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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Gap Analysis on the Impacts of Hydrogen Addition to the North American Natural Gas Infrastructure Polyethylene Pipelines

The existing natural gas pipeline system is being considered as a means to distribute blends of clean hydrogen and natural gas as one component of clean hydrogen’s role in enabling a future low-carbon energy system. With nearly three million miles of transmission and distribution lines in the United States, this national asset is uniquely situated as a transition strategy to assist in the decarbonization of the US economy. 1 This report reviews existing data on the effects of hydrogen on polyethylene (PE) natural gas pipeline materials and identifies gaps where additional investigation is required to fully assess deleterious impacts to the polyethylene pipes from exposure to hydrogen. This gap analysis will assist in determining the feasibility of blending hydrogen gas into existing natural gas pipelines.

08 HYDROGEN↗
DOE OSTI2021

On the Utility of Transmission Color Analysis i: Differentiating Super-Earths and Sub-Neptunes

The majority of exoplanets found to date have been discovered via the transit method, and transmission spectroscopy represents the primary method of studying these distant worlds. Currently, in-depth atmospheric characterization of transiting exoplanets entails the use of spectrographs on large telescopes, requiring significant observing time to study each planet. Previous studies have demonstrated trends for solar system worlds using color–color photometry of reflectance spectra, as well as trends within transmission spectra for hot Jupiters. Building on these concepts, we have investigated the use of transmission color photometric analysis for efficient, coarse categorization of exoplanets and for assessing the nature of these worlds, with a focus on resolving the bulk composition degeneracy to aid in discriminating super-Earths and sub-Neptunes. We present our methodology and first results, including spectrum models, model comparison frameworks, and wave band selection criteria. We present our results for different transmission “color” metrics, filter selection methods, and numbers of filters. Assuming noise-free spectra of isothermal atmospheres in chemical equilibrium, with our pipeline, we are able to constrain atmospheric mean molecular weight in order to distinguish between super-Earth and sub-Neptune atmospheres with >90% overall accuracy using specific low-resolution filter combinations, . We also found that increasing the number of filters does not substantially impact this performance. This method could allow for broad characterization of large numbers of planets much more efficiently than current methods permit, enabling population- and system-level studies. Additionally, data collected via this method could inform follow-up observing time by large telescopes for more detailed studies of worlds of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Pipeline Monitoring Using Highly Sensitive Vibration Sensor Based on Fiber Ring Cavity Laser

A vibration fiber sensor based on a fiber ring cavity laser and an interferometer based single-mode-multimode-single-mode (SMS) fiber structure is proposed and experimentally demonstrated. The SMS fiber sensor is positioned within the laser cavity, where the ring laser lasing wavelength can be swept to an optimized wavelength using a simple fiber loop design. To obtain a better signal-to-noise ratio, the ring laser lasing wavelength is tuned to the maximum gain region biasing point of the SMS transmission spectrum. A wide range of vibration frequencies from 10 Hz to 400 kHz are experimentally demonstrated. In addition, the proposed highly sensitive vibration sensor system was deployed in a field-test scenario for pipeline acoustic emission monitoring. An SMS fiber sensor is mounted on an 18” diameter pipeline, and vibrations were induced at different locations using a piezoelectric transducer. The proposed method was shown to be capable of real-time pipeline vibration monitoring.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. Here, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES's bidding, scheduling, and control decisions and the energy market's clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Equitable Energy Transition Planning in Holyoke, Massachusetts: A Technical Analysis for Strategic Gas Decommissioning and Grid Resiliency

Buildings account for 30% of the emissions in Massachusetts and are the largest source of emissions in the United States, along with transportation. Pipeline-delivered methane gas is the dominant heating source in Massachusetts, representing 51% of heating in the state. The current gas network in Massachusetts and across many other US states is aging, a relic of the coal gas era, with thousands of miles of cast iron and unprotected steel pipes that are considered leak prone. Even newer plastic pipes are subject to degradation and in need of replacement, an upgrade that averages $2.8 million per mile of pipeline replacement across investor-owned utilities in Massachusetts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Hydrogen carriers: Production, transmission, decomposition, and storage

