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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Machine‐Learning‐Assisted Stochastic Cloud Population Model as a Parameterization of Cumulus Convection

Abstract A machine‐learning‐assisted stochastic cloud population model is coupled with the Advanced Research Weather Research and Forecasting (WRF) model to represent fluctuations in the cloud‐base mass flux associated with the life cycles and interactions among cumulus convection cells. In this cloud population model, the size distribution and the associated cloud‐base mass flux of the convective cells are related to their previous state and to the change in the total convective area via a transition function. The convective area tendency in turn is assumed to depend on the cloud‐base mass flux that is resolved by the host WRF model. The transition function is represented by a single hidden‐layer neural network trained by the evolution of convective cell size distributions in a 1‐km grid‐spacing WRF simulation run over the Australian Monsoon region. At every grid point of the host model, the cloud population model predicts the cell size and cloud‐base mass flux distributions from which a random sample of cells is fed to an entraining parcel model that calculates precipitation as well as the associated liquid water potential temperature and total moisture tendencies. These tendencies are averaged over the cells and provided to the host model. Several regional simulations are performed over tropical and midlatitude domains to test this as a potential approach to scale‐aware parameterization. It is shown that such an approach could be a new promising path to simulating realistic precipitation statistics and propagation of precipitation associated with the Madden‐Julian Oscillation while maintaining realistic depictions of the diurnal cycle over both land and ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Structural, Spectroscopic, and Kinetic Insight into the Heating Rate Dependence of Studtite and Metastudtite Dehydration

Uranyl peroxide minerals studtite (UO 2 O 2 ·4H 2 O) and metastudtite (UO 2 O 2 ·2H 2 O) are important materials in the nuclear fuel cycle. When heated, they dehydrate and transform to amorphous uranium oxides (UO x ), yet phase stability and heating rate dependence of these transformations are poorly understood. This information is critical to proper management of fuel cycle materials. In this work, we use in situ powder X-ray diffraction (PXRD), Raman spectroscopy, and thermogravimetric analysis (TGA) to monitor the dehydration of studtite and metastudtite. Strong linear correlation between the heating rate and phase transition temperature is observed. Geometric contraction and diffusion-related kinetic models describe studtite dehydration at slow heating rates, whereas Avrami–Erofeev or reaction order models become more accurate for faster thermal treatments. A second order model describes the transition from metastudtite to UO x regardless of the heating rate. Water retention during studtite dehydration is indicated by PXRD, Raman spectroscopy, and TGA. Here, we observe mixed-phase UO x dehydration products of metastudtite with a likely formation mechanism involving conversion of some uranyl centers from hexagonal to pentagonal bipyramidal coordination units via peroxide liberation. Our observations clarify over 100 years of measurements on these materials and represent an advancement in understanding the chemical behavior of nuclear fuel cycle materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Functional capacities of microbial communities to carry out large scale geochemical processes are maintained during ex situ anaerobic incubation

Mechanisms controlling CO 2 and CH 4 production in wetlands are central to understanding carbon cycling and greenhouse gas exchange. However, the volatility of these respiration products complicates quantifying their rates of production in the field. Attempts to circumvent the challenges through closed system incubations, from which gases cannot escape, have been used to investigate bulk in situ geochemistry. Efforts towards mapping mechanistic linkages between geochemistry and microbiology have raised concern regarding sampling and incubation-induced perturbations. Microorganisms are impacted by oxygen exposure, increased temperatures and accumulation of metabolic products during handling, storage, and incubation. We probed the extent of these perturbations, and their influence on incubation results, using high-resolution geochemical and microbial gene-based community profiling of anaerobically incubated material from three wetland habitats across a permafrost peatland. We compared the original field samples to the material anaerobically incubated over 50 days. Bulk geochemistry and phylum-level microbiota in incubations largely reflected field observations, but divergence between field and incubations occurred in both geochemistry and lineage-level microbial composition when examined at closer resolution. Despite the changes in representative lineages over time, inferred metabolic function with regards to carbon cycling largely reproduced field results suggesting functional consistency. Habitat differences among the source materials remained the largest driver of variation in geochemical and microbial differences among the samples in both incubations and field results. While incubations may have limited usefulness for identifying specific mechanisms, they remain a viable tool for probing bulk-scale questions related to anaerobic C cycling, including CO 2 and CH 4 dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)

