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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Spaceborne Lidar Retrievals of PM2.5 for Air Quality Studies and Applications

Fine particulate matter (PM2.5) substantially contributes to air pollution and negatively affects human health. While many studies have investigated the use of passive column-integrated aerosol optical depth to infer surface PM2.5, the use of lidar observations for air quality characterization is not nearly as extensive. Lidar measurements are critical, however, due to the vertical aerosol information they provide, including near the surface. In this presentation, we first provide an overview of various lidar-based approaches for estimating PM2.5 concentrations and then discuss how lidar measurements can assist other air quality applications. For example, estimates of PM2.5 have been obtained in a physics-based approach through CALIOP near-surface aerosol extinction retrievals, assumptions on the mass extinction efficiency, and incorporating other parameters (an aerosol hygroscopic growth factor and PM2.5/PM10 ratio). Application of this algorithm over the contiguous United States (CONUS) from 2006 to 2018 yielded larger PM2.5 values over the eastern and western CONUS (~10-15 μg/m³) and lower PM2.5 levels in the central CONUS (~5 μg/m³). These spatial patterns were similar to those from gridded PM2.5 concentrations obtained through in situ measurements at ground stations operated by the US Environmental Protection Agency. In another approach, the Cloud Aerosol Transport System (CATS) lidar was used with the Goddard Earth Observing System (GEOS) model in a 1D ensemble-based variational technique to obtain PM2.5 over the US and Europe, and the spatial patterns of the CATS/GEOS based PM2.5 concentrations generally captured those from surface stations (with corresponding hourly EPA PM2.5 vs CATS PM2.5 statistics of R=0.4 and bias=1.5 μg/m³). In our recent work, as part of the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group, we have applied both the CALIOP and CATS/GEOS based approaches over the highly polluted country of India during the post-monsoon season (September-October 2016). We derived elevated levels of two-month mean PM2.5 (~100 μg/m³) in northern India, especially near New Delhi. These high PM2.5 concentrations in the Indo-Gangetic plain are driven in large part from the seasonal burning of crop residue and meteorological conditions typical at this time of the year, such as low wind speeds and a shallow boundary layer. While the satellite-derived PM2.5 moderately replicates (R = ~0.7-0.9) the spatial variability in the two-month mean of surface in situ PM2.5 from monitoring sites operated by the Central and State Pollution Control Boards, we show results from specific scenes for which there are large deviations between the satellite-derived PM2.5 and in situ measurements. Other current work on this topic focuses on developing PM2.5 estimates using airborne high spectral resolution lidar measurements through machine learning regression algorithms and involves several parameters (e.g., aerosol extinction, color ratio, lidar ratio). Application of this method over major metropolitan areas in the US and Asia have resulted in high correlations (R = 0.93) with surface measurements. This airborne lidar approach can be adapted to spaceborne lidar measurements, and all three of these approaches can be applied to ESA’s EarthCARE Atmospheric Lidar instrument, setting the stage for the future Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land Atmosphere System (CALIGOLA) mission. Ultimately, beyond estimates of PM2.5, the aerosol vertical distribution from lidars can benefit studies involving passive sensor approaches for PM2.5 proxies (including from geostationary satellites), wildfire smoke plume injection heights, volcanic emissions (e.g., ash height retrievals), and aerosol/air quality model assimilation, evaluation, and forecasts.

Travis D Toth↗
NASA NTRS1992

Methodologies for building robust schedules

COMPASS is the name of a Computer Aided Scheduling System designed and built for NASA. COMPASS can be used to develop schedule of activities based upon the temporal relationships of the activities and their resource requirements. COMPASS uses this information, and guided by the user, develops precise start and stop times for the activities. In actual practice however, it is impossible to know with complete certainty what the actual durations of the scheduled activities will really be. The best that one can hope for is knowledge of the probability distribution for the durations. This paper investigates methodologies for using a scheduling tool like COMPASS that is based upon definite values for the resource requirements, while building schedules that remain valid in the face of the schedule execution perturbations. Representations for the schedules developed by these methodologies are presented, along with a discussion of the algorithm that could be used by a computer onboard a spacecraft to efficiently monitor and execute these schedules.

