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DOE OSTI2020

Probability Density Function Control for Stochastic Nonlinear Systems using Monte Carlo Simulation

This paper presents a fast implementation framework of output probability density function (PDF) control for a class of stochastic nonlinear systems which are subjected to non-Gaussian noises. The statistical properties of the system outputs can be adjusted by shaping the dynamic output probability density function to track the reference stochastic distribution. However, the dynamic probability density function evolution is very difficult to obtain analytically even if the system model and the stochastic distributions of the noises are known. Motivated by Monte Carlo simulation, the dynamic probability density function can be estimated by sampling data which forms the contribution of this paper. In particular, the sampling points are generated following the stochastic distribution of the noise for each instant. These points go through the system would generate the histogram for system outputs, then the dynamic model can be established based on the dynamic histogram which reflects the randomness and the nonlinear dynamics of the investigated system. Based on the established model, the output probability density function tracking can be achieved and the simulation results and discussions show the effectiveness and benefits of the presented framework.

Zhang, Qichun↗

DOE OSTI2025

The DESI DR1 Peculiar Velocity Survey: Growth Rate Measurements from the Galaxy Power Spectrum

The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cross-power spectrum model to accommodate scenarios where the density and momentum fields are derived from distinct galaxy surveys. The growth rate of the large-scale structures of the Universe, commonly represented as $fσ_8$, is extracted by jointly fitting the monopole and quadrupole moments of the auto-density power spectrum, the monopole of the auto-momentum power spectrum, and the dipole of the cross-power spectrum. Our estimators, theoretical models and parameter-fitting framework have been tested using mocks, confirming their robustness and accuracy in retrieving the fiducial growth rate from simulation. These techniques are then applied to analyze the power spectrum of the DESI Bright Galaxy Survey and Peculiar Velocity Survey, and the fit result of the growth rate is $fσ_8=0.440^{+0.080}_{-0.096}$ at effective redshift $z_{\rm eff}=0.07$. By synthesizing the fitting outcomes from correlation functions, maximum likelihood estimation and power spectrum, yields a consensus value of $fσ_8(z_{\rm eff}=0.07) = 0.450 ^{+0.055}_{-0.055}$, and correspondingly we obtain $γ=0.580^{+0.110}_{-0.110}$, $Ω_\mathrm{m}=0.301^{+0.011}_{-0.011}$ and $σ_8=0.834^{+0.032}_{-0.032}$. The measured $fσ_8$ and $γ$ are consistent with the prediction of the $Λ$ Cold Dark Matter Model and General Relativity.

Qin, F. [Marseille, CPPM] (ORCID:0000000179507864)↗

DOE OSTI2020

Capacitor Voltage Ripple Estimation and Optimal Sizing of Modular Multi-Level Converters for Variable-Speed Drives

This article deals with the sizing of submodule capacitors for modular multilevel converters (MMCs) used for variable speed drives for medium voltage and high voltage electric machines. Variable speed drives are required to run over a wide frequency range from zero to a few hundred Hz or even over 1 kHz. Under low frequency operation (<30 Hz), a large current ripple flowing through the MMC submodule capacitors will cause significant capacitor voltage fluctuation. This article proposes an optimal submodule capacitor selection method based on the common-mode voltage injection. The proposed sizing model includes two functions: 1) accurately estimating the capacitor voltage ripple based on the drive system parameters; and 2) identifying the minimum capacitance of the submodule capacitors based on the allowed maximum capacitor voltage fluctuations. Simulation and experimental results show that the error between the actual and estimated values of the voltage fluctuation is within 3% using the proposed model.