Explicit consideration of microbial physiology in soil biogeochemical models that represent coupled carbon–nitrogen dynamics presents opportunities to deepen understanding of ecosystem responses to environmental change. The MIcrobial-MIneral Carbon Stabilization (MIMICS) model explicitly represents microbial physiology and physicochemical stabilization of soil carbon (C) on regional and global scales. Here we present a new version of MIMICS with coupled C and nitrogen (N) cycling through litter, microbial, and soil organic matter (SOM) pools. The model was parameterized and validated against C and N data from the Long-Term Inter-site Decomposition Experiment Team (LIDET; six litter types, 10 years of observations, and 13 sites across North America). The model simulates C and N losses from litterbags in the LIDET study with reasonable accuracy (C: R 2 =0.63; N: R 2 =0.29), which is comparable with simulations from the DAYCENT model that implicitly represents microbial activity (C: R 2 =0.67; N: R 2 =0.30). Subsequently, we evaluated equilibrium values of stocks (total soil C and N, microbial biomass C and N, inorganic N) and microbial process rates (soil heterotrophic respiration, N mineralization) simulated by MIMICS-CN across the 13 simulated LIDET sites against published observations from other continent-wide datasets. We found that MIMICS-CN produces equilibrium values in line with measured values, showing that the model generates plausible estimates of ecosystem soil biogeochemical dynamics across continental-scale gradients. MIMICS-CN provides a platform for coupling C and N projections in a microbially explicit model, but experiments still need to identify the physiological and stoichiometric characteristics of soil microbes, especially under environmental change scenarios.

58 GEOSCIENCES↗
DOE OSTI2026

Cradle-to-gate life cycle assessment of advanced composite panels incorporating CO 2 -derived multi-walled carbon nanotubes and hemp fiber for sustainable building applications

Advanced composite panels represent a promising pathway to reducing carbon emissions in the construction industry, yet comprehensive environmental impact assessments remain limited. Here, in this study, we conduct a life cycle assessment (LCA) to evaluate the environmental impacts of innovative composite panels produced from multi-walled carbon nanotubes (MWCNTs), hemp fiber (HF), recycled carbon fiber (rCF), and recycled polypropylene (PP), exploring their potential as baseline structural equivalents to conventional gypsum board. MWCNTs and HF play a critical role in sequestering carbon during raw material production, while the recycling processes for CF and PP generally require less energy compared to virgin material production. The LCA evaluates environmental performance using the TRACI 2.1 method, covering global warming potential (GWP), ozone depletion, smog formation, acidification, eutrophication, carcinogenic and non-carcinogenic effects, respiratory impacts, ecotoxicity, and fossil fuel depletion. Compositional variations—resin type (virgin vs. recycled), rCF content (9–29 wt%), and HF content (10–30 wt%)—are introduced for sensitivity and hotspot analyses. Results demonstrate that, when compared on the basis of preliminary structural equivalence, increasing recycled PP, rCF, and HF content can significantly reduce global warming potential compared to gypsum board. Beyond carbon reduction, the composite panels show trade-offs across other environmental categories. With the growing demand for composite materials in interior panels, ceiling systems, and exterior claddings, these findings highlight the environmental benefits and potential trade-offs of the proposed composites, establishing a foundational framework to support their continued development toward full building-system integration.

