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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Two dimensional topology optimization of heat exchangers with the volume fraction method

We perform a comparison study of two topology optimizations methods applied to the design of a two fluids heat exchanger modeled with a coupled thermal-flow problem. The flow follows an isothermal and incompressible Stokes-Brinkman equation and the heat transfer is governed by a convection-diffusion equation without internal generation and high Peclet number. To keep the two fluid phases separated, we solve two Stokes-Brinkman equations, where the Brinkman term models the other phase as a solid. These two velocity fields are then fed to the heat transfer equation. Our goal is to maximize the enthalpy at the cold outlet while constraining the pressure drop. We first solve the design modeling the solid and fluid phases with a volume fraction variable. A SIMP-like penalization in the Brinkman term drives the optimization to a discrete design. The cost and constraint function derivatives are calculated with the library pyadjoint and the optimization is performed by IPOPT. We present optimized designs in two dimensions and discuss the influence of the parameters.

Beck, VictorA.↗
DOE OSTI2021

Geo Thermal Cloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The project is motivated by the challenges, risks, and costs associated with geothermal exploration and production. Many processes and parameters impacting geothermal conditions are poorly understood. Diverse datasets are available to help characterize subsurface geothermal conditions (public and proprietary; satellite, airborne surveys, vegetation/water sampling, geological, geophysical, etc.). Yet, it is not clear how to properly leverage these datasets for geothermal exploration due to an incomplete understanding of how physical processes impacting subsurface geothermal conditions are represented in these observations. Recent advancements in machine learning (ML) provide great promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. Our goals and work under Phases 1 and 2 (as proposed) of this project address all these needs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Atmospheric Pressure Plasma Deposition of TiO2: A Review

Atmospheric pressure plasma (APP) deposition techniques are useful today because of their simplicity and their time and cost savings, particularly for growth of oxide films. Among the oxide materials, titanium dioxide (TiO2) has a wide range of applications in electronics, solar cells, and photocatalysis, which has made it an extremely popular research topic for decades. Here, we provide an overview of non-thermal APP deposition techniques for TiO2 thin film, some historical background, and some very recent findings and developments. First, we define non-thermal plasma, and then we describe the advantages of APP deposition. In addition, we explain the importance of TiO2 and then describe briefly the three deposition techniques used to date. We also compare the structural, electronic, and optical properties of TiO2 films deposited by different APP methods. Lastly, we examine the status of current research related to the effects of such deposition parameters as plasma power, feed gas, bias voltage, gas flow rate, and substrate temperature on the deposition rate, crystal phase, and other film properties. The examples given cover the most common APP deposition techniques for TiO2 growth to understand their advantages for specific applications. In addition, we discuss the important challenges that APP deposition is facing in this rapidly growing field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

In-situ synchrotron X-ray diffraction of hydroxyapatite-zirconia composite during conventional and flash sintering

Here, we conducted in-situ X-ray diffraction to study the crystalline phase evolution in hydroxyapatite-zirconia composites during both conventional and flash sintering processes. Additionally, we examined the thermal history and microstructure of the composite under these sintering conditions. Despite both sintering methods reaching similar average temperatures, they yielded distinct results in terms of crystalline phase composition and microstructure. In the flash sintered samples, we observed a complete transformation of hydroxyapatite into α- tricalcium phosphate and a complete tetragonal to cubic phase transition in zirconia. Conversely, the conventionally sintered samples remained practically stable. Notably, the flash sintered samples exhibited needle-like microstructures, which were absent in their conventionally sintered counterparts. This divergence suggests that the application of an electric field plays a role in generating athermal effects during the sintering of hydroxyapatite-zirconia composites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Patternable Mesoporous Thin Film Quantum Materials via Block Copolymer Self-Assembly: An Emergent Technology?

