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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Persistence and potential of soil organic carbon in nature‐based climate solutions: A review of managed disturbances

Societal Impact Statement Implementing nature-based climate solutions is important for mitigating climate change, which is a global issue, but requires local adjustments in management practices. Using the association between soil carbon and minerals as a proxy for carbon persistence, we evaluated the effect of different management regimes on soil carbon sequestration and loss. We identified areas where management practices that increase carbon inputs should be prioritized and areas where management should focus on avoiding severe disturbances. Using this storage-potential-and-persistence framework to identify how to increase or maintain soil organic carbon storage locally will increase the effectiveness of nature-based climate solutions globally. Summary Increasing soil organic carbon storage could reduce the pace of climate change, but the longevity of this nature-based climate solution depends on the persistence of carbon in soils, not just the input rates into soils. We apply a framework for considering how soil carbon persistence—namely, via the association with minerals—sheds light on soil carbon sequestration. We review how management of disturbances, such as prescribed burning, forestry, and grazing, can change soil carbon storage, persistence, and potential. Past work demonstrated that management of disturbances can sequester soil carbon, but it remains unclear how the potential stabilization of that accrual and vulnerability to loss varies across disturbance types and geographies. We found that there is substantial geographical heterogeneity in the overlap among estimates of carbon accrual, disturbance occurrence, and potential stabilization: Fire-prone grasslands and intensively grazed rangelands occur in areas estimated to have high potential to store mineral-associated organic carbon, and studies also find that adjusted fire and grazing can promote mineral-associated organic carbon. Plantation forestry and burned area span large regions where particulate organic matter is the dominant form, and studies find that particulate organic carbon is disproportionately lost following intense wildfires and forest harvests. Thus, areas with high mineral-associated organic carbon deficits should be prioritized for practices that increase carbon inputs; whereas areas with high proportions of particulate organic carbon should be prioritized for practices that help to avoid severe disturbances. Taken together, the distribution of and changes in persistence mechanisms shed light on the durability of nature-based climate solutions.

fire↗
DOE OSTI2021

Low diffusive methane emissions from the main channel of a large Amazonian run-of-the-river reservoir attributed to high methane oxidation

The global development of hydropower dams has rapidly expanded over the last several decades and has spread to historically non-impounded systems such as the Amazon River's main low land tributaries in Brazil. Despite the recognized significance of reservoirs to the global methane (CH4) emission, the processes controlling this emission remain poorly understood, especially in Tropical reservoirs. Here we evaluate CH4 dynamics in the main channel and downstream of the Santo Antônio hydroelectric reservoir, a large tropical run-of-the-river (ROR) reservoir in Amazonia. This study is intended to give a snapshot of the CH4 dynamics during the falling water season at the initial stage after the start of operations. Our results show substantial and higher CH4 production in reservoirs' littoral sediment than in the naturally flooded areas downstream of the dam. Despite the large production in the reservoir or naturally flooded areas, high CH4 oxidation in the main channel keep the concentration and fluxes of CH4 in the main channel low. Similar CH4 concentrations in the reservoir and downstream close to the dam suggest negligible degassing at the dam, but stable isotopic evidence indicates the presence of a less oxidized pool of CH4 after the dam. ROR reservoirs are designed to disturb the natural river flow dynamics less than traditional reservoirs. If enough mixing and oxygenation remain throughout the reservoir's water column, naturally high CH4 oxidation rates can also remain and limit the diffusive CH4 emissions from the main channel. Nevertheless, it is important to highlight that our results focused on emissions in the deep and oxygenated main channel. High emissions, mainly through ebullition, may occur in the vast and shallow areas represented by bays and tributaries. However, detailed assessments are still required to understand the impacts of this reservoir on the annual emissions of CH4.

