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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ChatGPT and Other Large Language Models for Cybersecurity of Smart Grid Applications

Cybersecurity breaches targeting electrical substations constitute a significant threat to the integrity of the power grid, necessitating comprehensive defense and mitigation strategies. Any anomaly in information and communication technology (ICT) should be detected for secure communications between devices in digital substations. This paper proposes large language models (LLMs), e.g., ChatGPT, for the cybersecurity of IEC 61850-based communications. Multi-cast messages such as generic object oriented system events (GOOSE) and sampled values (SV) are used for case studies. The proposed LLM-based cybersecurity framework includes, for the first time, data pre-processing of communication systems and human-in-the-loop (HITL) training (considering the cybersecurity guidelines recommended by humans). The results show a comparative analysis of detected anomaly data carried out based on the performance evaluation metrics for different LLMs. A hardware-in-the-loop (HIL) testbed is used to generate and extract a dataset of IEC 61850 communications.

ChatGPT↗
DOE OSTI2023

Developing a Disaster-Ready Power Grid Agent Through Geophysically-Informed Fault Event Scenarios

Management of the nation’s power grid over the coming decades will need to factor multiple climate-driven threats to the power system that can be stressful or even detrimental to its operations. During disasters, grid operators suffer from cognitive overload where the electric grid is severely impacted by the weather, yet grid operators have limited awareness of these factors. Meanwhile, the electric grid is facing an explosion of data coming from a variety of sources which can enable the operator to evaluate the risks and develop mitigation strategies against hazardous events. In this work, we processed heterogeneous environmental and power grid data to learn and model grid behavior caused by extreme weather events. In this study, we focused on two weather-driven hazards, hurricanes and wildfires, which were analysed for the electric grid of Texas. We the used this data to train a Reinforcement Learning (RL) agent by analysing and predicting future behaviour of the grid during those hazard events. All these parts are incorporated in one framework to have a geophysically informed power simulators that can be used to train RL agents.

electic grid, reinforcement learning, climate adap↗
DOE OSTI2017

Multi-Scenario Use Case based Demonstration of Buildings Cybersecurity Framework Webtool

The purpose of this paper is to demonstrate the cybersecurity and software capabilities of Buildings Cybersecurity Framework (BCF) webtool. The webtool is designed based on BCF document and existing NIST standards. It’s capabilities and features are depicted through a building usecase with four different investment scenarios geared towards improving the cybersecurity posture of the building. BCF webtool also facilitates implementation of the goals outlined in Presidential Executive Order (EO) on Strengthening the Cybersecurity of Federal Networks and Critical Infrastructure (May 2017. In realization of the EO goals, BCF includes five core elements: Identify, Protect, Detect, Respond, and Recover, to help determine various policy and process level vulnerabilities and provide mitigation strategies. With the BCF webtool, an organization can perform a cybersecurity self-assessment; determine the current cybersecurity posture; define investment based goals to achieve a target state; connect the cybersecurity posture with business processes, functions, and continuity; and finally, develop plans to answer critical organizational cybersecurity questions. In this paper, the webtool and its core capabilities are depicted by performing an extensive comparative assessment over four different scenarios.

Gourisetti, Sri Nikhil G.↗
DOE OSTI2021

Smart Meters Enabling Voltage Monitoring and Control Functionalities: The Last-Mile Voltage Stability Issue

It is a demanding yet challenging task to design the next generation of smart meters. This work investigates the new voltage monitoring and control function for the next-generation smart meters, and identifies its added values for power system voltage stability issues. In terms of voltage monitoring, the risk benefit analysis for adding voltage magnitudes to smart meter measurements is presented, and the risk mitigation strategies along with the co-simulation validation via GridLAB-D and NS-3 are proposed, all providing insight into the new function evaluation. In terms of voltage control, a new voltage stability control scheme is developed, which uses voltage measurements from smart meters and utilizes the observability and controllability of distributed energy resources and controllable loads. Different from traditional voltage control schemes focusing on voltage regulation and power quality monitoring from the utility perspective, the proposed control scheme can achieve the maximum real power transfer margin at the end user side, enabling the voltage stability issues being solved at the grid edge, i.e. the last-mile segment. It is the first work that considers voltage monitoring and control collectively for smart meter investment. It can help power engineering community supplement smart meter applications and shape the next-generation smart meters.

