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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Hydropower Potential at Non-Powered Dams: A Multi-Criteria Decision Analysis Tool based on Grid, Community, Industry, and Environmental Impacts

Non-powered dams (NPDs) are dams that do not include hydraulic turbine (hydropower) equipment. Currently, there are more than 80,000 such dams in the United States, which provide a variety of non-energy benefits, including flood control, water supply, navigation, and recreation. Approximately 500 of these NPDs are identified as having the potential to add hydropower generation (totaling up to a capacity of more than 8200 MW). A large share of investment costs and environmental impacts of dam construction have already been incurred at these NPDs. Hence, adding power to the existing dam structure is hypothesized to be achieved at a lower cost, with less risk, and a shorter timeframe than the development required for new dam construction. The abundance of NPDs, the associated environmental favorability, and cost advantages, combined with the reliability, predictability, and dispatchability of hydropower, make NPDs a strong candidate in the nation’s renewable energy portfolio. To assess the NPD to hydropower conversion potential, in this study, we developed a GIS-based multi-criterial decision analysis tool, which allows users to rank these NPDs based on the grid, community, industry, and environmental impacts (i.e., GCIE impacts). This web-based interactive tool (developed using open-source Python and JavaScript) lets the user choose from a wide range of features to define each of the GCIE impact scores through a user-friendly graphical user interface. These features are related to dam operation, hydropower generation opportunity, power market economy, social vulnerability and risk, proximity to critical infrastructure and energy generating facilities, environmental concerns (air, water, and critical habitat), and exposure to natural hazards. The overall priority score of NPDs is calculated based on user-defined weights for each of the GCIE impact scores. Besides ranking NPDs, the tool can also be used to estimate the energy-storage feasibility (battery, hydrogen, and pump-storage hydropower) at each of the potential sites.

13 HYDRO ENERGY↗
DOE OSTI2022

A Fast and Accurate Transient Stability Assessment Method Based on Deep Learning: WECC Case Study

Transient stability is one of the critical aspects of power system stability assessment. The increasing integration of inverter-based resources and the retirement of conventional synchronous generators result in the decreasing system inertia and growing complexity of system operating conditions. Using a few selected typical operating conditions cannot guarantee system transient stability in all operating conditions, and the time-domain simulation of all operating conditions requires tremendous time and is often infeasible. This paper proposes a more efficient transient stability assessment method based on deep learning. The binary search method is used to determine the critical clearing time (CCT) in creating training databased by time-domain simulation. This method is fast and accurate with 1 ms resolution. The buses whose CCTs are lower than 200 ms are considered critical buses. Buses close to each other are grouped based on their mutual admittance matrix to reduce the search space of the critical buses. This paper also proposes the generator feature normalization based on the physical model. Case study on the reduced 240-bus WECC system model demonstrates that the proposed method can predict CCT accurately and efficiently.

critical clearing time↗
DOE OSTI2022

Synergistic Retrieval of Temperature and Humidity Profiles from Space-Based and Ground-Based Infrared Sounders Using an Optimal Estimation Method

The atmospheric temperature and humidity profiles of the troposphere are generally measured by radiosondes and satellites, which are essential for analyzing and predicting weather. Nevertheless, the insufficient observation frequencies and low detection accuracy of the boundary layer restricts the description of atmospheric state changes by the temperature and humidity profiles. Therefore, this work focus on retrieving the temperature and humidity profiles using observations of the FengYun-4 (FY-4) Geostationary Interferometric Infrared Sounder (GIIRS) combined with ground-based infrared spectral observations from the Atmospheric Emitted Radiance Interferometer (AERI), which are more accurate than space-based individual retrieval results and have a wider effective retrieval range than ground-based individual retrieval results. Based on the synergistic observations, which are made by matching the space-based and ground-based data with those of different spatial and temporal resolutions, a synergistic retrieval process is proposed to obtain the temperature and humidity profiles at a high frequency under clear-sky conditions based on the optimal estimation method. In this research, using the line-by-line radiative transfer model (LBLRTM) as the forward model for observing simulations, a retrieval experiment was carried out in Qingdao, China, where an AERI is situated. Taking radiosonde data as a reference for comparing the retrieval results of the temperature and humidity profiles of the troposphere, the root-mean-square error (RMSE) of the synergistic retrieval algorithm below 400 hPa is within 2 K for temperature and within 12% for relative humidity. Compared with the GIIRS individual retrieval, the RMSE of temperature and relative humidity for the synergistic method is reduced by 0.13–1.5 K and 2.7–4.4% at 500 hPa, and 0.13–2.1 K and 2.5–7.2% at 900 hPa. Moreover, the forecast index (FI) calculated from the retrieval results shows reasonable consistency with the FIs calculated from the ERA5 reanalysis and from radiosonde data. The synergistic retrieval results have higher temporal resolution than space-based retrieval results and can reflect the changes in the atmospheric state more accurately. Overall, the results demonstrated the promising potential of the synergistic retrieval of temperature and humidity profiles at high accuracy and high temporal resolution under clear-sky conditions from FY-4/GIIRS and AERI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Comparison of Electromagnetic Transient and Phasor-based Simulation for the Stability of Grid-Forming-Inverter-based Microgrids

