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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mapping and Characterizing the Visual Impacts of the Existing US Wind Turbine Fleet

Visual impacts of wind turbines have been a persistent concern for wind energy development in the United States (US) for decades and remain a major source of project delays and cancellations. Assessments of visual impacts are frequently performed at a local scale for individual projects, but a comprehensive understanding of broader geographic patterns in visual impacts across the US is lacking. This paper presents a visual impact assessment of the existing land-based wind turbine fleet of the contiguous United States (CONUS). The assessment combines geographic information systems and 3D simulation methods to account for key factors driving the visual magnitude of impacts from the installed turbines. The results indicate that, despite the deployment of approximately 70,000 turbines and over 144 gigawatts of land-based wind in the CONUS, the visual impacts are very small when measured as a proportion of land area, population, and sensitive visual resources. Nonetheless, visual impacts are not evenly distributed: people experience a concentrated share in a small number of natural settings, primarily including plains, prairies, and deserts. Finally, we find that although increased density of wind development consistently leads to visual impacts across a greater proportion of land, it does not always lead to impacts to a greater share of the population. These findings suggest that visual impacts from wind energy are generally well-mitigated across the CONUS to date but also highlight the need for a deeper understanding of landscape sensitivity and individual perceptions of wind turbines in the most heavily impacted natural settings.

3D simulation↗
DOE OSTI2025

Multi-device analysis of energy loss duration and pellet penetration with implications for shattered pellet injection in ITER

A robust disruption mitigation system (DMS) requires accurate characterization of key disruption timescales, one of the most notable being the thermal quench (TQ). Recent modeling of shattered pellet injection (SPI) into ITER plasmas, using JOREK and INDEX, suggests long TQ durations (6–10 ms) and slow cold front propagation due to the large plasma size. If validated, these predictions would have an impact on the desired pellet parameters and mitigation strategies for the ITER DMS. To resolve these questions, a database of SPI experiments from several small-to-large sized devices (J-TEXT, KSTAR, AUG, DIII-D, and JET) has been compiled under the auspices of the International Tokamak Physics Activity MHD, disruptions, and control topical group. Analysis of the energy loss duration (proxy for the TQ duration) with machine size is presented for both mixed neon/deuterium (Ne/D) SPI and pure deuterium (D) SPI. Several metrics for the energy loss onset (e.g. soft x-ray signal drop, I p dip, and radiation flash) were considered as the conventional metric, electron cyclotron emission, is often cut-off during SPI. Several scalings with different onset metrics showed an increase in energy loss duration with machine size. The energy loss duration was additionally shown to be a function of the ratio between the number of SPI neon atoms injected and the stored energy. Analysis of the pellet shard position relative to the cold front found that in larger devices, pellets are typically found inboard of the q = 2 surface at the energy loss onset. Lastly, the delay between the pellet shards hitting the q = 2 surface and the energy loss onset was additionally found to increase with machine size. This suggests that the pellet shards in large devices will penetrate faster and further than the cooling front.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Impact of battery cell imbalance on electric vehicle range

Due to manufacturing variation, battery cells often possess heterogeneous characteristics, leading to battery state-of-charge variation in real-time. Since the lowest cell state-of-charge determines the useful life of battery pack, such variation can negatively impact the battery performance and electric vehicles range. Existing research has been focused on control design to mitigate cell imbalance. However, it is yet unclear how much impacts the cell imbalance can have on electric vehicle range. This paper closes this knowledge gap by using a simulation environment consisting of real-world driving speed data, vehicle longitudinal control, propulsion and vehicle dynamics, and cell level battery modeling. In particular, each battery cell is modeled as an equivalent circuit model, and variations among cell parameters are introduced to assess their impact on electric vehicles range and to identify the most influential parameter variations. Simulation results and analysis can be used to assist balancing control design and to benchmark control performance.