Advanced composite manufacturing↗
DOE OSTI2026

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗
DOE OSTI2022

Results of Application Demonstration of Autonomous Offshore Power System Supporting Multiple Mobile and Static Assets

Over the last decade, several technology trends have dominated the innovation cycle within the terrestrial economy. Electrification, cloud computing, decarbonization, digitization, and autonomy are representative examples of macro trends that have had a rapid and fundamental impact; an impact felt not only in user-facing technologies, such as electric vehicles and software-as-a-service, but also in the infrastructure required to deliver those technologies. However, the scale of the impact and rollout has not been felt equally between the terrestrial and ocean economies. Here, the innovation cycle in the ocean economy is significantly slower. What accounts for the difference and are there solutions to this issue?

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

The Role of Oxidation Resistance in High Temperature Alloy Selection for a Future with Green Hydrogen

Hydrogen is being considered integral to the future energy landscape but there is limited mechanistic understanding and a lack of predictive models to describe the combined effects of alloy and gas composition, temperature, thermal cycling and water vapor contents on the oxidation behavior of high-temperature materials. Experimental evaluations were combined with coupled thermodynamic-kinetic modeling to investigate the oxidation behavior of five representative Ni-based superalloys in two water vapor contents (10%, 60% H 2 O) under thermal cycling (1-h, 100-h cyles) conditions at 800°C and 1000°C. The alloy with the highest Ti content demonstrated the poorest cyclic oxidation behavior while the alloy with highest Cr and Al contents was expected to continue to support protective formation of a compact Al 2 O 3 scale. Finally, accelerated degradation of the chromia-forming alloys was observed in the higher water vapor content but the impact on transient oxidation of the alumina-forming alloys needs further investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mitigating Interfacial Mismatch between Lithium Metal and Garnet-Type Solid Electrolyte by Depositing Metal Nitride Lithiophilic Interlayer

Solid-state lithium batteries are generally considered as the next-generation battery technology that benefits from inherent nonflammable solid electrolytes and safe harnessing of high-capacity lithium metal. Among various solid-electrolyte candidates, cubic garnet-type Li 7 La 3 Zr 2 O 12 ceramics hold superiority due to their high ionic conductivity (10 –3 to 10 –4 S cm -1 ) and good chemical stability against lithium metal. However, practical deployment of solid-state batteries based on such garnet-type materials has been constrained by poor interfacing between lithium and garnet that displays high impedance and uneven current distribution. Herein, we propose a facile and effective strategy to significantly reduce this interfacial mismatch by modifying the surface of such garnet-type solid electrolyte with a thin layer of silicon nitride (Si 3 N 4 ). This interfacial layer ensures an intimate contact with lithium due to its lithiophilic nature and formation of an intermediate lithium–metal alloy. The interfacial resistance experiences an exponential drop from 1197 to 84.5 Ω cm 2 . Lithium symmetrical cells with Si 3 N 4 -modified garnet exhibited low overpotential and long-term stable plating/stripping cycles at room temperature compared to bare garnet. Furthermore, a hybrid solid-state battery with Si 3 N 4 -modified garnet sandwiched between lithium metal anode and LiFePO 4 cathode was demonstrated to operate with high cycling efficiency, excellent rate capability, and good electrochemical stability. This work represents a significant advancement toward use of garnet solid electrolytes in lithium metal batteries for the next-generation energy storage devices.

25 ENERGY STORAGE↗
DOE OSTI2021

Unraveling the Intermediate Reaction Complexes and Critical Role of Support-Derived Oxygen Atoms in CO Oxidation on Single-Atom Pt/CeO 2