Recent developments in quantum materials hold promise for revolutionizing energy and information technologies. The use of soft matter self-assembly, for example, by employing block copolymers (BCPs) as structure directing or templating agents, offers facile pathways toward quantum metamaterials with highly tunable mesostructures via scalable solution processing. Here, we report the preparation of patternable mesoporous niobium carbonitride-type thin film superconductors through spin-coating of a hybrid solution containing an amphiphilic BCP swollen by niobia sol precursors and subsequent thermal processing in combination with photolithography. Spin-coated as-made BCP-niobia hybrid thin films on silicon substrates after optional photolithographic definition are heated in air to produce a porous oxide, and subsequently converted in a multistep process to carbonitrides via treatment with high temperatures in reactive gases including ammonia. Grazing incidence small-angle X-ray scattering suggests the presence of ordered mesostructures in as-made BCP-niobia films without further annealing, consistent with a distorted alternating gyroid morphology that is retained upon thermal treatments. Wide-angle X-ray scattering confirms the synthesis of phase-pure niobium carbonitride nanocrystals with rock-salt lattices within the mesoscale networks. Electrical transport measurements of unpatterned thin films show initial exponential rise in resistivity characteristic of thermal activation in granular systems down to 12.8 K, at which point resistivity drops to zero into a superconducting state. Magnetoresistance measurements determine the superconducting upper critical field to be over 16 T, demonstrating material quality on par with niobium carbonitrides obtained from traditional solid-state synthesis methods. Here. we discuss how such cost-effective and scalable solution-based quantum materials fabrication approaches may be integrated into existing microelectronics processing, promising the emergence of a technology with tremendous academic and industrial potential by combining the capabilities of soft matter self-assembly with quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Stellar populations with MEGARA: The inner regions of NGC 7025

This paper aims to determine the capabilities of the MEGARA spectrograph at the Gran Telescopio Canarias (GTC), which is an optical integral-field unit, for studying stellar populations. We also aim to exploit its combination of high spectral (R ~ 6000, 12 000 and 20 000) and spatial (0.62") resolution within its 12".5 × 11"​​.3 field of view. We do this by analysing the commissioning data of the nearby S0a galaxy NGC 7025. We establish a systematic method through which we can determine the properties of the stellar populations in the observations made with MEGARA, more specifically, within the MEGADES legacy project. For this paper in particular, we determine the properties of the stellar populations of NGC 7025. We used MEGARA observations of galaxy NGC 7025 that were taken during the commissioning phase of the instrument. We applied different approaches to estimate the properties of the stellar populations with the highest possible certainty. In addition to the specific study of NGC 7025 and in the context of the MEGADES survey, we have carried out a number of tests to determine the expected errors (including potential biases) in these star formation history (SFH) derivations as a function of these parameters, namely spectral setup, signal-to-noise ratio, σ, and the SFH itself. All the studies we conduct (both full spectral fitting and absorption line indices) of the stellar populations of NGC 7025 indicate that the stars that form its bulge have supersolar metallicity and considerably old ages (~10 Gyr) in general. Using three different combinations of MEGARA spectral setups, we determined that the bulge of NGC 7025 has smild negative mass-weighted age gradient. For the more detailed SFH, our results indicate that in addition to a rather constant star formation at early epochs, a peak in the formation history of the stars in the bulge is also found 3.5–4.5 Gyr ago. This partly explains the mass-weighted age gradients we measured. The scenario presented in NGC 7025 is that of an isolated galaxy under secular evolution that about 3.5–4.5 Gyr ago likely experienced a minor merger (mass ratio 1/10) that induced an increase in star formation and also perturbed the morphology of its outer disc. In addition to these specific results for NGC 7025, we report different lessons learned for the ongoing exploitation of the MEGADES survey with the GTC, such as the need to obtain combined observations in the LR-B + LR-V setups and a signal-to-noise ratio of at least 20 per Å.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1988

Modelling of SAR polarisation phase difference from trees

The data for polarization phase difference Delta Phi between the HH- and VV-polarized backscattered waves from tree-covered fields were obtained with an airborne synthetic aperture radar at 1.225 GHz. The mean values over tree-covered fields were derived from the images of the phase difference and were examined as a function of incident beam angle from 15 to 55 deg. A theoretical model for simulating these data, based on the electromagnetic wave scatterings from the tree trunk and its branches, both of which are assumed as very long dielectric cylinders was developed. The radius and direction of a tree branch are taken as random variables and are chosen by a Monte Carlo method to encounter the incident waves in producing the scattering events. The Monte Carlo simulated results are in good agreement with the observations within experimental uncertainty.

Mo, Tsan↗
NASA NTRS2002

MAC/GMC Code Enhanced for Coupled Electromagnetothermoelastic Analysis of Smart Composites

Intelligent materials are those that exhibit coupling between their electromagnetic response and their thermomechanical response. This coupling allows smart materials to react mechanically (e.g., an induced displacement) to applied electrical or magnetic fields (for instance). These materials find many important applications in sensors, actuators, and transducers. Recently interest has arisen in the development of smart composites that are formed via the combination of two or more phases, one or more of which is a smart material. To design with and utilize smart composites, designers need theories that predict the coupled smart behavior of these materials from the electromagnetothermoelastic properties of the individual phases. The micromechanics model known as the generalized method of cells (GMC) has recently been extended to provide this important capability. This coupled electromagnetothermoelastic theory has recently been incorporated within NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC). This software package is user friendly and has many additional features that render it useful as a design and analysis tool for composite materials in general, and with its new capabilities, for smart composites as well.

