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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Battery and backup generator sizing for a resilient microgrid under stochastic extreme events

Owing to the recent power outages caused by extreme events, installing battery energy storage and backup generators is important to improve resiliency for a grid-tied microgrid. In the design stage, the event occurrence time and duration, which are highly uncertain and cannot be effectively predicted, may affect the needed battery and backup generator capacity but are usually assumed to be pre-determined in utility planning tools. This study investigates the optimal battery and backup generator sizing problem considering the stochastic event occurrence time and duration for the grid-tied microgrid under islanded operation. The reliability requirement is quantified by the mean value of the critical customer interruption time in each stochastic islanding time window (ITW), whose length is the duration and the centre is the occurrence time. The stochastic ITW constraint is then transformed to a probability-weighted expression to derive an equivalent Mixed Integer Linear Programming model. Numerical simulations on a realistic grid-tied PV-based microgrid demonstrate that the total cost is reduced by 11.5% considering the stochastic ITW, compared with the deterministic ITW under the same reliability requirement.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Quantifying the economic costs of power outages owing to extreme events: A systematic review

Quantifying the economic cost of long-duration power outages is crucial to justifying investments in resiliency and reliability improvements. However, extensive study on the subject complicates the identification of power outage costs and determining the most suitable approach to quantify them for an individual, specific facility, particularly in the context of extreme events. Here, this research provides a systematic review of economic studies estimating the impact of environmental disasters at the microeconomic and macroeconomic levels. Of 326 articles, evaluating the costs of power outages in extreme events, this work identified 22 studies that attempted to quantify the economic costs. These findings indicate that quantifying power outage costs lacks standardization, posing challenges for comparing different studies. Most analyses aiming to quantify these costs for utilities, sectors, and the overall economy rely on outdated survey data, which offer generalized rather than specific cost estimations. The costs of power outages exhibit a significant dependence on factors such as the sector involved, the type of customer affected, and the outage duration. To quantify industry costs, the research in this study suggests that using the National Renewable Energy Laboratory's online, open-access Customer Damage Function Calculator is the best option for individual-level assessments of industries, hospitals, offices, education centers, and similar facilities. However, the Interruption Cost Estimate Calculator can estimate outage costs across industrial, commercial, and residential sectors for macroeconomic outcomes. Finally, this article discusses the relative strengths of these methods and tools and the potential directions for future research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems, e.g., emergency asset management. Included is an example case study: Hurricane Dolly damaging a synthetic 2000-bus test system during its landing in Southern Texas. We perform statistical analysis of damages and discuss topological effects on the example synthetic grid. Also, we include a cursory evaluation of impacts using simplified operational models. Finally, we discuss how our method can be extended to use even higher-fidelity meteorological data sets and suggest directions for future work.

contingencies↗
DOE OSTI2012

Managing the risks of extreme events and disasters to advance climate change adaptation. Special report of the Intergovernmental Panel on Climate Change (IPCC)

This Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) has been jointly coordinated by Working Groups I (WGI) and II (WGII) of the Intergovernmental Panel on Climate Change (IPCC). The report focuses on the relationship between climate change and extreme weather and climate events, the impacts of such events, and the strategies to manage the associated risks. This Special Report, in particular, contributes to frame the challenge of dealing with extreme weather and climate events as an issue in decision making under uncertainty, analyzing response in the context of risk management. The report consists of nine chapters, covering risk management; observed and projected changes in extreme weather and climate events; exposure and vulnerability to as well as losses resulting from such events; adaptation options from the local to the international scale; the role of sustainable development in modulating risks; and insights from specific case studies. (LN)

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Investigating Extreme Events in the NASA GEOS Multiscale Modeling System

Advances in computing capabilities and scientific development have come together to evolve general circulation models into multi-scale Earth system modeling tools. The Goddard Earth Observing System (GEOS) model is one such example of this evolution. The GEOS model is driven by the finite-volume cubed-sphere (FV3) non-hydrostatic dynamical core. Surrounding FV3 is a scale-aware physics package and data assimilation capability permitting multi-scale application of GEOS for sub-seasonal to seasonal climate prediction, medium range weather prediction, and global mesoscale modeling at convection allowing resolutions. GEOS also includes a comprehensive chemistry package representing a range of capabilities from basic chemistry and interactve aerosols and gaseous species, to carbon emissions and uptake, and complex ozone photochemistry. In this study, we apply the GEOS model to study the fidelity of these processes with increasing horizontal resolution and scale-aware processes in GEOS on extreme events. The GEOS model is run for 40-days beginning in August 2016 at three uniform global resolutions of 13-km (c768), 6-km (c1536) and 3-km (c3072) with 72 vertical levels up to 0.01mb. The model physics use the Grell-Freitas scale-aware convection scheme to dynamically reduce the role of parameterized deep convection as resolved scale processes in the model take over at higher resolutions. We will include high-resolution global emissions and fluxes of aerosols and carbon downscaled from recent satellite observations. We will compare these simulations with reanalyses and observations, focusing on rainfall, clouds and radiative forcing at hourly to monthly timescales. We will closely examine the probability distribution of precipitation intensities and radiative properties of clouds on a daily time scale. In addition, we will focus on extreme events, in particular the diurnal cycle of convection over the US and the frequency and physical nature of organized convection and heavy rain events across the globe.

