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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Climate Change and Changes in Compound Coastal-Riverine Flooding Hazard Along the U.S. Coasts

The cooccurrence of coastal and riverine flooding leads to compound events with substantial impacts on people and property in low-lying coastal areas. Climate change could increase the level of compound flood hazard through higher extreme sea levels and river flows. Here, a bivariate flood hazard assessment method is proposed to estimate compound coastal-riverine frequency under current and future climate conditions. A copula-based approach is used to estimate the joint return period (JRP) of compound floods by incorporating sea-level rise (SLR) and changes in peak river flows into the marginal distributions of flood drivers. Specifically, the changes in JRP of compound major coastal-riverine flooding defined based on simultaneous exceedances above major coastal and riverine thresholds, are explored by midcentury. Subsequently, the increase in the probability of occurrence of at least one compound major coastal-riverine flooding for a given period of time is quantified. The proposed compound flood hazard assessment is conducted at 26 paired tidal-riverine stations along the Contiguous United States coast with long-term data and defined flood thresholds. We show that the northeast Atlantic and the western part of the Gulf coasts are experiencing the highest compound major coastal-riverine flood probability under current conditions. However, future SLR scenarios show the highest frequency amplification along the southeast Atlantic coast. The impact of changes in peak river flows is found to be considerably less than that of SLR. Climate change impacts, especially SLR, may lead to more frequent compound events, which cannot be ignored for future adaptation responses in estuary regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantifying Dam-Induced Fluctuations in Streamflow Frequencies Across the Colorado River Basin

Periodic fluctuations in natural streamflow are a major driver of river ecosystem dynamics and water resource management. However, most U.S. rivers are impacted both by long-term hydroclimatic trends and dams that alter flow variability. Despite these impacts, it remains largely unexplored how dams affect the dominant frequencies of natural streamflow over a highly regulated river network. We investigated the entire Colorado River Basin (CRB) to understand how the annual (10–14 months) and multi-annual (24–60 months) frequencies in natural flow regimes have been progressively altered by dams. Given the significant alteration over the CRB, we captured changes in streamflow frequencies between naturalized and observed monthly flows via wavelet analysis. Based on the similarity of changes in streamflow frequencies (annual and multi-annual) over the last 30 years, sections of the riverine network were classified into four groups. The annual frequency was relatively well preserved downstream of Hoover Dam, while showing a systematic trend of alteration downstream of Glen Canyon Dam until Hoover Dam. Meanwhile, the multi-annual frequency component was highly altered for the entire Lower Colorado main stem (i.e., downstream of Glen Canyon). We also identified dams with significant impacts on streamflow frequency by comparing wavelet coherence estimates. This study advances the notion that dams fundamentally alter river flow regimes across multiple frequencies and with varying amplitudes over time and space, with alteration propagating – or being dampened – by both hydroclimatic fluctuations and water resource management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

U.S. Nuclear Operating Experience Program for Probabilistic Risk Assessment Parameter Estimations

This presentation describes the overall process of the U.S. Nuclear Regulatory Commission (NRC)operating experience (OpE) program to estimate probabilistic risk assessment parameters, the estimations of initiating event frequencies, the component unreliability, and the quality assurance and quality control activities for the OpE program. This presentation can be used for training, workshop, or knowledge transfer purpose.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Analysis of vapor diffusion Nb$^{3}$Sn coating at Fermilab: Minimizing impurities using TOF-SIMS

Nb₃Sn demonstrates steady advancements nowadays offering reduced power cost in superconducting radio-frequency cavities due to its high critical temperature, quality factor, and achieved accelerating gradient. However, theoretical estimates of its radio-frequency parameters have not been achieved due to several potentially limiting mechanisms: tin spots, patchy regions, defects, thermal impedance, and impurities. While some of these limitations have been intensively studied, impurity analysis in Nb$_3$Sn coatings have received less attention. We report an investigation of impurities in several vapor-diffused Nb₃Sn coated samples using time-of-flight secondary ion mass spectroscopy (TOF-SIMS) and show allowable impurity levels in view of superconducting cavity performance. Challenges and lessons learned in maintaining clean Nb$_3$Sn coatings are also discussed.

