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At least 451 records · Page 25

NASA InterCenter Collaboration Increases ROI

Funding for National Aeronautics and Space Administration (NASA) space mission operations is tighter than ever in the current environment of federal government deficit reductions. Conventional wisdom would expect this environment to drive increasing competition between NASA centers for the limited available funds. However, recent inter-center activities at the Huntsville Operations Support Center (HOSC) at NASA's Marshall Space Flight Center emphasize collaboration rather than competition and demonstrate the value of partnerships to increase the return on shrinking investments. These efforts cover a variety of activities and potential returns. To facilitate sharing data from test and verification through operations without levying requirements on data format or software tools, the HOSC is working with multiple centers on an evolutionary path toward a distributed data architecture and archive. The approach reduces the required investment by allowing the partners to reuse their existing formats and tools, while facilitating gone ]stop h user visibility into and controlled access to the full complement of data regardless of user or data location. The HOSC is also working on two activities to promote sharing operations implementations and leveraging the experts and expertise across multiple NASA sites. In one, the use of Consultative Committee for Space Data Systems (CCSDS) standards for the message abstraction layer provides an interoperability layer on top of existing ground data system communication architectures. This allows missions to select the most appropriate solutions for their requirements with a minimal investment in rehosting the components in a coherent operational environment. The other emphasizes shared tools and increased remote access to minimize travel for tests and critical activities and reduce the floor space required for a dedicated operations center. This paper summarizes these and other inter-center collaboration activities at the HOSC and the benefits that each can bring, not just to the participants, but to the broader operations community.

Lankford, Kimberly↗

Single-Band and Dual-Band Infrared Detectors

Bias-switchable dual-band infrared detectors and methods of manufacturing such detectors are provided. The infrared detectors are based on a back-to-back heterojunction diode design, where the detector structure consists of, sequentially, a top contact layer, a unipolar hole barrier layer, an absorber layer, a unipolar electron barrier, a second absorber, a second unipolar hole barrier, and a bottom contact layer. In addition, by substantially reducing the width of one of the absorber layers, a single-band infrared detector can also be formed.

Ting, David Z.↗

High Efficiency Submillimeter-Wave Imaging Array

The period of a focal array is limited by the angular sampling and the f number of the system. This fact will limit the efficiency of imaging array systems to around 50%. Recently it been demonstrated that the use of a dielectric layer on top of an array of apertures can improve this efficiency limit. In this paper, we describe a similar structure that improves the efficiency in imaging applications and that it is easy to manufacture due to its compatibility with planar lithographic techniques.

Llombart, Nuria↗

Single-Band and Dual-Band Infrared Detectors

Bias-switchable dual-band infrared detectors and methods of manufacturing such detectors are provided. The infrared detectors are based on a back-to-back heterojunction diode design, where the detector structure consists of, sequentially, a top contact layer, a unipolar hole barrier layer, an absorber layer, a unipolar electron barrier, a second absorber, a second unipolar hole barrier, and a bottom contact layer. In addition, by substantially reducing the width of one of the absorber layers, a single-band infrared detector can also be formed.

Ting, David Z.↗

The Feasibility of Detecting Supercooled Liquid with a Forward-Looking Radiometer

A three-dimensional radiative transfer model is utilized to determine the feasibility of a forward-viewing passive sensor for remotely detecting hazardous icing conditions. Wband ground-based radar simulations show no obvious ability to discriminate a cloud-top supercooled layer; however, the spectra for a forward-viewing passive sensor show a strong signal at two stand-off distances when compared with the clear sky spectrum. Such an instrument would be critical for manned and unmanned aircraft, particularly when size, weight, and power requirements restrict the installation of deicing equipment.

