginal cost increase. Furthermore, the simulation result shows that an additional 8 h for the preferred thermal comfort can be achieved with a cost increase of only 1.77%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Mapping the magnetic field in the Taurus/B211 filamentary cloud with SOFIA HAWC + and comparing with simulation

ABSTRACT Optical and infrared polarization mapping and recent Planck observations of the filametary cloud L1495 in Taurus show that the large-scale magnetic field is approximately perpendicular to the long axis of the cloud. We use the HAWC + polarimeter on SOFIA to probe the complex magnetic field in the B211 part of the cloud. Our results reveal a dispersion of polarization angles of 36°, about five times that measured on a larger scale by Planck. Applying the Davis–Chandrasekhar–Fermi (DCF) method with velocity information obtained from Institut de Radioastronomie Millimétrique 30 m C18O(1-0) observations, we find two distinct sub-regions with magnetic field strengths differing by more than a factor 3. The quieter sub-region is magnetically critical and sub-Alfv$\acute{\rm e}$nic; the field is comparable to the average field measured in molecular clumps based on Zeeman observations. The more chaotic, super-Alfv$\acute{\rm e}$nic sub-region shows at least three velocity components, indicating interaction among multiple substructures. Its field is much less than the average Zeeman field in molecular clumps, suggesting that the DCF value of the field there may be an underestimate. Numerical simulation of filamentary cloud formation shows that filamentary substructures can strongly perturb the magnetic field. DCF and true field values in the simulation are compared. Pre-stellar cores are observed in B211 and are seen in our simulation. The appendices give a derivation of the standard DCF method that allows for a dispersion in polarization angles that is not small, present an alternate derivation of the structure function version of the DCF method, and treat fragmentation of filaments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Comprehensive simulation of heavy-ion collisions at nonzero baryon chemical potential

Here, we present results of hydrodynamic modeling of Au-Au collisions from $\sqrt{s_{NN}}$ = 7.7 to 200 GeV. Our simulations have three novel components. First, we use a Linear EXtrapolation of Ultratrelativistic nucleon-nucleon Scattering to nucleus-nucleus collisions (LEXUS) inspired Monte Carlo initial-state model. Second, we use a crossover equation of state at finite baryon densities without a critical point. Finally, we use departure functions derived from the quasiparticle theory of transport coefficients for hadronic matter at nonzero baryon densities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Transient Optimization of the Cryogenic Moderator System Controller at the Spallation Neutron Source for Improved Performance

The high-energy neutron beam generated at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is moderated to use cold (slow) neutrons for scientific discoveries. The Cryogenic Moderator System (CMS) removes heat from the neutron beam using cryogenic hydrogen (H 2 ) moderators connected via heat exchangers to a helium (He) refrigeration loop that dissipates heat using a compressor-brake system. However, the CMS is affected by sporadic losses in beam power, referred to as "beam trips," as these events generate significant disturbances in cooling requirements. To accommodate the heat load transients during beam trips, the CMS uses a decentralized control strategy consisting of four flow valves and one electric heater adjusted by independent proportional-integral (PI) controllers. During the CMS’s initial commissioning, the PI gains were calibrated based only on tracking performance, overlooking their effectiveness in disturbance rejection. A data-driven, control-oriented closed-loop model was developed to recalibrate the PI gains and minimize the transient disturbances caused by beam trips. The model consists of three main components: (1) a physics-based model of the He refrigeration loop, (2) a machine-learning model of the cryogenic H 2 cooling trains, and (3) the control logic used for feedback set-point tracking. Experimental results showed that the recalibrated gains obtained in this study improved the CMS’s transient response during beam trips.

Maldonado Puente, Bryan↗
DOE OSTI2024

eCC++ : A Compiler Construction Framework for Embedded Domain-Specific Languages

eCC++ is a new compiler construction framework for embedding domain-specific programming languages within C++. That is, the host language is C++, the guest language is the DSL to be embedded in C++, and eCC++ is the tool that enables the embedding. The eCC++ framework is composed of three main components: a front-end, an API for program verification based on a functional and declarative intermediate representation (IR), and a Multi-Level Intermediate Representation (MLIR) code generator. The eCC++ front-end consists of a library of C++ classes and operators that can be used to define the guest language. Guest sources are compiled with any standard C++ compiler, and when run, the resulting executable generates an eCC++ IR representation of the program, which can be verified within the eCC++ framework. Finally, eCC++ allows for high-level and domain-specific optimizations before generating MLIR. In summary, eCC++ aims to act as a generic front-end that enables embedding guest languages into C++, and provides necessary compiler technology for program verification, targeting the existing capabilities in the MLIR infrastructure. The paper evaluates the eCC++ expressiveness and usability describing the process of embedding GraphIt, a high-performance graph language in C++.

