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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Wave Energy Converter Power Take-Off Modeling and Validation From Experimental Bench Tests

This article describes the implementation of a new numerical model of the power take-off system installed in the Monterey Bay Aquarium Research Institute wave energy converter, a device developed to provide power to various oceanic research missions. The simultaneous presence of hydraulic, pneumatic, and electrical subsystems in the power take-off system represents a significant challenge in forging an accurate model able to replicate the main dynamic characteristics of the system. The validation of the new numerical model is addressed by comparing simulations with the measurements obtained during a series of bench tests. Data from the bench tests show good agreement with the numerical model. The validated model provides deeper insights into the complex nonlinear dynamics of the power take-off system and will support further performance improvements in the future.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Utility Managed Distributed Energy Resources Intelligent Community - UDERMS iCommunity (Final Technical Report)

The Utility Managed Distributed Energy Resources Intelligent Community (UDERMS iCommunity) project, led by PacifiCorp and supported by the U.S. Department of Energy’s Building Technologies Office (Award No. DEEE0009782), aimed to demonstrate an integrated, utility-managed “behind-the-meter” distributed energy resource (DER) program connecting multifamily, commercial, institutional, and industrial buildings to deliver grid services and improve energy efficiency.

14 SOLAR ENERGY↗
DOE OSTI2021

Interferometric SAR modelling of near surface data to improve geological model in the Surat Basin, Australia

Here we present a study on geophysical inverse modelling for subsurface structural properties of an unconventional hydrocarbon site that was monitored previously by Interferometric Synthetic Aperture Radar (InSAR) technology for surface deformation. A static three-dimensional geomodel along with extracted property maps replicates the depth of each underlying stratigraphic unit and structural feature with the density of each geological layer. We examine the hypothesis that integration of elastic properties of each formation layer with InSAR observations in a stratified elastic medium will lead to a viscoelastic geophysical inverse problem that can be solved to estimate fractional volume change at the reservoir level. Moreover, we examine synthetic scenarios in which the elastic properties of the formations are perturbed before determining the resulting impact on the rate of surface deformation. The results show that although the slope of underlying formations, their density and depth can define the extent and pattern of a deformation signal, their properties have a marginal impact on volumetric change compared to the dense network of shallow depth Coal Seam Gas (CSG) mining wells. Besides, it is also demonstrated that the inversion of InSAR deformation maps can resolve the uncertainties associated with low-resolution seismic interpretation as well as filling the data gaps within seismic acquisitions. A significant contribution of this investigation to the geological basin modelling involves a) introducing a remote and non-invasive technology such as InSAR to improve geophysical mapping of subsurface structures such as faults in areas with sparse or no reflective seismic information, and b) applying a multi-layer viscoelastic geophysical source model for an unconventional hydrocarbon reservoir such as CSG.

58 GEOSCIENCES↗
DOE OSTI2023

SPRUCE Peat Mercury, Methylmercury and Sulfur Concentrations from Experimental Plot Cores, 2012

This data set reports the results of analyses of peat core samples for total mercury and methylmercury, as well as carbon, nitrogen and sulfur. Samples were collected as part of a larger sampling campaign from the SPRUCE experimental study plots located in the S1-Bog. From 2012-08-13 to 2012-10-15, a team of SPRUCE investigators and collaborators collected core samples of peat in the SPRUCE experimental plots. The goal was to characterize the biological, physical, and chemical characteristics of peat, and how those characteristics changed throughout the depth profile of the bog, prior to the initialization of the SPRUCE experimental warming and CO2 treatments. Cores were collected from 16 experimental plots; peat cores were collected from the hummock and hollow surfaces to depths of 300 cm in 10 cm, 25, and 50 cm increments (Pierce et al, 2022). Three replicate cores were collected from both hummock and hollow locations in each plot. The coring locations within each plot were mapped. This dataset contains one file in comma separated (*.csv) format. User Note: The coring descriptions and some reported data are the same as in the related data set, Iverson et al. (2014). Samples for mercury and carbon, nitrogen and sulfur analyses by the University of Minnesota were collected as part of this sampling campaign.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Heating effects on pyrogenic organic matter mass loss and temperature in a sand matrix in a lab setting from 2022

