Proactive Frequency Stability Scheme Based on Bayesian Filters and Spectral Clustering
Not Available
24 POWER TRANSMISSION AND DISTRIBUTION↗
SEARCH · Search NASA
Results for “Distributed Estimation”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Machine Learning-Based Anomaly Detection for Load Forecasting Under Cyberattacks
Accurate load forecasting can create both economic and reliability benefits for power system operators. However, the cyberattack on load forecasting may mislead operators to make unsuitable operational decisions for the electricity delivery. To effectively and accurately detect these cyberattacks, this paper develops a machine learning-based anomaly detection (MLAD) methodology. First, load forecasts provided by neural networks are used to reconstruct the benchmark and scaling data by using the k-means clustering. Second, the cyberattack template is estimated by the naive Bayes classification based on the cumulative distribution function and statistical features of the scaling data. Finally, the dynamic programming is utilized to calculate both the occurrence and parameter of one cyberattack on load forecasting data. Here, a widely used symbolic aggregation approximation method is compared with the developed MLAD method. Numerical simulations on the publicly load data show that the MLAD method can effectively detect cyberattacks for load forecasting data with relatively high accuracy. Also, the robustness of MLAD is verified by thousands of attack scenarios based on Monte Carlo simulation.
97 MATHEMATICS AND COMPUTING↗
A Selective Overview and Comparison of Robust Mixture Regression Estimators
Summary Mixture regression models have been widely used in business, marketing and social sciences to model mixed regression relationships arising from a clustered and thus heterogeneous population. The unknown mixture regression parameters are usually estimated by maximum likelihood estimators using the expectation–maximisation algorithm based on the normality assumption of component error density. However, it is well known that the normality‐based maximum likelihood estimation is very sensitive to outliers or heavy‐tailed error distributions. This paper aims to give a selective overview of the recently proposed robust mixture regression methods and compare their performance using simulation studies.
Yu, Chun↗
Reliability comparisons between additively manufactured and conventional SiC–Si ceramic composites
Abstract An additively manufactured reaction‐bonded silicon carbide ceramic composite is fabricated using a bimodal powder feedstock and the binder‐jetting printing technique. On fabricating, the ceramic is investigated to report its composition, mechanical, and thermal properties at room temperature and high temperatures (up to 750). The ceramic has a density of 2.76 g/cc, and shows a hardness of 21.74 GPa, and a flexure strength of 207.5 MPa at room temperature. The mechanical property of flexure strength is used to estimate its failure probability under applied stress, using a Weibull distribution. The mechanical properties and failure probabilities are compared with those of conventionally fabricated reaction‐bonded silicon carbide ceramics reported in the literature. These ceramics were fabricated using methods such as slip‐casting, compacting, and tape‐casting. The comparison is used to elucidate the advantages and areas of improvement of the present additive manufacturing technique for reaction‐bonded ceramics.
14 SOLAR ENERGY↗
Temperature Dependent Raman Spectroscopic Study of the Fe Doped La{sub 0.67}Sr{sub 0.33}MnO{sub 3} Prepared Using Ball Milling Method
Polycrystalline samples of La{sub 0.67}Sr{sub 0.33}Mn{sub 0.65}Fe{sub 0.35}O{sub 3} (LSMFO) were synthesized using the standard ball mill method with different calcination temperatures ranging from 800 to 1100°C for 7 h. The phase purity of these samples was confirmed using X-ray diffraction (XRD) patterns. All samples were found to have rhombohedral crystal structure with R 3-bar c space group. The lattice parameters, cell volume, bond angle and bond length have been obtained using the Rietveld refinement by FullProf software. The average crystallite size calculated using the Debye-Scherrer formula was found between 27 and 60 nm. Surface morphology of the prepared samples has been examined using a scanning electron microscope (SEM). SEM images show the formation of well-arranged grain sizes distributed from 240 to 400 nm, much larger than one estimated using the Scherrer formula. All tiny particles are highly agglomerated with the increasing temperature and porosity decreases with increasing temperature. An analysis of the frequency and peak broadening of Raman modes as a function of temperature clearly shows the significant temperature effect on the A{sub 1g} and E{sub g} modes of LSMFO. The shifts and broadening of the A{sub 1g} and E{sub g} modes are discussed in light of the oxygen sublattice distortion. Our study shows the reduction in distortion with increasing calcination temperature, which suggests a decrease in the JT effect.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Microsimulation model calibration using incremental mixture approximate Bayesian computation
Microsimulation models (MSMs) are used to inform policy by predicting population-level outcomes under different scenarios. MSMs simulate individual-level event histories that mark the disease process (such as the development of cancer) and the effect of policy actions (such as screening) on these events. MSMs often have many unknown parameters; calibration is the process of searching the parameter space to select parameters that result in accurate MSM prediction of a wide range of targets. We develop Incremental Mixture Approximate Bayesian Computation (IMABC) for MSM calibration which results in a simulated sample from the posterior distribution of model parameters given calibration targets. IMABC begins with a rejection-based ABC step, drawing a sample of points from the prior distribution of model parameters and accepting points that result in simulated targets that are near observed targets. Next, the sample is iteratively updated by drawing additional points from a mixture of multivariate normal distributions and accepting points that result in accurate predictions. Posterior estimates are obtained by weighting the final set of accepted points to account for the adaptive sampling scheme. We demonstrate IMABC by calibrating CRC-SPIN 2.0, an updated version of a MSM for colorectal cancer (CRC) that has been used to inform national CRC screening guidelines.