The increasing interest in studying feeder-level, inverter-based microgrids requires appropriate simulation methods that can effectively simulate the dynamics of distribution feeders that typically have thousands of nodes. To examine the accuracy of phasor-based simulation for the stability of feeder-level, inverter-based microgrids, a comparative study between electromagnetic transient (EMT) and phasor-based simulation was conducted. Case studies of a two-inverter small microgrid and a modified version of the IEEE 34-Node Test System that has seven grid-forming inverters show that phasor-based simulation agrees well with EMT simulation when the P-f droop gains of grid-forming inverter controllers are within normal ranges. However, under extremely high P-f droop gains, phasor-based simulation can result in over-optimistic stability results. This study provides insight into the applicability of phasor-based simulation for the stability of feeder-level, inverter-based microgrids.

Du, Wei↗
DOE OSTI2022

Paper-based gold nanoparticles decorated SWCNTs chemiresistive sensor for sensitive detection of As(III) based on electrochemical doping

A paper-based chemiresistive sensor consisting of a single-walled carbon nanotubes network with electrodeposited gold nanoparticles (AuNPs-SWCNTs) was developed for the sensitive detection of As(III). A new sensing strategy was also proposed combined with a paper-based device for As(III) chemiresistive detection based on the electrochemical doping of As(0) on the AuNPs-SWCNTs channel. Here, the proposed paper-based chemiresistive sensor was manufactured by wax printing and vacuum deposition using a water-based SWCNTs ink. The sensor sensitivity was enhanced by optimizing the volume of SWCNTs ink used in the formation of the sensing network in the paper and the sweep segment of cyclic voltammetry used for the electrochemical deposition of AuNPs. Additionally, the mechanism of the sensing strategy based on the electrochemical n-doping of As(0) to the AuNPs-SWCNTs sensing channel was investigated using a liquid-ion gated FET system. The As(III) concentration detected by the as-fabricated chemiresistive sensor is as low as 1.35 × 10 -5 μM which is even lower than the maximum permissible concentration in drinking water defined by the WHO. In this paper, we provide a simple strategy for developing paper-based chemiresistive sensors with unique properties for practical As(III) determination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Uranium recovery from seawater using amidoxime-based braided polymers synthesized from acrylic fibers

Global demand for nuclear energy is expected to rise in the coming decades. To meet these growing needs, new uranium resources must be explored. One of the potential alternatives to traditional uranium mining is oceanic uranium. The capture and recovery of uranium from the ocean has been under investigation for some time, with many recent studies focused on amidoxime based adsorbents. These adsorbents while able to achieve high uranium recovery capacities are, nevertheless, expensive to produce and adsorb a significant amount of hard to remove vanadium. The purpose of this study is to evaluate the adsorption performance of amidoxime based polymer braids synthesized from acrylic fibers which are designed to significantly cut polymer synthesis and conditioning costs. Adsorption experiments were performed in a recirculating raceway flume system at environmental conditions, approximately 10.8 oC, with 40-micron prefiltered seawater over 28 days for small and large sized LCW polymer braids. For both braid sizes, the adsorption of vanadium was far lower on the LCW materials than on Oak Ridge National Laboratory’s amidoxime based AF1 and AI8 small braids, with the LCW small braids outperforming both materials with respect to uranium adsorption under similar conditions. Adsorption modeling was used to simulate the performance at higher temperatures based on 20oC experiments previously performed with similar materials. Simulation results indicated that the small LCW braids would have a less significant advantage with respect to uranium adsorption over both AF1 and AI8 at 20oC and adsorb slightly less uranium than AF1 at 31oC. Vanadium adsorption by LCW small braids was less than one third of vanadium adsorption by either AF1 or AI8 for all temperatures. This behavior indicates that the LCW materials are able to achieve comparable uranium adsorption to other amidoxime adsorbents previously developed, while being cheaper to produce and adsorbing significantly less vanadium.