Putman, William↗
DOE OSTI2022

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources: Preprint

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Included is an example case study: Hurricane Dolly damaging a synthetic 2000 bus test system during its landing in Southern Texas. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems including emergency asset management. We perform statistical analysis of damages and quantify topological effects on example synthetic grid. Also, we investigate loss-of-load events during two-day economic dispatch experiment. Finally, we point out various shortcomings of our method and suggest how it can be improved.

contingencies↗
DOE OSTI2024

TEAMER - Extreme Events Modeling for the MARMOK-OWC Wave Energy Converter

Through the TEAMER program, Sandia National Laboratories (SNL) collaborated with IDOM Incorporated to study their MARMOK-Oscillating Water Column (MARMOK-OWC) wave energy conversion device. The study yielded a quantitative understanding of hydrodynamic pressures on the oscillating water column (OWC) device surfaces, the mooring tensions, and the dynamic performance of the device under extreme ocean wave conditions. This project utilized a comprehensive multi-phase Navier-Stokes flow solver with an overset body-fit mesh to predict fluid velocities and hydrodynamic forces on the MARMOK-OWC device. Computational Fluid Dynamics (CFD) analysis were conducted using OpenFOAM. This data includes the OpenFOAM cases (setup and data) to run the extreme events developed during the project. This project is part of the TEAMER RFTS 4 (request for technical support) program.

16 TIDAL AND WAVE POWER↗
NASA NTRS2019

Thermospheric Heating and Cooling Times During Geomagnetic Storms, Including Extreme Events

We present the first quantitative calculations of thermospheric heating and cooling times for geomagnetic storms of different intensity, including extreme events. We utilize the neutral mass density database of the CHAllenging Mini‐satellite Payload and Gravity Recovery And Climate Experiment missions to produce thermospheric global system response to geomagnetic storms caused by coronal mass ejections via superposed epoch analysis during May 2001 to December 2015. Storm events are grouped in five different categories based on the minimum value of the SYM‐H index. We calculate the time from storm onset for the thermosphere to reach maximum intensification (heating time) and the time from onset for the thermosphere to recover (cooling time). We find that heating and cooling times decrease as storm intensity increases and the effect is more pronounced for the cooling times. For extreme storms, the thermospheric heating time is 9.5 hr, while the cooling time is 22 hr.

Zesta, Eftyhia↗
DOE OSTI2017

Grid Frequency Extreme Event Analysis and Modeling: Preprint

Sudden losses of generation or load can lead to instantaneous changes in electric grid frequency and voltage. Extreme frequency events pose a major threat to grid stability. As renewable energy sources supply power to grids in increasing proportions, it becomes increasingly important to examine when and why extreme events occur to prevent destabilization of the grid. To better understand frequency events, including extrema, historic data were analyzed to fit probability distribution functions to various frequency metrics. Results showed that a standard Cauchy distribution fit the difference between the frequency nadir and prefault frequency (f_(C-A)) metric well, a standard Cauchy distribution fit the settling frequency (f_B) metric well, and a standard normal distribution fit the difference between the settling frequency and frequency nadir (f_(B-C)) metric very well. Results were inconclusive for the frequency nadir (f_C) metric, meaning it likely has a more complex distribution than those tested. This probabilistic modeling should facilitate more realistic modeling of grid faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events

Here, we describe two unprecedented large (100-member), longterm (61-year) ensembles based on MRI-AGCM3.2, which were driven by historical and non-warming climate forcing. These ensembles comprise the "Database for Policy Decision making for Future climate change (d4PDF)". We compare these ensembles to large ensembles based on another climate model, as well as to observed data, to investigate the influence of anthropogenic activities on historical changes in the numbers of record-breaking events, including: the annual coldest daily minimum temperature (TNn), the annual warmest daily maximum temperature (TXx) and the annual most intense daily precipitation event (Rx1day). These two climate model ensembles indicate that human activity has already had statistically significant impacts on the number of record-breaking extreme events worldwide mainly in the Northern Hemisphere land. Specifically, human activities have altered the likelihood that a wider area globally would suffer record-breaking TNn, TXx and Rx1day events than that observed over the 2001- 2010 period by a factor of at least 0.6, 5.4 and 1.3, respectively. However, we also find that the estimated spatial patterns and amplitudes of anthropogenic impacts on the probabilities of record-breaking events are sensitive to the climate model and/or natural-world boundary conditions used in the attribution studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Trend Detection of Atmospheric Time Series: Incorporating Appropriate Uncertainty Estimates and Handling Extreme Events