97 MATHEMATICS AND COMPUTING↗
Space-based quantum networking in the presence of a nuclear disturbed environment
Space-based quantum networks provide a means for near-term long-distance transmission of quantum information. Here this article analyzed the performance of a downlink quantum network between a low-Earth-orbit satellite and an observatory operating in less-than-ideal atmospheric conditions. The effects from fog, haze, and a nuclear disturbed environment on the long-range distribution of quantum states were investigated. A density matrix that estimates the quantum state by capturing the effects from increased signal loss and elevated background noise to estimate the state fidelity of the transmitted quantum state was developed. It was found that the nuclear disturbed environment and other atmospheric effects have a degrading effect on the quantum state. These environments impede the ability to perform quantum communications for the duration of the effects. In the case of the nuclear disturbed environment, the nuclear effects subside quickly, and network performance should return to normal by the next satellite pass.
42 ENGINEERING↗
Dynamic pulse propagation modelling for predictive femtosecond-laser-microbonding of transparent materials
A dynamic pulse propagation modeling for femtosecond laser bonding of Borofloat glass is presented. The temperature evolution and internal modifications are predicted by incorporating the nonlinear electron dynamics along with temperature dependent thermal properties. The modelling predicts the spatial and temporal distribution of absorption coefficient and plasma density that gives quantitative estimations of the heat affected zone and weld geometry. The impact of focusing condition on heat affected zone and weld geometry is investigated, which for the first time to our knowledge allows to numerically determine the desired relative position between the geometrical focus of a femtosecond-laser-pulse and the interface of the two substrates to be welded. The prediction of the modelling on the offset distance is applied to weld Borofloat glass plates having optical contact and can be applied to other dielectric solids.
Sahoo, Pankaj K. (ORCID:0000000209437319)↗
Flight Arrival Data for Each Airport
This dataset contains flight arrival data for each airport, which serves as the input for generating load profiles and estimating energy needs and fleet and charger requirements.  Distribution of annual flight arrivals across different airport categories.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DES Y3 + KiDS-1000: Consistent cosmology combining cosmic shear surveys
We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter $S_8 = \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$ with a mean value of $0.790^{+0.018}_{-0.014}$. The mean marginal is lower than the maximum a posteriori estimate, $S_8=0.801$, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with $S_8$ constraints from observations of the cosmic microwave background by Planck, with agreement at the $1.7\sigma$ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum.
79 ASTRONOMY AND ASTROPHYSICS↗
Solid Oxide Based Electrolysis and Stack Technology with Ultra-High Electrolysis Current Density (>3A/cm 2 ) and Efficiency
Hydrogen, a valuable commodity gas, is increasingly recognized as an important fuel and energy storage pathway of the future. This project aims to develop an innovative solid oxide based electrolysis cell and stack technology with ultra-high steam electrolysis current (>3A/cm 2 ) for potentially ultra-low-cost, highly efficient hydrogen production from diverse renewable sources. In this project, solid oxide based high power density cells (HiPoD cells) were developed. Those cells demonstrated capability of operating at ultra-high electrolysis current density of 6 A/cm 2 at 1.67V. During a long term steady state electrolysis test, a HiPoD cell was operated for more than 1000 hours at 3 A/cm 2 with a low degradation rate of 1.8% per 1000 hours. A 20-cell electrolysis stack was built using HiPoD cells and an ultra-compact, low-cost stack design platform. This stack was used to explore the boundaries of high current density electrolysis operation and achieved an incredible stack current density of 3 A/cm 2 with an average cell voltage of only 1.493 V. The stack was further operated in steady-state electrolysis at 2 A/cm 2 for more than 1000 hours with an overall degradation of 0.57% per 1000 hours. With an improved understanding of electrolysis operation at ultra-high current density, a new compact stack architecture (CSA) design with scalability up to 55 kW (or 38 kg H 2 per day) was tested. A number of 45-cell CSA stack was built and demonstrated 10 kW and 245 g/hr hydrogen production at 1.8 A/cm 2 electrolysis current density. In addition to cell and stack development, a preliminary system design was developed by integrating the inputs from electrochemistry, cell/stack performance data, and system level implications of configuration and operational parameters. A module design was created based on a circular array of six stacks surrounded in a cool pressure vessel. Further architectural and controls strategies such as stack power control and instrumentation were determined through the development of the module. A comprehensive techno-economic study of an ultra-high current density SOEC system integrated with renewable energy sources has been conducted. To determine the estimated cost of hydrogen for the system, the H2A Current Distributed Hydrogen Production Model version 3.101 was applied. Annual system production cases at both commercial and industrial electricity rates as per the H2A model was analyzed. The option of meeting DOE 2020 Advanced Electrolysis Technologies targets were discussed. Feedstock electricity represents the bulk of projected hydrogen cost with either electricity rate. At an annual production volume of 250 units, H2A hydrogen cost of $2.3/kg can be achieved at electricity cost around 3.5¢/kWh.
