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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Smart Meter Pinging and Reading Through AMI Two-Way Communication Networks to Monitor Grid Edge Devices and DERs

Today’s power distribution system is changing to a power-electronics-enabled distribution system, especially with the increasing penetration of distributed energy resources (DERs). To monitor and manage those electronic devices and DERs at the grid edge, the advanced metering infrastructure (AMI) with two-way communications presents great potential. At present, extensive research explores the upstream communication from smart meters to electric utilities (e.g., meter reading) but few examine the downstream communication from the utilities to smart meters (e.g., meter pinging). This article discusses the AMI two-way communication and its recent industrial practice in the U.S., especially for applying the smart meter pinging functionality to monitor grid-edge devices and DERs. This paper then develops the two-way communication model and the network calculus method to quantify the impact of the two-way communication on the AMI network. In the end, the proposed method is validated with ns-3 simulation using the modified 13-node test feeder and real-world feeder systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Deep Reinforcement Learning based Model-free On-line Dynamic Multi-Microgrid Formation to Enhance Resilience

Multi-microgrid formation (MMGF) is a promising solution for enhancing power system resilience. This paper proposes a new deep reinforcement learning (RL) based model-free on-line dynamic MMGF scheme. Additionally, the dynamic MMGF problem is formulated as a Markov decision process, and a complete deep RL framework is specially designed for the topologytransformable micro-grids. In order to reduce the large action space caused by flexible switch operations, a topology transformation method is proposed and an action-decoupling Q-value is applied. Then, a convolutional neural network (CNN) based multi-buffer double deep Q-network (CM-DDQN) is developed to further improve the learning ability of the original DQN method. The proposed deep RL method provides real-time computing to support the on-line dynamic MMGF scheme, and the scheme handles a long-term resilience enhancement problem using an adaptive on-line MMGF to defend changeable conditions. The effectiveness of the proposed method is validated using a 7-bus system and the IEEE 123-bus system. The results show strong learning ability, timely response for varying system conditions and convincing resilience enhancement.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Distribution System Parameter and Topology Estimation Applied to Resolve Low-Voltage Circuits on Three Real Distribution Feeders

Accurate distribution secondary low-voltage circuit models are needed to enhance overall distribution system operations and planning, including effective monitoring and coordination of distributed energy resources located in the secondary circuits. We present a full-scale demonstration across three real feeders of a computationally efficient approach for estimating the secondary circuit topologies and parameters using historical voltage and power measurements provided by smart meters. The method is validated against several secondary configurations, and compares favorably to satellite imagery and the utility secondary model. Feeder-wide results show how much parameters can vary from simple assumptions. In conclusion, model sensitivities are tested, demonstrating only modest amounts of data and resolutions of data measurements are needed for accurate parameter and topology results.

42 ENGINEERING↗
DOE OSTI2025

Probability Density Function Control of Frequency Fluctuations in Renewable-Rich Power Systems

The stochastic nature of renewable energy sources (RESs) necessitates treating power system frequency response as a random process with a nonstationary probability density function (PDF). Here, based upon the stochastic distribution control theory originated by the second author, this paper proposes a novel stochastic controller to improve the frequency PDF in power grids when integrating a large amount of RESs, thereby minimizing the effects of uncertainties and enhancing overall system stability. The key idea is to manipulate the controllable power generation resources so that the frequency PDF is make to follow a target PDF by using the stochastic distribution control theory originated by the second author. The proposed method can easily be plugged into existing automatic generation controls for multi-area transmission grids. The proposed method is validated via a modified Kundar's two area system and 240-bus Western Electricity Coordinating Council systems. The simulation results show that the proposed control shapes the frequency PDF narrower and sharper, leading to a notable improvement toward minimizing the effects of randomness and uncertainty during grid operation.

frequency↗
DOE OSTI2016

False-negative rate, limit of detection and recovery efficiency performance of a validated macrofoam-swab sampling method for low surface concentrations of Bacillus anthracis Sterne and Bacillus atrophaeus spores