Bednarcyk, Brett A.↗
NASA NTRSDate not supplied

Slosh-Induced Ullage Collapse Validation by Computational Fluid Dynamics and Application to In-space Propellant Dynamics

Ullage collapse predictions made using Computational Fluid Dynamics (CFD) were validated then made for an in-space cryogenic propellant unsettling application. Ullage collapse is the decrease in propellant tank pressure due to cooling of the ullage gas, which can be significant for cryogenic propulsion systems. Vehicles may be developed that are robust to temperature and pressure changes caused by heat leaks, e.g., propellant tanks with high maximum operation pressures, technologies yielding active thermal conditioning, and systems with ample pressurant for conditioning. These methods are robust because additional mass, cost, and complexity are used to address cryogenic fluid management (CFM). As vehicles are optimized for increased payload capacity, tracking of events such as ullage collapse and self-pressurization in tanks will become increasingly important for propellant inventory calculations. Some ullage collapse events can be studied through ground experimentation, but propellant unsettling in and around in-space coast mission phases must be studied in the absence of an acceleration field. Computational Fluid Dynamics is a powerful tool to address this need, enabling prediction of complex physics prior to flight. Validation of the chosen CFD tool and modeling methodology was done using data from a previously conducted subscale slosh-induced ullage collapse ground test performed in part by the Japan Aerospace Exploration Agency (JAXA). A small tank was partially filled with liquid nitrogen and pressurized with gaseous nitrogen at various temperatures. The tank was oscillated laterally to induce high amplitude slosh dynamics resulting in wave breakup. Successful qualitative validation of slosh wave dynamics and quantitative validation of ullage collapse promoted confidence in extending ullage collapse predictions to a flight application. Mechanisms of ullage collapse caused by main engine cutoff while in-space were identified. Both slosh dynamics leading to engine shutdown and body dynamics following shutdown were shown to contribute to propellant unsettling and ullage collapse.

J M Brodnick↗
NASA NTRS2019

Computational Fluid Dynamics Methods Used in the Development of the Space Launch System Liftoff and Transition Lineloads Databases

The objective of this paper is to document the reasoning and trade studies that supported the selection of appropriate tools for constructing aerodynamic lineload databases for the Liftoff and Transition phases of flight for launch vehicles. These decisions were made amid the maturation of an evolving workflow for generating databases on variants of the Space Launch System launch vehicle, with most being based on results from brief developmental studies performed in response to specific, unforeseen challenges that were encountered in analyzing a given configuration. This report is intended to provide a summary of the results and the decision-making processes chronologically over the design cycles of various configurations, starting with isolated free-air bodies for the Block 1 Crew, then the Block 1B Crew and Cargo configurations, and most recently the Block 1B Crew configuration in proximity to the launch tower. The results from these analyses led to the selection of the CREATE-AV Kestrel flowsolver for simulating these problems. The need to accurately capture the expected leeward-wake flow field characteristics required the use of Delayed Detached Eddy Simulation (DDES) method, for which the vorticity magnitude was employed as the solution Adaptive Mesh Refinement (AMR) function over the off-body Cartesian grid region. In addition, the Spalart-Allmaras (SA) model is used to account for the flow turbulence effects.

Ratnayake, Nalin A.↗
DOE OSTI2022

Effects of doping, hydrostatic pressure, and thermal quenching on the phase transitions and magnetocaloric properties in Mn 1– x Co x NiGe

The effects of doping, hydrostatic pressure, and thermal quenching on the phase transitions and magnetocaloric properties of the Mn 1–x Co x NiGe system have been investigated. Cobalt doping on the Mn site shifted the martensitic structural transition toward lower temperature until it was ultimately absent, leaving only a magnetic transition from a ferromagnetic (FM) to a paramagnetic (PM) state in the high-temperature hexagonal phase. Co-occurrence of the magnetic and structural transitions to form a first-order magnetostructural transition (MST) from the FM orthorhombic to the PM hexagonal phase was observed in samples with 0.05 < x < 0.20. An additional antiferromagnetic–ferromagnetic-like transition was observed in the martensite phase for 0.05 < x < 0.10, which gradually vanished with increasing Co concentration (x > 0.10) or magnetic field (H > 0.5 T). The application of external hydrostatic pressure shifted the structural transition to lower temperature until an MST was formed in samples with x = 0.03 and 0.05, inducing large magnetic entropy changes up to –80.3 J kg –1 K –1 (x = 0.03) for a 7-T field change under 10.6-kbar pressure. Similar to the effects of the application of hydrostatic pressure, an MST was formed near room temperature in the sample with x = 0.03 by annealing at high temperature (1200 °C) followed by quenching, resulting in a large magnetic entropy change of –56.2 J kg –1 K –1 . Furthermore, these experimental results show that the application of pressure and thermal quenching, in addition to compositional variations, are effective methods to create magnetostructural transitions in the MnNiGe system, resulting in large magnetocaloric effects.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Intermittent Defect Fluctuations in Oxide Heterostructures

