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At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Structural and Optical Response of Polymer-Stabilized Blue Phase Liquid Crystal Films to Volatile Organic Compounds

Engineering useful mechanical properties into stimuli-responsive soft materials without compromising their responsiveness is, in many cases, an unresolved challenge. For example, polymer networks formed within blue-phase liquid crystals (BPs) have been shown to form mechanically robust films, but the impact of polymer networks on the response of these soft materials to chemical stimuli has not been explored. In this work, we report on the response of polymer-stabilized BPs (PSBPs) to volatile organic compounds (VOCs, using toluene as a model compound) and compare the response to BPs without polymer stabilization and to polymerized nematic and cholesteric phases. We find that PSBPs generate an optical response to toluene vapor (change in reflection intensity under crossed polars) that is sixfold greater in sensitivity than the polymerized nematic or cholesteric phases and with a limit of detection (140 ± 10 ppm at 25 °C) that is relevant to the measurement of permissible exposure limits for humans. Additionally, when compared to BPs that have not been polymerized, PSBPs respond to a broader range of toluene vapor concentrations (5000 vs <1000 ppm) over a wider temperature interval (25–45 vs 45–53 °C). We place these experimental observations into the context of a simple thermodynamic model to explore how the PSBP response reflects the effect of toluene on competing contributions of double-twisted LC cylinders, disclinations, and polymer network to the free energy that controls the PSBP lattice spacing. Overall, we conclude that the mechanical and thermal stability of PSBPs, when combined with their optical responsiveness to toluene, make this class of self-supporting LCs a promising one as the basis of passive and compact (e.g., wearable) sensors for VOCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Tensor networks for High Energy Physics: contribution to Snowmass 2021

Tensor network methods are becoming increasingly important for high-energy physics, condensed matter physics and quantum information science (QIS). We discuss the impact of tensor network methods on lattice field theory, quantum gravity and QIS in the context of High Energy Physics (HEP). These tools will target calculations for strongly interacting systems that are made difficult by sign problems when conventional Monte Carlo and other importance sampling methods are used. Further development of methods and software will be needed to make a significant impact in HEP. We discuss the roadmap to perform quantum chromodynamics (QCD) related calculations in the coming years. The research is labor intensive and requires state of the art computational science and computer science input for its development and validation. We briefly discuss the overlap with other science domains and industry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1989

Computational chaos in massively parallel neural networks

A fundamental issue which directly impacts the scalability of current theoretical neural network models to massively parallel embodiments, in both software as well as hardware, is the inherent and unavoidable concurrent asynchronicity of emerging fine-grained computational ensembles and the possible emergence of chaotic manifestations. Previous analyses attributed dynamical instability to the topology of the interconnection matrix, to parasitic components or to propagation delays. However, researchers have observed the existence of emergent computational chaos in a concurrently asynchronous framework, independent of the network topology. Researcher present a methodology enabling the effective asynchronous operation of large-scale neural networks. Necessary and sufficient conditions guaranteeing concurrent asynchronous convergence are established in terms of contracting operators. Lyapunov exponents are computed formally to characterize the underlying nonlinear dynamics. Simulation results are presented to illustrate network convergence to the correct results, even in the presence of large delays.

