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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Soil microbiome interventions for carbon sequestration and climate mitigation

Mitigating climate change in soil ecosystems involves complex plant and microbial processes regulating carbon pools and flows. Here, we advocate for the use of soil microbiome interventions to help increase soil carbon stocks and curb greenhouse gas emissions from managed soils. Direct interventions include the introduction of microbial strains, consortia, phage, and soil transplants, whereas indirect interventions include managing soil conditions or additives to modulate community composition or its activities. Approaches to increase soil carbon stocks using microbially catalyzed processes include increasing carbon inputs from plants, promoting soil organic matter (SOM) formation, and reducing SOM turnover and production of diverse greenhouse gases. Marginal or degraded soils may provide the greatest opportunities for enhancing global soil carbon stocks. Among the many knowledge gaps in this field, crucial gaps include the processes influencing the transformation of plant-derived soil carbon inputs into SOM and the identity of the microbes and microbial activities impacting this transformation. As a critical step forward, we encourage broadening the current widespread screening of potentially beneficial soil microorganisms to encompass functions relevant to stimulating soil carbon stocks. Moreover, in developing these interventions, we must consider the potential ecological ramifications and uncertainties, such as incurred by the widespread introduction of homogenous inoculants and consortia, and the need for site-specificity given the extreme variation among soil habitats. Incentivization and implementation at large spatial scales could effectively harness increases in soil carbon stocks, helping to mitigate the impacts of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Results From Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation

Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider threat detection and mitigation (ITDM). Advances in artificial neural networks (ANN) provide more robust pathways for capturing, analyzing, and collating disparate data signals into quantitative descriptions of operational workplace patterns. In response, a joint study by Sandia National Laboratories and the University of Texas at Austin explored the effectiveness of commercial artificial neural network (ANN) software to improve ITDM. Overall, this research demonstrates the benefit of learning patterns of organizational behaviors, detecting off-normal (or anomalous) deviations from these patterns, and alerting when certain types, frequencies, or quantities of deviations emerge for improving ITDM. Evaluating nearly 33,000 access control data points and over 1,600 intrusion sensor data points collected over a nearly twelve-month period, this study's results demonstrated the ANN could recognize operational patterns at the Nuclear Engineering Teaching Laboratory (NETL) and detect off-normal behaviors—suggesting that ANNs can be used to support a data-analytic approach to ITDM. Several representative experiments were conducted to further evaluate these conclusions, with the resultant insights supporting collective behavior-based analytical approaches to quantitatively describe insider threat detection and mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Modeling synergistic fuel cell membrane degradation with mitigating effects of cerium

During operation, polymer-electrolyte fuel cells undergo mechanical and chemical degradation, which behave synergistically and lead to accelerated membrane deterioration over time. This study builds upon previous modeling work on mechanical degradation, as described by a pinhole in the membrane, and chemical degradation mitigation by using cerium. By combining these two models, analysis can be carried out on the coupled degradation methods and how the mitigation effects of cerium disrupt the degradation cycle. The model results show how the presence of a pinhole in the membrane changes the distribution of cerium in the cell and modifies chemical degradation rates. In addition, the model shows how cerium affects the rate of pinhole growth by slowing down the rate of change in mechanical properties due to chemical degradation. Finally, the model shows how cerium modifies the mechanical and chemical degradation rates of the membrane under humidity- and voltage-cycling conditions.

Ehlinger, VM↗
DOE OSTI2021

Mitigation of PtCo/C Cathode Catalyst Degradation via Control of Relative Humidity

Maintaining the high performance of proton-exchange membrane fuel cells (PEMFC) over the course of its lifetime is a key enabling factor for its successful commercialization as a primary power source in zero-emission transportation applications. In this context, it is important to mitigate the degradation of PtCo-alloy based cathode catalysts used for oxygen reduction reaction (ORR). PtCo-alloy catalysts exhibit high activity at beginning-of-life (BOL) which tends to decrease during operation due to loss of electrochemical surface area (ECSA) and dissolution-contamination related effects of the Co-alloying component. Here, we demonstrate the use of relative humidity (RH) of the inlet gases as a controllable parameter to mitigate the degradation of PtCo-alloy catalyst degradation. We employ a catalyst-specific voltage cycling accelerated stress test (AST) durability protocol as a function of inlet RH to degrade PtCo catalysts. A series of in situ electrochemical diagnostics and ex situ characterizations have been carried out to investigate the catalyst layer characteristics at end-of-test (EOT). Our results show that at sub-saturated conditions of durability protocol operation, PtCo catalyst sustains higher EOT H 2 /air performance due to better retention of ECSA and smaller impact of Co 2+ dissolution/contamination.

