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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.

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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Vapor liquid solid-hydride vapor phase epitaxy (VLS-HVPE) growth of ultra-long defect-free GaAs nanowires: Ab initio simulations supporting center nucleation

High aspect ratio, rod-like and single crystal phase GaAs nanowires (NWs) were grown by gold catalyst-assisted hydride vapor phase epitaxy (HVPE). High resolution transmission electron microscopy and micro-Raman spectroscopy revealed polytypism-free zinc blende (ZB) NWs over lengths of several tens of micrometers for a mean diameter of 50 nm. Micro-photoluminescence studies of individual NWs showed linewidths smaller than those reported elsewhere which is consistent with the crystalline quality of the NWs. HVPE makes use of chloride growth precursors GaCl of which high decomposition frequency after adsorption onto the liquid droplet catalysts, favors a direct and rapid introduction of the Ga atoms from the vapor phase into the droplets. High influxes of Ga and As species then yield high axial growth rate of more than 100 μm/h. The diffusion of the Ga atoms in the liquid droplet towards the interface between the liquid and the solid nanowire was investigated by using density functional theory calculations. The diffusion coefficient of Ga atoms was estimated to be 3 × 10{sup −9} m{sup 2}/s. The fast diffusion of Ga in the droplet favors nucleation at the liquid-solid line interface at the center of the NW. This is further evidence, provided by an alternative epitaxial method with respect to metal-organic vapor phase epitaxy and molecular beam epitaxy, of the current assumption which states that this type of nucleation should always lead to the formation of the ZB cubic phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

WE-AB-202-06: Correlating Lung CT HU with Transformation-Based and Xe-CT Derived Ventilation

Purpose: Regional lung ventilation is useful to reduce radiation-induced function damage during lung cancer radiation therapy. Recently a new direct HU (Hounsfield unit)-based method was proposed to estimate the ventilation potential without image registration. The purpose of this study is to examine if there is a functional dependence between HU values and transformation-based or Xe-CT derived ventilation. Methods: 4DCT images acquired from 13 patients prior to radiation therapy and 4 mechanically ventilated sheep subjects which also have associated Xe-CT images were used for this analysis. Transformation-based ventilation was computed using Jacobian determinant of the transformation field between peak-exhale and peak-inhale 4DCT images. Both transformation and Xe-CT derived ventilation was computed for each HU bin. Color scatter plot and cumulative histogram were used to compare and validate the direct HU-based method. Results: There was little change of the center and shape of the HU histograms between free breathing CT and 4DCT average, with or without smoothing, and between the repeated 4DCT scans. HU of −750 and −630 were found to have the greatest transformation-based ventilation for human and sheep subjects, respectively. Maximum Xe-CT derived ventilation was found to locate at HU of −600 in sheep subjects. The curve between Xe-CT ventilation and HU was noisy for tissue above HU −400, possibly due to less intensity change of Xe gas during wash-out and wash-in phases. Conclusion: Both transformation-based and Xe-CT ventilation demonstrated that lung tissues with HU values in the range of (-750, −600) HU have the maximum ventilation potential. The correlation between HU and ventilation suggests that HU might be used to help guide the ventilation calculation and make it more robust to noise and image registration errors. Research support from NIH grants CA166703 and CA166119 and a gift from Roger Koch.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Mobile sensing of point-source gas emissions using Bayesian inference: An empirical examination of the likelihood function

This paper evaluates likelihood function forms for Bayesian inference of point-source gas emissions using a mobile sensor. Whereas Bayesian inference has been successfully used to estimate emission rates from time-averaged concentration data measured by stationary sensors, data collected by mobile sensors do not represent ensemble or time-averaged conditions. To examine the potential impact of this contrast, controlled release experiments were conducted with a mobile sensor measuring concentrations repeatedly along transverse cross sections of the downwind plumes. Experiments were conducted with measurements made at different downwind distances, different sensor heights, and with different obstacle states. An examination is made between two commonly-used likelihood functions, the Gaussian and the log-normal. For experiments conducted in the absence of obstacles, the Bayesian estimates using the log-normal likelihood function yield a much smaller bias than those based on the Gaussian likelihood function. This finding is consistent with the non-Gaussian nature of concentration fluctuations near a point-source. For experiments conducted in the presence of obstacles, the Bayesian inference based on the Gaussian likelihood function exhibits a better performance. This can be explained by the enhanced turbulent mixing due to the obstacle-introduced wake eddies. Overall, we find that the selection of the likelihood function can be physically related to the underlying conditions, and the proper selection is critical to ensure the performance of the Bayesian inference for source characterization using mobile sensing data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Reachable set bounding for a class of bidirectional associative memory NNSs with Markov jump switching parameters