Abstract The heterogeneous nature, local presence, and dynamic evolution of defects typically govern the ionic and electronic properties of a wide variety of functional materials. While the last 50 years have seen considerable efforts into development of new methods to identify the nature of defects in complex materials, such as the perovskite oxides, very little is known about defect dynamics and their influence on the functionality of a material. Here, the discovery of the intermittent behavior of point defects (oxygen vacancies) in oxide heterostructures employing X‐ray photon correlation spectroscopy is reported. Local fluctuations between two ordered phases in strained SrCoO x with different degrees of stability of the oxygen vacancies are observed. Ab‐initio‐informed phase‐field modeling reveals that fluctuations between the competing ordered phases are modulated by the oxygen ion/vacancy interaction energy and epitaxial strain. The results demonstrate how defect dynamics, evidenced by measurement and modeling of their temporal fluctuations, give rise to stochastic properties that now can be fully characterized using coherent X‐rays, coupled for the first time to multiscale modeling in functional complex oxide heterostructures. The study and its findings open new avenues for engineering the dynamical response of functional materials used in neuromorphic and electrochemical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fidelity and entanglement entropy for infinite-order phase transitions

Here, we study the fidelity and the entanglement entropy for the ground states of quantum systems that have infinite-order quantum phase transitions. In particular, we consider the quantum O(2) model with a spin-S truncation, where there is an infinite-order Gaussian (IOG) transition for S = 1 and there are Berezinskii-Kosterlitz-Thouless (BKT) transitions for S ≥ 2. We show that the height of the peak in the fidelity susceptibility (χ F ) converges to a finite thermodynamic value as a power law of 1 / L for the IOG transition and as 1 / ln (L) for BKT transitions. The peak position of χ F resides inside the gapped phase for both the IOG transition and BKT transitions. On the other hand, the derivative of the block entanglement entropy with respect to the coupling constant $S^{'}_{vN}$ has a peak height that diverges as ln 2 (L) for S = 1 and ln 3 (L) for S ≥ 2 and can be used to locate both kinds of transitions accurately. We include higher-order corrections for finite-size scalings and obtain the value of the central charge consistent with c = 1 predicted by conformal field theory. The crossing point of χ F between different system sizes is at the IOG point for S = 1 but is inside the gapped phase for S ≥ 2, while those of $S^{'}_{vN}$ are at the phase-transition points for all S truncations. Our work elaborates on how to use the finite-size scaling of χ F or $S^{'}_{vN}$ to detect infinite-order quantum phase transitions and discusses the efficiency and accuracy of the two methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1985

Corrected sidereal anisotropy for underground moons

Data from underground muon telescopes in New Mexico and Bolivia are analyzed in sidereal time and anti-sidereal time in the rigidity range 20 GV to a few 100's of GV. Using both vertical and north- and south- pointing telescopes in both hemispheres, a latitude range of 70 N to 50 S is covered. It is shown that there is an anti-sidereal variation of the P 1 over 2 type, having opposite phase in the Northern and Southern Hemispheres, and maximum amplitude at mid latitudes. The anti-sidereal data are used to correct the sidereal data, using the Nagashima method (Nagashima, 1984); the resulting corrected sidereal vectors for northern hemisphere telescopes have their sidereal maxima close to 3h sidereal time, in reasonable agreement with sidereal data at higher energies from small air showers. The Nagashima correction also eliminates effects due to the reversal of the Sun's polar magnetic field which show up in the uncorrected sidereal data.

Swinson, D. B.↗
NASA NTRS1986

Large-scale electric fields resulting from magnetic reconnection in the corona

The method of Forbes and Priest (2-D model) is applied to the large two-ribbon flare of July 29, 1973, for which both detailed H observations and magnetic data are available. For this flare the ribbons were long, nearly straight, and parallel to each other, and the 2-D model for the coronal field geometry may be adequate. The temporal profile E(t) is calculated and indicates that reconnection sets in at the beginning of the decay phase. From this time the electric field grows rapidly to a maximum value of about 2 V/cm within just a few minutes. Thereafter it decreases monotonically with time.

