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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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All sources NASA NTRS DOE OSTI

NASA NTRS2012

Progress Toward Affordable High Fidelity Combustion Simulations Using Filtered Density Functions for Hypersonic Flows in Complex Geometries

Significant progress has been made in the development of subgrid scale (SGS) closures based on a filtered density function (FDF) for large eddy simulations (LES) of turbulent reacting flows. The FDF is the counterpart of the probability density function (PDF) method, which has proven effective in Reynolds averaged simulations (RAS). However, while systematic progress is being made advancing the FDF models for relatively simple flows and lab-scale flames, the application of these methods in complex geometries and high speed, wall-bounded flows with shocks remains a challenge. The key difficulties are the significant computational cost associated with solving the FDF transport equation and numerically stiff finite rate chemistry. For LES/FDF methods to make a more significant impact in practical applications a pragmatic approach must be taken that significantly reduces the computational cost while maintaining high modeling fidelity. An example of one such ongoing effort is at the NASA Langley Research Center, where the first generation FDF models, namely the scalar filtered mass density function (SFMDF) are being implemented into VULCAN, a production-quality RAS and LES solver widely used for design of high speed propulsion flowpaths. This effort leverages internal and external collaborations to reduce the overall computational cost of high fidelity simulations in VULCAN by: implementing high order methods that allow reduction in the total number of computational cells without loss in accuracy; implementing first generation of high fidelity scalar PDF/FDF models applicable to high-speed compressible flows; coupling RAS/PDF and LES/FDF into a hybrid framework to efficiently and accurately model the effects of combustion in the vicinity of the walls; developing efficient Lagrangian particle tracking algorithms to support robust solutions of the FDF equations for high speed flows; and utilizing finite rate chemistry parametrization, such as flamelet models, to reduce the number of transported reactive species and remove numerical stiffness. This paper briefly introduces the SFMDF model (highlighting key benefits and challenges), and discusses particle tracking for flows with shocks, the hybrid coupled RAS/PDF and LES/FDF model, flamelet generated manifolds (FGM) model, and the Irregularly Portioned Lagrangian Monte Carlo Finite Difference (IPLMCFD) methodology for scalable simulation of high-speed reacting compressible flows.

Drozda, Tomasz G.↗

NASA NTRS2018

High-Efficiency Flexible Multilevel Photon Sieves by Single-Step Laser-Based Fabrication and Optical Analysis

Over the past several decades, the need for high-resolution, high-efficiency, lightweight, high contrast focusing optics has continued to increase due to their applications in fields such as astronomy, spectroscopy, free-space optical communications, defense, and remote sensing. In recent years, photon sieve planar diffractive optics have been developed on flexible, lightweight polyimide substrates. However, transmission efficiencies have continuously been very low (~1-4%), thus impeding the widespread use of photon sieves in practical applications. Here, we present a flexible, lightweight, N = 4 level phase photon sieve with over 25% transmission efficiency; nearly triple that of any other photon sieve reported thus far. In this study, the photon sieve was fabricated via a novel pulsed laser ablation method using an ultraviolet source, and the total time to fabricate a ~3 sq cm sample was tens of seconds. Theoretical analysis of the photon sieve was carried out via the FDTD method, and was in very good agreement with experimental results. We also calculated via FDTD modeling the behavior of higher step (N = 8, 16, 32) photon sieves for further enhanced efficiencies, and show a fundamental limit on photon sieve efficiency of 70% in the limit of increasing step number. This multilevel photon sieve represents a new step in high-resolution diffractive optics, moving towards efficiencies suitable for widespread applications.

Julian, Matthew N.↗

NASA NTRS1980

Alkali metal vapors - Laser spectroscopy and applications

The paper examines the rapidly expanding use of lasers for spectroscopic studies of alkali metal vapors. Since the alkali metals (lithium, sodium, potassium, rubidium and cesium) are theoretically simple ('visible hydrogen'), readily ionized, and strongly interacting with laser light, they represent ideal systems for quantitative understanding of microscopic interconversion mechanisms between photon (e.g., solar or laser), chemical, electrical and thermal energy. The possible implications of such understanding for a wide variety of practical applications (sodium lamps, thermionic converters, magnetohydrodynamic devices, new lasers, 'lithium waterfall' inertial confinement fusion reactors, etc.) are also discussed.