Barhen, Jacob↗

NASA NTRS1995

Optical fiber sensors for damage analysis in aerospace materials

Under this grant, fiber optic sensors were investigated for use in the nondestructive evaluation of aging aircraft. Specifically, optical fiber sensors for detection and location of impacts on a surface, and for detection of corrosion in metals were developed. The use of neural networks was investigated for determining impact location by processing the output of a network of fiberoptic strain sensors distributed on a surface. This approach employs triangulation to determine location by comparing the arrival times at several sensors, of the acoustic signal generated by the impact. For this study, a neural network simulator running on a personal computer was used to train a network using a back-propagation algorithm. Fiber optic extrinsic Fabry-Perot interferometer (EFPI) strain sensors are attached to or embedded in the surface, so that stress waves emanating from an impact can be detected. The ability of the network to determine impact location by time-or-arrival of acoustic signals was assessed by comparing network outputs with actual experimental results using impacts on a panel instrumented with optical fiber sensors. Using the neural network to process the sensor outputs, the impact location can be inferred to centimeter range accuracy directly from the arrival time data. In addition, the network can be trained to determine impact location, regardless of material anisotropy. Results demonstrate that a back-propagation network identifies impact location for an anisotropic graphite/bismaleimide plate with the same accuracy as that for an isotropic aluminum plate. Two different approaches were investigated for the development of fiber optic sensors for corrosion detection in metals, both utilizing optical fiber sensors with metal coatings. In the first approach, an extrinsic Fabry-Perot interferometric fiber optic strain sensor was placed under tensile stress, and while in the resulting strained position, a thick coating of metal was applied. Due to an increase in the quantity of material, the sensor does not return to its original position upon removal of the applied stress, and some residual strain is maintained within the sensor element. As the metal thickness decreases due to corrosion, this strain is released, providing the sensing mechanism for corrosion detection. In the second approach, photosensitive optical fibers with long period Bragg gratings in the core were coated with metal. The Bragg gratings serve to couple core modes at discrete wavelengths to cladding modes. Since cladding modes interact with the metal coating surrounding the fiber cladding, the specific wavelengths coupled from core to cladding depend on the refractive index of the metal coating. Therefore, as the metal corrodes, the resulting change in index of the coating may be measured by measuring the change in wavelength of the coupled mode. Results demonstrate that both approaches can be successfully used to track the loss in metal coating on the optical fiber sensors due to corrosion.

Schindler, Paul↗

DOE OSTI2024

Fracture Network Influence on Rock Damage and Gas Transport following an Underground Explosion

Simulations of rock damage and gas transport following underground explosions that omit preexisting fracture networks in the subsurface cannot fully characterize the influence of geo-structural variability on gas transport. Previous studies do not consider the impact that fracture network structure and variability have on gas seepage. In this study, we develop a sequentially coupled, axi-symmetric model to look at the damage pattern and resulting gas breakthrough curves following an underground explosion given different fracture network realizations. We simulate 0.327 and 0.164 kT chemical explosives with burial depths of 100 m for 90 stochastically generated fracture networks. Gases quickly reach the surface in 30% of the higher yield simulations and 5% of the lower yield simulations. The fast breakthrough can be attributed to the formation of connected pathways between fractures to the surface. The formation of a connected damage pathway to the surface is not clearly correlated with the fracture intensity (P32) in our simulations. Breakthrough curves with slower transport are highly variable depending on the fracture network sample. The variability in the breakthrough behavior indicates that ignoring the influence of fracture networks on rock damage, which strongly influences the hydraulic properties following an underground explosion, will likely lead to a large underestimation of the uncertainty in the gas transport to the surface. This work highlights the need for incorporation of fracture networks into models for accurately predicting gas seepage following underground explosions.

58 GEOSCIENCES↗

DOE OSTI2023

Assignment of Freight Traffic in a Large-scale Intermodal Network under Uncertainty

This paper presents a methodology for freight traffic assignment in a large-scale road-rail intermodal network under uncertainty. Network uncertainties caused by natural disasters have dramatically increased in recent years. Several of these disasters (e.g., Hurricane Sandy, Mississippi River Flooding, and Hurricane Harvey) severely disrupted the U.S. freight transportation network, and consequently, the supply chain. To account for these network uncertainties, a stochastic freight traffic assignment model is formulated. An algorithmic framework, involving the sample average approximation and gradient projection algorithm, is proposed to solve this challenging problem. The developed methodology is tested on the U.S. intermodal network with freight flow data from the Freight Analysis Framework. The experiments consider three types of natural disasters that have different risks and impacts on transportation networks: earthquakes, hurricanes, and floods. It is found that for all disaster scenarios, freight ton-miles are higher compared to the base case without uncertainty. The increase in freight ton-miles is the highest under the flooding scenario; this is because there are more states in the flood-risk areas, and they are scattered throughout the U.S.