42 ENGINEERING↗
DOE OSTI2021

Single Event Transient Response of Vertical and Lateral Waveguide-Integrated Germanium Photodiodes

Pulsed-laser induced single event current measurements on two geometries of waveguide-integrated germanium photodiodes were conducted over a range of operating voltages to examine the impact of photodiode geometry on the transient response. Vertical PIN photodiodes exhibit transients with a duration that is relatively independent of the operating voltage while the transient duration in lateral PIN photodiodes depends on operating voltage. Furthermore, the experimental measurements facilitate identification of device dimensions that impact the transient response. In this work, these results can be used to identify potential radiation mitigation strategies for photodiodes operating in a radiation environment. Understanding the implications of design choices is critical for designing integrated photonic systems that balance system performance with tolerance for radiation degradation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Robust Power System Stability Assessment Against Adversarial Machine Learning-Based Cyberattacks via Online Purification

The increasing complexity associated with renewable generation brings more challenges to power system stability assessment (SA). Data-driven approaches based on machine learning (ML) techniques for stability assessment have received significant research interest and shown their promising performance. However, ML-based models are recognized to be vulnerable to adversarial disturbances, where a slight perturbation to power system measurements could lead to unacceptable errors. To address this issue, this paper develops a novel lightweight mitigation strategy, i.e., robust online stability assessment (ROSA), to enhance the ML-based assessment model against both white-box and the black-box adversarial disturbances (i.e., purification) in the online implementation. The ROSA involves a supervised learning-based module for the primary stability assessment and a self-supervised learning-based module. Further, the two modules are trained jointly with different objective (loss) functions and implemented in sequence. A suitable purification objective and various time-series data augmentation methods are designed for SA applications to tackle adversarial disturbances adaptively. Case studies are performed, and the comparative results have clearly illustrated the competitive, robust accuracy against various adversarial scenarios and verified the effectiveness of the proposed online purification strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Reliable edge machine learning hardware for scientific applications

Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementations of ML algorithms: enabling bit-accurate functional simulations for performance validation in experimental software frameworks, verifying those ML models are robust under extreme quantization and pruning, and enabling ultra-fine-grained model inspection for efficient fault tolerance. We discuss approaches to developing and validating reliable algorithms at the scientific edge under such strict latency, resource, power, and area requirements in extreme experimental environments. We study metrics for developing robust algorithms, present preliminary results and mitigation strategies, and conclude with an outlook of these and future directions of research towards the longer-term goal of developing autonomous scientific experimentation methods for accelerated scientific discovery.

Baldi, Tommaso↗
DOE OSTI2017

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO 2

Heat and drought stresses are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO2 concentration. Here we present a study that quantified the current and future yield responses of US rainfed maize and soybean to climate extremes, and for the first time characterized spatial shifts in the relative importance of temperature, heat and drought stress. Crop yields are simulated using the Agricultural Production Systems sIMulator (APSIM), driven by the high-resolution (12 km) Weather Research and Forecasting (WRF) Model downscaled future climate scenarios at two time slices (1995-2005 and 2085-2094). Our results show that climatic yield gaps and interannual variability are greater in the core production area than in the remaining US by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of change is highly dependent on the current climate sensitivity and vulnerability. Elevated CO2 partially offsets the climatic yield gaps and reduces interannual yield variability, and effect is more prominent in soybean than in maize. We demonstrate that drought will continue to be the largest threat to US rainfed maize and soybean production, although its dominant role gradually gives way to other impacts of heat extremes. We also reveal that shifts in the geographic distributions of dominant stressors are characterized by increases in the concurrent stress, especially for the US Midwest. These findings imply the importance of considering drought and extreme heat simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management.

