SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Data for each figure of the article "Greater aperture counteracts effects of reduced stomatal density on WUE: a case study on sugarcane and meta-analysis" published in J. Ex. Bot.
Land resources are central to understanding the relationship between humans and their environment. We broadly define a land resource to include all the ecological resources of climate, water, soil, landforms, flora, and fauna, and all the socioeconomic systems that interact with agriculture, forestry, and other land uses within some system boundary. Understanding the vulnerability of land resources to changes in land management or climate forcing is critical to developing sustainable land management strategies. Vulnerability assessments are complex given the multiple uses of the assessments, the multi-disciplinary nature of the problem, limited understanding, the dynamic structure of vulnerability, scale issues, and problems with identifying effective vulnerability indicators. Here, we propose a novel conceptual framework for vulnerability assessments of land resources that combines the driver– pressure–state–impact–response (DPSIR) framework adopted by the European Environment Agency to describe interactions between society and the environment, and the exposure-sensitivity-adaptive capacity (ESA) framework used by the Intergovernmental Panel on Climate Change to assess impacts of climate change. The DPSIR-ESA Vulnerability Assessment (DEVA) framework operationalizes the process of assessing the vulnerability of a target system to external stressors. The DEVA framework includes the following elements: 1) Definition of the target system (Land resource), 2) Description of internal characteristics of the target system (State), 3) Description of target system vulnerability indicators (Adaptive capacity, Sensitivity), 4) Description of stressor characteristics (Drivers, Pressures), 5) Description of stressor vulnerability indicators (Exposure), 6) Description of target system response to stressors (Impacts), and 7) Description of modifications to target systems or stressors (Responses). In stating that they have “applied the DEVA framework”, analysts acknowledge that they have (a) considered the full breadth of each DEVA element, (b) have made conscious decisions to limit the scope and complexity of certain elements, and (c) can communicate both the rationale for these decisions and the impact of these decisions on the vulnerability assessment results and recommendations. The DEVA framework was refined during invited presentations and follow-up discussions from a series of Special Sessions with leading experts at two successive ASABE Annual International Meetings. Six case studies drawn from the sessions elaborate upon the DEVA framework and provide concrete examples of the key concepts. The DEVA approach gives engineers, planners, and analysts a new, flexible framework to apply a broad array of useful tools toward assessment of land resource system vulnerability.
To license new and advanced reactor designs, regulators must be convinced that their unique safety cases—relative to existing large scale reactors—have been adequately addressed by the designed reactor protection systems. In water cooled small modular reactors (SMRs), droplet entrainment in steam flow has significant implications on the progression of accident scenarios due to its compact design features, which requires representative test data applicable to SMR designs. Computer code, modeling and simulation (M&S) tools and models require adequate verification, assessment, and qualification. This includes M&S results validation against scaled empirical data within allowable uncertainty bands to gain regulatory approvals during the various stages of reactor system design, demonstration, and commercialization. However, measurement uncertainty within the empirical datasets and test data applicability ranges requires careful consideration of M&S inputs (i.e., boundary conditions, and initial conditions), and verification and validation efforts. This study focuses on uncertainty quantification in designing scaled test facilities for SMR applications with appropriate measurements and a standard data-reduction method to estimate thermal hydraulics characteristics parameters that incorporate physics phenomena of interest. In addition, this study supports the evaluation model development and assessment process using M&S that interfaces with advanced computing tools and digital twin capabilities. This will allow synchronization between experiment and modeling approaches for droplet entrainment testing and analysis, improving diagnostics, prognostics, and decision-making to accelerate regulatory approval.