The performance of a macrofoam-swab sampling method was evaluated using Bacillus anthracis Sterne (BAS) and Bacillus atrophaeus Nakamura (BG) spores applied at nine low target amounts (2-500 spores) to positive-control plates and test coupons (2 in × 2 in) of four surface materials (glass, stainless steel, vinyl tile, and plastic). Test results from cultured samples were used to evaluate the effects of surrogate, surface concentration, and surface material on recovery efficiency (RE), false negative rate (FNR), and limit of detection. For RE, surrogate and surface material had statistically significant effects, but concentration did not. Mean REs were the lowest for vinyl tile (50.8% with BAS and 40.2% with BG) and the highest for glass (92.8% with BAS and 71.4% with BG). FNR values ranged from 0 to 0.833 for BAS and 0 to 0.806 for BG; values increased as concentration decreased in the range tested (0.078 to 19.375 CFU/cm2). Surface material also had a statistically significant effect. A FNR-concentration curve was fit for each combination of surrogate and surface material. For both surrogates, the FNR curves tended to be the lowest for glass and highest for vinyl title. The FNR curves for BG tended to be higher than for BAS at lower concentrations, especially for glass. Results using a modified Rapid Viability-Polymerase Chain Reaction (mRV-PCR) analysis method were also obtained. The mRV-PCR results and comparisons to the culture results will be discussed in a subsequent article.

Bacillus anthracis↗
DOE OSTI2015

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

2D-DIC↗
DOE OSTI2015

Non‐invasive, whole‐plant imaging of chloroplast movement and chlorophyll fluorescence reveals photosynthetic phenotypes independent of chloroplast photorelocation defects in chloroplast division mutants

Summary Leaf chloroplast movement is thought to optimize light capture and to minimize photodamage. To better understand the impact of chloroplast movement on photosynthesis, we developed a technique based on the imaging of reflectance from leaf surfaces that enables continuous, high‐sensitivity, non‐invasive measurements of chloroplast movement in multiple intact plants under white actinic light. We validated the method by measuring photorelocation responses in Arabidopsis chloroplast division mutants with drastically enlarged chloroplasts, and in phototropin mutants with impaired photorelocation but normal chloroplast morphology, under different light regimes. Additionally, we expanded our platform to permit simultaneous image‐based measurements of chlorophyll fluorescence and chloroplast movement. We show that chloroplast division mutants with enlarged, less‐mobile chloroplasts exhibit greater photosystem II photodamage than is observed in the wild type, particularly under fluctuating high levels of light. Comparison between division mutants and the severe photorelocation mutant phot1‐5 phot2‐1 showed that these effects are not entirely attributable to diminished photorelocation responses, as previously hypothesized, implying that altered chloroplast morphology affects other photosynthetic processes. Our dual‐imaging platform also allowed us to develop a straightforward approach to correct non‐photochemical quenching ( NPQ ) calculations for interference from chloroplast movement. This correction method should be generally useful when fluorescence and reflectance are measured in the same experiments. The corrected data indicate that the energy‐dependent ( qE ) and photoinhibitory ( qI ) components of NPQ contribute differentially to the NPQ phenotypes of the chloroplast division and photorelocation mutants. This imaging technology thus provides a platform for analyzing the contributions of chloroplast movement, chloroplast morphology and other phenotypic attributes to the overall photosynthetic performance of higher plants.

Dutta, Siddhartha↗
DOE OSTI2015

Detector dose response in megavoltage small photon beams. I. Theoretical concepts

Purpose: To explain the reasons for significant quality correction factors in megavoltage small photon fields and clarify the underlying concepts relevant to dosimetry under such conditions. Methods: The validity of cavity theory and the requirement of charged particle equilibrium (CPE) are addressed from a theoretical point of view in the context of nonstandard beams. Perturbation effects are described into four main subeffects, explaining their nature and pointing out their relative importance in small photon fields. Results: It is demonstrated that the failure to meet classical cavity theory requirements, such as CPE, is not the reason for significant quality correction factors. On the contrary, it is shown that the lack of CPE alone cannot explain these corrections and that what matters most, apart from volume averaging effects, is the relationship between the lack of CPE in the small field itself and the density of the detector cavity. The density perturbation effect is explained based on Fano’s theorem, describing the compensating effect of two main contributions to cavity absorbed dose. Using the same approach, perturbation effects arising from the difference in atomic properties of the cavity medium and the presence of extracameral components are explained. Volume averaging effects are also discussed in detail. Conclusions: Quality correction factors of small megavoltage photon fields are mainly due to differences in electron density between water and the detector medium and to volume averaging over the detector cavity. Other effects, such as the presence of extracameral components and differences in atomic properties of the detection medium with respect to water, can also play an accentuated role in small photon fields compared to standard beams.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

SU-F-T-180: Evaluation of a Scintillating Screen Detector for Proton Beam QA and Acceptance Testing