25 ENERGY STORAGE↗
DOE OSTI2025

Mitigating Transition Metal Dissolution from Mn-rich Cathodes: Influence of Processing and Testing Methods

Manganese-rich oxides continue to gain interest with respect to the development of Earth-abundant options for lithium-ion cathodes. Of the unique challenges that hinder the respective performance of various classes of such materials, manganese dissolution still stands as a common theme. The work herein explores Li 3 PO 4 as a robust surface protection layer on a prototypical, Co-free, manganese-rich cathode in the way of a lithium- and manganese-rich oxide. The study highlights the critical importance of synthesis and processing in realizing optimal performance of a given surface treatment by comparing sol-gel and atomic layer deposition methods. Furthermore, cycling protocols are emphasized as a critical factor in adequately gauging the efficacy of surface protection strategies to mitigate manganese dissolution and the subsequent electrochemical consequence. Optimized Li 3 PO 4 coatings coatings on lithium- and manganese-rich cathode particles are shown to greatly mitigate capacity fade, impedance rise, pore/void formation and mechanical damage during long-term cycling.

Mallick, Subhadip [Argonne National Laboratory (AN↗
DOE OSTI2018

Electromagnetic Particle Injector for Fast Time Response Disruption Mitigation in Tokamaks

A novel, rapid time-response, disruption mitigation system referred to as the Electromagnetic Particle Injector (EPI) is described. This method can accurately deliver the radiative payload to the plasma center on a <10 ms time scale, much faster, and deeper, than what can be achieved using conventional methods. The EPI system accelerates a sabot electromagnetically. The sabot is a metallic capsule that can be accelerated to desired velocities by an electromagnetic impeller. At the end of its acceleration, within 2 ms, the sabot will release a radiative payload, which is composed of low-z granules, or a shell pellet containing smaller pellets. The primary advantage of the EPI concept over gas propelled systems is its potential to meet short warning time scales, while accurately delivering the required particle size and materials at the velocities needed for achieving the required penetration depth in high power ITER-scale discharges for thermal and runaway current disruption mitigation. The present experimental tests from a prototype system have demonstrated the acceleration of a 3.2 g sabot to over 150 m/s within 1.5 ms, consistent with the calculations, giving some degree of confidence that larger ITER-scale injector can be developed.

High velocity↗
DOE OSTI2019

Modelling of Ablatant Deposition from Electromagnetically Driven Radiative Pellets for Disruption Mitigation Studies

The Electromagnetic Particle Injector (EPI) concept is advanced through the simulation of ablatant deposition into ITER H-mode discharges with calculations showing penetration past the H-mode pedestal for a range of injection velocities and granule sizes concurrent with the requirements of disruption mitigation. As discharge stored energy increases in future fusion devices such as ITER, control and handling of disruption events becomes a critical issue. An unmitigated disruption could lead to failure of the plasma facing components resulting in financially and politically costly repairs. Methods to facilitate the quench of an unstable high current discharge are required. With the onset warning time for some ITER disruption events estimated to be less than 10 ms, a disruption mitigation system needs to be considered which operates at injection speeds greater than gaseous sound speeds. Such an actuator could then serve as a means to augment presently planned pneumatic injection systems. The EPI uses a rail gun concept whereby a radiative payload is delivered into the discharge by means of the JxB forces generated by an external current pulse, allowing for injection velocities in excess of 1 km/s. The present status of the EPI project is outlined, including the addition of boost magnetic coils. These coils augment the self-generated rail gun magnetic field and thus provide a more efficient acceleration of the payload. The coils and the holder designed to constrain them have been modelled with the ANSYS code to ensure structural integrity through the range of operational coil cu

