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DOE OSTI2022

Resilient Operating Constraints for Power Distribution Systems under Setpoint Attacks

Integration and operation of distributed generation (DG) and energy storage (ES) in power distribution systems are enabled by communication networks and embedded sensor and control devices that increase the vulnerability of the systems to cyber-threats, broadening the attack surface and making adversary actions more unpredictable. This paper proposes a methodology that uses ellipsoidal approximations to quantify the potential damage caused by successful attacks that affect, directly or indirectly, the desired operation setpoints and may drive the power distribution operation to unsafe states by violating the limits of voltage or line flows. More specifically, a new methodology is introduced to find the optimal non-symmetric operating constraints that can be imposed to each DG and ES in order to guarantee that the power distribution system is resilient to any malicious setpoints. The proposed method takes as inputs the system topology, DG and ES capabilities, and load limits to solve a convex optimization problem formulated using linear matrix inequalities (LMIs) and the power flow equations. The proposed solution is agnostic to the attacker's action or load profile and it does not require any assumption about the location or means of the attack. The numerical results on a test distribution feeder with several DG and ES illustrate how the proposed resilient operating constraints guarantee the security of the power distribution system under setpoint attacks.

Giraldo, Jairo↗

DOE OSTI2025

Lectures on statistical mechanics

Presented here is a transcription of the lecture notes from Professor Allan N. Kaufman’s graduate statistical mechanics course Physics 212A and 212B at the University of California Berkeley from the 1972–1973 academic year. 212A addressed equilibrium statistical mechanics with topics: fundamentals (micro-canonical and sub-canonical ensembles, adiabatic law and action conservation, fluctuations, pressure, and virial theorem), classical fluids and other systems (equation of state, deviations from ideality, virial coefficients and van der Waals potential, canonical ensemble and partition function, quasistatic evolution, grand-canonical ensemble and partition function, chemical potential, simple model of a phase transition, quantum virial expansion, numerical simulation of equations of state, and phase transition), chemical equilibrium (systems with multiple species and chemical reactions, law of mass action, Saha equation, chemical equilibrium including ionization and excited states), and long-range interactions (including Coulomb, dipole, and gravitational interactions, Debye–Hückel theory, and shielding). 212B addressed nonequilibrium statistical mechanics with topics: fundamentals (definitions: realizations, moments, characteristic function, and discrete variables), Brownian motion (Langevin equation, fluctuation–dissipation theorem, spatial diffusion, Boltzmann’s H-theorem), Liouville and Klimontovich equations, Landau equation (derivation, elaboration, and H-theorem, and irreversibility), Markov processes and Fokker–Planck equation (derivations of the Fokker–Planck equation and a master equation), linear response and transport theory (linear Boltzmann equation, linear response theory of Kubo and Mori, relation of entropy production to electrical conductivity, transport relations and coefficients, normal mode solutions of the transport equations, sketch of a generalized Langevin equation method for transport theory), and an introduction to nonequilibrium quantum statistical mechanics.

plasma dynamics↗

DOE OSTI2022

Thermal Hydroquinone Oxidation on Co/N-doped Carbon Proceeds by a Band-Mediated Electrochemical Mechanism

Molecules catalyze aerobic oxidation reactions via redox cycling at the metal center to effect sequential activation of O 2 and the substrate. Metal surfaces can catalyze the same transformations by coupling independent half-reactions for oxygen reduction and substrate oxidation mediated via the exchange of band-electrons. Metal/nitrogen-doped carbons (MNCs) are promising catalysts for aerobic oxidation that consist of molecule-like active sites embedded in a conductive carbon host. Owing to their combining molecular and metallic features, it remains unclear whether they proceed via the sequential redox cycling pathways of molecules or the band-mediated pathways of metals. Herein, we simultaneously track the potential of the catalyst and the rate of the turnover of aerobic hydroquinone oxidation on a cobalt-based MNC catalyst contacted to a catalytically inactive carbon electrode. By comparing operando measurements of rate and potential with the current-voltage behavior of each constituent half-reaction under identical conditions, we show that these molecular materials can display the band-mediated reaction mechanisms of extended metallic solids. Further, we show that the action of these band-mediated mechanisms explains fractional reaction orders in both oxygen and hydroquinone, the time evolution of catalyst potential and rate, and the dependence of rate on overall reaction free energy. Selective poisoning experiments suggest that oxygen reduction proceeds at cobalt sites, whereas quinone oxidation proceeds at native oxidic defects on the carbon. These findings highlight that molecule-like active sites can take advantage of band-mediated mechanisms when coupled to conductive hosts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Heterotic backgrounds via generalised geometry: moment maps and moduli