Stwalley, W. C.↗

DOE OSTI2025

Life-Cycle Cost Analysis Framework for Water Efficiency Measures

Life-Cycle Cost Analysis Framework for Water Efficiency Measures: Guidance Designed for Federal Agencies (hereafter referred to as “this report”) provides a technical framework for federal agencies to conduct a life-cycle cost analysis (LCCA) for water efficiency projects in accordance with 42 U.S.C. § 8253. This report leverages insights from the 2023 report, PNNL-34006, Water and Wastewater Annual Price Escalation Rates for Selected Cities Across the United States: 2023 Edition (Unger et al. 2023). The primary objective of this report is to provide a framework to assist federal agencies with evaluating the full economic impact of water efficiency projects by assessing both initial investments and long-term operational benefits. An LCCA can provide a comprehensive view of all costs associated with a water efficiency project, including initial investment, ongoing operations and maintenance (O&M), and eventual disposal or replacement, ensuring the most cost-effective solution is selected. The LCCA methodology outlined in this report enables users to compare base case scenarios with potential alternatives using a standardized present value approach. It incorporates key cost components such as energy, water and wastewater, installation, O&M, and equipment replacement. Additionally, the framework introduces relevant evaluation metrics, such as the net savings and the savings-to-investment ratio, to ensure that water efficiency measures are economically justified over the lifespan of the project. To support practical application, this report also describes various water efficiency strategies that may be analyzed using an LCCA, including plumbing retrofits, irrigation upgrades, alternative water use, and cooling system improvements. By applying this framework, federal agencies can ensure compliance with regulatory mandates while maximizing the return on investment and contributing to resilient water management practices. The information provided in this report is aligned with the Federal Energy Management Program (FEMP) life-cycle cost (LCC) methodology, as conveyed in National Institute of Standards and Technology (NIST) Handbook 135 (Kneifel and Webb 2022). This report is intended to provide relatively high-level guidance, acting as a complement to, rather than a substitute for, that resource.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1973

Facilitating the exploitation of ERTS-1 imagery using snow enhancement techniques

The author has identified the following significant results. The applications of ERTS-1 imagery for geological fracture mapping regardless of season has been repeatedly confirmed. The enhancement provided by a differential cover of snow increases the number and length of fracture-lineaments which can be detected with ERTS-1 data and accelerates the fracture mapping process for a variety of practical applications. The geological mapping benefits of the program will be realized in geographic areas where data are most needed - complex glaciated terrain and areas of deep residual soils. ERTS-1 derived fracture-lineament maps which provide detail well in excess of existing geological maps are not available in the Massachusetts-Connecticut area. The large quantity of new data provided by ERTS-1 may accelerate and improve field mapping now in progress in the area. Numerous other user groups have requested data on the techniques. This represents a major change in operating philosophy for groups who to data judged that snow obscured geological detail.

Wobber, F. J.↗

NASA NTRS1987

Ranger's Legacy

With its Landsat satellites, development of sensors, and advancement of processing techniques, NASA provided the initial technology base for another Earth-benefit application of image processing, Earth resources survey by means of remote sensing. Since each object has its own unique "signature," it is possible to distinguish among surface features and to generate computer-processed imagery identifying specific features of importance to resource managers. This capability, commercialized by Perceptive Scientific Instruments, Inc., offers practical application in such areas as agricultural crop forecasting, rangeland and forest management, land use planning, mineral and petroleum exploration, map making, water quality evaluation and disaster assessment. Major users of the technology have been federal, state, and local governments, but it is making its way into commercial operations, for example, resource exploration companies looking for oil, gas and mineral sources, and timber production firms seeking more efficient treeland management. Supporting both government and private users is a small industry composed of companies producing the processing hardware software. As is the case in the medical application, many of these companies are direct offspring of NASA's work.

