Search NASA⌕ Search

SEARCH · Search NASA

Results for “Function 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.

At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

The Ages of the Thin Disk, Thick Disk, and the Halo from Nearby White Dwarfs

We present a detailed analysis of the white dwarf luminosity functions derived from the local 40 pc sample and the deep proper motion catalog of Munn et al. Many previous studies have ignored the contribution of thick disk white dwarfs to the Galactic disk luminosity function, which results in an erroneous age measurement. We demonstrate that the ratio of thick/thin disk white dwarfs is roughly 20% in the local sample. Simultaneously fitting for both disk components, we derive ages of 6.8–7.0 Gyr for the thin disk and 8.7 ± 0.1 Gyr for the thick disk from the local 40 pc sample. Similarly, we derive ages of 7.4–8.2 Gyr for the thin disk and 9.5–9.9 Gyr for the thick disk from the deep proper motion catalog, which shows no evidence of a deviation from a constant star formation rate in the past 2.5 Gyr. We constrain the time difference between the onset of star formation in the thin disk and the thick disk to be 1.6{sub −0.4}{sup +0.3} Gyr. The faint end of the luminosity function for the halo white dwarfs is less constrained, resulting in an age estimate of 12.5{sub −3.4}{sup +1.4} Gyr for the Galactic inner halo. This is the first time that ages for all three major components of the Galaxy have been obtained from a sample of field white dwarfs that is large enough to contain significant numbers of disk and halo objects. The resultant ages agree reasonably well with the age estimates for the oldest open and globular clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Seasonal variations in fire conditions are important drivers in the trend of aerosol optical properties over the south-eastern Atlantic

Abstract. From June to October, southern Africa produces one-third of the global biomass burning (BB) emissions by widespread fires. BB aerosols are transported westward over the south-eastern Atlantic with the mid-tropospheric winds, resulting in significant radiative effects. Ascension Island (ASI) is located midway between Africa and South America. From June 2016 to October 2017, a 17-month in situ observation campaign on ASI found a low single-scattering albedo (SSA) as well as a high mass absorption cross-section of black carbon (MACBC), demonstrating the strong absorbing marine boundary layer in the south-eastern Atlantic. Here we investigate the monthly variations of critical optical properties of BB aerosols, i.e. SSA and MACBC, during the BB seasons and the driving factors behind these variations. Both SSA and MACBC increase from June to August and decrease in September and October. The average SSA during the BB seasons is 0.81 at 529 nm wavelength, with the highest mean ∼ 0.85 in October and the lowest ∼ 0.78 in August. The absorption enhancement (Eabs) derived from the MACBC shows similar trends with SSA, with the average during the whole of the BB seasons at ∼ 1.96 and ∼ 2.07 in 2016 and 2017, respectively. As the Eabs is higher than the ∼ 1.5 commonly adopted value by climate models, this result suggests the marine boundary layer in the south-eastern Atlantic is more absorbing than model simulations. We find the enhanced ratio of BC to CO (ΔBC/ΔCO, equal to BC/ΔCO as the BC background concentration is considered to be 0) is well correlated with SSA and MACBC, providing a simple way to estimate the aerosol optical characteristics in the south-eastern Atlantic. The exponential function we proposed can approximate SSA and MACBC with BC/ΔCO, and when BC/ΔCO is small it can capture the rapid growth of SSA as BC/ΔCO decreases. BC/ΔCO is influenced by combustion conditions and aerosol scavenging. From the analysis of the location of BB, the primary source fuel, the water content in the fuel, combined with the mean cloud cover and precipitation in the transport areas of the BB plume, we conclude that the increase in BC/ΔCO from June to August is likely to be caused by burning becoming more flaming. The reduction in the water content of fuels may be responsible for the change in the burning conditions from June to August. The decrease in BC/ΔCO in September and October may be caused by two factors, one being a lower proportion of flaming conditions, possibly associated with a decrease in mean surface wind speed in the burning area, and the other being an increase in precipitation in the BB transport pathway, leading to enhanced aerosol scavenging, which ultimately results in an increase in SSA and MACBC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Large-eddy simulations of surface roughness parameter sensitivity to canopy-structure characteristics