CeO 2 -supported Pt single-atom catalysts have been extensively studied due to their relevance in automobile emission control and for the fundamental understanding of CeO 2 -based catalysts. Though CeO 2 -supported Pt nanoparticles are often more active than their single-atom counterparts, the former could easily redisperse to Pt single atom under oxidizing diesel conditions. Therefore, to maximize the reactivity of every Pt atom, it is important to fully understand the reaction mechanism of CeO 2 -supported Pt single atoms. Here, we report a CO oxidation study on a Pt/CeO 2 single-atom catalyst, where we can account for all of the neighbors using in situ and operando spectroscopy techniques and microcalorimetric measurements. Coupled with density functional theory calculations, we present a comprehensive picture of the dynamics of the surface species, the role of surface intermediates, and explain the observed reaction kinetics. We started with a catalyst containing exclusively single atoms and used in situ/operando spectroscopy to provide evidence for their stability during the reaction and to identify the Pt 1 complexes before and during the reaction and their binding to CO. The results reveal that in the precatalyst, Pt is present as Pt(O) 4 on the CeO 2 (111) step edge sites, but during CO oxidation, we find that two Pt 1 complexes coexist, representing two states of the same active site in the reaction cycle. The dominant state/complex remains Pt(O) 4 , which adsorbs CO very weakly as shown by CO microcalorimetry. The second, minority state/complex, Pt(CO)(O) 3 is generated through the reaction of Pt(O) 4 with CO, and CO is bound strongly to Pt 1 . Labile oxygen adatoms from the CeO 2 surface play a major role in the regeneration of Pt(O) 4 either directly from Pt(O) 3 or by reaction with the strongly adsorbed CO in Pt(CO)(O) 3 . We show that the formation of an oxygen vacancy and generation of a labile O* are not barrierless, which explains the long lifetime of Pt(CO)(O) 3 and its detectability despite being a minority complex. The results help to develop a comprehensive view of the dynamic evolution of Pt 1 complexes along the reaction cycle and provide mechanistic insights to guide the design of Pt-based single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Technoeconomic Assessment of a Sequential Step-Leaching Process for Rare Earth Element Extraction from Acid Mine Drainage Precipitates

Herein, Coal waste products have been studied as a new source of Rare Earth Elements (REEs) and other Critical Minerals (CM) essential for the development of renewable energy technologies, but the economic viability of these source materials is not well understood. This paper examines the technoeconomic performance of a novel process for rare earth element extraction from acid mine drainage precipitates (AMDp) in the Appalachian Coal Basin. The three phase extraction process includes excavation and transportation of AMDp, multi-phase pH driven step-leaching of REEs at ambient conditions, and commercial solvent extraction to produce a saleable grade rare earth oxide material that can be reduced to a pure metal. We estimate the life-cycle cost of bench-scale extraction of REEs from two representative Appalachian AMDp feedstock chemistries at between 4000 – 6000 $/kg of mixed REE concentrate produced. Both the AMDp composition and process parameters affect the profitability of REE extraction, with the REE concentration and distribution of REE in the feedstock, extraction and precipitation reagent consumption rates, and the potential for reagent recycling as the key variables. Economically profitable valorization of REE from AMDp will require a combination of continued process innovation and sizable financial incentives to substantially influence domestic supply of REEs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Interactions Between the Amazonian Rainforest and Cumuli Clouds: A Large‐Eddy Simulation, High‐Resolution ECMWF, and Observational Intercomparison Study

Abstract The explicit coupling at meter and second scales of vegetation's responses to the atmospheric‐boundary layer dynamics drives a dynamic heterogeneity that influences canopy‐top fluxes and cloud formation. Focusing on a representative day during the Amazonian dry season, we investigate the diurnal cycle of energy, moisture and carbon dioxide at the canopy top, and the transition from clear to cloudy conditions. To this end, we compare results from a large‐eddy simulation technique, a high‐resolution global weather model, and a complete observational data set collected during the GoAmazon14/15 campaign. The overall model‐observation comparisons of radiation and canopy‐top fluxes, turbulence, and cloud dynamics are very satisfactory, with all the modeled variables lying within the standard deviation of the monthly aggregated observations. Our analysis indicates that the timing of the change in the daylight carbon exchange, from a sink to a source, remains uncertain and is probably related to the stomata closure caused by the increase in vapor pressure deficit during the afternoon. We demonstrate quantitatively that heat and moisture transport from the subcloud layer into the cloud layer are misrepresented by the global model, yielding low values of specific humidity and thermal instability above the cloud base. Finally, the numerical simulations and observational data are adequate settings for benchmarking more comprehensive studies of plant responses, microphysics, and radiation.

