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At least 1,099 records · Page 61

Nuclear Data Sheets for A=164

Experimental nuclear structure data for the known A=164 isobaric nuclides (Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Hf, Ta, W, Re, Os, Ir) have been evaluated, and presented together with Adopted properties of level energies, and associated γ rays. The decay data for these nuclides have also been evaluated, providing Adopted values of γ and β radiations, and log ft values. No excited states are known in 164 Eu, 164 Tb, and 164 Ir. Information for 164 Gd, 164 Re and 164 Os is limited due to insufficient experimental data. For radioactive nuclides, decay schemes of 164 Sm, 164 Gd and 164 Re are not known, and those of 164 W, 164 Tb, 164 Lu, 164 Hf, 164 Ta and 164 W are incomplete. The decay schemes of 164 Ho and the two activities of 164 Tm seem fairly complete. The decay scheme of 164 Yb presents a major problem that the Q(ε) value of 887 keV 29 recommended in 2017Wa10 is in disagreement with the population of levels at 928, 952 and 1060 keV in the daughter nucleus. This decay scheme, which so far has been mainly reported in a secondary reference (1982AdZZ) needs further investigation. Also the masses of 164 Yb and 164 Tm need either new measurements or a re-evaluation to resolve discrepancy of about 220 keV in the Q value of 164 Yb decay to 164 Tm. The reactions and decays for which no new experimental information has become available since the 2001 update have undergone revisions to incorporate conversion coefficients from BrIcc code, and evaluated Q values from 2017Wa10, but the essential content of such datasets may have remained the same as in previous evaluations. Finally, in this respect the present work greatly benefited from all the previous NDS evaluations (2001Si27,1992Sh07, 1986Sh03,1974Bu30), but at the same time data presented herein supersede all the previous published evaluations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Rapid Determination of Trace Palladium in Active Pharmaceutical Ingredients by Magnetic Solid-Phase Extraction and Flame Atomic Absorption Spectrometry

Clutaraldehyde cross-linked magnetic chitosan nanoparticles were synthesized and used as an adsorbent for the dispersive solid-phase extraction of palladium in active pharmaceutical ingredients (APIs) prior to analysis by a flame atomic absorption spectrophotometer. FT-IR, X-ray diffraction, and TEM were used to characterize the adsorbent. Various parameters of experimental performance, such as adsorbent amount, pH, adsorption time, desorption solutions, coexisting ions, and adsorbent reusability, were investigated and optimized. Under the optimized conditions, good linearity was achieved in the 5.0–500 μg/L concentration range, with correlation coefficients of 0.9989. The limit of detection is 2.8 μg/L and the recoveries of spiked samples ranged from 91.7 to 97.6%. It was confirmed that the GMCNs nanocomposite was a promising adsorbing material for extraction and preconcentration of Pd in APIs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Development of carbon nanosensor for vinpocetine at zinc oxide modified carbon matrix with anionic surfactant for clinical application

A nano-level sensing method was formulated for the trace-level detection and determination of vinpocetine (VIN) at a zinc oxide nanomaterial-based carbon matrix with immobilised anionic surfactant sodium dodecyl sulfate (ZnO-SDS/CPE) using cyclic voltammetry (CV) and square wave voltammetry (SWV) approaches. The catalytic properties of ZnO impact the electron rate of VIN activity, resulting in a threefold increase in the VIN peak response with the ZnO-SDS-modified sensor. Here, the effects of several factors, including scan rate, pH, accumulation length, modifier amount, and concentration, were investigated on the VIN peak current. The electro-oxidation of VIN by pH study involves one proton and one electron. The CV method also investigated the effect of scan rate. The charge transfer coefficient (α) is obtained to be 0.58, and the heterogeneous rate constant (k°) is estimated to be 4.46 s⁻¹. The concentration effect of VIN was studied using the SWV method. Specifically, the SWV methodology achieved the lowest detection limit compared to previously published approaches, with estimated values of the Limit of Detection (LOD) and Limit of Quantification (LOQ) being 2.2 × 10⁻⁸ M and 7.7 × 10⁻⁸ M, respectively. The trace level of VIN in tablet and urine samples was determined using the modified sensor. Moreover, the sensor demonstrates particular reproducibility and long-term stability, making it suitable for real-time applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochromic Properties of Perovskite NdNiO 3 Thin Films for Smart Windows

