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DOE OSTI2025

Graph-Learning-Assisted State and Event Tracking for Solar-Penetrated Power Grids with Heterogeneous Data Sources

Unlike transmission systems, distribution systems do not typically contain sufficient metering to enable real-time state estimation. The lack of sufficient real-time measurements prohibits accurate and timely monitoring of the state of distribution systems. As a result, control and optimal operation of distribution systems, especially those containing large numbers of renewable generation units are not possible without proper data and information about the current state of the system. The main motivation of this project is to address this shortcoming by developing an approach which provides “predicted” real-time measurements so that they can be used to execute a distribution system state estimator. Thus, the objective of the project is to make the distribution systems fully observable, such that the hosting capacity for solar generation can be accurately estimated, and unnecessary solar curtailments can be avoided. In order to accomplish this goal, the project investigated the use of a grid-model-informed machine learning (ML) tool which integrates heterogeneous data streams obtained from AMI meters, SCADA as well as PMU measurements and created synchronous measurement snapshots for the state estimator (SE); and developed a hybrid robust SE which provides not only accurate state estimates but also real-time feedback for the ML model refinement.

14 SOLAR ENERGY↗

DOE OSTI2021

Distributed control of electric power grids

A method for determining power output levels of a plurality of nodes in an electric power system includes receiving, at a first node of the plurality of nodes, voltage information and multipliers of all neighboring nodes of the first node within the electric power system, determining, by the first node, a local power generation and a local voltage using the voltage information and the multipliers of the neighboring nodes and distributing the local power generation and the local voltage to the neighboring nodes, determining, by the first node, an estimated voltage of each of the neighboring nodes and distributing the estimated voltage to each of the neighboring nodes, and updating, by the first node, a local multiplier using the voltage information received from the neighboring nodes and the estimated voltage of each of the neighboring nodes determined by the node.

Ghosh, Soumyadip↗

NASA NTRS1991

A distributed Petri Net controller for a dual arm testbed

This thesis describes the design and functionality of a Distributed Petri Net Controller (DPNC). The controller runs under X Windows to provide a graphical interface. The DPNC allows users to distribute a Petri Net across several host computers linked together via a TCP/IP interface. A sub-net executes on each host, interacting with the other sub-nets by passing a token vector from host to host. One host has a command window which monitors and controls the distributed controller. The input to the DPNC is a net definition file generated by Great SPN. Thus, a net may be designed, analyzed and verified using this package before implementation. The net is distributed to the hosts by tagging transitions that are host-critical with the appropriate host number. The controller will then distribute the remaining places and transitions to the hosts by generating the local nets, the local marking vectors and the global marking vector. Each transition can have one or more preconditions which must be fulfilled before the transition can fire, as well as one or more post-processes to be executed after the transition fires. These implement the actual input/output to the environment (machines, signals, etc.). The DPNC may also be used to simulate a Great SPN net since stochastic and deterministic firing rates are implemented in the controller for timed transitions.

Bjanes, Atle↗

NASA NTRS2015

The Suomi National Polar-Orbiting Partnership (SNPP): Continuing NASA Research and Applications

The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).

remote sensing↗

DOE OSTI2024

Inclusive and differential cross section measurements of $ \textrm{t}\overline{\textrm{t}}\textrm{b}\overline{\textrm{b}} $ production in the lepton+jets channel at $ \sqrt{s} $ = 13 TeV

Measurements of inclusive and normalized differential cross sections of the associated production of top quark-antiquark and bottom quark-antiquark pairs, $ \textrm{t}\overline{\textrm{t}}\textrm{b}\overline{\textrm{b}} $, are presented. The results are based on data from proton-proton collisions collected by the CMS detector at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb$^{−1}$. The cross sections are measured in the lepton+jets decay channel of the top quark pair, using events containing exactly one isolated electron or muon and at least five jets. Measurements are made in four fiducial phase space regions, targeting different aspects of the $ \textrm{t}\overline{\textrm{t}}\textrm{b}\overline{\textrm{b}} $ process. Distributions are unfolded to the particle level through maximum likelihood fits, and compared with predictions from several event generators. The inclusive cross section measurements of this process in the fiducial phase space regions are the most precise to date. In most cases, the measured inclusive cross sections exceed the predictions with the chosen generator settings. The only exception is when using a particular choice of dynamic renormalization scale, $ {\mu}_{\textrm{R}}=\frac{1}{2}{\prod}_{i=\textrm{t},\overline{\textrm{t}},\textrm{b},\overline{\textrm{b}}}{m}_{\textrm{T},i}^{1/4} $, where $ {m}_{\textrm{T},i}^2={m}_i^2+{p}_{\textrm{T},i}^2 $ are the transverse masses of top and bottom quarks. The differential cross sections show varying degrees of compatibility with the theoretical predictions, and none of the tested generators with the chosen settings simultaneously describe all the measured distributions.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Determinants of synapse diversity revealed by super-resolution quantal transmission and active zone imaging