Amazon, aquatic, biogeochemistry, carbon cycling, ↗
DOE OSTI2022

ECAR-6330 Rev 0 Computational Fluid Dynamics Evaluation of Core Pressure Drop for the Primary Coolant Apparatus Test

PCAT is a thermal-hydraulic test loop for MARVEL reactor. The design gap thickness between the heater rods of PCAT core is 1.0 mm. The heater elements were manufactured within a straightness tolerance for the designed gap thickness, but several elements have been distorted out of tolerance during the welding process. The distortion of heater rods could lead to flow maldistribution and excessive hotspot temperature when the gap between two heater rods is too narrow. Wire-wraps are the spacer devices widely used in the sodium cooled fast reactor system to maintain the design fuel pitch. Generally, a wire spacer can enhance the turbulent heat transfer, but it increases the pressure drop, which is not desirable for a natural-circulation system like PCAT. Therefore, three short wire-wrap spacers per heater have been proposed to contain the core pressure drops and keep the heater-to-heater gap in an acceptable range. The objectives of this ECAR is to evaluate the PCAR core pressure drop with short wire spacers to confirm that the additional pressure drop due to the wire spacer will not disturb the natural circulation of the PCAT.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

Predator mass mortality events restructure food webs through trophic decoupling

Predators have a key role in structuring ecosystems. However, predator loss is accelerating globally, and predator mass-mortality events (MMEs)—rapid large-scale die-offs—are now emblematic of the Anthropocene epoch. Owing to their rare and unpredictable nature, we lack an understanding of how MMEs immediately impact ecosystems. Past predator-removal studies may be insufficient to understand the ecological consequences of MMEs because, in nature, dead predators decompose in situ and generate a resource pulse, which could alter ensuing ecosystem dynamics by temporarily enhancing productivity. Here we experimentally induce MMEs in tritrophic, freshwater lake food webs and report ecological dynamics that are distinct from predator losses or resource pulses alone, but that can be predicted from theory. MMEs led to the proliferation of diverse consumer and producer communities resulting from weakened top-down predator control and stronger bottom-up effects through predator decomposition. In contrast to predator removals alone, enhanced primary production after MMEs dampened the consumer community response. As a consequence, MMEs generated biomass dynamics that were most similar to those of undisturbed systems, indicating that they may be cryptic disturbances in nature. These biomass dynamics led to trophic decoupling, whereby the indirect beneficial effects of predators on primary producers are lost and later materialize as direct bottom-up effects that stimulate primary production amid intensified herbivory. Furthermore, these results reveal ecological signatures of MMEs and demonstrate the feasibility of forecasting novel ecological dynamics arising with intensifying global change.

Food webs↗
DOE OSTI2020

Attack-resilient algorithms and testbed federation for wide-area protection and control in smart grid

Today’s energy infrastructure is undergoing a massive transformation across all generation, transmission, and distribution systems to provide reliability, efficiency, and sustainability to the power system network. During the past 10 years, there has been a remarkable enhancement in developing close-loop wide-area protection and control (WAPAC) applications, such as automatic generation control (AGC), wide-area protection scheme (WAPS), synchrophasor-based wide-area voltage control system (WAVCS), etc., in the energy management system (EMS) to provide an adequate situational awareness to control center operators during physical disturbances and natural events. The rapid digitalization, unencrypted communication, and numerous data-sharing devices have increased digital access points that have exposed the grid network to countless cyberattacks pertinent to the WAPAC cybersecurity. Given the amount of complex grid network coupled with legacy infrastructures, it is untrustworthy to completely rely on information technology (IT)-based conventional security measures to defend against evolving cyberattacks. Hence, there is a compelling need to go beyond the traditional paradigm of ‘security by obscurity’ and ‘bolt-on’ security measures, and develop a suite of innovative security solutions at multiple layers to transform the current “fault-resilient” grid into “fault and attack-resilient” grid of the future. This dissertation specifically focuses on developing application-specific attack-resilient solutions for critical WAPAC applications in the smart grid. The first part of the study, Attack-Resilient Wide-Area Protection Scheme, presents a cyber-physical attack-resilient system (CPARS) for WAPS, where two anomaly detection methods are proposed to detect multi-level cyberattacks followed by the rules-based intrusion mitigation system (RIMS) to initiate effective mitigation strategies, tailored to these attacks, to restore the normal grid operation after disturbances. The first anomaly detection component, Machine learning-based Anomaly Detection for Centralized WAPS, discusses a novel architecture and methodology for developing a machine-learning-based anomaly detection system (ADS) for the centralized wide-area protection system (CWAPS) by applying the variational mode decomposition (VMD) technique and decision tree (DT) algorithms using cyber logs and synchrophasor measurements. The second component, Multi-Agent-based Anomaly Detection for Decentralized WAPS, presents a two-level hierarchical multi-agent-based decentralized WAPS against the system-aware stealthy cyber-attacks. Finally, for the RIMS, the state transition diagram-based mitigation measures are defined based on the grid operation states and experimental testing and evaluation are presented in a cyber-physical testbed environment. The second part of the study, Attack-Resilient Wide-Area Voltage Control System, addresses the existing vulnerabilities in the wide-area voltage control system (WAVCS), presents the methodology for performing an impact analysis during data integrity attacks, and proposes a data-driven attackresilient system (DARS) by incorporating machine learning-based ADS and rules-based anomaly mitigation system (RAMS) to detect these attacks and provide necessary mitigation actions to maintain the transient voltage stability after disturbances. Finally, the third part, Networked Federation Testbed (NEFTSec) for Smart Grid Cybersecurity, focuses on developing an interconnected federated testbed through a common network like the internet, describes its conceptual architectures, and also presents its design components for experimental testing, validation, and evaluation. Further, it presents the co-simulation interface algorithm (CIA) to facilitate the geographically-dispersed real-time distributed simulation (GD-RTDS) during the cyber-physical federation. In general, this dissertation presents innovative attack-resilient solutions for WAPAC applications that are experimentally tested and evaluated using the PowerCyber testbed and NEFTSec platform to accelerate the transition of state-of-the-art research works to the real-field deployments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy: How do they compare?