Semiconductors with electrically tunable band gaps are of great interest in controlling transparency to electromagnetic radiation. Thin films of perovskite nickelate NdNiO 3 (NNO), a class of correlated oxides, were deposited on single-crystal (LaAlO 3 (LAO)) and polycrystalline (fluorine-doped tin oxide-coated glass (FTO)) substrates by magnetron sputtering, chemical solution deposition (CSD), and atomic layer deposition (ALD). Their electrochromic behaviors were investigated using a three-electrode setup in basic (KOH solution, pH = 12) electrolyte. During bleaching/coloration process, the proton intercalation/deintercalation and simultaneous electron compensation in the NNO lattice under electrical bias led to crossover of the material between the pristine-conducting phase (Ni 3+ ) and the strongly correlated insulating phase (Ni 2+ ), which serves as the working principle for electrochromic (tunable opacity in the visible range) behavior. Cyclic voltammetry (CV) scans demonstrate that NNO films are electrochemically stable in basic solutions for all three film deposition methods explored here. CV scans at varying rates enabled the extraction of diffusion coefficient of protons in thin film NNO, which is similar to 10 –7 cm 2 s –1 among all films studied. Large light transmittance modulation by bleaching and coloration was observed on films grown on both LAO and FTO substrates, suggesting its potential as an electrochromic material candidate for smart windows and optical shutter applications. Here, porous NNO films obtained by chemical solution deposition tend to demonstrate stronger electrochromic activity than dense films grown by sputtering or ALD.

36 MATERIALS SCIENCE↗

On the Stability of Power Transmission Systems Under Persistent Inverter Attacks: A Bi-Linear Matrix Approach

We investigate the stability and robustness properties of a power transmission system under persistent deceiving attacks on inverter-interfaced energy resources. The attacks can corrupt the damping coefficients in the inverters' controllers and measurements of the frequency at the points of coupling. Leveraging tools from hybrid dynamical systems theory, we characterize a broad family of persistent (and not necessarily periodic) attacks acting on the inverters, under which the stability properties of the transmission system can be shown to not be compromised. To address potentially conservative conditions identified through conventional bounding techniques, sufficient conditions on the average activation time of the attacks are identified via Lyapunov theory, as well as the formulation and solution of a class of bilinear matrix inequalities (BMI). The results are obtained for constant and slowly time-varying loads via input-to-state stability (ISS) tools. Numerical simulations on the IEEE 39-bus test system are also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Operational Data Reduction Procedure for Determining Density and Vertical Structure of the Martian Upper Atmosphere from Mars Global Surveyor Accelerometer Measurements

The success of aerobraking by the Mars Global Surveyor (MGS) spacecraft was partly due to the analysis of MGS accelerometer data. Accelerometer data was used to determine the effect of the atmosphere on each orbit, to characterize the nature of the atmosphere, and to predict the atmosphere for future orbits. To interpret the accelerometer data, a data reduction procedure was developed to produce density estimations utilizing inputs from the spacecraft, the Navigation Team, and pre-mission aerothermodynamic studies. This data reduction procedure was based on the calculation of aerodynamic forces from the accelerometer data by considering acceleration due to gravity gradient, solar pressure, angular motion of the MGS, instrument bias, thruster activity, and a vibration component due to the motion of the damaged solar array. Methods were developed to calculate all of the acceleration components including a 4 degree of freedom dynamics model used to gain a greater understanding of the damaged solar array. The total error inherent to the data reduction procedure was calculated as a function of altitude and density considering contributions from ephemeris errors, errors in force coefficient, and instrument errors due to bias and digitization. Comparing the results from this procedure to the data of other MGS Teams has demonstrated that this procedure can quickly and accurately describe the density and vertical structure of the Martian upper atmosphere.

