Search NASA⌕ Search

SEARCH · Search NASA

Results for “MITIGATION STRATEGIES”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The detection of marine microseismic activity with the CUORE tonne-scale cryogenic experiment

Vibrations from experimental setups and the environment are a persistent source of noise for low-temperature calorimeters searching for rare events, including neutrinoless double beta ( 0νββ ) decay or dark matter interactions. Such noise can significantly limit experimental sensitivity to the physics case under investigation. Here, we report the detection of marine microseismic vibrations using mK-scale calorimeters. This study employs a multi-device analysis correlating data from CUORE, the leading experiment in the search for 0νββ decay with mK-scale calorimeters, and the Copernicus Earth Observation program, revealing the seasonal impact of Mediterranean Sea activity on CUORE’s energy thresholds, resolution, and sensitivity over four years. The detection of marine microseisms underscores the need to address faint environmental noise in ultra-sensitive experiments. Understanding how such noise couples to the detector and developing mitigation strategies is essential for next-generation experiments. We demonstrate one such strategy: a noise decorrelation algorithm implemented in CUORE using auxiliary sensors, which reduces vibrational noise and improves detector performance. Enhancing sensitivity to 0νββ decay and to rare events with low-energy signatures requires identifying unresolved noise sources, advancing noise reduction methods, and improving vibration suppression systems, all of which inform the design of next-generation rare event experiments.

experimental nuclear physics↗
DOE OSTI2025

Enhanced flood synchrony and downstream severity in the Delaware River under rising temperatures

River floods threaten life and economic stability, with risks increasing globally, especially in densely populated coastal areas. In mountainous coastal watersheds like the Delaware River Basin, rising temperature is projected to reduce snowpack, reshaping upstream–downstream flood dynamics. However, the impact on flood synchronization between upland tributaries and estuarine mainstems remains poorly understood. Using multidecadal streamflow simulations from a high-resolution hydrological model, we find significant increases in the frequency and magnitude of synchronized floods under future warming scenarios, particularly severe floods (above the 75 th percentile). Under higher warming scenarios, snowpack and rain-on-snow floods in headwater subbasins nearly vanish. Surprisingly, this regime shift amplifies estuarine flooding by enhancing synchronization between historically snow-dominated subbasins and their downstream counterparts. Despite intensified synchronization and flood magnitude, cold-season flood risk declines due to fewer rain-on-snow events. Conversely, summer floods grow larger, more frequent, and synchronized, driving a seasonal reconfiguration of flood risk that should be considered in future mitigation strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Deep learning forecasts the spatiotemporal evolution of fluid-induced microearthquakes

Microearthquakes generated by subsurface fluid injection record the evolving stress state and permeability of reservoirs. Forecasting their spatiotemporal evolution is therefore critical for applications such as enhanced geothermal systems, carbon dioxide sequestration and other geoengineering applications. Here we propose a transformer neural network model that ingests hydraulic stimulation history and prior microearthquake observations to forecast four key quantities: cumulative microearthquake count, cumulative logarithmic seismic moment, and the 50th- and 95th-percentile extents of the microearthquake cloud. Applied to the EGS Collab Experiment 1 dataset, the model achieves R2 > 0.98 for the 1-s forecast horizon and R2 > 0.88 for the 15-s forecast horizon across all targets, and supplies uncertainty estimates through a learned standard deviation term. These accurate, uncertainty-quantified forecasts enable real-time inference of fracture propagation and permeability evolution, demonstrating the strong potential of deep-learning approaches to improve seismic-risk assessment and guide mitigation strategies in future fluid-injection operations.

Chung, Jaehong↗
DOE OSTI2023

Sulfate reduction accelerates groundwater arsenic contamination even in aquifers with abundant iron oxides