Variation in the electrical conductivity (EC) of water can reveal environmental disturbance and natural dynamics, including factors such as anthropogenic salinization. Broader application of open source (OS) EC sensors could provide an inexpensive method to measure water quality. While studies show that other water quality parameters can be robustly measured with sensors, a similar effort is needed to evaluate the performance of OS EC sensors. To address this need, we evaluated the accuracy (mean error, %) and precision (sample standard deviation) of OS EC sensors in the laboratory via comparison to EC calibration standards using three different OS and OS/commercial-hybrid (OS/C) EC sensors and data logger configurations and two commercial (C) EC sensors and data logger configurations. We also evaluated the effect of cable length (7.5 m and 30 m) and sensor calibration on OS sensor accuracy and precision. We found a significant difference between OS sensor mean accuracy (3.08%) and all other sensors combined (9.23%). Our study also found that EC sensor precision decreased across all sensor configurations with increasing calibration standard EC. There was also a significant difference between OS sensor mean precision (2.85 μS/cm) and the mean precision of all other sensors combined (9.12 μS/cm). Cable length did not affect OS sensor precision. Furthermore, our results suggest that future research should include evaluating how performance is impacted by combining OS sensors with commercial data loggers as this study found significantly decreased performance in OS/commercial-hybrid sensor configurations. To increase confidence in the reliability of OS sensor data, more studies such as ours are needed to further quantify OS sensor performance in terms of accuracy and precision across different settings and OS sensor and data collection platform configurations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data and Scripts associated with: “Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy”

This data package is associated with the publication “Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy: How do they compare?” submitted to PLOS ONE and accepted for publication (Fulton, S.G. et al. 2023; doi not yet available).Variation in electrical conductivity (EC) of water is important to reveal environmental disturbance and natural dynamics, including factors such as anthropogenic salinization. This data package supports a study addressing the need for a robust performance assessment of open source (OS) EC sensors. We evaluated the accuracy (mean error, %) and precision (sample standard deviation) of OS EC sensors in the laboratory via comparison to EC calibration standards using three different OS and OS/commercial-hybrid (OS/C) EC sensors and data logger configurations and two commercial (C) EC sensors and data logger configurations. We also evaluated the effect of cable length (7.5 m and 30 m) and sensor calibration on OS sensor accuracy and precision. This data package presents the results from the different testing laboratory configurations. It also includes an R script for statistical analysis of the data and an Arduino IDE file used to calibrate and collect data with the OS Atlas EC sensor. File types are .csv, .pdf, .R, and .ino.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multi-scale quantification of anthropogenic, fire, and drought-associated forest disturbances across the continental U.S., 2000–2014