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to, 1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry; 2) describe a range of trend-detection methods; and 3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short- and long-term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to, 1) review trend detection methods for addressing different levels of data complexity in different chemical species; 2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability; 3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates; and 4) present an advanced method of quantifying regional trends based on the inter-site correlations of multi-site data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

Trace gas↗
DOE OSTI2015

PULSAR OBSERVATIONS OF EXTREME SCATTERING EVENTS

Extreme scattering events (ESEs) in the interstellar medium (ISM) were first observed in regular flux measurements of compact extragalactic sources. They are characterized by a flux variation over a period of weeks, suggesting the passage of a “diverging plasma lens” across the line of sight (LOS). Modeling the refraction of such a lens indicates that the structure size must be of the order of AU and the electron density of the order of 10s of cm{sup −3}. Similar structures have been observed in measurements of pulsar intensity scintillation and group delay. Here we report observations of two ESEs, showing increases in both intensity scintillation and dispersion made with the Parkes Pulsar Timing Array. These allow us to make more complete models of the ESE, including an estimate of the “outer-scale” of the turbulence in the plasma lens. These observations clearly show that the ESE structure is fully turbulent on an AU scale. They provide some support for the idea that the structures are extended along the LOS, such as would be the case for a scattering shell. The dispersion measurements also show a variety of AU scale structures that would not be called ESEs, yet involve electron density variations typical of ESEs and likely have the same origin.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2024

NPCC4: Tail Risk, Climate Drivers of Extreme Heat, and New Methods for Extreme Event Projections

We summarize historic New York City (NYC) climate change trends and provide the latest scientific analyses on projected future changes based on a range of global greenhouse gas emissions scenarios. Building on previous NPCC assessment reports, we describe new methods used to develop the projections of record for sea level rise, temperature, and precipitation for NYC, across multiple emissions pathways and analyze the issue of the “hot models” associated with the 6th phase of the Coupled Model Intercomparison Project (CMIP6) and their potential impact on NYC's climate projections. We describe the state of the science on temperature variability within NYC and explain both the large-scale and regional dynamics that lead to extreme heat events, as well as the local physical drivers that lead to inequitable distributions of exposure to extreme heat. We identify three areas of tail risk and potential for its mischaracterization, including the physical processes of extreme events and the effects of a changing climate. Finally, we review opportunities for future research, with a focus on the hot model problem and the intersection of spatial resolution of projections with gaps in knowledge in the impacts of the climate signal on intraurban heat and heat exposure.

NPCC4↗
DOE OSTI2018

Higher CO 2 concentrations increase extreme event risk in a 1.5 °C world

The Paris Agreement aims to ‘pursue efforts to limit the temperature increase to 1.5 °C above pre-industrial levels.’ However, it has been suggested that temperature targets alone are insufficient to limit the risks associated with anthropogenic emissions. Here, using an ensemble of model simulations, we show that atmospheric CO 2 increase—an even more predictable consequence of emissions than global temperature increase—has a significant direct impact on Northern Hemisphere summer temperature, heat stress, and tropical precipitation extremes. Hence in an iterative climate mitigation regime aiming solely for a specific temperature goal, an unexpectedly low climate response may have corresponding ‘dangerous’ changes in extreme events. The direct impact of higher CO 2 concentrations on climate extremes therefore substantially reduces the upper bound of the carbon budget, and highlights the need to explicitly limit atmospheric CO2 concentration when formulating allowable emissions. Thus, complementing global mean temperature goals with explicit limits on atmospheric CO 2 concentrations in future climate policy would limit the adverse effects of high-impact weather extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Integrating Models with Real-time Field Data for Extreme Events: From Field Sensors to Models and Back with AI in the Loop

Focal Area(s): This whitepaper is responsive to focal area (1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). We discuss Artificial Intelligence and Machine Learning (AI/ML) enabled integration of real-time data into the extreme event modeling workflow to improve the predictive capabilities of these models, and deliver real-time feedback to remote sensors, including software and data engineering challenges.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Drought onset mechanisms revealed by satellite solar-induced chlorophyll fluorescence: Insights from two contrasting extreme events