25 ENERGY STORAGE↗
DOE OSTI2023

Signal processing to reduce dark noise impact in precision timing

We introduce a technique to mitigate the effects of low frequency noise on precision timing. The example of Dark Count Noise Rate (DCR) in Silicon Photomultipliers (SiPMs) is emphasized. This technique exploits the correlation between time shifts on the leading edge of a signal and the residual slope of the baseline (due to noise) which remains after baseline subtraction. In fast timing applications (such as for Time-of-flight particle ID) the signal arrival time is typically captured on the signal leading edge. The signal risetime is often fixed by the physics of the sensor and input circuit. Then accurate pulse timing can be achieved by correcting a leading edge threshold time (depending on a slope proportional to both the Amplitude and the risetime) to a “constant fraction” time. This compensation for time walk due to amplitude fluctuations breaks down once we introduce interference from low frequency noise on the leading edge. In this paper we demonstrate that an additional measurement of the slope at threshold can be used to correct for this noise jitter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

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↗
DOE OSTI2025

A resource adequacy assessment of correlated wide-area outages in the power grid

As the power grid is undergoing rapid transformations, numerous questions are emerging about its vulnerability to wide-area extreme events (WAEE), which could influence its operations. Relatively few analyses have been conducted to date regarding the impact of correlated outages during WAEEs on the grid’s ability to balance resources with demand. This study addresses this gap by conducting a resource adequacy analysis for a hurricane-inspired WAEE on a 2035 synthetic power grid system for the United States. A sensitivity analysis was also conducted to characterize the relative impact of weather on unserved energy. Our results indicate that although the magnitude and duration of the shortfalls vary depending on weather conditions, persistent shortfalls are observed in some regions. Initial explorations indicate a strong correlation between transmission-constrained regions and regions with persistent shortfalls. Future work could generate empirically-grounded representations for generator outages as well as conduct causal analyses of these shortfalls to improve understanding of drivers as well as possible mitigation strategies. Continued exploration of extreme weather impacts on the grid is important to develop more robust understanding of the reliability and resilience of our power systems, especially as they undergo rapid transformations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Compressive properties of silicone Bouligand structures

Abstract This article presents an examination of silicone, Bouligand lattices in compression. Appearing frequently in biological organisms and manufacturing design, Bouligand structures comprise layers of parallel strands or fibers oriented in a helical fashion. They can exhibit exceptional fracture resistance when composed of rigid or composite materials. The behavior of elastomeric Bouligand structures, however, is less well understood. Additively manufactured (AM) elastomeric lattices have applications in stress mitigation, medical devices, and soft robotics. This article demonstrates that Bouligand structures are a useful addition to the design space of AM elastomers. By adjusting the layer-rotation parameters, lattice stress can increase by more than 300% without altering the porosity. Additionally, we introduce path length metrics that help explain the observed relationship between layer rotation and compression response. Impact statement Additive manufacturing (AM) continues to push the boundary of manufacturable structures and enhance the ability to robustly design for specific properties and behaviors. The more we understand the design space of a novel AM microstructure, the greater its application range. In this article, we describe the mechanical behavior of helicoidal, elastomeric lattices and introduce path length metrics to help explain their stress response. We show that these structures can exhibit a large range of mechanical behaviors in compression, making them well suited for applications such as stress mitigation and impact absorption. Additionally, the path length metrics could become useful design tools and may be applicable to a larger set of cellular structures. These findings expand our ability to rapidly design materials with highly specific and customizable properties to meet the needs of modern engineering challenges. Graphical abstract

Van Meerbeek, I. M. (ORCID:000000021258132X)↗
DOE OSTI2025

Q-Cluster: Quantum Error Mitigation Through Noise-Aware Unsupervised Learning

Quantum error mitigation (QEM) is critical in reducing the impact of noise in the pre-fault-tolerant era, and is expected to complement error correction in fault-tolerant quantum computing (FTQC). In this work, we propose a novel QEM approach, Q-Cluster, that uses unsupervised learning (clustering) to reshape the measured bit-string distribution. Our approach starts with a simplified bit-flip noise model. It first performs clustering on noisy measurement results, i.e., bit-strings, based on the Hamming distance. The centroid of each cluster is calculated using a qubit-wise majority vote. Next, the noisy distribution is adjusted with the clustering outcomes and the bitflip error rates using Bayesian inference. Our simulation results show that Q-Cluster can mitigate high noise rates (up to 40% per qubit) with the simple bit-flip noise model. However, real quantum computers do not fit such a simple noise model. To address the problem, we (a) apply Pauli twirling to tailor the complex noise channels to Pauli errors, and (b) employ a machine learning model, ExtraTrees regressor, to estimate an effective bit-flip error rate using a feature vector consisting of machine calibration data (gate & measurement error rates), circuit features (number of qubits, numbers of different types of gates, etc.) and the shape of the noisy distribution (entropy). Our experimental results show that our proposed Q-Cluster scheme improves the fidelity by a factor of 1.46x, on average, compared to the unmitigated output distribution, for a set of low-entropy benchmarks on five different IBM quantum machines. Our approach outperforms the state-of-art QEM approaches RZNE [28], M3 [24], Hammer [35], and QBEEP [33] by 1.26x,1.29x,1.47x, and 2.65 x, respectively.