We describe the geometry of generic heterotic backgrounds preserving minimal supersymmetry in four dimensions using the language of generalised geometry. They are characterised by an SU(3) × Spin(6 + n) structure within O(6, 6 + n) x $\mathbb{R}$ + generalised geometry. Supersymmetry of the background is encoded in the existence of an involutive subbundle of the generalised tangent bundle and the vanishing of a moment map for the action of diffeomorphisms and gauge symmetries. We give both the superpotential and the Kähler potential for a generic background, showing that the latter defines a natural Hitchin functional for heterotic geometries. Intriguingly, this formulation suggests new connections to geometric invariant theory and an extended notion of stability. Finally we show that the analysis of infinitesimal deformations of these geometric structures naturally reproduces the known cohomologies that count the massless moduli of supersymmetric heterotic backgrounds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Development of a novel minigenome and recombinant VSV expressing Seoul hantavirus glycoprotein-based assays to identify anti-hantavirus therapeutics

Seoul virus (SEOV) is an emerging global health threat that can cause hemorrhagic fever with renal syndrome (HFRS), which results in case fatality rates of ~2%. There are no approved treatments for SEOV infections. We developed a cell-based assay system to identify potential antiviral compounds for SEOV and generated additional assays to characterize the mode of action of any promising antivirals. Here, to test if candidate antivirals targeted SEOV glycoprotein-mediated entry, we developed a recombinant reporter vesicular stomatitis virus expressing SEOV glycoproteins. To facilitate the identification of candidate antiviral compounds targeting viral transcription/replication, we successfully generated the first reported minigenome system for SEOV. This SEOV minigenome (SEOV-MG) screening assay will also serve as a prototype assay for discovery of small molecules inhibiting replication of other hantaviruses, including Andes and Sin Nombre viruses. Ours is a proof-of-concept study in which we tested several compounds previously reported to have activity against other negative-strand RNA viruses using our newly developed hantavirus antiviral screening systems. These systems can be used under lower biocontainment conditions than those needed for infectious viruses, and identified several compounds with robust anti-SEOV activity. Our findings have important implications for the development of anti-hantavirus therapeutics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Risk to ecological resources following remediation can be due mainly to increased resource value of successful restoration: A case study from the Department of Energy's Hanford Site

Several nations are faced with the need to remediate large contaminated sites following World War II, the Cold War, and abandoned industrial sites, and to return them to productive land uses. In the United States, the Department of Energy (DOE) has the largest cleanup challenge, and its Hanford Site in the state of Washington has the most extensive and most expensive cleanup task. Ideally, the risk to ecological resources on remediation sites is evaluated before, during, and after remediation, and the risk from, or damage to, ecological resources from contaminants should be lower following remediation. In this paper, we report the risk to ecological resources before, during, and as a consequence of remediation on contaminated units requiring cleanup, and then examine the causes for changes in risk by evaluating 56 cleanup evaluation units (EUs) at the Hanford Site. In this case, remediation includes a restoration phase. In general, the risk to ecological and eco-cultural resources is currently not discernible or low at most contaminated units, increases during remediation, and decreases thereafter. Remediation often causes physical disruption to ecosystems as it reduces the risk from exposure to contaminants. Most new remediation projects at the Hanford Site include ecological restoration. Ecological restoration results in the potential for the presence of higher quality resources after remediation than currently exists on these contaminated lands and facilities. Although counter-intuitive, our evaluation of the risk to ecological resources following remediation indicated that a significant percentage of units (61%) will be at increased risk in the post-remediation period. This increased risk is due to DOE's successful remediation and restoration that results in a higher percent of native vegetation and higher ecological value on the sites in the post-remediation period than before. These newly-created resources can then be at risk from post-remediation activities. Risks to these new higher quality resources include the potential for spread of invasive species and of noxious grasses used in previous cleanup actions, disruption of ecosystems (including those with state or federally listed species and unique ecosystems), compaction of soil, use of pesticides to control invasive species, and the eventual need for continued monitoring activities. Thus, by greatly improving the existing habitat and health of eco-receptors, and maintaining habitat corridors between high quality habitats, the ecological resources in the post-remediated units are at risk unless care is taken to protect them. Many of the negative effects of both remediation and future monitoring (or other future land uses) can be avoided by planning and management early in the remediation process. We suggest DOE and other agencies convene a panel of managers, remediation scientists, regulators, environmental and ecological scientists, Native Americans, economists, and the public to develop a generic list of performance metrics for the restoration phase of remediation, including evaluation of success, which could be applied across the DOE complex.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Integrating multi-modal remote sensing, deep learning, and attention mechanisms for yield prediction in plant breeding experiments

