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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Initial plant community responses to hardwood control treatments in restoration of remnant longleaf pine (Pinus palustris) woodlands

Changes in land use over the past century have contributed to substantial losses of longleaf pine (Pinus palustris) woodlands in the southeastern USA and replacement with higher density, mixed pine and hardwood stands that suppress understory development and limit application of prescribed fire. To increase understanding of limiting factors and identify potential approaches for restoring longleaf pine woodlands, we studied in this work initial availability of light and soil water and 2-year (2018–2019) plant community responses after controlling overstory hardwoods in five remnant longleaf pine woodlands having no evidence of previous agriculture at the Savannah River Site near Aiken, SC, USA. Seven hardwood control treatments and a non-treated check were compared in a randomized compete block experiment: cutting, cutting + shredding of logging residues, stem injection with imazapyr herbicide, cutting + basal spray with imazapyr herbicide, cutting + basal spray with triclopyr herbicide, cutting + directed foliar spray with a mixture of glyphosate and imazapyr herbicides, and cutting + broadcast foliar spray with the same herbicide mixture. In the year prior to hardwood cutting (2016), understory light availability averaged 23% of full sun. Throughout the year of treatment installation (2017), average soil water content (SWC) was below permanent wilting point (5.5% SWC) where overstory hardwoods were retained; whereas, it was above wilting point (7.5%) where they had been cut. Thus, combined effects of shade and root competition from overstory hardwoods probably limited cover of herbaceous species in the non-treated check. In the 2 years following treatment, hardwood survival averaged > 99%, 62%, 42% and < 1% for the non-treated check, cutting, shredding, and herbicide treatments, respectively. Relative to the non-treated check, herbaceous species richness was increased by shredding, stem injection, basal spray, or directed foliar treatments; herbaceous cover was increased by basal spray or directed foliar treatments; and woody cover was decreased by directed or broadcast foliar treatments. The directed foliar spray was the most effective treatment for achieving many of the desired understory characteristics of a longleaf pine woodland, including a diverse understory dominated by herbaceous vegetation capable of supporting periodic prescribed fires. Although the imazapyr basal spray treatment increased cover of remnant woodland indicator species, none of the treatments increased richness of this species group, suggesting that restoration of native species composition will be expedited by enrichment seedings or plantings.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Towards generic memory forensic framework for programmable logic controllers

A Programmable Logic Controller (PLC) is a microprocessor-based controller that is used to automate physical processes in critical infrastructure and various other industries and manufacturing sectors. Initially, PLCs were completely isolated from the Internet, and cyber security was not incorporated at the time of development. The introduction of industry 4.0 and the evolution of ICS systems to communicate over public IP addresses from the Internet enhanced productivity and efficiency, but Internet connectivity exposed the systems and their vulnerabilities, which led to an increase in cyber attacks. When a system is sabotaged/compromised, security analysts need to get to the root cause of the attack as quickly as possible to recover the system. To do so, memory forensic analysis is critical to provide a unique insight into the run-time memory activities and extract a reliable source of evidence. In this paper, we analyze the memory structure of the Schneider Electric Modicon M221 PLC. To build a memory profile, we reverse engineer the communication protocol and conduct differential analysis to gain knowledge about the structure of the memory and the low-level representation of control logic instructions. We then identify dynamic and static memory regions by modifying different project fields and conducting differential analysis, which allows us to identify boundaries of critical memory structures and extract important forensic artifacts that can be found in the memory. The Python implementation of the memory profile can help reduce the time and effort required for manual analysis in case of cyber incident or system failure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Utilization of an Advanced Sensor network to determine fuel heating value and Real-Time net unit heat rate during transient operation

