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DOE OSTI2016

Critical role of morphology on the dielectric constant of semicrystalline polyolefins

A particularly attractive method to predict the dielectric properties of materials is density functional theory (DFT). While this method is very popular, its large computational requirements allow practical treatments of unit cells with just a small number of atoms in an ordered array, i.e., in a crystalline morphology. By comparing DFT and Molecular Dynamics (MD) simulations on the same ordered arrays of functional polyolefins, we confirm that both methodologies yield identical estimates for the dipole moments and hence the ionic component of the dielectric storage modulus. Additionally, MD simulations of more realistic semi-crystalline morphologies yield estimates for this polar contribution that are in good agreement with the limited experiments in this field. However, these predictions are up to 10 times larger than those for pure crystalline simulations. Here, we show that the constraints provided by the surrounding chains significantly impede dipolar relaxations in the crystalline regions, whereas amorphous chains must sample all configurations to attain their fully isotropic spatial distributions. These results, which suggest that the amorphous phase is the dominant player in the context, argue strongly that the proper polymer morphology needs to be modeled to ensure accurate estimates of the ionic component of the dielectric constant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A three-point velocity estimation method for two-dimensional coarse-grained imaging data

Time delay and velocity estimation methods have been widely studied subjects in the context of signal processing, with applications in many different fields of physics. The velocity of waves or coherent fluctuation structures is commonly estimated as the distance between two measurement points divided by the time lag that maximizes the cross correlation function between the measured signals, but this is demonstrated to result in erroneous estimates for two spatial dimensions. We present an improved method to accurately estimate both components of the velocity vector, relying on three non-aligned measurement points. We introduce a stochastic process describing the fluctuations as a superposition of uncorrelated pulses moving in two dimensions. Using this model, we show that the three-point velocity estimation method, using time delays calculated through cross correlations, yields the exact velocity components when all pulses have the same velocity. The two- and three-point methods are tested on synthetic data generated from realizations of such processes for which the underlying velocity components are known. The results reveal the superiority of the three-point technique. Finally, we demonstrate the applicability of the velocity estimation on gas puff imaging data of strongly intermittent plasma fluctuations due to the radial motion of coherent, blob-like structures at the boundary of the Alcator C-Mod tokamak.

Materials Science↗

NASA NTRS1989

Temperature dependence of attitude sensor coalignments on the Solar Maximum Mission (SMM)

Results are presented on the temperature correlation of the relative coalignment between the fine pointing sun sensor (FPSS) and fixed head star trackers (FHSTs) on the Solar Maximum Mission (SMM). This correlation can be caused by spacecraft electronic and mechanical effects. Routine daily measurements reveal a time dependent sensor coalignment variation. The magnitude of the alignment variation is on the order of 120 arc seconds (arc sec), which greatly exceeds the prelaunch thermal structural analysis estimate of 15 acr sec. Differences between FPSS-only and FHST-only yaw solutions as a function of mission day are correlated with the relevant spacecraft temperature. If unaccounted for, the sensor misalignments due to thermal effects are a significant source of error in attitude determination accuracy. Prominent sources of temperature variation are identified and correlated with the temperature profile observed on the SMM. It was determined that even relatively small changes in spacecraft temperature can affect the coalignments between the attitude hardware on the SMM and the science instrument support plate and that frequent recalibration of sensor alignments is necessary to compensate for this effect. An alterntive to frequent recalibration is to model the variation of alignments as a function of temperature and use this to maintain accurate ground or onboard alignment estimates. These flight data analysis results may be important consierations for prelaunch analysis of future missions.

Pitone, D. S.↗

NASA NTRS1990

The confusion limits to the sensitivity of submillimeter telescopes

The two major sources of confusion that limit the sensitivity of continuum observations at submillimeter wavelengths outside the galactic plane are discussed. One of the sources is the spatial structure of the thermal emission from dust in the Milky Way. The crowding of extragalactic sources at faint levels is the second source of confusion. Estimates of the noise expected from these two types of confusion as a function of wavelength and beam size on the sky are presented and compared to detector and photon noise estimates for proposed spaceborne telescopes.