Groundwater contamination by geogenic arsenic is a global problem affecting nearly 200 million people. In South and Southeast Asia, a cost-effective mitigation strategy is to use oxidized low-arsenic aquifers rather than reduced high-arsenic aquifers. Aquifers with abundant oxidized iron minerals are presumably safeguarded against immediate arsenic contamination, due to strong sorption of arsenic onto iron minerals. However, preferential pumping of low-arsenic aquifers can destabilize the boundaries between these aquifers, pulling high-arsenic water into low-arsenic aquifers. We investigate this scenario in a hybrid field-column experiment in Bangladesh where naturally high-arsenic groundwater is pumped through sediment cores from a low-arsenic aquifer, and detailed aqueous and solid-phase measurements are used to constrain reactive transport modelling. Here we show that elevated groundwater arsenic concentrations are induced by sulfate reduction and the predicted formation of highly mobile, poorly sorbing thioarsenic species. Furthermore, this process suggests that contamination of currently pristine aquifers with arsenic can occur up to over 1.5 times faster than previously thought, leading to a deterioration of urgently needed water resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Wildfire and power grid nexus in a changing climate

Global wildfire events have had increasingly severe impacts in recent years, particularly in the western USA, driven by extreme fire-weather conditions, fuel accumulation and multiple ignition sources. Wildfires sparked by power lines tend to be larger and more destructive, as they often occur during high winds, which accelerate the spread of fires. Moreover, efforts to contain wildfires frequently result in power outages, causing considerable economic disruption. Here, in this Review, we examine wildfire risks related to power-line-induced ignitions, infrastructure damage, climate-induced environmental impacts, grid operational risks, real-time grid management risks, vegetation management risks, and financial and funding risks in the context of a changing climate and their interdependence with power grid infrastructures. We then explore the resilience of power grids under wildfire threats, looking at risk analysis, prediction and mitigation strategies. The Review also shares practical insights and experiences in the USA to inform researchers, policymakers and industry professionals.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site

Carbon dioxide (CO2) storage into geological formations is regarded as an important mitigation strategy for anthropogenic CO2 emissions to the atmosphere. This study first simulates the leakage of CO2 and brine from a storage reservoir through the caprock. Then, we estimate the resulting pressure changes at the zone overlying the caprock also known as Above Zone Monitoring Interval (AZMI). A data-driven approach of arbitrary Polynomial Chaos (aPC) Expansion is then used to quantify the uncertainty in the above zone pressure prediction based on the uncertainties in different geologic parameters. Finally, a global sensitivity analysis is performed with Sobol indices based on the aPC technique to determine the relative importance of different parameters on pressure prediction. The results indicate that there can be uncertainty in pressure prediction locally around the leakage zones. The degree of such uncertainty in prediction depends on the quality of site specific information available for analysis. The scientific results from this study provide substantial insight that there is a need for site-specific data for efficient predictions of risks associated with storage activities. The presented approach can provide a basis of optimized pressure based monitoring network design at carbon storage sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Heteropoly acid functionalized fluoroelastomer with outstanding chemical durability and performance for vehicular fuel cells

To further facilitate commercialization of automotive fuel cells, durability concerns need to be addressed. Currently the addition of a mechanical support in the membrane is able to adequately solve issues of mechanical degradation, but chemical degradation via oxygenated radical attack remains an unsolved challenge. Typical mitigation strategies use cerium or manganese species to serve as radical scavengers, but these ions are able to migrate in the membrane and even leach out of the system. The approach used in this paper is to covalently link and immobilize a heteropoly acid (HPA), more specifically 11-silicotungstic acid (HSiW11), a lacunary HPA of the Keggin structure to a fluoroelastomer, serving as both a radical decomposition catalyst and the proton conducting acid. This dual functionality allows for both high content of radical scavenging species and high ion-exchange capacity. An efficient three step, high yield (77%), commercially viable synthesis for this polymer is reported. The synthesis route for making this new heteropoly acid functionalized polymer is confirmed using infrared spectroscopy (IR), nuclear magnetic resonance (NMR) spectroscopy, and thermogravimetric analysis (TGA). The material exhibits clustering of the HSiW11 moieties, resulting in a poorly connected proton conducting phase when dry, but excellent conductivity is achieved at elevated humidities (0.298 S cm -1 at 80 °C and 95% RH). The proton conductivity shows an enhancement above 60 °C due to a softening of the polymer, as shown by DSC. Under an aggressive chemical accelerated stress test (AST), 90 °C, 30% RH, zero current, and pure O 2 , the PolyHPA losses only 0.05 V of open circuit voltage (OCV) after 500 h, greatly out performing any other material reported in the literature. For comparison, the Nafion® N211 fuel cell drops below 0.8 V after only 76 h under the same conditions. Finally, in fuel cell testing the PolyHPAs have outstanding chemical stability and also possess very low in situ high frequency resistance (HFR) leading to high performance (1.14 W cm -2 at 2 A cm -2 ), compared to 1.11 W cm -2 for the Nafion® N211 fuel cell at the same current. At 75 wt% HSiW11 loading, the fuel cell HFR showed a 22% decrease over N211.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Challenges and opportunities for adsorption-based CO 2 capture from natural gas combined cycle emissions

