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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.

Vrieling, Anton↗
DOE OSTI2018

ECP-copa/ExaMiniMD

ExaMiniMD is a proxy application for Molecular Dynamics (MD) codes such as LAMMPS. Its intend is to facilitate research and development on MD algorithms in particular in the context of CoDesign efforts with hardware vendors. Currently, ExaMiniMD implements a basic Lennard Jones two body potential as well as the SNAP many body potential, both of which are available in LAMMPS. It also includes basic neighbor list builds as well as constant energy integration as found in LAMMPS and other MD codes. A feature not generally available in other MD codes is a set of statistical correctness checks which will help other developers judge whether changes to the code still give correct answers. ExaMiniMD is using the Kokkos programming model to achieve performance portability and is able to run across all major HPC platforms (GPUs, ManyCore, CPUs).

Thompson, Aidan↗
DOE OSTI2020

High-temperature and high-pressure NMR investigations of low viscous fluids confined in mesoporous systems

Abstract In this contribution, the relaxation and diffusional behaviors of low viscous fluids, water and methanol confined into mesoporous silica and controlled size pore glass were investigated. The engineered porous systems are relevant to geologically important subsurface energy materials. The engineered porous proxies were characterized by Brunauer–Emmett–Teller (BET) surface analyzer, nuclear magnetic resonance (NMR) spectroscopy, and electron microscopy (EM) to determine surface area, pore-wall protonation and morphology of these materials, respectively. The confined behavior of the low viscous fluids was studied by varying pore diameter, fluid-to-solid ratio, temperature, and pressure, and then compared to bulk liquid state. Both relaxation and diffusion behaviors for the confined fluids showed increasing deviation from pure bulk fluids as the fluid-to-solid ratio was decreased, and surface-to-volume ratio ( S / V ) was varied. Variable pressure deuteron NMR relaxation of confined D 2 O and confined methanol, deuterated at the hydroxyl or methyl positions, were performed to exploit the sensitivity of the deuteron quadrupole moment to molecular rotation. The methanol results demonstrated greater pressure dependence than those for water only in bulk. The deviations from bulk liquid behavior arise from different reasons such as confinement and the interactions between confined fluid and the nano-pore wall. The results of the present report give insight into the behavior of low viscosity fluid in nano-confined geometries under different state conditions.

Chemistry↗
DOE OSTI2019

Genetic variation of biomass recalcitrance in a natural Salix viminalis (L.) population

Background Salix spp. are high-productivity crops potentially used for lignocellulosic biofuels such as bioethanol. In general, pretreatment is needed to facilitate the enzymatic depolymerization process. Biomass resistance to degradation, i.e., biomass recalcitrance , is a trait which can be assessed by measuring the sugar released after combined pretreatment and enzymatic hydrolysis. We have examined genetic parameters of enzymatic sugar release and other traits related to biorefinery use in a population of 286 natural Salix viminalis clones. Moreover, we have evaluated phenotypic and genetic correlations between these traits and performed a genomewide association mapping analysis using a set of 19,411 markers. Results Sugar release (glucose and xylose) after pretreatment and enzymatic saccharification proved highly variable with large genetic and phenotypic variations, and chip heritability estimates (h 2 ) of 0.23-0.29. Lignin syringyl/guaiacyl (S/G) ratio and wood density were the most heritable traits (h 2 = 0.42 and 0.59, respectively). Sugar release traits were positively correlated, phenotypically and genetically, with biomass yield and lignin S/G ratio. Association mapping revealed seven marker-trait associations below a suggestive significance threshold, including one marker associated with glucose release. Conclusions We identified lignin S/G ratio and shoot diameter as heritable traits that could be relatively easily evaluated by breeders, making them suitable proxy traits for developing low-recalcitrance varieties. One marker below the implied threshold for marker associations was identified for sugar release, meriting further investigation while also highlighting the difficulties in employing genomewide association mapping for complex traits.