Helou, George↗

DOE OSTI2025

Validation of the DESI 2024 Lyα forest BAO analysis using synthetic datasets

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-α (Lyα) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift z = 2.33. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Lyα forest BAO measurement presented in [1]. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Lyα forest. The synthetic data sets span a redshift range 1.8 < z < 3.8, and are analyzed using the same framework and pipeline used for the DESI 2024 Lyα forest BAO measurement. To measure BAO, we use both the Lyα auto-correlation and its cross-correlation with quasar positions. We use the mean of correlation functions from the set of DESI DR1 realizations to show that our model is able to recover unbiased measurements of the BAO position. We also fit each mock individually and study the population of BAO fits in order to validate BAO uncertainties and test our method for estimating the covariance matrix of the Lyα forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Lyα forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Active learning with multifidelity modeling for efficient rare event simulation

Here, while multifidelity modeling provides a cost-effective way to conduct uncertainty quantification with computationally expensive models, much greater efficiency can be achieved by adaptively deciding the number of required high-fidelity (HF) simulations, depending on the type and complexity of the problem and the desired accuracy in the results. We propose a framework for active learning with multifidelity modeling emphasizing the efficient estimation of rare events. Our framework works by fusing a low-fidelity (LF) prediction with an HF-inferred correction, filtering the corrected LF prediction to decide whether to call the high-fidelity model, and for enhanced subsequent accuracy, adapting the correction for the LF prediction after every HF model call. The framework does not make any assumptions as to the LF model type or its correlations with the HF model. In addition, for improved robustness when estimating smaller failure probabilities, we propose using dynamic active learning functions that decide when to call the HF model. We demonstrate our framework using several academic case studies (including some high-dimensional problems) and two finite element model case studies: estimating Navier-Stokes velocities using the Stokes approximation and estimating stresses in a transversely isotropic model subjected to displacements via a coarsely meshed isotropic model. Across these case studies, not only did the proposed framework estimate the failure probabilities accurately, but compared with either Monte Carlo or a standard variance reduction method, it also required only a small fraction of the calls to the HF model.

42 ENGINEERING↗

NASA NTRS1982

Asymptotic Expansions and Estimates for the Capillary Problem

The asymptotic properties for the small Bond number B of the equilibrium capillary interface interior to a circular cylindrical tube vertically dipped in an infinite reservoir of liquid are discussed. (The Bond number B is a dimensionless parameter which is the ratio of gravitational to capillary forces.) The formal expansion in powers of B of the solution to the differential equation describing the equilibrium surface (as can be obtained by standard perturbation methods) is proved to be truly asymptotic -- to all orders and uniformly in the variable and parameter gamma, the contact angle. Sequences of general estimates, in closed form, from above and from below, are also given for the solution and related functions. The M-th term in these sequences are asymptotically exact to order m. An idiosyncrasy of the problem, crucial in obtaining these estimates, is the absolute monotonicity of the structural function of the system in integral form.

Brulois, F. P.↗

NASA NTRS1992

Radiation dose to critical body organs for October 1989 proton event

The Geostationary Operational Environmental Satellite (GOES-7) provides high-quality environmental data about the temporal development and energy characteristics of the protons emitted during a solar particle event. The GOES-7 time history of the hourly averaged integral proton flux for various particle kinetic energies are analyzed for the solar proton event occurring October 19-29, 1989. This event is similar to the August 1972 event that has been widely studied to estimate free-space and planetary radiation-protection requirements. By analyzing the time-history data, the dose rates, which can vary over many orders of magnitude in the early phases of the flare, can be estimated as well as the cumulative dose as a function of time. When basic transport results are coupled with detailed body organ thickness distributions calculated with the Computerized Anatomical Man and Computerized Anatomical Female models, the dose rates and cumulative doses to specific organs can be predicted. With these results, the risks of cancer incidence and mortality are estimated for astronauts in free space protected by various water shield thicknesses.