Purpose: To test the performance of a commercial scintillating screen detector for acceptance testing and Quality Assurance of a proton pencil beam scanning system. Method: The detector (Lexitek DRD 400) has 40cm × 40cm field, uses a thin scintillator imaged onto a 16-bit scientific CCD with ∼0.5mm resolution. A grid target and LED illuminators are provided for spatial calibration and relative gain correction. The detector mounts to the nozzle with micron precision. Tools are provided for image processing and analysis of single or multiple Gaussian spots. Results: The bias and gain of the detector were studied to measure repeatability and accuracy. Gain measurements were taken with the LED illuminators to measure repeatability and variation of the lens-CCD pair as a function with f-stop. Overall system gain was measured with a passive scattering (broad) beam whose shape is calibrated with EDR film placed in front of the scintillator. To create a large uniform field, overlapping small fields were recorded with the detector translated laterally and stitched together to cover the full field. Due to the long exposures required to obtain multiple spills of the synchrotron and very high detector sensitivity, borated polyethylene shielding was added to reduce direct radiation events hitting the CCD. Measurements with a micro ion chamber were compared to the detector’s spot profile. Software was developed to process arrays of Gaussian spots and to correct for radiation events. Conclusion: The detector background has a fixed bias, a small component linear in time, and is easily corrected. The gain correction method was validated with 2% accuracy. The detector spot profile matches the micro ion chamber data over 4 orders of magnitude. The multiple spot analyses can be easily used with plan data for measuring pencil beam uniformity and for regular QA comparison.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-260: Using Portal Image Device for Pre-Treatment QA in Volumetric Modulated Arc Plans with Flattening Filter Free (FFF) Beams

Purpose: To implement and validate a method of using electronic portal image device (EPID) for pre-treatment quality assurance (QA) of volumetric modulated arc therapy (VMAT) plans using flattering filter free (FFF) beams for stereotactic body radiotherapy (SBRT). Methods: On Varian Edge with 6MV FFF beam, open field (from 2×2 cm to 20×20 cm) EPID images were acquired with 200 monitor unit (MU) at the image device to radiation source distance of 150cm. With 10×10 open field and calibration unit (CU) provided by vendor to EPID image pixel, a dose conversion factor was determined by dividing the center dose calculated from the treatment planning system (TPS) to the corresponding CU readout on the image. Water phantom measured beam profile and the output factors for various field sizes were further correlated to those of EPID images. The dose conversion factor and correction factors were then used for converting the portal images to the planner dose distributions of clinical fields. A total of 28 VMAT fields of 14 SBRT plans (8 lung, 2 prostate, 2 liver and 2 spine) were measured. With 10% low threshold cutoff, the delivered dose distributions were compared to the reference doses calculated in water phantom from the TPS. A gamma index analysis was performed for the comparison in percentage dose difference/distance-to-agreement specifications. Results: The EPID device has a linear response to the open fields with increasing MU. For the clinical fields, the gamma indices between the converted EPID dose distributions and the TPS calculated 2D dose distributions were 98.7%±1.1%, 94.0%±3.4% and 70.3%±7.7% for the criteria of 3%/3mm, 2%/2mm and 1%/1mm, respectively. Conclusion: Using a portal image device, a high resolution and high accuracy portal dosimerty was achieved for pre-treatment QA verification for SBRT VMAT plans with FFF beams.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-201-11: Evaluating the Validity of Prospective Risk Analysis Methods: A Comparison of Traditional FMEA and Modified Healthcare FMEA

Purpose: To examine the ability of traditional Failure mode and effects analysis (FMEA) and a light version of Healthcare FMEA (HFMEA), called Scenario analysis of FMEA (SAFER) by comparing their outputs in terms of the risks identified and their severity rankings. Methods: We applied two prospective methods of the quality management to surface image guided, linac-based radiosurgery (SIG-RS). For the traditional FMEA, decisions on how to improve an operation are based on risk priority number (RPN). RPN is a product of three indices: occurrence, severity and detectability. The SAFER approach; utilized two indices-frequency and severity-which were defined by a multidisciplinary team. A criticality matrix was divided into 4 categories; very low, low, high and very high. For high risk events, an additional evaluation was performed. Based upon the criticality of the process, it was decided if additional safety measures were needed and what they comprise. Results: Two methods were independently compared to determine if the results and rated risks were matching or not. Our results showed an agreement of 67% between FMEA and SAFER approaches for the 15 riskiest SIG-specific failure modes. The main differences between the two approaches were the distribution of the values and the failure modes (No.52, 54, 154) that have high SAFER scores do not necessarily have high FMEA RPN scores. In our results, there were additional risks identified by both methods with little correspondence. In the SAFER, when the risk score is determined, the basis of the established decision tree or the failure mode should be more investigated. Conclusion: The FMEA method takes into account the probability that an error passes without being detected. SAFER is inductive because it requires the identification of the consequences from causes, and semi-quantitative since it allow the prioritization of risks and mitigation measures, and thus is perfectly applicable to clinical parts of radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Direct constraint on the Higgs–charm coupling from a search for Higgs boson decays into charm quarks with the ATLAS detector

