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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 OSTI2022

Analysis of the Selective Flotation of Elemental Gold from Pyrite Using Diisobutyl Monothiophosphate

The gold contained in copper ores is an important resource for the gold industry. In some cases, elemental gold is present and can be recovered by selective flotation. It has been reported that the gold grade and recovery can be increased, without sacrificing the copper recovery, by replacing AERO 3477 (diisobutyl dithiophosphate (DTP)) with AERO 7249 (mixture of diisobutyl monothiophosphate (MTP) and diisobutyl dithiophosphate (DTP)) as the main collector. The fundamental understanding of the improvement in selectivity with the addition of MTP in the flotation of elemental gold from pyrite is limited and is the subject of this paper. In this regard, the hydrophobicity and selectivity of DTP and MTP in the flotation of pyrite and gold are compared and discussed. Density functional theory (DFT) was used to examine the electron density, reactivity, highest occupied molecular orbital (HOMO), and lowest unoccupied molecular orbital (LUMO) of the MTP and DTP collectors. The interaction energies for the adsorption of MTP and DTP from fresh pyrite, oxidized pyrite and gold surfaces were calculated and discussed with respect to the experimental results reported in the literature. Molecular dynamics simulation (MDS) was used to examine the adsorption state of MTP and DTP on the pyrite (100) and Au (111) surfaces.

58 GEOSCIENCES↗
DOE OSTI2025

Characterization of Gulf Stream energy resources: A 30-year high-resolution simulation study

The strength and proximity of the Gulf Stream (GS) along the U.S. coast offers opportunities for marine energy extraction. Leveraging high-resolution (up to 400 m) long-term (30-year) hindcasts based on an unstructured grid model, this study characterizes the energy potential of the GS in two viable locations: the Florida Straits (FS) and Cape Hatteras (CH). Results reveal distinct characteristics in the kinetic energy flux (KEF) and kinetic energy density (KED) for the two regions. The 30-year mean KEF at CH is 27.50 GW, surpassing the 19.74 GW estimated for the FS, which is attributed to the wider cross-section of the GS in CH. Additionally, CH exhibits higher KEF variability due to GS’s larger path shifts and meanders. Estimated KEDs at ADCP site locations reach up to 2,908 W/m 2 in the FS and 1,512 W/m 2 in the CH at a depth of 20 m. High-energy zones are closer to shore in the FS, whereas energy-rich areas at CH are located further offshore. A depth-based KED analysis shows significant decreases across typical energy extraction depths (20 to 100 m), with reductions up to 44%. Finally, this study provides high-resolution resource characterization, forming a foundation for optimized site selection and marine hydrokinetic system design.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

The Reservoir Temperature Estimator (RTEst): A multicomponent geothermometry tool

The Reservoir Temperature Estimator (RTEst) is a multicomponent geothermometry tool for estimating reservoir geochemical parameters including reservoir temperature, CO 2 fugacity, mass of water lost or gained, and a reaction factor. It estimates these parameters and their associated uncertainties by minimizing an objective function that is the weighted sum of squares of the saturation indices of a user-selected set of minerals believed to be equilibrated with the reservoir fluid. RTEst accomplishes these estimates by combining the geochemical modeling capabilities of The Geochemist’s Workbench® with the optimization/parameter estimation resources of PEST®. An included interface aids the user in selecting plausible mineral phases to comprise the objective function and calculates their weighting factors. The working principles of RTEst are described and its efficacy is illustrated by presenting results of its application to various geothermal fields with known conditions. These examples show RTEst can account for the alteration of ascending reservoir fluid by mineral (calcite) re-equilibration with changes in temperature, reconstruct waters with CO 2 loss, correct for the deficit of water and other volatiles (CO 2,gas , H 2 S gas ) from boiling, and determine the amount of mixing of thermal and non-thermal waters. RTEst can use data with basis species below detection limit, missing, or unreliable either by assuming equilibrium with a controlling mineral (fixed-analyte method) or by treating the analyte concentration as an optimization parameter. The inverse of variance weighting method included in RTEst provides more representative results than either the normalization or unit weighting methods. Finally, the ability of RTEst to calculate reservoir temperatures, gas fugacity, and mixing fractions demonstrates its usefulness as a tool for evaluating geothermal systems.