This paper studies the problem how to estimate the reachable set for a class of delayed bidirectional associative memory neural network systems (NNSs), which have Markov switching parameters and unit-energy or unit-peak bounded disturbance inputs. The feature of the Markov jump bidirectional associative memory NNSs shows in the following twofold: the time delay is time varying; the transition rates is time varying. Moreover, the time-varying transition rates is piecewise constant. Using the Lyapunov functional method, delay-partitioning and linear matrix inequalities techniques, the estimate problem of the reachable set depending on time delay is solved. The effectiveness of the given results is illustrated by the proposed numerical examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Density functional study of the electronic structure of dye-functionalized fullerenes and their model donor-acceptor complexes containing P3HT

We study the electronic structure of C{sub 60} fullerenes functionalized with a thiophene-diketo-pyrrolopyrrole-thiophene based chromophore using density functional theory combined with large polarized basis sets. As the attached chromophore has electron donor character, the functionalization of the fullerene leads to a donor-acceptor (DA) system. We examine in detail the effect of the linker and the addition site on the electronic structure of the functionalized fullerenes. We further study the electronic structure of these DA complexes with a focus on the charge transfer excitations. Finally, we examine the interface of the functionalized fullerenes with the widely used poly(3-hexylthiophene-2,5-diyl) (P3HT) donor. Our results show that all functionalized fullerenes with an exception of the C{sub 60}-pyrrolidine [6,6], where the pyrrolidine is attached at a [6,6] site, have larger electron affinities relative to the pristine C{sub 60} fullerene. We also estimate the quasi-particle gap, lowest charge transfer excitation energy, and the exciton binding energies of the functionalized fullerene-P3MT model systems. Results show that the exciton binding energies in these model complexes are slightly smaller compared to a similarly prepared phenyl-C{sub 61}-butyric acid methyl ester (PCBM)-P3MT complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Nonlinear Integral Equations with Potential-Type Kernels on a Segment

We study various classes of nonlinear equations containing operators of potential type (Riesz potential). By the method of monotone operators in the Lebesgue spaces of real-valued functions L{sub p}(a, b) we prove global theorems on the existence, uniqueness, estimates, and methods of construction of their solutions. We present applications that illustrate the results obtained.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series

Hydropower is one of the most mature forms of renewable energy generation. The United States (US) has almost 103 GW of installed, with 80 GW of conventional generation and 23 GW of pumped hydropower [1]. Moreover, the potential for future development on Non-Powered Dams is up to 10 GW. With the US setting its goals to become carbon neutral [2], more renewable energy in the form of hydropower needs to be integrated with the grid. Currently, there are no publicly available tool that can estimate the hydropower potential for existing hydropower dams or other non-powered dams. The HydroGenerate is an open-source python library that has the capability of estimating hydropower generation based on flow rate either provided by the user or received from United States Geological Survey (USGS) water data services. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the “head” provided by the user.

Mitra, Bhaskar↗
DOE OSTI2022

Data-driven Minimum Entropy Control for Stochastic Nonlinear Systems using the Cumulant-Generating Function

Here, we present a novel minimum entropy control algorithm for a class of stochastic nonlinear systems subjected to non-Gaussian noises. The entropy control can be considered as an optimization problem for the system randomness attenuation, but the mean value has to be considered separately. To overcome this disadvantage, a new representation of the system stochastic properties was given using the cumulant-generating function based on the moment-generating function, in which the mean value and the entropy was reflected by the shape of the cumulant-generating function. Based on the samples of the system output and control input, a time-variant linear model was identified, and the minimum entropy optimization was transformed to system stabilization. Then, an optimal control strategy was developed to achieve the randomness attenuation, and the boundedness of the controlled system output was analyzed. The effectiveness of the presented control algorithm was demonstrated by a numerical example. In this paper, a data-driven minimum entropy design is presented without pre-knowledge of the system model; entropy optimization is achieved by the system stabilization approach in which the stochastic distribution control and minimum entropy are unified using the same identified structure; and a potential framework is obtained since all the existing system stabilization methods can be adopted to achieve the minimum entropy objective.