09 BIOMASS FUELS↗
DOE OSTI2020

Development of MGMC: A proxy Multi-Group Monte Carlo Particle Transport Application

This document details the development and current state of MGMC: a proxy Multi-Group Monte Carlo transport application. The goal of this work was to develop a light-weight Monte Carlo transport solver that could be easily reconfigured to test parallelization strategies targeting advanced architectures and heterogeneous computing environments. Additionally, MGMC is able to act as a proxy-app for testing the development of algorithms and the integration of other libraries and into Monte Carlo transport codes. MGMC is currently able to run in parallel using OpenMP for CPU threads or CUDA for NVIDIA GPUs. MGMC was also used to investigate the using SYCL for portable parallelization targeting either CPU threads, vender-agnostic GPUs, and ARM chips, detailed in Section II. In the process of developing MGMC, several other C++ libraries have been created with the intent for re-use in future research projects and potential inclusion in production-level codes, detailed in Section III. The physics capabilities in MGMC are detailed in Section IV, code verification is detailed in Section V, and performance results are detailed in Section VI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

ALTSched: Improved Scheduling for Time-domain Science with LSST

Abstract Telescope scheduling is the task of determining the best sequence of observations (pointings and filter choices) for a survey system. Because it is computationally intractable to optimize over all possible multiyear sequences of observations, schedulers use heuristics to pick the best observation at a given time. A greedy scheduler selects the next observation by choosing whichever one maximizes a scalar merit function, which serves as a proxy for the scientific goals of the telescope. This sort of bottom-up approach for scheduling is not guaranteed to produce a schedule for which the sum of merit over all observations is maximized. As an alternative to greedy schedulers, we introduce ALTS ched, which takes a top-down approach to scheduling. Instead of considering only the next observation, ALTS ched makes global decisions about which area of sky and which filter to observe in, and then refines these decisions into a sequence of observations taken along the meridian to minimize airmass. We implement ALTS ched for the Large Synoptic Survey Telescope (LSST) and show that it equals or outperforms the baseline greedy scheduler in essentially all quantitative performance metrics. Due to its simplicity, our implementation is considerably faster than O p S im , the simulated greedy scheduler currently used by the LSST Project: a full 10-yr survey can be simulated in 4 minutes, as opposed to tens of hours for O p S im . LSST’s hardware is fixed, so improving the scheduling algorithm is one of the only remaining ways to optimize LSST’s performance. We see ALTS ched as a prototype scheduler that gives a lower bound on the performance achievable by LSST.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

Using Cloud-to-Ground Lightning Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

Each morning, the forecasters at the National Weather Service in Melbourn, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (http://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in central Florida, especially during the warm season months of May-September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC (0700 AM EST) each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Currently, the forecasters create each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent is to increase consistency between forecasters while enabling them to focus on the mesoscale detail of the forecast, ultimately benefiting the end-users of the product. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) for which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities from National Lightning Detection Network (NLDN) data. The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at the two organizations provided this data and supporting software for the work performed by the AMU. The densities were first stratified by flow regime, then by time in 1-, 3-, 6-, 12-, and 24-hour increments while maintaining the 2.5 km x 2.5 km grid resolution. A CG frequency of occurrence was calculated for each stratification and grid box by counting the number of days with lightning and dividing by the total number of days in the data set. New CG strike densities were calculated for each stratification and grid box by summing the strike number values over all warm seasons, then normalized by dividing the summed values by the number of lightning days. This makes the densities conditional on whether lightning occurred. The frequency climatology values will be used by forecasters as proxy inputs for lightning prObability, while the density climatology values will be used for CG amount. In addition to the benefits outlined above, these climatologies will provide improved temporal and spatial resolution, expansion of the lightning threat area to include adjacent coastal waters, and potential to extend the forecast to include the day-2 period. This presentation will describe the lightning threat index map, discuss the work done to create the maps initialized with climatological guidance, and show examples of the climatological CG lightning densities and frequencies of occurren based on flow regime.

Lambert, Winnie↗
DOE OSTI2016

Redshift Measurement and Spectral Classification for eBoss Galaxies with the Redmonster Software

“Cosmological redshift surveys” are experiments conducted with astronomical telescopes, imagers, and spectrographs, which map the three-dimensional structure of the universe on the largest scales. These maps are delineated by the positions of galaxies, quasars, and intergalactic hydrogen clouds. When interpreted in the context of Einstein’s theory of gravity, these maps can be used to infer the nature of the contents of the universe, including the mysterious “dark energy” that is driving the expansion of the universe to accelerate. While the directional positions of galaxies and other objects can be measured directly in images of the sky, the third dimension of their position (i.e., their distance from the Earth and the Milky Way Galaxy) must be measured by spectrographs that distribute their light as a function of frequency, enabling a measurement of their cosmological Doppler shift (or “redshift”), which serves as an observable proxy for distance. The largest cosmological redshift surveys, such as the “eBOSS” experiment of the fourth Sloan Digital Sky Survey, collect spectroscopic data for hundreds of thousands to millions of galaxies. Future experiments such as the Dark Energy Spectroscopic Instrument will in turn collect tens of millions of spectra. To be feasible, redshift measurement methods in datasets of this scale must be made with automated software. This paper describes the algorithms, astrophysical templates, and implementation of a new redshift measurement software package that is optimized to run on large numbers of spectra with relatively low signal-to-noise ratio, typical of the most ambitious current and future cosmological redshift surveys. The software is demonstrated on spectroscopic data from the eBOSS survey, with performance that meets the scientific requirements of that experiment. The software is implemented in a general framework that will allow application to spectra from the DESI project in the future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2004