Recognizing the potential role of liquid hydrogen carriers in overcoming the inherent limitations in transporting and storing gaseous and liquid hydrogen, a complete production and use scenario is postulated and analyzed for perspective one-way and two-way carriers. The carriers, methanol, ammonia and toluene/MCH (methylcyclohexane), are produced at commercially viable scales in a central location, transmitted by rail or pipelines for 2000 miles, and decomposed near city gates to generate fuel-cell quality hydrogen for distribution to refueling stations. In terms of the levelized cost of H 2 distributed to the stations, methanol is less expensive to produce (1.22 dollars per kg-H 2 ) than MCH (1.35 dollars per kg-H 2 ) or ammonia (2.20 dollars per kg-H 2 ). Levelized train transmission cost is smaller for methanol (0.63 dollars per kg-H 2 ) than ammonia (1.29 dollars per kg-H 2 ) or toluene/MCH system (2.07 dollars per kg-H 2 ). Levelized decomposition cost is smaller for ammonia (0.30-1.06 dollars per kg-H 2 ) than MCH (0.54-1.22 dollars per kg-H 2 ) or methanol (0.43-1.12 dollars per kg-H 2 ). Over the complete range of demand investigated, 10-350 tpd-H 2 , the levelized cost of H2 distributed to stations is aligned as methanol « ammonia ~ MCH. With pipelines at much larger scale, 6000 tpd-H 2 , the levelized cost decreases by ~1 dollar per kg-H 2 for ammonia and MCH and much less for methanol. Methanol is a particularly attractive low-risk carrier in the transition phase with lower than 50-tpd H 2 demand.

08 HYDROGEN↗
DOE OSTI2023

Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array

While there is a growing appreciation of three-dimensional (3D) neural tissues (i.e., hydrogel-based, organoids, and spheroids), shown to improve cellular health and network activity to mirror brain-like activity in vivo , functional assessment using current electrophysiology techniques (e.g., planar multi-electrode arrays or patch clamp) has been technically challenging and limited to surface measurements at the bottom or top of the 3D tissue. As next-generation MEAs, specifically 3D MEAs, are being developed to increase the spatial precision across all three dimensions (X, Y, Z), development of improved computational analytical tools to discern region-specific changes within the Z dimension of the 3D tissue is needed. In the present study, we introduce a novel computational analytical pipeline to analyze 3D neural network activity recorded from a “bottom-up” 3D MEA integrated with a 3D hydrogel-based tissue containing human iPSC-derived neurons and primary astrocytes. Over a period of ~6.5 weeks, we describe the development and maturation of 3D neural activity (i.e., features of spiking and bursting activity) within cross sections of the 3D tissue, based on the vertical position of the electrode on the 3D MEA probe, in addition to network activity (identified using synchrony analysis) within and between cross sections. Then, using the sequential addition of postsynaptic receptor antagonists, bicuculline (BIC), 2-amino-5-phosphonovaleric acid (AP-5), and 6-cyano-5-nitroquinoxaline-2,3-dione (CNQX), we demonstrate that networks within and between cross sections of the 3D hydrogel-based tissue show a preference for GABA and/or glutamate synaptic transmission, suggesting differences in the network composition throughout the neural tissue. The ability to monitor the functional dynamics of the entire 3D reconstructed neural tissue is a critical bottleneck; here we demonstrate a computational pipeline that can be implemented in studies to better interpret network activity within an engineered 3D neural tissue and have a better understanding of the modeled organ tissue.

3D culture↗
DOE OSTI2021

FLC Award: QED: Quantum Ensured Defense of the Smart Electric Grid

A reliable electric power supply is crucial for modern day life as well as national security, economic productivity, and life-and-death essentials. During the COVID pandemic, internet and cell communications became a “must-have” for government and business operations, education, and communicating COVID testing for vaccine information. Loss of electric power quickly leads to human health and national security emergencies. When a major winter storm hit Texas in mid-February 2021, the system was overwhelmed and over 4M people lost power. Although this crisis arose from an unprecedented weather event - not a cyberattack - it serves as a vivid illustration of the impact power disruption can have on our American way of life. The recent cyberattack on the Colonial Oil Pipeline also provides a stark reminder that infrastructure supporting our daily lives has vulnerabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