15 GEOTHERMAL ENERGY↗
NASA NTRS1979

Concepts leading to the IMAGE-100 hybrid interactive system

As LACIE Procedure 1 evolved from the Classification and Mensuration Subsystem smallfields procedures, it became evident that two computational systems would have merit-the LACIE/Earth Resources Interactive Processing System based on a large IBM-360 computer oriented for operational use with high computational throughput, and a smaller, highly interactive system based on a PDP 11-45 minicomputer and its display system, the IMAGE-100. The latter had advantages for certain phases; notably, interactive spectral aids could be implemented quite rapidly. This would allow testing and development of Procedure 1 before its implementation on the LACIE/Earth Resources Interactive Processing System. The resulting minicomputer system, called the Classification and Mensuration Subsystem IMAGE-100 Hybrid System, allowed Procedure-1 operations to be performed interactively, except for clustering, classification, and automatic selection of best acquisitions, which were offloaded to the LACIE/Earth Resources Interactive Processing System.

Mackin, T. F.↗
DOE OSTI2018

A facile recovery process for cathodes from spent lithium iron phosphate batteries by using oxalic acid

A simplistic and novel leaching process is developed to dispose spent lithium iron phosphate (LiFePO 4 ) batteries. In this paper, oxalic acid is selected as a leaching reagent to recover lithium as a resource and remove phosphorus from LiFePO 4 batteries, benefiting from its low natural effects. The physical properties of spent cathode materials (before leaching) and residues (after leaching) are identified by X-ray diffraction (XRD) and scanning electronic microscopy (SEM) with energy dispersive X-ray spectroscopy (EDS). The total amounts of Li and Fe are analyzed by inductively coupled plasma-atomic emission spectroscopy (ICP-AES). The process occurs under conditions of a 0.3 mol·L -1 oxalic acid concentration, a temperature of 80°C, a reaction time of 60 min and a solid/liquid ratio of 60 g· L -1 . It can effectively precipitate ~92% ferrum in terms of FeC 2 O 4 ·2H 2 O from LiFePO 4 , with the leaching efficiency of Li achieving up to 98%. This method demonstrates a new strategy for dealing with spent lithium iron phosphate batteries with a low cost and low environmental impact.

25 ENERGY STORAGE↗
DOE OSTI2019

A Study of the Impact of Reduced Inertia in Power Systems

Inertia in power systems plays an important role in maintaining the stability and reliability of the system by counteracting changes in frequency. However, the traditional sources of synchronous generation are being displaced by renewable resources, which often have no inherent inertia. This paper investigates the impact of reduced system inertia on several aspects of the dynamic stability of power systems, such as angular stability, primary frequency response, and oscillatory modes. This study is performed on a large-scale 2000 bus synthetic Texas model by selectively replacing synchronous generators with inverter-based generation resources. This paper also compares the analysis results obtained by the above-mentioned inertia-reduction approach of renewable integration with another approach in which the inertia constant of all synchronous generators is decreased. This paper demonstrates that only reducing the inertia of all synchronous generators in a system does not provide an accurate analysis of the challenges associated with the reduced system inertia caused by renewable integration.

System Inertia, Angular stability, System Inertial↗
NASA NTRS1981

Application of HCMM data to regional geologic analysis for mineral and energy resource evaluation

Experimentation with several potentially promising techniques led to the selection of a fairly simple scheme for registration of data from the HCMM using an affine transformation. A method based solely on remote sensing was developed to estimate those meteorological effects which are required for thermal inertia mapping. It assumes that the atmospheric fluxes are spatially invariant and that the solar, sky and sensible heat fluxes can be approximated by a simple mathematical form. Coefficients are determined from least squares method by fitting observational data to the thermal model.

