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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

North Slope of Alaska Snow Intensive Operational Period Field Campaign Report

The campaign was motivated by the need to improve the quantification of measurements of ice-phase precipitation in the Arctic and was by the acquisition and deployment of the new X- and Ka/W-band radars. These radars opened up an opportunity for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility to obtain spatial estimates of snowfall rates using the polarimetric X-band measurements and dual-frequency measurements (using different combinations of the three wavelengths). However, calculations of X- and Ka-band radar back-scattering of ice crystal aggregates with their complex structure suggest that the commonly used T-matrix approach (Matrosov et al. 2007) for modeling the radar back-scattering underestimates the reflectivity by several decibels, with errors increasing with increasing radar frequency (Botta et al. 2010, 2011). Moreover, the X-band polarimetric measurements and the Ka/W-band measurements are sensitive to the assumed shape of the snow (Botta et al. 2011). One of the five ARM two-dimensional video disdrometers (manufactured by Joanneum Research) were deployed in Barrow at the ARM North Slope of Alaska (NSA) site from 1 October, 2011 to 31 May, 2012 in an attempt to use the instrument in a novel way. The instrument was originally designed to measure the drop size distribution of rain but it seemed worthwhile to explore its capability to quantify ice precipitation particle size and shape distributions in the cold north for scattering calculations and precipitation estimations. Furthermore, this deployment gave us an opportunity to see how reliable it could be in arctic conditions.

Ka-band radar↗
DOE OSTI2022

A Hybrid Data-Driven and Model-Based Anomaly Detection Scheme for DER Operation

This paper proposes a hybrid data and model-based anomaly detection scheme to secure the operation of distributed energy resources (DERs) in distribution grids. Data-driven autoencoders are set up at the edge device level and they use local DER operational data as inputs. The abnormal statuses are detected by analyzing reconstruction errors. In parallel, modelbased state estimation (SE) is set up at the central level and it uses system-wide models and measurements as data inputs. The anomalies are identified by analyzing measurement residuals. The hybrid scheme preserves the benefits of both data-driven and model-based analyses and thus improves the robustness and the accuracy of anomaly detection. Numerical tests based on the model of a real distribution feeder in Southern California highlight the proposed scheme's effectiveness and benefits.

anomaly detection↗
DOE OSTI2023

A General Method for Estimating Zonal Transmission Interface Limits from Nodal Network Data: Preprint

Capacity expansion models for the electric power system often employ zonal (rather than nodal) resolution, necessitating estimates of aggregate power transfer limits across the interfaces between model zones. Interface limits between planning areas are sometimes published, but they are not generalizable to arbitrary zone shapes. There is thus a need for a reproducible method for estimating interface transfer limits (ITLs) between user-defined zones directly from nodal transmission system data. Here, we present a simple method for estimating ITLs using a DC power flow approximation via the power transfer distribution factor (PTDF) matrix. Linear optimization is performed to identify the distribution of power flows that maximizes the total flow on interface-crossing lines, subject to individual line ratings, limits on bus injection/withdrawal, and the relationships among flows, injections, and withdrawals imposed by the PTDF matrix. We demonstrate the application of the method on a 134-zone ~65000-bus system, and we explore the influence of flow direction, contingency level, and zone size on the estimated ITLs. There is significant heterogeneity in the ratio of the ITL to the sum of interface-crossing line ratings, which highlights the importance of accounting for the physical constraints on power flows imposed by Kirchhoff's laws when estimating zonal ITLs.