Source record↗

NASA NTRS2010

The Utility of the OMI HCHO and NO2 Data Products in Air Quality Decision- Making Activities

We will present three related air quality applications of the OMI HCHO (formaldehyde) and NO2 (nitrogen dioxide) data products, which we us to support mission planning of an OMI-like instrument for the proposed GEO-CAPE satellite that has as one of its objectives to study air quality from space. First, we will discuss a novel and practical application of the data products to the "weight of evidence" in the air quality decision-making process (e.g., State Implementation Plan (SIP)) for a city, region, or state to demonstrate that it is making progress toward attainment of the National Ambient Air Quality Standard (NAAQS) for ozone. Any trend, or lack thereof, in the observed OMI HCHO/NO2, which we use as an air quality indicator, may support that an emission control strategy implemented to reduce ozone is or is not occurring for a metropolitan area. Second, we will discuss how we use variations in the OMI HCHO product as a proxy for variability in the biogenic hydrocarbon, isoprene, which is an important player for the formation of high levels of ozone and the dominant source of HCHO in the eastern U.S. Third, we will discuss the variability of NO2 in the U.S. as indicated by the OMI NO2 product. In addition, we will show the impact of the 2005 hurricanes on pollutant emissions, including those associated with the intensive oil extraction and refining activities, in the Gulf of Mexico region using the OMI NO2 product. The variability of HCHO and NO2 as indicated by OMI helps us to understand changes in the OMI HCHO/NO2 and the implications for ozone formation.

Duncan, Bryan N.↗

DOE OSTI2025

A systematic review of machine learning in groundwater monitoring

With increasing concerns about water scarcity, groundwater has become crucial since this resource provides most of the freshwater needs. However, various human and natural activities often contaminate the groundwater, making it unsuitable for use. Over the years, scientists and engineers have used many methods to predict and track groundwater contamination as part of environmental monitoring. Consequently, there is an urgent need for improved methods, particularly in the face of increasing contamination. Machine learning has sometimes been used to monitor groundwater, air quality, and climate. Traditional methods must be improved due to the complexity and large amount of environmental data. This includes using hybrid models that combine traditional and new techniques. Despite the use of machine learning in many scientific areas, there is a lack of comprehensive reviews focusing on its use in environmental monitoring, especially groundwater monitoring. We aim to fill this gap by exploring machine-learning applications in groundwater monitoring. We discuss relevant methods, their limitations, and future potential. We summarize research on automating data processing and model training using groundwater sensor data. Our research underscores the transformative potential of machine learning to revolutionize long-term groundwater monitoring and contamination detection, providing valuable insights for future research and practical applications.

AI/ML↗

DOE OSTI2023

Reducing ion diffusion at atmospheric pressure through intermingled positive and negative ions

Increasing ion molecule reaction times for ambient ionization techniques can increase sensitivity of detection. Longer reaction times result in an increase in analyte signal relative to the reactant ion signal, however with a subsequent decrease in the total ion intensity. This loss in the total number of ions reaching the detector limits the extent to which increased reaction time can improve detection in practical applications. In this study ion loss was measured using either electric fields or gas flow to control ion transit time. Ion transit times ranged from 40 ms to 8s, which resulted in ion densities ranging from 5 x 10 6 to 2 x 10 4 ions/cm 3 , respectively. These results provide insights into practical reaction time limitations or experimental boundaries when exploring sensitivity enhancements in ambient ionization. When exploring longer reaction times with an atmospheric flow tube coupled to a mass spectrometer (AFT-MS), an additional corona discharge ionization source of the same polarity was added in an attempt to increase total ion signal, but no improvement in signal was observed. This observation suggested that there was a maximum ion density being reached by the corona discharge that could not be increased by adding more of the same polarity ions. A hypothesis was that intermingling both polarities of ions would reduce ion loss and increase the measured ion signal. When two corona discharge sources—one each of positive and negative polarity—were used simultaneously in an AFT-MS, the total ion signal of either polarity measured by the MS was approximately double the current from a single corona discharge source. An increase in the negative ion signal was also observed when ~10 parts-per-trillion vapor levels of an explosive (RDX) were introduced. In this case both the nitrate reactant ions and the RDX signal more than doubled with the addition of a corona discharge source producing positive ions. When intermingling positive and negative ions, an increase in ion current was also observed when the AFT was coupled directly to a Faraday detector or to an ion mobility spectrometer. This was the first demonstration of interfacing the AFT to an IMS. The observations and developments from this work will help in creating more portable instruments with improved sensitivity for detection of chemicals.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Controlling Surface Phase Transition and Chemical Reactivity of O3-Layered Metal Oxide Cathodes for High-Performance Na-Ion Batteries