This dataset contains data associated with the preprint “A laboratory method for simulating the effects of subsequent fires on pyrogenic organic matter at different exposure depths in a sand matrix” (https://doi.org/10.1101/2024.07.30.605814), which has been accepted for publication in the International Journal of Wildland Fire. The dataset was generated to investigate the effects of subsequent fires on preexisting pyrogenic organic matter (PyOM) at different soil depths. Specifically, we designed a laboratory method to simulate soil heating from above, applying realistic heat flux profiles (High, Low, Control) derived from jack pine (Pinus banksiana Lamb.) log burns. Using a cone calorimeter, these profiles were applied to buried jack pine PyOM (produced at 350°C) in a sand matrix pyrocosm to examine PyOM mass loss at different depths (surface, 1 cm, 5 cm). Each treatment (e.g., High heat flux at 1 cm depth) was applied once to five replicates in a pyrocosm.The dataset includes mass loss fraction of PyOM and time-series temperature profiles (measured with type K thermocouples). Additionally, calibration datasets for high and low heat flux profiles are provided, including programmed heat flux profile data and three sets of calibration results. All datasets are in .csv format and were analyzed in R using code found at https://github.com/MengmengLuo/Reburning-pyrogenic-organic-matter-A-laboratory-method-for-dosing-dynamic-heat-fluxes-from-above. This dataset supports research on PyOM transformations during subsequent fires, and methodological advancements in simulating soil heating. It can be used to explore fire-induced PyOM alterations across different fire intensities and soil depths.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Measurement Error and Resolution in Quantitative Stable Isotope Probing: Implications for Experimental Design

Quantitative stable isotope probing (qSIP) estimates isotope tracer incorporation into DNA of individual microbes and can link microbial biodiversity and biogeochemistry in complex communities. As with any quantitative estimation technique, qSIP involves measurement error, and a fuller understanding of error, precision, and statistical power benefits qSIP experimental design and data interpretation. We used several qSIP data sets—from soil and seawater microbiomes—to evaluate how variance in isotope incorporation estimates depends on organism abundance and resolution of the density fractionation scheme. We assessed statistical power for replicated qSIP studies, plus sensitivity and specificity for unreplicated designs. As a taxon’s abundance increases, the variance of its weighted mean density declines. Nine fractions appear to be a reasonable trade-off between cost and precision for most qSIP applications. Increasing the number of density fractions beyond that reduces variance, although the magnitude of this benefit declines with additional fractions. Our analysis suggests that, if a taxon has an isotope enrichment of 10 atom% excess, there is a 60% chance that this will be detected as significantly different from zero (with alpha 0.1). With five replicates, isotope enrichment of 5 atom% could be detected with power (0.6) and alpha (0.1). Finally, we illustrate the importance of internal standards, which can help to calibrate per sample conversions of %GC to mean weighted density. These results should benefit researchers designing future SIP experiments and provide a useful reference for metagenomic SIP applications where both financial and computational limitations constrain experimental scope.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Geothermal Play Fairway Analysis of Low-Temperature Resources for Sedimentary Basin Geothermal Play Types: An Example in the Denver Basin

This project is part of a nationwide effort to highlight the advantages of incorporating low-temperature geothermal resource evaluation into the implementation of combined heat and power (CHP), and geothermal direct use (GDU) technologies (e.g., space heating and/or cooling). The initiative aims to hasten the nation's decarbonization process by exploring the potential for using low-temperature geothermal resources (< 150 Degrees Celsius) in selected sedimentary basins that have several population centers. The Play Fairway Analysis (PFA) techniques were modified from earlier studies of sedimentary basin geothermal play types (SBGPTs) that assessed the viability of low-temperature resources. The decision-making process for leveraging low-temperature geothermal resources for GDU and CHP applications is complex and considers a variety of factors, including geological, economic, and risk criteria. This study covers workflows, relevant datasets, python code, and both common and composite maps used to create low-temperature geothermal resource favorability maps for the Denver Basin, which extends across Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. The proposed geothermal PFA approach for low-temperature geothermal resources includes: (1) identifying available relevant data and grouping data sets into PFA criteria (e.g., geological, economic, and risk criteria); (2) analyzing data gaps enable future focalized exploration; (3) performing uncertainty quantification; (4) weighting relevant data; (5) developing favorability and common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection. This project will facilitate future deployment of CHP and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources in sedimentary basins.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