42 ENGINEERING↗

NASA NTRS1982

A network control concept for the 30/20 GHz communication system baseband processor

The architecture and system design for a satellite-switched TDMA communication system employing on-board processing was developed by Motorola for NASA's Lewis Research Center. The system design is based on distributed processing techniques that provide extreme flexibility in the selection of a network control protocol without impacting the satellite or ground terminal hardware. A network control concept that includes system synchronization and allows burst synchronization to occur within the system operational requirement is described. This concept integrates the tracking and control links with the communication links via the baseband processor, resulting in an autonomous system operational approach.

Sabourin, D. J.↗

NASA NTRS2003

Thermal Conductivity Studies of Sedimentary Materials from Central Australia and the Implications for Mars

In the search for life on Mars, investigating fluvial deposits will be a high priority for future landers. Although there is abundant evidence that fluvial processes worked with great intensity in the past (e.g., outflow channels, valley networks, and modified impact craters), aeolian processes dominate under the current environmental conditions. In fact there is evidence that extensive aeolian deposits may have filled in valley networks [1] and even shallow depressions where water may have ponded [2]. Thus, quite often there may be a disparity between the geology identified by orbital data and the geology accessible to a lander. Determining where fluvial deposits occur on the surface is important for addressing NASA's goal to "follow the water." In order to do that, however, existing remote sensing data must be evaluated and a set of diagnostic criteria for recognizing fluvial deposits must be established. To that end, we are conducting a first order analysis of the thermal characteristics of fluvial and aeolian materials collected from central Australia.

Craddock, Robert A.↗

NASA NTRS2023

Impacts of Marine Surface Pressure Observations From A Spaceborne Differential Absorption Radar Investigated With an Observing System Simulation Experiment

A new instrument has been proposed for measuring surface air pressure over the marine surface with a combined active/passive scanning multi-channel differential absorption radar (DAR) to provide an estimate of the total atmospheric column oxygen content. A demonstrator instrument, the Microwave Barometric Radar and Sounder (MBARS), has been funded by the National Aeronautics and Space Administration (NASA) for airborne test missions. Here, a proof-of-concept study to evaluate the potential impact of spaceborne surface pressure data on numerical weather prediction is performed using the Goddard Modeling and Assimilation Office global observing system simulation experiment (OSSE) framework. This OSSE framework employs the Goddard Earth Observing System model and the hybrid 4D ensemble variational Gridpoint Statistical Interpolation data assimilation system. Multiple flight and scanning configurations of potential spaceborne orbits are examined. Swath width and observation spacing for the surface pressure data are varied to explore a range of sampling strategies. For wider swaths, the addition of surface pressures reduces the root mean square surface pressure analysis error by as much as 20% over some ocean regions. The forecast sensitivity observation impact tool estimates impacts on the Pacific Ocean basin boundary layer 24-hour forecast temperatures for spaceborne surface pressures on par with rawinsondes and aircraft, and greater impacts than the current network of ships and buoys. The largest forecast impacts are found in the southern hemisphere extratropics.

N.C. Privé↗

DOE OSTI2025

Solution‐Like Water Transport Across Molecular to Macroscopic Length Scales in Crosslinked Poly(Ethylene Glycol Diacrylate) Networks With Tailored Sidechains

Poly(ethylene glycol) (PEG)‐based materials, like PEG‐diacrylate (PEGDA), are prized for their hydrophilic, inert properties, and leveraged in hydrogels and as membrane mimics. While network chemistry is often tuned for selective transport and antifouling, fundamental understanding of water dynamics at the network surface and the impact on bulk transport is limited. We utilize Overhauser dynamic nuclear polarization (ODNP) to measure nanoscale water diffusivity near a tethered spin label at the water‐polymer surface and compare it to bulk water diffusivity from pulsed field gradient (PFG) NMR. Via active ester chemistry, spin labels and varied sidechain chemistries are introduced, modulating network hydrophilicity. Tuning network hydration through crosslinker content and functional groups further impacts water diffusivity. Results show rapid nanoscale water transport at the polymer surface, reflecting network volumetric water content, with further modulation by sidechain functionality. These findings demonstrate PEGDA's utility as a membrane mimic and the critical impact of network chemistry on water transport.