In recent years, the power sector has shown a growing reliance on natural gas, a cleaner-burning fuel than coal that emits approximately half as much CO 2 per kW h of energy produced. This rapid growth in the consumption of natural gas has led to increased CO 2 emissions from gas-fired power plants. To limit the contribution of fossil fuel combustion to atmospheric CO 2 levels, carbon capture and sequestration has been proposed as a potential emission mitigation strategy. However, despite extensive exploration of solid adsorbents for CO 2 capture, few studies have examined the performance of adsorbents in post-combustion capture processes specific to natural gas flue emissions. In this perspective, we emphasize the importance of considering gas-fired power plants alongside coal-fired plants in future analyses of carbon capture materials. We address specific challenges and opportunities related to adsorptive carbon capture from the emissions of gas-fired plants and discuss several promising candidate materials. Lastly, we suggest experiments to determine the viability of new CO 2 capture materials for this separation. This broadening in the scope of current carbon capture research is urgently needed to accelerate the deployment of transformational carbon capture technologies.

03 NATURAL GAS↗
DOE OSTI2024

Delocalization error poisons the density-functional many-body expansion

The many-body expansion is a fragment-based approach to large-scale quantum chemistry that partitions a single monolithic calculation into manageable subsystems. This technique is increasingly being used as a basis for fitting classical force fields to electronic structure data, especially for water and aqueous ions, and for machine learning. Here, we show that the many-body expansion based on semilocal density functional theory affords wild oscillations and runaway error accumulation for ion–water interactions, typified by F − (H 2 O) N with N ≳ 15. We attribute these oscillations to self-interaction error in the density-functional approximation. The effect is minor or negligible in small water clusters, explaining why it has not been noticed previously, but grows to catastrophic proportion in clusters that are only moderately larger. This behavior can be counteracted with hybrid functionals but only if the fraction of exact exchange is ≳50%, whereas modern meta-generalized gradient approximations including ωB97X-V, SCAN, and SCAN0 are insufficient to eliminate divergent behavior. Other mitigation strategies including counterpoise correction, density correction (i.e., exchange–correlation functionals evaluated atop Hartree–Fock densities), and dielectric continuum boundary conditions do little to curtail the problematic oscillations. In contrast, energy-based screening to cull unimportant subsystems can successfully forestall divergent behavior. These results suggest that extreme caution is warranted when the many-body expansion is combined with density functional theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Analysis of thermochemical energy storage in metal carbonates: characterizing cycling-induced degradation

A solid–gas reaction rate modeling framework is applied to characterize degradation in thermochemical materials induced by thermal cycling. Time constants and a kinetic conversion ratio are established for a representative carbonation-calcination reaction, which provides insight into degradation mechanisms and reveals a mitigation strategy by tuning reaction duration.

25 ENERGY STORAGE↗
DOE OSTI2026

Effect of externally applied pressure on rechargeable alkaline zinc batteries at limited depth of discharge

Rechargeable alkaline zinc batteries (AZBs) are being actively researched for grid-scale energy storage due to their safety, low toxicity, abundance, low cost, and ease-of-production. However, numerous studies on alkaline Zn–MnO 2 batteries have shown that issues such as heterogeneous Zn deposition, passivation, dendrite formation, hydrogen evolution, and formation of chemically irreversible byproducts on the electrode surfaces still limit their rechargeability. Several mitigating strategies have been proposed to improve the rechargeability of alkaline Zn–MnO 2 batteries, but the effect of pressure on electrochemical behavior has not been systematically investigated. In this paper, we demonstrate that an externally applied pressure at 20% MnO 2 depth-of-discharge (DOD MnO 2 ) has a profound effect on impedance, electrochemical cycling behavior, and materials morphology of alkaline Zn–MnO 2 batteries. Better electrochemical performance and improved morphology were achieved at 2.12 MPa pressure compared to 0.05 MPa pressure. Moreover, we examined the effect of externally applied pressure from 0 to 5.05 MPa before cycling and found that charge transfer resistance decreases significantly with pressure. Furthermore, we reported stable electrochemical cycling of MnO 2 ‖MnO 2 symmetric cells for 500 hours at 20% DOD under 2.12 MPa pressure. In conclusion, our efforts in understanding the effect of pressure could help design high performance and durable rechargeable alkaline Zn–MnO 2 batteries for grid-scale energy storage.

