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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ectomycorrhizal effects on decomposition are highly dependent on fungal traits, climate, and litter properties: A model-based assessment

It has been proposed that competition between ectomycorrhizal (ECM) fungi and free-living saprotrophs for resources like nitrogen (N) slows decomposition and increases the soil carbon storage in ECM ecosystems compared to arbuscular (AM) ecosystems. However, empirical evidence for the generality of such ECM effects is equivocal, and confounding mechanisms have been proposed that affect the magnitude and direction of ECM effects on soil carbon. Here, for this work, we conduct a theoretical modeling experiment, where we explicitly incorporate mycorrhizal processes into the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model. We use the model to explore the conditions under which ECM N acquisition processes can induce stronger saprotrophic N limitation and result in slower decomposition rates and greater soil organic carbon accumulation compared to AM processes. We found that the ECM fungi more strongly inhibited decomposition when litter inputs were N-depleted and relatively recalcitrant and when ECM fungi possessed a strong capacity to mine N from both recalcitrant soil organic matter and microbial necromass. Climate and seasonality also played a role as the ECM competition effect was strongest at low mean annual temperatures and when litterfall peaked seasonally. Priming effects driven by high root exudation rates in ECM-dominated systems could overwhelm the competition effect and reduce soil carbon under some circumstances. The ECM effect on decomposition in our simulations was highly context dependent. Based on our model results, we expect to see a strong ECM competition effect in temperate deciduous and boreal forests with relatively recalcitrant litter inputs, and with ECM fungi that produce oxidases and necromass-degrading enzymes. However, even a relatively strong ECM competition effect on decomposition only increased soil organic carbon accumulation by ~10%.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Cybersecurity Assessment in DER-rich Distribution Operations: Criticality Levels and Impact Analysis

The integration of distributed energy resources (DERs) in distribution networks has become a pivotal strategy for achieving decarbonization, enhancing grid resilience, and optimizing grid efficiency. Remote monitoring and control op- erations of such resources rely on a network of sensors and communication infrastructure, exposing the system to potential cyber threats. Therefore, as the deployment of DERs increases, ensuring secure monitoring and control becomes an imperative challenge. This paper utilizes real-time feeder models, which are instrumental in developing cybersecurity testbeds tailored for hardware-in-loop (HIL) systems. These models enable users to simulate cyber attacks in a real-world environment and analyze the power distribution operations during vulnerabilities. Furthermore, we discuss several practical sets of grid parameters to identify critical levels of DERs and evaluate various scenarios that simulate cyber threats on sensitive DERs. The modified IEEE 123-bus model is used as the test case for demonstrating the proposed scenarios. The findings from this study provide valuable insights into the vulnerabilities and potential consequences of cyber attacks on DERs, allowing for better mitigation strategies and improved cyber resilience in future distribution networks.

Maharjan, Manisha↗
DOE OSTI2021

CO 2 Source Assessment, Wabash CarbonSAFE Subtask 10.1 (Technical Report)

This document describes the CO 2 source at Wabash Valley Resources, namely the gasification process and configuration of the facility, and separation of the hydrogen product from the CO 2 byproduct which will be captured for subsurface storage. This document then presents a summary of CO 2 storage considerations and estimated project expenses for adding CO 2 capture and sequestration to the existing gasification plant.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Assessing the Economic Value of Underground Thermal Storage for Hybrid Geothermal Power

Solutions are needed to address resource adequacy in the electric power system for highly decarbonized systems. The storage duration, the length of time a storage device can provide continuous output at its rated capacity, must be sufficient to receive full credit toward resource adequacy. Longer peaks and high fractions of variable renewable generation have increased the required duration to potentially seasonal durations. Underground Thermal Energy Storage (UTES) can be adapted to a hybrid storage power plant or heating and cooling applications to satisfy the need for long-duration storage. In this study, we use the Renewable Energy Deployment System (ReEDS) capacity expansion model to evaluate the increase in value for an enhanced geothermal system (EGS) resources by adding UTES. In modeled scenarios, using geothermal without storage as a baseline we compare the increase in economic value for plants with a range of storage characteristics. The added value of a hybrid storage plant changes depending on assumptions including the length of storage duration, efficiency, and ability to charge storage from the grid during periods of low energy prices. Relating proposed characteristics for geothermal UTES hybrids to the modeled economic value provides insight into economically viable costs for developing UTES as well as what combination of technology characteristics and future energy and policy assumptions drive significant value increases.