O3-layered metal oxides are promising cathode materials for high-energy Na-ion batteries (SIBs); however, they suffer from fast capacity fade. In this work, we develop a high-performance O3-NaNi 0.68 Mn 0.22 Co 0.10 O 2 cathode for SIBs toward practical applications by suppressing the formation of a rock salt layer at the cathode surface with an advanced electrolyte. The cathode can deliver a high specific capacity of ~196 mAh g –1 and demonstrates >80% capacity retention over 1000 cycles. NaNi 0.68 Mn 0.22 Co 0.10 O 2 –hard carbon full-cells with practical loading (>2.5 mAh cm –2 ) and lean electrolyte (~40 μL) demonstrate ~82% capacity retention after 450 cycles. A 60 mAh single-layer pouch cell has also been fabricated and demonstrated stable performance. This work represents a significant leap in SIB development and brings new insights to the development of advanced layered metal oxide cathodes for alkaline-ion batteries.

25 ENERGY STORAGE↗

NASA NTRS2003

Stability Analysis of Flow Induced by the Traveling Magnetic Field

Re-circulating flow in molten metal columns can be conveniently induced by the axisymmetric traveling magnetic field. A number of applications can benefit from this technique, such as mixing under microgravity environment, or.crysta1 growth from metallic melts. For small magnetic field excitations, the flow is laminar and stationary. As the imposed field increases, a more complex flow will set up in the cylindrical column. Conditions for stable laminar flow are of importance for practical applications. In this work, a linear stability analysis is performed in order to determine the onset of the bifurcation in the system. Here the analysis is restricted to the axisymmetric modes and the low-frequency regime.

Mazuruk, Konstantin↗

DOE OSTI2020

Deterministic incident-wave elevation prediction in intermediate water depth

Potential performance gains from optimal (non-causal) impedance-matching control of wave energy devices in irregular ocean waves are dependent on deterministic wave elevation prediction techniques that work well in practical applications. Although a number of devices are designed for operation in intermediate water depths, little work has been reported on deterministic wave prediction in such depths. Here, we investigated a deterministic wave-prediction technique based on an approximate propagation model that leads to an analytical formulation, which may be convenient to implement in practice. To improve accuracy, an approach to combine predictions based on multiple up-wave measurement points is evaluated. The overall method is tested using experimental time-series measurements recorded in the U.S. Navy MASK basin in Carderock, MD, USA. For comparison, an alternative prediction approach based on Fourier coefficients is also tested with the same data. Comparison of prediction approaches with direct measurements suggest room for improvement. Possible sources of error including tank reflections are estimated, and potential mitigation approaches are discussed.

