Search NASA⌕ Search

SEARCH · Search NASA

Results for “energy disruption”

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 37 records · Page 2

On the energy budget in the current disruption region

This study investigates the energy budget in the current disruption region of the magnetotail, coincident with a pre-onset thin current sheet, around substorm onset time using published observational data and theoretical estimates. We find that the current disruption/dipolarization process typically requires energy inflow into the primary disruption region. The disruption dipolarization process is therefore endoenergetic, i.e., requires energy input to operate. Therefore we argue that some other simultaneously operating process, possibly a large scale magnetotail instability, is required to provide the necessary energy input into the current disruption region.

Hesse, Michael↗

Measurement of post-disruption runaway electron kinetic energy and pitch angle during final loss instability in DIII-D

Post-disruption runaway electron (RE) kinetic energy K and pitch angle sin$\vartheta$ are critical parameters for determining resulting first wall material damage during wall strikes, but are very challenging to measure experimentally. During the final loss instability, confined RE K and sin$\vartheta$ are reconstructed during center-post wall strikes for both high impurity (high-Z) and low impurity (low-Z) plasmas by combining soft x-ray, hard x-ray, synchrotron emission, and total radiated power measurements. Deconfined (wall impacting) RE sin$\vartheta$ is then reconstructed for these shots by using time-decay analysis of infra-red imaging. Additionally, deconfined RE K and sin$\vartheta$ are reconstructed for a low-Z downward loss shot by analyzing resulting damage to a sacrificial graphite dome limiter. The damage analysis uses multi-step modeling simulating plasma instability, RE loss orbits, energy deposition, and finally material expansion (MARS-F, KORC, GEANT-4, and finally COMSOL). Overall, mean kinetic energies are found to be in the range $\langle$$K$$\rangle$ $≈ 3-4$ MeV for confined REs. KORC simulations indicate that the final loss instability process does not change individual RE kinetic energy K. In conclusion, confined RE pitch angles are found to be fairly low initially pre-instability, $\langle$sin$\vartheta$$\rangle$ $≈ 0.1 – 0.2$, but appear to increase roughly 2x, to $\langle$sin$\vartheta$$\rangle$ $≈ 0.3 – 0.4$ for both confined and deconfined REs during instability onset in the low-Z case; this increase is not observed in the high-Z case.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

One-dimensional cloud fluid model for propagating star formation

The aim of this project was to study the propagation of star formation (SF) with a self-consistent deterministic model for the interstellar gas. The questions of under what conditions does star formation propagate in this model and what are the mechanisms of the propagation are explored. Here, researchers used the deterministic Oort-type cloud fluid model of Scalo and Struck-Marcell (1984, also see the review of Struck-Marcell, Scalo and Appleton 1987). This cloud fluid approach includes simple models for the effects of cloud collisional coalescence or disruption, collisional energy dissipation, and cloud disruption and acceleration as the result of young star winds, HII regions and supernovae. An extensive one-zone parameter study is presented in Struck-Marcell and Scalo (1987). To answer the questions above, researchers carried out one-dimensional calculations for an annulus within a galactic disk, like the so-called solar neighborhood of the galactic chemical evolution. In the calculations the left-hand boundary is set equal to the right hand boundary. The calculation is obviously idealized; however, it is computationally convenient to study the first order effects of propagating star formation. The annulus was treated as if it were at rest, i.e., in the local rotating frame. This assumption may remove some interesting effects of a supersonic gas flow, but was necessary to maintain a numerical stability in the annulus. The results on the one-dimensional propagation of SF in the Oort cloud fluid model follow: (1) SF is propagated by means of hydrodynamic waves, which can be generated by external forces or by the pressure generated by local bursts. SF is not effectively propagated via diffusion or variation in cloud interaction rates without corresponding density and velocity changes. (2) The propagation and long-range effects of SF depend on how close the gas density is to the critical threshold value, i.e., on the susceptibility of the medium.

Titus, Timothy N.↗

Pandemic, War, and Global Energy Transitions

The COVID-19 pandemic and Russia’s war on Ukraine have impacted the global economy, including the energy sector. The pandemic caused drastic fluctuations in energy demand, oil price shocks, disruptions in energy supply chains, and hampered energy investments, while the war left the world with energy price hikes and energy security challenges. The long-term impacts of these crises on low-carbon energy transitions and mitigation of climate change are still uncertain but are slowly emerging. This paper analyzes the impacts throughout the energy system, including upstream fuel supply, renewable energy investments, demand for energy services, and implications for energy equity, by reviewing recent studies and consulting experts in the field. We find that both crises initially appeared as opportunities for low-carbon energy transitions: the pandemic by showing the extent of lifestyle and behavioral change in a short period and the role of science-based policy advice, and the war by highlighting the need for greater energy diversification and reliance on local, renewable energy sources. However, the early evidence suggests that policymaking worldwide is focused on short-term, seemingly quicker solutions, such as supporting the incumbent energy industry in the post-pandemic era to save the economy and looking for new fossil fuel supply routes for enhancing energy security following the war. As such, the fossil fuel industry may emerge even stronger after these energy crises creating new lock-ins. This implies that the public sentiment against dependency on fossil fuels may end as a lost opportunity to translate into actions toward climate-friendly energy transitions, without ambitious plans for phasing out such fuels altogether. We propose policy recommendations to overcome these challenges toward achieving resilient and sustainable energy systems, mostly driven by energy services.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Energy burden aware and thermal resilience informed thermal energy storage system planning for disadvantaged communities