Cancro, George J.↗

On-Orbit Calibration and Performance of Aqua MODIS Reflective Solar Bands

Aqua MODIS has successfully operated on-orbit for more than 6 years since its launch in May 2002, continuously making global observations and improving studies of changes in the Earth's climate and environment. 20 of the 36 MODIS spectral bands, covering wavelengths from 0.41 to 2.2 microns, are the reflective solar bands (RSB). They are calibrated on-orbit using an on-board solar diffuser (SD) and a solar diffuser stability monitor (SDSM). In addition, regularly scheduled lunar observations are made to track the RSB calibration stability. This paper presents Aqua MODIS RSB on-orbit calibration and characterization activities, methodologies, and performance. Included in this study are characterizations of detector signal-to-noise ratio (SNR), short-term stability, and long-term response change. Spectral wavelength dependent degradation of the SD bidirectional reflectance factor (BRF) and scan mirror reflectance, which also varies with angle of incidence (AOI), are examined. On-orbit results show that Aqua MODIS onboard calibrators have performed well, enabling accurate calibration coefficients to be derived and updated for the Level 1B (L1B) production and assuring high quality science data products to be continuously generated and distributed. Since launch, the short-term response, on a scan-by-scan basis, has remained extremely stable for most RSB detectors. With the exception of band 6, there have been no new RSB noisy or inoperable detectors. Like its predecessor, Terra MODIS, launched in December 1999, the Aqua MODIS visible (VIS) spectral bands have experienced relatively large changes, with an annual response decrease (mirror side 1) of 3.6% for band 8 at 0.412 microns, 2.3% for band 9 at 0.443 microns, 1.6% for band 3 at 0.469 microns, and 1.2% for band 10 at 0.488 microns. For other RSB bands with wavelengths greater than 0.5 microns, the annual response changes are typically less than 0.5%. In general, Aqua MODIS optics degradation is smaller than Terra MODIS and the mirror side differences are much smaller. Overall, Aqua MODIS RSB on-orbit performance is better than Terra MODIS.

Xiong, Xiaoxiong↗

Satellite Soil Moisture Data Assimilation Impacts on Modeling Weather Variables and Ozone in the Southeastern US – Part 2: Sensitivity to Dry-Deposition Parameterizations

Ozone (O3) dry deposition is a major O3 sink. As a follow-up study of Huang et al. (2021), we quantify the impact of satellite soil moisture (SM) on model representations of this process when different dry-deposition parameterizations are implemented, based on which the implications for interpreting O3 air pollution levels and assessing the O3 impacts on human and ecosystem health are provided. The SM data from NASA's Soil Moisture Active Passive mission are assimilated into the Noah-Multiparameterization (Noah-MP) land surface model within the NASA Land Information System framework, semicoupled with Weather Research and Forecasting model with online Chemistry (WRF-Chem) regional-scale simulations covering the southeastern US. Major changes in the modeling system used include enabling the dynamic vegetation option, adding the irrigation process, and updating the scheme for the surface exchange coefficient. Two dry-deposition schemes are implemented, i.e., the Wesely scheme and a “dynamic” scheme, in the latter of which dry-deposition parameterization is coupled with photosynthesis and vegetation dynamics. It is demonstrated that, when the dynamic scheme is applied, the simulated O3 dry-deposition velocities vd and their stomatal and cuticular portions, as well as the total O3 fluxes Ft, are larger overall; vd and Ft are 2–3 times more sensitive to the SM changes due to the data assimilation (DA). Further, through case studies at two forested sites with different soil types and hydrological regimes, we highlight that, applying the Community Land Model type of SM factor controlling stomatal resistance (i.e., β factor) scheme in replacement of the Noah-type β factor scheme reduced the v(d) sensitivity to SM changes by ∼75 % at one site, while it doubled this sensitivity at the other site. Referring to multiple evaluation datasets, which may be associated with variable extents of uncertainty, the model performance of vegetation, surface fluxes, weather, and surface O3 concentrations shows mixed responses to the DA, some of which display land cover dependency. Finally, using model-derived concentration- and flux-based policy-relevant O3 metrics as well as their matching exposure–response functions, the relative biomass/crop yield losses for several types of vegetation/crops are estimated to be within a wide range of 1 %–17 %. Their sensitivities to the model's dry-deposition scheme and the implementation of SM DA are discussed.