42 ENGINEERING↗
DOE OSTI2018

Assessment of CO 2 Storage Potential in Naturally Fractured Reservoirs With Dual–Porosity Models

Naturally Fractured Reservoirs (NFR’s) have received little attention as potential CO 2 storage sites. Two main facts deter from storage projects in fractured reservoirs: (1) CO 2 tends to be nonwetting in target formations and capillary forces will keep CO 2 in the fractures, which typically have low pore volume; and (2) the high conductivity of the fractures may lead to increased spatial spreading of the CO 2 plume. Numerical simulations are a powerful tool to understand the physics behind brine-CO 2 flow in NFR’s. Dual-porosity models are typically used to simulate multiphase flow in fractured formations. However, existing dual-porosity models are based on crude approximations of the matrix-fracture fluid transfer processes and often fail to capture the dynamics of fluid exchange accurately. Therefore, more accurate transfer functions are needed in order to evaluate the CO 2 transfer to the matrix. This work presents an assessment of CO 2 storage potential in NFR’s using dual-porosity models. We investigate the impact of a system of fractures on storage in a saline aquifer, by analyzing the time scales of brine drainage by CO 2 in the matrix blocks and the maximum CO 2 that can be stored in the rock matrix. A new model to estimate drainage time scales is developed and used in a transfer function for dual-porosity simulations. Furthermore, we then analyze how injection rates should be limited in order to avoid early spill of CO 2 (lost control of the plume) on a conceptual anticline model. Numerical simulations on the anticline show that naturally fractured reservoirs may be used to store CO 2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Weighted FFT estimators for 1D and 3D correlations of the Lyman- α forest

Correlations in the Lyman-α (Lyα) forest, both as a function of line of sight separation (1D) and 3D separation, provide a unique window to the distribution of matter at redshifts not accessible by current galaxy surveys. While optimal quadratic estimators have been used to measure 1D correlations, they are computationally expensive and difficult to extend to 3D analyses. On the other hand, estimators based on the Fast Fourier Transform (FFT) are significantly faster, but are affected by missing data in the spectra (masked pixels) and so far have not used pixel weights to reduce the uncertainties in the measurement. In this publication we describe how to compute the window matrix that enables forward-modelling the impact of masked pixels and weights on the FFT-based estimators. Here, we use Gaussian and hydrodynamical simulations with artificially masked pixels to validate the method on the measurement of 1D correlations. Finally, we show that the formalism can be extended to model the impact on 3D correlations, in particular on the cross-spectrum, the correlation of 1D Fourier modes as a function of transverse separation. This work will enable more precise clustering measurements with the Lyα forest dataset recently collected by the Dark Energy Spectroscopic Instrument (DESI).

Lokken, Martine [Univ. Autonoma de Barcelona (Spai↗
DOE OSTI2020

Impedance-Based Prediction of SSR-Generated Harmonics in Doubly-Fed Induction Generators

Doubly-fed induction generators (DFIGs) are prone to subsynchronous resonance (SSR) with series-compensated transmission lines and experiencing SSR-generated harmonics of wide-ranging magnitudes. This paper presents a large-signal impedance-based approach for the prediction of the magnitude of SSR-generated harmonics in DFIGs. Note that the large-signal impedance of a network shows variation in its impedance response with the magnitude of perturbation at its terminals. It is discovered in this paper that the impedance of a series-compen- sated transmission line starts changing with the magnitude of SSR because of the metal-oxide varistor-based protection of series capacitors in the line. The changing line impedance halts the growth of the SSR beyond a certain point, where the DFIG forms a limit-cycle mode and emits harmonics at the SSR frequency. The discovered role of the protection of series capacitors in SSR not only enables the prediction of SSR-generated harmonics but also can be used for the timely detection of an SSR event to avoid system disruption and sudden loss of bulk generation. The large- signal impedance-based prediction of SSR-generated harmonics in DFIG-based wind and hydro generators is demonstrated using numerical simulations of a 2.5-MVA, 690-V DFIG supplying to a series-compensated transmission line.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Accelerated impurity solver for DMFT and its diagrammatic extensions