From Reads to Function Workshop - Milano 2026

The Bicocca Sampling Days (BSDs) model offers a reproducible “citizen science” framework integrating research, education, and public engagement through large-scale microbiome sampling, followed by a workshop of data analysis on select samples. We identified 9 bacterial and archaeal metagenome-assembled genomes from six soil samples across three separate sampling days in two approaches with indidivual sample and replicate co-assembly spanning three unique classes, providing genomic insights into microbial nutrient cycling in these systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing

Wheat, being the third largest U.S. crop and the principal food grain, faces significant risks from climate extremes such as drought. This necessitates identifying and developing methods for early water-stress detection to prevent yield loss and improve water-use efficiency. This study investigates the potential of hyperspectral imaging to detect the early stages of drought stress in wheat. The goal is to utilize this technology as a tool for screening and selecting drought-tolerant wheat genotypes in breeding programs. Additionally, this research aims to systematically evaluate the effectiveness of various existing sensors and methods for detecting early stages of water stress. The experiment was conducted in a durum wheat experimental field trial in Maricopa, Arizona, in the spring of 2019 and included well-watered and water-limited treatments of a panel of 224 replicated durum wheat genotypes. Spectral indices derived from hyperspectral imagery were compared against other plant-level indicators of water stress such as Photosystem II (PSII) and relative water content (RWC) data derived from proximal sensors. Our findings showed a 12% drop in photosynthetic activity in the most affected genotypes when compared to the least affected. The Leaf Water Vegetation Index 1 (LWVI1) highlighted differences between drought-resistant and drought-susceptible genotypes. Drought-resistant genotypes retained 43.36% more water in leaves under well-watered conditions compared to water-limited conditions, while drought-susceptible genotypes retained only 15.69% more. The LWVI1 and LWVI2 indices, aligned with the RWC measurements, revealed a strong inverse correlation in the susceptible genotypes, underscoring their heightened sensitivity to water stress in earlier stages. Several genotypes previously classified based on their drought resistance showed spectral indices deviating from expectations. Results from this research can aid farmers in improving crop yields by informing early management practices. Moreover, this research offers wheat breeders insights into the selection of drought-tolerant genotypes, a requirement that is becoming increasingly important as weather patterns continue to change.

Roy, Bishal (ORCID:0000000199125505)↗
DOE OSTI2020

Mesoscale informed parameter estimation through machine learning: A case-study in fracture modeling

Scale bridging is a critical need in computational sciences, where the modeling community has developed accurate physics models from first principles, of processes at lower length and time scales that influence the behavior at the higher scales of interest. However, it is not computationally feasible to incorporate all of the lower length scale physics directly into upscaled models. This is an area where machine learning has shown promise in building emulators of the lower length scale models, which incur a mere fraction of the computational cost of the original higher fidelity models. We demonstrate the use of machine learning using an example in materials science estimating continuum scale parameters by emulating, with uncertainties, complicated mesoscale physics. Additionally, we describe a new framework to emulate the fine scale physics, especially in the presence of microstructures, using machine learning, and showcase its usefulness by providing an example from modeling fracture propagation. Our approach can be thought of as a data-driven dimension reduction technique that yields probabilistic emulators. Our results show well-calibrated predictions for the quantities of interests in a low-strain simulation of fracture propagation at the mesoscale level. Furthermore, on average, we achieve ~10% relative errors on time-varying quantities like total damage and maximum stresses. Successfully replicating mesoscale scale physics within the continuum models is a crucial step towards predictive capability in multi-scale problems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Test–retest reliability for a social discounting of personal information task

Increasing cybercrime rates means identifying potential victims is critically important. Social discounting tasks show that individuals share less personally identifying information as social distance increases. However, the test–retest reliability and uniqueness of this measure is unclear. The current study assessed social discounting for personally identifying information (SDPII), delay discounting, risk taking, and personality at two measurement waves 30 days apart for 64 undergraduate students. Test–retest reliability was statistically significant for the SDPII and all other measures, replicating previous studies. SDPII rates were not significantly correlated with other measures during both measurement waves, showing discriminant validity. SDPII rates were lower than those reported in a previous study but were still well described by a hyperbolic discounting function, suggesting replicability across studies. Furthermore, the high test–retest reliability, uniqueness, and replicability of the SDPII suggests that it may quantitatively identify cybercrime victimization. Future research should test which measure or combination of measures can accurately predict scam and cybercrime victimization to inform data-based interventions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Numerical Investigation of Observational Flux Partitioning Methods for Water Vapor and Carbon Dioxide

