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NASA NTRS2011

A Model fot the Sources of the Slow Solar Wind

Models for the origin of the slow solar wind must account for two seemingly contradictory observations: the slow wind has the composition of the closed-field corona, implying that it originates from the continuous opening and closing of flux at the boundary between open and closed field. On the other hand, the slow wind also has large angular width, up to approx.60deg, suggesting that its source extends far from the open-closed boundary. We propose a model that can explain both observations. The key idea is that the source of the slow wind at the Sun is a network of narrow (possibly singular) open-field corridors that map to a web of separatrices and quasi-separatrix layers in the heliosphere. We compute analytically the topology of an open-field corridor and show that it produces a quasi-separatrix layer in the heliosphere that extends to angles far from the heliospheric current sheet. We then use an MHD code and MDI/SOHO observations of the photospheric magnetic field to calculate numerically, with high spatial resolution, the quasi-steady solar wind, and magnetic field for a time period preceding the 2008 August 1 total solar eclipse. Our numerical results imply that, at least for this time period, a web of separatrices (which we term an S-web) forms with sufficient density and extent in the heliosphere to account for the observed properties of the slow wind. We discuss the implications of our S-web model for the structure and dynamics of the corona and heliosphere and propose further tests of the model. Key words: solar wind - Sun: corona - Sun: magnetic topology

Antiochos, S. K.↗

NASA NTRS2012

Thermal and Fluid Modeling of the CRYogenic Orbital TEstbed (CRYOTE) Ground Test Article (GTA)

The purpose of this study was to anchor thermal and fluid system models to data acquired from a ground test article (GTA) for the CRYogenic Orbital TEstbed - CRYOTE. To accomplish this analysis, it was broken into four primary tasks. These included model development, pre-test predictions, testing support at Marshall Space Flight Center (MSFC} and post-test correlations. Information from MSFC facilitated the task of refining and correlating the initial models. The primary goal of the modeling/testing/correlating efforts was to characterize heat loads throughout the ground test article. Significant factors impacting the heat loads included radiative environments, multi-layer insulation (MLI) performance, tank fill levels, tank pressures, and even contact conductance coefficients. This paper demonstrates how analytical thermal/fluid networks were established, and it includes supporting rationale for specific thermal responses seen during testing.

Piryk, David↗

NASA NTRS2004

Objective Lightning Forecasting at Kennedy Space Center/Cape Canaveral Air Force Station using Cloud-to-Ground Lightning Surveillance System Data

The 45th Weather Squadron (45 WS) forecasters at Cape Canaveral Air Force Station (CCAFS) in Florida include a probability of thunderstorm occurrence in their daily morning briefings. This information is used by personnel involved in determining the possibility of violating Launch Commit Criteria, evaluating Flight Rules for the Space Shuttle, and daily planning for ground operation activities on Kennedy Space Center (KSC)/CCAFS. Much of the current lightning probability forecast is based on a subjective analysis of model and observational data. The forecasters requested that a lightning probability forecast tool based on statistical analysis of historical warm-season (May - September) data be developed in order to increase the objectivity of the daily thunderstorm probability forecast. The tool is a set of statistical lightning forecast equations that provide a lightning occurrence probability for the day by 1100 UTC (0700 EDT) during the warm season. This study used 15 years (1989-2003) of warm season data to develop the objective forecast equations. The local CCAFS 1000 UTC sounding was used to calculate stability parameters for equation predictors. The Cloud-to-Ground Lightning Surveillance System (CGLSS) data were used to determine lightning occurrence for each day. The CGLSS data have been found to be more reliable indicators of lightning in the area than surface observations through local informal analyses. This work was based on the results from two earlier research projects. Everitt (1999) used surface observations and rawinsonde data to develop logistic regression equations that forecast the daily thunderstorm probability at CCAFS. The Everitt (1999) equations showed an improvement in skill over the Neumann-Pfeffer thunderstorm index (Neumann 1971), which uses multiple linear regression, and also persistence and climatology forecasts. Lericos et al. (2002) developed lightning distributions over the Florida peninsula based on specific flow regimes. The flow regimes were inferred from the average wind direction in the 1000-700 mb layer at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), Florida, and the lightning data were from the National Lightning Detection Network. The results suggested that the daily flow regime may be an important predictor of lightning occurrence on KSC/CCAFS.