16 TIDAL AND WAVE POWER↗

DOE OSTI2020

Chapter 4: Perovskite Solar Cells

In the following sections of this chapter, we first discuss the structural and optoelectronic properties as well as the defect tolerance of halide perovskites for solar cell applications. We then compare the various common device architectures for PSCs and discuss several perovskite fabrication strategies, including solution deposition and vacuum processes, that are key to preparing high -quality perovskite thin films for high-performance PSCs. Many research and development (R&D) challenges exist that must be addressed to ready PSCs for practical applications. We review key issues on stability (moisture, thermal, light, and chemical compatibility), material toxicity (Pb and Pb-free PSCs), and scaling up (material, device architecture, and coating approach selection). A key focus area for further PSC development is characterization. Since perovskite behaves differently than conventional semiconductors, specific characterization protocols must be established to reliably evaluate the progress among different research groups. Stability characterization needs special attention given the complexity of perovskite in response to various external stress factors. Finally, we provide an outlook on the research trends in PSC development toward commercialization.

coating approach selection↗

DOE OSTI2024

Taming the terminological tempest in invasion science

ABSTRACT Standardised terminology in science is important for clarity of interpretation and communication. In invasion science – a dynamic and rapidly evolving discipline – the proliferation of technical terminology has lacked a standardised framework for its development. The result is a convoluted and inconsistent usage of terminology, with various discrepancies in descriptions of damage and interventions. A standardised framework is therefore needed for a clear, universally applicable, and consistent terminology to promote more effective communication across researchers, stakeholders, and policymakers. Inconsistencies in terminology stem from the exponential increase in scientific publications on the patterns and processes of biological invasions authored by experts from various disciplines and countries since the 1990s, as well as publications by legislators and policymakers focusing on practical applications, regulations, and management of resources. Aligning and standardising terminology across stakeholders remains a challenge in invasion science. Here, we review and evaluate the multiple terms used in invasion science (e.g. ‘non‐native’, ‘alien’, ‘invasive’ or ‘invader’, ‘exotic’, ‘non‐indigenous’, ‘naturalised’, ‘pest’) to propose a more simplified and standardised terminology. The streamlined framework we propose and translate into 28 other languages is based on the terms ( i ) ‘non‐native’, denoting species transported beyond their natural biogeographic range, ( ii ) ‘established non‐native’, i.e. those non‐native species that have established self‐sustaining populations in their new location(s) in the wild, and ( iii ) ‘invasive non‐native’ – populations of established non‐native species that have recently spread or are spreading rapidly in their invaded range actively or passively with or without human mediation. We also highlight the importance of conceptualising ‘spread’ for classifying invasiveness and ‘impact’ for management. Finally, we propose a protocol for classifying populations based on ( i ) dispersal mechanism, ( ii ) species origin, ( iii ) population status, and ( iv ) impact. Collectively and without introducing new terminology, the framework that we present aims to facilitate effective communication and collaboration in invasion science and management of non‐native species.

Soto, Ismael↗

NASA NTRS2003

Stability Analysis of Flow Induced by the Traveling Magnetic Field

Re-circulating flow in molten metal columns can be conveniently induced by the axisymmetric traveling magnetic field. A number of applications can benefit from this technique, such as mixing under microgravity environment, or crysta1 growth from metallic melts. For small magnetic field excitations, the flow is laminar and stationary. As the imposed field increases, a more complex flow will set up in the cylindrical column. Conditions for stable laminar flow are of importance for practical applications. In this work, a linear stability analysis is performed in order to determine the onset of the bifurcation in the system. Here the analysis is restricted to the axisymmetric modes and the low-frequency regime.

Mazuruk, Konstantin↗

DOE OSTI2025

Remote Sensing and Fluxes Upscaling for Real-world Impact (Workshop Report)

The "Remote Sensing and Fluxes Upscaling for Real-world Impact" workshop, held on July 9-10, 2024, at Lawrence Berkeley National Lab, was a collaborative effort led by the AmeriFlux Management Project, NEON, and the Carbon Dew Community of Practice. The event brought together over 200 registrants and approximately 100 attendees each day, including leading experts, researchers, and practitioners. The primary focus was on bridging the gap between cutting-edge research and practical applications in environmental monitoring by integrating remote sensing and flux data. Key themes included the importance of site-level measurements for validating remote sensing products, providing nature-based climate solutions, and addressing challenges such as instrument costs and the need for standardized methods. At the regional scale, discussions centered on addressing spatial heterogeneity and using high-resolution remote sensing and machine learning methods to enhance data interpretation. Global scale challenges included data consistency, gap filling, and accurate emission source identification, with opportunities for international collaboration and standardized practices to improve global carbon budget assessments. The workshop emphasized the critical need for integrating data across local, regional, and global scales through explicit scale-matching and developed a workflow for scaling flux data using "straight shot" and "explicit nesting" approaches. The event highlighted the importance of connecting scientific research with real-world applications in carbon, energy, and water management, ensuring that advancements translate into tangible societal benefits. These insights will guide future research, technology transfer, and collaboration, maximizing the potential of environmental fluxes to address real-world challenges.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Feature Extraction for Pipeline Defects Inspection Based Upon Distributed Acoustic Fiber Optic Sensing Data