disruption↗
DOE OSTI2017

Disruption Physics and Mitigation on DIII-D

The contributions of the DIII-D tokamak toward the understanding and control of disruptions are reviewed. Disruptions are found to be deterministic, and the underlying causes of disruption can therefore be predicted and avoided. With sufficiently rapid detection, possible damage from disruptions can be mitigated using an understanding of disruption phenomenology and plasma physics. Regimes of high β are readily available in DIII-D and provide access to relatively high energy density disruptions, despite DIII-D’s moderate magnetic field and size. DIII-D, with all-graphite wall armor and wall conditioning between discharges, has proven highly resilient to the deleterious effects that disruptions can have on plasma operations. Simultaneously, exploitation and adaptation of DIII-D’s extensive core and edge plasma diagnostic set have allowed for unique plasma measurements during disruptions. These measurements have tied into the development of several physical models used to understand aspects of disruptions, such as magnetohydrodynamic growth at the disruption onset, radiation energy balance through the thermal quench, and halo currents during the current quench. Finally, based on this fundamental understanding, DIII-D has developed techniques to mitigate the harmful effects of disruptions by radiative dissipation of the plasma energy and extrapolated these techniques for possible use on larger devices like ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Scalable process for mitigation of laser-damaged potassium dihydrogen phosphate crystal optic surfaces with removal of damaged antireflective coating

Here, we investigate an approach for the recycling of laser-damaged large-aperture deuterated potassium dihydrogen phosphate (DKDP) crystals used for optical switching (KDP) and for frequency conversion (DKDP) in megajoule-class high-power laser systems. The approach consists of micromachining the surface laser damage sites (mitigation), combined with multiple soaks and ultrasonication steps in a coating solvent to remove, synergistically, both the highly adherent machining debris and the laser-damage-affected antireflection coating. We then identify features of the laser-damage-affected coating, such as the “solvent-persistent” coating and the “burned-in” coating, that are difficult to remove by conventional approaches without damaging the surface. We also provide a solution to the erosion problem identified in this work when colloidal coatings are processed during ultrasonication. Finally, we provide a proof of principle of the approach by testing the full process that includes laser damage mitigation of DKDP test parts, coat stripping, reapplication of a new antireflective coat, and a laser damage test demonstrating performance up to at least 12 J/cm 2 at UV wavelengths, which is well above current requirements. Our approach ultimately provides a potential path to a scalable recycling loop for the management of optics in large, high-power laser systems that can reduce cost and extend lifetime of highly valuable and difficult to grow large DKDP crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Dynamic mitigation of EDFA power excursions with machine learning

Dynamic optical networking has promising potential to support the rapidly changing traffic demands in metro and long-haul networks. However, the improvement in dynamicity is hindered by wavelength-dependent power excursions in gain-controlled erbium doped fiber amplifiers (EDFA) when channels change rapidly. We introduce a general approach that leverages machine learning (ML) to characterize and mitigate the power excursions of EDFA systems with different equipment and scales. An ML engine is developed and experimentally validated to show accurate predictions of the power dynamics in cascaded EDFAs. Recommended channel provisioning based on the ML predictions achieves within 1% error of the lowest possible power excursion over 94% of the time. In conclusion, we also showcase significant mitigation of EDFA power excursions in super-channel provisioning when compared to the first-fit wavelength assignment algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Advancing representations of equity and justice in climate mitigation futures

THIS PAPER WAS PRIMARILY COMPLETED PRIOR TO THE AUTHOR JOINING PNNL AND NO DOE FUNDING WAS USED FOR THIS PAPER. In this work, we review how equity and justice issues in global climate mitigation scenarios are addressed within Integrated Assessment Models (IAMs) and propose a new research agenda to strengthen their integration in model development and application. We begin by examining prominent concerns at the science-policy interface. We introduce a typology of equity and justice limitations in climate mitigation scenarios, distinguishing among structural, methodological, and epistemological biases that shape what integrated assessment models can reveal at policy-relevant scales. Reflecting on these concerns, we propose a research agenda that describes new avenues of work and draws together distinct emerging initiatives. This agenda is based on the feasibility and depth of required interventions, from incremental improvements to structural reforms and alternative participatory approaches. Drawing on reflexive insights from integrated assessment practitioners, it addresses the operational challenges of translating justice concepts into metrics, including risks of reductionism, tokenism, and narrow definitions. Underlying this research agenda is a recognition that modeling communities must engage more critically with implicit assumptions in model design and use that have equity and justice implications. Achieving equitable climate futures will require transformative actions that integrate diverse justice concerns, advance sustainable development goals, and confront systemic inequities across both human and ecological dimensions. Although models will never capture all these aspects, they can be significantly enhanced to support more informed discussion and practical application. Our contribution proposes a way forward to achieving this goal.