Advances in Scientific Balloon Thermal Modeling

The National Aeronautics and Space Administration's Balloon Program office has long acknowledged that the accurate modeling of balloon performance and flight prediction is dependant on how well the balloon is thermally modeled. This ongoing effort is focused on developing accurate balloon thermal models that can be used to quickly predict balloon temperatures and balloon performance. The ability to model parametric changes is also a driver for this effort. This paper will present the most recent advances made in this area. This research effort continues to utilize the "Thrmal Desktop" addition to AUTO CAD for the modeling. Recent advances have been made by using this analytical tool. A number of analyses have been completed to test the applicability of this tool to the problem with very positive results. Progressively detailed models have been developed to explore the capabilities of the tool as well as to provide guidance in model formulation. A number of parametric studies have been completed. These studies have varied the shape of the structure, material properties, environmental inputs, and model geometry. These studies have concentrated on spherical "proxy models" for the initial development stages and then to transition to the natural shaped zero pressure and super pressure balloons. An assessment of required model resolution has also been determined. Model solutions have been cross checked with known solutions via hand calculations. The comparison of these cases will also be presented. One goal is to develop analysis guidelines and an approach for modeling balloons for both simple first order estimates and detailed full models. This papa presents the step by step advances made as part of this effort, capabilities, limitations, and the lessons learned. Also presented are the plans for further thermal modeling work.

Bohaboj, T.↗
DOE OSTI2020

Duration of Contagion of Foot-And-Mouth Disease Virus in Infected Live Pigs and Carcasses

Data-driven modeling of incursions of high-consequence, transboundary pathogens of animals is a critical component of veterinary preparedness. However, simplifying assumptions and excessive use of proxy measures to compensate for gaps in available data may compromise modeled outcomes. The current investigation was prospectively designed to address two major gaps in current knowledge of foot-and-mouth disease virus (FMDV) pathogenesis in pigs: the end (duration) of the infectious period and the viability of FMDV in decaying carcasses. By serial exposure of sentinel groups of pigs to the same group of donor pigs infected by FMDV A24 Cruzeiro, it was demonstrated that infected pigs transmitted disease at 10 days post infection (dpi), but not at 15 dpi. Assuming a latent period of 1 day, this would result in a conservative estimate of an infectious duration of 9 days, which is considerably longer than suggested by a previous report from an experiment performed in cattle. Airborne contagion was diminished within two days of removal of infected pigs from isolation rooms. FMDV in muscle was inactivated within 7 days in carcasses stored at 4°C. By contrast, FMDV infectivity in vesicle epithelium harvested from intact carcasses stored under similar conditions remained remarkably high until the study termination at 11 weeks post mortem. The output from this study consists of experimentally determined data on contagion associated with FMDV-infected pigs. This information may be utilized to update parameterization of models used for foot-and-mouth disease outbreak simulations involving areas of substantial pig production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

High-Performance and Traditional Multicrystalline Silicon: Comparing Gettering Responses and Lifetime-Limiting Defects

In recent years, high-performance multicrystalline silicon (HPMC-Si) has emerged as an attractive alternative to traditional ingot-based multicrystalline silicon (mc-Si), with a similar cost structure but improved cell performance. Herein, we evaluate the gettering response of traditional mc-Si and HPMC-Si. Microanalytical techniques demonstrate that HPMC-Si and mc-Si share similar lifetime-limiting defect types but have different relative concentrations and distributions. HPMC-Si shows a substantial lifetime improvement after P-gettering compared with mc-Si, chiefly because of lower area fraction of dislocation-rich clusters. In both materials, the dislocation clusters and grain boundaries were associated with relatively higher interstitial iron point-defect concentrations after diffusion, which is suggestive of dissolving metal-impurity precipitates. The relatively fewer dislocation clusters in HPMC-Si are shown to exhibit similar characteristics to those found in mc-Si. Given similar governing principles, a proxy to determine relative recombination activity of dislocation clusters developed for mc-Si is successfully transferred to HPMC-Si.