APSIM↗
DOE OSTI2020

Total ecosystem carbon stocks at the marine-terrestrial interface: Blue carbon of the Pacific Northwest Coast, United States

The coastal ecosystems of temperate North America provide a variety of ecosystem services including high rates of carbon sequestration. Yet, little data exist for the carbon stocks of major tidal wetland types in the Pacific Northwest, United States. We quantified the total ecosystem carbon stocks (TECS) in seagrass, emergent marshes, and forested tidal wetlands, occurring along increasing elevation and decreasing salinity gradients. The TECS included the total aboveground carbon stocks and the entire soil profile (to as deep as 3 m). TECS significantly increased along the elevation and salinity gradients: 217 ± 60 Mg C/ha for seagrass (low elevation/high salinity), 417 ± 70 Mg C/ha for low marsh, 551 ± 47 Mg C/ha for high marsh, and 1,064 ± 38 Mg C/ha for tidal forest (high elevation/low salinity). Soil carbon stocks accounted for >98% of TECS in the seagrass and marsh communities and 78% in the tidal forest. Soils in the 0–100 cm portion of the profile accounted for only 48%–53% of the TECS in seagrasses and marshes and 34% of the TECS in tidal forests. Thus, the commonly applied limit defining TECS to a 100 cm depth would greatly underestimate both carbon stocks and potential greenhouse gas emissions from land-use conversion. The large carbon stocks coupled with other ecosystem services suggest value in the conservation and restoration of temperate zone tidal wetlands through climate change mitigation strategies. However, the findings suggest that long-term sea level rise effects such as tidal inundation and increased porewater salinity will likely decrease ecosystem carbon stocks in the absence of upslope wetland migration buffer zones.

Kauffman, J Boone↗
DOE OSTI2021

Bioenergy for climate change mitigation: Scale and sustainability

Many global climate change mitigation pathways presented in IPCC assessment reports rely heavily on the deployment of biomass for bioenergy, often used in conjunction with carbon capture and storage (BECCS). We review the literature on bioenergy, including the modelling of bioenergy in integrated assessment models (IAMs) and bottom-up modelling and non-modelling studies on the implications of bioenergy use. We summarise the limitations of existing modelling studies and what is known about the potential co-benefits and adverse side-effects of bioenergy systems. We find that the implications of bioenergy supply on mitigation and other sustainability criteria are context dependent and influenced by feedstock, management regime, climatic region, scale of deployment and the counterfactual land use and energy system. However, due to limitations of the existing models, and uncertainty over the future context with respect to the many variables that influence availability of biomass and land resources, it is not possible to precisely quantify the sustainability implications for different scales of bioenergy implementation. Given these uncertainties, the dependence on large-scale deployment of bioenergy in mitigation scenarios carries risks. The deployment of bioenergy technologies and the evolution of biomass supply chains at a scale that achieves significant mitigation and carbon sequestration requires integrative policies, coordinated institutions and improved governance mechanisms. As a result, bioenergy, and the use of land to produce biomass, is an essential part of many climate mitigation strategies but there are limits to its use due to trade-offs with sustainability.

09 BIOMASS FUELS↗
DOE OSTI2022

Continental United States may lose 1.8 petagrams of soil organic carbon under climate change by 2100

Abstract Aims High‐resolution information on soils’ vulnerability to climate‐induced soil organic carbon (SOC) loss can enable environmental scientists, land managers, and policy makers to develop targeted mitigation strategies. This study aims to estimate baseline and decadal changes in continental US surface SOC stocks under future emission scenarios. Location Continental United States. Time period 2014–2100. Methods We used recent SOC field observations ( n = 6,213 sites), environmental factors ( n = 32), and an ensemble machine learning (ML) approach to estimate baseline SOC stocks in surface soils across the continental United States at 100‐m spatial resolution, and decadal changes under the projected climate scenarios of Coupled Model Intercomparison Project Phase Six (CMIP6) earth system models (ESMs). Results Baseline SOC projections from ML approaches captured more than 50% of variability in SOC observations, whereas ESMs represented only 6–16% of observed SOC variability. ML estimates showed a mean total loss of 1.8 Pg C from US surface soils under the high‐emission scenario by 2100, whereas ESMs showed no significant change in SOC stocks with wide variation among ESMs. Both ML and ESM predictions agree on the direction of SOC change (net emissions or sequestration) across 46–51% of continental US land area. These differences are attributable to the high‐resolution site‐specific data used in the ML models compared to the relatively coarse grid represented in CMIP6 ESMs. Main conclusions Our high‐resolution estimates of baseline SOC stocks, identification of key environmental controllers, and projection of SOC changes from US land cover types under future climate scenarios suggest the need for high‐resolution simulations of SOC in ESMs to represent the heterogeneity of SOC. We found that the SOC change is sensitive to key soil related factors (e.g. soil drainage and soil order) that have not been historically considered as input parameters in ESMs, because currently more than 95% variability in the SOC of CMIP6 ESMs is controlled by net primary productivity, temperature, and precipitation. Using additional environmental factors to estimate the baseline SOC stocks and predict the future trajectory of SOC change can provide more accurate results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Reduced and Earlier Snowmelt Runoff Impacts Traditional Irrigation Systems

