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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO

Abstract Streambed grain sizes control river hydro‐biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo‐driven, artificial intelligence (AI)‐enabled, and theory‐based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground‐truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log‐normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy‐Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined.

58 GEOSCIENCES↗
DOE OSTI2017

Interaction and Impact Studies for Distributed Energy Resource, Transactive Energy, and Electric Grid, using High Performance Computing ?based Modeling and Simulation

The electric utility industry is undergoing significant transformations in its operation model, including a greater emphasis on automation, monitoring technologies, and distributed energy resource management systems (DERMS). With these changes and new technologies, while driving greater efficiencies and reliability, these new models may introduce new vectors of cyber attack. The appropriate cybersecurity controls to address and mitigate these newly introduced attack vectors and potential vulnerabilities are still widely unknown and performance of the control is difficult to vet. This proposal argues that modeling and simulation (M&S) is a necessary tool to address and better understand these problems introduced by emerging technologies for the grid. M&S will provide electric utilities a platform to model its transmission and distribution systems and run various simulations against the model to better understand the operational impact and performance of cybersecurity controls.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Convergence of ray sequences of Frobenius-Padé approximants

Let σ-hat be a Cauchy transform of a possibly complex-valued Borel measure σ and {p_n} a system of orthonormal polynomials with respect to a measure μ, where supp(μ)∩supp(σ)=∅. An (m,n)th Frobenius-Padé approximant to σ-hat is a rational function P/Q, deg (P)≤m, deg (Q)≤n, such that the first m+n+1 Fourier coefficients of the remainder function Q σ-hat −P vanish when the form is developed into a series with respect to the polynomials p{sub n}. We investigate the convergence of the Frobenius-Padé approximants to σ-hat along ray sequences n/(n+m+1)→c>0, n−1≤m, when μ and σ are supported on intervals of the real line and their Radon-Nikodym derivatives with respect to the arcsine distribution of the corresponding interval are holomorphic functions. Bibliography: 30 titles. (paper)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Cybersecurity Assessment for a Behind-the-Meter Solar PV System: A Use Case for the DER-CF

The world's energy production is shifting toward lower-cost, cleaner, more efficient, and sustainable sources. The increasing numbers of distributed energy resources (DERs) are allowing for the rapid transformation of electric grids toward achieving the goal of energy decarbonization. Along with cleaner and more efficient energy, however, we must also aim for a secure energy future. Solar photovoltaic (PV) systems are an important part of this transition. This paper discusses a cybersecurity risk assessment for behind-the-meter DERs using a solar PV system as a use case of the Distributed Energy Resource Cybersecurity Framework (DER-CF) developed by the National Renewable Energy Laboratory. This poster presents a conference paper on the risk assessment processes and summarizes the DER-CF's use case recommendations to strengthen the cybersecurity posture of the electric grid.

cybersecurity↗
DOE OSTI2016

SU-F-T-279: Impact of Beam Energy Drifts On IMRT Delivery Accuracy

Purpose: According to TG-40 percent-depth-dose (PDD) tolerance is ±2% but TG-142 is ±1%. Now the question is, which one is relevant in IMRT era? The primary objective of this study is to evaluate dosimetric impact of beam-energy-drifts on IMRT-delivery. Methods: Beam-energy drifts were simulated by adjusting Linac’s bending-magnet-current (BMC) followed by tuning the pulse-forming network and adjusting gun-current. PDD change of −0.6% and +1.2% were tested. Planar-dosimetry measurements were performed using an ionization-chamber-array in solid-water phantoms. Study includes 10-head-and-neck and 3-breast cancer patients. en-face beam-deliveries were also tested at 1.3cm and 5.3cm depths. Composite and single-field dose-distributions were compared against the plans to determine %Gamma pass-rates (%GPRs). For plan dose comparisons, changes in %Gamma pass-rates (cPGPRs) were computed/reported to exclude the differences between dose-computation and delivery. Dose distributions of the drifted-energies were compared against their baseline measurements to determine the% GPRs. A Gamma criteria of 3%/3mm was considered for plan-dose comparisons while 3%/1mm used for measured dose intercomparisons. Results: For composite-dose delivery, average cPGPRs were 0.41%±2.48% and −2.54%±3.65% for low-energy (LE) and high-energy (HE) drifts, respectively. For measured dose inter-comparisons, the average%GPRs were 98.4%±2.2% (LE-drift) and 95.8%±4.0 (HE-drift). The average %GPR of 92.6%±4.3% was noted for the worst-case scenario comparing LE-drift to HE-drift. All en-face beams at 5.3 cm depth have cPGPRs within ±4% of the baseline-energy measurements. However, greater variations were noted for 1.3cm depth. Average %GPRs for drifted energies were >99% at 5.3cm and >97% at 1.3cm depths. However, for the worst-case scenario (LE-drift to HE-drift) these numbers dropped to 95.2% at 5.3cm and 93.1% at 1.3cm depths. Conclusion: The dosimetric impact of beam-energy drifts was found to be within clinically acceptable tolerance. However, this study includes a single energy with limited range of PDD change. Further studies are on going and the results will be presented. Received funding from Varian Medical Systems, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