Coal-fired utility boilers are being increasingly used as variable electricity generation to resolve the imbalance in the energy market from the expansion of intermittent renewable energy. The frequent transient operation required to meet residual energy demand has created a challenge for coal-fired units to operate efficiently. This work utilizes an advanced sensor network (ASN) to calculate net unit heat rate (NUHR) of a coal-fired boiler in real time through combustion calculations and statistical correlations to provide the tools for optimizing dynamic operation. Real-time heating values that were necessary to determine fuel input energy to calculate accurate NUHR were found using both fundamental and data-driven methods. Real-time NUHR shows distinct shifts that reflect changes in process conditions that will improve the ability to optimize transient operation. Data-driven heating value correlations had 24% lower root mean square error (RMSE) than the fundamental combustion calculation approach when compared to daily retrospective proximate analysis. Furthermore, the data-driven method RMSE improved by 7% with the inclusion of ASN data. Future work is to validate by comparing unit performance with and without the inclusion of NUHR as a control parameter for the dynamic neural network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Dynamics of hydrogen–ammonia–natural gas lean-premixed high-pressure flames

The influence of fuel composition on self-excited combustion instabilities in a high-pressure combustor operated with ammonia, hydrogen, and natural gas fuels is characterized with high-frequency pressure measurements and imaging of the flame structure. A micromix multi-stage injector with 19 elements is used to introduce the fuel blend premixed with heated air into an optically accessible combustor operated at ~1.1 MPa. As hydrogen is substituted for natural gas, longitudinal thermoacoustic instabilities are observed in the combustor with pressure fluctuation amplitudes as large as 8% of the mean chamber value. In the absence of natural gas, limit-cycle instability magnitude is largely insensitive to ammonia addition. However, fuel compositions with > 20% natural gas result in positive correlation between instability amplitude and ammonia concentration. Spatial distribution of heat release in the combustor evaluated from OH* chemiluminescence imaging reveals axial growth in the regions of heat release fluctuation as hydrogen decreases, thus correlating flame length to instability amplitude. Distinct transitions from the first harmonic of the fundamental longitudinal acoustic mode (~1100 Hz) to the fundamental mode (~550 Hz) are observed with root mean square pressure fluctuations exceeding 7% of the mean chamber value. Here, these cases correspond to hydrogen mole fractions ≤ 50%. Analysis of the phase relationship between pressure fluctuations upstream and downstream of the flame zone indicates acoustic coupling of the injector as a key contributor to instability growth.

03 NATURAL GAS↗
DOE OSTI2024

CG-Kit: Code Generation Toolkit for performant and maintainable variants of source code applied to Flash-X hydrodynamics simulations

CG-Kit is a new Code Generation tool-Kit that we have developed as a part of the solution for portability and maintainability for multiphysics computing applications. The development of CG-Kit is rooted in the urgent need created by the shifting landscape of high-performance computing platforms and the algorithmic complexities of a particular large-scale multiphysics application: Flash-X. To efficiently use computing resources on a heterogeneous node, an application must have a map of computation to resources and a mechanism to move the data and computation to the resources according to the map. Most existing performance portability solutions are focussed on abstracting the expression of computations so that a unified source code can be specialized to run on different resources. However, such an approach is insufficient for a code like Flash-X, which has a multitude of code components that can be assembled in various permutations and combinations to form different instances of applications. Similar challenges apply to any code that has composability, where a single specified way of apportioning work among devices may not be optimal. Additionally, use cases arise where the optimal control flow of computation may differ for different devices while the underlying numerics remain identical. This combination leads to unique challenges including handling an existing large code base in Fortran and/or C/C++, subdivision of code into a great variety of units supporting a wide range of physics and numerical methods, different parallelization techniques for distributed and shared memory systems and accelerator devices, and heterogeneity of computing platforms requiring coexisting variants of parallel algorithms. All of these challenges demand that scientific software developers apply existing knowledge about domain applications, algorithms, and computing platforms to determine custom abstractions and granularity for code generation. There is a critical lack of tools to tackle those problems. CG-Kit is designed to fill this gap by providing a user with the ability to express their desired control flow and computation-to-resource map in the form a pseudocode-like recipe. It consists of standalone tools that can be combined into highly specific and, we argue, highly effective portability and maintainability toolchains. Here we present the design of our new tools: parametrized source trees, control flow graphs, and recipes. The tools are implemented in Python. They are agnostic to the programming language of the source code targeted for code generation. In conclusion, we demonstrate the capabilities of the toolkit with two examples, first, multithreaded variants of the basic AXPY operation, and second, variants of parallel algorithms within a hydrodynamics solver, called Spark, from Flash-X that operates on block-structured adaptive meshes.