42 ENGINEERING↗

NASA NTRS2023

Understanding Volume Estimation Uncertainty of Lakes and Wetlands Using Satellites and Citizen Science

We studied variations in the volume of water stored in small lakes and wetlands using satellite remote sensing and lake water height data contributed by citizen scientists. A total of 94 water bodies across the globe were studied using satellite data in the optical and microwave wavelengths from Landsat 8, Sentinel-1, and Sentinel-2. The uncertainty in volume estimation as a function of geography and geophysical factors, such as cloud cover, precipitation, and water surface temperature, was studied. The key finding that emerged from this global study is that uncertainty is highest in regions with a distinct precipitation season, such as in the monsoon dominated South Asia or the Pacific Northwestern region of the USA. This uncertainty is further compounded when small lakes and wetlands are seasonal with alternating land use as a water body and agricultural land, such as the wetlands of Northeastern Bangladesh. On an average, 45% of studied lakes could be estimated of their volume change with a statistical significant uncertainty that is less than the expected volume in South Asia. In North America, this statistically significant uncertainty in volume estimation was found to be around 50% in lakes eastward of the 108th meridian with lowest uncertainty found in lakes along the East coast of the USA. The article provides a baseline for understanding the current state of the art in estimating volumetric change of lakes and wetlands using citizen science in anticipation of the recently launched Surface Water and Ocean Topography Mission.

Shahzaib Khan↗

NASA NTRS1995

Revised predictions of long-period ocean tidal effects on Earth's rotation rate

The rotational response of Earth to long-period tidal forces, embodied in a 'zonal response function,' can be expected to vary with frequency because of variable contributions by the oceans, mantle, and core. The zonal response function has been estimated from 9 years of International Radio Interferometric Surveying (IRIS) universal time (UT1) data and compared with theoretical predictions, using a spherical harmonic tide model to compute the oceans' dynamic response, at semiannual, monthly, fortnightly, and 9-day lunisolar tidal frequencies. Different amounts of mantle anelasticity have been considered for both the oceanic and soild earth responses; predictions have been made assuming axial core-mantle coupling which is either complete or absent. Additionally, an extensive recalibration of the ocean model's frictional parameters was performed using constraints derived in part from Space92 polar motion data; zonal response function predictions have also been made employing this recalibrated ocean tide model. Our results indicate that any amount of core coupling can be ruled out at a fortnightly period and probably at a 9-day period, but not at a monthly period. Our results also suggest that the mantle responds purely elastically at a 9-day period but may behave increasingly anelastically at longer periods. A simple dispersive rule is postulated for periods ranging up to the 14-month Chandler wobble period.

Dickman, S. R.↗

NASA NTRSDate not supplied

Perceptual Attributes of eVTOL Noise Noticeability and Blend with Reference to the Ambient

In most prior laboratory research, studies of human response to aircraft and rotorcraft noise have emphasized annoyance ratings, usually as a function of level. Estimates of detection and noticeability have also been addressed, e.g. in surveys of community response. This presentation explores an alternative subjective criterion, based on an average threshold where trained subjects estimate the level at which a new auditory object (an eVTOL event) “blends” into the existing ambient, as an experimentally defined threshold of acceptance. Contrasting an annoyance rating, subjects rate the level at which sound is no more significant than any other sound source in ambient, with a prescribed attitude focusing on the acceptance of an inevitable new transportation source with positive attributes for the community. The approach utilizes manipulations of ambient type as an experimental variable, using spatially veridical recordings in the laboratory. In one example, the method of limits can be used for determining blend as a function of eVTOL level; other manipulations include the spatial trajectory of the eVTOL relative to the listener, and/or manipulations of its tonal spectra. It is likely that a “blend” threshold lies somewhere between a detection and annoyance threshold as a function of level.

urban air mobility↗

DOE OSTI2018

Estimation of volume-weighted average grain size in Fe-based nanocrystalline soft magnetic materials by autocorrelation function

Highlights: • Normalized ACF of TEM images estimates the volume-weighted average grain size. • Grain size estimation by normalized ACF shows good accuracy and time efficiency. • Normalized ACF can reveal grain size difference in different areas of a TEM sample. • Normalized ACF helps modelling of grain size distributions in Fe-B nanostructures. - Abstract: The coercivity of Fe-based nanocrystalline soft magnetic materials depends critically on the grain size of bcc-Fe grains. Accurately estimating the volume-weighted mean grain size is extremely important to develop new Fe-based nanocrystalline soft magnetic materials with low coercivity. This article shows that autocorrelation analysis of dark-field transmission electron microscope (TEM) images provides a very good estimation of bcc-Fe grain size in nanocrystalline soft magnetic materials. This method can be used to efficiently estimate the volume-weighted average grain size from multiple TEM images with much less inherent bias than manual measurement techniques. The estimated grain sizes show good consistency to the grain sizes estimated by X-ray diffraction (XRD) and manual measurement. In contrast to XRD, this method can also reveal the differences in grain size from different micron-sized regions of a sample.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Using ultrasonic attenuation in cortical bone to infer distributions on pore size