Abstract While yearly budgets of CO 2 flux (F c ) and evapotranspiration (ET) above vegetation can be readily obtained from eddy‐covariance measurements, the separate quantification of their soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. In this work, we investigate four methods to partition observed total fluxes into soil and plant sources: two new and two existing approaches that are based solely on analysis of conventional high frequency eddy‐covariance (EC) data. The physical validity of the assumptions of all four methods, as well as their performance under different scenarios, are tested with the aid of large‐eddy simulations, which are used to replicate eddy‐covariance field experiments. Our results indicate that canopies with large, exposed soil patches increase the mixing and correlation of scalars; this negatively impacts the performance of the partitioning methods, all of which require some degree of uncorrelatedness between CO 2 and water vapor. In addition, best performances for all partitioning methods were found when all four flux components are non‐negligible, and measurements are collected close to the canopy top. Methods relying on the water‐use efficiency (W) perform better whenWis known a priori, but are shown to be very sensitive to uncertainties in this input variable especially when canopy fluxes dominate. We conclude by showing how the correlation coefficient between CO 2 and water vapor can be used to infer the reliability of differentWparameterizations.

Environmental Sciences & Ecology↗
DOE OSTI2024

From Sim to Real: A Pipeline for Training and Deploying Traffic Smoothing Cruise Controllers

Designing and validating controllers for connected and automated vehicles to enhance traffic flow presents significant challenges, from the complexity of replicating real-world stop-and-go traffic dynamics in simulation, to the intricacies involved in transitioning from simulation to actual deployment. In this work, we present a full pipeline from data collection to controller deployment. Specifically, we collect 772 km of driving data from the I-24 in Tennessee, and use it to build a one-lane simulator, placing simulated vehicles behind real-world trajectories. Using policy-gradient methods with an asymmetric critic, we improve fuel efficiency by over 10% when simulating congested scenarios. Our comprehensive approach includes reinforcement learning for controller training, software verification, hardware validation and setup, and navigating various sim-to-real challenges. Furthermore, we analyze the controller's behavior and wave-smoothing properties, and deploy it on four Toyota Rav4’s in a real-world validation experiment on the I-24. Lastly, we release the driving dataset, the simulator and the trained controller, to enable future benchmarking and controller design.

42 ENGINEERING↗
DOE OSTI2024

Tropical root responses to global changes: A synthesis

Tropical ecosystems face escalating global change. These shifts can disrupt tropical forests' carbon (C) balance and impact root dynamics. Since roots perform essential functions such as resource acquisition and tissue protection, root responses can inform about the strategies and vulnerabilities of ecosystems facing present and future global changes. However, root trait dynamics are poorly understood, especially in tropical ecosystems. We analyzed existing research on tropical root responses to key global change drivers: warming, drought, flooding, cyclones, nitrogen (N) deposition, elevated (e) CO 2 , and fires. Based on tree species- and community-level literature, we obtained 266 root trait observations from 93 studies across 24 tropical countries. We found differences in the proportion of root responsiveness to global change among different global change drivers but not among root categories. In particular, we observed that tropical root systems responded to warming and eCO 2 by increasing root biomass in species-scale studies. Drought increased the root: shoot ratio with no change in root biomass, indicating a decline in aboveground biomass. Despite N deposition being the most studied global change driver, it had some of the most variable effects on root characteristics, with few predictable responses. Episodic disturbances such as cyclones, fires, and flooding consistently resulted in a change in root trait expressions, with cyclones and fires increasing root production, potentially due to shifts in plant community and nutrient inputs, while flooding changed plant regulatory metabolisms due to low oxygen conditions. The data available to date clearly show that tropical forest root characteristics and dynamics are responding to global change, although in ways that are not always predictable. This synthesis indicates the need for replicated studies across root characteristics at species and community scales under different global change factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Development and Validation of a Simulation Testbed for the Intelligent Building Agents Laboratory (IBAL) Using TRNSYS