In both plant breeding and crop management, interpretability plays a crucial role in instilling trust in AI-driven approaches and enabling the provision of actionable insights. The primary objective of this research is to explore and evaluate the potential contributions of deep learning network architectures that employ stacked LSTM for end-of-season maize grain yield prediction. A secondary aim is to expand the capabilities of these networks by adapting them to better accommodate and leverage the multi-modality properties of remote sensing data. In this study, a multi-modal deep learning architecture that assimilates inputs from heterogeneous data streams, including high-resolution hyperspectral imagery, LiDAR point clouds, and environmental data, is proposed to forecast maize crop yields. The architecture includes attention mechanisms that assign varying levels of importance to different modalities and temporal features that, reflect the dynamics of plant growth and environmental interactions. The interpretability of the attention weights is investigated in multi-modal networks that seek to both improve predictions and attribute crop yield outcomes to genetic and environmental variables. This approach also contributes to increased interpretability of the model's predictions. The temporal attention weight distributions highlighted relevant factors and critical growth stages that contribute to the predictions. The results of this study affirm that the attention weights are consistent with recognized biological growth stages, thereby substantiating the network's capability to learn biologically interpretable features. Accuracies of the model's predictions of yield ranged from 0.82-0.93 R 2 ref in this genetics-focused study, further highlighting the potential of attention-based models. Further, this research facilitates understanding of how multi-modality remote sensing aligns with the physiological stages of maize. The proposed architecture shows promise in improving predictions and offering interpretable insights into the factors affecting maize crop yields, while demonstrating the impact of data collection by different modalities through the growing season. By identifying relevant factors and critical growth stages, the model's attention weights provide valuable information that can be used in both plant breeding and crop management. The consistency of attention weights with biological growth stages reinforces the potential of deep learning networks in agricultural applications, particularly in leveraging remote sensing data for yield prediction. To the best of our knowledge, this is the first study that investigates the use of hyperspectral and LiDAR UAV time series data for explaining/interpreting plant growth stages within deep learning networks and forecasting plot-level maize grain yield using late fusion modalities with attention mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1974

Lessons learned on the Skylab program

Lessons learned in the Skylab program and their application and adaptation to other space programs are summarized. Recommendations and action taken on particular problems are described. The use of Skylab recommendations to identify potential problems of future space programs is discussed.

Source record↗

NASA NTRS2002

Prospects for Improved Forecasts of Weather and Short-Term Climate Variability on Subseasonal (2-Week to 2-Month) Times Scales

This workshop, held in April 2002, brought together various Earth Sciences experts to focus on the subseasonal prediction problem. While substantial advances have occurred over the last few decades in both weather and seasonal prediction, progress in improving predictions on these intermediate time scales (time scales ranging from about two weeks to two months) has been slow. The goals of the workshop were to get an assessment of the "state of the art" in predictive skill on these time scales, to determine the potential sources of "untapped" predictive skill, and to make recommendations for a course of action that will accelerate progress in this area. One of the key conclusions of the workshop was that there is compelling evidence for predictability at forecast lead times substantially longer than two weeks. Tropical diabatic heating and soil wetness were singled out as particularly important processes affecting predictability on these time scales. Predictability was also linked to various low-frequency atmospheric "phenomena" such as the annular modes in high latitudes (including their connections to the stratosphere), the Pacific/North American (PNA) pattern, and the Madden Julian Oscillation (MJO). The latter, in particular, was highlighted as a key source of untapped predictability in the tropics and subtropics, including the Asian and Australian monsoon regions.