14 SOLAR ENERGY↗
NASA NTRS2009

Tele-Supervised Adaptive Ocean Sensor Fleet

The Tele-supervised Adaptive Ocean Sensor Fleet (TAOSF) is a multi-robot science exploration architecture and system that uses a group of robotic boats (the Ocean-Atmosphere Sensor Integration System, or OASIS) to enable in-situ study of ocean surface and subsurface characteristics and the dynamics of such ocean phenomena as coastal pollutants, oil spills, hurricanes, or harmful algal blooms (HABs). The OASIS boats are extended- deployment, autonomous ocean surface vehicles. The TAOSF architecture provides an integrated approach to multi-vehicle coordination and sliding human-vehicle autonomy. One feature of TAOSF is the adaptive re-planning of the activities of the OASIS vessels based on sensor input ( smart sensing) and sensorial coordination among multiple assets. The architecture also incorporates Web-based communications that permit control of the assets over long distances and the sharing of data with remote experts. Autonomous hazard and assistance detection allows the automatic identification of hazards that require human intervention to ensure the safety and integrity of the robotic vehicles, or of science data that require human interpretation and response. Also, the architecture is designed for science analysis of acquired data in order to perform an initial onboard assessment of the presence of specific science signatures of immediate interest. TAOSF integrates and extends five subsystems developed by the participating institutions: Emergent Space Tech - nol ogies, Wallops Flight Facility, NASA s Goddard Space Flight Center (GSFC), Carnegie Mellon University, and Jet Propulsion Laboratory (JPL). The OASIS Autonomous Surface Vehicle (ASV) system, which includes the vessels as well as the land-based control and communications infrastructure developed for them, controls the hardware of each platform (sensors, actuators, etc.), and also provides a low-level waypoint navigation capability. The Multi-Platform Simulation Environment from GSFC is a surrogate for the OASIS ASV system and allows for independent development and testing of higher-level software components. The Platform Communicator acts as a proxy for both actual and simulated platforms. It translates platform-independent messages from the higher control systems to the device-dependent communication protocols. This enables the higher-level control systems to interact identically with heterogeneous actual or simulated platforms.

Lefes, Alberto↗
DOE OSTI2023

Extrapair offspring of the blue-footed booby show no sign of higher fitness in the first 10 years of life

According to the good genes and genetic compatibility hypotheses, females of socially monogamous species obtain genetic benefits for their offspring by performing extrapair copulations with males of higher quality than their social mates or males with whom they are more genetically compatible. If extrapair offspring do receive genetic benefits in the form of advantageous alleles or more compatible allele combinations, they should outperform their within-pair half-siblings' survival and/or reproductive output. Here, in this study, we followed 52 extrapair and 737 within-pair blue-footed booby, Sula nebouxii, offspring during their first 10 years of life (excluding the embryonic period and the first 10 days after hatching) to assess whether they differed in fledging probability, fledgling body condition, recruitment probability, age at first reproduction, number of breeding events or accumulated breeding success. Extrapair and within-pair offspring did not differ in any of these proxies of fitness. Furthermore, we found that extrapair offspring were equally likely to occur in any hatching position. However, differences in fledgling production over the lifetime could not be ruled out, and because only within-pair production of eggs and fledglings was tallied, the possibility remains that extrapair offspring could produce more extrapair offspring later in life than do within-pair offspring. Furthermore, the possibility of context-dependent genetic benefits occurring only under stressful conditions cannot be discounted because our sample of offspring was obtained in a single exceptionally favourable reproductive season.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Early experiences evaluating the HPE/Cray ecosystem for AMD GPUs

Summary The Oak Ridge Leadership Computing Facility (OLCF) has a long history of supporting and promoting GPU‐accelerated computing starting with the deployment of the Titan supercomputer in 2021 and continuing with the Summit supercomputer which has a theoretical peak performance of approximately 200 petaflops. Because the majority of Summit's computational power comes from its 27,972 GPUs, users must port their applications to one of the supported programming models in order to make efficient use of the system. To prepare the transition to Frontier, the OLCF's exascale supercomputer, users will need to adapt to an entirely new ecosystem which will include new hardware and software technologies. First, users will need to familiarize themselves with the AMD Radeon GPU architecture. Furthermore, users who have been previously relying on CUDA will need to transition to the Heterogeneous‐Computing Interface for Portability (HIP) or one of the other supported programming models (e.g., OpenMP, OpenACC). In this work, we describe our initial experiences and lessons learned in porting three applications or proxy apps currently running on Summit to the HPE/Cray ecosystem to leverage the compute power from AMD GPUs: minisweep, GenASiS, and Sparkler. Each one is representative of current production workloads utilized at the OLCF, different programming languages, and different programming models.