Neural circuit function depends on the pattern of synaptic connections between neurons and the strength of those connections. Synaptic strength is determined by both postsynaptic sensitivity to neurotransmitter and the presynaptic probability of action potential evoked transmitter release (P r ). Whereas morphology and neurotransmitter receptor number indicate postsynaptic sensitivity, presynaptic indicators and the mechanism that sets P r remain to be defined. To address this, we developed QuaSOR, a super-resolution method for determining P r from quantal synaptic transmission imaging at hundreds of glutamatergic synapses at a time. We mapped the P r onto super-resolution 3D molecular reconstructions of the presynaptic active zones (AZs) of the same synapses at the Drosophila larval neuromuscular junction (NMJ). We find that P r varies greatly between synapses made by a single axon, quantify the contribution of key AZ proteins to P r diversity and find that one of these, Complexin, suppresses spontaneous and evoked transmission differentially, thereby generating a spatial and quantitative mismatch between release modes. Transmission is thus regulated by the balance and nanoscale distribution of release-enhancing and suppressing presynaptic proteins to generate high signal-to-noise evoked transmission.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1987

A diffuse radar scattering model from Martian surface rocks

Remote sensing of Mars has been done with a variety of instrumentation at various wavelengths. Many of these data sets can be reconciled with a surface model of bonded fines (or duricrust) which varies widely across the surface and a surface rock distribution which varies less so. A surface rock distribution map from -60 to +60 deg latitude has been generated by Christensen. Our objective is to model the diffuse component of radar reflection based on this surface distribution of rocks. The diffuse, rather than specular, scattering is modeled because the diffuse component arises due to scattering from rocks with sizes on the order of the wavelength of the radar beam. Scattering for radio waves of 12.5 cm is then indicative of the meter scale and smaller structure of the surface. The specular term is indicative of large scale surface undulations and should not be causally related to other surface physical properties. A simplified model of diffuse scattering is described along with two rock distribution models. The results of applying the models to a planet of uniform fractional rock coverage with values ranging from 5 to 20% are discussed.

Calvin, W. M.↗

DOE OSTI2023

Comprehensive Analysis of Model Parameter Uncertainty Influence on Evaluation of HVAC Operation to Mitigate Indoor Virus: A Case Study for an Office Building in a Cold and Dry Climate

Simulation-based studies of HVAC operation to mitigate indoor virus have been conducted to understand tradeoffs between indoor air quality (IAQ) and energy consumption. However, the influence of model parameter uncertainty in these studies has not been systematically quantified, which is critical when providing guidance to building operators. To address this gap, we identify 20 model parameters for a typical medium office building system in a cold and dry climate that can influence IAQ and energy consumption for indoor virus scenarios. Next, the distributions of the parameter values are estimated from literature and a set of simulation samples for three representative days is generated that simultaneously sample all of the parameters from their distributions. Two HVAC virus mitigation strategies are studied: increased filtration using MERV 13 filters and increased ventilation, via supply of 100% outdoor air into buildings. The model parameter uncertainty leads to significant variability in the results, particularly for the IAQ because of the highly uncertain virus generation rate. Use of 100% outdoor air can be beneficial for some uncertain scenarios on the hot day, but shows less IAQ improvement and/or significant energy increases on the other days. The virus removal efficiency and pressure drop of the HVAC filter, fan efficiency, and internal heat gain are the most important parameters to determining the tradeoffs of the two strategies. Our results demonstrate how this model parameter uncertainty analysis methodology can provide practical guidance to building operators.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Physics-driven learning of Wasserstein GAN for density reconstruction in dynamic tomography

Object density reconstruction from projections containing scattered radiation and noise is of critical importance in many applications. Existing scatter correction and density reconstruction methods may not provide the high accuracy needed in many applications and can break down in the presence of unmodeled or anomalous scatter and other experimental artifacts. Incorporating machine-learning models could prove beneficial for accurate density reconstruction, particularly in dynamic imaging, where the time evolution of the density fields could be captured by partial differential equations or by learning from hydrodynamics simulations. In this work, we demonstrate the ability of learned deep neural networks to perform artifact removal in noisy density reconstructions, where the noise is imperfectly characterized. Here, we use a Wasserstein generative adversarial network (WGAN), where the generator serves as a denoiser that removes artifacts in densities obtained from traditional reconstruction algorithms. We train the networks from large density time-series datasets, with noise simulated according to parametric random distributions that may mimic noise in experiments. The WGAN is trained with noisy density frames as generator inputs, to match the generator outputs to the distribution of clean densities (time series) from simulations. A supervised loss is also included in the training, which leads to an improved density restoration performance. In addition, we employ physics-based constraints such as mass conservation during the network training and application to further enable highly accurate density reconstructions. Our preliminary numerical results show that the models trained in our frameworks can remove significant portions of unknown noise in density time-series data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1991