Schubert, Siegfried↗

NASA NTRS2012

SOFIA: Flying the Telescope

The Stratospheric Observatory For Infrared Astronomy (SOFIA) is an international cooperative development and operations program between the United States National Aeronautics and Space Administration (NASA) and the German Space Agency, DLR (Deutsches Zentrum fuer Luft-und Raumfahrt). SOFIA is a 2.5 meter, optical/infrared/sub-millimeter telescope mounted in a Boeing model 747SP-21 aircraft and will be used for many basic astronomical observations performed at stratospheric altitudes. It will accommodate installation of different focal plane instruments with in-flight accessibility provided by investigators selected from the international science community. The Facility operational lifetime is planned to be greater than 20 years. This presentation will present the results of developmental testing of SOFIA, including analysis, envelope expansion and the first operational mission. It will describe a brief history of open cavities in flight, how NASA designed and tested SOFIAs cavity, as well as flight test results. It will focus on how the test team achieved key milestones by systematically and efficiently reducing the number of test points to only those absolutely necessary to achieve mission requirements, thereby meeting all requirements and saving the potential loss of program funding. Finally, it will showcase examples of the observatory in action and the first operational mission of the observatory, illustrating the usefulness of the system to the international scientific community. Lessons learned on how to whittle a mountain of test points into a manageable sum will be presented at the conclusion.

Asher, Troy↗

NASA NTRS2021

Extreme Ozone Loss Following Nuclear War Results in Enhanced Surface Ultraviolet Radiation

For the first time, we use a modern climate model with interactive chemistry including the effects of aerosols on photolysis rates to simulate the consequences of regional and global scale nuclear wars (injecting 5 and 150 Tg of soot respectively) for the ozone layer and surface ultraviolet (UV) light. For a global nuclear war, heating in the stratosphere, reduced photolysis, and an increase in catalytic loss from the Hox cycle cause a 15 year-long reduction in the ozone column, with a peak loss of 75% globally and 65% in the tropics. This is larger than predictions from the 1980s, which assumed large injections of nitrogen oxides (NOx),but did not include the effects of smoke. NOx from the fireball and the fires provide a small (5%) Increase to the global average ozone loss for the first few years. Initially, soot would shield the surface from UV-B, but UV Index values would become extreme: greater than 35in the tropics for 4years, and greater than 45during the summer in the southern polar regions for 3 years. For a regional war, global column ozone would be reduced by 25% with recovery taking 12 years. This is similar to previous simulations, but with a faster recovery time due to a shorter lifetime for soot in our simulations. In-line photolysis provides process specific action spectra enabling future integration with biogeochemistry models and allows output that quantifies the potential health impacts from changes in surface UV for this and other larger aerosol injections.

nuclear war↗

NASA NTRSDate not supplied

Future Pathways for Arctic Forest Fires

Wildfires are expected to become more common and more severe in the Arctic states due to climate change. Main cause for the fires is human activity, even in the boreal and Arctic forests. Therefore, activities such forest management and tourism, together with firefighting capacity and readiness, can have a significant impact on future wildfire risks and impacts. To assess the impacts of these factors we have created pathways for future wildfires up to 2050 for the Arctic states. We explore high and low fire activity and risk pathways for all the Arctic states and suggest most our best guess pathways for each state separately. The low activity and fire risk pathway assumes active fire suppression via population participation and official land management, efficient fuel treatments to reduce fire risk, and active firefighting. The high activity and fire risk pathway assumes the opposite due to lack of government and community response, with addition of lacking response to climate-driven changes to wildfire risks. In the Nordic countries, human ignition sources, such as timber extraction, tourism, summer cottages, and expanding wildland-urban intermix due to exurban growth may increase. In addition to these in Canada and Alaska, expansion of agriculture increases the likelihood of open burning of agricultural waste, increasing risk of the fire spreading to wildlands. Drier fuels due to climate change increase the risk of fires, and there is a growing risk of extreme heat conditions, creating favorable conditions for extreme wildfires from any ignition source. Throughout the Arctic lightning is expected to increase, increasing the risk of tundra (specifically grassland) fires, with potential to occur in hard-to-reach locations for firefighting. In short, policy actions and education play a crucial role in future wildfire management and adaptation.