We show seasonal runoff from montane uplands is crucial for plant growth in agricultural communities of northern New Mexico. These communities typically employ traditional irrigation systems, called acequias, which rely mainly upon spring snowmelt runoff for irrigation. The trend of the past few decades is an increase in temperature, reduced snow pack, and earlier runoff from snowmelt across much of the western United States. In order to predict the potential impacts of changes in future climate a system dynamics model was constructed to simulate the surface water supplies in a montane upland watershed of a small irrigated community in northern New Mexico through the rest of the 21 st century. End-term simulations of representative concentration pathways (RCP) 4.5 and 8.5 suggest that runoff during the months of April to August could be reduced by 22% and 56%, respectively. End-term simulations also displayed a shift in the beginning and peak of snowmelt runoff by up to one month earlier than current conditions. Results suggest that rising temperatures will drive reduced runoff in irrigation season and earlier snowmelt runoff in the dry season towards the end of the 21 st century. Modeled results suggest that climate change leads to runoff scheme shift and increased frequency of drought; due to the uncontemporaneous of irrigation season and runoff scheme, water shortage will increase. Potential impacts of climate change scenarios and mitigation strategies should be further investigated to ensure the resilience of traditional agricultural communities in New Mexico and similar regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Geographic, sectoral, and constituent characteristics of US off‐site manufacturing wastewater disposal

This study employs recent US Environmental Protection Agency off-site manufacturing wastewater disposal data and a socioenvironmental assessment tool for the United States to understand the characteristics of such disposal in terms of geography, major contributing sectors and pollutants, and environmental impacts. Environmental impact analyses of manufacturing are insufficient without encompassing the extended physical boundary of waste management. Our analysis reveals that off-site manufacturing wastewater disposal occurs disproportionately in populations residing in census tracts already negatively impacted by environmental hazards (impacted populations, or IPs) with 44% of transfers and 55% of Risk Screening Environmental Indicators (RSEI) Hazard going to these areas, compared to their national share of 37%. Disposal hazard is concentrated in a small number of populations, with a Gini coefficient of 0.99 for RSEI Hazard. Four manufacturing sub-sectors are significant generators: Chemicals, Fabricated Metals, Primary Metals, and Transportation Equipment, with Chemicals off-site wastewater disposal largely occurring in IPs. For individual contaminants, chromium compounds and chromium represent more than 85% of the hazard but less than 10% of transfers. We explore transfer distances and waste generation and disposal hotspots, finding that the Midwest hosts a disproportionate share of off-site wastewater disposal. Further, RSEI Hazard steeply rises at shorter distances and plateaus over distances >500 miles, revealing opportunities to reduce hazard by reducing 20–500-mile transfers. Our findings strongly support targeted mitigation strategies like process substitutions, control technologies, on-site recycling and treatment, and minimizing transfer distances. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges.