Algorithmic portability↗
DOE OSTI2021

Repeated freeze-thaw cycles increase extractable, but not total, carbon and nitrogen in a Maine coniferous soil

Northeastern North America has been experiencing warmer winters with reduced snow accumulation, with more frequent winter freeze-thaw cycles. We conducted a laboratory experiment to investigate how increased frequency of freeze-thaw cycles (FTC) would alter soil C and N availability. Organic (O) and mineral (B) horizon soils were collected from a coniferous forest in Maine, processed to exclude roots, and then frozen in the laboratory (-10 °C) with one (FTC-1), two (FTC-2), or six (FTC-6) thaw periods. Soils were analyzed for extractable inorganic ammonium (NH4-N), water extractable organic carbon (WEOC), carbon dioxide flux (respiration), and total C and N. Extractable NH4-N increased following FTC, for both horizons. WEOC in O horizons had a lower SUVA254, indicating a stronger microbial influence (i.e., microbial cell lysis) in these soils after FTC. Respiration in O horizon soils decreased post-incubation and did not differ between FTC and Control soils. In the B horizon, however, FTC soils showed greater respiration than Control soils, suggesting that the newly available nutrients may have stimulated microbial activity. In contrast to these results, total C and N remained unaltered by FTC, presumably because the FTC disturbances represented mostly a translocation of C and N from one pool into another, and losses due to respiration were too small to significantly influence the large TC and TN pools. The effect of FTC on NH4-N did not change with FTC frequency, suggesting that a single FTC is sufficient to alter both C and N availability and quality, and that additional FTC may not have a significant further effect. This study provides fresh insights on how organic and mineral soils might respond to increased freeze-thaw frequency in winter.

Patel, Kaizad F.↗
DOE OSTI2021

Vertical movement of soluble carbon and nutrients from biocrusts to subsurface mineral soils

Dryland ecosystems can be constrained by low soil fertility. Within drylands, the soil nutrient and organic carbon (C) cycling that does occur is often mediated by soil surface communities known as biological soil crusts (biocrusts), which cycle C and nutrients in the top ca. 0–2 cm of soil. However, the degree to which biocrusts are influencing soil fertility and biogeochemical cycling in deeper, subsurface mineral soils is unclear. The movement of dissolved resources from biocrusts to deeper soil layers in leachate may be one of the main mechanisms through which biocrust fertility is transferred downward towards deeper microbial communities and plant roots occurring within mineral soil. Here, in this study, we examined the role of biocrust leachate in contributing to subsurface nutrient and soluble C pools and subsurface microbial cycling. We collected biocrusts from three biocrust successional stages and explored resource pools in situ at multiple soil depths, while collecting leachate and measuring nutrient and organic C concentrations and metabolite composition from each successional stage in the laboratory. After four leachate collections, we conducted an incubation of mineral soil collected from below each biocrust successional stage to measure heterotrophic microbial CO 2 flux and biomass. Overall, our findings observed that the degree of nutrient and C connectivity between biocrusts and the sub-crust mineral soil depended on the biocrust successional stage and the element being considered, and the influence of biocrust successional stage on mineral soil CO 2 flux is likely related to long-term resource build up. Together, our results suggest that the influence of biocrust leachate on subsurface mineral soil is complex and context dependent, but, over longer time periods and at later successional stages, can have measurable effects on dryland soil biogeochemical cycling with feedbacks to resource availability and CO 2 flux.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the U.S. Midwest?