Disadvantaged communities often face a disproportionate energy burden because they need to allocate a higher percentage of their income to energy costs. More importantly, climate change-induced extreme weather events, such as heat waves and severe cold snaps, exacerbate these communities’ energy burdens. As a result, low- and medium-income communities are more likely to experience energy supply disruptions, increased health risks, and elevated energy bills because of inadequate thermal insulation and airtightness in their houses. Thermal energy storage (TES) systems, such as large-scale (community-level) geothermal energy storage and small-scale (building-level) phase change material (PCM)–based storage, have a great potential to improve building energy efficiency and to enhance thermal comfort, load shifting, and integration with renewable energy. The objective of this study is to optimally allocate building level PCM-based TES systems at the community level by considering energy equity and extreme weather effects. To this end, we developed an energy burden and thermal resilience–informed TES system planning framework, which includes three modules: (1) a community-level energy burden and thermal resilience assessment module, (2) building-level a TES system integration and assessment module, and (3) a community-level optimal planning module. Case studies were conducted on four disadvantaged communities in Montgomery and Shelby Counties in Tennessee with energy burdens >10% and with high percentages of people of color. The results indicate that this comprehensive planning framework can assist disadvantaged communities in reducing their energy burden and in bolstering their resilience against the adverse effects of climate change.

Shen, Zhenglai↗

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Nonlinear multiobjective and dynamic real-time predictive optimization for optimal operation of baseload power plants under variable renewable energy

Considering the increase of disruptive variable renewable energy penetration into the power grid, this article focuses on the investigation of a multiobjective and dynamic real-time optimization framework to address the cycling of large-scale power plants under renewable penetration. In this framework, a parallelized particle swarm optimization step is first performed to generate feasible initial points. Then, a multiobjective and dynamic real-time optimization formulation generates optimal trajectories. Further, the benefit of predictive capability is investigated for the dynamic component, which introduces the novel nonlinear multiobjective and dynamic real-time predictive optimization approach. Two multiobjective formulations to obtain Pareto front optimal in real time are explored: the modified Tchebycheff-based weighted metric and ϵ-constraint methods. Economic and environmental objectives are considered in this study. A novel topical discussion on the intersection of dynamic real-time optimization with model predictive control is also presented. The developed framework is successfully applied to a baseload coal-fired power plant with postcombustion CO 2 capture. Results indicate that the approach can be deployed for a large-scale system if automatic differentiation, model reduction, and parallelization are adopted to improve computational tractability, with computational improvement up to 120-folds after performing these steps. Finally, market and carbon policies showed an impact on the optimal compromise between the objectives with an additional 63 ton of CO 2 captured under favorable market conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Influence of Slope Breaks on Lava Flow Surface Disruption

Changes in the underlying slope of a lava flow impart a significant fraction of rotational energy beyond the slope break. The eddies, circulation and vortices caused by this rotational energy can disrupt the flow surface, having a significant impact on heat loss and thus the distance the flow can travel. A basic mechanics model is used to compute the rotational energy caused by a slope change. The gain in rotational energy is deposited into an eddy of radius R whose energy is dissipated as it travels downstream. A model of eddy friction with the ambient lava is used to compute the time-rate of energy dissipation. The key parameter of the dissipation rate is shown to be rho R(sup 2/)mu, where ρ is the lava density and mu is the viscosity, which can vary by orders of magnitude for different flows. The potential spatial disruption of the lava flow surface is investigated by introducing steady-state models for the main flow beyond the steepening slope break. One model applies to slow-moving flows with both gravity and pressure as the driving forces. The other model applies to fast-moving, low-viscosity, turbulent flows. These models provide the flow velocity that establishes the downstream transport distance of disrupting eddies before they dissipate. The potential influence of slope breaks is discussed in connection with field studies of lava flows from the 1801 Hualalai and 1823 Keaiwa Kilauea, Hawaii, and 2004 Etna eruptions.

disruption↗

Modelling and experiment to stabilize disruptive tearing modes in the ITER baseline scenario in DIII-D