Our understanding of broad-scale forest disturbances under climatic extremes remains incomplete. Drought, as a typical extreme event, is a key driver of forest mortality but there have been no reports on continental-scale quantification of its impact on forest mortality or how it compares to other natural or anthropogenic drivers. Thus, our ability to understand and predict broad-scale carbon cycling in response to changing climate and extreme events is limited. In this study, we applied an attribution approach based on different sources of data to quantify the area and potential carbon loss/transfer in continental U.S. (CONUS) from four types of disturbance: (1) anthropogenic (especially timber harvest); (2) fire; (3) drought-associated; and (4) other from 2000 to 2014. Our results showed that anthropogenic disturbances, fire, drought-associated disturbances, and other disturbances accounted for 54.3, 10.7, 12.7, and 22.3% of total canopy area loss, respectively. Anthropogenic disturbance was the most important driver contributing to 58.1% potential carbon loss/transfer in CONUS for 2000–2014. The potential carbon loss/transfer from natural disturbances (fire, drought, and other) for the same study period accounted for approximately 41.9% of the total loss/transfer from all agents, suggesting that natural disturbances also played a very important role in forest carbon turnover. Potential carbon loss/transfer associated with drought accounted for approximately 11.6% of the total loss/transfer in CONUS, which was of similar magnitude to potential carbon loss/transfer from fire (~11.0%). The other natural disturbance accounted for 19.3% of potential carbon loss/transfer. Our results demonstrated the importance of the impacts of various disturbances on forest carbon stocks at the continental scale, and the drought-associated carbon loss/transfer data developed here could be used for evaluating the performance of predictive models of tree mortality under droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Model predictive control for robust quantum state preparation

A critical engineering challenge in quantum technology is the accurate control of quantum dynamics. Model-based methods for optimal control have been shown to be highly effective when theory and experiment closely match. Consequently, realizing high-fidelity quantum processes with model-based control requires careful device characterization. In quantum processors based on cold atoms, the Hamiltonian can be well-characterized. For superconducting qubits operating at milli-Kelvin temperatures, the Hamiltonian is not as well-characterized. Unaccounted for physics (i.e., mode discrepancy), coherent disturbances, and increased noise compromise traditional model-based control. This work introduces model predictive control (MPC) for quantum control applications. MPC is a closed-loop optimization framework that (i) inherits a natural degree of disturbance rejection by incorporating measurement feedback, (ii) utilizes finite-horizon model-based optimizations to control complex multi-input, multi-output dynamical systems under state and input constraints, and (iii) is flexible enough to develop synergistically alongside other modern control strategies. We show how MPC can be used to generate practical optimized control sequences in representative examples of quantum state preparation. Specifically, we demonstrate for a qubit, a weakly-anharmonic qubit, and a system undergoing crosstalk, that MPC can realize successful model-based control even when the model is inadequate. These examples showcase why MPC is an important addition to the quantum engineering control suite.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Bacterial response to the 2021 Orange County, California, oil spill was episodic but subtle relative to natural fluctuations

ABSTRACT An oil spill began in October 2021 off the coast of Orange County, California, releasing 24,696 gallons of crude oil into coastal environments. Although oil spills, such as this one, are recurrent accidents along the California coast, no prior studies have been performed to examine the severity of the local bacterial response. A coastal 10-year time series of short-read metagenomes located within the impacted area allowed us to quantify the magnitude and duration of the disturbance relative to natural fluctuations. We found that the largest change in bacterial beta-diversity occurred at the end of October. The change in taxonomic beta-diversity corresponded with an increase in the sulfur-oxidizing clade Candidatus Thioglobus, an increase in the total relative abundance of potential hydrocarbon-degrading bacteria, and an anomalous decline in the picocyanobacteria Synechococcus . Similarly, changes in function were related to anomalous declines in photosynthetic pathways and anomalous increases in sulfur metabolism pathways as well as aromatic degradation pathways. There was a lagged response in taxonomy and function to peaks in total PAHs. One week after peaks in total PAH concentrations, the largest shifts in taxonomy were observed, and 1 week after the taxonomy shifts were observed, unique functional changes were seen. This response pattern was observed twice during our sampling period, corresponding with the combined effect of resuspended PAHs and increased nutrient concentrations due to physical transport events. Thus, the impact of the spill on bacterial communities was temporally extended and demonstrates the need for continued monitoring for longer than 3 months after initial oil exposure. IMPORTANCE Oil spills are common occurrences in waterways, releasing contaminants into the aquatic environment that persist for long periods of time. Bacterial communities are rapid responders to environmental disturbances, such as oil spills. Within bacterial communities, some members will be susceptible to the disturbance caused by crude oil components and will decline in abundance, whereas others will be opportunistic and will be able to use crude oil components for their metabolism. In many cases, when an oil spill occurs, it is difficult to assess the oil spill’s impact because no samples were collected prior to the accident. Here, we examined the bacterial response to the 2021 Orange County oil spill using a 10-year time series that lies within the impacted area. The results presented here are significant because (i) susceptible and opportunistic taxa to oil spills within the coastal California environment are identified and (ii) the magnitude and duration of the in situ bacterial response is quantified for the first time.