Surface roughness parameters, namely the roughness length and displacement height, are an integral input used to model surface fluxes. However, most models assume these parameters to be a fixed property of plant functional type and disregard the governing structural heterogeneity and dynamics. In this study, we use large-eddy simulations to explore, in silico, the effects of canopy-structure characteristics on surface roughness parameters. We performed a virtual experiment to test the sensitivity of resolved surface roughness to four axes of canopy structure: (1) leaf area index, (2) the vertical profile of leaf density, (3) canopy height, and (4) canopy gap fraction. We found roughness parameters to be highly variable, but uncovered positive relationships between displacement height and maximum canopy height, aerodynamic canopy height and maximum canopy height and leaf area index, and eddy-penetration depth and gap fraction. We also found negative relationships between aerodynamic canopy height and gap fraction, as well as between eddy-penetration depth and maximum canopy height and leaf area index. We generalized our model results into a virtual "biometric" parameterization that relates roughness length and displacement height to canopy height, leaf area index, and gap fraction. Using a decade of wind and canopy-structure observations in a site in Michigan, we tested the effectiveness of our model-driven biometric parameterization approach in predicting the friction velocity over heterogeneous and disturbed canopies. We compared the accuracy of these predictions with the friction-velocity predictions obtained from the common simple approximation related to canopy height, the values calculated with large-eddy simulations of the explicit canopy structure as measured by airborne and ground-based lidar, two other parameterization approaches that utilize varying canopy-structure inputs, and the annual and decadal means of the surface roughness parameters at the site from meteorological observations. We found that the classical representation of constant roughness parameters (in space and time) as a fraction of canopy height performed relatively well. Nonetheless, of the approaches we tested, most of the empirical approaches that incorporate seasonal and interannual variation of roughness length and displacement height as a function of the dynamics of canopy structure produced more precise and less biased estimates for friction velocity than models with temporally invariable parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

10 Megawatts Electric Coal Direct Chemical Looping Large Pilot Plant - Pre-Front End Engineering and Design Study

The Peer Review presentation covered the following items: Perform pilot studies to obtain design information. Perform a pre-FEED study of a modular 10 MWeCDCL pilot plant. Provide Functional specifications for integration with host site. Provide risk assessment, schedule and cost estimate for fabrication, construction and testing. Update commercial 550 MWeCDCL plant design and economic analysis

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Impedance-Based State-of-Health Estimation for Lithium-Ion Battery Management Systems

This paper discusses an impedance-based state-of-health (SOH) estimation for lithium-ion battery management systems. Features obtained from the Nyquist plot of the electrochemical impedance spectroscopy (EIS) are utilized to estimate the SOH. Two commercial lithium-ion batteries were aged (cycled) in the laboratory to collect aging and impedance data. An algorithm for SOH estimation is presented and evaluated. The performance evaluation results show that the SOH features extracted from the Nyquist plot can be utilized for SOH estimation. Estimated SOH values can be then utilized in various battery management systems (BMS) functions such as for calibrating the available capacity, adjusting charging/discharging strategies, and protection.