42 ENGINEERING↗
DOE OSTI2025

Peening Techniques for Mitigating Chlorine-Induced Stress Corrosion Cracking of Dry Storage Canisters for Nuclear Applications

Fusion-welded austenitic stainless steel (ASS) was predominantly employed to manufacture dry storage canisters (DSCs) for the storage applications of spent nuclear fuel (SNF). However, the ASS weld joints are prone to chloride-induced stress corrosion cracking (CISCC), a critical safety issue in the nuclear industry. DSCs were exposed to a chloride-rich environment during storage, creating CISCC precursors. The CISCC failure leads to nuclear radiation leakage. Therefore, there is a critical need to enhance the CISCC resistance of DSC weld joints using promising repair techniques. This review article encapsulates the current state-of-the-art of peening techniques for mitigating the CISCC in DSCs. More specifically, conventional shot peening (CSP), ultrasonic impact peening (UIP), and laser shock peening (LSP) were elucidated with a focus on CISCC mitigation. The underlying mechanism of CISCC mitigation in each process was summarized. Finally, this review provides recent advances in surface modification techniques, repair techniques, and developments in welding techniques for CISCC mitigation in DSCs.

Chemistry↗
DOE OSTI2024

Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?

Variational Quantum Algorithms (VQAs) are often viewed as the best hope for near-term quantum advantage. However, recent studies have shown that noise can severely limit the trainability of VQAs, e.g., by exponentially flattening the cost landscape and suppressing the magnitudes of cost gradients. Error Mitigation (EM) shows promise in reducing the impact of noise on near-term devices. Thus, it is natural to ask whether EM can improve the trainability of VQAs. In this work, we first show that, for a broad class of EM strategies, exponential cost concentration cannot be resolved without committing exponential resources elsewhere. This class of strategies includes as special cases Zero Noise Extrapolation, Virtual Distillation, Probabilistic Error Cancellation, and Clifford Data Regression. Second, we perform analytical and numerical analysis of these EM protocols, and we find that some of them (e.g., Virtual Distillation) can make it harder to resolve cost function values compared to running no EM at all. As a positive result, we do find numerical evidence that Clifford Data Regression (CDR) can aid the training process in certain settings where cost concentration is not too severe. Our results show that care should be taken in applying EM protocols as they can either worsen or not improve trainability. On the other hand, our positive results for CDR highlight the possibility of engineering error mitigation methods to improve trainability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Air-conditioning adoption and electricity demand highlight climate change mitigation–adaptation tradeoffs

Abstract We elucidate mid-century climate change impacts on electricity demand accounting for endogenous adoption of residential air-conditioning (AC) in affluent, cooler countries in Europe, and in poorer, hotter states in India. By 2050, in a high-warming scenario (SSP585) AC prevalence grows twofold in Europe and fourfold in India, reaching around 40% in both regions. We document a mitigation-adaptation tradeoff: AC expansion reduces daily heat exposures by 150 million and 3.8 billion person degree-days (PDDs), but increases annual electricity demand by 34 TWh and 168 TWh in Europe and India, respectively (corresponding to 2% and 15% of today’s consumption). The increase in adoption and use of AC would result in an additional 130 MMTCO2, of which 120 MMTCO2 in India alone, if the additional electricity generated were produced with today’s power mix. The tradeoff varies geographically and across income groups: a one PDD reduction in heat exposure in Europe versus India necessitates five times more electricity (0.53 kWh vs 0.1 kWh) and two times more emissions (0.16 kgCO $$_2$$ 2 vs 0.09 kgCO $$_2$$ 2 ), on average. The decomposition of demand drivers offers important insights on how such tradeoff can be moderated through policies promoting technology-based and behavioral-based adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Food–energy–water implications of negative emissions technologies in a +1.5 °C future