NEMESIS: Exoplanet Transit Survey of Nearby M-dwarfs in TESS FFIs. I

In this work, we present an analysis of 33,054 M-dwarf stars, located within 100 parsecs, via the Transiting Exoplanet Survey Satellite (TESS) full-frame images (FFIs) of observed sectors 1–5. We present a new pipeline called NEMESIS, developed to extract detrended photometry, and to perform transit searches of single-sector data in TESS FFIs. As many M-dwarfs are faint, and are not observed with a two-minute cadence by TESS, FFI transit surveys can provide an empirical validation of how many planets are missed, using the 30-minute cadence data. In this work, we detect 183 threshold crossing events, and present 29 candidate planets for sectors 1–5, 24 of which are new detections. Our sample contains orbital periods ranging from 1.25 to 6.84 days, and planetary radii from 1.26 to 5.31 R {sub ⊕}. With the addition of our new planet candidate detections, along with detections previously observed in sectors 1–5, we calculate an integrated occurrence rate of 2.49 ± 1.58 planets per star, for the period range ∈ [1, 9] days, and planet radius range ∈ [0.5,11] R {sub ⊕}. We project an estimated yield of 122 ± 11 transit detections of nearby M-dwarfs. Of our new candidates, 23 have signal-to-noise ratios >7, transmission spectroscopy metrics >38, and emission spectroscopy metrics >10. We present all of our data products for our planet candidates via the Filtergraph data visualization service, located at https://filtergraph.com/NEMESIS.

47 OTHER INSTRUMENTATION↗
NASA NTRS1979

Landsat-D data acquisition and processing

The Landsat-D system, in which S-band and X-band data links will provide real-time direct transmission of sensor data, is described. System performance objectives include input data quantity of 200 MSS scenes/day and 100 TM scenes/day by the Domestic Communication Satellite, and processing capability, in a pipeline mode, of 2.6 x 10 to the 11th input bits of sensor data per 16-hour day. Data processing techniques, including automated cloudcover assessment, control point library build system, radiometric calibration, and geometric correction are discussed.

Smith, P. L., Jr.↗
DOE OSTI2020

Open Source Visualization and Analysis Platform for 3D Reconstructions of Materials by Transmission Electron Microscopy

Three-dimensional characterization of materials at the nano- and meso-scale has become possible with transmission and scanning transmission electron microscopes (S/TEM). Its importance has extended to a wide class of nanomaterials such as hydrogen fuel cells, solar cells, industrial catalysts, new battery materials and semiconductor devices, as well as spanning high-tech industry, universities, and national labs. While capable instrumentation is abundant, this rapidly expanding demand for high-resolution tomography is bottlenecked by software that is instead tailored for lower-dose, biological applications and not optimized for higher-resolution materials applications. Existing tomography fails to utilize the chemical information provided by S/TEM spectrometers. To address this problem, this project delivered a scalable, fully functional, freely-distributable, open Source materials tomography package with a modern user interface that enables automated acquisition, alignment, and real-time reconstruction of raw tomography data, and provides advanced segmentation, three-dimensional chemical visualization and analysis optimized for materials applications. It has established an extendable framework capable of automation for high-throughput for the tomography of materials from data acquisition to visualization. Phase I and II delivered a full-featured, cross-platform, clean and integrated application for S/TEM materials tomography. It can read projection data from the microscope, with graphical tools for alignment of data, tomographic reconstruction, segmentation, and visualization of the reconstructed 3D volume. The entire pipeline can be saved to an XML state file, enabling fully reproducible data processing and analysis with a full Python environment for the development of custom algorithms, processing, and analysis requirements. Phase IIB extended the application to provide real-time tomographic reconstruction, "live updates" as data is processed, analysis of big data, and multi-channel tomography. Here, quantitative assessment of nanomaterials can occur as data is being recorded on a 3D visualization platform that accommodates additional information from multiple channels. We provide unmatched high-throughput tomography, where the complete tomographic pipeline from measurement to 3D visualization can occur rapidly. The project was extended to offer capabilities for micro-CT, X-ray, neutron, focused ion beam, atomic electron tomography and atom probe tomography. With over 600 transmission electron microscopes worldwide and approximately 50 coming online each year, the demand and impact of an open-source tomography tool is large. Significant opportunities exist in high-tech industry, universities, and national labs to enable or enhance three-dimensional imaging at the nanoscale and bring automated high-throughput approaches that will accelerate progress in materials characterization and metrology. The project supports a service based business model by enabling lab-specific acquisition and processing customization and integration-support and development that will be provided into Phase III and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Graph-Theoretic Approaches to Quantifying Power System Resiliency