08 HYDROGEN↗
Impact of wetland decline on decreasing dissolved organic carbon concentrations along the Mississippi River continuum
Prior to discharging to the ocean, large rivers constantly receive inputs of dissolved organic carbon (DOC) from tributaries or fringing floodplains and lose DOC via continuous in situ processing along distances that span thousands of kilometers. Current concepts predicting longitudinal changes in DOC mainly focus on in situ processing or exchange with fringing floodplain wetlands, while effects of heterogeneous watershed characteristics are generally ignored. We analyzed results from a 17-year time-series of DOC measurements made at seven sites and three expeditions along the entire Mississippi River main channel with DOC measurements made every 17 km. The results show a clear downstream decrease in DOC concentrations that was consistent throughout the entire study period. Downstream DOC decreases were primarily (~63–71%) a result of constant dilutions by low-DOC tributary water controlled by watershed wetland distribution, while in situ processing played a secondary role. We estimate that from 1780 to 1980 wetland loss due to land-use alterations caused a ca. 58% decrease in in DOC concentrations in the tributaries of the Mississippi River. DOC reductions caused by watershed wetland loss likely impacted the capacity for the river to effectively remove nitrogen via denitrification, which can further exacerbate coastal hypoxia. Lastly, these findings highlight the importance of watershed wetlands in regulating DOC longitudinally along the headland to ocean continuum of major rivers.
54 ENVIRONMENTAL SCIENCES↗
Search for hyperluminous infrared dust-obscured galaxies selected with WISE and SDSS
We aim to search for hyperluminous infrared (IR) galaxies (HyLIRGs) with IR luminosity L{sub IR} > 10{sup 13} L{sub ☉} by applying the selection method of dust-obscured galaxies (DOGs). They are spatially rare but could correspond to a maximum phase of cosmic star formation (SF) and/or active galactic nucleus (AGN) activity; hence, they are a crucial population for understanding the SF and mass assembly history of galaxies. Combining the optical and IR catalogs obtained from the Sloan Digital Sky Survey (SDSS) and Wide-field Infrared Survey Explorer (WISE), we performed the extensive HyLIRGs survey; we selected 5311 IR-bright DOGs with i − [22] > 7.0 and flux at 22 μm > 3.8 mJy in 14,555 deg{sup 2}, where i and [22] are i-band and 22 μm AB magnitudes, respectively. Among them, 67 DOGs have reliable spectroscopic redshifts that enable us to estimate their total IR luminosity based on the spectral energy distribution fitting. Consequently, we successfully discovered 24 HyLIRGs among the 67 spectroscopically confirmed DOGs. We found that (i) i − [22] color of IR-bright DOGs correlates with the total IR luminosity and (ii) the surface number density of HyLIRGs is >0.17 deg{sup −2}. A large fraction (∼73%) of IR-bright DOGs with i − [22] > 7.5 show L{sub IR} > 10{sup 13} L{sub ☉}, and the DOG criterion we adopted could be independently effective against the “W1W2-dropout method,” based on four WISE bands, for searching hyperluminous IR populations of galaxies.
79 ASTRONOMY AND ASTROPHYSICS↗
MALT90 Kinematic Distances to Dense Molecular Clumps
Using molecular-line data from the Millimetre Astronomy Legacy Team 90 GHz Survey (MALT90), we have estimated kinematic distances to 1905 molecular clumps identified in the ATLASGAL 870 μ m continuum survey over the longitude range 295° < l < 350°. The clump velocities were determined using a flux-weighted average of the velocities obtained from Gaussian fits to the HCO{sup +}, HNC, and N{sub 2}H{sup +} (1–0) transitions. The near/far kinematic distance ambiguity was addressed by searching for the presence or absence of absorption or self-absorption features in 21 cm atomic hydrogen spectra from the Southern Galactic Plane Survey. Our algorithm provides an estimation of the reliability of the ambiguity resolution. The Galactic distribution of the clumps indicates positions where the clumps are bunched together, and these locations probably trace the locations of spiral arms. Several clumps fall at the predicted location of the far side of the Scutum–Centaurus arm. Moreover, a number of clumps with positive radial velocities are unambiguously located on the far side of the Milky Way at galactocentric radii beyond the solar circle. The measurement of these kinematic distances, in combination with continuum or molecular-line data, now enables the determination of fundamental parameters such as mass, size, and luminosity for each clump.