Min Huang↗

Enhancing Radiative Transfer Models for Optimized Assimilation of Microwave and Radar Observations

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.

Isaac Moradi↗

Optimizing Assimilation of Microwave and Radar Observations in the NWP Models

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.

Isaac Moradi↗

Assimilation of Spaceborne Microwave and Radar Observations

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.

Isaac Moradi↗

Nanoscale Hybrid Electrolytes with Viscosity Controlled Using Ionic Stimulus for Electrochemical Energy Conversion and Storage

As renewable energy is rapidly integrated into the grid, the challenge has become storing intermittent renewable electricity. Technologies including flow batteries and CO 2 conversion to dense energy carriers are promising storage options for renewable electricity. To achieve this technological advancement, the development of next generation electrolyte materials that can increase the energy density of flow batteries and combine CO 2 capture and conversion is desired. Liquidlike nanoparticle organic hybrid materials (NOHMs) composed of an inorganic core with a tethered polymeric canopy (e.g., polyetheramine (HPE)) have a capability to bind chemical species of interest including CO 2 and redox-active species. In this study, the unique response of NOHM-I-HPE-based electrolytes to salt addition was investigated, including the effects on solution viscosity and structural configurations of the polymeric canopy, impacting transport behaviors. The addition of 0.1 M NaCl drastically lowered the viscosity of NOHM-based electrolytes by up to 90%, reduced the hydrodynamic diameter of NOHM-I-HPE, and increased its self-diffusion coefficient, while the ionic strength did not alter the behaviors of untethered HPE. This study is the first to fundamentally discern the changes in polymer configurations of NOHMs induced by salt addition and provides a comprehensive understanding of the effect of ionic stimulus on their bulk transport properties and local dynamics. These insights could be ultimately employed to tailor transport properties for a range of electrochemical applications.

25 ENERGY STORAGE↗

Correlation Between Microscopic Current Fluctuations Observed at Ultra-Microelectrodes and Macroscopic Bulk Electrolysis Performance in Redox-Active Microemulsions

Microemulsions (μEs) have been proposed as redox flow battery (RFB) electrolytes that maximize ionic conductivity and charge capacity by synergizing two immiscible phases. However, charge transfer during electrolysis in μEs is poorly understood. Here, we show that ultramicroelectrode electrolysis of ferrocene-loaded μEs –20%, 60%, and 90% water - reveals stochastic current fluctuations. These are differentiated in the scanning electrochemical microscopy (SECM) geometry, where power spectral density analysis showed distinct changes in the frequency contributions. SECM in the substrate generation-tip collection mode showed that fluctuations arise under mass-transfer control. Significant differences in the diffusion coefficient of ferrocene species were deducted from SECM approach curves, suggesting phase transfer behavior. Using bulk electrolysis, we calculated the charge accessibility and cycling behavior in the μEs. A decrease in the stochastic behavior of the μEs seems to correlate to a higher accessibility and cycling performance, with the 90% water μE displaying the best reversibility and the 60% the lowest. Altogether, these results suggest that Marangoni-type convection driven by concentration gradients and/or μE restructuring during charge transfer play a role in the electrochemical performance of μEs. This presents opportunities for screening and diagnosing the performance of these emerging RFB electrolytes.