Dean, John H.↗
DOE OSTI2025

Diagnostic Systems in the Muon $g-2$ experiment at Fermilab

The muon anomalous magnetic moment, $a_\mu=\frac{g-2}{2}$, is a low-energy observable which can be both measured and computed to high precision, making it a sensitive test of the Standard Model and a probe for new physics. This anomaly was measured with a precision of $0.20$~parts per million (ppm) by the Fermilab's Muon g-2 (E989) experiment. The final goal of the E989 experiment is to reach a precision of $0.14$~ppm. The experiment is based on the measurement of the muon spin anomalous precession frequency, $\omega_a$, based on the arrival time distribution of high-energy decay positrons observed by 24 electromagnetic calorimeters, placed around the inner circumference of a $14$~m diameter storage ring, and on the precise knowledge of the storage ring magnetic field and of the beam time and space distribution. Achieving this level of precision requires strict control over systematics, which is ensured through several diagnostic devices. At the accelerator level, these devices monitor the quality of the injected beam (e.g., verifying that it has the correct momentum), while at the detector level, they track both the magnetic field and the gain of the calorimeters. In this work the devices and techniques used by the E989 experiment will be presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Guidance for Integrating Energy Justice and Equity in Building Technology Deployment Programs: Tracking, Reporting, and Maximizing the Flow of Benefits from Building System Technology Deployment Activities to Disadvantaged Communities and Target Sectors

The Federal Justice40 Initiative directs at least 40% of the overall benefits of certain clean energy investments to flow to disadvantaged communities and requires that all federal programs covered by Justice40 consult stakeholders to determine the program benefits, and that the flow of benefits to disadvantaged communities is tracked and reported. Unequal distribution of benefits, in terms of access to clean energy research, design, development, and deployment, can disproportionately benefit or burden certain communities. This can result in higher rates of pollution, negative health effects, and increased energy burdens and insecurities in disadvantaged communities. Programs focused on decarbonizing the built environment can enhance health, quality of life, and economic opportunities for impacted communities. This guidance document, developed by Pacific Northwest National Laboratory and funded by the U.S. Department of Energy’s Building Technologies Office, provides best practices and approaches for incorporating energy justice and equity principles into building technology deployment activities. It provides best practices and recommendations for communicating with and involving disadvantaged communities and target building sectors in program activities, along with methods to monitor and report the distribution of benefits to these sectors. This document lays out a set of strategies, metrics, and best practices that can be implemented over time to apply energy justice and equity approaches, whether the program is just starting out or ongoing. Although this guidance was designed for Building Technologies Office technology deployment programs, the best practices, recommendations, and methods can be valuable to any program concerned with the equitable deployment of clean energy technologies. The goal of this project is to enable the equitable development, deployment, and adoption of clean energy technologies and practices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Bayesian High-Rank Hankel Matrix Completion for Nonlinear Synchrophasor Data Recovery

Phasor measurement units (PMUs) provide high temporal-resolution synchrophasor measurements for power system monitoring and control. The frequent data quality issues, such as missing and bad data, prevent the incorporation of synchrophasor data in real-time operations. Most existing data-driven data recovery methods assume the power system dynamics can be approximated by a linear dynamical system, and the recovery performance degrades significantly when the power system is experiencing nonlinear dynamics during significant events. Here, this paper proposes a data-driven Bayesian nonlinear synchrophasor data recovery method (Ba-NSDR) that can recover a consecutive time period of simultaneous data losses or errors across all channels, even when the underlying system is highly nonlinear. The idea is to lift the Hankel matrix of the spatial-temporal synchrophasor data to a higher dimension such that the lifted Hankel matrix is low-rank in that space and can be processed with the kernel trick. Our proposed Bayesian method then infers the probabilistic distributions of synchrophasor from the partial observations. Some distinctive features of Ba-NSDR include an uncertainty index to measure the accuracy of the recovery result and the robustness to parameter selections. Our method is verified on both synthetic and recorded event datasets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Distributed Coaxial Cable Sensors for In-Situ Condition Based Monitoring of Coal-Fired Boiler Tubes