Wiechert, Alexander I.↗
DOE OSTI2024

First-principles calculation of lattice distortion, electronic structure, and bonding properties of GeTe-based and PbSe-based high-entropy chalcogenides

The massive amount of wasted heat energy from industry has pushed the development of thermoelectric (TE) materials that directly convert heat into electricity to a new level of concern. Recently, multicomponent alloys such as GeTe-based and PbSe-based high-entropy (HE) chalcogenides have attracted a great deal of attention due to their potential application as TE materials. The nature of the interatomic bonding, lattice distortion (LD), and the electronic structure in this class of materials is not fully understood. Herein, we report a comprehensive computational investigation of nine GeTe-based HE alloys with eight metallic elements (Ag, Pb, Sb, Bi, Cu, Cd, Mn, and Sn) with large supercells of 1080 atoms each; seven PbSe-based HE solid solutions: Pb0.99−ySb0.012SnySe1−2xTexSx (x = 0.1, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, with y = 0) with supercells of 1000 atoms each; and five Pb0.99−ySb0.012SnySe1−2xTexSx (y = 0.05, 0.1, 0.15, 0.2, 0.25 with x = 0.25) solid solutions with supercells of 1000 atoms each. All these HE models are theoretically investigated for the first time. The electronic structure, interatomic bonding, charge transfer, and lattice distortion (LD) are investigated by first-principles calculations based on density functional theory. Multicomponent HE alloys can cause a significant LD, which affects their mechanical, thermal, and TE properties. The calculations for the GeTe-based HE chalcogenides showed that they are semiconductors with a narrow bandgap, except for m8, which has a semi-metallic characteristic, and this makes them good candidates for TE applications. For most of these models, the Fermi level shifts upward and locates deeply in the conduction bands, resulting in the enhancement of the electrical conductivity (σ). The bonding properties showed that most bonds in m5 are more dispersed, indicating highest LD and lower lattice thermal conductivity. For PbSe-based HE solid solutions, the LD calculations showed that the models Pb0.99Sb0.012Se0.5Te0.25S0.25 and Pb0.89Sb0.012Sn0.1Se0.5Te0.25S0.25 have the higher LD, and thus a lower lattice thermal conductivity. Such investigations are in high demand since it enables us to design new HE chalcogenides for TE applications. We use the novel concept of total bond order density as a single quantum mechanical metric to characterize the internal cohesion of these HE alloys and correlate with calculated properties, especially the mechanical properties. This work provides a solid database for HE chalcogenides and a road map for many potential applications. Moreover, the computational procedure we developed can be used to design new HE chalcogenides for specific TE applications.

Physics↗
DOE OSTI2022

Computer-Vision-Based Vibration Tracking Using a Digital Camera: A Sparse-Optical-Flow-Based Target Tracking Method

Computer-vision-based target tracking is a technology applied to a wide range of research areas, including structural vibration monitoring. However, current target tracking methods suffer from noise in digital image processing. In this paper, a new target tracking method based on the sparse optical flow technique is introduced for improving the accuracy in tracking the target, especially when the target has a large displacement. The proposed method utilizes the Oriented FAST and Rotated BRIEF (ORB) technique which is based on FAST (Features from Accelerated Segment Test), a feature detector, and BRIEF (Binary Robust Independent Elementary Features), a binary descriptor. ORB maintains a variety of keypoints and combines the multi-level strategy with an optical flow algorithm to search the keypoints with a large motion vector for tracking. Then, an outlier removal method based on Hamming distance and interquartile range (IQR) score is introduced to minimize the error. The proposed target tracking method is verified through a lab experiment—a three-story shear building structure subjected to various harmonic excitations. It is compared with existing sparse-optical-flow-based target tracking methods and target tracking methods based on three other types of techniques, i.e., feature matching, dense optical flow, and template matching. The results show that the performance of target tracking is greatly improved through the use of a multi-level strategy and the proposed outlier removal method. The proposed sparse-optical-flow-based target tracking method achieves the best accuracy compared to other existing target tracking methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Intra-annual variations of regional total column ozone, aerosol optical depth, and water vapor from ground-based, satellite-based and model-based observations