Watson, K.↗
DOE OSTI2025

Microbiome Adaptation Could Amplify Modeled Projections of Global Soil Carbon Loss With Climate Warming

Warming alters soil microbial traits through ecological and evolutionary processes, directly influencing the decomposition of organic matter, which significantly affects global soil carbon emissions. Yet, soil carbon models largely ignore these processes and their implications for global responses to warming. Here, we incorporate eco-evolutionary theory into a mechanistic model describing microbial soil carbon decomposition to address the question of whether such processes could have consequential effects on climate carbon feedbacks globally. We assume that a key trait of microbes, their resource allocation to production of exoenzymes (which facilitate decomposition of organic matter)—is optimized to environmental temperatures by natural selection. We find that eco-evolutionary optimization results in microbes allocating more resources to enzyme production under warming. When applied at the global scale, eco-evolutionary optimization enhances the biological realism of soil carbon models and significantly amplifies global soil carbon loss by 2100. Our results highlight the significant potential of microbial eco-evolutionary responses to influence carbon cycle feedbacks to climate change, and motivate an urgent need for more comprehensive data to accurately quantify the adaptive potential of microbiomes in response to climate change.

Biodiversity & Conservation↗
DOE OSTI2022

A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow

With the increasing penetration of distributed energy resources, distributed optimization algorithms have attracted significant attention for power systems applications due to their potential for superior scalability, privacy, and robustness to a single point-of-failure. The Alternating Direction Method of Multipliers (ADMM) is a popular distributed optimization algorithm; however, its convergence performance is highly dependent on the selection of penalty parameters, which are usually chosen heuristically. In this work, we use reinforcement learning (RL) to develop an adaptive penalty parameter selection policy for alternating current optimal power flow (ACOPF) problem solved via ADMM with the goal of minimizing the number of iterations until convergence. We train our RL policy using deep Q-learning and show that this policy can result in significantly accelerated convergence (up to a 59% reduction in the number of iterations compared to existing, curvatureinformed penalty parameter selection methods). Furthermore, we show that our RL policy demonstrates promise for generalizability, performing well under unseen loading schemes as well as under unseen losses of lines and generators (up to a 50% reduction in iterations). This work thus provides a proof-of-concept for using RL for parameter selection in ADMM for power systems applications.

alternating current optimal power flow↗
DOE OSTI2018

Behavior of the maximum likelihood in quantum state tomography

Quantum state tomography on a d-dimensional system demands resources that grow rapidly with d. They may be reduced by using model selection to tailor the number of parameters in the model (i.e., the size of the density matrix). Most model selection methods typically rely on a test statistic and a null theory that describes its behavior when two models are equally good. Here, we consider the loglikelihood ratio. Because of the positivity constraint ρ ≥ 0, quantum state space does not generally satisfy local asymptotic normality (LAN), meaning the classical null theory for the loglikelihood ratio (the Wilks theorem) should not be used. Thus, understanding and quantifying how positivity affects the null behavior of this test statistic is necessary for its use in model selection for state tomography. We define a new generalization of LAN, metric-projected LAN, show that quantum state space satisfies it, and derive a replacement for the Wilks theorem. In addition to enabling reliable model selection, our results shed more light on the qualitative effects of the positivity constraint on state tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1992

Seeing the forest for the trees: Networked workstations as a parallel processing computer

Unlike traditional 'serial' processing computers in which one central processing unit performs one instruction at a time, parallel processing computers contain several processing units, thereby, performing several instructions at once. Many of today's fastest supercomputers achieve their speed by employing thousands of processing elements working in parallel. Few institutions can afford these state-of-the-art parallel processors, but many already have the makings of a modest parallel processing system. Workstations on existing high-speed networks can be harnessed as nodes in a parallel processing environment, bringing the benefits of parallel processing to many. While such a system can not rival the industry's latest machines, many common tasks can be accelerated greatly by spreading the processing burden and exploiting idle network resources. We study several aspects of this approach, from algorithms to select nodes to speed gains in specific tasks. With ever-increasing volumes of astronomical data, it becomes all the more necessary to utilize our computing resources fully.