Rechargeable alkaline batteries↗
DOE OSTI2024

A graph embedding‐based approach for automatic cyber‐physical power system risk assessment to prevent and mitigate threats at scale

Abstract Power systems are facing an increasing number of cyber incidents, potentially leading to damaging consequences to both physical and cyber aspects. However, the development of analytical methods for the study of large‐scale power infrastructures as cyber‐physical systems is still in its early stages. Drawing inspiration from machine‐learning techniques, the authors introduce a method inspired by the principles of graph embedding that is tailored for quantitative risk assessment and the exploration of possible mitigation strategies of large‐scale cyber‐physical power systems. The primary advantage of the graph embedding approach lies in its ability to generate numerous random walks on a graph, simulating potential access paths. Meanwhile, it enables capturing high‐dimensional structures in low‐dimensional spaces, facilitating advanced machine‐learning applications, and ensuring scalability and adaptability for comprehensive network analysis. By employing this graph embedding‐based approach, the authors present a structured and methodical framework for risk assessment in cyber‐physical systems. The proposed graph embedding‐based risk analysis framework aims to provide a more insightful perspective on cyber‐physical risk assessment and situation awareness for power systems. To validate and demonstrate its applicability, the method has been tested on two cyber‐physical power system models: the Western System Coordinating Council (WSCC) 9‐Bus System and the Illinois 200‐Bus System , thereby showing its advantages in enhancing the accuracy of risk analysis and comprehensiveness of situational awareness.

Sun, Shining↗
DOE OSTI2024

Photovoltaic inverter-based quantification of snow conditions and power loss

Snow is a significant challenge for photovoltaic (PV) systems at northern latitudes, where the pace of deployment is rapid but snow-related power losses can exceed 30% of annual production. Accurate snow-related power loss estimation methods for utility-scale sites can support snow mitigation strategies, inform resource planning and validate predictive snow-loss models. This study builds on our previous work on inverter-based detection of snow, and its implications for utility-scale power production, by validating the accuracy of our snow-loss method across different PV sites and system designs and highlighting its value in bringing greater visibility to PV plant operations in winter. Our estimation method is both novel and scalable, requiring only standard monitoring data to correlate snow-related losses with meteorological data. As demonstrated here, our validation method involved three main steps: 1) estimation of performance losses for multiple systems by comparing measured inverter data to modeled data; 2) application of a detection framework to identify which performance losses are snow-related; and 3) comparison of snow-related losses among three utility-scale sites differing in tilt angle. Results show that utility-scale systems at higher tilt angles consistently shed snow more quickly/completely than their lower-tilt counterparts. Further, monthly and seasonal snow losses are inversely and non-linearly correlated with tilt angle when normalized for cumulative snowfall. These results are consistent with the findings of previous studies and support the broad applicability of this method to fixed-tilt utility-scale PV systems around the world that routinely experience snow-related performance losses.

Cooper, Emma C. (ORCID:0000000190554098)↗
DOE OSTI2013

Challenges and opportunities for multi-functional oxide thin films for voltage tunable radio frequency/microwave components