Tagdulang, Nikki [Fermilab]↗
DOE OSTI2025

Challenges of Vapor Diffusion $Nb_3Sn$ Coating at Fermilab: Minimizing Impurities Using TOF-SIMS

Nb$_3$Sn demonstrates steady advancements nowadays offering reduced power cost in superconducting radio-frequency cavities due to its high critical temperature, quality factor, and achieved accelerating gradient. However, theoretical estimates of its radio-frequency parameters have not been achieved due to several potentially limiting mechanisms: tin spots, patchy regions, defects, thermal impedance, and impurities. While some of these limitations have been intensively studied, impurity analysis in Nb$_3$Sn coatings have received less attention. We report an investigation of impurities in several vapor-diffused Nb$_3$Snn coated samples using time-of-flight secondary ion mass spectroscopy (TOF-SIMS) and show allowable impurity levels in view of superconducting cavity performance. Challenges and lessons learned in maintaining clean Nb$_3$Sn coatings are also discussed.

Tagdulang, N. [Fermilab]↗
DOE OSTI2023

Multi-Agent Simulation Based Framework for Power Restoration Time Estimation at Distribution Level

The growing frequency of power outages has prompted increased interest in developing a more resilient power grid that can quickly recover from weather-related damage. At the distribution level, power restoration is a complex, multi-stage process involving multiple response entities. Providing utility stakeholders, government regulators, and the public with information about outage duration and estimated time to restoration is crucial. The research employs a multi-agent simulation approach, which allows for the simulation of decision-making behaviors among different entities and the incorporation of various uncertainties. Specifically, the study uses the open-source simulation package Mesa-Geo in conjunction with the Python language and constructs a road network using the open-source network extension pgRouting for routing queries. The research design includes several experiments focused on Florida as a case study, comparing repair crew sizes, power outage numbers, and road damage scenarios. The findings could offer valuable managerial guidance on resource allocation in the restoration process.

Chen, Yang↗
DOE OSTI2023

Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors

The reactive nature of traditional under-frequency load shedding schemes can lead to delayed response and unnecessary loss of load. This work presents a proactive framework for power system frequency stability. Bayesian filters and synchrophasors are leveraged to produce predictions after disturbances are detected. By being able to estimate the future state of frequency corrective actions can be taken before the system reaches a critical condition. This proactive approach makes it possible to optimize the response to a disturbance, which results in a decrease in the amount of compensation utilized. The framework is tested via Matlab simulations based on Kundur’s Two-Area System, and the IEEE 14-Bus System. Performance metrics are provided and evaluated against other contemporary solutions found in literature. During testing this framework outperformed other solutions by drastically reducing the amount of load dropped during compensation.

42 ENGINEERING↗
DOE OSTI2020

PFLOTRAN-SIP: A PFLOTRAN Module for Simulating Spectral-Induced Polarization of Electrical Impedance Data

Spectral induced polarization (SIP) is a non-intrusive geophysical method that collects chargeability information (the ability of a material to retain charge) in the time domain or its phase shift in the frequency domain. Although SIP is a temporal method, it cannot measure the dynamics of flow and solute/species transport in the subsurface over long times (i.e., 10–100 s of years). Data collected with the SIP technique need to be coupled with fluid flow and reactive-transport models in order to capture long-term dynamics. To address this challenge, PFLOTRAN-SIP was built to couple SIP data to fluid flow and solute transport processes. Specifically, this framework couples the subsurface flow and transport simulator PFLOTRAN and geoelectrical simulator E4D without sacrificing computational performance. PFLOTRAN solves the coupled flow and solute-transport process models in order to estimate solute concentrations, which were used in Archie’s model to compute bulk electrical conductivities at near-zero frequency. These bulk electrical conductivities were modified while using the Cole–Cole model to account for frequency dependence. Using the estimated frequency-dependent bulk conductivities, E4D simulated the real and complex electrical potential signals for selected frequencies for SIP. These frequency-dependent bulk conductivities contain information that is relevant to geochemical changes in the system. This study demonstrated that the PFLOTRAN-SIP framework is able to detect the presence of a tracer in the subsurface. SIP offers a significant benefit over ERT in the form of greater information content. It provided multiple datasets at different frequencies that better constrained the tracer distribution in the subsurface. Consequently, this framework allows for practitioners of environmental hydrogeophysics and biogeophysics to monitor the subsurface with improved resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Analyzing historical snow trends in interior Alaska

