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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Comparative analysis of nutrient concentrations in generalist and specialist tree species and soils, Manaus, Brazil

This dataset was collected near Manaus, Brazil, at ZF-2 site, inside the North-South transect plots from 20221011 to 20221020. Measurements were made on specialists and generalist tree species along topographic gradient (in upland high-clay content soils of plateaus and high sandy content and partially flooded soils of valleys). We selected nine species (with four replicates each, totaling 35 individuals) occurring in different topographic positions: three plateau specialists, three valley specialists, and three generalists, where leaf and trunk samples were collected from each individual, and soil samples for carbon and nutrient analysis and quantification. Three soil pits were opened around each sample tree, about one meter apart (total of 105 soil pits each 60-cm deep), where soil samples were collected at four depths: 0-5, 5-10, 10-30 and 30-50 cm. In each of the three pits around each tree, one single sample was taken at each depth and combined to obtain a composite sample per depth per individual tree (35 trees × 4 depths = 140 soil samples). The files “Plant_Nutrient_Concentrations_NS_Transect_Manaus.csv” and “Soil_Nutrient_Concentrations_NS_Transect_Manaus.csv” contain the nutrient concentration data from plant and soil material, respectively. Additionally, the file “Sample_Info.csv” contains details about each variable including units and data type. The file “Species_Info.csv” includes information about each sampled individual, such as species, family, diameter at the breast height (DBH), and more. The dataset is ready to be used in any programming language like python or R. This dataset was originally published on the NGEE Tropics Archive and is being mirrored on ESS-DIVE for long-term archival Acknowledgement: Funding for NGEE-Tropics data resources was provided by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Duke Energy’s Integrated System and Operations Planning: A comparative analysis of integrated planning practices

Lawrence Berkeley National Laboratory and the National Renewable Energy Laboratory provided technical assistance to the South Carolina Office of Regulatory Staff to examine how Duke Energy’s Integrated System Operations Planning (ISOP) framework interacts with other electricity planning processes in South Carolina. While this report was prepared for the South Carolina ORS, the information contained herein may be useful to audiences in other states who are interested in IDP, including public utility commissions, state energy offices, other state agencies, utilities, and stakeholders. The report discusses how to access the ISOP process diagram created for the report, provides observations about Duke Energy’s ISOP from our interviews and review of publicly available materials; and assesses ISOP, based on best practices for integrated distribution planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Comparative Analysis of HEATNETS for Geothermal Network Performance

Thermal energy networks (TENs), also known as 5th generation district energy systems, or more specifically geothermal networks when exchanging heat with geothermal boreholes, are an important technology for decarbonization. In these networks an ambient loop connects buildings and thermal sources, such as a borehole field, to exchange energy and maintain a desired loop temperature. Water-source heat pumps are used at the buildings to connect to the ambient or thermal loop to meet to the building heating and cooling loads and maintain comfort. A semi-transient, reduced-order technical model and techno-economic model, called HEATNETS, has been developed at NREL that captures the flow of energy around a TEN. In this work, a comparison of the HEATNETS technical model and a well-known coding platform used for modeling geothermal networks, TRNSYS, has been completed for a proposed geothermal network as a verification and validation process. Hourly data provided from the TRNSYS simulation included building loads, pumping power, heat pump power, temperature entering and leaving the borehole field, and mass flow rates. The hourly borehole temperatures were used to create a linear regression model utilized in HEATNETS to estimate the borehole field heat exchange. The building loads and mass flow rates were direct inputs to HEATNETS while the pumping power, heat pump power, borehole temperatures, and coefficients of performance were all simulated and calculated by HEATNETS, allowing for direct comparison of the thermal energy transfer HEATNETS considers the full process from design inputs to economic outputs and can provide modeling options for high-level initial system design and operational optimization. This study focuses on a validation of HEATNETS using results from TRNSYS. HEATNETS is not intended to replace other modeling tools, but this work demonstrates, via a comparison with an industry standard code, that HEATNETS can be a unique, high-level and rapid modeling tool for estimating the performance of a full geothermal network system.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