Lambert, Winifred↗

NASA NTRS2012

Southern Hemisphere Additional Ozonesondes (SHADOZ) Ozone Climatology (2005-2009): Tropospheric and Tropical Tropopause Layer (TTL) Profiles with Comparisons to Omi-based Ozone Products

We present a regional and seasonal climatology of SHADOZ ozone profiles in the troposphere and tropical tropopause layer (TTL) based on measurements taken during the first five years of Aura, 2005-2009, when new stations joined the network at Hanoi, Vietnam; Hilo, Hawaii; Alajuela Heredia, Costa Rica; Cotonou, Benin. In all, 15 stations operated during that period. A west-to-east progression of decreasing convective influence and increasing pollution leads to distinct tropospheric ozone profiles in three regions: (1) western Pacific eastern Indian Ocean; (2) equatorial Americas (San Cristobal, Alajuela, Paramaribo); (3) Atlantic and Africa. Comparisons in total ozone column from soundings, the Ozone Monitoring Instrument (OMI, on Aura, 2004-) satellite and ground-based instrumentation are presented. Most stations show better agreement with OMI than they did for EPTOMS comparisons (1998-2004; Earth-ProbeTotal Ozone Mapping Spectrometer), partly due to a revised above-burst ozone climatology. Possible station biases in the stratospheric segment of the ozone measurement noted in the first 7 years of SHADOZ ozone profiles are re-examined. High stratospheric bias observed during the TOMS period appears to persist at one station. Comparisons of SHADOZ tropospheric ozone and the daily Trajectory-enhanced Tropospheric Ozone Residual (TTOR) product (based on OMIMLS) show that the satellite-derived column amount averages 25 low. Correlations between TTOR and the SHADOZ sondes are quite good (typical r2 0.5-0.8), however, which may account for why some published residual-based OMI products capture tropospheric interannual variability fairly realistically. On the other hand, no clear explanations emerge for why TTOR-sonde discrepancies vary over a wide range at most SHADOZ sites.

gravity waves↗

NASA NTRS2015

Huygens Crater: Insights into Noachian Volcanism, Stratigraphy, and Aqueous Processes

Huygens crater is a well preserved peak ring structure on Mars centered at 13.5 deg S, 55.5 deg E in the Noachian highlands between Terras Tyrrhena and Sabaea near the NW rim of Hellas basin. With a diameter of approximately 470 km, it uplifted and exhumed pre-Noachian crustal materials from depths greater than 25 km, penetrating below the thick, ubiquitous layer of Hellas ejecta. In addition, Huygens served as a basin for subsequent aqueous activity, including erosion/deposition by fluvial valley networks and subsurface alteration that is now exposed by smaller impacts. Younger mafic-bearing plains that partially cover the basin floor and surrounding intercrater areas were likely emplaced by later volcanism.

Ackiss, S. E.↗

NASA NTRS2018

The Use of MERRA-2 Near Surface Meteorology to Understand the Behavior of Planetary Boundary Layer Heights Derived from Wind Profiler Data over the US Great Plains

The atmospheric general circulation model (GCM) that underlies the MERRA-2 reanalysis includes a suite of physical parameterizations that describe the processes that occur in the planetary boundary layer (PBL). The data assimilation system assures that the atmospheric state variables used as input to these parameterizations are constrained to the best fit to all of the available observations. Many studies, however, have shown that the GCM-based estimates of MERRA-2 PBL heights are biased high, and so are not reliable for boundary layer studies.A 20-year record of PBL heights was derived from Wind Profiler (WP) backscatter data measured at a wide network of stations throughout the US Great Plains and has been validated against independent estimates. The behavior of these PBL heights shows geographical and temporal variations that are difficult to attribute to particular physical processes without additional information that are not part of the observational record.In the present study, we use information on physical processes from MERRA-2 to understand the behavior of the WP derived PBL heights. The behavior of the annual cycle of both MERRA-2 and WP PBL heights shows four classes of behavior: (i) canonical, characterized by a monthly progression in PBL height that follows the solar insolation, (ii) double peak, characterized by canonical behavior that is interrupted by a minimum in July, (iii) late peak, characterized by a suppressed heights in May and June, and return to canonical in July and August, and (iv) early peak where the PBL height rises with solar insolation but is suppressed later in the summer. The explanation for these behaviors and the relationship to local precipitation, temperature, sensible and latent heat fluxes, net radiation and aerosol load is articulated using information from MERRA-2.