Kopp, R. A.↗
NASA NTRS2016

Constructing the 'Best' Reliability Data for the Job - Developing Generic Reliability Data from Alternative Sources Early in a Product's Development Phase

Reliability practitioners advocate getting reliability involved early in a product development process. However, when assigned to estimate or assess the (potential) reliability of a product or system early in the design and development phase, they are faced with lack of reasonable models or methods for useful reliability estimation. Developing specific data is costly and time consuming. Instead, analysts rely on available data to assess reliability. Finding data relevant to the specific use and environment for any project is difficult, if not impossible. Instead, analysts attempt to develop the "best" or composite analog data to support the assessments. Industries, consortia and vendors across many areas have spent decades collecting, analyzing and tabulating fielded item and component reliability performance in terms of observed failures and operational use. This data resource provides a huge compendium of information for potential use, but can also be compartmented by industry, difficult to find out about, access, or manipulate. One method used incorporates processes for reviewing these existing data sources and identifying the available information based on similar equipment, then using that generic data to derive an analog composite. Dissimilarities in equipment descriptions, environment of intended use, quality and even failure modes impact the "best" data incorporated in an analog composite. Once developed, this composite analog data provides a "better" representation of the reliability of the equipment or component. It can be used to support early risk or reliability trade studies, or analytical models to establish the predicted reliability data points. It also establishes a baseline prior that may updated based on test data or observed operational constraints and failures, i.e., using Bayesian techniques. This tutorial presents a descriptive compilation of historical data sources across numerous industries and disciplines, along with examples of contents and data characteristics. It then presents methods for combining failure information from different sources and mathematical use of this data in early reliability estimation and analyses.

Kleinhammer, Roger K.↗
NASA NTRS2018

UAS-Based P-Band Signals of Opportunity for Remote Sensing of Snow and Root Zone Soil Moisture

We have developed the P-band Signals of Opportunity (SoOp) sensor based on the Unmanned Aircraft System (UAS) to remotely sense Snow Water Equivalent (SWE) and Root Zone Soil Moisture (RZSM). The P-band UAS SoOp sensor for Hydrology (UASHydro) would operate on the S2 aircraft developed by Black Swift Technologies for sensing of SWE and RZSM with a spatial resolution of about 10m. Root-zone soil moisture and snow water storage in land are critical parameters of the water cycle. The long-term goal of our development would be to use small UAS to perform regional high resolution observation of two key hydrological measurements to improve the estimation of terrestrial water storage for water management, crop production and forecasts of natural hazard. The UASHydro concept utilizes passive receivers to detect the reflection of strong existing P-band radio signals at the 360-380 MHz band from geostationary Mobile Use Objective System (MUOS) communication satellites launched by the US Navy. The SWE remote sensing measurement principle using the P-band SoOp is based on the propagation delay (or phase change) of radio signals through the snowpack. The time delay of the reflected signal due to the snowpack with respect to snow-free conditions is directly proportional to the snowpack SWE, while the soil moisture can be retrieved from the reflectivity at the P-band frequencies for MUOS. We have been conducting ground-based campaigns to test the instrumentation and data processing methods at the Fraser Experimental Forest in Colorado since February 2016. The field campaign data has provided support to the measurement concept. To install the SoOp technologies on the UAS, a lightweight antenna has been built and interfaces with the S2 built by Black Swift Technologies have been completed. A set of flights have been planned starting April 2018 through the end of 2018 in Colorado.

Elston, Jack↗
DOE OSTI2021

Entanglement and many-body effects in collective neutrino oscillations

Collective neutrino oscillations play a crucial role in transporting lepton flavor in astrophysical settings, such as supernovae, where the neutrino density is large. In this regime, neutrino-neutrino interactions are important and simulations in the mean-field approximation show evidence for collective oscillations occurring at timescales much shorter than those associated with vacuum oscillations. In this work, we study the out-of-equilibrium dynamics of a corresponding spin model using matrix product states and show how collective bipolar oscillations can be triggered by many-body correlations if appropriate initial conditions are present. We find entanglement entropies scaling at most logarithmically in the system size suggesting that classical tensor network methods could be efficient in describing collective neutrino dynamics more generally. These observation provide a clear path forward, not only to increase the accuracy of current simulations, but also to elucidate the mechanism behind collective flavor oscillations without resorting to the mean-field approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