Cropland carbon budget depicts the amount of carbon flowing in and out of agroecosystems and the changes in carbon stocks of soil and living biomass during the same period. Soil carbon credit is the additional change in soil carbon stock under certain farming practices compared with the business-as-usual practices. Accurately calculating cropland carbon budget and soil carbon credit is critical to assessing climate change mitigation potential in agroecosystems. The calculation of cropland carbon budget and soil carbon credit is sensitive to local soil and climatic conditions, especially initial soil organic carbon (SOC) stock, which is determined by both SOC concentration (SOC%) and bulk density (Bulk_Density). SOC stock data are either from soil sampling or gridded public survey data. In agroecosystem models, SOC stock data are a key model input for quantifying cropland carbon budget and soil carbon credit. However, various types and degrees of uncertainties exist in SOC stock datasets, which propagate to the quantification of SOC stock change. In particular, a large discrepancy is found in two widely used SOC stock datasets — Rapid Carbon Assessment dataset (RaCA) and Gridded Soil Survey Geographic Database (gSSURGO) — in the U.S. Midwest, with a relative difference (quantified using Normalized Root Mean Square Error, NRMSE) of 48.0% for 0–30 cm SOC stock between the two datasets. It remains largely unclear how uncertainty in SOC stocks affects the calculation of cropland carbon budget and soil carbon credit. To address this question, we used a well-validated process-based agroecosystem model, ecosys, to assess the impacts of SOC stock uncertainty on carbon budget and soil carbon credit calculation in the U.S. Midwestern corn-soybean rotation systems. Our results reveal the following findings: (1) A sizable discrepancy exists in simulated cropland carbon budget between using gSSURGO and using RaCA for their SOC% and Bulk_Density as model inputs, with a Pearson correlation coefficient (r) of only 0.4 for simulated change of SOC stock (ΔSOC) using these two different soil datasets. (2) Simulated cropland carbon budget components were more sensitive to initial SOC% than to Bulk_Density. For example, the upper and lower quartiles of multi-year averaged ΔSOC were –29.8 and 4.8 gC/m 2 /year for the selected counties respectively, with an uncertainty of 13.7 and 0.7 gC/m 2 /year induced by uncertainties in initial SOC% and Bulk_Density, respectively. (3) Both simulated ΔSOC and its uncertainty were negatively correlated with initial SOC%, whereas ΔSOC was negatively correlated with air temperature, and ΔSOC uncertainty was positively correlated with air temperature. (4) The uncertainty of calculated soil carbon credits was much smaller compared with the uncertainty of calculated absolute carbon budgets assuming the same SOC stock uncertainty level in the inputs. Specifically, in our assessment comparing planting cover crops vs no cover crop, the uncertainty of calculated soil carbon credits induced by initial SOC% uncertainty was less than 4% (relative to the quantified value of the soil carbon credits) for 90% of the cases. Our analysis highlights that high accuracy measurement of SOC% as inputs is needed for the calculation of cropland carbon budgets; however, soil carbon credit quantification is much less sensitive to the initial SOC% inputs, and the current publicly available soil datasets (e.g., gSSURGO) are largely suitable for the calculation of soil

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Adaptive Algebraic Derivative Estimation for Battery Electric Buses Energy Consumption Forecasting

The limited service life of onboard batteries for EVs is a challenge, underscoring the need for real-time battery usage prediction. This paper proposes an adaptive Algebraic Derivative Estimation (ADE) approach for forecasting the energy consumption of battery electric buses. By dynamically adjusting the sliding window length, the adaptive ADE retains the fixed-length ADE’s key advantage—namely, operating online without reliance on extensive historical datasets—while substantially bolstering forecast accuracy by actively trading estimation bias off estimation variance. Comparative experiments against both the conventional ADE with a fixed length and a representative machine learning algorithm, XGBoost, were conducted, with performance evaluated via root mean square error, mean absolute error, and the coefficient of determination. The results demonstrate that the proposed approach significantly outperforms baseline methods.

Cui, Tianyang [The University of Texas at Dallas]↗
DOE OSTI2021

A Statistics-Based Threshold for the RMS-Energy Oscillation Detector

System operators and reliability coordinators currently rely on extensive baselining studies to set thresholds for their oscillation detectors. The resulting thresholds are based largely on engineering judgment and may vary significantly between organizations. In this paper, statistical distribution theory is used to derive a detection threshold for the widely deployed root-mean-square (RMS)-energy detector. This expression provides a theoretical basis for the detector's configuration, simplifies the process of selecting the threshold, and enables improved consistency among organizations that need to coordinate during system-wide events. Three methods for calculating the threshold using synchrophasor measurements are also proposed. These methods ensure that the threshold can be calculated reliably for various applications. Tests with simulated and field-measured data demonstrate that the statistics-based threshold provides consistent detection of grid disturbances while maintaining a low probability of false alarm.