The increasing contributions of renewable energy sources present new challenges to the operation and maintenance of the existing coal-fired power plants. One of the major operational risks is the unexpected failure of superheater boiler tubes, leading to the most unplanned power plant outrages. The boiler tube failure is difficult to predict due to the harsh operating environments. Therefore, condition-based monitoring (CBM) with a reliable high temperature sensor becomes necessary to produce a meaningful assessment of the health condition of boiler tubes and their remaining lifetime. In this work, the stainless-steel and quartz coaxial cable sensor (SSQ-CCS) is proposed for in-situ distributed monitoring of the boiler tube temperatures in existing coal-fired power plants. Comprehensive tests have been conducted with an in-house testing facility at Clemson University to study and evaluate the sensors’ performance in the temperature range of 100℃ to 600℃. The results indicated that the measurement resolution of the SSQ-CCS sensor is better than 1℃, and the drift is less than 2% over long-period testing. Meanwhile, multi-physics finite element analysis has been conducted to optimize the design and evaluate the safety of the SSQ-CCS temperature sensor under various operational conditions. Based on the performance obtained in the laboratory-scale testing, a field test has been implemented at a power plant. Four SSQ-CCS temperature sensors were installed for in-situ monitoring of the temperatures of a power plant’s superheat tube assembles. The data acquisition system has been successfully set up and collected sensing signals for more than three months. The sensing signals have been post-processed, and the monitored temperature history through the SSQ-CCS temperature sensor has been validated and compared with the conventional high temperature thermal couple data.

Jiao, Xinyu↗
DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Portable chemical detection platform for on-site monitoring of odorant levels in natural gas

The adequate odorization of natural gas is critical to identify gas leaks and to reduce accidents. To ensure odorization, natural gas utility companies collect samples to be processed at core facilities or a trained human technician smells a diluted natural gas sample. In this work, we report a detection platform that addresses the lack of mobile solutions capable of providing quantitative analysis of mercaptans, a class of compounds used to odorize natural gas. Detailed description of the platform hardware and software components is provided. Designed to be portable, the platform hardware facilitates extraction of mercaptans from natural gas, separation of individual mercaptan species, and quantification of odorant concentration, with results reported at point-of-sampling. The software was developed to accommodate skilled users as well as minimally trained operators. Detection and quantification of six commonly used mercaptan compounds (ethyl mercaptan, dimethyl sulfide, n-propylmercaptan, isopropyl mercaptan, tert–butyl mercaptan, and tetrahydrothiophene) at typical odorizing concentrations of 0.1–5 ppm was performed using the device. We demonstrate the potential of this technology to ensure natural gas odorizing concentrations throughout distribution systems.

03 NATURAL GAS↗
DOE OSTI2023

Production and testing of the powerboard for ATLAS ITk Strip barrel modules

The upgrade of the ATLAS ITk strips detector for HL-LHC will employ a custom PCB (powerboard) for on-module DC-DC conversion, HV switching, and monitoring. Production of about 14100 of such PCBs with high reliability is a big challenge. In this paper we will present the production procedure and quality control (QC) testing system for the powerboards to be installed on ITk Strip barrel modules. During production, about 150 powerboards will be produced every week. Each powerboard will need to pass QC tests before they are assembled to module. The QC tests include thermal cycling between -35 °C and 40 °C, soak test (continuous running of DC-DC converter at high load at 20 °C), and basic functionality and characterization electrical tests of the low voltage (LV), high voltage (HV), and monitoring functions of the powerboard. A custom QC test system is described, which is based on a reusable PCB (active board) with all testing circuits, a one-time powerboard carrier card, and a Z-turn SoC board which hosts and runs the testing program. The production procedure and QC test system has been tested with 400 powerboards during pre-production, and the system has been proven ready for production with the desired testing program, speed, safety, and cost. Performance and typical failures of powerboards observed during the QC test of pre-production powerboards is also presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Lawrence Livermore National Laboratory Environmental Report 2021