Salmun, Haydee↗

NASA NTRS2022

Towards the Development of a Multi-Agent Cognitive Networking System for the Lunar Environment

This paper details the development of a multi-agent cognitive system intended to optimize networking performance in the lunar environment. One concept of the future of lunar communication, LunaNet, outlines a complex network of networks. Challenges such as scalability, interoperability, and reliability must first be addressed to successfully fulfill this vision. Machine intelligence can greatly reduce the reliance on human operators and enable efficient operations for tasks such as scheduling and network management. Machine learning, artificial intelligence, and other automated decision-making techniques can be used to allow network nodes to intelligently sense and adapt to changes in the environment such as link disruptions, new nodes joining the network, and support for a diverse range of protocols. Cognitive networking seeks to evolve these technologies into an autonomous system with improved science data return, reliability, and scalability. In this paper, we study four main areas as a means to further develop cognitive networking capabilities: networking protocol development, analysis of wireless data for modeling and simulation, development of algorithms for a multi-agent system, and spectrum sensing technology.

cognitive networking↗

DOE OSTI2022

Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows

We investigate how to improve new physics detection strategies exploiting variational autoencoders and normalizing flows for anomaly detection at the Large Hadron Collider. As a working example, we consider the DarkMachines challenge dataset. We show how different design choices (e.g., event representations, anomaly score definitions, network architectures) affect the result on specific benchmark new physics models. Once a baseline is established, we discuss how to improve the anomaly detection accuracy by exploiting normalizing flow layers in the latent space of the variational autoencoder.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Efficient solar cells using all-organic nanocrystalline networks

An optoelectronic device and a method of fabricating a photosensitive optoelectronic device includes depositing a first organic semiconductor material on a first electrode to form a continuous first layer; depositing a layer of a second organic semiconductor material on the first layer to form a discontinuous second layer, portions of the first layer remaining exposed; and depositing the first organic semiconductor material on the second layer to form a discontinuous third layer, portions of at least the second layer remaining exposed. The depositing of the first and second organic semiconductor materials are alternated a number of times until a final layer of the second organic material is added to form a continuous layer. A second electrode is deposited over this final layer. One of the first electrode and the second electrode is transparent, and the first organic semiconductor material is one or more donor-type materials or one or more acceptor-type materials relative to second organic semiconductor material, which is one or more materials of the other material type.

Sun, Kai↗

NASA NTRS1992

Application of neural networks to prediction of advanced composite structures mechanical response and behavior

Two types of neural networks were used to evaluate acousto-ultrasonic (AU) data for material characterization and mechanical reponse prediction. The neural networks included a simple feedforward network (backpropagation) and a radial basis functions network. Comparisons of results in terms of accuracy and training time are given. Acousto-ultrasonic (AU) measurements were performed on a series of tensile specimens composed of eight laminated layers of continuous, SiC fiber reinforced Ti-15-3 matrix. The frequency spectrum was dominated by frequencies of longitudinal wave resonance through the thickness of the specimen at the sending transducer. The magnitude of the frequency spectrum of the AU signal was used for calculating a stress-wave factor based on integrating the spectral distribution function and used for comparison with neural networks results.