capacity expansion model↗
DOE OSTI2023

A Review of Advanced Test Reactor Fuel and Assessment of Its Compatibility with the ZIRCEX Chlorination Process

Advanced Test Reactor (ATR) fuel has been identified as a resource for high-assay low-enriched uranium (HALEU) production. A survey was performed on the published literature describing ATR fuel. The geometry of the fuel is complex; different parts of the fuel compact experience differing neutron flux and burnup. The literature is sparse, and access is controlled. Therefore, fundamental studies of fuel reprocessing must use a model fuel that represents the main chemical and structural features. Advanced chlorination, or chlorination with sulfur-chlorine bearing reagents is being investigated as way to separate the fuel from metal matrix alloys. A UAl x alloy will be fabricated with x = 3, 4, and 5. The potential chlorination of individual UAl x intermetallics will be assessed in the advanced chlorination process of Al-8001 and Al-6061 as well as a representative mixture. Initial studies will track the alloying elements of the Al, which are Si, Fe, Cu, Mn, Mg, Cr, Zn, and Ti, in addition to the U itself. Further studies will include fission product simulants. Because advanced chlorination solvents include sulfur, the chemistry of sulfur with major and minor constituents will also be investigated. The experimental work accompanied by neutronic calculations will allow the assessment of the feasibility of advanced chlorination to separate aluminum from uranium. If bench-scale testing appears promising, then small-scale tests in shielded facilities with irradiated cladding, lightly irradiated fuel, and spent nuclear fuel are recommended to track the complete inventory of fissile actinides, fission product impurities, and reagent solids and liquids.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Existing Methods for Grid Strength Assessment and Role of Hydropower in Future Grids

The power system is undergoing rapid evolution with increasing penetration of inverter-based resources (IBRs), large loads, microgrids, and power electronic devices. Ensuring reliable and stable operation of the modern power grid is a multi-faceted challenge that requires detailed understanding of this complex system. Dynamic stability is a major concern in maintaining the security of power grids as the generation mixes and large loads transitions to include high shares of power electronic devices. The operation of IBRs in regions with low system strength and higher grid impedances has been found to be the main reason behind many of the power system instabilities that manifest themselves in various types of oscillations and interactions that, if not properly addressed and damped, can jeopardize the reliable operation of the power system. Weak grid conditions compound such stability problems, particularly when many IBRs operate in proximity to and connect to weak power grids. Therefore, it is important to assess grid strength for planning, integration and operation of IBRs for a given power system. In this report, we aim to understand and classify existing methodologies for grid strength assessment, along with their limitations and future needs. Further, we aim to utilize the huge untapped potential in utilizing hydro energy resources in addressing some of the pertinent challenges of grid strength and reliable operation of modern power systems. Hydropower, historically valued for its flexibility and dispatchability, now faces new constraints due to reduced share of synchronous machines in the generation mix and seasonal variability of available water resources. Yet, these same plants present untapped potential beyond energy generation - notably, as providers of critical grid services. This report explores how hydropower plants, particularly through operation as synchronous condensers, can play a pivotal role in strengthening the grid amid evolving system dynamics.

13 HYDRO ENERGY↗
DOE OSTI2020

An Approach to Dependence Assessment in Human Reliability Analysis: Application of Lag and Linger Effects