Vilà‐Guerau de Arellano, J.↗
DOE OSTI2023

Dominant heterocyclic composition of dissolved organic nitrogen in the ocean: A new paradigm for cycling and persistence

Marine dissolved organic nitrogen (DON) is one of the planet’s largest reservoirs of fixed N, which persists even in the N-limited oligotrophic surface ocean. The vast majority of the ocean’s total DON reservoir is refractory (RDON), primarily composed of low molecular weight (LMW) compounds in the subsurface and deep sea. However, the composition of this major N pool, as well as the reasons for its accumulation and persistence, are not understood. Past characterization of the analytically more tractable, but quantitatively minor, high molecular weight (HMW) DON fraction revealed a functionally simple amide-dominated composition. While extensive work in the past two decades has revealed enormous complexity and structural diversity in LMW dissolved organic carbon, no efforts have specifically targeted LMW nitrogenous molecules. Here, we report the first coupled isotopic and solid-state NMR structural analysis of LMW DON isolated throughout the water column in two ocean basins. Together these results provide a first view into the composition, potential sources, and cycling of this dominant portion of marine DON. Our data indicate that RDON is dominated by 15N-depleted heterocyclic-N structures, entirely distinct from previously characterized HMW material. This fundamentally new view of marine DON composition suggests an important structural control for RDON accumulation and persistence in the ocean. The mechanisms of production, cycling, and removal of these heterocyclic-N-containing compounds now represents a central challenge in our understanding of the ocean’s DON reservoir.

58 GEOSCIENCES↗
DOE OSTI2024

Seeing the forest for the trees: implementing dynamic representation of forest management and forest carbon in a long-term global multisector model

Abstract Studies have found that understanding forest management is critical in understanding the interaction between the carbon cycle and the integrated human-Earth system. This makes effectively representing forest management decisions such as planting and harvesting important. Here, we implement a novel dynamic forest harvest model in a global state of the art multi-sector dynamics model, namely the Global Change Analysis Model (GCAM). We implement an approach that explicitly tracks forest age and generates rotation ages for forest harvest that are responsive to changes in wood prices, changes in forest age and regional preferences for forest rotation. Furthermore, the forest sector in GCAM competes for investment with other land use types in the future years based on expected profit. Our baseline scenario results indicate that with the new forest harvest model, the current global wood product demand in GCAM can be met with minimal loss of old growth forest through the age-based harvest decisions. We find that economic pressure for deforestation and consequent loss of forest carbon is a bigger driver of global forest change than wood harvests, especially in developing regions. Under alternative scenarios where an economic value is placed on carbon across the terrestrial and energy systems, while there is an increase in forest plantations, there can be corresponding decreases in forest cover in some regions as forest land competes with land for bio-energy crops. When the carbon in forests is assigned a price, we find that the average rotation age for wood harvests can be reduced across regions to harvest forests in a more carbon efficient manner.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