In this case study analysis, we identified fungal traits that were associated with the responses of taxa to 4 global change factors: elevated CO2, warming and drying, increased precipitation, and nitrogen (N) enrichment. We developed a trait-based framework predicting that as global change increases limitation of a given nutrient, fungal taxa with traits that target that nutrient will represent a larger proportion of the community (and vice versa). In addition, we expected that warming and drying and N enrichment would generate environmental stress for fungi and may select for stress tolerance traits. We tested the framework by analyzing fungal community data from previously published field manipulations and linking taxa to functional gene traits from the MycoCosm Fungal Portal. Altogether, fungal genera tended to respond similarly to 3 elements of global change: increased precipitation, N enrichment, and warming and drying. The genera that proliferated under these changes also tended to possess functional genes for stress tolerance, which suggests that these global changes—even increases in precipitation—could have caused environmental stress that selected for certain taxa. In addition, these genera did not exhibit a strong capacity for C breakdown or P acquisition, so soil C turnover may slow down or remain unchanged following shifts in fungal community composition under global change. Since we did not find strong evidence that changes in nutrient limitation select for taxa with traits that target the more limiting nutrient, we revised our trait-based framework. The new framework sorts fungal taxa into Stress Tolerating versus C and P Targeting groups, with the global change elements of increased precipitation, warming and drying, and N enrichment selecting for the stress tolerators.
This package contains the data, simulation setups, notebooks and figures used in “Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California” (Xu et al., 2025). In this study, we selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise on coastal hydrology using the process-based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site-specific data. We designed a novel modeling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modeled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected sea level rise over the next few decades. The low-lying Yampah Marsh, the reference site, is likely to be inundated due to future sea level rise when highest tides arrive; while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.Several files can be found from this data package.1. README.md: This file describes the title, journal, co-authors, abstract, repository structure and model version.2. Simulation_Setups.zip: The file contains the model configuration files (XML format) for ATS. 3. Notebooks.zip: The file contains the Jupyter notebooks for generating the pre- and post-restoration meshes and the meshes of future scenarios. 4. Figures.zip: The file contains the figures used in the manuscript.5. Data.zip: The file contains the data used to drive the model simulations, including watershed and wetlands boundaries, mesh files and references to additional datasets (e.g., meteorological forcing, tidal dataset, DEMs, land cover, soil properties). Also, it contains water level observations at the restored wetland.
Abstract The global shift to electricity as the main energy carrier will require innovation in electrochemical energy storage (EES). EES systems are the key to the “electron energy economy,” minimizing losses and increasing reliability between energy supply and demand. However, steep challenges such as cost, cycle/calendar life, energy density, material availability, and safety limit widespread adoption of batteries for large-scale grid and vehicle applications. Battery innovation that meets today’s challenges will require new chemistries, which can originate from understanding charge transport phenomena at multiple time and length scales. The advancement of operando characterization can expedite this progress as changes can be observed during battery function. This article highlights progress in bulk and interfacial operando characterization of batteries. Specifically, a case study involving Fe 3 O 4 is provided demonstrating that combining X-ray absorption spectroscopy and isothermal microcalorimetry can provide real-time characterization of productive faradaic redox processes and parasitic interfacial reactions during (de)lithiation. Graphic abstract
Since its first demonstration in the early 2000s, the exploration of gamma-ray spectrometry (GRS) applications as a geophysical tool in archaeology remains nascent. While intentional neutron activation, which requires a gamma-ray analysis, has seen increasing use as a geoforensics technique in archaeology, little or no research has been published concerning the possibility of GRS as an industrial archaeological tool for use in exploring nuclear sites or facilities where neutron activation and surface contamination may have already occurred. Consequently, the use of GRS as a geophysical tool for the archaeological investigation of abandoned or decommissioned nuclear facilities is proposed, demonstrated, and discussed using a case study from the Nevada Test Site Nuclear Rocket Development Station.
Produced water data processed into the NEWTS data format for easy input into aqueous chemistry modeling software, including oil & gas and coal bed methane produced waters, and geothermal waters. Includes information on rare earth elements (REEs) and critical minerals (CMs). Case studies are included to demonstrate solved streams using aqueous chemistry software. An input template is provided for modeling stream data in OLI Studio. Original data from: Quillinan, Scott, Nye, Charles, Engle, Mark, Bartos, Timothy T., Neupane, Ghanashyam, Brant, Jonathan, Bagdonas, Davin, McLing, Travis, McLaughlin, J. Fred, Phillips, Erin, Hallberg, Laura L., Shahabadi, Mahdi, and Johnson, Matthew. Assessing rare earth element concentrations in geothermal and oil and gas produced waters: A potential domestic source of strategic mineral commodities (Final Report). United States: N. p., 2018. Web. doi:10.2172/1509037.