This study uses the droughts of 2011 in Texas and 2012 over the central Great Plains as case studies to explore the potential of satellite-observed solar-induced chlorophyll fluorescence (SIF) for monitoring drought dynamics. We find that the spatial patterns of negative SIF anomalies from the Global Ozone Monitoring Experiment 2 (GOME-2) closely resembled drought intensity maps from the U.S. Drought Monitor for both events. The drought-induced suppression of SIF occurred throughout 2011 but was exacerbated in summer in the Texas drought. This event was characterized by a persistent depletion of root zone soil moisture caused by yearlong below-normal precipitation. In contrast, for the central Great Plains drought, warmer temperatures and relatively normal precipitation boosted SIF in the spring of 2012; however, a sudden drop in precipitation coupled with unusually high temperatures rapidly depleted soil moisture through evapotranspiration, leading to a rapid onset of drought in early summer. Accordingly, SIF reversed from above to below normal. For both regions, the GOME-2 SIF anomalies were significantly correlated with those of root zone soil moisture, indicating that the former can potentially be used as proxy of the latter for monitoring agricultural droughts with different onset mechanisms. Further analyses indicate that the contrasting dynamics of SIF during these two extreme events were caused by changes in both fraction of absorbed photosynthetically active radiation fPAR and fluorescence yield, suggesting that satellite SIF is sensitive to both structural and physiological/biochemical variations of vegetation. Here, we conclude that the emerging satellite SIF has excellent potential for dynamic drought monitoring.

58 GEOSCIENCES↗
DOE OSTI2024

Geological study of an outburst flood event in the upper Yangtze River and risk of similar extreme events

Here, outburst flood sediments are studied on the upper course of the Yangtze River (known as the Jinsha River) where is a key region for the development of hydroelectric power. As the history and magnitude of outburst flooding in this stretch of the Jinsha River during historic times has remained largely undocumented, we have endeavored as part of this study to conduct field investigations into, and provide numerical dating (using OSL and 14 C dating techniques) of outburst flood evidence found in the First Bend area of the Yangtze River. Carbonized nutshells and charcoal from the ancient settlement yielded 14 C ages that precisely pinpointed an outburst flood event ~1200–1300 cal yr BP, during China's Tang Dynasty (618–907 CE). However, OSL ages using the minimum age model for all outburst flood samples ranged from 9.1 to 1.8 ka, which was ~0.5–7.8 ka older than the 14 C-dated outburst flood. This discrepancy suggests a potential overestimation of quartz age when dating outburst flood sediments from the Holocene period. Furthermore, using 2D hydraulic modeling, we estimated the magnitude of the aforementioned outburst flood, revealing a reconstructed peak flow discharge of 51,000–55,300 m 3 /s. This discharge was three times greater than the 10,000-year flood for the hydroelectric power station nearest to the study area. Our study underscores the significant role of combining archaeological and geological evidence in enhancing paleoflood hydrology research. Through a multidisciplinary approach, our findings emphasize the importance of paleoflood hydrology studies in comprehending both the latent and catastrophic flood risks in alpine mountain areas amid the context of global warming.

14C dating↗
DOE OSTI2017

Concentration-discharge relationships during an extreme event: Contrasting behavior of solutes and changes to chemical quality of dissolved organic material in the Boulder Creek Watershed during the September 2013 flood: SOLUTE FLUX IN A FLOOD EVENT

During the week of September 10-17, 2013, close to 20 inches of rain fell across Boulder County, Colorado, USA. This rainfall represented a 1000-year event that caused massive hillslope erosion, landslides, and mobilization of sediments. The resultant stream flows corresponded to a 100-year flood. For the Boulder Creek Critical Zone Observatory (BC-CZO), this event provided an opportunity to study the effect of extreme rainfall on solute concentration-discharge relationships and biogeochemical catchment processes. We observed base cation and dissolved organic carbon (DOC) concentrations at two sites on Boulder Creek following the recession of peak flow. We also isolated three distinct fractions of dissolved organic matter (DOM) for chemical characterization. At the upper site, which represented the forested mountain catchment, the concentrations of the base cations Ca, Mg and Na were greatest at the peak flood and decreased only slightly, in contrast with DOC and K concentrations, which decreased substantially. At the lower site within urban corridor, all solutes decreased abruptly after the first week of flow recession, with base cation concentrations stabilizing while DOC and K continued to decrease. Additionally, we found significant spatiotemporal trends in the chemical quality of organic matter exported during the flood recession, as measured by fluorescence, 13C-NMR spectroscopy, and FTICR-MS. Similar to the effect of extreme rainfall events in driving landslides and mobilizing sediments, our findings suggest that such events mobilize solutes by the flushing of the deeper layers of the critical zone, and that this flushing regulates terrestrial-aquatic biogeochemical linkages during the flow recession.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