A search for the Higgs boson decaying into a pair of charm quarks is presented. The analysis uses proton–proton collisions to target the production of a Higgs boson in association with a leptonically decaying W or Z boson. The dataset delivered by the LHC at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV and recorded by the ATLAS detector corresponds to an integrated luminosity of 139 fb -1 . Flavour-tagging algorithms are used to identify jets originating from the hadronisation of charm quarks. The analysis method is validated with the simultaneous measurement of WW, WZ and ZZ production, with observed (expected) significances of 2.6 (2.2) standard deviations above the background-only prediction for the $(W/Z)Z( → c\bar{c})$ process and 3.8 (4.6) standard deviations for the $(W/Z)W(→cq)$ process. The $(W/Z)Z( → c\bar{c})$ search yields an observed (expected) upper limit of 26 (31) times the predicted Standard Model cross-section times branching fraction for a Higgs boson with a mass of 125 GeV, corresponding to an observed (expected) constraint on the charm Yukawa coupling modifier |$k_c$| < 8.5 (12.4), at the 95% confidence level. A combination with the ATLAS $(W/Z)H,H → b\bar{b}$ analysis is performed, allowing the ratio $k_c/k_b$ to be constrained to less than 4.5 at the 95% confidence level, smaller than the ratio of the b- and c-quark masses, and therefore determines the Higgs-charm coupling to be weaker than the Higgs-bottom coupling at the 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Demonstration of neutron identification in neutrino interactions in the MicroBooNE liquid argon time projection chamber

A significant challenge in measurements of neutrino oscillations is reconstructing the incoming neutrino energies. While modern fully-active tracking calorimeters such as liquid argon time projection chambers in principle allow the measurement of all final state particles above some detection threshold, undetected neutrons remain a considerable source of missing energy with little to no data constraining their production rates and kinematics. We present the first demonstration of tagging neutrino-induced neutrons in liquid argon time projection chambers using secondary protons emitted from neutron-argon interactions in the MicroBooNE detector. We describe the method developed to identify neutrino-induced neutrons and demonstrate its performance using neutrons produced in muon-neutrino charged current interactions. The method is validated using a small subset of MicroBooNE’s total dataset. The selection yields a sample with 60% of selected tracks corresponding to neutron-induced secondary protons. At this purity, the integrated efficiency is 8.4% for neutrons that produce a detectable proton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) [SWR 18-23]

Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. https://www.nrel.gov/docs/legosti/old/6231.pdf For EnergyPlus® and OpenStudio®, generation of test cases, simulation, and reporting has been a manual or partially automated process that typically took a number of months after a new version of EnergyPlus came out. Building Energy Simulation Test - Generation Simulation and Reporting (BESTEST-GSR) was developed to fully automate this process so it is less error-prone, less time-consuming, and can be quickly run on request for any development branch of EnergyPlus and OpenStudio. The initial use case is to directly support OpenStudio and EnergyPlus development, but the software is configured to support use by external software developers that build tools on top of EnergyPlus and/or OpenStudio. Tools built on top of OpenStudio can leverage the test generation, simulation, and reporting, while tools built on EnergyPlus can leverage the test simulation and reporting. The model generation is accomplished by running OpenStudio measures for envelope, heating, or cooling test cases. At this stage the specified weather file required for a specific test case is assigned to the model. Simulation is enabled using the OpenStudio Command Line Interface (CLI) to run a series of OpenStudio and Reporting measures to a specified seed model. The specified workflow is defined with an OpenStudio OSW file. The first measure generates the test case model, while the second measure is a reporting measure that runs after the simulation to collect necessary simulation results from the EnergyPlus SQL file. The Reporting stage gathers data from individual OpenStudio OSW files and populates a series of BESTEST Microsoft Excel spreadsheets. BESTEST-GSR also gathers zip files from individual simulations for diagnostic purposes.