The Microtops II ozonometer has been deployed to continuously measure the total column ozone (TCO), pre-cipitable water content (PWC) and aerosol optical thickness (AOT) at Atigre village (16.74° N, 74.37° E, 604 m above sea level, masl) located on the southeastern slope of Indian western Ghats. The Microtops II ozonometer measurements during the period from September 2017 to June 2018 were analyzed along with the retrieved products of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellites and also the ERA-interim reanalysis model. We found that the TCO (or PWC) data from the OMI (or MODIS) and the ERA reanalysis model data products are in good agreement. The mea-surements showed strong seasonal variability such that TCO was lowest in the winter season but increased in the summer season, and both PWC and AOT were lowest in the post-monsoon season and increased in the summer season. In continuous ERA-interim reanalysis TCO observations, we found the three types of periodicities in the daily mean TCO as well as PWC (i) The weekly (7 days), (ii) quasi-biweekly (14 to 16 days), (iii) Madden Julian Oscillations (MJO) (30–60 days) oscillations. These oscillations depend on the periodic weather changes in the troposphere. We also observe that the average day to day variability in daily mean TCO observations in the observational period is about 1.4%, 1.1%, 2.62% in the Microtops II ozonometer, ERA-interim reanalysis, and OMI data respectively. We found the positive correlation between daily mean AOT and PWC in all seasons (except monsoon), which is maximum in the winter season, showing the hygroscopic nature of aerosols. The sources of water vapor and aerosol at our location are also studied using back-trajectory analysis.

Nade, Dada R.↗
DOE OSTI2022

Machine Learning Based Network Parameter Estimation Using AMI Data

The expansion of distribution power system and the growing penetration of distributed energy resources present new challenges for situational awareness. Calibrating the extended system model with sensor measurements and maintaining the usability is critical for utilities. This paper presents a distribution network parameter estimation (DNPE) approach using machine learning (ML) and metering data that improve the quality of extended distribution power system modeling. The reliability model can improve the ability of endpoint data to be translated into network-level situational awareness in real time and help distribution system operators (DSOs) solve branch flow and voltage problems. In addition, a data analytic and automate processing scheme is proposed to improve the sensor data quality and prevent misleading information. The effectiveness of the proposed method is verified with actual advanced metering infrastructure (AMI) data on a real utility feeder model, while considering the higher penetration of photovoltaic power generation. The test of DNPE and study results are demonstrated in this paper.

Parameter estimation, machine learning, power dist↗
DOE OSTI2024

Preventive Power Outage Estimation Based on a Novel Scenario Clustering Strategy

The increasing occurrence of extreme weather events is challenging power grid operation. For extreme weather events, the system operator is responsible for estimating the power outages and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The outputs of an outage prediction model tool are used to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers repair crews and mobile energy resources (MERs). Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative profiles which the system operator can focus on. Finally, case studies on a distribution system evaluate the damage caused by an extreme weather event and verify the effectiveness of the proposed scenario clustering strategy.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗
DOE OSTI2020

High-Power Lithium Metal Batteries Enabled by High-Concentration Acetonitrile-Based Electrolytes with Vinylene Carbonate Additive

To enable next-generation high power, high-energy-density lithium (Li) metal batteries (LMBs), an electrolyte possessing both high Li Coulombic efficiency (CE) at high-rate and good anodic stability on cathodes is critical. Acetonitrile (AN) is a well-known organic solvent for high anodic stability and high ionic conductivity, yet its application in LMBs is limited due to its poor compatibility with Li metal anode even at high salt concentration conditions. Here, we developed a highly concentrated AN-based electrolyte with vinylene carbonate (VC) additive to suppress Li+ depletion at high current densities. Addition of VC in the AN-based electrolyte leads to the formation of a polycarbonate-based solid electrolyte interphase which minimizes Li corrosion and leads to very high Li CE of up to 99.1% at a current density of 0.2 mA cm-2. Using such an electrolyte, fast charging of Li||NMC333 cells has been realized at a high current density of 3.6 mA cm-2, and stable cycling of Li||NMC622 cells with a high cathode loading of 4 mAh cm-2 has also been demonstrated.

Peng, Zhe↗
DOE OSTI2024

Stabilized bases for high-order, interpolation semi-Lagrangian, element-based tracer transport

In a computational fluid model of the atmosphere, the advective transport of trace species, or tracers, can be computationally expensive. For efficiency, models often use semi-Lagrangian advection methods. High-order interpolation semi-Lagrangian (ISL) methods, in particular, can be extremely efficient, if the problem of property preservation specific to them can be addressed. Atmosphere models often use geometrically and logically nonuniform grids for efficiency and, as a result, element-based discretizations. Such grids and discretizations make stability a particular problem for ISL methods. Generally, high-order, element-based ISL methods that use the natural polynomial interpolant associated with a nodal finite-element discretization are unstable. Here, we derive new bases having order of accuracy up to nine, with positive nodal weights, that stabilize the element-based ISL method. We use these bases to construct the linear advection operator in the property-preserving Interpolation Semi-Lagrangian Element-based Transport (Islet) method. Then we discuss key software implementation details. Finally, we show performance results for the Energy Exascale Earth System Model's atmosphere dynamical core, comparing the original and new transport methods. These simulations used up to 27,600 Graphical Processing Units (GPU) on the Oak Ridge Leadership Computing Facility's Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