A hybrid Monte Carlo and response matrix Monte Carlo method in criticality calculation

Full core calculations are very useful and important in reactor physics analysis, especially in computing the full core power distributions, optimizing the refueling strategies and analyzing the depletion of fuels. To reduce the computing time and accelerate the convergence, a method named Response Matrix Monte Carlo (RMMC) method based on analog Monte Carlo simulation was used to calculate the fixed source neutron transport problems in repeated structures. To make more accurate calculations, we put forward the RMMC method based on non-analog Monte Carlo simulation and investigate the way to use RMMC method in criticality calculations. Then a new hybrid RMMC and MC (RMMC+MC) method is put forward to solve the criticality problems with combined repeated and flexible geometries. This new RMMC+MC method, having the advantages of both MC method and RMMC method, can not only increase the efficiency of calculations, also simulate more complex geometries rather than repeated structures. Several 1-D numerical problems are constructed to test the new RMMC and RMMC+MC method. The results show that RMMC method and RMMC+MC method can efficiently reduce the computing time and variations in the calculations. Finally, the future research directions are mentioned and discussed at the end of this paper to make RMMC method and RMMC+MC method more powerful. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Dark energy survey internal consistency tests of the joint cosmological probes analysis with posterior predictive distributions

Beyond ΛCDM, physics or systematic errors may cause subsets of a cosmological data set to appear inconsistent when analysed assuming ΛCDM. Here, we present an application of internal consistency tests to measurements from the Dark Energy Survey Year 1 (DES Y1) joint probes analysis. Our analysis relies on computing the posterior predictive distribution (PPD) for these data under the assumption of ΛCDM. We find that the DES Y1 data have an acceptable goodness of fit to ΛCDM, with a probability of finding a worse fit by random chance of p = 0.046. Using numerical PPD tests, supplemented by graphical checks, we show that most of the data vector appears completely consistent with expectations, although we observe a small tension between large- and small-scale measurements. A small part (roughly 1.5 per cent) of the data vector shows an unusually large departure from expectations; excluding this part of the data has negligible impact on cosmological constraints, but does significantly improve the p-value to 0.10. The methodology developed here will be applied to test the consistency of DES Year 3 joint probes data sets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Dynamical modeling of tidal streams

I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its 'track') in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of 'orphan' streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Determination of aquatic hazard concentrations for the oil spill response product class of surface washing agents using species sensitivity distributions

Surface washing agents (SWAs) are a diverse class of oil spill response products intended to facilitate removal of stranded oil from shorelines. This class of agents has high application rates relative to other categories of spill response products, but global toxicity data is generally limited to two standard test species: inland silverside and mysid shrimp. Here, in this study, we provide a framework to maximize the utility of limited toxicity data across a product class. To characterize species sensitivity to SWAs, the toxicity of three agents spanning a range of chemical and physical properties were tested in eight species. The relative sensitivity of mysids shrimp and inland silversides as surrogate test organisms was determined. Toxicity normalized species sensitivity distributions (SSDn) were used to estimate fifth centile hazard concentration (HC5) values for SWAs with limited toxicity data. Chemical toxicity distributions (CTD) of SWA HC5 values were used to compute a fifth centile chemical hazard distribution (HD5) to provide a more comprehensive assessment of hazard across a spill response product class with limited toxicity data than traditional single species or single agent approaches can give.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2014

Microstructure of sheared monosized colloidal suspensions resulting from hydrodynamic and electrostatic interactions