17 WIND ENERGY↗
DOE OSTI2016

WE-H-207A-06: Hypoxia Quantification in Static PET Images: The Signal in the Noise

Purpose: Quantification of hypoxia from PET images is of considerable clinical interest. In the absence of dynamic PET imaging the hypoxic fraction (HF) of a tumor has to be estimated from voxel values of activity concentration of a radioactive hypoxia tracer. This work is part of an effort to standardize quantification of tumor hypoxic fraction from PET images. Methods: A simple hypoxia imaging model in the tumor was developed. The distribution of the tracer activity was described as the sum of two different probability distributions, one for the normoxic (and necrotic), the other for the hypoxic voxels. The widths of the distributions arise due to variability of the transport, tumor tissue inhomogeneity, tracer binding kinetics, and due to PET image noise. Quantification of HF was performed for various levels of variability using two different methodologies: a) classification thresholds between normoxic and hypoxic voxels based on a non-hypoxic surrogate (muscle), and b) estimation of the (posterior) probability distributions based on maximizing likelihood optimization that does not require a surrogate. Data from the hypoxia imaging model and from 27 cervical cancer patients enrolled in a FAZA PET study were analyzed. Results: In the model, where the true value of HF is known, thresholds usually underestimate the value for large variability. For the patients, a significant uncertainty of the HF values (an average intra-patient range of 17%) was caused by spatial non-uniformity of image noise which is a hallmark of all PET images. Maximum likelihood estimation (MLE) is able to directly optimize for the weights of both distributions, however, may suffer from poor optimization convergence. For some patients, MLE-based HF values showed significant differences to threshold-based HF-values. Conclusion: HF-values depend critically on the magnitude of the different sources of tracer uptake variability. A measure of confidence should also be reported.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Online State Estimation for Time-Varying Systems

The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states. In lieu of a batch linear least-squares (LS) approach well-suited for static networks, where a sufficient number of measurements could be collected to obtain a full-rank design matrix the paper proposes an online algorithm to estimate the possibly time-varying state by processing measurements as and when available. The design of the algorithm hinges on a generalized LS cost augmented with a proximal-point-type regularization. With the solution of the regularized LS problem available in closed-form, the online algorithm is written as a linear dynamical system where the state is updated based on the previous estimate and based on the new available measurements. Conditions under which the algorithmic steps are in fact a contractive mapping are shown, and bounds on the estimation error are derived for different noise models. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

SU-F-T-24: Impact of Source Position and Dose Distribution Due to Curvature of HDR Transfer Tubes

Purpose: Brachytherapy is a highly targeted from of radiotherapy. While this may lead to ideal dose distributions on the treatment planning system, a small error in source location can lead to change in the dose distribution. The purpose of this study is to quantify the impact on source position error due to curvature of the transfer tubes and the impact this may have on the dose distribution. Methods: Since the source travels along the midline of the tube, an estimate of the positioning error for various angles of curvature was determined using geometric properties of the tube. Based on the range of values a specific shift was chosen to alter the treatment plans for a number of cervical cancer patients who had undergone HDR brachytherapy boost using tandem and ovoids. Impact of dose to target and organs at risk were determined and checked against guidelines outlined by radiation oncologist. Results: The estimate of the positioning error was 2mm short of the expected position (the curved tube can only cause the source to not reach as far as with a flat tube). Quantitative impact on the dose distribution is still in the process of being analyzed. Conclusion: The accepted positioning tolerance for the source position of a HDR brachytherapy unit is plus or minus 1mm. If there is an additional 2mm discrepancy due to tube curvature, this can result in a source being 1mm to 3mm short of the expected location. While we do always attempt to keep the tubes straight, in some cases such as with tandem and ovoids, the tandem connector does not extend as far out from the patient so the ovoid tubes always contain some degree of curvature. The dose impact of this may be significant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

SOSAT: Geohazard Risk Assessment in Carbon Sequestration Operations

Like all operations in which fluids are injected into the subsurface, geologic carbon storage (GCS) presents inherit risks that must be assessed and mitigated to successfully deploy such technology in the field. For example, alterations to pore pressure and the stress state due to fluid injection may trigger certain geohazards, such as potential fault activation and induced seismicity or unintentional hydraulic fracturing. Here we present capabilities for assessing these potential risks using the State of Stress Analysis Tool (SOSAT): a Python library and web-based application capable of probabilistically estimating the subsurface state of stress informed by various field observations. Using posterior distributions of principal stress components, SOSAT can assess the risk of fault activation within the injection formation for either a critically oriented fault or a fault with a user-prescribed orientation. Additionally, SOSAT can estimate the probability of unintentional hydraulic fracturing of the intact reservoir rock. Here, we demonstrate these SOSAT capabilities using a hypothetical GCS site. This type of risk assessment can assist with the effective deployment of GCS technology in the field by informing safe design and management practices.