clouds↗

The SkyView Data Model: Handling Heterogeneous Data Using Dynamic Software

The SkyView Virtual Telescope allows users to query over 75 distinct datasets of astronomical imagery including more than 190 distinct surveys. These holdings are extraordinarily diverse ranging over more than 15 orders of magnitude in frequency and5 orders of magnitude in resolution. To accommodate supporting these data, SkyView has developed a simple data model for surveys. Nor surprisingly, given the diverse origins of the datasets included, some surveys do not easily fit within this model. The conventional approach to dealing with such outliers is to build a layer on top of the actual data which more faithfully adheres to the data model. With SkyView we have used a somewhat alternative approach. We allow the data model to define new behaviors in the SkyView code itself either by customizing the use of existing capabilities or pointing to new classes that have non-standard behavior. This approach is feasible since in modern computer languages the code that is run can be selected dynamically with new classes completely overriding traditional behavior. This paper describes this approach and considers how it may become more useful as our software structures become increasingly dynamically linked.

Thomas McGlynn↗

Preconditioning of overcast-to-broken cloud transitions by riming in marine cold air outbreaks

Marine cold air outbreaks (CAOs) commonly form overcast cloud decks that transition into broken cloud fields downwind, dramatically altering the local radiation budget. In this study, we investigate the impact of frozen hydrometeors on these transitions. We focus on a CAO case in the NW Atlantic, the location of the multi-year flight campaign ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment). We use MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, version 2) reanalysis fields to drive large eddy simulations with mixed-phase two-moment microphysics in a Lagrangian framework. We find that transitions are triggered by substantial rain (rainwater paths >25 g m−2), and only simulations that allow for aerosol depletion result in sustained breakups, as observed. Using a range of diagnostic ice nucleating particle concentrations, Ninp, we find that increasing ice progressively accelerates transitions, thus abbreviating the overcast state. Ice particles affect the cloud-topped boundary layer evolution, primarily through riming-related processes prior to substantial rain, leading to (1) a reduction in cloud liquid water, (2) early consumption of cloud condensation nuclei, and (3) early and light precipitation cooling and moistening below cloud. We refer to these three effects collectively as “preconditioning by riming”. Greater boundary layer aerosol concentrations available as cloud condensation nuclei (CCN) delay the onset of substantial rain. However, cloud breakup and low CCN concentration final stages are found to be inevitable in this case, due, primarily, to liquid water path buildup. An ice-modulated cloud transition speed suggests the possibility of a negative cloud–climate feedback. To address prevailing uncertainties in the model representation of mixed-phase processes, the magnitude of ice formation and riming impacts and, thereby, the strength of an associated negative cloud–climate feedback process, requires further observational evaluation by targeting riming hot spots with in situ imaging probes that allow for both the characterization of ice particles and abundance of supercooled droplets.

Marine cold air outbreaks↗

Effect of Rain-Adjusted Satellite Sea Surface Salinity on ENSO Predictions from the GMAO S2S Forecast System

ENSO has a significant impact on climate variability throughout the world and so has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of altimetry and in situ data lead to improved short-term forecasts of the coupled system. However, few studies have focused on improving the near-surface density/mixing through assimilation of satellite sea surface salinity (SSS). For expediency, most projects that do assimilate SSS do so as if these data were observed at the top model layer instead of at the surface. In rainy regions where buoyant water sits as a fresh lens at the surface, this assumption is likely invalid. Therefore, we adjust SSS so that it more accurately represents the salinity at the first model layer. The Rain Impact Model (RIM) uses a simple diffusion model to determine the near surface salinity gradient (i.e., 1 cm to 5 m). Satellite SSS data are modified using this near-surface salinity gradient, so the salinity values are now valid at the first model layer (we call this SSS@5m). We assess the impact of satellite SSS observations for near-surface dynamics within ocean reanalyses and how these impact dynamical ENSO forecasts using the NASA GMAO S2S coupled system. For all reanalysis experiments, all available along-track sea level and in situ observations are assimilated for 2011 to 2020 using the LETKF scheme (Penny et al., 2013). One reanalysis assimilates Aquarius /SMAP SSS as before. An additional reanalysis is performed assimilating the SSS@5m data. Validation statistics are compared for experiments that assimilate SSS (sub-optimally as before) versus the SSS@5m. We also compare results of coupled forecasts that are initialized from these reanalyses in spring. For all but the big La Niña in 2017, all NINO3.4 forecasts were improved by using the RIM. We will show that improved SSS estimates upgrades density and near-surface mixing leading to more accurate coupled air/sea interaction and better forecasts.