Fuchs, Heidi [Lawrence Berkeley National Laborator↗
DOE OSTI2026

Multi‐season analysis reveals hundreds of drought‐responsive genes in sorghum

Persistent drought affects global crop production and is becoming more severe in many parts of the world in recent decades. Deciphering how plants respond to drought will facilitate the development of flexible mitigation strategies. Sorghum bicolor L. Moench (sorghum), a major cereal crop and an emerging bioenergy crop, exhibits remarkable resilience to drought. To better understand the molecular traits that underlie sorghum's remarkable drought tolerance, we undertook a large-scale sorghum gene expression profiling effort, totaling nearly 1500 transcriptome profiles, across a 3-year field study with replicated plots in California's Central Valley. This study included time-resolved gene expression data from roots and leaves of two sorghum genotypes, BTx642 and RTx430, with different pre-flowering and post-flowering drought-tolerance adaptations under control and drought conditions. Quantification of genotype-specific drought tolerance effects was enabled by de novo sequencing, assembly, and annotation of both BTx642 and RTx430 genomes. These reference-quality genomes were used to construct a pangene set for characterizing conserved and genotype-specific expression. By integrating time-resolved transcriptomic responses to drought in the field across three consecutive years, we identified a set of 726 drought-responsive genes that responded similarly in all 3 years of our field study. Functional enrichment analysis identified abiotic stress, secondary cell wall-related processes and metabolism as particularly affected under both types of drought stress. We also found that some glyoxylate cycle pathway genes, including malate synthase and isocitrate lyase, are differentially regulated particularly during post-flowering drought stress, implicating this pathway as potentially important for drought responsiveness. This expansive dataset represents a unique resource for sorghum and drought research communities and provides a methodological framework for the integration of multi-faceted time-resolved transcriptomic datasets.

Cole, Benjamin [USDOE Joint Genome Institute (JGI)↗
DOE OSTI2016

Joining Dissimilar Materials Using Friction Stir Scribe Technique

Development of a robust and cost-effective method of joining dissimilar materials could provide a critical pathway to enable widespread use of multi-material designs and components in mainstream industrial applications. The use of multi-material components such as steel-aluminum and aluminum-polymer would allow design engineers to optimize material utilization based on service requirements and could often lead to weight and cost reductions. However, producing an effective joint between materials with vastly different thermal, microstructural, and deformation responses is highly problematic using conventional joining and/or fastening methods. This is especially challenging in cost sensitive, high volume markets that largely rely on low cost joining solutions. Friction stir scribe technology was developed to meet the demands of joining materials with drastically different properties and melting regimes. The process enables joining of light metals like magnesium and aluminum to high temperature materials like steel and titanium. Viable joints between polymer composites and metal can also be made using this method. This paper will present the state of the art, progress made, and challenges associated with this innovative derivative of friction stir welding in reference to joining dissimilar metals and polymer/metal combinations.

Upadhyay, Piyush↗
DOE OSTI2022

FOULING MITIGATION FOR LASER IGNITERS IN NATURAL GAS ENGINES

Due to several recent developments in lasers and optics, laser igniters can now be designed to be (i) compact so as to have the same footprint as a standard spark plug, (ii) have low power draw, usually less than 50 Watts, and (iii) have vibration and temperature resistance at levels typical of reciprocating engines. Primary advantages of these laser igniters remain (i) extension of lean or dilution limits for ignition of combustible mixtures, and (ii) improved ignition at higher pressures. Recently, tests performed in a 350 kW six-cylinder stationary natural gas reciprocating engine retrofitted with these igniters showed an extension of the operational envelope to yield efficiency improvements of the order of 2.6% points while being compliant with the mandated emission regulations. Even though laser igniters offer promise, fouling of the final optical element that introduces the laser into the combustion chamber is of concern. After performing a thorough literature search, a test plan was devised to evaluate various fouling mitigation strategies. The final approach that was used is a combination of three strategies and helped sustain an optical transmissivity exceeding 98% even after 1500 h of continuous engine operation at 2400 rpm. Based on the observed trend in transmissivity, it now appears that laser igniters can last up to 6000 h of continuous engine operation in a stationary engine running at 1800 rpm.

spark ignited engines, laser ignition, natural gas↗
DOE OSTI2022

In-situ visualization of the transition metal dissolution in layered cathodes

Transition metal dissolution in layered cathodes is one of the most intractable issues that deteriorates the battery performance and lifetime. It not only aggravates the structure degradation in cathode, but also damages the solid electrolyte interphase in anode and even induce the formation of lithium dendrites. In this work, we investigate the dissolution behaviors of polycrystalline and single-crystalline layered cathode via operando X-ray imaging techniques. The described cathode particle morphology appears to have a significant impact on the evolution of the dissolution dynamics. As a mitigation strategy, we reveal that doping with trace amount of Zr in the layered cathode could improve its robustness against the transition metal dissolution. Our finding provides valuable insights for designing the next-generation highly-stable layered battery cathodes.

25 ENERGY STORAGE↗