Simonsen, Lisa C.↗

DOE OSTI2017

Mechanistic insights into heterogeneous methane activation

While natural gas is an abundant chemical fuel, its low volumetric energy density has prompted a search for catalysts able to transform methane into more useful chemicals. This search has often been aided through the use of transition state (TS) scaling relationships, which estimate methane activation TS energies as a linear function of a more easily calculated descriptor, such as final state energy, thus avoiding tedious TS energy calculations. It has been shown that methane can be activated via a radical or surface-stabilized pathway, both of which possess a unique TS scaling relationship. Herein, we present a simple model to aid in the prediction of methane activation barriers on heterogeneous catalysts. Analogous to the universal radical TS scaling relationship introduced in a previous publication, we show that a universal TS scaling relationship that transcends catalysts classes also seems to exist for surface-stabilized methane activation if the relevant final state energy is used. We demonstrate that this scaling relationship holds for several reducible and irreducible oxides, promoted metals, and sulfides. By combining the universal scaling relationships for both radical and surface-stabilized methane activation pathways, we show that catalyst reactivity must be considered in addition to catalyst geometry to obtain an accurate estimation for the TS energy. Here, this model can yield fast and accurate predictions of methane activation barriers on a wide range of catalysts, thus accelerating the discovery of more active catalysts for methane conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1994

X-ray clusters from a high-resolution hydrodynamic PPM simulation of the cold dark matter universe

A new three-dimensional hydrodynamic code based on the piecewise parabolic method (PPM) is utilized to compute the distribution of hot gas in the standard Cosmic Background Explorer (COBE)-normalized cold dark matter (CDM) universe. Utilizing periodic boundary conditions, a box with size 85 h(exp-1) Mpc, having cell size 0.31 h(exp-1) Mpc, is followed in a simulation with 270(exp 3)=10(exp 7.3) cells. Adopting standard parameters determined from COBE and light-element nucleosynthesis, Sigma(sub 8)=1.05, Omega(sub b)=0.06, we find the X-ray-emitting clusters, compute the luminosity function at several wavelengths, the temperature distribution, and estimated sizes, as well as the evolution of these quantities with redshift. The results, which are compared with those obtained in the preceding paper (Kang et al. 1994a), may be used in conjuction with ROSAT and other observational data sets. Overall, the results of the two computations are qualitatively very similar with regard to the trends of cluster properties, i.e., how the number density, radius, and temeprature depend on luminosity and redshift. The total luminosity from clusters is approximately a factor of 2 higher using the PPM code (as compared to the 'total variation diminishing' (TVD) code used in the previous paper) with the number of bright clusters higher by a similar factor. The primary conclusions of the prior paper, with regard to the power spectrum of the primeval density perturbations, are strengthened: the standard CDM model, normalized to the COBE microwave detection, predicts too many bright X-ray emitting clusters, by a factor probably in excess of 5. The comparison between observations and theoretical predictions for the evolution of cluster properties, luminosity functions, and size and temperature distributions should provide an important discriminator among competing scenarios for the development of structure in the universe.

Bryan, Greg L.↗

DOE OSTI2019

A Probabilistic Data-Driven Method for Photovoltaic Pseudo-Measurement Generation in Distribution Systems

This paper presents a probabilistic data-driven method to model the uncertainty of distributed photovoltaic (PV) generation to enhance the observability of distribution grids with a high penetration of renewable resources. The proposed method employs a kernel density estimation (KDE) technique to develop the conditional probability density function (PDF) of PV outputs given the time of the day, using the measurement data from observed PV systems. Then time series of output power of unmeasured PV generators, located at the same grid, are generated according to the corresponding PDF and used as pseudo-measurements in distribution system state estimation (DSSE). The proposed model has been tested and verified using real PV data and utility networks.