Breen, J. O.↗
DOE OSTI2015

Geothermally Coupled Well-Based Compressed Air Energy Storage

Previous work by McGrail et al. (2013, 2015) has evaluated the possibility of pairing compressed air energy storage with geothermal resources in lieu of a fossil-fired power generation component, and suggests that such applications may be cost competitive where geology is favorable to siting both the geothermal and CAES components of such a system. Those studies also note that the collocation of subsurface resources that meet both sets of requirements are difficult to find in areas that also offer infrastructure and near- to mid-term market demand for energy storage. This study examines a novel application for the compressed air storage portion of the project by evaluating the potential to store compressed air in disused wells by amending well casings to serve as subsurface pressure vessels. Because the wells themselves would function in lieu of a geologic storage reservoir for the CAES element of the project, siting could focus on locations with suitable geothermal resources, as long as there was also existing wellfield infrastructure that could be repurposed for air storage. Existing wellfields abound in the United States, and with current low energy prices, many recently productive fields are now shut in. Should energy prices remain stagnant, these idle fields will be prime candidates for decommissioning unless they can be transitioned to other uses, such as redevelopment for energy storage. In addition to the nation’s ubiquitous oil and gas fields, geothermal fields, because of their phased production lifetimes, also may offer many abandoned wellbores that could be used for other purposes, often near currently productive geothermal resources. These existing fields offer an opportunity to decrease exploration and development uncertainty by leveraging data developed during prior field characterization, drilling, and production. They may also offer lower-cost deployment options for hybrid geothermal systems via redevelopment of existing well-field infrastructure. This project assessed the technical and economic feasibility of implementing geothermally coupled well-based CAES for grid-scale energy storage. Based on an evaluation of design specifications for a range of casing grades common in U.S. oil and gas fields, a 5-MW CAES project could be supported by twenty to twenty-five 5,000-foot, 7-inch wells using lower-grade casing, and as few as eight such wells for higher-end casing grades. Using this information, along with data on geothermal resources, well density, and potential future markets for energy storage systems, The Geysers geothermal field was selected to parameterize a case study to evaluate the potential match between the proven geothermal resource present at The Geysers and the field’s existing well infrastructure. Based on calculated wellbore compressed air mass, the study shows that a single average geothermal production well could provide enough geothermal energy to support a 15.4-MW (gross) power generation facility using 34 to 35 geothermal wells repurposed for compressed air storage, resulting in a simplified levelized cost of electricity (sLCOE) estimated at 11.2 ¢/kWh (Table S.1). Accounting for the power loss to the geothermal power project associated with diverting geothermal resources for air heating results in a net 2-MW decrease in generation capacity, increasing the CAES project’s sLCOE by 1.8 ¢/kWh.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Geothermally Coupled Well-Based Compressed Air Energy Storage

Previous work by McGrail et al. (2013, 2015) has evaluated the possibility of pairing compressed air energy storage with geothermal resources in lieu of a fossil-fired power generation component, and suggests that such applications may be cost competitive where geology is favorable to siting both the geothermal and CAES components of such a system. Those studies also note that the collocation of subsurface resources that meet both sets of requirements are difficult to find in areas that also offer infrastructure and near- to mid-term market demand for energy storage. This study examines a novel application for the compressed air storage portion of the project by evaluating the potential to store compressed air in disused wells by amending well casings to serve as subsurface pressure vessels. Because the wells themselves would function in lieu of a geologic storage reservoir for the CAES element of the project, siting could focus on locations with suitable geothermal resources, as long as there was also existing wellfield infrastructure that could be repurposed for air storage. Existing wellfields abound in the United States, and with current low energy prices, many recently productive fields are now shut in. Should energy prices remain stagnant, these idle fields will be prime candidates for decommissioning unless they can be transitioned to other uses, such as redevelopment for energy storage. In addition to the nation’s ubiquitous oil and gas fields, geothermal fields, because of their phased production lifetimes, also may offer many abandoned wellbores that could be used for other purposes, often near currently productive geothermal resources. These existing fields offer an opportunity to decrease exploration and development uncertainty by leveraging data developed during prior field characterization, drilling, and production. They may also offer lower-cost deployment options for hybrid geothermal systems via redevelopment of existing well-field infrastructure. This project assessed the technical and economic feasibility of implementing geothermally coupled well-based CAES for grid-scale energy storage. Based on an evaluation of design specifications for a range of casing grades common in U.S. oil and gas fields, a 5-MW CAES project could be supported by twenty to twenty-five 5,000-foot, 7-inch wells using lower-grade casing, and as few as eight such wells for higher-end casing grades. Using this information, along with data on geothermal resources, well density, and potential future markets for energy storage systems, The Geysers geothermal field was selected to parameterize a case study to evaluate the potential match between the proven geothermal resource present at The Geysers and the field’s existing well infrastructure. Based on calculated wellbore compressed air mass, the study shows that a single average geothermal production well could provide enough geothermal energy to support a 15.4-MW (gross) power generation facility using 34 to 35 geothermal wells repurposed for compressed air storage, resulting in a simplified levelized cost of electricity (sLCOE) estimated at 11.2 ¢/kWh (Table S.1). Accounting for the power loss to the geothermal power project associated with diverting geothermal resources for air heating results in a net 2-MW decrease in generation capacity, increasing the CAES project’s sLCOE by 1.8 ¢/kWh.