hydrogels↗

DOE OSTI2024

Enriching OpenStreetMap network data for transportation applications: Insights into the impact of urban congestion on accessibility

OpenStreetMap (OSM) data is a valuable open-source resource for various transportation, traffic, and planning applications. However, OSM network data lack operating traffic speed information, which is critical for transport planning and operations. Addressing this shortcoming, this study leverages commercial vendor data (to serve as ground truth) with exogenous, open-source variables characterizing local transport infrastructure, land use, and demographic information to predict average congested traffic speeds on OSM networks. Three machine-learning models were tested and estimated for OSM links with and without speed limit information in the Denver metropolitan region. Among these, XGBoost performed best, with mean absolute errors of 3.27 and 3.62 mph for links with and without speed limits, respectively. The developed models accurately predicted traffic speeds for different hours and days of the week compared to ground truth data. Using these predicted speeds, drive accessibility scores were computed for the Denver region for different time periods using the Mobility Energy Productivity (MEP) metric to understand the impact of congestion on energy-efficient accessibility. Results show that congestion-adjusted drive accessibility can be significantly lower compared to accessibility calculated using free flow speeds. Specifically, weekday evening hours saw a 42 % drop in accessibility due to reduced speeds, particularly around downtown Denver. Across the Denver metro region, approximately half as many opportunities and jobs are accessible in under 20 min by car during the evening peak period relative to free flow conditions. These findings underscore the importance of using congestion-adjusted operating speeds rather than speed limits in accessibility calculations, as reliance on speed limits can substantially overestimate energy-efficient drive accessibility in large, car-centric cities susceptible to significant congestion. In conclusion, the methodology presented here could further enrich OSM network data, making them useful for an even broader range of transportation applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1998

Potential Mars Surveyor 2001 Landing Sites: Low-Elevation Cratered "Highlands" in Central and Eastern Sinus Meridiani and Near Amenthes Fossae