Follum, James D.↗
DOE OSTI2022

Measurement-driven, model-based estimation of residual stress and its effects on fatigue crack growth. Part 1: Validation of an eigenstrain model

The objective of this paper is to validate a measurement-driven, model-based approach to estimate residual stress (RS) in samples machined from quenched aluminum stock. Model input is derived from measurement of RS in the parent stock. Validation is performed for prismatic T-sections removed from bars at different locations. We find RS predicted agrees with RS measured, by contour and neutron diffraction methods, with root-mean-square model-measurement difference of 22 MPa. Follow-on work (in Part 2) applies the RS estimation to samples representative of aircraft structures and examines the effects of RS on fatigue crack growth in the RS-bearing samples.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-scale dynamic modeling and validation of radial flow fixed bed contactors for post-combustion CO 2 capture using bench scale and pilot plant data

Here, in this work, a multi-scale model of a radial flow fixed bed contactor packed with a carbon sorbent is developed and validated with laboratory-scale and pilot plant scale dynamic data. For the lab scale system, the model results were compared with low, medium and high gas and sweep flowrates, yielding root mean square error (RMSE) of 0.80, 0.63, 0.96 CO 2 mol%, respectively, for the outlet CO 2 concentration profile considering the entire A-D cycle. For the bed outer temperature profile, maximum RMSE was found to be 5.5 °C considering all flowrates and entire A-D cycles. An experimental campaign was developed and applied to a pilot plant at Technology Center Mongstad (TCM), Norway. Approaches were developed for pre-processing of data including consideration of the effect of gas mixing, measurement delay, and determination of cyclic steady-state conditions. Considering profiles during A-D cycles for all test runs, it was found that the maximum RMSE for pressure drop, temperature for the outer section of the bed, temperature for the middle section of the bed, and outlet CO 2 concentration profile remained less than 1.5 mbar, 3.5 °C, 2.8 °C, and 1.3 CO 2 mol%, respectively. The validated model was used to perform sensitivity studies on several key design operating variables for the adsorption-desorption cycle. It was found that the flow rate and concentration of flue gas have dominant nonlinear effects on the breakthrough time while the desorption time was strongly affected by the sweep gas flowrate for the specific sorbent being evaluated in this study.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Lithium promotion of Pt/m-ZrO 2 catalysts for low temperature water-gas shift

Low temperature water-gas shift (LTS) is an important reaction occurring in a fuel processor for producing and purifying hydrogen. Platinum supported on m-ZrO 2 belongs to a family of catalysts consisting of metal nanoparticles and an active partially reducible oxide, with the catalysis proposed to occur at the boundary between metal particles and the support. In this investigation, increasing the loading of lithium dopant increased the LTS rate up to 0.54 wt % lithium, where conversion was 2.4 times that of the unpromoted catalyst at 260°C. Further increases in lithium loading up to 1.5 wt % decreased the rate, although it remained higher than that of the unpromoted catalyst. Infrared spectroscopy and CO 2 temperature programmed desorption experiments showed three effects with increasing lithium loading: (1) lithium promoter weakened the C–H bond of formate, the proposed rate limiting step of the interfacial surface formate mechanism; (2) high levels of lithium suppressed the platinum site capacity required for hydrogen transfer; and (3) high levels of lithium increased catalyst basicity. Aspects (2) and (3) tended to inhibit desorption of product CO 2 , an acidic molecule the removal of which is metal-catalyzed. XANES and XPS experiments revealed that electron transfer to enrich Pt nanoparticles is unlikely the root cause of C–H bond weakening in formate. However, other electronic effects (e.g., electrostatic effects or molecular rearrangement due to enhanced basicity) were not ruled out.