Brock, Melissa L. (ORCID:0000000340329241)↗
DOE OSTI2023

Establishing connectivity patterns of eastern oysters ( Crassostrea virginica ) on regional oceanographic scales

Localized depletion of marine and estuarine populations often results from large-scale natural and anthropogenic disturbances (e.g., hurricanes, oil spills) as well as overharvest of fisheries resources. Understanding how such localized depletions may affect populations at larger regional scales requires knowledge of connectivity among local populations within the larger regional landscape or metapopulation. Efforts to restore populations following such decreases require similar knowledge. During the 2010 Deepwater Horizon oil spill, dramatic declines of oysters occurred throughout estuaries west and east of the Mississippi River. We examined trajectories of particles, which were parameterized to mimic oyster larvae, using the ADvanced CIRCulation (ADCIRC; https://adcirc.org ) model to evaluate potential connectivity within and among embayments from Western Louisiana to Alabama. Patterns of larval settlement, which we defined as the intersection of a larval particle with known or expected oyster habitat at any point 13–21 days post-release, reflected much greater local contributions, with 50%–90% of settled particles originating within the same subdivision of embayments. Exchange among subdivision was much less (0%–40%) and settlement originating from outside the embayment of release was trivial under most scenarios (0%–14%). Connectivity between adjacent basins was greatest for larvae released in the southern portions of the embayment, whereas connectivity among nonadjacent basins was not predicted under the scenarios modeled. Because most local populations are relatively isolated on ecological timescales, areas suffering from extensive local depletion are likely to require extensive time to recover due to the lack of larval subsidy from the overall regional population. Restoration would require building stepping-stone populations or reefs within and among basin to restore a high degree of connectivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of an Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST by extending the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5,000 annual synthetic storm events in a 2,227 $km^2$ Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

58 GEOSCIENCES↗
DOE OSTI2023

Earth Sciences Applications for Energy and Global Security: A Few Vignettes [Slides]

Understanding the physics of flow and transport in the subsurface environment is crucial to several National Security applications. In the Energy Security realm, some examples include characterizing radioactive waste disposal, exploring natural gas extraction and sequestering CO2. An example in the Global Security arena is to be able to distinguish between anthropogenic and naturally occurring seismic disturbances, the former being of particular concern as underground nuclear testing activity has seen an increase in recent years. A common theme across these applications is the ability to accurately model fluid flow in porous and/or fractured subsurface media. For decades, researchers have grappled with how to include the effects of uncertainties in these models, including but not limited to heterogeneity, unknown initial and boundary conditions and issues with scalability. More recently advances in computing and machine learning methodologies have allowed a broader exploration of the uncertainty space as we strive for real time decision making. I will present an overview of the field and discuss a few examples of how my own research in these topics has evolved over nearly two decades.

58 GEOSCIENCES↗
DOE OSTI2020

Forest Structural Complexity and Biomass Predict First-Year Carbon Cycling Responses to Disturbance

The pre-disturbance vegetation characteristics that predict carbon (C) cycling responses to disturbance are not well known. To address this gap, we initiated the Forest Resilience Threshold Experiment, a manipulative study in which more than 3600 trees were stem girdled to achieve replicated factorial combinations of four levels (control, 45, 65, and 85% gross defoliation) of disturbance severity and two disturbance types (targeting upper or lower canopy strata). Applying a standardized stability framework in which initial C cycling resistance to disturbance was calculated as the first-year natural log response ratio of disturbance and control treatments, we investigated to what extent pre-disturbance levels of species diversity, aboveground woody biomass, leaf area index, and canopy rugosity—a measure of structural complexity—predict the initial responses of subcanopy light-saturated leaf CO 2 assimilation (A sat ), aboveground wood NPP (ANPP w ), and soil respiration (R s ) to phloem-disrupting disturbance. In the year following stem girdling, we found that above-ground C cycling processes, A sat and ANPP w , were highly resistant to increases in disturbance severity, while Rs resistance declined as severity increased. Disturbance type had no effect on first-year resistance. Pre-disturbance aboveground woody biomass, and canopy rugosity were positive predictors of ANPP w resistance and, conversely, negatively related to R s resistance. Subcanopy A sat resistance was not related to pre-disturbance vegetation characteristics. Stability of C uptake processes along with R s declines suggest the net C sink was sustained in the initial months following disturbance. Therefore, we conclude that biomass and complexity are significant, but not universal, predictors of initial C cycling resistance to disturbance. Moreover, our findings highlight the utility of standardized stability measures when comparing functional responses to disturbance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Power quality disturbances diagnosis: A 2D densely connected convolutional network framework