Al-Smadi, Mohammad↗
DOE OSTI2014

The potential of positron emission tomography for intratreatment dynamic lung tumor tracking: A phantom study

Purpose: This study aims to evaluate the potential and feasibility of positron emission tomography for dynamic lung tumor tracking during radiation treatment. The authors propose a center of mass (CoM) tumor tracking algorithm using gated-PET images combined with a respiratory monitor and investigate the geometric accuracy of the proposed algorithm. Methods: The proposed PET dynamic lung tumor tracking algorithm estimated the target position information through the CoM of the segmented target volume on gated PET images reconstructed from accumulated coincidence events. The information was continuously updated throughout a scan based on the assumption that real-time processing was supported (actual processing time at each frame ≈10 s). External respiratory motion and list-mode PET data were acquired from a phantom programmed to move with measured respiratory traces (external respiratory motion and internal target motion) from human subjects, for which the ground truth target position was known as a function of time. The phantom was cylindrical with six hollow sphere targets (10, 13, 17, 22, 28, and 37 mm in diameter). The measured respiratory traces consisted of two sets: (1) 1D-measured motion from ten healthy volunteers and (2) 3D-measured motion from four lung cancer patients. The authors evaluated the geometric accuracy of the proposed algorithm by quantifying estimation errors (Euclidean distance) between the actual motion of targets (1D-motion and 3D-motion traces) and CoM trajectories estimated by the proposed algorithm as a function of time. Results: The time-averaged error of 1D-motion traces over all trajectories of all targets was 1.6 mm. The error trajectories decreased with time as coincidence events were accumulated. The overall error trajectory of 1D-motion traces converged to within 2 mm in approximately 90 s. As expected, more accurate results were obtained for larger targets. For example, for the 37 mm target, the average error over all 1D-motion traces was 1.1 mm; and for the 10 mm target, the average error over all 1D-motion traces was 2.8 mm. The overall time-averaged error of 3D-motion traces was 1.6 mm, which was comparable to that of the 1D-motion traces. There were small variations in the errors between the 3D-motion traces, although the motion trajectories were very different. The accuracy of the estimates was consistent for all targets except for the smallest. Conclusions: The authors developed an algorithm for dynamic lung tumor tracking using list-mode PET data and a respiratory motion signal, and demonstrated proof-of-principle for PET-guided lung tumor tracking. The overall tracking error in phantom studies is less than 2 mm.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Bootstrap-based confidence interval estimation for thermal security region of bulk power grid

Thermal security region (TSR) is a powerful tool for monitoring and controlling the thermal security of bulk power grid with high penetration of renewable energy. One of the major challenges of TSR in practical application is to obtain the exact analytical expression of the TSR boundary (TSRB) because TSRB is a nonlinear hypersurface described by an implicit function. For this reason, the TSRB is usually approximated by hyperplane instead of getting the exact analytical expression. Traditionally, the coefficients of the hyperplane are estimated with a set of original TSRB points using least square estimation (LSE). However, LSE is a point estimation method, which is incapable of evaluating the quality of the estimation. In addition, the accuracy and computational efficiency of the hyperplane approximation are influenced by the number of TSRB points significantly. Here, a bootstrap based confidence interval estimation is proposed to estimate not only the coefficients of TSRB approximation hyperplane, but also the standard deviations and confidence intervals of the coefficients for evaluating the quality and reliability of the approximation results. First, empirical distribution functions (EDFs) of the coefficients of TSRB approximation hyperplane are approximated from a set of original TSRB points by using residual resampling bootstrap method. Then, the EDFs of the coefficients are employed to estimate the coefficients of the approximation hyperplane. Meanwhile, the standard deviations and confidence intervals of the estimated coefficients of the hyperplanes are also calculated for evaluating the quality and reliability of the approximation. The proposed approach is tested on the China Southern Power Grid (CSG). Results of simulations validate the accuracy and efficiency of the proposed approach in approximating the TSRB.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Cardiac myosin activation with 2-deoxy-ATP via increased electrostatic interactions with actin