Study region The Chena River watershed in Interior Alaska, USA Study focus This study examines 40 years (water years 1982–2021) of snowpack characteristics to consider its hydrological implications in the 5350 km² Chena River basin. Using observations and a fine-scale physics model, we analyzed trends of snow water equivalent (SWE), snow onset and disappearance, and snow cover duration (SCD). New hydrological insights for the region Results indicate a decline in SWE across the modeled domain, averaging a decrease of 3 mm per decade, with larger decreases (up to 10 mm per decade) at lower elevations. While domain-averaged SWE trends were not statistically significant, observed SCD showed statistically significant decreases: −5.2, −5.0, and −4.4 days per decade at Teuchet Creek, Fairbanks F.O., and Little Chena Ridge, respectively. Notably, observations at SNOTEL stations and modeling revealed no statistically significant change in domain-averaged Rain-on-Snow (ROS) events over the 40-year period, contrasting some regional future estimates of increased ROS frequency. Peak streamflow did not consistently correlate with peak SWE levels, suggesting that other environmental factors such as ROS events and rapid temperature increases (e.g., a 10°C spike observed in 1992) are key drivers of hydrological outcomes. These findings improve understanding of complex subarctic hydrological processes impacting permafrost and highlight the need for adaptive water resource management to mitigate multi-factor risks like flooding and wildfire, requiring proactive planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Laser Doppler vibrometry for piezoelectric coefficient ($d_{33}$) measurements in irradiated aluminum nitride

Sensors used for experiments in advanced reactors must survive in harsh environments. Few material systems can be used to construct sensors viable for extreme conditions. Aluminum nitride (AlN) is one such material because it has high thermal stability and radiation resistance and sustains good piezoelectric and dielectric properties at high temperatures. In this work, the piezoelectric coefficient $d_{33}$ of the AlN single-crystal with thermal and irradiation damage was investigated using an indirect method with a laser Doppler vibrometer (LDV). Surface electrodes were deposited on the AlN samples, and the vibration response of the samples to an applied voltage was monitored using the LDV as a function of the excitation frequency. The $d_{33}$ estimation was based on the excitation voltage and the thickness-mode displacement extracted from the LDV measurements. Further, six AlN substrates were irradiated with 8 MeV Al 2+ at three fluences (10 15 , 10 16 , and 10 17 ions/cm 2 ) and two temperatures (300 °C and 500 °C). The $d_{33}$ for the six irradiated samples and one pristine sample were measured, and the measurement uncertainty was estimated based on five repeated tests. All samples were also measured by a commercial piezometer for comparison. The experimental results demonstrate that the piezoelectric coefficients obtained by LDV were about 0.8–1.16 pm/V lower than those obtained by the piezometer. With the compensation of the clamping effect, the corrected LDV values are similar to the piezometer results. Both show similar trends in all samples, which validates the feasibility of the proposed method for $d_{33}$ measurement. Based on the LDV results, the irradiated samples show a 12%–22% decrease in $d_{33}$ compared with the pristine samples. The samples irradiated under the same fluence at a higher temperature (500 °C) demonstrated a lower $d_{33}$ than those at 300 °C. The effect of the retro-reflective tape, sample temperature, and sample size on the $d_{33}$ measurement were also studied.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Sample spinning to mitigate polarization artifact and interstitial-vacancy imbalance in ion-beam irradiation