Pachauri, Shonali↗
DOE OSTI2019

UNDERSTANDING AND MITIGATION OF FIELD EMISSION IN CEBAF SRF LINACS

We present our current understanding of field emission (FE) in two 1.1 GeV continuous wave (CW) superconducting radio frequency (SRF) linacs at CEBAF and its mitigation for improved CEBAF energy reach and operation reliability. We focus on the root causes of FE in operational SRF cavities, including recently installed cavities for CEBAF 12 GeV energy upgrade. We evaluate the effect of initial mitigations implemented since 2016, aimed at reducing generation and transportation of new field emitting particulates. Effects of cavity thermal cycling aimed at abating activation of settled field emitting particulates will be evaluated as well. Remaining issues toward predictable control of field emission in operational SRF cavities will be discussed.

Geng, R.L.↗
DOE OSTI2026

Ion Trapping Studies and Mitigation Strategies for the EIC ERL-Based Strong Hadron Cooler

An Energy Recovery Linac based strong hadron cooler was previously considered for the Electron-Ion Collider. The required electron beam parameters for variable-energy strong hadron cooling place significant constraints on ion trapping and collective effects. This paper presents initial studies of these constraints through a combination of analytical modelling and numerical simulations of ion production, trapping behaviour, and mitigation strategies. A multi-bunch tracking framework based on ELEGANT with the ionEffects module is used to simulate machine operation over millisecond time scales, corresponding to more than 3 × 10^5 electron bunches. The simulations include modelling of ionisation processes together with transverse electron–ion dynamics, allowing the evolution and accumulation of ions to be investigated. Analytical expressions based on Gaussian beam distributions are used to estimate ion trapping conditions and benchmark the simulation results. A bi-periodic bunch spacing scheme is also investigated as a possible mitigation method by detuning the ion oscillation frequency. These studies provide an initial assessment of ion trapping in the strong hadron cooler and demonstrate possible approaches for reducing beam–ion effects.

Bi, R. [Lancaster University, Cockcroft Institute]↗
DOE OSTI2026

Beam loss modeling and mitigation due to intra-beam stripping

Intra-Beam Stripping (IBS) is a critical beam loss mechanism in high-intensity H- linacs and presents a significant limitation to increasing beam power. This work presents a computational framework to evaluate and mitigate IBS-induced beam loss along the Spallation Neutron Source (SNS) LINAC. Our calculation is based on an analytic theory and involves evaluation of a 9D integral using the Monte-Carlo technique. We first benchmarked our calculations against simplified, analytically solvable cases. We then applied our algorithm to Gaussian bunches with a known probability density function (PDF). We next expanded our algorithm to arbitrary bunch distributions using the Neural Spline Flow (NSF) models trained on PyORBIT tracking data. In the future, we plan to validate our algorithm experimentally and apply it to design IBS mitigation strategies.

Nln, Shivam [ORNL]↗
DOE OSTI2024

Mitigation of Safety and Environmental Challenges Posed by Low and Ultra-low GWP Refrigerants