Future↗

NASA NTRS2023

Sewage Treatment Plant #1 Area, SWMU 117 Per- and Polyfluoroalkyl Substances (PFAS) Site Assessment Progress Report

This Per- and Polyfluoroalkyl Substances (PFAS) Site Assessment (SA) Progress Report (SAPR) discusses the investigation activities and findings for the Sewage Treatment Plant #1 (STP1) Area located at Kennedy Space Center (KSC), Florida (Figure 1-1). This site has been designated Solid Waste Management Unit (SWMU) 117 under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action Program, as the sewage treatment plant and associated areas were identified as a potential source of PFAS to the environment. This PFAS SAPR was prepared by Tetra Tech, Inc., for the National Aeronautics and Space Administration (NASA) under Indefinite Delivery Indefinite Quantity Contract 80KSC019D0011-80KSC019F0070. This is the first progress report to document on-going SA activities; supplemental progress reports will be provided as additional data is collected. PFAS SA activities were conducted between April 2020 and March 2022 to collect additional data to supplement the existing datasets to better understand the extent of PFAS impacts to the environment in the STP1 Area. The SA for the STP1 Area covers an approximately 130-acre investigation area with multiple structures and buildings. The focus of the SA is the STP1 Complex and associated structures, including the former Polishing Pond, former Sludge Disposal8 Area, and former Spray Field. The STP1 Complex is located in the KSC Industrial Area, at the southwest corner of 4th Street SE and C Avenue SE. The STP1 Complex is located approximately ¼-mile south and downgradient of the Fire Station #1 site (SWMU 116), which is also currently undergoing a PFAS SA because of potential releases of PFAS-containing aqueous film-forming foam (AFFF). During the SA, a total of seven soil, 131 groundwater direct push technology (DPT), 24 groundwater monitoring well, and 11 surface water samples were collected between April 2020 and March 2022. Monitoring well samples were analyzed for 18 PFAS compounds, with all other samples analyzed for 28 PFAS compounds. The SA sample results were used along with historical results to evaluate the extent of PFAS impacts to the environment in the STP1 Area. Data generated to date and prior results were screened against the United States Environmental Protection Agency (USEPA) May 2022 Tap Water Regional Screening Levels (RSL) for groundwater and residential RSLs for soil (hazard quotient of 0.1). Surface water results were screened against the State of Florida Human Health Surface Water Screening Levels (SWSLs). Results from the SA showed exceedances of the applicable screening criteria for groundwater and surface water. Considering the current and historical dataset, PFOS is the prevalent PFAS compound. Based on these results, additional groundwater DPT and surface water sampling should be considered for PFAS analysis, focused on evaluating surface water bodies in the southeast portion of the Industrial Area, which discharge into the Banana River. Additionally, installation of monitoring wells should be considered to evaluate the interaction between the groundwater and surface water at the site. Collection of additional samples for TOC analysis should also be considered from representative groundwater (saturated soils) and surface water locations to further evaluate potential correlations between PFAS and TOC to provide a more comprehensive dataset to assist in fate and transport analyses.