A Comparative Analysis of Infrastructure-Based Perception Sensors for Intelligent Transportation Systems

The rise of privatized and public investment in smart city infrastructure and intelligent transportation systems has generated a heightened demand for perception sensors that effectively track and detect objects while being reliable in diverse weather and lighting conditions. This growing demand for perception sensors has accelerated their development and enhanced their capabilities. With these new capabilities, it is challenging to determine the most suitable sensing unit to use in each situation. Therefore, it is essential to have a comprehensive understanding of the benefits and limitations of each sensing unit to effectively leverage their capabilities. The purpose of this paper is to provide a detailed evaluation of various perception sensors. Additionally, this paper will demonstrate the benefits of combining multiple perception sensors, which complement each other by addressing data gaps inherent to single-sensor systems, to facilitate the creation of a digital twin that models the real world. The Infrastructure, Perception, and Control (IPC) team will conduct data analysis using data collected through field testing at traffic intersections in Colorado Springs, Colorado, to make comparisons between sensors. This research aims to provide clear and concise information about modern perception systems, which will support the development of intelligent transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Comparative Analysis of Microbial Diversity Across Temperature Gradients in Hot Springs From Yellowstone and Iceland

Geothermal hot springs are a natural setting to study microbial adaptation to a wide range of temperatures reaching up to boiling. Temperature gradients lead to distinct microbial communities that inhabit their optimum niches. We sampled three alkaline, high temperature (80–100°C) hot springs in Yellowstone and Iceland that had cooling outflows and whose microbial communities had not been studied previously. The microbial composition in sediments and mats was determined by DNA sequencing of rRNA gene amplicons. Over three dozen phyla of Archaea and Bacteria were identified, representing over 1700 distinct organisms. We observed a significant non-linear reduction in the number of microbial taxa as the temperature increased from warm (38°C) to boiling. At high taxonomic levels, the community structure was similar between the Yellowstone and Iceland hot springs. We identified potential endemism at the genus level, especially in thermophilic phototrophs, which may have been potentially driven by distinct environmental conditions and dispersal limitations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Comparative Analysis via CFD Simulation on the Impact of Graphite Anode Morphologies on the Discharge of a Lithium-Ion Battery

The morphology of electrode materials plays a crucial role in determining the performance of lithium-ion batteries. Traditional computational models often simplify graphite flakes as uniformly sized spheres, which limits their predictive accuracy. In this study, we present a computational workflow that overcomes these limitations by incorporating a more realistic representation of graphite morphologies. This workflow is designed to be flexible and reproducible, enabling efficient evaluation of electrochemical performance across diverse material structures. By exploring different graphite morphologies, our approach accelerates the optimization of material preparation techniques and processing conditions. Our findings reveal that incorporating greater morphological complexity leads to significant deviations from classical model predictions. Instead, our refined model offers a more accurate representation of battery discharge behavior, closely aligning with experimental data. This improvement underscores the importance of detailed morphological descriptions in advancing battery design and performance assessments. To promote accessibility and reproducibility, we provide the developed code for seamless integration with the COMSOL API, allowing researchers to implement and adapt it easily. This computational framework serves as a valuable tool for investigating the impact of graphite morphology on battery performance, bridging the gap between theoretical modeling and experimental validation to enhance lithium-ion battery technology.