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

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

25 ENERGY STORAGE↗
DOE OSTI2022

Integrated Optimization and Control of a Hybrid Gas Turbine/sCO 2 Power System

During phase-I, the project team led by Echogen Power Systems (EPS) had two primary objectives based on investigating the application of gas turbines with supercritical carbon dioxide (sCO 2 ) power cycles. The first objective was to improve the overall efficiency and performance of a hybrid gas turbine/sCO 2 power system through a joint optimization of the two subsystems (gas turbine and sCO 2 power cycle) using non-linear optimization techniques that simultaneously evaluate thermal performance of the combined cycle. The hybrid power system included several points of interaction, including (but not limited to) gas turbine exhaust, fuel heating, inlet chilling and turbine cooling. The second objective was to establish a baseline transient response model of the hybrid power system and a notional microgrid and begin steps to integrate the control systems of the three major elements (gas turbine, sCO 2 cycle and grid controller). The project team established a baseline performance for a combined cycle power plant using a production gas turbine and scaled sCO 2 power cycle only utilizing exhaust heat recovery. Echogen’s non-linear techno-economic optimization code was extended by adding gas turbine component models derived from a in-house developed gas turbine design code. With the two cycles coupled by the gas turbine exhaust, design parameters of both cycles were allowed to vary simultaneously to determine performance opportunity versus isolated designs. Returning to the baseline gas turbine/sCO 2 power cycle transient models: Echogen had in-house developed sCO 2 cycle transient model in GT-Suite system simulation software, and had partnered with Siemens Finspång for gas turbine transient model, and Siemens PTI group to provide micro-grid load profile as well as hybrid power cycle generated load (power and frequency) analysis. The transient model for the SGT-750 Siemens gas turbine was a “black-box” functional mock-up interface (FMI) model developed by Siemens Industrial Turbomachinery in Finspång, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8°C. The transient model for sCO 2 power cycle was developed by Echogen in GT-SUITE 1D system simulation software platform. The basic CO 2 flow circuit has single-shaft turbomachinery with net 11.5 MW electrical power output at design conditions. The power turbine has a double-ended shaft with one end connected to synchronous generator through a fixed-ratio gearbox. The other end of power turbine is connected to the compressor through a continuously variable transmission. The major components of the sCO 2 power cycle modeled include air cooled condenser/cooler, CO 2 compressor, recuperator, two waste heat exchanger coils, power turbine, continuous variable transmission, gearbox and generator. Integration of SGT-750 transient model and sCO 2 power cycle transient model was done in Matlab Simulink. In the integrated model, the gas turbine and sCO 2 power cycle interacted at two points, first one being the gas turbine exhaust gas flow rate and temperature, which were inputs to sCO 2 power cycle model. The second point was the distribution of micro-grid load demand signal between the SGT-750 generator and sCO 2 cycle generator. For a given combined-cycle load demand, the gas turbine load demand was equal to the total demand minus the sCO 2 cycle power generated. In the present study the integrated model was simulated for two cases of grid load demand: (i) for a step change, both positive-step and negative-step, in grid load demand (ii) for a micro-grid load demand curve provided by Siemens PTI group. Finally, the time series plots representing load demand versus integrated system response were presented including the sCO 2 power cycle control system performance plots. The actual generated power and frequency of both the generators, gas turbine and sCO 2 power cycle, was supplied to Siemens PTI group for dynamic grid assessment, results of which are provided in appendices.

03 NATURAL GAS↗
DOE OSTI2024

Toward a Universal Model of Hyporheic Exchange and Nutrient Cycling in Streams

In this paper we demonstrate that several ubiquitous hyporheic exchange mechanisms can be represented simply as a one-dimensional diffusion process, where the diffusivity decays exponentially with depth into the streambed. Based on a meta-analysis of 106 previously published laboratory measurements of hyporheic exchange (capturing a range of bed morphologies, hydraulic conditions, streambed properties, and experimental approaches) we find that the reference diffusivity and mixing length-scale are functions of the permeability Reynolds Number and Schmidt Number. These dimensionless numbers, in turn, can be estimated for a particular stream from the median grain size of the streambed and the stream's depth, slope, and temperature. Application of these results to a seminal study of nitrate removal in 72 headwater streams across the United States, reveals: (a) streams draining urban and agricultural landscapes have a diminished capacity for in-stream and in-bed mixing along with smaller subsurface storage zones compared to streams draining reference landscapes; (b) under steady-state conditions nitrate uptake in the streambed is primarily biologically controlled; and (c) median reaction timescales for nitrate removal in the hyporheic zone are 0.5 and 20 hr for uptake by assimilation and denitrification, respectively. While further research is needed, the simplicity and extensibility of the framework described here should facilitate cross-disciplinary discussions and inform reach-scale studies of pollutant fate and transport and their scale-up to watersheds and beyond.

54 ENVIRONMENTAL SCIENCES↗