Goldwasser, David↗
DOE OSTI2021

LoTToR: An Algorithm for Missing-Wedge Correction of the Low-Tilt Tomographic 3D Reconstruction of a Single-Molecule Structure (LoTToR) v1.0

The low-tilt tomographic reconstruction (LoTToR) method is a post-processing method to correct the missing-wedge artifact, which contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of ±15°. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination. Moreover, the software can be used for hospital computer tomography (CT) to reduce the radiation damage to patients without reducing the CT image quality.

Ren, Gang↗
DOE OSTI2022

BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) 2023 [SWR 18-23]

Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. https://www.nrel.gov/docs/legosti/old/6231.pdf The purpose of this repository is to generate BESTEST test case models, run simulations, and populate data for ASHRAE Standard 140 reporting spreadsheets for EnergyPlus® based whole building simulation tools. It was originally setup for 2014 version of Standard 140. In May of 2022 it was updated to the 2020 version of Standard 140. This update included updates and additions to existing test suites, the bulk of which was in Section 5.2 (Building Thermal Envelope and Fabric Load Tests). We did not add Section 5.5 Airside HVAC Equipment Performance, but we hope to add that later in 2022. At some point we also hope to add Section 5.2.4 ground modeling, which is currently excluded. Supported Tools The default IDF generation is based on the OpenStudio® CLI, but the workflow supports a 'Bring your own IDF' use case. Additionally, for non-EnergyPlus® based tools the post processing scripts can be used if simulation results are provided as a CSV file.The scripts on this repository should work on Mac, Windows, and Linux. Dependencies Install OpenStudio® 3.4.0 make sure command line can recognize the 'openstudio' command This includes EnergyPlus® 22.1 Install Ruby on your system if it isn't already setup. 2.7 is used for development but other versions may work Since OpenStudio has its own embedded Ruby, which is used for running measures, you don't necessarily have to use a version of Ruby supported by OpenStudio. Install RubyXL Ruby gem This is used to modify Microsoft Excel spreadsheets Install Parallel Ruby gem This allows the CLI to run simulations in parallel

Goldwasser, David↗
DOE OSTI2021

Improved Prediction of Cold-Air Pools in the Weather Research and Forecasting Model Using a Truly Horizontal Diffusion Scheme for Potential Temperature

The terrain-following vertical coordinate system used by many atmospheric models, including the Weather Research and Forecasting (WRF) Model, is prone to errors in regions of complex terrain. These errors stem, in part, from the calculation of horizontal gradients within the diffusion term of the momentum or scalar evolution equations. In WRF, such gradients can be calculated along coordinate surfaces, or using metric terms that help account for grid skewness. However, neither of these options ensures a truly horizontal gradient calculation, especially if a grid cell is skewed enough that the heights of the neighboring grid points used in the calculation fall outside the vertical range of the cell. In this work, an improved scheme that uses Taylor series approximations to vertically interpolate variables to the level necessary for a truly horizontal gradient calculation is implemented in WRF for the diffusion of potential temperature. The scheme is validated using an atmosphere-at-rest configuration, in which spurious flows develop only as a result of numerical errors and can thus be used as a proxy for model performance. Following validation, the method is applied to the simulation of cold-air pools (CAPs), which occur in regions of complex terrain and are characterized by strong near-surface temperature gradients. Using the truly horizontal scheme, idealized simulations demonstrate reduced numerical mixing in a quiescent CAP, and a realistic case study in the Columbia River basin shows a reduction in positive wind speed bias by up to roughly 20% compared to observations from the Second Wind Forecast Improvement Project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A deep learning-enhanced framework for multiphysics joint inversion

Joint inversion has drawn considerable attention due to the availability of multiple geophysical data sets, ever-increasing computational resources, the development of advanced algorithms, and its ability to reduce inversion uncertainty. A key issue of joint inversion is to develop effective strategies to link different geophysical data in a unified mathematical framework, in which the information obtained from different models can complement each other. We have developed a deep learning-enhanced joint inversion framework to simultaneously reconstruct different physical models by fusing different types of geophysical data. Traditionally, structure similarity constraints are pursued by joint inversion algorithms using manually crafted formulations (e.g., cross gradient). The constraint is constructed by a deep neural network (DNN) during the learning process. The framework is designed to combine the DNN and a traditional independent inversion workflow and improve the joint inversion result iteratively. The network can be easily extended to incorporate multiphysics without structural changes. Numerical experiments on the joint inversion of 2D DC resistivity data and seismic traveltime are used to validate our method. In addition, this learning-based framework demonstrates excellent generalization abilities when tested on data sets using different geologic structures. It also can handle different sensing configurations and nonconforming discretization.

Geochemistry & Geophysics↗