Dependence assessment refers to an approach used in human reliability analysis (HRA) to adjust a human error probability (HEP) for the following action by considering the impact of the preceding action. It has been known to significantly affect the overall results of probabilistic safety assessment (PSA). If the dependence assessment is not adequate, the result could be unconvincing for explaining the operator failures in the context of PSA. To date, several methods and some recent research have identified suggestions for treating dependence issues in HRA; however, these are still exclusively based on the intrinsic approach of the Technique for Human Error Rate Prediction (THERP), an HRA method. THERP inevitably has a challenge with the subjectivity of expert evaluation as well as the requirement for PSA and HRA expertise with resource-intensive and time-consuming processes. This paper suggests an approach to dependence assessment that could not only minimize the influence of expert judgment, but also saves time to perform the analysis with reasonable manpower. It modifies existing HRA methods with considering lag and linger effects to apply dependence effects for them. Based on a representative HRA method, i.e., Standardized Plant Analysis Risk - HRA (SPAR-H), guidance for how to apply lag and linger effects for the HRA method is suggested. Then, an investigation is carried out to compare quantification results of the revised HRA method with that of the original approach based on experimental data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2021

Dynamic Linking of Upstream Energy and Freight Demands for Bio and Fossil Energy Pathways in the Global Change Analysis Model

Comprehensive study of the environmental impacts associated with demand for an energy resource or carrier in any one sector requires a full consideration of the direct and indirect impacts on the rest of the regional and global energy system. It is important to consider the energy that is consumed in producing primary energy resources and energy consumed in transporting these energy resources internationally and domestically in order to produce a complete picture of these impacts. Biofuels are especially complex since they have feedbacks not just to the energy system but also to regional and global crop markets. Different modeling and analysis strategies have been applied to consider these impacts, which occur “upstream” of final energy consumption, with some success. Traditional life cycle models allow for rich technological detail in linking upstream impacts of energy demand with downstream final consumption; however, they cannot by themselves represent dynamic economic feedbacks across multiple sectors and regions over time. Computable general equilibrium (CGE) modeling does account for economic feedback among all sectors and regions; however, CGE modeling does not lend itself to physical representation of technological detail. Partial equilibrium (PE) modeling is a heterogeneous category describing economic models that focus on a subset of the economy, and they differ in coverage and ease in incorporating more sectors and economic links. In this study, we present a strategy for dynamically including the direct and indirect impacts of energy demand with physical and technology detail by explicitly adding these upstream energy and transportation links to GCAM, a PE model of global energy, land use, and emissions. We incorporate the following inter-sectoral linkages: energy inputs to crop production, energy inputs to fossil resource production, and freight transport requirements of energy and agricultural commodities. We assess the implications of explicitly including these links by measuring the global impacts of increased corn ethanol demand in the United States with and without these links included. Although the net global impact of the upstream links on energy and emissions are relatively modest in the scenarios we studied, the inclusion of these links illustrates interesting trade-offs in energy and transportation demand among fossil fuel and agriculture sectors. These sectoral interactions suggest that this level of modeling detail could be important in evaluating future analytical questions.

Sampedro Martinez de Estivariz, Jon↗
DOE OSTI2023

A hybrid data-driven and model-based approach for computationally efficient stochastic unit commitment and economic dispatch under wind and solar uncertainty

Stochastic unit commitment (UC) and economic dispatch (ED) are imperative in dealing with uncertainty in renewable forecast for power system operation and planning such that the overall expected production cost is minimized over the planning horizon. However, accurate calculation of the expected production cost requires assessment of a very large number of different scenarios of uncertain renewable resources, such as solar and wind, which is practically infeasible to simulate in real time. This article proposes a hybrid datadriven and physics-based model-predictive paradigm to efficiently solve for stochastic unit commitment and economic dispatch considering uncertainty in wind and solar power forecasts. Here, the novelty of the approach lies in decoupling the production cost estimation from the unit commitment and economic dispatch optimization problems under uncertainty without compromising on the fidelity of the solutions. A data-driven machine learning model is first developed to predict the mean optimal production cost. A physics-based inverse problem is then solved to get the stochastic UC and ED profiles from the expected cost. The presented approach considers, for the first time, solar uncertainty in UC/ED determination and enables efficient and accurate propagation of wind and solar uncertainty to estimate the statistics of the production cost. The effectiveness of the developed approach is demonstrated systematically on a stylized RTS-GMLC single-node system. The overall framework predicts the expected cost 62.5% more accurately than the existing state-of-the-art, on unforeseen days during the entire year, and yields, for the first time, the associated physically consistent UC and ED profiles. The solutions are also shown to be flexible in providing adequate daily reserves to address any statistical deviations from probabilistic power forecasts. The computational time associated with the presented method is only about 10 s compared to over 24 h needed for a conventional stochastic UC/ED determination under uncertainty on an Intel Core i9 processor with 32 GB of RAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Insight into Acetic Acid Synthesis from the Reaction of CH 4 and CO 2