The naturally occurring nucleotide 2-deoxy-adenosine 5'-triphosphate (dATP) can be used by cardiac muscle as an alternative energy substrate for myosin chemomechanical activity. We and others have previously shown that dATP increases contractile force in normal hearts and models of depressed systolic function, but the structural basis of these effects has remained unresolved. In this work, we combine multiple techniques to provide structural and functional information at the angstrom-nanometer and millisecond time scales, demonstrating the ability to make both structural measurements and quantitative kinetic estimates of weak actin–myosin interactions that underpin sarcomere dynamics. Exploiting dATP as a molecular probe, we assess how small changes in myosin structure translate to electrostatic-based changes in sarcomere function to augment contractility in cardiac muscle. Through Brownian dynamics simulation and computational structural analysis, we found that deoxy-hydrolysis products [2-deoxy-adenosine 5′-diphosphate (dADP) and inorganic phosphate (Pi)] bound to prepowerstroke myosin induce an allosteric restructuring of the actin-binding surface on myosin to increase the rate of cross-bridge formation. We then show experimentally that this predicted effect translates into increased electrostatic interactions between actin and cardiac myosin in vitro. Finally, using small-angle X-ray diffraction analysis of sarcomere structure, we demonstrate that the proposed increased electrostatic affinity of myosin for actin causes a disruption of the resting conformation of myosin motors, resulting in their repositioning toward the thin filament before activation. The dATP-mediated structural alterations in myosin reported here may provide insight into an improved criterion for the design or selection of small molecules to be developed as therapeutic agents to treat systolic dysfunction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Fracture mechanics approach to estimate fatigue lives of welded lap-shear specimens

A full range of stress intensity factor solutions for a kinked crack with finite length is developed as a function of weld width and the sheet thickness. When used with the main crack solutions (global stress intensity factors) in terms of the applied load and the specimen geometric parameters, the fatigue lived of the kinked crack can be estimated for the laser-welded lap-shear specimens. The predicted curve for the load range-fatigue life passes through the cluster of experimental data and is in good agreement. A classical solution associated with an infinitesimal kink is also employed. Furthermore, its life prediction tends to overestimate the actual fatigue life. In addition, the traditional fatigue life estimation based on structural stress is performed for completeness. As a result, this non-fracture mechanics approach only agrees well with the experimental data under high cyclic load conditions.

42 ENGINEERING↗
DOE OSTI2018

The Volumetric Coefficient of Thermal Expansion of PBX 9502

TATB (1,3,5-triamino-2,4,6-trinitrobenzene) is an insensitive high explosive (IHE) used in plastic-bonded explosives (PBXs) such as PBX 9502. TATB’s plate-like crystals have highly anisotropic coefficient of thermal expansion (CTE) values, where the through-plane direction grows about twice as much as the in-plane directions. Compactions of TATB have preferred alignment of crystals, with resulting CTE anisotropy. Additionally, TATB-based compactions exhibit anisotropic irreversible volume expansion (ratchet growth) when thermal cycled to temperatures away from ambient. From a series of measurements on a thermal mechanical analyzer (TMA), the initial thermal ramps away from ambient were used to estimate the volumetric coefficient of thermal expansion of PBX 9502. The TMA measures the change in axial strain of the material as a function of temperature. Starting at ambient, thermal ramps of 1°C per minute were conducted to various endpoint temperatures from -43°C to 173°C on specimens machined from isostatically-pressed hemispheres of PBX 9502. Anisotropy was measured and the volumetric CTE estimated over this temperature range. For ease of use by experimentalists, a 5th-order polynomial was fit to the calculated change in density as a function of temperature. The CTE of neat TATB, PBX 9502, and the Kel-F binder were compared over the given temperature range. At lower temperatures, TATB expands more than PBX 9502 until the melt temperature of Kel-F (80°C), above which the two exhibit similar CTE values.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Gearbox bearing crack growth prognostics and uncertainty quantification with physics-informed machine learning