Here, in this work we infer the underlying distribution on pore radius in human cortical bone samples using ultrasonic attenuation data. We first discuss how to formulate polydisperse attenuation models using a probabilistic approach and the Waterman Truell model for scattering attenuation. We then compare the Independent Scattering Approximation and the higher-order Waterman Truell models’ forward predictions for total attenuation in polydisperse samples. Following this, we formulate an inverse problem under the Prohorov Metric Framework coupled with variational regularization to stabilize this inverse problem. We then use experimental attenuation data taken from human cadaver samples and solve inverse problems resulting in nonparametric estimates of the probability density function on pore radius. We compare these estimates to the “true” microstructure of the bone samples determined via microCT imaging. We find that our methodology allows us to reliably estimate the underlying microstructure of the bone from attenuation data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Making Steppingstones out of Stumbling Blocks: A Bayesian Model Evidence Estimator with Application to Groundwater Transport Model Selection

Bayesian model evidence (BME) is a measure of the average fit of a model to observation data given all the parameter values that the model can assume. By accounting for the trade-off between goodness-of-fit and model complexity, BME is used for model selection and model averaging purposes. For strict Bayesian computation, the theoretically unbiased Monte Carlo based numerical estimators are preferred over semi-analytical solutions. This study examines five BME numerical estimators and asks how accurate estimation of the BME is important for penalizing model complexity. The limiting cases for numerical BME estimators are the prior sampling arithmetic mean estimator (AM) and the posterior sampling harmonic mean (HM) estimator, which are straightforward to implement, yet they result in underestimation and overestimation, respectively. We also consider the path sampling methods of thermodynamic integration (TI) and steppingstone sampling (SS) that sample multiple intermediate distributions that link the prior and the posterior. Although TI and SS are theoretically unbiased estimators, they could have a bias in practice arising from numerical implementation. For example, sampling errors of some intermediate distributions can introduce bias. We propose a variant of SS, namely the multiple one-steppingstone sampling (MOSS) that is less sensitive to sampling errors. We evaluate these five estimators using a groundwater transport model selection problem. SS and MOSS give the least biased BME estimation at an efficient computational cost. If the estimated BME has a bias that covariates with the true BME, this would not be a problem because we are interested in BME ratios and not their absolute values. On the contrary, the results show that BME estimation bias can be a function of model complexity. Thus, biased BME estimation results in inaccurate penalization of more complex models, which changes the model ranking. This was less observed with SS and MOSS as with the three other methods.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1994

Effect of land use change on the carbon cycle in Amazon soils

The overall goal of this study was to provide a quantitative understanding of the cycling of carbon in the soils associated with deep-rooting Amazon forests. In particular, we wished to apply the understanding gained by answering two questions: (1) what changes will accompany the major land use change in this region, the conversion of forest to pasture? and (2) what is the role of carbon stored deeper than one meter in depth in these soils? To construct carbon budgets for pasture and forest soils we combined the following: measurements of carbon stocks in above-ground vegetation, root biomass, detritus, and soil organic matter; rates of carbon inputs to soil and detrital layers using litterfall collection and sequential coring to estimate fine root turnover; C-14 analyses of fractionated SOM and soil CO2 to estimate residence times; C-13 analyses to estimate C inputs to pasture soils from C-4 grasses; soil pCO2, volumetric water content, and radon gradients to estimate CO2 production as a function of soil depth; soil respiration to estimate total C outputs; and a model of soil C dynamics that defines SOM fractions cycling on annual, decadal, and millennial time scales.