The purposes of the Lawrence Livermore National Laboratory Environmental Report 2021 are to record Lawrence Livermore National Laboratory’s (LLNL’s) compliance with environmental standards and requirements, describe LLNL’s environmental protection and remediation programs, and present the results of environmental monitoring at the two LLNL sites—the Livermore Site and Site 300. The report is prepared for the U.S. Department of Energy (DOE) by LLNL’s Environmental Functional Area. Submittal of the report satisfies requirements under DOE Order 231.1B, “Environment, Safety and Health Reporting,” and DOE Order 458.1, “Radiation Protection of the Public and Environment.” The report is distributed electronically and is available at https://saer.llnl.gov/, the website for the LLNL annual environmental report. Previous LLNL annual environmental reports beginning with 1994 are also on the website. Some references in the electronic report text are underlined, which indicates that they are clickable links. Clicking on one of these links will open the related document, data workbook, or website. Sampling location maps throughout this report were created using ArcGIS® software by Esri. The report begins with an executive summary, which provides the purpose of the report and an overview of LLNL’s compliance and monitoring results. The first three chapters provide background information: Chapter 1 is an overview of the location, meteorology, and hydrogeology of the two LLNL sites; Chapter 2 is a summary of LLNL’s compliance with environmental regulations; and Chapter 3 is a description of LLNL’s environmental programs with an emphasis on the Environmental Management System including pollution prevention. The majority of the report covers LLNL’s environmental monitoring programs and monitoring data for 2021: effluent and ambient air monitoring and dose assessment (Chapter 4); waters, including wastewater, storm water runoff, surface water, rain, and groundwater (Chapter 5); and terrestrial, including soil, sediment, vegetation, foodstuff, ambient radiation, and special status wildlife and plants (Chapter 6). The remaining two chapters discuss LLNL’s groundwater remediation program (Chapter 7), and quality assurance for the environmental monitoring programs (Chapter 8). Complete monitoring data, which are summarized in the body of the report, are provided in Appendix A. The report uses Système International units, consistent with the federal Metric Conversion Act of 1975 and Executive Order 12770, “Metric Usage in Federal Government Programs” (1991). For ease of comparison to environmental reports issued prior to 1991, dose values and many radiological measurements are given in both metric and U.S. customary units. A conversion table is provided in the glossary. The report is the responsibility of LLNL’s Environmental Functional Area. Monitoring data were obtained through the combined efforts of the Environmental Functional Area; Environmental Restoration Department; Physical and Life Sciences Environmental Monitoring Radiological Laboratory; and the Radiation Protection Functional Area.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Evolution of the JPSS Ground Project Calibration and Validation System

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administrations (NOAA) next-generation operational Earth observation Program that acquires and distributes global environmental data from multiple polar-orbiting satellites. The JPSS Program plays a critical role to NOAAs mission to understand and predict changes in weather, climate, oceans, coasts, and space environments, which supports the Nation’s economy and protection of lives and property. The National Aerospace and Atmospheric Administration (NASA) is acquiring and implementing the JPSS, comprised of flight and ground systems on behalf of NOAA. The JPSS satellites are planned to fly in the afternoon orbit and will provide operational continuity of satellite-based observations and products for NOAA Polar-orbiting Operational Environmental Satellites (POES) and the Suomi National Polar-orbiting Partnership (SNPP) satellite. To support the JPSS Calibration and Validation (CalVal) node Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) services facilitate: Algorithm Integration and Checkout, Algorithm and Product Operational Tuning, Instrument Calibration, Product Validation, Algorithm Investigation, and Data Quality Support and Monitoring. GRAVITE is a mature, deployed system that currently supports the SNPP Mission and has been in operations since SNPP launch. This paper discusses the major re-architecture for Block 2.0 that incorporates SNPP lessons learned, architecture of the system, and demonstrates how GRAVITE has evolved as a system with increased performance. It is now a robust, stable, reliable, maintainable, scalable, and secure system that supports development, test, and production strings, replaces proprietary and custom software, uses open source software, and is compliant with NASA and NOAA standards.

Data Processing↗
NASA NTRSDate not supplied

Vapor Growth of ZnSe-based Compound Semiconductors in Low Gravity environment on International Space Station