Accelerator-based ion-beam irradiation has been widely used to mimic the effects of neutron radiation damage in nuclear reactors. However, ion radiation is most often monodisperse in the incoming ions’ momentum direction, leading to excessive polarization in defect distribution, while the scattering under neutron irradiation is often more isotropic and has less radiation-induced polarization. Mitigation of the excess-polarization as well as the damage non-uniformity artifact might be crucial for making the simulation of neutron radiation by ion-beam radiation more realistic. In this work, a general radiation polarization theory in treating radiation as external polar stimuli is established to understand the natural material responses in different contexts, and the possibility to correct the defect polarization artifact in ion-beam irradiation. Inspired by Magic Angle Spinning in Nuclear Magnetic Resonance, we present a precise sample spinning strategy to reduce the point-defect imbalance effect in ion-beam irradiation. It can be seen that with optimized surface inclination angle and the axis of sample rotation, the vacancy-interstitial population imbalance, as well as the damage profile non-uniformity in a designated region in the target are both reduced. It is estimated that sample spinning frequency on the order of kHz should be sufficient to scramble the ion momentum monodispersity for commonly taken ion fluxes and dose rates, which is experimentally feasible.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Forecasting fluid-injection induced seismicity to choose the best injection strategy for safety and efficiency

Induced seismicity poses a challenge to the development of Enhanced Geothermal Systems (EGS). Improving monitoring and forecasting techniques is essential to mitigate induced seismicity and thereby fostering a positive perception of EGS projects among local authorities and population. Induced seismicity is the result of complex and coupled thermo-hydro-mechanical-chemical mechanisms. Injection flux and pressure are crucial controlling parameters for both hydraulic stimulation and circulation protocols. We develop a methodology combining a hydro-mechanical model with a seismicity rate model to estimate the magnitude and frequency of mainshocks and aftershocks induced by fluid injection. We apply the methodology to the case of the Basel EGS (2006, Switzerland) to compare the effects of progressive, cyclic and constant injections on the mechanical response of discrete faults. Results from the coupled hydro-mechanical models show that the pore pressure diffusion and consequent enhancement of fault permeability are limited to the vicinity of the injection well during cyclic injection. Additionally, constant injection induces seismicity from the start of the injection but enhances the permeability of most of the faults within a shorter duration, inducing less post-injection seismicity. The methodology can be adapted to any numerical model and allows new projects to be developed by anticipating the safest injection protocol. This article is part of the theme issue ‘Induced seismicity in coupled subsurface systems’.

58 GEOSCIENCES↗
DOE OSTI2022

Autonomous Wireless Technology Detection in Seamless IoT Applications

The ever-increasing use of Internet of Things (IoT) devices results in the implementation of multiple wireless technologies that would not only cater their data rate requirements but also support various applications. To optimize the energy efficiency and security of the wireless transmission, it is imperative to identify the wireless technologies in various IoT implementations. Many of the existing approaches are based on measuring only the receiving signal strength indicator (RSSI). However, such approaches may not work well because of transmit power control and complex channel variations among different wireless technologies. In this article, we propose an autonomous wireless detection scheme that considers multiple distinguishable physical (PHY)-layer settings for real-time identification of wireless technologies for real-time applications. Specifically, the proposed scheme relies on the PHY-layer measurements of the targeted spectrum. Transmission settings, such as bandwidth, carrier frequency, and RSSI are estimated from the raw in-phase and quadrature-phase (I/Q) measurements. In addition, a symbol-level extraction scheme is implemented to extract unique features of modulation settings. These aforementioned features are applied to a machine learning process to identify the received wireless technologies. Compared with raw I/Q measurements, the extracted features are much simplified and, thus, the machine learning classifier can be designed with a simple structure for fast processing on IoT nodes. Finally, the proposed schemes are primarily evaluated theoretically, followed by implementing them on a USRP software-defined radio (SDR)-based hardware testbed. The evaluation results demonstrate high accuracy in the real-time detection of different wireless technologies for seamless IoT applications.