Cios, K. J.↗

DOE OSTI2023

Roles of Hydrogen Bonds and Alignment in Oriented Attachment of Gibbsite Nanoparticles: Insights from Molecular Dynamics

Oriented attachment (OA) of nanoparticles is an important crystal growth pathway in the synthesis of hierarchical structures. Although a significant understanding of OA has been made, the effect of atomistic misalignment and the roles of solvent/particle and particle/particle interactions on the structure–energy relationship during an OA remain elusive. In this study, we perform molecular dynamics simulations to calculate the potential of mean force (PMF) profile for gibbsite particle translation on a gibbsite slab with 1 or 2 intervening water layers (1W or 2W). The structures of the gibbsite surfaces and the confined water are analyzed to determine how the number and type of hydrogen bonds (H-bonds) influence the free energy profile during the translation. The PMF profile exhibits a periodicity of length 5.078 Å, consistent with the gibbsite unit cell size along the translation direction. The changes in the surface–water and water–water hydrogen bond network and water and surface OH groups’ orientations during the translation are strongly coupled with the changes in the PMF profile in the 1W case. However, when increasing the number of intervening water layers from 1W to 2W, the particle/slab misalignment becomes a dominant factor controlling the behavior of the PMF profile. We also establish a method to quantify misalignment between the particle and the slab, which exhibits a strong correlation with the free energy for the 2W case. These results shed more light into the roles of particle/slab misalignment and hydrogen bond network in the OA of mineral particles in aqueous solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2011

Interplanetary Overlay Network Bundle Protocol Implementation

The Interplanetary Overlay Network (ION) system's BP package, an implementation of the Delay-Tolerant Networking (DTN) Bundle Protocol (BP) and supporting services, has been specifically designed to be suitable for use on deep-space robotic vehicles. Although the ION BP implementation is unique in its use of zero-copy objects for high performance, and in its use of resource-sensitive rate control, it is fully interoperable with other implementations of the BP specification (Internet RFC 5050). The ION BP implementation is built using the same software infrastructure that underlies the implementation of the CCSDS (Consultative Committee for Space Data Systems) File Delivery Protocol (CFDP) built into the flight software of Deep Impact. It is designed to minimize resource consumption, while maximizing operational robustness. For example, no dynamic allocation of system memory is required. Like all the other ION packages, ION's BP implementation is designed to port readily between Linux and Solaris (for easy development and for ground system operations) and VxWorks (for flight systems operations). The exact same source code is exercised in both environments. Initially included in the ION BP implementations are the following: libraries of functions used in constructing bundle forwarders and convergence-layer (CL) input and output adapters; a simple prototype bundle forwarder and associated CL adapters designed to run over an IPbased local area network; administrative tools for managing a simple DTN infrastructure built from these components; a background daemon process that silently destroys bundles whose time-to-live intervals have expired; a library of functions exposed to applications, enabling them to issue and receive data encapsulated in DTN bundles; and some simple applications that can be used for system checkout and benchmarking.

Burleigh, Scott C.↗

DOE OSTI2022

UAV remote sensing imagery - Miscanthus trials 2020 - Energy Farm - UIUC

Aerial imagery utilized as input in the manuscript "Deep convolutional neural networks exploit high spatial and temporal resolution aerial imagery to predict key traits in miscanthus" . Data was collected over M. Sacchariflorus and Sinensis breeding trials at the Energy Farm, UIUC in 2020. Flights were performed using a DJI M600 mounted with a Micasense Rededge multispectral sensor at 20 m altitude around solar noon. Imagery is available as tif file by field trial and date (10). The post-processing of raw images into orthophoto was performed in Agisoft Metashape software. Each crop surface model and multispectral orthophoto was stacked into an unique raster stack by date and uploaded here. Each raster stack includes 6 layers in the following order: Layer 1 = crop surface model, Layer 2 = Blue, Layer 3 = Green, Layer 4 = Red, Layer 5 = Rededge, and Layer 6 = NIR multispectral bands. Msa raster stacks were resampled to 1.67 cm spatial resolution and Msi raster stacks were resampled to 1.41 cm spatial resolution to ease their integration into further analysis. 'MMDDYYYY' is the date of data collection, 'MSA' is M. Sacchariflorus trial, 'MSI' is Miscanthus Sinensis trial, 'CSM' is crop surface model layer, and 'MULTSP' are the five multispectral bands.