08 HYDROGEN↗
DOE OSTI2022

Switching from batch to continuous granulation: A case study of metoprolol succinate ER tablets

Continuous manufacturing (CM) has been used to produce several immediate release drug products. No extended-release (ER) product manufactured employing CM technology has been approved yet. Herein this study investigated the critical aspects of switching from the batch mode of high shear granulation to the continuous operation of twin-screw granulation for extended-release tablets. Metoprolol succinate ER tablets was used as a model ER formulation for this purpose. A central composite design (CCD) was employed to determine the effects of high shear granulator (HSG) parameters, namely impeller speed, granulation time, and binder liquid feeding rate, on the critical granulation characteristics important for product performance. These critical granulation characteristics served as a guide for switching from the batch processing to the continuous operation for achieving the same breaking strength and dissolution for this ER metoprolol tablets. The granulation time was the most critical factor affecting the bulk properties of granules which contributed to tablet dissolution. The higher density and lower compressibility of granules were attained at the longest granulation time of 5.4 min with the fastest liquid feeding rate of 75 g/min. The granules’ density was the primary factor negatively affecting the dissolution of metoprolol tablets. However, the breaking strength of tablets confounded the effect of granules density on metoprolol dissolution. Switching the processing parameters of high shear granulation to twin-screw granulation achieved similar dissolution profiles (F2 greater than 50). The screw speed was not found to affect bulk properties of granules. The root cause of granulation failures in twin-screw granulation, such as premature consolidation, excessive swelling, poor cohesion, inconsistent shearing effects, and formation of deformed agglomerates, were identified. In conclusion, the use of critical granulation characteristics through a performance-based approach of ER tablets facilitated the switching of manufacturing of an ER formulation form batch to continuous operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Prediction and demonstration of periodic tensile cracking in rate-dependent porous cement

Periodic dilation bands are shown to occur when cylinder-shaped saturated cement specimens are subjected to rapid decompression, with the spacing between the bands scaling as a power law of the decompression time. This behavior is predicted by theory, which is specified to this scenario based on prior work that was more general and applied to compaction. Specifically, the formation of the bands is shown to coincide with periodicity that naturally arises in the effective stress when the material follows a Terzaghi-type consolidation law, although in reverse for dilation and with material deformation described by a rate-dependent viscoplastic law. When strain rate is proportional to effective stress to a power that is greater than one, periodic regions of tensile effective stress arise through the poromechanical fluid-solid coupling. The theoretically-predicted exponent of the resulting power-law relationship between dilation band spacing and unloading time successfully brackets the experimental results, for which it is observed that the exponent is slightly stronger than a square-root relationship (0.28 to 0.67) at testing temperatures of 20 °C and 90 °C. Further, these results demonstrate that rapid-depressurization leads to periodic fracturing that could, on the one hand, be detrimental to the isolation provided by cement used to seal wellbores in the petroleum industry. On the other hand, the dilation bands could also be favorable to production if generated in low-permeability reservoir rocks such as shales that are targeted for petroleum production or granites that are targeted for geothermal energy.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Silica nanocluster binding rate coefficients from molecular dynamics trajectory calculations

Oxide nanoparticle growth from vapor phase precursors occurs in high temperature aerosol reactors first via the formation of nanoclusters, which are nanometer-scale condensed-phase species composed of 10 1 -10 2 atoms. The binding rate for nanoclusters, defined as the rate at which two nanoclusters collide with and stick to one another, is hence of interest in predicting nanoparticle size distribution functions in an aerosol. We have utilized molecular dynamics (MD) trajectory calculations to determine the homogeneous (equal-sized) and heterogeneous (disparate-sized) binding rate coefficients of SiO2 (silica) nanoclusters composed of 18, 144, and 333 atoms. MD trajectory calculations incorporated all-atom models of nanoclusters using a combined Born–Huggins–Mayer-Lennard-Jones potential model, which accounts for both short range interactions and electrostatic interactions. MD calculations were utilized to determine the binding probability as a function of both initial relative velocity and impact parameter; integration of the binding probability across impact parameter and relative velocity space yields the binding rate coefficient. MD trajectory calculations reveal that the most common type of encounters between nanoclusters leading to binding are grazing collisions, i.e. instances where collision would not occur without induced dipole potential influences. The resulting binding rate coefficients are found to be extremely weakly dependent on system temperature, which is in contrast to the use of rate coefficient models which are the product of a hard-sphere collision rate coefficient and a constant enhancement factor (leading to a rate coefficient proportional to the square root of temperature). Enhancement factors defined from MD trajectory calculations fall in the range of 3–9 as system temperature decreases from 1500 K to 300 K. Furthermore, such large values suggest that potential interactions need to be considered when modeling oxide nanocluster growth in the gas phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data