Abstract The achievement of high gain, stationary conditions in a tokamak scenario aimed at producing fusion energy in the ITER Project is crucial to the demonstration that this form of energy can be used in future reactors to provide cheap and clean energy globally. Disruptions are a challenge for the fusion energy field, in particular for the ‘ITER Baseline Scenario’ (IBS), as reproduced in the DIII-D tokamak. This work shows that a solution has been found for the m = 2/ n = 1 tearing modes that have consistently caused disruptions in the IBS: stable operation down to zero input torque was achieved by modifying the current density profile at the beginning of the pressure flattop and the ELM character later in the discharges, guided by previous results showing that the most likely cause of these instabilities is the current density profile. The coupling between sawteeth, n>2 modes and the 2/1 TMs is shown to not be statistically significant, nor the leading origin for the evolution towards instability. Ideal and resistive MHD modeling provide positive verification that a steeper ‘well’ in the region of the q = 2 rational surface leads to worse ideal stability, higher tearing index Δ’ and lower threshold Δ’ c for resistive instabilities, consistent with the experimental results. This provides confidence that the methods used in this work can be extrapolated to other devices and applied to avoid disruptions in ITER and pulsed fusion devices worldwide.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Technical Resilience Navigator: Risk-Informed Decision Making to Support Resilience Planning

The Technical Resilience Navigator (TRN) helps organizations manage the risk to critical functions at a site from disruptions in energy and water services. Developed in partnership by the Pacific Northwest National Laboratory and the National Renewable Energy Laboratory, under direction and funding from the Department of Energy’s Federal Energy Management Program, the TRN helps organizations enhance their resilience to a variety of disruptive events, both natural and human-caused, that could interrupt normal operations for an unknown period of time. This report provides an overview of the TRN’s risk-informed approach to resilience planning and formally describes how it uses a streamlined risk model to identify effective strategies for improving resilience.

99 GENERAL AND MISCELLANEOUS↗

Roadmap for Solar Photovoltaic (PV) Cybersecurity: A vision for improving cyber maturity of distributed and utility-scale solar energy installations

As the solar energy sector continues to expand, its integration into the broader energy infrastructure presents both unprecedented opportunities and new risks. The increasing reliance on digital technologies and interconnected systems in solar energy creates an expanded attack surface for motivated cyber adversaries. Cyberattacks have the potential to cause disruptions in energy production, damage to equipment, financial losses, and compromises in national security. Therefore, ensuring robust cybersecurity measures is paramount to protect the integrity, availability, confidentiality, and access control of solar energy systems. However, there are still key gaps and challenges to be addressed in industry and research, which stakeholders must race to address as they combat a growing number of real-world cyber incidents that affect solar energy systems and a growing number of vulnerabilities discovered and disclosed in key types of equipment. This roadmap explore the current state of solar PV cybersecurity and the gaps and challenges still to be addressed.

14 - SOLAR ENERGY↗

Resilient Communities, Maryland (RCM): A Framework for Community-Driven Energy Resilience (Final Technical Report)

The Resilient Communities, Maryland (RCM) project integrates community-based participatory research (CBPR) approaches into energy resilience planning. The combination of qualitative, community-driven data and quantitative utility data improves both the effectiveness and efficiency of assessing the impacts of disruptions to energy infrastructure. Centered around a metric of critical services access, RCM created a repeatable framework for evaluating and modeling energy resilience in communities and promoted community engagement, resulting in more equitable stakeholder participation and improved decision-making processes for siting infrastructure to improve community energy resilience.

14 SOLAR ENERGY↗

Strengthening U.S. National Security Through Advanced Energy Innovation

NREL's work in strategic energy security is focused on keeping the United States secure and its citizens safe by applying expertise in advanced energy systems and technologies to prevent energy system disruptions from any source, natural or human. NREL pursues national security objectives by providing partners an accurate understanding of national and international security implications of global energy trends; novel installation, facility, and operational energy solutions; access to NREL R&D capabilities to incorporate advanced energy technologies and biomaterials into mission requirements; and the ability to test future technologies using large-scale grid modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling Systems’ Disruption and Social Acceptance—A Proof-of-Concept Leveraging Reinforcement Learning

As the need for a just and equitable energy transition accelerates, disruptive clean energy technologies are becoming more visible to the public. Clean energy technologies, such as solar photovoltaics and wind power, can substantially contribute to a more sustainable world and have been around for decades. However, the fast pace at which they are projected to be deployed in the United States (US) and the world poses numerous technical and nontechnical challenges, such as in terms of their integration into the electricity grid, public opposition and competition for land use. For instance, as more land-based wind turbines are built across the US, contention risks may become more acute. This article presents a methodology based on reinforcement learning (RL) that minimizes contention risks and maximizes renewable energy production during siting decisions. As a proof-of-concept, the methodology is tested on a case study of wind turbine siting in Illinois during the 2022–2035 period. Results show that using RL halves potential delays due to contention compared to a random decision process. This approach could be further developed to study the acceptance of offshore wind projects or other clean energy technologies.