Trumbore, Susan E.↗

NASA NTRS2002

Global Surface Temperature Change and Uncertainties Since 1861

The objective of this talk is to analyze the warming trend and its uncertainties of the global and hemi-spheric surface temperatures. By the method of statistical optimal averaging scheme, the land surface air temperature and sea surface temperature observational data are used to compute the spatial average annual mean surface air temperature. The optimal averaging method is derived from the minimization of the mean square error between the true and estimated averages and uses the empirical orthogonal functions. The method can accurately estimate the errors of the spatial average due to observational gaps and random measurement errors. In addition, quantified are three independent uncertainty factors: urbanization, change of the in situ observational practices and sea surface temperature data corrections. Based on these uncertainties, the best linear fit to annual global surface temperature gives an increase of 0.61 +/- 0.16 C between 1861 and 2000. This lecture will also touch the topics on the impact of global change on nature and environment. as well as the latest assessment methods for the attributions of global change.

Shen, Samuel S. P.↗

NASA NTRS2005

Aerodynamic Parameter Estimation for the X-43A (Hyper-X) from Flight Data

Aerodynamic parameters were estimated based on flight data from the third flight of the X-43A hypersonic research vehicle, also called Hyper-X. Maneuvers were flown using multiple orthogonal phase-optimized sweep inputs applied as simultaneous control surface perturbations at Mach 8, 7, 6, 5, 4, and 3 during the vehicle descent. Aerodynamic parameters, consisting of non-dimensional longitudinal and lateral stability and control derivatives, were estimated from flight data at each Mach number. Multi-step inputs at nearly the same flight conditions were also flown to assess the prediction capability of the identified models. Prediction errors were found to be comparable in magnitude to the modeling errors, which indicates accurate modeling. Aerodynamic parameter estimates were plotted as a function of Mach number, and compared with estimates from the pre-flight aerodynamic database, which was based on wind-tunnel tests and computational fluid dynamics. Agreement between flight estimates and values computed from the aerodynamic database was excellent overall.

Morelli, Eugene A.↗

NASA NTRS2015

Dose Calibration of the ISS-RAD Fast Neutron Detector

The ISS-RAD instrument has been fabricated by Southwest Research Institute and delivered to NASA for flight to the ISS in late 2015 or early 2016. ISS-RAD is essentially two instruments that share a common interface to ISS. The two instruments are the Charged Particle Detector (CPD), which is very similar to the MSL-RAD detector on Mars, and the Fast Neutron Detector (FND), which is a boron-loaded plastic scintillator with readout optimized for the 0.5 to 10 MeV energy range. As the FND is completely new, it has been necessary to develop methodology to allow it to be used to measure the neutron dose and dose equivalent. This talk will focus on the methods developed and their implementation using calibration data obtained in quasi-monoenergetic (QMN) neutron fields at the PTB facility in Braunschweig, Germany. The QMN data allow us to determine an approximate response function, from which we estimate dose and dose equivalent contributions per detected neutron as a function of the pulse height. We refer to these as the "pSv per count" curves for dose equivalent and the "pGy per count" curves for dose. The FND is required to provide a dose equivalent measurement with an accuracy of 10% of the known value in a calibrated AmBe field. Four variants of the analysis method were developed, corresponding to two different approximations of the pSv per count curve, and two different implementations, one for real-time analysis onboard ISS and one for ground analysis. We will show that the preferred method, when applied in either real-time or ground analysis, yields good accuracy for the AmBe field. We find that the real-time algorithm is more susceptible to chance-coincidence background than is the algorithm used in ground analysis, so that the best estimates will come from the latter.