Here, we present ComCTQMC, a GPU accelerated quantum impurity solver. It uses the continuous-time quantum Monte Carlo (CTQMC) algorithm wherein the partition function is expanded in terms of the hybridisation function (CT-HYB). ComCTQMC supports both partition and worm-space measurements, and it uses improved estimators and the reduced density matrix to improve observable measurements whenever possible. ComCTQMC efficiently measures all one and two-particle Green's functions, all static observables which commute with the local Hamiltonian, and the occupation of each impurity orbital. ComCTQMC can solve complex-valued impurities with crystal fields that are hybridized to both fermionic and bosonic baths. Most importantly, ComCTQMC utilizes graphical processing units (GPUs), if available, to dramatically accelerate the CTQMC algorithm when the Hilbert space is sufficiently large. We demonstrate acceleration by a factor of over 600 (100) in a simulation of δ-Pu at 600 K with (without) crystal fields. In easier problems, the GPU offers less impressive acceleration or even decelerates the CTQMC. Here we describe the theory, algorithms, and structure used by ComCTQMC in order to achieve this set of features and level of acceleration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

The NANOGrav nine-year data set: Noise budget for pulsar arrival times on intraday timescales

The use of pulsars as astrophysical clocks for gravitational wave (GW) experiments demands the highest possible timing precision. Pulse times of arrival (TOAs) are limited by stochastic processes that occur in the pulsar itself, along the line of sight through the interstellar medium, and in the measurement process. On timescales of seconds to hours, the TOA variance exceeds that from template-fitting errors due to additive noise. We assess contributions to the total variance from two additional effects: amplitude and phase jitter intrinsic to single pulses and changes in the interstellar impulse response from scattering. The three effects have different dependencies on time, frequency, and pulse signal-to-noise ratio. We use data on 37 pulsars from the North American Nanohertz Observatory for GWs to assess the individual contributions to the overall intraday noise budget for each pulsar. We detect jitter in 22 pulsars and estimate the average value of rms jitter in our pulsars to be ∼1% of pulse phase. We examine how jitter evolves as a function of frequency and find evidence for evolution. Finally, we compare our measurements with previous noise parameter estimates and discuss methods to improve GW detection pipelines.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A rigorous physics-based enhanced parameter estimation (EPE) methodology for calibration of building energy simulations

Buildings rarely perform as designed/simulated and there are numerous tangible benefits if this gap is reconciled. A new scientifically rigorous yet pragmatic methodology for calibrating building energy simulations - called Enhanced Parameter Estimation (EPE) - is proposed that allows physically relevant parameter estimation rather than a blind force-fit to energy use data. Starting with a rapidly created simulation model, calibration is performed in two stages: (a) building shell calibration with the HVAC system replaced by an ideal system that meets the loads (b) HVAC system calibration with the building shell and all internal loads replaced by a box with only process loads. In the first stage, EPE identifies a small number of high-level heat flows in the energy balance, calculates them with specifically tailored individual driving functions, introduces physically significant parameters to best accomplish energy balance, and, estimates the parameters and their uncertainty bounds. Calibration is thus done with corrective heat flows without any arbitrary tuning of input parameters. Calibration accuracy is enhanced by machine learning of the residual errors. The EPE methodology is demonstrated by means of: a synthetic building and an actual 75,000 sq. ft. building in Pennsylvania. Future work needed for widespread application is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

A new RASS galaxy cluster catalogue with low contamination extending to z ∼ 1 in the DES overlap region