Six low-gravity experiments of crystal growth of ZnSe-based compound semiconductors by physical vapor transport (PVT) are scheduled to be processed inside Low Gradient Furnace (LGF) on Materials Science Research Rack (MSRR) in Material Science Laboratory (MSL) on International Space Station (ISS) starting from February 27th, 2023. The flight samples consist of three unseeded growths of ZnSe, Cr-doped ZnSe and ZnSeTe as well as growth of ZnSe on top of three single crystal ZnSe seeds with orientation of (100), (110) and (111). The main scientific objective of the flight experiments is to establish the effects of gravity-driven fluid flows on Earth to (i) the non-uniform incorporation of impurities and defects and (ii) the deviation from stoichiometry observed in the grown crystals caused by growth interface fluctuations and evolution as the results of buoyancy-driven convection and irregular fluid-flows. The investigation will also evaluate the effects of gravity on the PVT process by examining (i) the growth kinetics on various seed orientations, (ii) the dopant segregation and distribution in the Cr doped ZnSe, and (iii) the compositional segregation and distribution in the ternary ZnSeTe crystal grown by PVT. Additionally, from X-ray diffraction/topography and by measuring the density and distribution of various crystalline defects it will assess the self-induced strain effects developed during processing at elevated temperatures caused by the weight of the crystals. During the ground-based preparations, the following tasks have been accomplished: • Establish the thermodynamic properties of the ZnSe binary and related ternary systems by measuring the partial pressures of the vapor phase coexisting with the condensed phases and perform phase diagram calculations for comparison. • Evaluate the effects of gravity-driven convection in the growth process by performing experiments under various vapor transport orientations relative to gravity vector, i.e., horizontal, vertically stabilized and destabilized configurations. • Establish a quantitative correlation between growth parameters and the characteristics and properties of the grown crystals by characterizing the crystals using a variety of techniques. • Evaluate the fundamentals of the current theories on vapor transport and crystal growth kinetics by performing in-situ and real-time monitoring techniques during growth. • Develop a one-dimensional diffusion limited theory of mass transport and two- and three-dimensional numerical simulations of both mass transport and heat transfer and thus establish the microgravity requirements for the flight experiments and to predict the characteristics of the grown crystals such as the solid-vapor interface shapes… etc. and establish a fundamental understanding of the crystal growth process from the comparison with experimental results.

ZnSe↗
NASA NTRS1998

Monitoring Direct Effects of Delta, Atlas, and Titan Launches from Cape Canaveral Air Station

Launches of Delta, Atlas, and Titan rockets from Cape Canaveral Air Station (CCAS) have potential environmental effects that could arise from direct impacts of the launch exhaust (e.g., blast, heat), deposition of exhaust products of the solid rocket motors (hydrogen chloride, aluminum oxide), or other effects such as noise. Here we: 1) review previous reports, environmental assessments, and environmental impact statements for Delta, Atlas, and Titan vehicles and pad areas to clarity the magnitude of potential impacts; 2) summarize observed effects of 15 Delta, 22 Atlas, and 8 Titan launches; and 3) develop a spatial database of the distribution of effects from individual launches and cumulative effects of launches. The review of previous studies indicated that impacts from these launches can occur from the launch exhaust heat, deposition of exhaust products from the solid rocket motors, and noise. The principal effluents from solid rocket motors are hydrogen chloride (HCl), aluminum oxide (Al2O3), water (H2O), hydrogen (H2), carbon monoxide (CO), and carbon dioxide (CO2). The exhaust plume interacts with the launch complex structure and water deluge system to generate a launch cloud. Fall out or rain out of material from this cloud can produce localized effects from acid or particulate deposition. Delta, Atlas, and Titan launch vehicles differ in the number and size of solid rocket boosters and in the amount of deluge water used. All are smaller and use less water than the Space Shuttle. Acid deposition can cause damage to plants and animals exposed to it, acidify surface water and soil, and cause long-term changes to community composition and structure from repeated exposure. The magnitude of these effects depends on the intensity and frequency of acid deposition.

Schmalzer, Paul A.↗
NASA NTRS1999

"Novel Techniques in Non-Stationary Analysis of Rotorcraft Vibration Signitures"

This research effort produced new methods to analyze the performance of linear predictors that track non-stationary processes. Specifically, prediction methods have been applied to the vibration pattern of rotorcraft drivetrains. This analysis is part or a larger rotorcraft Health and Usage Monitoring System (HUMS) that can diagnose immediate failures of the subsystems, as indicated by abrupt change in the vibration signature, and prognosticate future health, by examining the vibration patterns against long-term trends. This problem is described by a earlier joint paper co-authored by members of the funding agency and the recipient institutions prior to this grant effort. Specific accomplishments under this grant include the following: (1) Definition of a framework for analysis of non-stationary time-series estimation using the coefficients of an adaptive filter. (2) Description of a novel method of combining short-term predictor error and long-term regression error to analyze the performance of a non-stationary predictor. (3) Formulation of a multi-variate probability density function that quantifies the performance of a adaptive predictor by using the short- and long-term error variables in a Gamma function distribution. and (4) Validation of the mathematical formulations with empirical data from NASA flight tests and simulated data to illustrate the utility beyond the domain of vibrating machinery.