This paper introduces the extreme theory of functional connections (X-TFC), a physics-informed machine learning algorithm, and tailors it to estimate the remaining useful life (RUL) of wind turbine gearbox bearings experiencing fatigue crack growth. Unlike purely data-driven methods, X-TFC embeds a physics model, based on Head's theory in this work, into its training objective. The core of X-TFC is a random-projection single-layer neural network trained via an extreme learning machine, which requires only limited damage progression data and solves for output weights with a least-squares optimization algorithm. A composite loss function balances the network's fit to observed degradation data against the residuals of the governing crack growth differential equation, ensuring the learned damage trajectory remains physically plausible. When applied to a vibration-based health-index (HI) dataset measured during the growth of a crack on the inner ring of a high-speed bearing in a wind turbine gearbox (Bechhoefer and Dubé, 2020), X-TFC achieves near-zero prediction bias. Even when trained on only the first 10 %–20 % of the damage progression data, with sufficient physics weighting its predictions remain monotonic and smooth, delivering high prognosability and trendability. To quantify the epistemic uncertainty, we employ a Monte Carlo ensemble of independently initialized X-TFC models trained on noise-perturbed data, which yields confidence intervals around each RUL estimate and captures both model-parameter and epistemic uncertainty. In addition to a vibration-based HI, we demonstrate that the proposed framework can be directly applied to a supervisory control and data acquisition (SCADA) data-based HI (Eftekhari Milani et al., 2026) measured during similar wind turbine gearbox bearing crack faults, preserving its accuracy and interpretability. This extension shows the versatility of our approach, which is applicable to bearings of multiple gearbox manufacturers, models, and ratings using only SCADA data. By integrating domain knowledge with machine learning, X-TFC offers a rapid, reliable tool for crack prognostics. Its adaptability to other bearing failure modes, such as pitch bearing ring cracks, positions X-TFC as a powerful enabler of data-driven, physics-informed asset management in the wind energy sector and beyond.

17 WIND ENERGY↗
DOE OSTI2021

Information Content of the Parity-Violating Asymmetry in Pb 208

The parity-violating asymmetry A PV in 208 Pb, recently measured by the PREX-2 Collaboration, is studied using modern relativistic (covariant) and nonrelativistic energy density functionals. We first assess the theoretical uncertainty on A PV which is intrinsic to the adopted approach. To this end, we use quantified functionals that are able to accommodate our previous knowledge on nuclear observables such as binding energies, charge radii, and the dipole polarizability α D of 208 Pb. We then add the quantified value of A PV together with α D to our calibration dataset to optimize new functionals. Based on these results, we predict a neutron skin thickness in 208 Pb r skin = 0.19 ± 0.02 fm and the symmetry-energy slope L = 54 ± 8 MeV. These values are consistent with other estimates based on astrophysical data and are significantly lower than those recently reported using a particular set of relativistic energy density functionals. Here, we also make a prediction for the A PV value in 48 Ca that will be soon available from the CREX measurement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Baseline effects of transcranial direct current stimulation on glutamatergic neurotransmission and large-scale network connectivity

Transcranial direct current stimulation (tDCS) modulates glutamatergic neurotransmission and can be utilized as a novel treatment intervention for a multitude of populations. However, the exact mechanism by which tDCS modulates the brain's neural architecture, from the micro to macro scales, have yet to be investigated. In this paper, using a within-subjects design, resting-state functional magnetic resonance imaging (rs-fMRI) and proton magnetic resonance spectroscopy ( 1 H MRS) were performed immediately before and after the administration of anodal tDCS over right parietal cortex. Group independent component analysis (ICA) was used to decompose fMRI scans into 75 brain networks, from which 12 resting-state networks were identified that had significant voxel-wise functional connectivity to anatomical regions of interest. 1 H MRS was used to obtain estimates of combined glutamate and glutamine (Glx) concentrations from bilateral intraparietal sulcus. Paired sample t-tests showed significantly increased Glx under the anodal electrode, but not in homologous regions of the contralateral hemisphere. Increases of within-network connectivity were observed within the superior parietal, inferior parietal, left frontal–parietal, salience and cerebellar intrinsic networks, and decreases in connectivity were observed in the anterior cingulate and the basal ganglia ( p <0.05, FDR-corrected). Individual differences in Glx concentrations predicted network connectivity in most of these networks. Finally, the observed relationships between glutamatergic neurotransmission and network connectivity may be used to guide future tDCS protocols that aim to target and alter neuroplastic mechanisms in healthy individuals as well as those with psychiatric and neurologic disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-130: Automating Liver Segmentation Via Combined Global and Local Optimization

Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is supported by NIH/NIBIB (1R01-EB016777), National Natural Science Foundation of China (No.61471226 and No.61201441), Research funding from Shandong Province (No.BS2012DX038 and No.J12LN23), and Research funding from Jinan City (No.201401221 and No.20120109)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

The Γ-convergence of oscillating integrands with nonstandard coercivity and growth conditions

We study the Γ-convergence as ε→0 of a family of integral functionals with integrand f{sub ε}(x,u,∇u), where the integrand oscillates with respect to the space variable x. The integrands satisfy a two-sided power estimate on the coercivity and growth with different exponents. As a consequence, at least two different variational Dirichlet problems can be connected with the same functional. This phenomenon is called Lavrent'ev's effect. We introduce two versions of Γ-convergence corresponding to variational problems of the first and second kind. We find the Γ-limit for the aforementioned family of functionals for problems of both kinds; these may be different. We prove that the Γ-convergence of functionals goes along with the convergence of the energies and minimizers of the variational problems. Bibliography: 23 titles. (paper)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Uncertainty quantification for nuclear density functional theory and information content of new measurements

Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squares optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. In addition, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Surface Charge of the Calcite (104) Terrace Measured by Rb + Adsorption in Aqueous Solutions Using Resonant Anomalous X-ray Reflectivity

Adsorption of Rb+ on the (104) plane of single crystal calcite was investigated to estimate the charge of the ionic crystal calcite – water interface. The adsorbed Rb+ coverage was quantified as a function of Rb concentration (1 – 100 mM) in calcite-saturated solutions at pH 8.3 by using in-situ resonant anomalous X-ray reflectivity in transmission cell geometry. The Rb+ coverages for all solution conditions were small with the maximum ion coverage (Γmax) of 0.12(4) Rb+/nm2 estimated by the best-fit Langmuir isotherm model. This result provides an estimate of the upper limit to the effective surface charge density of about –0.02 C/m2 considering that any Rb+ adsorption to the terrace plane is likely induced by electrostatic attraction. This charge density is significantly lower (by a factor of ≥10) than those estimated from macroscopic measurements, implying that any excess charge likely originates from surface defects.

adsorption↗
DOE OSTI2019

An Adaptive Bayesian Parameter Estimation of a Synchronous Generator Under Gross Errors

Polynomial-chaos-expansion-based surrogate models have recently been advocated in the literature for power system dynamic parameter estimation. Regarding the estimation of the uncertain generator parameters, a Bayesian inference framework has been proposed based on a polynomial-based reduced-order representation of the synchronous machines using assumed parameter values. Then, the non-Gaussian posterior probability distribution functions (pdfs) of these parameters are recovered through the stochastic sampling approach efficiently. However, facing very large parameter errors, the reliability of the surrogate model decreases, yielding biased estimation results. To overcome this problem, here we develop hierarchical Bayesian inference framework that processes the measurements provided by phasor measurement units, while making use of multifidelity surrogates together with the importance sampling method. The latter allows us to estimate in an efficient manner the posterior pdfs of the uncertain parameters through the normalized weights of the prior samples. To improve the accuracy of the posterior pdfs, an adaptive procedure is further adopted in the importance sampling for the gradual evolution of its proposal functions. The new proposals assist in fine-tuning the sample space and thereby help to construct surrogates with higher fidelity. Through an iterative process, this approach is able to estimate accurately and efficiently non-Gaussian posterior pdfs of the uncertain generator parameters subject to gross errors.

42 ENGINEERING↗