ABSTRACT We present the MARD-Y3 catalogue of between 1086 and 2171 galaxy clusters (52 per cent and 65 per cent new) produced using multicomponent matched filter (MCMF) follow-up in 5000 deg2 of DES-Y3 optical data of the ∼20 000 overlapping ROSAT All-Sky Survey source catalogue (2RXS) X-ray sources. Optical counterparts are identified as peaks in galaxy richness as a function of redshift along the line of sight towards each 2RXS source within a search region informed by an X-ray prior. All peaks are assigned a probability fcont of being a random superposition. The clusters lie at 0.02 < z < 1.1 with more than 100 clusters at z > 0.5. Residual contamination is 2.6 per cent and 9.6 per cent for the cuts adopted here. For each cluster we present the optical centre, redshift, rest frame X-ray luminosity, M500 mass, coincidence with NWAY infrared sources, and estimators of dynamical state. About 2 per cent of MARD-Y3 clusters have multiple possible counterparts, the photo-z’s are high quality with σΔz/(1 + z) = 0.0046, and ∼1 per cent of clusters exhibit evidence of X-ray luminosity boosting from emission by cluster active galactic nuclei. Comparison with other catalogues (MCXC, RM, SPT-SZ, Planck) is performed to test consistency of richness, luminosity, and mass estimates. We measure the MARD-Y3 X-ray luminosity function and compare it to the expectation from a fiducial cosmology and externally calibrated luminosity- and richness–mass relations. Agreement is good, providing evidence that MARD-Y3 has low contamination and can be understood as a simple two step selection – X-ray and then optical – of an underlying cluster population described by the halo mass function.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bayesian inference for the seismic moment tensor using regional waveforms and a data-derived distribution of velocity models

The largest source of uncertainty in any source inversion is the velocity model used to construct the transfer function employed in the forward model that relates observed ground motion to the seismic moment tensor. However, standard inverse procedures often does not quantify uncertainty in the seismic moment tensor due to error in the Green’s functions from uncertain event location and Earth structure. We attempt to incorporate this uncertainty into an estimation of the seismic moment tensor using a distribution of velocity models calculated in a prior effort based on different and complementary data sets. The posterior distribution of velocity models is then used to construct Green’s functions for use in Bayesian inference of an unknown seismic moment tensor using regional waveform data. The combined likelihood is estimated using data-specific error models and the posterior of the seismic moment tensor is estimated and can be interpreted in terms of most-probable source-type.

58 GEOSCIENCES↗
DOE OSTI2017

Trigonometric polynomial approximation, K-functionals and generalized moduli of smoothness

Best approximation and approximation by families of linear polynomial operators (FLPO) in the spaces L{sub p}, 0<p⩽+∞, are investigated for periodic functions of an arbitrary number of variables in terms of the generalized modulus of smoothness generated by a periodic generator which, near the origin, is assumed to be close in a certain sense to some homogeneous function of positive order. Direct and inverse theorems (Jackson- and Bernstein-type estimates) are proved; conditions on the generators are obtained under which the approximation error by an FLPO is equivalent to an appropriate modulus of smoothness. These problems are solved by going over from the modulus to an equivalent K-functional. The general results obtained are applied to classical objects in the theory of approximation and smoothness. In particular, they are applied to the methods of approximation generated by Fejér, Riesz and Bochner-Riesz kernels, and also to the moduli of smoothness and K-functionals corresponding to the conventional, Weyl and Riesz derivatives and to the Laplace operator. Bibliography: 24 titles. (paper)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

On the Impact of Income, Age, and Travel Distance on the Value of Time

The value of time (VOT) is a fundamental component used in transportation modeling, policy analysis, and economic appraisal. Decades of research and practice have empirically estimated the VOT across many factors (e.g., mode, purpose, time, comfort, etc.), yet little is known about its underlying form. Although it is well established that VOT can vary, it is still unclear whether patterns exist in this variation. The objective of this paper is not to merely estimate the VOT, but to model the VOT across multiple continuous and interacting variables. The purpose is to reveal its functional form with respect to mode, age, gender, purpose, income, and time of day to provide a generalizable understanding for future research and practice. Such an understanding can help develop simpler models and reduce the need for bespoke estimations for every conceivable variable perturbation. This research utilized a household travel survey containing 14,159 reported trips with imputed travel time and costs for the alternative mode choices. The average overall estimated VOT is 40.32 $/h, with results showing VOT varying log-linearly with income and trip distance, but following a Gaussian function (normal curve) with age. Overall, the results show that travel distance dominates VOT variation, which increases exponentially at a rate that is 3.61 times higher per mile of distance than per $10,000 of income, and that VOT by age peaks at age 54. This basic understanding of how the VOT varies sets the foundation for answering the subsequent question for why it might vary.

Engineering↗