42 ENGINEERING↗
DOE OSTI2024

Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks - 2024 Annual Workshop Presentation

This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to estimate the magnitude-frequency response of stimulation-induced seismicity. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 15, 2024.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Rapid attribution analysis of the extraordinary heat wave on the Pacific coast of the US and Canada in June 2021

Towards the end of June 2021, temperature records were broken by several degrees Celsius in several cities in the Pacific Northwest areas of the US and Canada, leading to spikes in sudden deaths and sharp increases in emergency calls and hospital visits for heat-related illnesses. Here we present a multi-model, multi-method attribution analysis to investigate the extent to which human-induced climate change has influenced the probability and intensity of extreme heat waves in this region. Based on observations, modelling and a classical statistical approach, the occurrence of a heat wave defined as the maximum daily temperature (TXx) observed in the area 45–52 °N, 119–123 °W, was found to be virtually impossible without human-caused climate change. The observed temperatures were so extreme that they lay far outside the range of historical temperature observations. This makes it hard to state with confidence how rare the event was. Using a statistical analysis that assumes that the heat wave is part of the same distribution as previous heat waves in this region led to a first-order estimation of the event frequency of the order of once in 1000 years under current climate conditions. Using this assumption and combining the results from the analysis of climate models and weather observations, we found that such a heat wave event would be at least 150 times less common without human-induced climate change. Also, this heat wave was about 2 °C hotter than a 1-in-1000-year heat wave would have been in 1850–1900, when global mean temperatures were 1.2 °C cooler than today. Looking into the future, in a world with 2 °C of global warming (0.8 °C warmer than today), a 1000-year event would be another degree hotter. Our results provide a strong warning: our rapidly warming climate is bringing us into uncharted territory with significant consequences for health, well-being and livelihoods. Adaptation and mitigation are urgently needed to prepare societies for a very different future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Short communication: Cosmogenic noble gas depletion in soils by wildfire heating

Measurements of cosmic-ray-produced beryllium-10, neon-21, and helium-3 in quartz in a soil profile from a forested landscape in the Oregon Coast Range show that the cosmogenic noble gases 21 Ne and 3 He are depleted relative to 10Be in the shallow subsurface. The noble gases are mobile in mineral grains via thermally activated diffusion and 10 Be is not, implying that noble gas depletion is the result of surface heating by wildfires and subsequent mixing of partially degassed quartz downward into the soil. Cosmogenic noble gas depletion by wildfire heating of soils is a potential means of estimating wildfire intensity and/or frequency over pre-observational timescales.

58 GEOSCIENCES↗
DOE OSTI2025

Resonant shattering flares as asteroseismic tests of chiral effective field theory

Chiral effective field theory (𝜒⁢EFT) has proved to be a powerful microscopic framework for predicting the properties of neutron-rich nuclear matter with quantified theoretical uncertainties up to about twice the nuclear saturation density. Tests of 𝜒⁢EFT predictions are typically performed at low densities using nuclear experiments, with neutron star (NS) constraints only being considered at high densities. In this work, we discuss how asteroseismic quasinormal modes within NSs could be used to constrain specific matter properties at particular densities not just the integrated quantities to which bulk NS observables are sensitive. We focus on the crust-core interface mode, showing that measuring this mode's frequency would provide a meaningful test of 𝜒⁢EFT at densities around half the saturation density. Conversely, we use nuclear matter properties predicted by 𝜒⁢EFT to estimate that this mode's frequency is around 185 ± 50Hz. Asteroseismic observables such as resonant phase shifts in gravitational-wave signals and multimessenger resonant shattering flare timings, therefore, have the potential to provide useful tests of 𝜒⁢EFT.

effective field theory↗