25 ENERGY STORAGE↗
DOE OSTI2021

Comparative Analysis of Machine Learning Models for Day-Ahead Photovoltaic Power Production Forecasting

A main challenge for integrating the intermittent photovoltaic (PV) power generation remains the accuracy of day-ahead forecasts and the establishment of robust performing methods. The purpose of this work is to address these technological challenges by evaluating the day-ahead PV production forecasting performance of different machine learning models under different supervised learning regimes and minimal input features. Specifically, the day-ahead forecasting capability of Bayesian neural network (BNN), support vector regression (SVR), and regression tree (RT) models was investigated by employing the same dataset for training and performance verification, thus enabling a valid comparison. The training regime analysis demonstrated that the performance of the investigated models was strongly dependent on the timeframe of the train set, training data sequence, and application of irradiance condition filters. Furthermore, accurate results were obtained utilizing only the measured power output and other calculated parameters for training. Consequently, useful information is provided for establishing a robust day-ahead forecasting methodology that utilizes calculated input parameters and an optimal supervised learning approach. Finally, the obtained results demonstrated that the optimally constructed BNN outperformed all other machine learning models achieving forecasting accuracies lower than 5%.

14 SOLAR ENERGY↗
DOE OSTI2025

A Comparative Analysis of Waste-as-a-Feedstock Accounting Methods in Life Cycle Assessments

Global waste generation is a ubiquitous challenge, driving a paradigm shift towards viewing waste as a valuable resource for a circular economy across diverse sectors. While innovative waste-to-resource pathways are crucial, rigorous Life Cycle Assessment (LCA) is essential to ensure the pathways are an important part of current practices. However, LCA application to waste valorization varies, leading to incomparable results due to differing methodological choices. This paper examines three key nuances in waste-as-resource LCAs: the zero-burden assumption, the biogenic carbon neutrality assumption, and the benchmark assumption for emissions avoidance. Using a waste gasification to hydrogen case study, we demonstrate how these methodological decisions impact LCA outcomes. Our findings reveal that waste composition significantly influences the results and highlight challenges associated with biogenic carbon accounting under various system boundary assumptions. Emissions avoidance accounting requires multi-functional unit perspectives and robust benchmark selection. This paper clarifies these accounting approaches, empirically illustrates their influence, and discusses broad implications for accurate sustainability assessment, emphasizing the critical role of transparent LCA choices for effective policy and investment in circular economy solutions.

LCA method↗
DOE OSTI2020

Comparative Analysis of Thrombin Calibration Algorithms and Correction for Thrombin-α2macroglobulin Activity

Background: The thrombin generation (TG) test is useful for characterizing global hemostasis potential, but fluorescence substrate artifacts, such as thrombin-α2macroglobulin (T-α2MG) signal, inner filter effect (IFE), substrate consumption, and calibration algorithms have been suggested as sources of intra- and inter-laboratory variance, which may limit its clinical utility. Methods: Effects of internal vs. external normalization, IFE and T-α2MG on TG curves in normal plasma supplemented with coagulation factors, thrombomodulin, and tissue factor were studied using the Calibrated Automated Thrombinography (CAT; Diagnostica Stago, Parsippany, NJ, USA) and in-house software. Results: The various calibration methods demonstrated no significant difference in producing TG curves, nor increased the robustness of the TG assay. Several TG parameters, including thrombin peak height (TPH), produced from internal linear calibration did not differ significantly from uncalibrated TG parameters. Further, TPH values from internal linear and nonlinear calibration with or without T-α2MG correction correlated well with TPH from external calibration. Higher coefficients of variation (CVs) for TPH values were observed in both platelet-free and platelet-rich plasma with added thrombomodulin. Conclusions: Our work suggests minimal differences between distinct computational approaches toward calibrating and correcting fluorescence signals into TG levels, with most samples returning similar or equivalent TPH results.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Comparative Analysis of In Vitro Responses and Regeneration between Diverse Bioenergy Sorghum Genotypes