There has been significant progress on the fundamental science and technological applications of complex oxides and multiferroics. Among complex oxide thin films, barium strontium titanate (BST) has become the material of choice for room-temperature-based voltage-tunable dielectric thin films, due to its large dielectric tunability and low microwave loss at room temperature. BST thin film varactor technology based reconfigurable radio frequency (RF)/microwave components have been demonstrated with the potential to lower the size, weight, and power needs of a future generation of communication and radar systems. Low-power multiferroic devices have also been recently demonstrated. Strong magneto-electric coupling has also been demonstrated in different multiferroic heterostructures, which show giant voltage control of the ferromagnetic resonance frequency of more than two octaves. This manuscript reviews recent advances in the processing, and application development for the complex oxides and multiferroics, with the focus on voltage tunable RF/microwave components. The over-arching goal of this review is to provide a synopsis of the current state-of the-art of complex oxide and multiferroic thin film materials and devices, identify technical issues and technical challenges that need to be overcome for successful insertion of the technology for both military and commercial applications, and provide mitigation strategies to address these technical challenges.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Invited Article: Characterization of background sources in space-based time-of-flight mass spectrometers

For instruments that use time-of-flight techniques to measure space plasma, there are common sources of background signals that evidence themselves in the data. The background from these sources may increase the complexity of data analysis and reduce the signal-to-noise response of the instrument, thereby diminishing the science value or usefulness of the data. This paper reviews several sources of background commonly found in time-of-flight mass spectrometers and illustrates their effect in actual data using examples from ACE-SWICS and MESSENGER-FIPS. Sources include penetrating particles and radiation, UV photons, energy straggling and angular scattering, electron stimulated desorption of ions, ion-induced electron emission, accidental coincidence events, and noise signatures from instrument electronics. Data signatures of these sources are shown, as well as mitigation strategies and design considerations for future instruments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Magnetohydrodynamic actuation of droplets for millimetric planar fluidic systems

In this work, a magnetohydrodynamic method is proposed for the actuation of droplets in small-scale planar fluidic systems, providing an alternative to commonly used methods such as electrowetting-on-dielectric. Elementary droplet-based operations, including transport, merging, and mixing, are demonstrated. The forces acting on millimetric droplets are carefully investigated, with a primary focus on the magnetic actuation force and on the unbalanced capillary forces that arise due to hysteresis. A super-hydrophobic channel is 3D printed to guide the droplets, with thin wires installed as contact electrodes and permanent magnets providing a static magnetic field. It is shown that droplet motion is enhanced by increasing the droplet size and minimizing the electrode contact surface. The effects of channel geometry on threshold voltage and minimum moveable droplet volume are characterized. Finally, the presence of electrolysis is investigated and mitigating strategies are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Development of an inertial confinement fusion platform to study charged-particle-producing nuclear reactions relevant to nuclear astrophysics

Here, this paper describes the development of a platform to study astrophysically relevant nuclear reactions using inertial-confinement fusion implosions on the OMEGA and National Ignition Facility laser facilities, with a particular focus on optimizing the implosions to study charged-particle- producing reactions. Primary requirements on the platform are high yield, for high statistics in the fusion product measurements, combined with low areal density, to allow the charged fusion products to escape. This is optimally achieved with direct-drive exploding pusher implosions using thin-glass-shell capsules. Mitigation strategies to eliminate a possible target sheath potential which would accelerate the emitted ions are discussed. The potential impact of kinetic effects on the implosions is also considered. The platform is initially employed to study the complementary T(t,2n)α, T( 3 He,np)α and 3 He( 3 He,2p)α reactions. Proof-of-principle results from the first experiments demonstrating the ability to accurately measure the energy and yields of charged particles are presented. Lessons learned from these experiments will be used in studies of other reactions. Ultimately, the goals are to explore thermonuclear reaction rates and fundamental nuclear physics in stellarlike plasma environments, and to push this new frontier of nuclear astrophysics into unique regimes not reachable through existing platforms, with thermal ion velocity distributions, plasma screening, and low reactant energies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Constraining radon backgrounds in LZ

The LZ dark matter detector, like many other rare-event searches, will suffer from backgrounds due to the radioactive decay of radon daughters. In order to achieve its science goals, the concentration of radon within the xenon should not exceed 2 μBq/kg, or 20 mBq total within its 10 tonnes. The LZ collaboration is in the midst of a program to screen all significant components in contact with the xenon. The four institutions involved in this effort have begun sharing two cross-calibration sources to ensure consistent measurement results across multiple distinct devices. We present here five preliminary screening results, some mitigation strategies that will reduce the amount of radon produced by the most problematic components, and a summary of the current estimate of radon emanation throughout the detector. This best estimate totals < 17.3 mBq, sufficiently low to meet the detector's science goals.

Miller, E. H.↗