The main scientific goal for the Mars Surveyor Program 2001 (MSP 01) landed mission is to collect and characterize 91 rock and 13 soil core samples using an integrated instrument suite onboard the Athena Rover. If possible, these samples will be retrieved and returned to Earth via a MSP 05 or MSP 07 mission. Preliminary engineering constraints for the MSP 01 landing site call for a location that lies between 15 S and 30 N, and below about 2 km elevation (based on Viking-era topography). Desirable landing sites for MSP 01 are to be located "in the ancient highlands where the environmental conditions may have been favorable to the preservation of evidence of possible prebiotic or biotic processes including the emergence (and, potentially, the persistence) of life". We interpret this to mean that the desirable sites include those that have evidence of aqueous sediments that might have been deposited during the Noachian and/or Hesperian Epochs of Mars' history. In addition to the search for subaqueous sedimentary deposits, we took into consideration the fact that the rover, Athena, will need to be able to access these materials. Thus, a site where aeolian deflation has occurred might be desirable because it might expose, in situ, layered sedimentary deposits. Deflated areas, of course, might include potential landing hazards in the form of meterscale buttes and mesas (e.g., Christmas Lake Valley, OR), thus careful study of such sites with high resolution images will be required before a decision is made to land. We have been examining three regions that have potential to be considered for MSP 01 landing sites. This work is based on Viking (VIS, IRTM) and Phobos 2 (Termoskan) observations and should be regarded as preliminary because we believe that the final site selection should also be based upon analysis of Mars Global Surveyor observations that help constrain mineralogy (TES) and local geomorphology (MOC, MOLA). (1) Eastern Sinus Meridiani Region (proposed by K. S. Edgett) Sinus Meridiani is a persistent low-albedo (< 0. 16) region on the martian equator that has been recognized for about 400 years. All of Sinus Meridiani is below the 2 km elevation constraint for MSP 01. The region includes cratered highlands, valley networks, aeolian dunes, and possible aqueous sedimentary deposits. The landing site study region is located in the eastern portion of Sinus Meridiani. It is bounded by latitudes 10 S to 2 N, longitudes 355 W to 345 W, and the elevations are mostly 1-2 km. The center of this area contains a medium-albedo (0.19-0.21), relatively smooth-surfaced deposit that was suggested by Rice to be a lacustrine deposit. Several potential landing areas can be suggested within this region. Based on Viking and Phobos 2 data, the favored sites so far are centered at 7.6 S, 346.9 W and 0.8 S, 349 W. Thermal inertias are 3.2-7.0 x 10(exp -3) cal /sq cm s(exp -0.5)/K; and rock abundances are around 2-6%. The site at 7.6 S, 346.9 W is at the southern end of the smooth, medium-albedo unit that might have a lacustrine origin. At this location, numerous channels appear to have drained toward the smooth unit. Viking images from orbit 747A show this area at about 15 m/pixel ground resolution. The images reveal that aeolian deflation has occurred along the deposit's margins. Bright (i.e., albedo >= 0.21) aeolian dunes are present on the channel floors and in some of the depressions on the smooth unit. The bright, apparently active dunes might consist of material (perhaps lakedeposited sands) that has been eroded from the smooth unit. The site at approximately 0.8 S, 349 W is selected because it offers an opportunity to solve a long-standing puzzle about Mars remote sensing. There are three main "color" units on Mars: "dark red, dark gray, and bright red". This landing site would allow the Athena rover an opportunity to investigate all three materials within close proximity (the best place on Mars to do so). There are no high resolution (better than 100 m/pixel) Viking or Mariner images of this site. (2) Central Sinus Meridiani Region (proposed by K. S. Edgett and T. J. Parker) Central Sinus Meridiani is characterized by two types of surfaces [4]. One is like typical martian cratered highlands elsewhere- there are old valley networks and old impact craters. The other is relatively smooth and flat. These two units are in contact around 3.1 S between 5 W and 4 E longitudes. Valley networks- including one at 6'S, 358 W that rivals the Grand Canyon of Arizona- once drained toward the smooth unit. Edgett and Parker [4] proposed that the smooth unit might consist of sediments laid down in a large Noachian-aged sea/ocean that would have covered much of the northern hemisphere. Schultz and Lutz [I I I suggested that it is a paleopolar layered deposit. Regardless, the smooth unit where it contacts the cratered terrain would make an excellent site for Athena rover to investigate. The site is best seen in Viking high resolution images from orbits 408B (about 30 m/pixel) and 746A (about 12 m/pixel). These images suggest that aeolian deflation has occurred along the margin of the smooth unit, and this deflation has exposed horizontal larrs of material. The elevation is about 0.5 km; thermal inertias are 6.5-8.0 x 10(exp -3) cal /sq cm s(exp -0.5) / K; rock abundances are 2-4%; and the surface is probably sandy with dark drifts and ripples but almost no actual dunes. We suggest a landing around 3.2 S, 3.0 W would test the aqueous sediment hypothesis and provide a potentially smooth surface on which to land. (3) Amenthes Fossae Region (proposed by S. N. Huntwork and K. S. Edgett) The Amenthes Fossae are a series of graben/fissures that are circumferential to the southeast side of Isidis Planitia. These fissures cross a variety of ancient, heavily cratered Noachian terrain and younger, Hesperian and Amazonian terrain. We focused our search on a region 0-15 N, 250 - 270 W. Elevations are -0.5 to 2 km. Depending upon whether Isidis Planitia was ever a water-rich environment, this region might have been influenced by aqueous sedimentation. Valley networks are common, and they drained toward the north and northwest. We focused our work on a set of Viking orbiter high-resolution images, 719A 1-48. These have resolutions 16-24 rri/pixel. We examined images 20-23, centered at 2 N, 258 W. This site, on the plains just southwest of a 42 km-diameter crater, includes a valley network channel, a relatively young crater ejecta deposit, a few buttes composed of presumably ancient, Noachian bedrock, and a "plains" unit. The plains might make an ideal landing surface, except for the presence of some fine-scale ridges (oriented approximately N-S). The ridges are probably yardangs, thus this site offers a place where aeolian deflation has probably exposed some of the layered rock units that comprise the "plains". Thermal inertias are 7.9-8.3 x 10(exp -3) cal/sq cm s(exp -0.5) /K and rock abundances are 10-15%. A rover traverse might include the opportunity to go down to the floor (and sample along the walls) of the valley network channel at 2 N 258.1 W.