Inversion techniques for recovering two-dimensional distributions of auroral emission rates from tomographic rocket photometer measurements

This paper demonstrates how the spatial distribution of optical emission rates within an auroral arc may be recovered from rocket photometer measurements made in a tomographic spin scan mode. The tomographic inversion procedures required to recover this information and the implementation of two inversion algorithms that are particularly well suited for dealing with the problem of noise in the observational data are described. The performance of the inversion algorithms and the limitations of the rocket tomography technique are assessed using various sets of simulated rocket measurements that were generated from 'known' auroral emission-rate distributions. The simulations are used to investigate how the quality of the tomographic recovery may be influenced by various factors such as noise in the data, rocket penetration of the auroral form, background sources of emission, smearing due to the photometer field of view, and temporal variations in the auroral form.

Mcdade, Ian. C.↗

DOE OSTI2025

Deployment and validation of predictive 6-dimensional beam diagnostics through generative reconstruction with standard accelerator elements

Understanding the 6-dimensional phase space distribution of particle beams is essential for optimizing accelerator performance. Conventional diagnostics such as use of transverse deflecting cavities offer detailed characterization but require dedicated hardware and space. Generative phase space reconstruction (GPSR) methods have shown promise in beam diagnostics, yet prior implementations still rely on such components. Here we present the first experimental implementation and validation of the GPSR methodology, realized by the use of standard accelerator elements including accelerating cavities and dipole magnets, to achieve complete 6-dimensional phase space reconstruction. Through simulations and experiments at the Pohang Accelerator Laboratory X-ray Free Electron Laser facility, we successfully reconstruct complex, nonlinear beam structures. Furthermore, we validate the methodology by predicting independent downstream measurements excluded from training, revealing the reconstruction closely resembling ground truth. This advancement establishes a pathway for predictive diagnostics across beamline segments while reducing hardware requirements and expanding applicability to various accelerator facilities.

Kim, Seongyeol [Pohang Univ. of Science and Techno↗

NASA NTRS1991

A user-oriented synthetic workload generator

A user oriented synthetic workload generator that simulates users' file access behavior based on real workload characterization is described. The model for this workload generator is user oriented and job specific, represents file I/O operations at the system call level, allows general distributions for the usage measures, and assumes independence in the file I/O operation stream. The workload generator consists of three parts which handle specification of distributions, creation of an initial file system, and selection and execution of file I/O operations. Experiments on SUN NFS are shown to demonstrate the usage of the workload generator.

Kao, Wei-Lun↗

NASA NTRS1990

Power system state estimation for a spacecraft power system

An application of the maximum likelihood state estimator to a space-based power system is presented. The state estimator uses current and voltage measurements to generate estimates of node voltages for an electrical power distribution system for the Space Shuttle. Preliminary results on the effect of noisy measurements on estimated parameters are reported. The software used in generating these results is part of an overall package being developed at Louisiana Tech University. Intended applications of this package include the analysis of power systems and real-time parallel processing on the Space Shuttle.

Berry, F. C.↗

DOE OSTI2022

Mass distributions of dijet resonances from excited quarks at proton-proton colliders

We study the expected experimental mass distributions of dijet resonances from excited quarks in proton-proton collisions at energies $\sqrt{s}$ = 13, 14, 27, 100, 300, and 500 TeV. We explore in detail the expected shapes at both the generator and experimental levels, and identify within the distributions the effects of the excited quark natural width, parton momentum distributions of the proton, radiation, and experimental resolution. We present both differential and cumulative probability distributions as a function of dijet mass, and the signal acceptance of a window in dijet mass centered on each resonance. We find that for a range of resonance masses, between 10% and 50% of $\sqrt{s}$, the dijet mass distributions and window acceptance are practically universal, approximately invariant under changes in resonance mass and $\sqrt{s}$. This universality is violated when the resonance mass reaches 60% of $\sqrt{s}$, because the steepness of the parton momentum distributions of the proton produces a significant tail at low dijet mass. This work supports our Snowmass 2021 study on the sensitivity to dijet resonances at proton-proton colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1977

Microvascular pressure responses of second-generation rats chronically exposed to 2 g centrifugation

Preliminary results are presented for a study aimed at a quantitative comparison of microvascular dynamics in second-generation rats reared in a 2-g force field produced by centrifugation with similar data from animals reared in a centrifuge that produced only a 1-g force. It is shown that the pressure distribution in the mesenteric microvasculature of the second generation of rats reared in a 2-g environment, as well as the animals' blood pressure response to epinephrine, are significantly different compared to their 1-g counterparts. In particular, 1-g and 2-g chronic centrifugation enhances the arterial blood pressure, and the 2-g force field attenuates the pressor effects of norepinephrine.