Scenarios for meeting ambitious climate targets rely on large-scale deployment of negative emissions technologies (NETs), including direct air capture (DAC). However, the tradeoffs between food, water and energy created by deploying different NETs are unclear. Here we show that DAC could provide up to 3 GtCO 2 yr -1 of negative emissions by 2035—equivalent to 7% of 2019 global CO 2 emissions—based on current-day assumptions regarding price and performance. DAC in particular could exacerbate demand for energy and water, yet it would avoid the most severe market-mediated effects of land-use competition from bioenergy with carbon capture and storage and afforestation. This could result in staple food crop prices rising by approximately fivefold relative to 2010 levels in many parts of the Global South, raising equity concerns about the deployment of NETs. Overall, these results highlight that delays in aggressive global mitigation action greatly increase the requirement for DAC to meet climate targets, and correspondingly, energy and water impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of prescribed fire on soil microbial communities in a Southern Appalachian Forest clear-cut

Escalating wildfire frequency and severity, exacerbated by shifting climate patterns, pose significant ecological and economic challenges. Prescribed burns, a common forest management tool, aim to mitigate wildfire risks and protect biodiversity. Nevertheless, understanding the impact of prescribed burns on soil and microbial communities in temperate mixed forests, considering temporal dynamics and slash fuel types, remains crucial. Our study, conducted at the University of Tennessee Forest Resources AgResearch and Education Center in Oak Ridge, TN, employed controlled burns across various treatments, and the findings indicate that low-intensity prescribed burns have none or minimal short-term effects on soil parameters but may alter soil nutrient concentrations, as evidenced by significant changes in porewater acetate, formate, and nitrate concentrations. These burns also induce shifts in microbial community structure and diversity, with Proteobacteria and Acidobacteria increasing significantly post-fire, possibly aiding soil recovery. In contrast, Verrucomicrobia showed a notable decrease over time, and other specific microbial taxa correlated with soil pH, porewater nitrate, ammonium , and phosphate concentrations. Our research contributes to understanding the intricate relationships between prescribed fire, soil dynamics, and microbial responses in temperate mixed forests in the Southern Appalachian Region, which is valuable for informed land management practices in the face of evolving environmental challenges.

Microbiology↗
DOE OSTI2023

Vegetation Management Cost and Maintenance Implications of Different Ground Covers at Utility-Scale Solar Sites

Utility-scale solar photovoltaics (PV) is the largest and fastest-growing sector of the solar energy market, and plays an important role in ensuring that state and local jurisdictions can meet renewable energy targets. Potential adverse environmental impacts of utility-scale solar PV are well-documented, and the effects of diverse mitigation and dual land use strategies under the banner of ’low-impact solar’ are justly receiving more attention; this article seeks to contribute to improving understanding of this topic. Capital costs for different PV configurations are well-documented; however, operation and maintenance (O&M) costs for vegetation management at low-impact utility-scale solar PV sites are not as well-understood, particularly as they compare to costs for sites that use more conventional ground cover practices, such as turfgrass or gravel. After a literature review of different vegetation strategies and O&M cost considerations, we collected data from utility-scale solar PV O&M stakeholders, including site owners/operators, O&M service providers, vegetation maintenance companies, and solar graziers, on costs and activities associated with vegetation management at low-impact, agrivoltaic, and conventional PV sites. In this paper, we perform data analysis to detail the per-activity and total O&M costs for vegetation management at PV sites with different ground covers and management practices, providing the most comprehensive and detailed assessment of PV vegetation O&M costs to date. For the 54 sites included in our analysis, we found that while the per-acre and per-kilowattdc (kWdc) costs for individual activities, such as mowing, trimming, and herbicide application at native or pollinator friendly ground covers, were lower than at turfgrass sites, the total combined vegetation O&M costs were slightly higher; this is presumably because more individual activities are required for the first 3–5 years of vegetation establishment. Qualitative results include recommendations from data providers for site and system design, and ongoing vegetation management operations.