17 WIND ENERGY↗

CyOTE ASSET OWNER ENGAGEMENT – SIDE CHANNEL POWER ANALYSIS PROTOTYPE

The U.S. Department of Energy’s (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER), through the Cybersecurity for the Operational Technology Environment (CyOTE) Program, worked with energy sector asset owners and operators (AOOs), partners, and Idaho National Laboratory (INL) to develop capabilities for AOOs to independently identify adversarial tactics, techniques, and procedures (TTPs) within their operational technology (OT) environments. The CyOTE methodology seeks to identify adversarial techniques within an AOO OT environment that could result in physical disruptions to energy flow or damage to equipment. CyOTE provides a general roadmap for AOOs, starting from a triggering event, or the point in time and space they perceive an anomalous event or condition meriting investigation, and culminating when the AOO has sufficient confidence to make a business risk decision on the appropriate resolution. This paper outlines the results of one such engagement with the New York Power Authority (NYPA), where the CyOTE program partnered with an AOO to develop a design specification for a power side channel detector to identify anomalous changes to device load. It describes the goal of developing this capability, the development process, the challenges the technical teams faced and the future steps an AOO will need to take to install and use this detector in its OT environment.

99 GENERAL AND MISCELLANEOUS↗

Cell prestress. II. Contribution of microtubules

The tensegrity model hypothesizes that cytoskeleton-based microtubules (MTs) carry compression as they balance a portion of cell contractile stress. To test this hypothesis, we used traction force microscopy to measure traction at the interface of adhering human airway smooth muscle cells and a flexible polyacrylamide gel substrate. The prediction is that if MTs balance a portion of contractile stress, then, upon their disruption, the portion of stress balanced by MTs would shift to the substrate, thereby causing an increase in traction. Measurements were done first in maximally activated cells (10 microM histamine) and then again after MTs had been disrupted (1 microM colchicine). We found that after disruption of MTs, traction increased on average by approximately 13%. Because in activated cells colchicine induced neither an increase in intracellular Ca(2+) nor an increase in myosin light chain phosphorylation as shown previously, we concluded that the observed increase in traction was a result of load shift from MTs to the substrate. In addition, energy stored in the flexible substrate was calculated as work done by traction on the deformation of the substrate. This result was then utilized in an energetic analysis. We assumed that cytoskeleton-based MTs are slender elastic rods supported laterally by intermediate filaments and that MTs buckle as the cell contracts. Using the post-buckling equilibrium theory of Euler struts, we found that energy stored during buckling of MTs was quantitatively consistent with the measured increase in substrate energy after disruption of MTs. This is further evidence supporting the idea that MTs are intracellular compression-bearing elements.

Non-NASA Center↗

Interaction of SPI pellets with plasma on JET and associated disruptions

Abstract The presented data refer to the Shattered Pellet Injector (SPI) experiments carried out at JET in 2019–2020. This paper is a full journal version of the data originally presented as posters at TMPDM_2020 and EPS_2021. This paper presents various aspects of the interaction of pellets with plasma and associated disruptions. The experiment was performed with I p = (1.1–3.1) MA plasmas and mainly with Ne + D 2 pellet composition, but also with Ar pellets. The Current Quench (CQ) time, τ 80−20 , is the key characteristic of mitigation effectiveness. A pellet with a high content of Ne or Ar can reduce the CQ duration below the upper required JET threshold. Plasmas with high (thermal + internal poloidal magnetic) pre-disruptive plasma energy require a high content of Ne pellets to obtain a short CQ duration. Pellets with a small amount of Ne (and accordingly large amount of D), instead of causing a mitigated CQ, create the conditions for a ‘cold’ Vertical Displacement Events (VDE). The SPI was applied to plasma with different status: mainly to normal (‘healthy’) plasma, i.e. not prone to disruption, post-disruptive and VDE plasma. This study shows that SPI effectiveness in terms of CQ duration and, accordingly, EM loads does not depend on the state of the plasma, whether it is ‘healthy’ or post-disruptive plasma. SPI has been shown to reduce the axisymmetric vertical vessel reaction forces by about (30–40) % compared to unmitigated disruptions. On JET, the VDE, whether ‘hot’ or ‘cold’, always creates the conditions for a toroidal asymmetry in the plasma, so the VDE on the JET is referred to as Asymmetric VDE (AVDE). The interrupting of VDE and prevention of AVDE with SPI has been demonstrated. Thus, the effectiveness of disruption mitigation using SPI has been confirmed.

Gerasimov, S. N. (ORCID:0009000237937211)↗