The reaction of CH 4 and CO 2 to produce acetic acid is an atom-efficient way for using carbon resources and for mitigating CO 2 emissions. This article provides a critical assessment of the progress in this catalytic reaction from the perspective of identifying and constructing the active sites. We elucidate how Cu- and Zn-based catalysts with different structures are used for the activation of CH 4 and CO 2 . The differences in the metal oxidation state may affect the adsorption of CH 4 and CO 2 and consequently change the activation barriers for the dissociation of the C–H bond of CH 4 and the C–C coupling reaction. We discuss how the active sites and transition states can be modified by the location of metal sites, the framework environment, and the promotion effect of different acid sites. Additionally, we also compare different technologies, including catalyst pretreatment, preactivation with CO 2 , tandem reaction, and plasma-driven catalysis for the CH 4 and CO 2 conversion. We conclude by identifying opportunities for improving the efficiency of heterogeneous catalysts for this important reaction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Nonstationarity in the global terrestrial water cycle and its interlinkages in the Anthropocene

Climate change and human activities alter the global freshwater cycle, causing nonstationary processes as its distribution shifting over time, yet a comprehensive understanding of these changes remains elusive. Here, we develop a remote sensing–informed terrestrial reanalysis and assess the nonstationarity of and interconnections among global water cycle components from 2003 to 2020. We highlight 20 hotspot regions where terrestrial water storage exhibits strong nonstationarity, impacting 35% of the global population and 45% of the area covered by irrigated agriculture. Emerging long-term trends dominate the most often (48.2%), followed by seasonal shifts (32.8%) and changes in extremes (19%). Notably, in mid-latitudes, this encompasses 34% of Asia and 27% of North America. The patterns of nonstationarity and their dominant types differ across other water cycle components, including precipitation, evapotranspiration, runoff, and gross primary production. These differences also manifest uniquely across hotspot regions, illustrating the intricate ways in which each component responds to climate change and human water management. Our findings emphasize the importance of considering nonstationarity when assessing water cycle information toward the development of strategies for sustainable water resource usage, enhancing resilience to extreme events, and effectively addressing other challenges associated with climate change.

Science & Technology - Other Topics↗
DOE OSTI2022

From Event Data to Wind Power Plant DQ Admittance and Stability Risk Assessment

This paper presents a dynamic event data-based stability risk assessment method for power grids with high penetrations of inverter-based resources (IBRs). This method relies on obtaining the IBRs' DQ admittance through dynamic event data and computing the system's eigenvalues based on the admittance models. Two critical technologies are employed in this research, including time-domain and frequency-domain data fitting and dq-frame voltage and current signal derivation. The first technology is key to obtaining the s-domain expressions from the transient response data, and the s-domain DQ admittance model from the frequency-domain measurements. The second technology is key to obtaining the dq-frame voltage and current signals from either the three-phase instantaneous measurements or the phasor measurement unit (PMU) data. The method is illustrated using data generated from a Type-4 wind power plant modeled in PSCAD. This paper demonstrates the technical feasibility of the proposed approach.

17 WIND ENERGY↗
DOE OSTI2022

Root responses to elevated CO 2 , warming and irrigation in a semi-arid grassland: Integrating biomass, length and life span in a 5-year field experiment