ENSO↗

Detail Enhancement of AIRS/AMSU Temperature and Moisture Profiles Using a 3D Deep Neural Network

In recent decades, spaceborne microwave and hyperspectral infrared sounding instruments have significantly benefited weather forecasting and climate science. However, existing retrievals of lower troposphere temperature and humidity profiles have limitations in vertical resolution, and often cannot accurately represent key features such as the mixed layer thermodynamic structure and the inversion at the planetary boundary layer (PBL) top. Because of the existing limitations in PBL remote sensing from space, there is a compelling need to improve routine, global observations of the PBL and enable advances in scientific understanding and weather and climate prediction. To address this, we have developed a new 3D deep neural network (DNN) which enhances detail and reduces noise in Level 2 granules of temperature and humidity profiles from the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) sounder instruments aboard NASA’s Aqua spacecraft. We show that the enhancement improves accuracy and detail including key features such as capping inversions at the top of the PBL over land, resulting in improved accuracy in estimations of PBL height.

Adam B Milstein↗

Laminated magnetic materials for on-chip magnetic inductors/transformers

A technique relates to a method of forming a laminated multilayer magnetic structure. An adhesion layer is deposited on a substrate. A magnetic seed layer is deposited on top of the adhesion layer. Magnetic layers and non-magnetic spacer layers are alternatingly deposited such that an even number of the magnetic layers is deposited while an odd number of the non-magnetic spacer layers is deposited. The odd number is one less than the even number. Every two of the magnetic layers is separated by one of the non-magnetic spacer layers. The first of the magnetic layers is deposited on the magnetic seed layer, and the magnetic layers each have a thickness less than 500 nanometers.

36 MATERIALS SCIENCE↗

Laminated magnetic materials for on-chip magnetic inductors/transformers

A technique relates to a method of forming a laminated multilayer magnetic structure. An adhesion layer is deposited on a substrate. A magnetic seed layer is deposited on top of the adhesion layer. Magnetic layers and non-magnetic spacer layers are alternatingly deposited such that an even number of the magnetic layers is deposited while an odd number of the non-magnetic spacer layers is deposited. The odd number is one less than the even number. Every two of the magnetic layers is separated by one of the non-magnetic spacer layers. The first of the magnetic layers is deposited on the magnetic seed layer, and the magnetic layers each have a thickness less than 500 nanometers.

36 MATERIALS SCIENCE↗

Characterization of Engineered Pinholes in Dielectric Stacks of High-Performance Poly-Silicon Passivating Contacts