Lakes provide critical water resources for human activities and ecosystems, particularly in the Mongolian Plateau (MP), which is characterized by a dry climate and a harsh environment. As a region that is sensitive to anthropogenic warming, tracking lake surface water temperature (LSWT) changes in Mongolian lakes is crucial for understanding the consequences of a warming climate on lake ecosystems. However, the long-term monitoring of LSWT is restricted by the spatiotemporal gaps in the raw imagery of remote sensing-based land surface temperature (LST), e.g., the commonly used Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. This study applied an improved gap-filling method by utilizing the discrete cosine transform-based penalized least squares (DCT-PLS) strategy in the spatial domain combined with the linear interpolation (LI) algorithm in the temporal domain. The method was applied to fill gaps in the LSWT imagery of 12 representative lakes across MP. The randomly sampled high-quality MODIS LSWT values in the spatial and temporal domains were excavated as false data gaps and considered “virtual true” validation datasets. The spatial validation results showed that the estimated LSWT for all the lake cases were comparable with the “virtual true” LSWT values, with the average values of the coefficient of determination, mean absolute error, mean square error, and root mean square error being 0.98, 0.38 °C, 0.45 °C, and 0.59 °C, respectively. Meanwhile, the error of nighttime LSWT results was relatively lower than that of daytime LSWT. For temporal interpolation validation, the LI algorithm exhibited relatively better performance and could more objectively indicate the variation in LSWT. Benefiting from the spatially and temporally well-constrained data, we analyzed the interannual and intra-annual change characteristics of the LSWTs of the 12 lakes. The long-term variations of annual and seasonal mean LSWTs in the 12 selected lakes exhibited no evident trends in 2000–2020, while presented apparent interannual fluctuations. The slight changes in the average LSWTs of the 12 selected lakes were in excellent synchronization with the surrounding LST derived from the reanalysis datasets, confirming the widely reported phenomenon of “global warming hiatus” that occurred in the early 21st century. This study improves the understanding of the LSWT variations in Mongolian lakes in response to global climate change. It has the potential to provide an effective approach for monitoring LSWT changes in other large-scale studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mapping wall-to-wall fractional cover of Arctic tundra plant functional types in Alaska using 20-m spatial resolution satellite imagery and harmonized plot observations

Estimates of fractional cover (fCover) across given land surfaces are used to assess, and often model, vegetation composition and diversity, which are crucial for understanding the health and functioning of terrestrial ecosystems. Remote sensing provides a useful means for scaling local, plot-measured fCover estimates to regional scales. Leveraging a recently synthesized and harmonized plot database, this study generated wall-to-wall maps of fCover for six Alaskan-Arctic plant functional types (PFT), including non-vascular plants, forbs, graminoids, and deciduous and evergreen shrubs, using 20-m satellite data (Sentinel-1, Sentinel-2, ArcticDEM) using a machine learning regression approach, specifically the random forest (RF) algorithm, which is well-suited for handling nonlinear relationships and high-dimensional satellite datasets. This study additionally addressed the spatio-temporal inconsistencies e.g., sampling scale, plot size, and collection year in plot measured fCover by adopting a multivariate outlier detection approach—Cook’s distance—to identify high-quality plots for model training and validation. Our approach achieves high accuracy (R 2 = 0.59–0.93, root mean squared errors = 0.02–0.10 for all PFTs) between plot-observed and satellite-derived fCover when using high-quality plot samples. The mapped fCover characterizes the spatial patterns of different PFTs across the tundra biome at a 20-m resolution, providing key information needed for improved representation of Arctic tundra vegetation in terrestrial biosphere models to better understand climate-vegetation feedback across the Arctic tundra.

Arctic tundra↗