25 ENERGY STORAGE↗

Developing predictive models for µ opioid receptor binding using machine learning and deep learning techniques

Opioids exert their analgesic effect by binding to the µ opioid receptor (MOR), which initiates a downstream signaling pathway, eventually inhibiting pain transmission in the spinal cord. However, current opioids are addictive, often leading to overdose contributing to the opioid crisis in the United States. Therefore, understanding the structure-activity relationship between MOR and its ligands is essential for predicting MOR binding of chemicals, which could assist in the development of non-addictive or less-addictive opioid analgesics. This study aimed to develop machine learning and deep learning models for predicting MOR binding activity of chemicals. Chemicals with MOR binding activity data were first curated from public databases and the literature. Molecular descriptors of the curated chemicals were calculated using software Mold2. The chemicals were then split into training and external validation datasets. Random forest, k-nearest neighbors, support vector machine, multi-layer perceptron, and long short-term memory models were developed and evaluated using 5-fold cross-validations and external validations, resulting in Matthews correlation coefficients of 0.528–0.654 and 0.408, respectively. Furthermore, prediction confidence and applicability domain analyses highlighted their importance to the models’ applicability. Our results suggest that the developed models could be useful for identifying MOR binders, potentially aiding in the development of non-addictive or less-addictive drugs targeting MOR.

Research & Experimental Medicine↗

On the flight derived/aerodynamic data base performance comparisons for the NASA Space Shuttle entries during the hypersonic regime

Aerodynamic performance data from the first four Shuttle reentry flights are compared with preflight predictions covering hypersonic longitudinal mode down to Mach 2. The extraction of the flight coefficients, as measured by the spacecraft angular rates and the linear accelerations, derived from the inertial measurement unit, the best estimate trajectory, and the remotely measured atmosphere are discussed. The ground predictions were developed from 30,000 hr of wind tunnel testing. Actual flight data are presented for 80-260 kft, from Mach 2-26, comprising the dynamic pressure, the vehicle air relative attitude angles, control surface deflections, reaction jet activity, and body axis rates and accelerations. The second and fourth flights gave results which deviated from predictions between 230-260 kft. The accuracy limits of the derived atmospheric densities are considered, together with potential data base updates in the light of limitations imposed on the corrections by available flight data.

Findlay, J. T.↗

A Probabilistic Framework for the Validation and Certification of Computer Simulations

The paper presents a methodology for quantifying, propagating, and managing the uncertainty in the data required to initialize computer simulations of complex phenomena. The purpose of the methodology is to permit the quantitative assessment of a certification level to be associated with the predictions from the simulations, as well as the design of a data acquisition strategy to achieve a target level of certification. The value of a methodology that can address the above issues is obvious, specially in light of the trend in the availability of computational resources, as well as the trend in sensor technology. These two trends make it possible to probe physical phenomena both with physical sensors, as well as with complex models, at previously inconceivable levels. With these new abilities arises the need to develop the knowledge to integrate the information from sensors and computer simulations. This is achieved in the present work by tracing both activities back to a level of abstraction that highlights their commonalities, thus allowing them to be manipulated in a mathematically consistent fashion. In particular, the mathematical theory underlying computer simulations has long been associated with partial differential equations and functional analysis concepts such as Hilbert spares and orthogonal projections. By relying on a probabilistic framework for the modeling of data, a Hilbert space framework emerges that permits the modeling of coefficients in the governing equations as random variables, or equivalently, as elements in a Hilbert space. This permits the development of an approximation theory for probabilistic problems that parallels that of deterministic approximation theory. According to this formalism, the solution of the problem is identified by its projection on a basis in the Hilbert space of random variables, as opposed to more traditional techniques where the solution is approximated by its first or second-order statistics. The present representation, in addition to capturing significantly more information than the traditional approach, facilitates the linkage between different interacting stochastic systems as is typically observed in real-life situations.