Fiber-optic distributed acoustic sensing (DAS) is becoming an increasingly important tool for real-time monitoring of energy and civil infrastructure structural health such as pipelines. We present a systematic theoretical study of the potential for DAS to be directly coupled with guided ultrasonic waves typically used in conventional acoustic non-destructive evaluation (NDE) methods for real-time pipeline health monitoring. We are referring to this innovative new NDE technique as ultrasonic guided wave and optical fiber sensor fusion. In the practical application of DAS coupled with guided ultrasonic waves, the structural design of (1) the specific guided waves excited, (2) the physical installation of the acoustic transducers and the fiber optic sensors, and (3) the functional performance specifications (gauge length, sensitivity, Etc.) of fiber optic DAS have an important influence on overall capabilities of the monitoring system. Meanwhile, physics-based analysis of acoustic waves is still a challenge due to the complex nature of the Lamb wave when it propagates, scatters, and disperses in the presence of structural defects. In this work, we simulate carbon steel pipes relevant for oil and gas pipeline applications with diameters of approximately 6-12” and wall thickness of 0.5” as the objects to be monitored. By establishing and implementing these capabilities, we seek to pursue an in-depth study on structural parameter optimization of DAS network, measurement range, and signal processing with an ultimate goal of increasing the sensitivity and efficacy of DAS to defect identification for various modes of corrosion expected in practice. To study the characteristics of scattered acoustic waves and performance of DAS for defect identification, we simulated the response of DAS for multiple pipe structures, defect types, and DAS sensor network configuration using finite element software Ansys, then the properties of signal response are extracted to construct defect-sensitive features. The raw data simulated, and the associated features extracted can ultimately be utilized as annotated training data to benchmark various designs for DAS applications, guided acoustic excitation sources, and learning model parameters to enhance early detection of potentially problematic defects.

Pipeline Defects Inspection, Fiber-optic sensors, ↗

DOE OSTI2020

Simulation-driven optimization of high-order meshes in ALE hydrodynamics

Here we propose tools for high-order mesh optimization and demonstrate their benefits in the context of multi-material Arbitrary Lagrangian-Eulerian (ALE) compressible shock hydrodynamic applications. The mesh optimization process is driven by information provided by the simulation which uses the optimized mesh, such as shock positions, material regions, known error estimates, etc. These simulation features are usually represented discretely, for instance, as finite element functions on the Lagrangian mesh. The discrete nature of the input is critical for the practical applicability of the algorithms we propose and distinguishes this work from approaches that strictly require analytical information. Our methods are based on node movement through a high-order extension of the Target-Matrix Optimization Paradigm (TMOP). The proposed formulation is fully algebraic and relies only on local Jacobian matrices, so it is applicable to all types of mesh elements, in 2D and 3D, and any order of the mesh. We discuss the notions of constructing adaptive target matrices and obtaining their derivatives, reconstructing discrete data in intermediate meshes, node limiting that enables improvement of global mesh quality while preserving space-dependent local mesh features, and appropriate normalization of the objective function. The adaptivity methods are combined with automatic ALE triggers that can provide robustness of the mesh evolution and avoid excessive remap procedures. The benefits of the new high-order TMOP technology are illustrated on several simulations performed in the high-order ALE application BLAST.

97 MATHEMATICS AND COMPUTING↗