Although gaining growing importance, the subject of power system resiliency still lacks a commonly acknowledged metric. As a contribution to solving this complication, in this paper we leverage the concepts of spanning trees and Fiedler value from graph theory to propose two topology-based indices for quantifying the resiliency of power systems. The proposed indices require least information and may be applied to any other flow network, such as water or gas pipeline networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Natural gas maximal load delivery for multi-contingency analysis

An increasing dependence on natural gas has amplified existing vulnerabilities to the power grid, including disruptions to gas transmission networks from natural and man-made disasters. To address the operational challenges arising from these disruptions, we, in this study, consider the problem of estimating the steady-state operating capacity of a damaged gas pipeline network while ensuring the maximal delivery of load. Specifically, we formulate the mixed-integer nonconvex maximal load delivery (MLD) problem, which proves difficult to solve on large-scale networks. To address this challenge, we present a relaxation of the MLD problem and use it to determine bounds on the transport capacity of a gas pipeline system. A rigorous computational evaluation over network models ranging in size from 11 to 4,197 junctions shows that the relaxation-based method is suitable for analyzing the impacts of multi-contingency network disruptions, often converging to the optimal solution of the relaxation in less than ten seconds.

03 NATURAL GAS↗
DOE OSTI2023

Advanced techniques in automated high-resolution scanning transmission electron microscopy

Scanning transmission electron microscopy is a common tool used to study the atomic structure of materials. It is an inherently multimodal tool allowing for the simultaneous acquisition of multiple information channels. Despite its versatility, however, experimental workflows currently rely heavily on experienced human operators and can only acquire data from small regions of a sample at a time. Here, we demonstrate a flexible pipeline-based system for high-throughput acquisition of atomic-resolution structural data using an all-piezo sample stage applied to large-scale imaging of nanoparticles and multimodal data acquisition. As a result, the system is available as part of the user program of the Molecular Foundry at Lawrence Berkeley National Laboratory.

4D-STEM↗
DOE OSTI2021

Fe Thin Film-Coated Optics for Corrosion Monitoring: Optical and Electrochemical Studies

Corrosion proxy materials integrated with an optical sensing platform enable a real-time optical corrosion sensor for natural gas pipelines to prevent methane leaks and catastrophic events. Effects of CO 2 , pH, and film thickness on corrosion of Fe thin films (25, 50, 100 nm) were studied using optical and electrochemical methods in 3.5%wt. NaCl solutions at 30 °C. An increase in light transmission (T%) corresponded to corrosion of Fe thin films. CO 2 accelerated corrosion of Fe thin films due to the lower pH and the promoted corrosion reactions, resulting in a faster increase of T% than without CO 2 or at higher pH. While the corrosion rate increased with increasing film thickness, electrochemical corrosion of Fe thin films was in good agreement with that of bulk carbon steel, verifying that Fe thin films can serve as a representative corrosion proxy when integrated with the optical sensing platform.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Representing Carbon Dioxide Transport and Storage Network Investments within Power System Planning Models

Carbon dioxide (CO 2 ) capture and storage (CCS) is frequently identified as a potential component to achieving a decarbonized power system at least cost; however, power system models frequently lack detailed representation of CO 2 transportation, injection, and storage (CTS) infrastructure. In this paper, we present a novel approach to explicitly represent CO 2 storage potential and CTS infrastructure costs and constraints within a continental-scale power system capacity expansion model. In addition, we evaluate the sensitivity of the results to assumptions about the future costs and performance of CTS components and carbon capture technologies. We find that the quantity of CO 2 captured within the power sector is relatively insensitive to the range of CTS costs explored, suggesting that the cost of CO 2 capture retrofits is a more important driver of CCS implementation than the costs of transportation and storage. Finally, we demonstrate that storage and injection costs account for the predominant share of total costs associated with CTS investment and operation, suggesting that pipeline infrastructure costs have limited influence on the competitiveness of CCS.

24 POWER TRANSMISSION AND DISTRIBUTION↗