Ghanem, Roger↗

ADEPT for Secondary Payloads

Deployable entry vehicles provide an enabling capability for large payloads at destinations across the solar system. The primary advantage of such systems derives from the fundamental limitation of available launch vehicle shroads preventing tried-and-true rigid aeroshell technology from being applied. However, little mission-pull exists for deployable entry vehicle technology for missions where the entry vehicle is the primary payload and can fit within available shrouds. The propensity toward applying rigid aeroshell technology is logical given that deployable concepts are higher risk and provide no marginal scientific benefit for missions where a rigid aeroshell is an option. A movement toward flying smaller spacecraft has emerged in recent years and is revealing novel applications for deployable entry vehicles as secondary payloads. Secondary payloads must minimize interference with the primary payload in order to ease accomodation. Advancements in small spacecraft technology have caught the attention of government entities who are now recognizing the high value proposition of small spacecraft for frequent, incremental technology development and science return rather than the traditional high cost and infrequent big-bang approaches. Worldwide, well over 200 small satellites (mass < 180 kg) have launched in recent years for such purposes as eduation, technology development, science, commerce, and defense. The Adaptable Deployable Entry and Placement Technology (ADEPT), a mechanically-deployable entry vehicle technology, has been under development at NASA since 2011. An Ames Center Innovation Fund (CIF) proposal was recently awarded to study ADEPT for EDL of small payloads. The unique capability of ADEPT for small science payloads comes from its ability to stow within a slender volume and deploy passively to achieve a mass-efficient drag surface with a high heat rate capability. The low ballistic coefficient results in entry heating and mechanical loads that can be met by a revolutionary three-dimensionally woven carbon fabric supported with rib structures. This carbon fabric has test-proven capability as both primary structure and payload thermal protection. This presentation will inform the EDL community of the capability of ADEPT for delivery of small secondary payloads as well as provide status of on-going technology development activities. Results of a mission applications study for secondary payloads to Mars and Venus will be presented. A primary goal of these mission design activities is to integrate high-value verification approaches wherever possible. For example, for some mission applications it is possible to test in NASA arc jet facilities at full-scale. This enables endto- end thermostructural requirement verification with a single test. Another important challenge that needs to be solved is the reliability of the decelerator to achieve the desired shape using simple passive mechanical actuators (such as springs) that do not require power from the primary payload for deployment. A configuration of ADEPT is being prototyped and used to evaluate the functionality and reliability of the deployment mechanism through bench-top testing. The prototype will then be tested in a low speed wind tunnel in late 2014 to evaluate aerodynamic load-carrying capability and deflected shape. Results of the deployment testing and status of wind tunnel test plans will be discussed.

Smith, B.↗

Gas-phase metallicity determinations in nearby AGNs with SDSS-IV MaNGA: evidence of metal-poor accretion

ABSTRACT We derive the metallicity (traced by the O/H abundance) of the narrow-line region (NLR) of 108 Seyfert galaxies as well as radial metallicity gradients along their galaxy discs and of these of a matched control sample of no active galaxies. In view of that, observational data from the SDSS-IV MaNGA survey and strong emission-line calibrations taken from the literature were considered. The metallicity obtained for the NLRs was compared to the value derived from the extrapolation of the radial oxygen abundance gradient, obtained from H ii region estimates along the galaxy disc, to the central part of the host galaxies. We find that, for most of the objects ($\sim 80\, {{\ \rm per\ cent}}$), the NLR metallicity is lower than the extrapolated value, with the average difference ($\langle$D$\rangle$) between these estimates ranging from 0.16 to 0.30 dex. We suggest that $\langle$D$\rangle$ is due to the accretion of metal-poor gas to the AGN that feeds the nuclear supermassive black hole (SMBH), which is drawn from a reservoir molecular and/or neutral hydrogen around the SMBH. Additionally, we look for correlations between D and the electron density (Ne), [O iii]λ5007, and H α luminosities, extinction coefficient (AV) of the NLRs, as well as the stellar mass (M*) of the host galaxies. Evidence of an inverse correlation between the D and the parameters Ne, M*, and Av was found.

79 ASTRONOMY AND ASTROPHYSICS↗