bioenergy↗

DOE OSTI2024

Complex multicomponent spectrum analysis with Deep Neural Network

Here, in this paper, we present the use of deep neural networks to estimate physical parameters from complex optical emission spectra of the D β /H β transition. Specifically, we focus on estimating the radio frequency electric field vector of the lower hybrid wave and isotope ratio within the scrape-off-layer plasma of the WEST tokamak. Fitting the spectral data using a traditional non-linear least squares analysis requires many free parameters and is computationally expensive, rendering the data unusable for real-time control. By implementing relatively small neural networks, the physical parameters can be directly extracted from the spectral data with reasonable accuracy in a few milliseconds. The deep neural network prediction can serve as input for a reduced model using least-squares fitting or for real-time control. We show that deep neural networks can be an effective tool for analyzing complex multicomponent spectra, providing a speedup of more than 10 5 times compared to least residual analysis, with an accuracy of 0.5% for the isotope ratio, and 0.09 kV/cm and 0.38 kV/cm for the RF radial and poloidal electric field respectively.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

AOI-2, A Novel Access Control Blockchain Paradigm for Cybersecure Sensor Infrastructure in Fossil Power Generation Systems

Fossil power generation systems are increasingly vulnerable to attack from both cybercriminals as well as internal threats. These vulnerabilities demand that emerging technologies such as blockchains be utilized to secure the data involved in the information flows within the Supervisory Control and Data Acquisition (SCADA) systems of the fossil power generation plants. The publicly accessible blockchain protocols, although secure, are visible to everyone. Even private blockchains currently are unable to support different levels of access to different participants, which is a critical requirement for the existing SCADA systems running the power plants. In light of the above, novel blockchain protocols that are specifically adapted to fossil power generation environments need to be developed in order to achieve the goal of cybersecure sensor networks. In this work, we address this question by creating a novel blockchain technology, namely smart private ledger, for cybersecure communication within the fossil power generation systems. A lab-scale sensor network consisting of strain and temperature sensors is constructed to develop the ledger. The technology has hierarchical access control which is compatible with the existing SCADA systems in fossil power plants. The sensor data is used with cryptographic digital signatures and secret sharing protocols within the nodes of the blockchain technology. The research results will lead to cybersecurity for machine-to-machine interactions, infrastructure for secure data logging for sensors, decentralized data storage, and second-layer technologies for high volume machine-to-machine interactions in the power plants. The work aims to largely address the concerns for the security of distributed sensor networks in such systems that can be compromised by insider threats and by cybercriminals. The research has led to the training of the next generation of engineers and scientists in the important areas of sensor engineering and blockchain technology.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS2012

An Integrated, Layered-Spinel Composite Cathode for Energy Storage Applications

At low operating temperatures, commercially available electrode materials for lithium-ion batteries do not fully meet the energy and power requirements for NASA fs exploration activities. The composite cathode under development is projected to provide the required energy and power densities at low temperatures and its usage will considerably reduce the overall volume and weight of the battery pack. The newly developed composite electrode material can provide superior electrochemical performance relative to a commercially available lithium cobalt system. One advantage of using a composite cathode is its higher energy density, which can lead to smaller and lighter battery packs. In the current program, different series of layered-spinel composite materials with at least two different systems in an integrated structure were synthesized, and the volumetric and gravimetric energy densities were evaluated. In an integrated network of a composite electrode, the effect of the combined structures is to enhance the capacity and power capabilities of the material to levels greater than what is possible in current state-of-the-art cathode systems. The main objective of the current program is to implement a novel cathode material that meets NASA fs low temperature energy density requirements. An important feature of the composite cathode is that it has at least two components (e.g., layered and spinel) that are structurally integrated. The layered material by itself is electrochemically inactive; however, upon structural integration with a spinel material, the layered material can be electrochemically activated, thereby delivering a large amount of energy with stable cycling. A key aspect of the innovation has been the development of a scalable process to produce submicronand micron-scale particles of these composite materials. An additional advantage of using such a composite electrode material is its low irreversible loss (.5%), which is primarily due to the unique activation of the composite. High columbic efficiency (greater than 99%) upon cycling may indicate the formation of a stable SEI (solid-electrolyte interface) layer, which can contribute to long cycle life. The innovation in the current program, when further developed, will enable the system to maintain high energy and power densities at low temperatures, improve efficiency, and further stabilize and enhance the safety of the cell.