Richardson, D. R.↗

NASA NTRS1999

Feature Profile Evolution of SiO2 Trenches In Fluorocarbon Plasmas

Etching of silicon microstructures for semiconductor manufacturing in chlorine plasmas has been well characterized. The etching proceeds in a two-part process, where the chlorine neutrals passivate the Si surface and then the ions etch away SiClx. However, etching in more complicated gas mixtures and materials, such as etching of SiO2 in Ar/C4F8, requires knowledge of the ion and neutral distribution functions as a function of angle and velocity, in addition to modeling the gas surface reactions. In order to address these needs, we have developed and integrated a suite of models to simulate the etching process from the plasma reactor level to the feature profile evolution level. This arrangement allows for a better understanding, control, and prediction of the influence of equipment level process parameters on feature profile evolution. We are currently using the HPEM (Hybrid Plasma Equipment Model) and PCMCM (Plasma Chemistry Monte Carlo Model) to generate plasma properties and ion and neutral distribution functions for argon/fluorocarbon discharges in a GEC Reference Cell. These quantities are then input to the feature scale model, Simulation of Profile Evolution by Level Sets (SPELS). A surface chemistry model is used to determine the interaction of the incoming species with the substrate material and simulate the evolution of the trench profile. The impact of change of gas pressure and inductive power on the relative flux of CFx and F to the wafer, the etch and polymerization rates, and feature profiles will be examined. Comparisons to experimental profiles will also be presented.

Hwang, Helen↗

DOE OSTI2021

NO PLIF flow visualization and time-resolved temperature distributions in laser induced breakdown plumes

NO planar laser induced fluorescence (PLIF) is used to obtain images of laser-induced breakdown plasma plumes in NO-seeded nitrogen and dry air at near atmospheric pressure. Single-shot PLIF-images show that the plume development 5–50 μs after the breakdown pulse is fairly reproducible shot-to-shot, although the plume becomes increasingly stochastic on longer timescales, 100–500 μs. The stochastic behavior of the plume is quantified using probability distributions of the loci of the plume boundary. Analysis of the single-shot images indicates that the mixing of the plume with ambient gas on sub-ms time scale is insignificant. The induced flow velocity in the plume is fairly low, up to 30 m s –1 , suggesting that laser breakdowns are ineffective for mixing enhancement in high speed flows. The ensemble-averaged PLIF images indicate the evolution of the plume from an initially elongated shape to near-spherical to toroidal shape, with a subsequent radial expansion and formation of an axial jet in the center. Temperature distributions in the plume in air are obtained from the NO PLIF images, using two rotational transitions in the NO(X, v' = 0 → A, v'' = 0) band, J'' = 6.5 and 12.5 of the Q R 12 + Q 2 branch. The results indicate that the temperature in the plume remains high, above 1000 K, for approximately 100 μs, after which it decays gradually, to below 500 K at 500 μs. The residual NO fraction in the plume is ~0.1%, indicating that repetitive laser-assisted ignition may result in significant NO-generation. Furthermore, these measured temperature and velocity distributions can be used for detailed validation of kinetic models of laser-induced breakdown and assessment of their predictive capability.

42 ENGINEERING↗

DOE OSTI2026

Effectively Considering the Distribution System in Integrated Resource Plans

While electricity planning practices vary by state and utility based on utility type and market structure, integrated resource planning (IRP) remains a prominent vehicle — even in states with centrally-organized wholesale electricity markets. IRP focuses on meeting forecasted long-term electricity needs. Typically, utilities have not considered impacts of design and operation of the low-voltage distribution network in IRP. With advanced capabilities of grid-edge technologies to generate and store electricity and provide load flexibility, and large utility investments in distribution systems, it's increasingly important to consider at least some distribution planning elements in IRP. This report considers the value proposition for doing so, such as reducing utility costs through resource co-optimization and strategic siting of grid-edge resources, and idenfities the most important touchpoints between planning for bulk power and distribution systems and provide a range of tactics for integrating these two processes.

Relf, Grace [Lawrence Berkeley National Laboratory↗