The abatement of safety and environmental burden associated with low and ultra-low Global Warming Potential (GWP) refrigerants is a critical undertaking. As the industry shifts towards more environmentally friendly alternatives, mitigating the potential risks and ensuring safety standards becomes paramount. The adoption of low GWP and ultra-low GWP refrigerants contributes significantly to minimizing the greenhouse gas impact on the environment, aligning with global climate and sustainability goals. However, it is essential to address safety concerns and potential environmental implications associated with the end use of these refrigerants.A method to mitigate the safety risk in a flammable refrigerant based HVACR system is the primary focus of this paper. Advent of A2L and A3 refrigerants as replacements to high GWP refrigerants requires careful handling of leak episodes to lower or eliminate the risk associated with creating flammable mixtures capable of fire/explosion hazard. Solid materials tailored to target the molecule of interest (i.e., refrigerant.) by engineering the microporous structure as well as chemically functionalizing the surface to attract and hold on to the chemical compound being removed from the gas stream was realized. Additionally, a chromatic transformation technique is investigated for rapid on-site analysis of refrigerant blends. Preliminary results demonstrating the feasibility of both of these methods for successful deployment of low-GWP refrigerants are presented.

Cheekatamarla, Praveen↗
DOE OSTI2013

HPNAIDM: The High-Performance Network Anomaly/Intrusion Detection and Mitigation System

Identifying traffic anomalies and attacks rapidly and accurately is critical for large network operators. With the rapid growth of network bandwidth, such as the next generation DOE UltraScience Network, and fast emergence of new attacks/virus/worms, existing network intrusion detection systems (IDS) are insufficient because they: • Are mostly host-based and not scalable to high-performance networks; • Are mostly signature-based and unable to adaptively recognize flow-level unknown attacks; • Cannot differentiate malicious events from the unintentional anomalies. To address these challenges, we proposed and developed a new paradigm called high-performance network anomaly/intrustion detection and mitigation (HPNAIDM) system. The new paradigm is significantly different from existing IDSes with the following features (research thrusts). • Online traffic recording and analysis on high-speed networks; • Online adaptive flow-level anomaly/intrusion detection and mitigation; • Integrated approach for false positive reduction. Our research prototype and evaluation demonstrate that the HPNAIDM system is highly effective and economically feasible. Beyond satisfying the pre-set goals, we even exceed that significantly (see more details in the next section). Overall, our project harvested 23 publications (2 book chapters, 6 journal papers and 15 peer-reviewed conference/workshop papers). Besides, we built a website for technique dissemination, which hosts two system prototype release to the research community. We also filed a patent application and developed strong international and domestic collaborations which span both academia and industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Update on Common-Cause Failure Experience and Mitigation Practices

Experience in other industries has shown that digital technology can provide substantial benefits in terms of performance and reliability. However, the U.S. nuclear power industry has been slow to adopt the technology extensively in its instrumentation and control (I&C) applications because of inhibiting factors such as regulatory uncertainty, insufficient technological experience base, implementation complexity, limited availability of nuclear-qualified products and vendors, and inadequate definition of modernization cost recapture. Although there have been examples of digital technology usage in the nuclear power industry, challenges to the qualification of digital technology for high-integrity nuclear power plant (NPP) applications have severely constrained more widespread progress in achieving the benefits that are possible through the transition to digital. The U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) established the Advanced Sensors and Instrumentation (ASI) technology area under the Nuclear Energy Enabling Technologies (NEET) Program to coordinate the instrumentation and controls (I&C) research across DOE NE and to identify and lead efforts to address common needs. As part of the NEET ASI research program, the Digital Technology Qualification project was established. Under this project, the Oak Ridge National Laboratory (ORNL) is leading the investigation into mitigation of digital common-cause failure (CCF) vulnerabilities for nuclear-qualified applications. This technical report documents updated and expanded findings from research activities by ORNL. Specifically, the report describes CCF experience in the nuclear and nonnuclear industries, identifies the state of the practice for CCF mitigation through key examples, and presents conclusions from the determination of knowledge gaps.

Wood, Richard Thomas↗
DOE OSTI2015

Advanced CO 2 Leakage Mitigation using Engineered Biomineralization Sealing Technologies

This research project addresses one of the goals of the DOE Carbon Sequestration Program (CSP). The CSP core R&D effort is driven by technology and is accomplished through laboratory and pilot scale research aimed at new technologies for greenhouse gas mitigation. Accordingly, this project was directed at developing novel technologies for mitigating unwanted upward leakage of carbon dioxide (CO 2 ) injected into the subsurface as part of carbon capture and storage (CCS) activities. The technology developed by way of this research project is referred to as microbially induced calcite precipitation (MICP).

Spangler, Lee↗