Sorghum has been considered a recalcitrant plant in vitro and suffers from a lack of regeneration protocols that function broadly and efficiently across a range of genotypes. This study was initiated to identify differential genotype-in vitro protocol responses across a range of bioenergy sorghum parental lines and the common grain sorghum genotype Tx430 in order to characterize response profiles for use in future genetic studies. Two different in vitro protocols, LG and WU, were used for comparisons. Distinct genotype-protocol responses were observed, and the WU protocol performed significantly better for plantlet regeneration. Most bioenergy genotypes performed as well, if not better than Tx430, with Rio and PI329311 as the top regenerating lines. Genotypes displayed protocol-dependent, differential phenolic exudation responses, as indicated by medium browning. During the callus induction phase, genotypes prone to medium browning exhibited a response on WU medium which was either equal or greater than on LG medium. Genotype- and protocol-dependent albino plantlet regeneration was also noted, with three of the bioenergy genotypes showing albino plantlet regeneration. Grassl, Rio and Pink Kafir were susceptible to albino plantlet regeneration, with the response strongly associated with the WU protocol. These bioenergy parental genotypes, and their differential responses under two in vitro protocols, provide tools to further explore and assess the role of genetic loci, candidate genes, and allelic variants in the regulation of in vitro responsiveness in sorghum.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Comparative Analysis of Hotspot Stress Endurance in Pristine and Thermal Cycled Prestressed Glass–Glass Photovoltaic Modules

Hotspots pose a significant long-term reliability challenge in photovoltaic (PV) modules that can have a detrimental impact on the efficiency, safety, and financial viability of a PV system. This paper aims to evaluate the endurance of hotspot stress in pristine and prestressed glass–glass (GG) modules. The accelerated prestressing was conducted for 600 thermal cycles (TC600) to represent decades of field exposure. GG modules are quickly becoming an alternative to the traditional glass–backsheet (GB) modules that have been the industry standard. Unlike other conventional studies that subject only pristine modules to hotspot stress, this paper evaluates the performance of an accelerated/simulated field-aged GG module (using TC600) and a pristine GG module. Pre- and post-characterizations were performed before and after each test to determine changes in electrical performance and observe any defects in GG modules. During the hotspot test, an approximately 200 °C maximum cell temperature was observed with a cell shading of 25% (the worst-case shading ratio). After the hotspot test, electroluminescence imaging indicated that most cells in the prestressed GG module exhibited severe damage whereas no significant defects were evident in the pristine GG module where the prestressed GG module degraded 8.2% and the pristine GG module degraded 1.5% in maximum power. These findings are critical for the industry, considering that GG bifacial modules will dominate the market.

14 SOLAR ENERGY↗
DOE OSTI2025

Characterisation and comparative analysis of mitochondrial genomes of false, yellow, black and blushing morels provide insights on their structure and evolution

Morchella species have considerable significance in terrestrial ecosystems, exhibiting a range of ecological lifestyles along the saprotrophism-to-symbiosis continuum. However, the mitochondrial genomes of these ascomycetous fungi have not been thoroughly studied, thereby impeding a comprehensive understanding of their genetic makeup and ecological role. In this study, we analysed the mitogenomes of 30 Morchellaceae species, including yellow, black, blushing and false morels. These mitogenomes are either circular or linear DNA molecules with lengths ranging from 217 to 565 kbp and GC content ranging from 38% to 48%. Fifteen core protein-coding genes, 28–37 tRNA genes and 3–8 rRNA genes were identified in these Morchellaceae mitogenomes. The gene order demonstrated a high level of conservation, with the cox1 gene consistently positioned adjacent to the rnS gene and cob gene flanked by apt genes. Some exceptions were observed, such as the rearrangement of atp6 and rps3 in Morchella importuna and the reversed order of atp6 and atp8 in certain morel mitogenomes. However, the arrangement of the tRNA genes remains conserved. We additionally investigated the distribution and phylogeny of homing endonuclease genes (HEGs) of the LAGLIDADG (LAGs) and GIY-YIG (GIYs) families. A total of 925 LAG and GIY sequences were detected, with individual species containing 19–48HEGs. These HEGs were primarily located in the cox1, cob, cox2 and nad5 introns and their presence and distribution displayed significant diversity amongst morel species. These elements significantly contribute to shaping their mitogenome diversity. Overall, this study provides novel insights into the phylogeny and evolution of the Morchellaceae.

59 BASIC BIOLOGICAL SCIENCES↗