Meng, Teresa↗
NASA NTRS2016

Evolution of the JPSS Ground Project Calibration and Validation System

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administration's (NOAA) next-generation operational Earth observation Program that acquires and distributes global environmental data from multiple polar-orbiting satellites. The JPSS Program plays a critical role to NOAA's mission to understand and predict changes in weather, climate, oceans, coasts, and space environments, which supports the Nation's economy and protection of lives and property. The National Aeronautics and Space Administration (NASA) is acquiring and implementing the JPSS, comprised of flight and ground systems, on behalf of NOAA. The JPSS satellites are planned to fly in the afternoon orbit and will provide operational continuity of satellite-based observations and products for NOAA Polar-orbiting Operational Environmental Satellites (POES) and the Suomi National Polar-orbiting Partnership (SNPP) satellite. To support the JPSS Calibration and Validation (CalVal) node Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) services facilitate: Algorithm Integration and Checkout, Algorithm and Product Operational Tuning, Instrument Calibration, Product Validation, Algorithm Investigation, and Data Quality Support and Monitoring. GRAVITE is a mature, deployed system that currently supports the SNPP Mission and has been in operations since SNPP launch. This paper discusses the major re-architecture for Block 2.0 that incorporates SNPP lessons learned, architecture of the system, and demonstrates how GRAVITE has evolved as a system with increased performance. It is now a robust, stable, reliable, maintainable, scalable, and secure system that supports development, test, and production strings, replaces proprietary and custom software, uses open source software, and is compliant with NASA and NOAA standards.

Next-Generation↗
DOE OSTI2020

Probabilistic Look-ahead Contingency Analysis Integration with Commercial Tool and Practical Data

This paper presents an initial effort of integrating a smart sampling-based probabilistic look-ahead contingency analysis algorithm with General Electric (GE) Grid Solutions’ commercial energy management system (EMS) tool as a proof-of-concept for a seamless research tool integration using real world large-scale grid data. With the increasing impact of random forces such as variable generation and load, their stochastic behaviors cannot be ignored. However, the current practices are still dominated by deterministic tools. They are becoming increasingly inadequate for the future grid. The developed look-ahead contingency analysis algorithm incorporates forecast errors of variable energy and load to address the challenges brought by the increasing uncertainty of power system. The algorithm can reveal the potential violations caused by the variance of variable energy and load that are not normally detected by traditional deterministic approaches. To test its performance under practical environments ( real data with real commercial tool), significant efforts have been made to prepare test cases, modify GE EMS tool, and adapt an extreme value distribution algorithm to analyze the GE EMS’s violation-only outputs. The test results clearly demonstrate the effectiveness of the developed algorithm as new transformer violations that were not previously detected have been identified. This performance provides better situational awareness to engineers for their decision-making process under uncertainty. Moreover, with the discussion of computational performance and future work, this paper has shown a clear path for integrating the probabilistic algorithm with commercial tools to make us better equipped for the changing power system.

Modeling and simulation of power systems, constrai↗
DOE OSTI2022

TRACER-CAT-LANL Aerosol Optics and Chemical Speciation - Tracegases

Aerosol size distribution, optical properties, and speciation data collected in La Port TX, during TRACER-CAT-LANL, July 2022, with basic trace gas measurements. All sampling was conducted with an identical aerosol inlet as the standard ARM-AOS systems. The TRacking Aerosol Convection interactions ExpeRiment Carbonaceous Aerosols Thrust by Los Alamos National Laboratory (TRACER-CAT-LANL, July 2022) was designed to complement the larger ARM TRACER science goals to understand convective cloud lifecycles and aerosol-convection interactions. TRACER-CAT-LANL is focused on understanding the relationship between particle composition and light absorption and the influence of water uptake on this relationship. This aerosol and trace gas data can be used to understand the relationship between particle composition and light absorption and the influence of water uptake on this relationship. Instruments Include: Picarro GHG Photoacoustic Soot Spectrometer (PASS-3) Humidified-cavity attenuated phase shift-single scattering albedo particulate matter monitor (H-CAPS-PMSSA) Soot Particle Aerosol Mass Spectrometer (SPAMS) Single-Particle Soot Photometer (SP2) Cloud Condensation Nuclei Counter (CCNc) Aerodynamic Particle Sizer (APS) Scanning Mobility Particle Sizer (SMPS)

54 ENVIRONMENTAL SCIENCES↗