Data from the US EPA Gasification Database containing gasification effluent data from selected U.S. coal power plants. Original data from: Nguyen, Dan-Tam, Eastern Research Group. Sep 29, 2015. Analytical Database for the Steam Electric Rulemaking - DCN SE05359. https://www.regulations.gov/document/EPA-HQ-OW-2009-0819-5640 Files include: Original data tab, processed data and charge balance information in "NEWTS_EPA_Gasification_Effluent_Dataset_all_tabs.xlsx" Individual .csv files for data in format for input into aqueous chemistry modeling software (OLI Systems and Geochemist's Workbench) Data input templates for modeling streams in OLI Systems and Geochemist's Workbench Case studies for selected solved streams modeled in OLI Systems and Geochemist's Workbench
Data compiled for the study "Evaluating Offshore Legacy Wells for Geologic Carbon Storage: A Case Study from the Galveston and Brazos Areas in the Gulf of Mexico"
This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.
Abstract This study aims to develop a 4D Vertical Seismic Profile (VSP) integration workflow to improve the prediction of subsurface stress changes. The selected study site is a 5-spot pattern within the ongoing CO2-EOR operations at the Farnsworth Field Unit FWU in Ochiltree County, Texas. The specific pattern has undergone extensive geological and geomechanical characterization through the acquisition of 3D seismic data, geophysical well logs, and core. This workflow constrains a numerical hydromechanical model by applying a penalty function formed between "modeled" versus "observed" time-lapse compressional and shear seismic velocity changes. Analyses of geophysical logs and ultra-sonic measurements on core exhibit measurable sensitivities to changes in both fluid saturation and mean effective stress. These data are used to develop a site-specific rock physics model and stress-velocity relationship, which inform the numerical models used to generate the "modeled" portion of the penalty function. The "observed" portion of the penalty function is provided by a novel elastic full-waveform inversion of the available 3D baseline and three monitor surveys to produce high-quality estimates of time-lapse compressional and shear seismic velocity changes. The modeling workflow accounts sequentially for fluid substitution and stress impacts. Hydrodynamic and geomechanical properties of the 3D coupled numerical model are estimated through geostatistical integration of well log and core data with 3D seismic inversion products. Changes in seismic velocities due to fluid substitution are computed using the Biot-Gassmann workflow and site-specific rock physics. Stress impacts on time-lapse seismic velocity changes are modeled from the effective stress output of the hydromechanical model and are initially based on the velocity versus effective stress relationship extracted from core mechanical testing. Based on the principle of superposition of seismic wavefields, seismic velocity changes attributed to fluid substitution and that due to changes in mean effective stress are treated as linearly additive. The modeled results are upscaled using Backus averaging to reconcile scale discrepancies between the modeled and measured datasets to formulate the penalty function. This manuscript presents the forward modeling process and concludes that for the base case, the seismic velocity changes due to mean effective stress dominates over the seismic velocity changes attributed to fluid substitution because of the extensive range of the pressure perturbations. Successful minimization of this penalty function calibrates the coupled hydrodynamic geomechanical numerical model and affirms the suitability of acoustic time-lapse measurements such as 4D-VSP for geomechanical calibration.
This paper presents a data-driven framework for assessing and enhancing energy resilience in urban communities. The resilience assessment is based on two datasets: 1) annual aggregated power outage data and 2) 15-minute interval outage data. High-impact, low-probability (HILP) events are identified within these datasets to evaluate community resilience under extreme conditions. To enhance resilience, an optimization framework utilizing mixed integer linear programming is developed to determine the optimal sizing and placement of solar photovoltaic (PV) systems and battery energy storage systems (BESS). This method offers a cost-effective and practical solution for improving energy resilience in vulnerable communities. Furthermore, a case study of the City of Detroit in Michigan demonstrates the effectiveness of the framework through simulation and validation.