Gonzalez Tallada, Marc↗
DOE OSTI2020

An Integrated Platform for Collaborative Data Analytics

While collaboration among data scientists is a key to organizational productivity, data analysts face significant barriers to achieving this end, including data sharing, accessing and configuring the required computational environment, and a unified method of sharing knowledge. Each of these barriers to collaboration is related to the fundamental question of knowledge management “how can organizations use knowledge more effectively?”. In this paper, we consider the problem of knowledge management in collaborative data analytics and present ShareAL, an integrated knowledge management platform, as a solution to that problem. The ShareAL platform consists of three core components: a full stack web application, a dashboard for analyzing streaming data and a High Performance Computing (HPC) cluster for performing real time analysis. Prior research has not applied knowledge management to collaborative analytics or developed a platform with the same capabilities as ShareAL. ShareAL overcomes the barriers data scientists face to collaboration by providing intuitive sharing of data and analytics via the web application, a shared computing environment via the HPC cluster and knowledge sharing and collaboration via a real time messaging application.

Oesch, T↗
DOE OSTI2023

Origin of Soft-Switching Output Capacitance Loss in Cascode GaN HEMTs at High Frequencies

Output capacitance (C OSS ) loss (E DISS ) is produced when the C OSS of a power device is charged and discharged, which ideally should be a lossless process. This loss was recently revealed to be a crucial concern for GaN high electron mobility transistors (HEMTs) in high-frequency soft-switching applications. Among various GaN devices, the composite-type, cascode GaN HEMT was reported to show the largest E DISS with a voltage dependence distinct from discrete GaN HEMTs. However, the physical origins of the EDISS in cascode GaN HEMTs remain unclear. This work fills this gap by identifying three loss components and, for the first time, experimentally quantifying them in the multi-MHz resonant switching. These loss components include a) the avalanche loss of Si MOSFET, b) the intrinsic E DISS of GaN HEMT, and c) the Si avalanche-induced GaN turn-ON loss. The last component was found to dominate E DISS at high voltage. By eliminating the Si avalanche and the associated loss components (a) and (c), the E DISS of cascode GaN HEMTs can be reduced by up to 75% at the price of an increase in output charge and switching transition time. Furthermore, these results provide new physical insights and practical guidelines to trim the soft-switching loss of cascode GaN HEMTs in high-frequency applications.

42 ENGINEERING↗
DOE OSTI2022

Hierarchical Control of Megawatt-Scale Charging Stations for Electric Trucks with Distributed Energy Resources

Electrifying medium- and heavy-duty trucks is critical to decarbonizing the transportation sector. Energy needs of electric trucks will likely require megawatt-scale charging stations, which could significantly stress the electric distribution grid. Distributed energy resources (DER) can alleviate this stress and reduce charging costs with proper management. To that end, this work develops a hierarchical predictive control algorithm for future multi-port megawatt-scale charging stations that can provide real-time energy management for stations, decide charging rates, dispatch energy storage system (ESS), and provide grid voltage support. We integrate three algorithmic components: (i) an energy management optimization (EMO) that provides supervisory control to DER assets and charging loads at minute scale, (ii) a real-time energy management system (RT-EMS) that heuristically compensates for fast disturbances at sub-second scale, and (iii) a model predictive control (MPC)-based battery management system (BMS) that communicates future charging demands to the EMO, to manage the overall megawatt-scale site. Additionally, validation in a controller hardware-in-the-loop (CHIL) environment shows that the hierarchical controller can reduce the total energy consumption from the grid by approximately 28% compared to an uncontrolled case for the station configuration in this paper, without impacting charging time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Reinforcement Learning for Load-balanced Parallel Particle Tracing

We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three novel components: (1) a work donation algorithm, (2) a high-order workload estimation model, and (3) a communication cost model. First, we design an RL-based work donation algorithm. Our algorithm monitors workloads of processes and creates RL agents to donate data blocks and particles from high-workload processes to low-workload processes to minimize program execution time. The agents learn the donation strategy on the fly based on reward and cost functions designed to consider processes' workload changes and data transfer costs of donation actions. Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations. Third, we design a communication cost model that considers both block and particle data exchange costs, helping RL agents make effective decisions with minimized communication costs. We demonstrate that our algorithm adapts to different flow behaviors in large-scale fluid dynamics, ocean, and weather simulation data. Our algorithm improves parallel particle tracing performance in terms of parallel efficiency, load balance, and costs of I/O and communication for evaluations with up to 16,384 processors.

Distributed and parallel particle tracing↗