Edgett, K. S.↗

DOE OSTI2021

Topological Machine Learning Methods for Power System Responses to Contingencies

While deep learning tools, coupled with the emerging machinery of topological data analysis, are proven to deliver various performance gains in a broad range of applications, from image classification to biosurveillance to blockchain fraud detection, their utility in areas of high societal importance such as power system modeling and, particularly, resilience quantification in the energy sector yet remains untapped. To provide fast acting synthetic regulation and contingency reserve services to the grid while having minimal disruptions on customer quality of service, we propose a new topology-based system that depends on a neural network architecture for impact metric classification and prediction in power systems. This novel topology-based system allows one to evaluate the impact of three power system contingency types, in conjunction with transmission lines, transformers, and transmission lines combined with transformers. We show that the proposed new neural network architecture equipped with local topological measures facilitates more accurate classification of unserved load as well as the amount of unserved load. In addition, we are able to learn more about the complex relationships between electrical properties and local topological measurements on their simulated response to contingencies for the NREL-SIIP power system.

contingency analysis↗

DOE OSTI2021

Topological Machine Learning Methods for Power System Responses to Contingencies: Preprint

While deep learning tools, coupled with the emerging machinery of topological data analysis, are proven to deliver various performance gains in a broad range of applications, from image classification to biosurveillance to blockchain fraud detection, their utility in areas of high societal importance such as power system modeling and, particularly, resilience quantification in the energy sector yet remain untapped. To provide fast acting synthetic regulation and contingency reserve services to the grid while having minimal disruptions on customer quality of service, we propose a new topologybased system that depends on neural network architecture for impact metrics classification and prediction in power systems. This novel topology-based system allows one to evaluate the impact of three power system contingency types, namely, in conjunction with transmission lines, transformers, and transmission lines combined with transformers. We show that the proposed new neural network architecture equipped with local topological measures facilitates both more accurate classification of unserved load as well as the amount of unserved load. In addition, we are able to learn complex relationships between electrical properties and local topological measurements on the simulated response to contingencies for NREL-SIIP power system.

graph theory↗

DOE OSTI2025

Time‐series multi‐omics analysis of micronutrient stress in Sorghum bicolor reveals iron and zinc crosstalk and regulatory network conservation