79 ASTRONOMY AND ASTROPHYSICS↗
A Novel Statistical Method for Measuring the Temperature–Density Relation in the IGM Using the b – N Hi Distribution of Absorbers in the Ly α Forest
We propose a new method for determining the thermal state of the intergalactic medium based on Voigt profile decomposition of the Lyα forest. The distribution of Doppler parameter and column density (b–N H i distribution) is sensitive to the temperature–density relation T = T 0 (ρ/ρ 0 ) γ-1 , and previous work has inferred T 0 and γ by fitting its low-b cutoff. This approach discards the majority of available data and is susceptible to systematics related to cutoff determination. We introduce an approach that exploits all information encoded in the b – N H i distribution by modeling its entire shape. We apply kernel density estimation to discrete absorption lines to generate model probability density functions, and then we use principal component decomposition to create an emulator that can be evaluated anywhere in thermal parameter space. We introduce a Bayesian likelihood based on these models enabling parameter inference via Markov Chain Monte Carlo. The method's robustness is tested by applying it to a large grid of thermal history simulations. By conducting 160 mock measurements, we establish that our approach delivers unbiased estimates and valid uncertainties for a 2D ( T 0 , γ) measurement. Furthermore, we conduct a pilot study applying this methodology to real observational data at z = 2. Using 200 absorbers, equivalent in path length to a single Lya forest spectrum, we measure $\mathrm{log}{T}_{0}={4.092}_{-0.055}^{+0.050}$ and $\gamma ={1.49}_{-0.074}^{+0.073}$ in excellent agreement with cutoff fitting determinations using the same data. Our method is far more sensitive than cutoff fitting, enabling measurements of log T 0 and γ with precision on $\mathrm{log}{T}_{0}$ (γ) nearly two (three) times higher for current data set sizes.
79 ASTRONOMY AND ASTROPHYSICS↗
Retrieval of warm precipitation microphysics
Intrieri et al. (1993) and later O’Connor et al. (2005) proposed a technique to constrain water drop size distribution using lidar backscatter (related to water drop cross-section) and Doppler spectral width (related to the width of the water drop size distribution). This radar-lidar technique can be used to estimate precipitation rate and microphysical characteristics at all levels in the subcloud layer when collocated radar and ceilometer observations are available. We apply this technique to the vertically pointing ARM ceilometer lidar and Ka-band Zenith Radar (KAZR2) pair. The O’Connor et al. (2005) technique requires ceilometer backscatter to be calibrated and remapped to the radar spatio-temporal resolution (here 2 s x 30 m). Ceilometer backscatter is calibrated following a variation of the O'Connor et al. (2004) technique by scaling observed path-integrated backscatter in thick stratocumulus to match theoretical cloud lidar ratio values. Satisfactory conditions for ceilometer backscatter calibration are identified as the first (in time) 20-min periods each day with standard deviation of lidar ratio smaller than 1.5. The observed backscatter during the “satisfactory 20-min period” are input to Hogan (2006)’s multi scattered model to determine a daily backscatter calibration factor. For days where satisfactory conditions are not observed, a climatological calibration factor of 1.35 is used to calibrate the observed backscatter. Calibrated ceilometer backscatter is subsequently mapped on the KAZR2 time-height grid using a nearest-neighbor approach. Following Kollias et al. (2019), KAZR2 calibration is performed using collocated surface-based Parsivel laser disdrometer-equivalent radar reflectivity estimates during light precipitation events. This radar-lidar technique generates time-height maps of precipitation rate from 200 m above ground level to 90 m below cloud base height that are filtered for aerosol contamination.
54 ENVIRONMENTAL SCIENCES↗
vdisquants: Video Distrometer derived radar equivalent quantities. Retrievals from the VDIS instrument providing radar equivalent quantities, including dual polarization radar quantities (e.g., Z, Differential Reflectivity ZDR).
1. Provide cleaned and filtered data stream from multiple ARM disdrometers; 2. Estimate commonly-used physical parameters of the Drop Size Distribution (DSD). 3. Calculate radar equivalent quantities such as the Radar Reflectivity Factor Z.
54 ENVIRONMENTAL SCIENCES↗