Haagenson, Ryan J.↗
DOE OSTI2018

Integrating GLL-Weibull Distribution Within a Bayesian Framework for Life Prediction of Shape Memory Alloy Spring Undergoing Thermo-mechanical Fatigue

The present paper tackles an important but unmapped problem of the reliability estimations of smart materials. First, an experimental setup is developed for accelerated life testing of the shape memory alloy (SMA) springs. Generalized log-linear Weibull (GLL-Weibull) distribution-based novel approach is then developed for SMA spring life estimation. Applied stimulus (voltage), elongation and cycles of operation are used as inputs for the life prediction model. The values of the parameter coefficients of the model provide better interpretability compared to artificial intelligence based life prediction approaches. In addition, the model also considers the effect of operating conditions, making it generic for a range of the operating conditions. Moreover, a Bayesian framework is used to continuously update the prediction with the actual degradation value of the springs, thereby reducing the uncertainty in the data and improving the prediction accuracy. In addition, the deterioration of material with number of cycles is also investigated using thermogravimetric analysis and scanning electron microscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Modeling and control of fuel distribution in a dual-fuel internal combustion engine leveraging late intake valve closings

In internal combustion engines, cycle-to-cycle and cylinder-to-cylinder variations of the combustion process have been shown to negatively impact the fuel efficiency of the engine and lead to higher exhaust emissions. The combustion variations are generally tied to differences in the composition and condition of the trapped mass throughout each cycle and across individual cylinders. Thus, advanced engines featuring exhaust gas recirculation, flexible valve actuation systems, advanced fueling strategies, and turbocharging systems are prone to exhibit higher variations in the combustion process. In this study, the cylinder-to-cylinder variations of the combustion process in a dual-fuel internal combustion engine leveraging late intake valve closing are investigated and a model to predict and address one of the root causes for these variations across cylinders is developed. The study is conducted on an inline six-cylinder heavy-duty dual-fuel engine equipped with exhaust gas recirculation, a variable geometry turbocharger, and a fully flexible variable intake valve actuation system. The engine is operated with late intake valve closure timings in a dual-fuel combustion mode in which a high reactivity fuel is directly injected into the cylinders and a low reactivity fuel is port injected into the cylinders. The cylinder-to-cylinder variations observed in the study have been associated with the maldistribution of the port-injected fuel, which is exacerbated at late intake valve timings. The resulting difference in indicated mean effective pressure between the cylinders ranges from 9% at an intake valve closing of 570° after top dead center to 38% at an intake valve closing of 620° after top dead center and indicates an increasingly uneven fuel distribution. The study leverages both experimental and simulation studies to investigate the distribution of the port-injected fuel and its impact on cylinder-to-cylinder variation. The effects of intake valve closing as well as the impact of intake runner length on fuel distribution were quantitatively analyzed, and a model was developed that can be used to accurately predict the fuel distribution of the port-injected fuel at different operating conditions with an average estimation error of 1.5% in cylinder-specific fuel flow. A model-based control strategy is implemented to adjust the fueling at each port and shown to significantly reduce the cylinder-to-cylinder variations in fuel distribution.