Passivating contact structures are expected to be implemented in > 50 % of industrially manufactured silicon photovoltaics produced over the next decade. One type of passivating contact utilizes a c-Si/dielectric/doped poly-Si layer stack. In cases where the dielectric layer/s are thick enough to impede tunneling of charge carriers, it was shown that disruptions (pinholes) in the dielectric are required to facilitate transport.[1] Pinholes in SiOx layers have typically been formed via high temperature annealing that allows localized breakup of this layer. This approach has drawbacks; 1) high temperature annealing increases cost and 2) pinhole formation is sensitive to both the SiOx thickness and wafer surface morphology making control of density and dimensions difficult. Recently, an alternative method of pinhole formation relying on metal assisted chemical etching (MACE) was shown to allow control over pinhole areal densities.[2] Such control is critical as both the density and dimensions of the pinholes determine saturation current density and contact resistivity. The contacts formed with the MACE process are known as polysilicon on locally etched oxide or PLEO and also result in low saturation current densities and low contact resistivity due to SiOx passivation and engineered pinhole enabled charge carrier transport, respectively. Photovoltaic devices with efficiencies greater than 20 % have recently been produced with these contacts, demonstrating the viability of contacts with engineered pinholes. Experimentally, preferential local collection of excess charge carriers has been observed and definitively connected to thermally induced pinholes in thick SiOx layers within c-Si/SiOx/poly-Si contact structures.[3] Recent work has shown that enhanced local collection of excess carriers can result from enhanced diffusion of dopants through pinholes in SiOx layers.[4] This study was restricted to simulation and characterization of poly-Si with the same dopant type as the c-Si substrates. In this work we focus our analysis on boron doped poly-Si with different stacks of dielectric layers (PLEO and PLENO where the N refers to a SiNy layer on top of the SiOx) on n-type crystalline silicon. This provides insight into how engineered pinholes affect charge collection across the p-n junction. Like previous observations of locally enhanced carrier transport through thermally induced pinholes, the EBIC images in Figure 1 shows that engineered pinholes in PLENO (1a) and PLEO (1b) also exhibit locally enhanced carrier transport at pinhole locations (bright spots in the images). We will also present detailed correlative nanoscale structural and chemical analysis using TEM imaging and EELS analysis with sample preparation guided by EBIC imaging. This allows us to connect the density and dimensions of engineered pinholes with charge carrier transport and measured photovoltaic device parameters. Our findings will accelerate the adoption of PLEO and PLENO contacts in industrially manufactured photovoltaic devices.

EBIC↗

Single Carrier Modulation Resource Allocation for Massive MIMO with Virtual Antennas

Today’s Massive MIMO cellular operation is dominated by orthogonal frequency division multiplexing (OFDM) modulation. One of the advantages of OFDM is the flexibility to carve up the available spectrum into resource blocks (RBs) that can operate adjacent to one another. Massive MIMO adds spatial multiplexing layers on top of the RBs, enabling the simultaneous operation of dozens of UEs. Cyclic prefixed single carrier modulation (CP-SCM) is an alternative to OFDM that also benefits from massive MIMO and is useful as an OFDM alternative in specific scenarios. However, until recently, no resource allocation method has been proposed for CP-SCM. In this paper, we present a CP-SCM resource allocation scheme using virtual antennas in a massive MIMO time domain duplexed scenario. By creating several virtual antennas for each physical antenna, the benefits of massive MIMO are achieved with a smaller physical antenna count. Resources are quantized into data streams, and each user can be assigned a variable number of simultaneous streams. This paper presents a detailed development and analysis of multi-stream processing (MSP) for both uplink detection and downlink precoding. We also introduce heterogeneous MSP, where CP-SCM and OFDM signals can be processed in the same MSP framework.

5G and beyond communications↗

The Area Localized Coupled Model for Analytical Mean Flow Prediction in Arbitrary Wind Farm Geometries

This work introduces the area localized coupled (ALC) model, which extends the applicability of approaches that couple classical wake superposition models and atmospheric boundary layer models to wind farms with arbitrary layouts. Coupling wake and top–down boundary layer models is particularly challenging since the latter requires averaging over planform areas associated with turbine-specific regions of the flow that need to be specified. The ALC model uses Voronoi tessellation to define this local area around each turbine. A top–down description of a developing internal boundary layer is then applied over Voronoi cells upstream of each turbine to estimate the local mean velocity profile. Coupling between the velocity at hub-height based on this localized top–down model and a wake model is achieved by enforcing a minimum least-square-error in mean velocity in each cell. The wake model in the present implementation takes into account variations in wind farm inflow velocity and represents the wake profile behind each turbine as a super-Gaussian function that smoothly transitions between a top-hat shape in the region immediately following the turbine to a Gaussian profile downstream. Detailed comparisons to large-eddy simulation (LES) data from two different wind farms demonstrate the efficacy of the model in accurately predicting both wind farm power output and local turbine hub-height velocity for different wind farm geometries. These validations using data generated from two different LES codes demonstrate the model's versatility with respect to capturing results from different simulation setups and wind farm configurations.

49 EE - Wind and Water Power Program - Wind (EE-4W↗