The fast and accurate diagnosis of power quality disturbances (PQD) aids in avoiding shutdowns and unnecessary procedures, concerning electric energy distribution systems. As such, a number of techniques have been tested and applied in order to reach this objective. Majority of the techniques applied are two-step based. On the first step, power quality disturbances features are extracted. Second step, considering features extracted, disturbance classification is implemented. Recently, relevant literature has presented data-driven signal processing-based approaches, as deep convolutional neural networks (DCNN), which can implement both processing steps while providing automated recognition of patterns and outliers in data. However, not considered by state-of-art, power quality disturbances are evolving in nature, while all possible regularities might not be represented in the dataset. In this work a 2 Dimension Densely Connected Convolutional Network (2D-DenseNet) framework is presented. Further, a case study with synthetic disturbance events are analyzed. Easy-to-implement formulation, built on the 2D-DenseNet, without hard-to-design parameters, highlight potential aspects for real-life implementation.

42 ENGINEERING↗
DOE OSTI2021

Approximation of the Frequency-Amplitude Curve Using the Homotopy Analysis Method

The Frequency-Amplitude (F-A) curve on power system oscillation under a large disturbance characterizes how a natural oscillation mode transitions to nonlinear oscillations with growing amplitudes and decaying frequencies. The existing formulation of the F-A curve is derived by solving elliptical integrals on oscillation of a single-machine-infinite-bus equivalent about the targeted oscillation mode. The formula is in a form of infinite series and needs to sum a large number of terms for satisfactory accuracy. This paper introduces an explicit, approximate expression obtained from the Homotopy Analysis Method on the F-A curve. The proposed F-A curve expression is derived from an SMIB system and verified on the IEEE 3-machine 9-bus system to show how the oscillation frequency of a dominant mode varies with oscillation amplitude under large disturbances.

frequency-amplitude (F-A) curve↗
DOE OSTI2026

A U.S. scientific community review of carbon cycle science gaps and opportunities to better support earth system science and carbon management

Greenhouse gas (GHG) emissions continue to grow, while natural carbon reservoirs are becoming increasingly vulnerable to anthropogenic pressures, climate extremes, and disturbance. These changes are impacting humans, ecosystems, and natural resources worldwide. Tracking and mitigating GHG emissions require a pivot to operational monitoring of regional carbon flux and stock changes. The current GHG observing system is addressing needs at two distinct scales: 1) Local scale (< 1 km), related to anthropogenic point source emissions, and 2) global scales (> 1000 km), related to land and ocean carbon sinks. More focus on intermediate (10–1000 km) scales is needed to more effectively monitor progress in reducing carbon emissions, enhancing removals, and maintaining sinks. Representatives from carbon cycle biomass and flux communities across United States government agencies and academic institutions met in September 2024 to discuss the rationale and scientific context for more effectively implementing an operational system for GHG monitoring in support of urban and national carbon management needs. To guide development of this system, we propose a multi-tiered global spaceborne observing framework for carbon flux and stock, prioritizing: 1) frequent GHG partial columns for carbon emissions and removals; 2) continuous time series and data fusion of biomass from Lidar and Synthetic Aperture Radar (SAR) for carbon stocks, and 3) expanded coverage of tropical, high latitude, and oceanic regions to monitor carbon cycle tipping points and feedbacks. This system should be complemented by expanded surface and airborne networks for oceanic and terrestrial/aquatic ecosystems for calibration, ground truthing, and study of under-sampled regions.

54 ENVIRONMENTAL SCIENCES↗