Yuan, Yuxuan↗

DOE OSTI2024

Unveiling the transferability of PLSR models for leaf trait estimation: lessons from a comprehensive analysis with a novel global dataset

Leaf traits are essential for understanding many physiological and ecological processes. Partial least squares regression (PLSR) models with leaf spectroscopy are widely applied for trait estimation, but their transferability across space, time, and plant functional types (PFTs) remains unclear. We compiled a novel dataset of paired leaf traits and spectra, with 47 393 records for >700 species and eight PFTs at 101 globally distributed locations across multiple seasons. Using this dataset, we conducted an unprecedented comprehensive analysis to assess the transferability of PLSR models in estimating leaf traits. While PLSR models demonstrate commendable performance in predicting chlorophyll content, carotenoid, leaf water, and leaf mass per area prediction within their training data space, their efficacy diminishes when extrapolating to new contexts. Specifically, extrapolating to locations, seasons, and PFTs beyond the training data leads to reduced R 2 (0.12–0.49, 0.15–0.42, and 0.25–0.56) and increased NRMSE (3.58–18.24%, 6.27–11.55%, and 7.0–33.12%) compared with nonspatial random cross-validation. The results underscore the importance of incorporating greater spectral diversity in model training to boost its transferability. These findings highlight potential errors in estimating leaf traits across large spatial domains, diverse PFTs, and time due to biased validation schemes, and provide guidance for future field sampling strategies and remote sensing applications.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2002

Autonomic neural control of dynamic cerebral autoregulation in humans

BACKGROUND: The purpose of the present study was to determine the role of autonomic neural control of dynamic cerebral autoregulation in humans. METHODS AND RESULTS: We measured arterial pressure and cerebral blood flow (CBF) velocity in 12 healthy subjects (aged 29+/-6 years) before and after ganglion blockade with trimethaphan. CBF velocity was measured in the middle cerebral artery using transcranial Doppler. The magnitude of spontaneous changes in mean blood pressure and CBF velocity were quantified by spectral analysis. The transfer function gain, phase, and coherence between these variables were estimated to quantify dynamic cerebral autoregulation. After ganglion blockade, systolic and pulse pressure decreased significantly by 13% and 26%, respectively. CBF velocity decreased by 6% (P<0.05). In the very low frequency range (0.02 to 0.07 Hz), mean blood pressure variability decreased significantly (by 82%), while CBF velocity variability persisted. Thus, transfer function gain increased by 81%. In addition, the phase lead of CBF velocity to arterial pressure diminished. These changes in transfer function gain and phase persisted despite restoration of arterial pressure by infusion of phenylephrine and normalization of mean blood pressure variability by oscillatory lower body negative pressure. CONCLUSIONS: These data suggest that dynamic cerebral autoregulation is altered by ganglion blockade. We speculate that autonomic neural control of the cerebral circulation is tonically active and likely plays a significant role in the regulation of beat-to-beat CBF in humans.

Non-NASA Center↗

NASA NTRS2024

Unveiling the Transferability of PLSR Models for Leaf Trait Estimation: Lessons from a Comprehensive Analysis with a Novel Global Dataset

Leaf traits are essential for understanding many physiological and ecological processes. Partial least-squares regression (PLSR) models with leaf spectroscopy are widely applied for trait estimation, but their transferability across space, time and plant functional types (PFTs) remains unclear. We compiled a novel dataset of paired leaf traits and spectra, with 47,393 records for >700 species and eight PFTs at 101 globally-distributed locations across multiple seasons. Using this dataset, we conducted an unprecedented comprehensive analysis to assess the transferability of PLSR models in estimating leaf traits. While PLSR models demonstrate commendable performance in predicting chlorophyll content, carotenoid, leaf water and leaf mass per area prediction within their training data space, their efficacy diminishes when extrapolating to new contexts. Specifically, extrapolating to locations, seasons, and PFTs beyond the training data leads to reduced R 2 (0.12-0.49, 0.15-0.42, and 0.25-0.56) and increased NRMSE (3.58-18.24%, 6.27-11.55% and 7.0-33.12%) compared to nonspatial random cross-validation (NRCV). The results underscore the importance of incorporating greater spectral diversity in model training to boost its transferability. These findings highlight potential errors in estimating leaf traits across large spatial domains, diverse PFTs and time due to biased validation schemes and provide guidance for future field sampling strategies and remote sensing applications.