Behind-the-meter energy storage systems paired with distributed photovoltaic (DPV) - with the capability to act as both generation and load - represent a unique and disruptive power sector technology capable of providing a range of important services to customers, utilities, and the broader power system. How should regulators, utilities, and policymakers manage the range of challenges and opportunities that increased behind-the-meter energy storage deployment will bring to the power system, in particular when these systems are paired with DPV? This report is intended to offer key regulatory considerations for facilitating DPV-plus-storage programs for retail customers; relevant cases from U.S. states are provided as examples of how novel regulatory issues related to behind-the-meter energy storage systems paired with DPV are being addressed in practice. At a high level, designing a regulatory framework that aligns DPV-plus-storage deployment with larger policy objectives requires thoughtful deliberation across a range of technical and economic issues. While this report attempts to segment many of these issues into distinct topics to enhance reader understanding, in reality, DPV-plus-storage regulatory issues are all closely integrated, and design decisions on a single aspect often have broader implications. With that in mind, this report outlines a series of steps that can be employed by regulators to approach DPV-plus-storage regulatory design.
This simple Microgrid Design Toolkit (MDT) use case will provide you an example of a basic microgrid design. It will introduce basic principles of using the MDT islanded mode optimization by modifying a baseline microgrid design and performing an analysis of the results. Please reference the MDT User Guide (SAND2020-4550) for detailed instructions on how to use the tool.
This simple Microgrid Design Toolkit (MDT) use case will provide you an example of performing microgrid sizing by identifying the types and quantities of technology to be purchased for use in a microgrid. It will introduce basic principles of using the MDT microgrid sizing capability by comparing the results of two microgrids in two different markets. Please reference the MDT User Guide (SAND2020-4550) for detailed instructions on how to use the tool.
This report documents new work intended to update the current building thermal fabric software-to-software comparative test specifications and example results of ANSI/ASHRAE Standard 140-2017, Sections 5.2.1, 5.2.2, 5.2.3, and related supporting sections. The Building Energy Simulation Test and Diagnostic Method (BESTEST) test specification and example results that provide the basis for these Standard 140 sections were originally published in 1995. The state of the art in building energy simulation modeling has advanced since then. Additionally, comments on the test specification over the years highlighted ambiguities, further necessitating the update to the original work. This new work was conducted for the U.S. Department of Energy (DOE) by Argonne National Laboratory (Argonne) and National Renewable Energy Laboratory (NREL), in collaboration with a working group of international experts associated with the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Standing Standard Project Committee (SSPC) 140. SSPC 140 is responsible for ANSI/ASHRAE Standard 140. The new work, presented in this report, defined the test cases and specifications such that building energy simulation programs with time steps of one hour or less can perform the tests. Revisions to the test specification and update of example results follow the vetting process of iterative field trials established for previous BESTEST work that has been adapted for ASHRAE Standard 140.
This DOE Fossil Energy project, FEAA117, addressed materials issues relevant to qualifying and deploying a Ni-base alloy for a new application in an advanced ultra-supercritical coal-fired boiler. The goal was the deployment of Haynes International alloy Haynes® 282® for applications in superheaters, reheaters, and steam delivery pipes, by completing base metal, cross-weld and all-weld metal mechanical testing needed for an ASME Boiler and Pressure Vessel Code Case and the associated microstructural analyses needed for assurance of boiler-relevant lifetimes. The alloy also is of interest for other applications including supercritical CO₂ power generation cycles. Tensile testing was completed from 20°-927°C on the three base metal alloy 282 heats, two sets of cross-weld specimens and all weld metal specimens. A total of 148 creep tests with over 565,000 h of cumulative testing was completed on base metal, cross-weld and all weld metal specimens. This project was performed with cost share from Haynes International.