Hydrodynamic and near-particle interactions in sheared suspensions are communicated through suspension microstructure to produce a wide variety of rheological behaviors. To characterize this microstructure, the individual positions of monosized silica particles flowing through a microchannel are obtained with near simulation-level detail. The pair distribution functions of the microstructure at moderate to high Péclet number shear rates are very similar to previous numerical studies. Viscometric functions calculated based on the detailed microstructure obtained through this technique show qualitative agreement with computational results. These results elucidate the origins of shear-thickening of suspensions at high shear rates. While efforts are taken to screen electrostatic interactions to study hydrodynamic and Brownian interactions, the role of electrostatic interaction between particles is also investigated by reducing suspension ionic strength. These non-hydrodynamic electrostatic interactions result in a loss of anisotropy that generally agrees with previous findings of “soft” particle systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Solution Method for the Filtered Lifting Line Theory

The filtered lifting line theory presents a continuous form of the inviscid momentum equations of flow over a lifting device, such as a wing or rotor blade, using body forces without mathematical singularities. This theory is also consistent with an actuator line representation of a lifting device. In this work, we present a reformulation of the equations in terms of the local flow angle along the line, which allows solving the stand-alone equations using multivariate root-finding algorithms. This approach can be used to obtain a fast, computationally inexpensive solution of the loading distribution along a wing without the need to perform computational fluid dynamic simulations. We study the requirements in terms of resolution in the spanwise direction and establish the criteria for spacing and minimum amount of points required along the blade to obtain converged solutions. The solutions are compared to results from large-eddy simulations, and we observed excellent agreement with less than a percent difference in quantities along the blade between the methods.

17 WIND ENERGY↗
DOE OSTI2014

Generation of graphite particles by sliding abrasion and their characterization

Characterization of graphite particles (dust) produced by abrasion that would occur in a pebble bed reactor is of interest for reasons of safety, operation, and maintenance. To better understand this abrasion and particle generation, we have built a test apparatus to produce particles by sliding abrasion in a 1% to 5% relative humidity air environment. We have used a commercial-grade graphite in our experiments and have generated size distributions for the abraded particles. We have also fit lognormal functions to those size distributions (for use in computer codes); determined particle shapes; measured temperature and humidity during the tests; measured and calculated wear rates; and measured the surface roughness of both pretest and posttest samples, particle surface areas, pore volumes, and pore volume distributions of particles produced during abrasion of graphite surfaces under different loadings and sliding speeds. The experiments showed that as loading (analogous to pebble depth in the reactor) and sliding speed increase, so do the wear rates and numbers of particles produced, while surface roughness decreases, increases, and then decreases. Brunauer-Emmett-Teller measurements show that abrasion increases surface area from 0.583 m 2 /g in the bulk material to 555 m 2 /g in material abraded at high loading and high sliding speed. Wear rates range from 0.005 to 0.991 g/m per contact site. As a result, the size of the particles observed was <4000 nm. Finally, in all, our research shows that pebble abrasion is a complex process that is not constant during operation and thus should be considered for future work.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Maximum Likelihood Estimation: Some Basics

The maximum likelihood estimation is a general estimation procedure. It is often compared to estimation procedures like the ordinary least squares regression or generalized method of moments, to name a few. We discuss some basics about the maximum likelihood estimation, its advantages and disadvantages, and provide an example application to a gamma distribution function.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

Joint probabilities and quantum cognition

In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Distribution of tunnelling times for quantum electron transport

In electron transport, the tunnelling time is the time taken for an electron to tunnel out of a system after it has tunnelled in. We define the tunnelling time distribution for quantum processes in a dissipative environment and develop a practical approach for calculating it, where the environment is described by the general Markovian master equation. We illustrate the theory by using the rate equation to compute the tunnelling time distribution for electron transport through a molecular junction. The tunnelling time distribution is exponential, which indicates that Markovian quantum tunnelling is a Poissonian statistical process. The tunnelling time distribution is used not only to study the quantum statistics of tunnelling along the average electric current but also to analyse extreme quantum events where an electron jumps against the applied voltage bias. The average tunnelling time shows distinctly different temperature dependence for p- and n-type molecular junctions and therefore provides a sensitive tool to probe the alignment of molecular orbitals relative to the electrode Fermi energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