Plant roots mediate the impacts of environmental change on ecosystems, yet knowledge of root responses to environmental change is limited because few experiments evaluate multiple environmental factors and their interactions. Inferences about root functions are also limited because root length dynamics are rarely measured. Using a 5-year experiment in a mixed-grass prairie, we report the responses of root biomass, length and life span to elevated carbon dioxide (CO 2 ), warming, elevated CO 2 and warming combined, and irrigation. Root biomass was quantified using soil cores and root length dynamics were assessed using minirhizotrons. By comparing root dynamics with published results for soil resources and above-ground productivity, we provide mechanistic insights into how climate change might impact grassland ecosystems. In the upper soil layer, 0–15 cm depth, both irrigation and elevated CO 2 alone increased total root length by twofold, but irrigation decreased root biomass and elevated CO 2 had only small positive effects on root biomass. The large positive effects of irrigation and elevated CO 2 alone on total root length were due to increases in both root length production and root life span. The increased total root length and life span under irrigation and elevated CO 2 coincided with apparent shifts from water limitation of plant growth to nitrogen limitation. Warming alone had minimal effects on root biomass, length and life span in this shallow soil layer. Warming and elevated CO 2 combined increased root biomass and total root length by c. 25%, but total root length in this treatment was lower than expected if the effects of CO 2 and warming alone were additive. Treatment effects on total root length and root life span varied with soil depth and root diameter. Synthesis. Sub-additive effects of CO 2 and warming suggest studies of elevated CO 2 alone might overestimate the future capacity of grassland root systems to acquire resources. In this mixed-grass prairie, elevated CO 2 with warming stimulated total root length and root life span in deeper soils, likely enhancing plant access to more stable pools of growth-limiting resources, including water and phosphorus. Therefore, these root responses help explain previous observations of higher, and more stable, above-ground productivity in these projected climate conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Airport Risk Assessment Model (ARAM)

The Airport Risk Assessment Model (ARAM) model automatically determines the optimal allocation of limited security resources to minimize total risk to the airport. At the same time, the model adds an element of randomness to the, reducing the predictability of asset schedules and further increasing countermeasure effectiveness.

Brigantic, Robert↗
DOE OSTI2022

Installation and imaging of thousands of minirhizotrons to phenotype root systems of field-grown plants

Roots are vital to plant performance because they acquire resources from the soil and provide anchorage. However, it remains difficult to assess root system size and distribution because roots are inaccessible in the soil. Existing methods to phenotype entire root systems range from slow, often destructive, methods applied to relatively small numbers of plants in the field to rapid methods that can be applied to large numbers of plants in controlled environment conditions. Much has been learned recently by extensive sampling of the root crown portion of field-grown plants. But, information on large-scale genetic and environmental variation in the size and distribution of root systems in the field remains a key knowledge gap. Minirhizotrons are the only established, non-destructive technology that can address this need in a standard field trial. Prior experiments have used only modest numbers of minirhizotrons, which has limited testing to small numbers of genotypes or environmental conditions. This study addressed the need for methods to install and collect images from thousands of minirhizotrons and thereby help break the phenotyping bottleneck in the field. Over three growing seasons, methods were developed and refined to install and collect images from up to 3038 minirhizotrons per experiment. Modifications were made to four tractors and hydraulic soil corers mounted to them. High quality installation was achieved at an average rate of up to 84.4 minirhizotron tubes per tractor per day. A set of four commercially available minirhizotron camera systems were each transported by wheelbarrow to allow collection of images of mature maize root systems at an average rate of up to 65.3 tubes per day per camera. This resulted in over 300,000 images being collected in as little as 11 days for a single experiment. The scale of minirhizotron installation was increased by two orders of magnitude by simultaneously using four tractor-mounted, hydraulic soil corers with modifications to ensure high quality, rapid operation. Image collection can be achieved at the corresponding scale using commercially available minirhizotron camera systems. Along with recent advances in image analysis, these advances will allow use of minirhizotrons at unprecedented scale to address key knowledge gaps regarding genetic and environmental effects on root system size and distribution in the field.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Results of Storage Complex Readiness Evaluation

In this report, the results from Task 4.2.1 and 2.1.b are used to evaluate storage complex readiness. In this subtask we compare the results of the traditional formation-by-formation storage assessment to a new method designed to consider all the potential storage resource. This work has been in part coordinated with a study funded as part of the Lawrence Livermore National Laboratory led “Road to Removal” study. This overview is a at national scale and places the SECARB region in that context.

54 ENVIRONMENTAL SCIENCES↗