Kassa, Mateos↗
DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

bayesian structural time series↗
DOE OSTI2025

Estimating Soil Thermal Inertia Profiles From the Passive Equilibration of a Temperature Probe

Knowledge of the distribution of soil thermal properties is important for understanding subsurface hydrological and biogeochemical processes. This study describes and evaluates quick thermal profiling (QTP), a new measurement technique aimed at providing rapid, depth-resolved measurements of soil thermal inertia at numerous locations across the landscape. A cylindrical probe with temperature sensors at multiple depths is quickly inserted into the ground, and soil thermal inertia is estimated from how quickly the probe temperature equilibrates with the soil. To this end, a finite volume heat transfer model is used to generate temperature equilibration time series across combinations of controlling factors, and a gridded search inversion approach is applied to infer soil thermal inertia. Field tests in the Arctic indicate that QTP measurements have a minimum uncertainty of 0.14 J m −2 K −1 s −1/2 and covary with dual-probe heat pulse thermal analyzer measurements (concordance correlation coefficient = 0.56) with a root-mean-square error of 0.40 J m −2 K −1 s −1/2 . Besides demonstrating the value of QTP for estimating thermal inertia, this study identifies various sources of measurement uncertainty, particularly probe-soil contact resistance and frictional heating. Further, analysis of soil samples indicates that thermal inertia can be used to estimate thermal conductivity and dry bulk density in the studied area, although such inferences are highly site-specific. Overall, the QTP method holds promise to generate thermal inertia data products and to complement other characterization approaches for advancing understanding of soil properties across far more locations than is currently possible.

Lamb, J. R. [Lawrence Berkeley National Laboratory↗
DOE OSTI2020

Constraining magnetic fields in the circumgalactic medium

ABSTRACT We study the properties of magnetic fields in the circumgalactic medium (CGM) of z < 1 galaxies by correlating Faraday rotation measures (RMs) of ∼1000 high-redshift radio sources with the foreground galaxy number density estimated from the DESI Legacy Imaging Surveys. This method enables us to extract signals of RMs contributed by intervening gas around multiple galaxies. Our results show that there is no detectable correlation between the distribution of RMs and the number of foreground galaxies, contrary to several previous results. Utilizing the non-detection signals, we estimate 3σ upper limits to the RMs from the CGM of $\sim \!20 \rm \ rad\, m^{-2}$ within 50 kpc and $\sim \!10 \rm \ rad \, m^{-2}$ at separations of 100 kpc. By adopting a column density distribution of ionized gas obtained from absorption-line measurements, we further estimate the strengths of coherent magnetic fields parallel to the line of sight of $\lt \rm 2 \ \mu G$ in the CGM. We show that the estimated upper limits of RMs and magnetic field strengths are sufficient to constrain outputs of recent galaxy magnetohydrodynamic simulations. Finally, we discuss possible causes for the inconsistency between our results and previous works.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

On Large Deviations for Sums of i.i.d. Bernoulli Random Variables

Tail probabilities are studied for the binomial distribution. The Hoeffding inequality is sharpened in this particular case through estimating an integral factor in the Esscher transform, which is omitted in Hoeffding’s proof. This approach was already used by Talagrand (1995) in the general case. However, our results are much more precise. In particular, all involved constants are given in the explicit form.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A probability density function model describing height estimation uncertainty due to image pixel intensity noise in digital fringe projection measurements

Digital fringe projection is a surface-profiling technique used for highly accurate non-contact measurements. As with any measurement technique, a variety of sources degrade to the measurement accuracy of the method. Here, this paper presents an analytically-derived probability density function that explicitly models the surface height measurement error due to inevitable phase measurement error, and it includes the specific case of pixel noise inducing the phase measurement error that ultimately leads to the height estimation error. The accuracy of the model was validated through Monte-Carlo simulations of resultant height distributions subject to arbitrarily correlated pixel intensity noise and experimental digital fringe projection measurements where the pixel-by-pixel height uncertainty estimations were compared to the predictions of the derived model.