Leaf traits↗

NASA NTRS1981

Pressure broadening of oxygen and its implications for cosmic background measurements

The pressure broadening of oxygen transitions at 119 and 425 GHz have been measured in the laboratory for nitrogen and oxygen broadening as a function of temperature. The measured values are significantly different from estimates used by Woody and Richards to obtain a secondary calibration in their cosmic background measurements. The effect of the new determination is to move the calibrated cosmic background further from a Planck function.

Pickett, H. M.↗

NASA NTRS2014

Current Pressure Transducer Application of Model-based Prognostics Using Steady State Conditions

Prognostics is the process of predicting a system's future states, health degradation/wear, and remaining useful life (RUL). This information plays an important role in preventing failure, reducing downtime, scheduling maintenance, and improving system utility. Prognostics relies heavily on wear estimation. In some components, the sensors used to estimate wear may not be fast enough to capture brief transient states that are indicative of wear. For this reason it is beneficial to be capable of detecting and estimating the extent of component wear using steady-state measurements. This paper details a method for estimating component wear using steady-state measurements, describes how this is used to predict future states, and presents a case study of a current/pressure (I/P) Transducer. I/P Transducer nominal and off-nominal behaviors are characterized using a physics-based model, and validated against expected and observed component behavior. This model is used to map observed steady-state responses to corresponding fault parameter values in the form of a lookup table. This method was chosen because of its fast, efficient nature, and its ability to be applied to both linear and non-linear systems. Using measurements of the steady state output, and the lookup table, wear is estimated. A regression is used to estimate the wear propagation parameter and characterize the damage progression function, which are used to predict future states and the remaining useful life of the system.

Fault Estimation↗

DOE OSTI2021

Investigations on the electronic properties and effect of chitosan capping on the structural and optical properties of zinc aluminate quantum dots

Quantum confined uncapped and chitosan capped nanoparticles of ZnAl 2 O 4 synthesized by microwave-assisted sol–gel method were investigated by structural analysis and optical techniques. X-ray diffraction studies confirmed the formation of cubic spinels with crystallite size 4.5 nm and 3.4 nm, respectively for uncapped and chitosan capped ZnAl 2 O 4 nanoparticles. Chitosan capping produced a blue shift in bandgap energy (3.84 to 3.94 eV) agreeing with size effects according to the Brus equation. A blue shift in emission peak and enhancement in photoluminescence intensity was also observed upon chitosan capping. The electronic band structure and the density of states of the bulk spinel were also calculated using density functional theory. The effective masses of electrons and holes estimated based on the band structure were used to extract the excitonic Bohr radius.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Development of Real-Time System Identification to Detect Abnormal Operations in a Gas Turbine Cycle

Here, we present a novel online system identification methodology for monitoring the performance of power systems. This methodology was demonstrated in a gas turbine recuperated power plant designed for a hybrid configuration. A 120-kW Garrett microturbine modified to test dynamic control strategies for hybrid power systems designed at the National Energy Technology Laboratory (NETL) was used to implement and validate this online system identification methodology. The main component of this methodology consists of an empirical transfer function model implemented in parallel to the turbine speed operation and the fuel control valve, which can monitor the process response of the gas turbine system while it is operating. During fully closed-loop operations or automated control, the output of the controller, fuel valve position, and the turbine speed measurements were fed for a given period of time to a recursive algorithm that determined the transfer function parameters during the nominal condition. After the new parameters were calculated, they were fed into the transfer function model for online prediction. The turbine speed measurement was compared against the transfer function prediction, and a control logic was implemented to capture when the system operated at nominal or abnormal conditions. To validate the ability to detect abnormal conditions during dynamic operations, drifting in the performance of the gas turbine system was evaluated. A leak in the turbomachinery working fluid was emulated by bleeding 10% of the airflow from the compressor discharge to the atmosphere, and electrical load steps were performed before and after the leak. This tool could detect the leak 7 s after it had occurred, which accounted for a fuel flow increase of approximately 15.8% to maintain the same load and constant turbine speed operations.

algorithms↗