Micronutrient stress impacts growth, biomass production, and grain yield in crops. Multi-omics studies are valuable resources in identifying genes for functional studies and trait improvement, such as accumulation of Fe or Zn under deficient or excess conditions for bioenergy or grain agriculture. We conducted transcriptomics and ionomics analyses on Sorghum bicolor BTx623, grown under Fe and Zn limited and excess conditions over a 21-day period. To identify early and late transcriptional response in roots and leaves, 180 RNAseq libraries were sequenced for differential expression and co-expression network analyses. Fe and Zn accumulation was measured using ICP-MS at each time point, and a fluorometer was used to estimate chlorophyll content in leaves. Among the four treatments, Fe limitation and Zn excess resulted in the largest phenotypic effects and transcriptional response in roots and leaves. Several of the reduction (Strategy I) and chelation (Strategy II) strategy genes that improve bioavailability of Fe and Zn in plant roots often used by non-grass and grass species, respectively, were differentially expressed. Gene regulatory network (GRN) analysis of roots revealed enrichment of genes from Fe limiting and Zn excess which strongly connect to homologues of SbFIT, SbPYE, and SbBTS as hub genes. The GRN for leaf responses showed homologues of SbPYE and SbBTS as hubs connecting genes for chloroplast biosynthesis, Fe-S cluster assembly, photosynthesis, and ROS scavenging. Expression analyses suggest sorghum uses Strategy II genes for Fe and Zn uptake, as expected, but can also utilize Strategy I genes, which may be advantageous in variable moisture environments. We found strong overlap between Fe and Zn responsive GRNs, indicative of micronutrient crosstalk. We also found conservation of root and leaf GRNs, and known homologous genes suggest strong constraints on homeostasis networks in plants. These data will provide a resource for functional genetics to enhance micronutrient transport in sorghum, and opportunities to conduct further comparative GRN analysis across diverse crops species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

A Data Processing Pipeline for Socio-Technical Network Analysis [Slides]

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

A Data Processing Pipeline for Adversarial Socio-Technical Network Analysis

With the rapid adoption of emerging technologies, there is a need to catalog and model sociotechnical interdependencies that have been historically used to influence the operation of Critical Infrastructure networks including the impacts of mergers and acquisitions, hostile takeovers, and foreign investment. Our research intends to address this need with two primary contributions. First, we have developed a data curation and processing pipeline to generate sociotechnical networks extracted from a variety of data sources including SEC filings and infrastructure asset databases. The pipeline, implemented in Apache Airflow, extracts and normalizes the representation of entities and relations, specified within ontologies. Our intent is to provide an extensible, machine-actionable approach to quickly communicate such models, reproduce previous results, and adapt them to new, unanticipated situations. Second, networks produced by our pipeline enable the development of graph-theoretic metrics that consider the properties of network components in addition to its topology. Metadata associated with network components---whether semantic, temporal, or geospatial---affects the alignment of generated networks with assumptions underlying complexity metrics. Validation of generated networks relative to component types defined by an ontology, may allow the research community to adapt metrics to the semantics of the domains being studied. Generated networks may be processed as knowledge, dynamic, or spatial graphs and enables a variety of analyses including automated reasoning and measures of network complexity. Automated reasoning views extracted entities and relations as a knowledge graph; this enables application of inference rules that represent historically-attested adversarial business methods and applies that behavior to a specific geographic context. Measures of network complexity, including degree distribution, reachability analyses, temporal analysis, and community detection can be adapted to indicate adversarial organizational influence.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

ML-Based Power System Stability Assessment Considering Network Topology Changes: WECC 20,000+ Bus System Case Study

Modern power grids are fast-changing and thus require real-time monitoring and online stability assessment. With the rapid development of machine learning (ML) techniques, using data-driven models to provide fast and accurate estimations of power system stability marginal information, such as frequency nadir for frequency stability and critical clearing time (CCT) for transient stability, have become possible. However, despite the numerous research on ML-based methods for frequency nadir and CCT prediction, there is limited work on the impact of different network topology changes. Furthermore, most previous studies only focused on small or synthetic systems, and there is a lack of research on actual large power system models. In this paper, the above issues are addressed by studying the actual U.S. Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. Massive simulations are conducted in PowerWorld Simulator to study the impact of various topology change scenarios on both frequency stability and transient stability. System operating information is extracted from the success dispatch cases of various network topologies to generate a comprehensive dataset for ML-based models. Two ML methods, random forest (RF) and multilayer perceptron (MLP) neural network, are trained and tested for both frequency nadir prediction and CCT prediction. Test results have proven the models are capable of online stability assessment for large power networks such as the WECC system with sufficient accuracy.

critical clearing time↗