Zeitlin, C.↗

DOE OSTI2026

CO 2 Sorption in Moisture Swing Anion Exchange Resins for Direct Air Capture: Experimental Isotherm Determination and Modeling

Moisture swing (MS) sorption is a promising direct air capture (DAC) technology to achieve negative CO 2 emissions and counter global warming. Here, in this study, MS CO 2 sorption in a model MS sorbent, IRA900, was investigated. IRA900 is a macroporous commercial strong-base anion exchange resin (AER) with quaternary ammonium functional groups. A rigorous CO 2 desorption process was developed to desorb all CO 2 from the sample and obtain CO 2 sorption isotherms as a function of relative humidity, CO 2 partial pressure, and temperature. CO 2 sorption increased with decreasing relative humidity, decreasing temperature, and increasing CO 2 partial pressure. Remarkably, the total CO 2 uptake from the sorption isotherms matched the ion exchange capacity (IEC) of the material, suggesting a stoichiometry of one CO 2 molecule reacting per active site. An isotherm model for CO 2 sorption starting with empty sorption sites (i.e., with the AER in the OH – form) described the experimental data well, supporting the hypothesis that the bicarbonate-loaded AER fully unloaded to the OH – state following rigorous CO 2 desorption. CO 2 sorption kinetics were studied, and carbon diffusion coefficients were estimated as a function of %RH and CO 2 partial pressure. Overall, this study provides a roadmap for the systematic evaluation of MS CO 2 DAC materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Relationships between the Stellar, Gaseous, and Star Formation Disks in LITTLE THINGS Dwarf Irregular Galaxies: Indirect Evidence for Substantial Fractions of Dark Molecular Gas

The stellar, gaseous and young stellar disks in the LITTLE THINGS sample of nearby dwarf irregular galaxies are fitted with functions to search for correlations between the parameters. We find that the H i radial profiles are generally flatter in the center and fall faster in the outer regions than the V-band profiles, while young stars are more centrally concentrated, especially if the H i is more centrally flat. This pattern suggests that the H i is turning into molecules in the center, and the molecular clouds are forming stars and FUV. A model that assumes the molecular surface density is proportional to the total gas surface density to a power of 1.5 or 2, in analogy with the Kennicutt–Schmidt relation, reproduces the relationship between the ratio of the visible to the H i scale length and the H i Sérsic index. The molecular fraction is estimated as a function of radius for each galaxy by converting the FUV to a molecular surface density using conventional calibrations. The average molecular fraction inside 3R {sub D} is 23% ± 17%. However, the break in the stellar surface brightness profile has no unified tracer related to star formation.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1989

Automated frequency domain system identification of a large space structure

This paper presents the development and experimental results of an automated on-orbit system identification method for large flexible spacecraft that yields estimated quantities to support on-line design and tuning of robust high performance control systems. The procedure consists of applying an input to the plant, obtaining an output, and then conducting nonparametric identification to yield the spectral estimate of the system transfer function. A parametric model is determined by curve fitting the spectral estimate to a rational transfer function. The identification method has been demonstrated experimentally on the Large Spacecraft Control Laboratory in JPL.

Yam, Y.↗

NASA NTRSDate not supplied

Hybrid NEP-Chemical Vehicle and Propulsion Technology Study for Crewed Mars Missions

Nuclear Electric Propulsion (NEP) is a suite of technologies with the potential to enable crewed opposition-class missions to Mars. Each subsystem comprising an NEP system has multiple technology options that present tradeoffs in vehicle sizing and technology development risk. Multiple vehicle concepts have been studied in the past and are currently being studied at NASA. Three models have been developed to illustrate the impact of key technology parameters on overall sizing for a crewed Mars transportation vehicle. Vehicle mass required to close the mission as a function of NEP system alpha (kWe/kg) and specific impulse (Isp) is estimated with a detailed trajectory model. A power system mass model estimates alpha as a function of power and radiator mass assumption. A power conversion system thermodynamic model predicts the radiator area required to close a Brayton cycle power conversion system. Combined with the architecture mass required for mission closure, the radiator area and alpha model provide insight into how technology development may impact the mission. Our focus is on parametric sweeps of the whole design space rather than any particular point design. Results from the mission model comparing electric propulsion technology (Hall, Ion, Magnetoplasmadynamic) and both 2039 and 2042 opposition-class mission launch windows are included. The results of the study illustrate the technology parameters that can result in mission closure and illustrate where the architecture is sensitive to variations in technology performance or requirements.

Matthew Duchek↗