14 SOLAR ENERGY↗
DOE OSTI2025

Explicit Dynamic Impact Analysis of the Building 3525 Packages

The safe transport and handling of radioactive material containers is critical to ensure the protection of personnel, facilities, and the environment. Accidental drops during handling pose a significant hazard, necessitating robust design and analysis to mitigate potential consequences. This study presents an explicit dynamic impact analysis of two container designs, the Baby Sugarman and the Core Conduction Cooldown Test Facility (CCCTF) Tall Boy, used in Building 3525 at Oak Ridge National Laboratory. The analysis employed nonlinear finite element modeling in LS-DYNA to simulate free-fall impacts from a height of 16.5 ft across eight critical orientations. The study evaluated deformation, strain failure, and shielding integrity under these extreme conditions. Results demonstrated that both designs maintain structural integrity, with no breaches or loss of shielding under specified administrative controls. Notably, a maximum shielding loss of 10 lbs was observed during a top-corner drop, highlighting the need to limit drop heights to less than 1 ft for certain orientations. These findings underscore the effectiveness of engineering controls and design measures in preventing containment breaches and ensuring compliance with safety requirements. This work provides a comprehensive methodology for impact analysis, contributing valuable insights to the field of radioactive materials packaging and transportation safety.

Martinez, Oscar [ORNL] (ORCID:0000000181814046)↗
DOE OSTI2022

Tracking the environmental impacts of ecological engineering on coastal wetlands with numerical modeling and remote sensing

Coastal wetlands are the most valuable ecosystems on the earth but facing severe degradation and losses owing to climate change and anthropogenic activities. Many ecological engineering projects (EEP) have been conducted to mitigate the degradation of coastal wetlands. However, the geomorphological impacts of EEP on coastal wetlands have not been well documented. In this study, a method employed a process-based hydrodynamic model and remote sensing (RS) was developed to evaluate the impacts of EEP on the geomorphological change of a prototype Ramsar site. Results demonstrated that RS has great potential in improving the quality of bathymetry data for the numerical model with a decrease of RMSE from 0.52 m to 0.3 m. It also showed good capacity in trend detection of geomorphological change spatially. Results showed the Chongming Dongtan wetland experienced erosion with an annual rate of -0.035 m/yr from 2013 to 2016 after the implementation of EEP. The deposition rate changed significantly in the area within 200 m of the EEP. It is found that the EEP modified the composition of vegetation, sediment transportation, as well as substrate stability, affecting the geomorphological change of coastal wetlands. It is suggested that the EEP with moderate anthropogenic disturbance is a direct and effective way to recover the coastal habitats for waterbirds. However, the modification of the coastal wetland ecosystem by EEP will lead to the potential vulnerability to global climate change. Therefore, how to mitigate the advantages and disadvantages of the EEP is needed to be further studied to find a more sustainable way for coastal management.

geomorphological change, coastal wetlands, Ecologi↗
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

Beneficial effect of surfactant in adsorption/desorption of lignocellulose-degrading enzymes on/from lignin with different structure

Nonionic surfactant Tween 80 is effective in alleviating the adsorption of lignocellulose-degrading enzymes onto lignin. However, the impacts of lignin structural characteristics on this mitigation effect of Tween 80 were still not clear. Herein, effects of Tween 80 on cellulase and xylanase adsorption on different enzymatic residual lignins (ERLs) and poplar samples were investigated. Besides, effects of Tween 80 on desorption of the two enzyme preparations from different ERLs and poplar samples were also evaluated. By adding Tween 80, the inhibition of ERLs to cellulase hydrolysis was offset and the positive role of Tween 80 in Avicel hydrolysis with presence of ERLs was more effective. Binding strength of cellulase with ERLs was alleviated from 236.0 – 410.9 to 43.9 – 116.6 mL/g after adding 0.5 mg/mL Tween 80. When ERLs was more hydrophobic and had more condensed phenolic OH, the alleviation effect of Tween 80 on cellulase adsorption on ERLs was intensified but its positive effect on enhancing cellulase desorption was weakened. Tween 80 was effective in increasing xylanase activity and preventing xylanase deactivation. Further, with the increase of lignin content and phenolic OH in pretreated poplar, the effect of Tween 80 in alleviating xylanase adsorption on poplar samples was intensified but the effect in enhancing xylanase desorption from poplar samples was weakened. The results provided distinct findings to understand the interaction between Tween 80 and cellulase/xylanase in enzymatic saccharification of lignocelluloses.

59 BASIC BIOLOGICAL SCIENCES↗