Melesse Vergara, Verónica G.↗
NASA NTRS2010

Analysis of TRMM-LIS Lightning and Related Microphysics Using a Cell-Scale Database

Previous studies of tropical lightning activity using Tropical Rainfall Measurement Mission (TRMM) Lightning Imaging Sensor (LIS) data performed analyses of lightning behavior over mesoscale "feature" scales or over uniform grids. In order to study lightning and the governing ice microphysics intrinsic to thunderstorms at a more process-specific scale (i.e., the scale over which electrification processes and lightning occur in a "unit" thunderstorm), a new convective cell-scale database was developed by analyzing and refining the University of Utah's Precipitation Features database and retaining precipitation data parameters computed from the TRMM precipitation radar (PR), microwave imager (TMI) and LIS instruments. The resulting data base was to conduct a limited four-year study of tropical continental convection occurring over the Amazon Basin, Congo, Maritime Continent and the western Pacific Ocean. The analysis reveals expected strong correlations between lightning flash counts per cell and ice proxies, such as ice water path, minimum and average 85GHz brightness temperatures, and 18dBz echo top heights above the freezing level in all regimes, as well as regime-specific relationships between lighting flash counts and PR-derived surface rainfall rates. Additionally, radar CFADs were used to partition the 3D structure of cells in each regime at different flash counts. The resulting cell-scale analyses are compared to previous mesoscale feature and gridded studies wherever possible.

Leroy, Anita↗
DOE OSTI2022

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Infrared-safe energy weighting does not guarantee small nonperturbative effects

Infrared and collinear (IRC) safety has long been used a proxy for robustness when developing new jet substructure observables. This guiding philosophy has been carried into the deep learning era, where IRC-safe neural networks have been used for many jet studies. For graph-based neural networks, the most straightforward way to achieve IRC safety is to weight particle inputs by their energies. However, energy-weighting by itself does not guarantee that perturbative calculations of machine-learned observables will enjoy small nonperturbative corrections. Here, in this paper, we demonstrate the sensitivity of IRC-safe networks to nonperturbative effects, by training an energy flow network (EFN) to maximize its sensitivity to hadronization. We then show how to construct Lipschitz energy flow networks (L-EFNs), which are both IRC safe and relatively insensitive to nonperturbative corrections. We demonstrate the performance of L-EFNs on generated samples of quark and gluon jets, and showcase fascinating differences between the learned latent representations of EFNs and L-EFNs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

ASCR Cybersecurity for Scientific Computing Integrity - Research Pathways and Ideas Workshop

At the request of the U.S. Department of Energy's (DOE) Office of Science (SC) Advanced Scientific Computing Research (ASCR) program office, a workshop was held June 2-3, 2015, in Gaithersburg, MD, to identify potential long term (10 to +20 year) cybersecurity fundamental basic research and development challenges, strategies and roadmap facing future high performance computing (HPC), networks, data centers, and extreme-scale scientific user facilities. This workshop was a follow-on to the workshop held January 7-9, 2015, in Rockville, MD, that examined higher level ideas about scientific computing integrity specific to the mission of the DOE Office of Science. Issues included research computation and simulation that takes place on ASCR computing facilities and networks, as well as network-connected scientific instruments, such as those run by various DOE Office of Science programs. Workshop participants included researchers and operational staff from DOE national laboratories, as well as academic researchers and industry experts. Participants were selected based on the submission of abstracts relating to the topics discussed in the previous workshop report [1] and also from other ASCR reports, including "Abstract Machine Models and Proxy Architectures for Exascale Computing" [27], the DOE "Preliminary Conceptual Design for an Exascale Computing Initiative" [28], and the January 2015 machine learning workshop [29]. The workshop was also attended by several observers from DOE and other government agencies. The workshop was divided into three topic areas: (1) Trustworthy Supercomputing, (2) Extreme-Scale Data, Knowledge, and Analytics for Understanding and Improving Cybersecurity, and (3) Trust within High-end Networking and Data Centers. Participants were divided into three corresponding teams based on the category of their abstracts. The workshop began with a series of talks from the program manager and workshop chair, followed by the leaders for each of the three topics and a representative of each of the four major DOE Office of Science Advanced Scientific Computing Research Facilities: the Argonne Leadership Computing Facility (ALCF), the Energy Sciences Network (ESnet), the National Energy Research Scientific Computing Center (NERSC), and the Oak Ridge Leadership Computing Facility (OLCF). The rest of the workshop consisted of topical breakout discussions and focused writing periods that produced much of this report.

97 MATHEMATICS AND COMPUTING↗