42 ENGINEERING↗
DOE OSTI2023

Extending the predictive power of perturbative QCD using the principle of maximum conformality and the Bayesian analysis

In addition to the evaluation of high-order loop contributions, the precision and predictive power of perturbative QCD (pQCD) predictions depends on two important issues: (1) how to achieve a reliable, convergent fixed-order series, and (2) how to reliably estimate the contributions of unknown higher-order terms. The recursive use of renormalization group equation, together with the Principle of Maximum Conformality (PMC), eliminates the renormalization scheme-and-scale ambiguities of the conventional pQCD series. The result is a conformal, scale-invariant series of finite order which also satisfies all of the principles of the renormalization group. In this paper we propose a novel Bayesian-based approach to estimate the size of the unknown higher order contributions based on an optimized analysis of probability distributions. We show that by using the PMC conformal series, in combination with the Bayesian analysis, one can consistently achieve high degree of reliability estimates for the unknown high order terms. Thus the predictive power of pQCD can be greatly improved. We illustrate this procedure for two pQCD observables: R e+e– and R τ , which are each known up to four loops in pQCD. Numerical analyses confirm that by using the scale-independent and more convergent PMC conformal series, one can achieve reliable Bayesian probability estimates for the unknown higher-order contributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

2025 California Demand Response Potential Study - Charting California’s Demand Response Future. Final Report on Phase 2 Results

California’s legislative and regulatory goals for renewable energy are changing the power grid’s dynamics. Increased variable generation resource penetration connected to the bulk power system, as well as, distributed energy resources (DERs) connected to the distribution system affect the grid’s reliable operation over many different time scales (e.g., days to hours to minutes to seconds). As the state continues this transition, it will require careful planning to ensure resources with the right characteristics are available to meet changing grid management needs. Demand response (DR) has the potential to provide important resources for keeping the electricity grid stable and efficient, to defer upgrades to generation, transmission and distribution systems, and to deliver customer economic benefits. This study estimates the potential size and cost of future DR resources for California’s three investor-owned utilities (IOUs): Pacific Gas and Electric Company (PG&E), Southern California Edison Company (SCE), and San Diego Gas & Electric Company (SDG&E). Our goal is to provide data-driven insights as the California Public Utilities Commission (CPUC) evaluates how to enhance DR’s role in meeting California’s resource planning needs and operational requirements. We address two fundamental questions: 1. What cost-competitive DR service types will meet California’s future grid needs as it moves towards clean energy and advanced infrastructure? 2. What is the size and cost of the expected resource base for the DR service types?

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

The star formation properties of the observed and simulated AGN Universe: BAT versus EAGLE

ABSTRACT In this paper, we present data from 72 low-redshift, hard X-ray selected active galactic nucleus (AGN) taken from the Swift–BAT 58 month catalogue. We utilize spectral energy distribution fitting to the optical to infrared photometry in order to estimate host galaxy properties. We compare this observational sample to a volume- and flux-matched sample of AGN from the Evolution and Assembly of GaLaxies and their Environments (EAGLE) hydrodynamical simulations in order to verify how accurately the simulations can reproduce observed AGN host galaxy properties. After correcting for the known +0.2 dex offset in the SFRs between EAGLE and previous observations, we find agreement in the star formation rate (SFR) and X-ray luminosity distributions; however, we find that the stellar masses in EAGLE are 0.2–0.4 dex greater than the observational sample, which consequently leads to lower specific star formation rates (sSFRs). We compare these results to our previous study at high redshift, finding agreement in both the observations and simulations, whereby the widths of sSFR distributions are similar (∼0.4–0.6 dex) and the median of the SFR distributions lie below the star-forming main sequence by ∼0.3–0.5 dex across all samples. We also use EAGLE to select a sample of AGN host galaxies at high and low redshift and follow their characteristic evolution from z = 8 to z = 0. We find similar behaviour between these two samples, whereby star formation is quenched when the black hole goes through its phase of most rapid growth. Utilizing EAGLE we find that 23 per cent of AGN selected at z ∼ 0 are also AGN at high redshift, and that their host galaxies are among the most massive objects in the simulation. Overall, we find EAGLE reproduces the observations well, with some minor inconsistencies (∼0.2 dex in stellar masses and ∼0.4 dex in sSFRs).

Jackson, Thomas M.↗