Sewage Treatment Plant↗

DOE OSTI2022

How to Build a Connected Community: Policies to Promote Grid-interactive Efficient Buildings and Demand Flexibility

Efficient, connected, grid-interactive, smart, and flexible buildings are key to decarbonizing the U.S. energy economy, optimizing energy use, reducing electric consumers’ bills, integrating variable renewable energy resources, and improving the reliability and performance of the nation’s electricity grids. Such grid-interactive efficient buildings have high levels of energy efficiency layered with other distributed energy resources (DERs) and intelligent controls to provide demand flexibility. Policy support is unfolding at the federal, state, and local levels to transform homes and workplaces into state-of-the-art energy-efficient buildings and community-level grid services. This paper starts by describing the potential benefits. Next, it highlights existing policies — with a focus on state-level actions — that support grid-interactive efficient building deployment and demand flexibility. Finally, it identifies current trends and gaps, policies and programs that promote grid-interactive efficient buildings, and aggregations of grid-interactive efficient buildings referred to as Virtual Power Plants.

Schwartz, Lisa C↗

DOE OSTI2024

Lawrence, Massachusetts, Residential Building Efficiency and Electrification Analysis [Slides]

As part of the Communities Local Energy Action Program (CLEAP), the Lawrence Stakeholders Coalition (LSC) is interested in assessing and understanding the potential for and pathways to electrification for the City of Lawrence. The LSC's main questions are: What is the impact of various electrification packages on residential electricity bills and what types of buildings should the LSC target for electrification plus weatherization packages? This technical assistance, using ResStock tool modeling, aims to assist the Coalition's electrification and energy burden reduction planning by: 1. Providing cross-cutting data on housing stock characteristics, energy burden characteristics, fuel types, energy consumption, and system efficiency; and 2. Providing information on upgrade package costs, emissions reduction, and energy reductions by prioritized housing segment. The ResStock analysis presented here focuses on opportunities to reduce energy burden, energy consumption, and energy bills for single family homes, multifamily buildings, and mobile homes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

A Generic Advanced Computing Framework for Executing Windows-based Dynamic Contingency Analysis Tool in Parallel on Cluster Machines

Dynamic contingency analysis tool (DCAT) has been developed to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. By including more customized protection models and corrective actions into the Windows-based commercial tools, DCAT can help operators understand the cascading behavior and find mitigation approaches to reduce the risk of cascading outages in a more realistic manner. In order to further enhance the capability of DCAT, this paper presents a design of an advanced computing framework that enables DCAT to run on a cluster machine to improve its computational performance. This framework is generic and can be applied to other Windows-based simulation tools to fill the technical gap of applying advanced computing technology to vendors' Windows-based tools. The preliminary tests using medium to large power systems have shown the effectiveness of this framework and its potential for accelerating the adoption of advanced computing in utilities.

Advanced computing, dynamic contingency analysis, ↗

DOE OSTI2024

Multi-State Transportation Electrification Impact Study: Preparing the Grid for Light-, Medium-, and Heavy-Duty Electric Vehicles

Recent U.S. Environmental Protection Agency (EPA) notices of proposed rulemakings for GHG emissions standards for light-, medium-, and heavy-duty on-road vehicles would accelerate ongoing advancements already happening in the industry because of private investment, consumer demand, state-level policies, and federal incentives. As the EPA finalizes these regulations, questions persist regarding the cost of the requisite charging infrastructure and associated upgrades to the nation's electric grid. With support from the U.S. Department of Energy, U.S. Joint Office of Energy and Transportation, and the EPA, a multidisciplinary team conducted a Multi-State Transportation Electrification Impact Study that quantitatively assesses the incremental investment necessary to enable the levels of vehicle electrification expected to be induced by pending EPA regulations and to estimate the potential value of deferred investments in electric distribution infrastructure stemming from proactive vehicle-grid integration planning and deployment. This study finds the simulated incremental capital cost of charging infrastructure (including grid upgrades) to be at least 2.5 times smaller than the lifetime net benefits of vehicle electrification (including fuel savings but excluding the value of avoided emissions). Additionally, the incremental distribution grid upgrade cost of the EPA Action-Unmanaged scenario was found to be approximately 3% of existing utility distribution system investments (on an annual basis). Finally, the potential for managed charging to defer distribution grid upgrades was found to be significant with costs found to decrease from $2.3 billion to an incremental cost of $1 billion across five states in the Action-Managed scenario (relative to the No Action-Unmanaged scenario).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Transportation Electrification Impact Study (TEIS)

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