Hagh, Nader↗

NASA NTRS2023

A Methodology for Estimating the Energy and Moisture Budget of the Convective Boundary Layer Using Continuous Ground-Based Infrared Spectrometer Observations

Land-atmosphere interactions play a critical role in both the atmospheric water and energy cycles. Changes in soil moisture and vegetation alter the partitioning of surface water and energy fluxes, influencing diurnal evolution of the planetary boundary layer (PBL). The mixing diagram framework has proven useful in understanding the evolution of the heat and moisture budget within the convective boundary layer (CBL). We demonstrate that observations from the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site provide all of the needed inputs needed for the mixing diagram framework, allowing us to quantify the impact from the surface fluxes, advection, radiative heating, encroachment, and entrainment on the evolution of the CBL. Profiles of temperature and humidity retrieved from the ground-based infrared spectrometer (called the Atmospheric Emitted Radiance Interferometer, or AERI) are a critical component in this analysis. Large eddy simulation results demonstrate that mean mixed-layer values derived are shown to be critical to close the energy and moisture budgets. A novel approach demonstrated here is the use of network of AERIs and Doppler lidars to quantify the advective fluxes of heat and moisture. The framework enables the estimation of the entrainment fluxes as a residual, providing a way to observe the entrainment fluxes without using multiple lidar systems. Finally, the high temporal resolution of the AERI observations enable the morning, midday, and afternoon evolution of the CBL to be quantified. This work provides a new way to use observations in this framework to evaluate weather and climate models.

Boundary layer↗

DOE OSTI2023

Quantum paramagnetism in a non-Kramers rare-earth oxide: Monoclinic Pr 2 Ti 2 O 7

Little is so far known about the magnetism of the A 2 B 2 O 7 monoclinic layered perovskites that replace the spin-ice supporting pyrochlore structure for r A /r B > 1.78. We show that high quality monoclinic Pr 2 Ti 2 O 7 single crystals with a three-dimensional network of non-Kramers Pr 3+ ions that interact through edge-sharing superexchange interactions, form a singlet ground-state quantum paramagnet that does not undergo any magnetic phase transitions down to, at least, 1.8 K. The chemical phase stability, structure, and magnetic properties of the layered perovskite Pr 2 Ti 2 O 7 were investigated using x-ray diffraction, transmission electron microscopy, and magnetization measurements. Synthesis of polycrystalline samples with the nominal compositions of Pr 2 Ti 2+x O 7 (–0.16 ≤ x ≤ 0.16 ) showed that deviations from the Pr 2 Ti 2 O 7 stoichiometry lead to secondary phases of related structures including the perovskite phase Pr 2/3 TiO 3 and the orthorhombic phases Pr 4 Ti 9 O 24 and Pr 2 TiO 5 . No indications of site disordering (stuffing and antistuffing) or vacancy defects were observed in the Pr 2 Ti 2 O 7 majority phase. A procedure for growth of high-structural-quality stoichiometric single crystals of Pr 2 Ti 2 O 7 by the traveling solvent floating zone method is reported. Thermomagnetic measurements of single-crystalline Pr 2 Ti 2 O 7 reveal an isolated singlet ground state that we associate with the low-symmetry crystal electric-field environments that split the (2J + 1 = 9)-fold degenerate spin-orbital multiplets of the four differently coordinated Pr 3+ ions into 36 isolated singlets resulting in an anisotropic temperature-independent van Vleck susceptibility at low T. Here, a small isotropic Curie term is associated with 0.96(2)% noninteracting Pr 4+ impurities.

36 MATERIALS SCIENCE↗