This paper documents the development and validation of a dynamic primary cooling and thermal storage system simulation testbed. The system simulation testbed, sIBAL, is based on the Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST), which is a research infrastructure and testbed for the development, evaluation, and demonstration of intelligent control algorithms. The sIBAL testbed developed in this project will serve as a virtual twin of the real facility for future control algorithm development. The details of the methodologies used to develop and validate the simulation testbed, which replicates the dynamic behaviors of the primary cooling and ice storage system in the IBAL facility, are presented. The simulation testbed was developed in TRNSYS using built-in component models and MATLAB functions to replicate the two water-cooled chillers, a thermal storage tank, pumps, valves and other components for four different operation modes. Experiments on IBAL components were designed and executed to generate experimental data for model development and verification of the simulation platform. The validation of the simulation results was carried out in two phases: 1) independent component simulations for the chillers and thermal storage tank, and 2) a combined testbed simulation of the entire hydronic system. Comparison of simulation results to the experimental data obtained from the IBAL facility showed errors within 1 °C for the temperatures outputs of both the chiller and the thermal storage model. The error is within an acceptable range for further intelligent control algorithms development. The findings from the study are summarized and presented along with areas where additional research is needed. In addition, data filtering procedures and model refinement measures utilized to improve the accuracy and accelerate the computation time of the simulation are presented.

cooling systems↗
DOE OSTI2024

Low-Temperature Geothermal Play Fairway Analysis for the Denver Basin: Preprint

This project is part of a national initiative to showcase the benefits of incorporating low-temperature geothermal resource assessment into the deployment of geothermal heating and cooling (GHC), combined heat and power (CHP), and geothermal direct use (GDU) technologies. The initiative was established to accelerate the country's decarbonization efforts by identifying potential for low-temperature geothermal resource utilization (< 150 Degrees Celsius, i.e., GHC, CHP, and GDU) in selected sedimentary basins with numerous population centers. The Play Fairway Analysis (PFA) methodologies in this study were adapted from previous PFA investigations of sedimentary basin geothermal play types (SBGPTs) that evaluated the potential for low-temperature resources (< 150 Degrees Celsius). Workflows, relevant datasets, python code, common and composite geological criteria maps are utilized to develop low-temperature geothermal resource favorability maps for the Denver Basin, a sedimentary basin spanning Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. To facilitate future assessment of low-temperature geothermal resources in SBGPTs, this project provides PFA workflows, data, tools, and favorability maps that will ultimately support the utilization of low-temperature geothermal resources in sedimentary basins.

Denver Basin↗
DOE OSTI2025

Low-Temperature Geothermal Play Fairway Analysis for the Denver Basin

This project is part of a national initiative to showcase the benefits of incorporating low-temperature geothermal resource assessment into the deployment of geothermal heating, combined heat and power (CHP), and geothermal direct-use (GDU) technologies. The initiative was established to accelerate the country's decarbonization efforts by identifying potential for low-temperature geothermal resource utilization (<150 degrees C, e.g., CHP and GDU) in selected sedimentary basins with numerous population centers. The play fairway analysis (PFA) methodologies in this study were adapted from previous PFA investigations of sedimentary basin geothermal play types (SBGPTs) that evaluated the potential for low-temperature resources (<150 degrees C). Workflows, relevant datasets, a new Python library, and common and composite geological criteria maps are utilized to develop low-temperature geothermal resource favorability maps for the Denver Basin, a sedimentary basin spanning Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. To facilitate future assessment of low-temperature geothermal resources in SBGPTs, this project provides PFA workflows, data, tools, and favorability maps that will ultimately support the utilization of low-temperature geothermal resources in sedimentary basins.

combined heat and power↗
DOE OSTI2026

Next-Generation Sequencing Data from a CUT&RUN Study of R. toruloides IFO0880 Cse4 and Orc1 Binding Sites

Rhodotorula toruloides has been increasingly explored as a host for bioproduction of lipids, fatty acid derivatives and terpenoids. Various genetic tools have been developed, but neither a centromere nor an autonomously replicating sequence (ARS), both necessary elements for stable episomal plasmid maintenance, has yet been reported. In this study, cleavage under targets and release using nuclease (CUT&RUN), a method used for genome-wide mapping of DNA–protein interactions, was used to identify R. toruloides IFO0880 genomic regions associated with the centromeric histone H3 protein Cse4, a marker of centromeric DNA. Fifteen putative centromeres ranging from 8 to 19 kb in length were identified and analyzed, and four were tested for, but did not show, ARS activity. These centromeric sequences contained below average GC content, corresponded to transcriptional cold spots, were primarily nonrepetitive and shared some vestigial transposon-related sequences but otherwise did not show significant sequence conservation. Future efforts to identify an ARS in this yeast can utilize these centromeric DNA sequences to improve the stability of episomal plasmids derived from putative ARS elements.

Genome Engineering↗