25 ENERGY STORAGE↗
DOE OSTI2016

Model Test Bed for Evaluating Wave Models and Best Practices for Resource Assessment and Characterization

A wave model test bed is established to benchmark, test and evaluate spectral wave models and modeling methodologies (i.e., best practices) for predicting the wave energy resource parameters recommended by the International Electrotechnical Commission, IEC TS 62600-101Ed. 1.0 ©2015. Among other benefits, the model test bed can be used to investigate the suitability of different models, specifically what source terms should be included in spectral wave models under different wave climate conditions and for different classes of resource assessment. The overarching goal is to use these investigations to provide industry guidance for model selection and modeling best practices depending on the wave site conditions and desired class of resource assessment. Modeling best practices are reviewed, and limitations and knowledge gaps in predicting wave energy resource parameters are identified.

13 HYDRO ENERGY↗
DOE OSTI2021

Analysis of Selected Publicly Available Geothermal Exploration Data Gaps

As part of a United States Department of Energy (DOE) supported retrospective analysis of DOE's Play Fairway Analysis (PFA) projects, the National Renewable Energy Laboratory (NREL) compiled and analyzed publicly available geothermal exploration datasets to identify and highlight data gaps in areas prospective for hosting geothermal resources. The analysis was intended to understand the existing geographic coverage of selected datasets commonly utilized both by the PFA projects and geothermal developers during resource assessments including geologic mapping, temperature gradient drilling, and aeromagnetic, gravimetric, and lidar surveys. Results indicate that broad areas of the western United States estimated to have geothermal potential lack sufficient geologic and geophysical coverage necessary for even regional resource exploration. The study directly informed the recent Geoscience Data Acquisition for Western Nevada, or GeoDAWN - which united DOE's Geothermal Technologies Office (GTO) with the U.S. Geological Survey (USGS) of the U.S. Department of the Interior to assist U.S. needs for energy and critical minerals. The study also has the potential to inform public investment in further data acquisition for characterization of the Earth both for geothermal and other natural resource assessments.

data↗
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 OSTI2012

Quantifying uncertainty in LCA-modelling of waste management systems

Highlights: Black-Right-Pointing-Pointer Uncertainty in LCA-modelling of waste management is significant. Black-Right-Pointing-Pointer Model, scenario and parameter uncertainties contribute. Black-Right-Pointing-Pointer Sequential procedure for quantifying uncertainty is proposed. Black-Right-Pointing-Pointer Application of procedure is illustrated by a case-study. - Abstract: Uncertainty analysis in LCA studies has been subject to major progress over the last years. In the context of waste management, various methods have been implemented but a systematic method for uncertainty analysis of waste-LCA studies is lacking. The objective of this paper is (1) to present the sources of uncertainty specifically inherent to waste-LCA studies, (2) to select and apply several methods for uncertainty analysis and (3) to develop a general framework for quantitative uncertainty assessment of LCA of waste management systems. The suggested method is a sequence of four steps combining the selected methods: (Step 1) a sensitivity analysis evaluating the sensitivities of the results with respect to the input uncertainties, (Step 2) an uncertainty propagation providing appropriate tools for representing uncertainties and calculating the overall uncertainty of the model results, (Step 3) an uncertainty contribution analysis quantifying the contribution of each parameter uncertainty to the final uncertainty and (Step 4) as a new approach, a combined sensitivity analysis providing a visualisation of the shift in the ranking of different options due to variations of selected key parameters. This tiered approach optimises the resources available to LCA practitioners by only propagating the most influential uncertainties.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