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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 217 records · Page 12

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DOE OSTI2024

Environmental life-cycle analysis of hydrogen technology pathways in the United States

Hydrogen is a zero-carbon energy carrier with potential to decarbonize industrial and transportation sectors, but its life-cycle greenhouse gas (GHG) emissions depend on its energy supply chain and carbon management measures (e.g., carbon capture and storage). Global support for clean hydrogen production and use has recently intensified. In the United States, Congress passed several laws that incentivize the production and use of renewable and low-carbon hydrogen, such as the Bipartisan Infrastructure Law (BIL) in 2021 and the Inflation Reduction Act (IRA) in 2022, which provides tax credits of up to $3/kg depending on the carbon intensity of the produced hydrogen. A comprehensive life-cycle accounting of GHG emissions associated with hydrogen production is needed to determine the carbon intensity of hydrogen throughout its value chain. In the United States, Argonne’s R&D GREET ® (Greenhouse Gases, Regulated emissions, and Energy use in Technologies) model has been widely used for hydrogen carbon intensity calculations. This paper describes the major hydrogen technology pathways considered in the United States and provides data sources and carbon intensity results for each of the hydrogen production and delivery pathways using consistent system boundaries and most recent technology performance and supply chain data.

Elgowainy, Amgad↗

DOE OSTI2025

Product ion distributions using H 3 O + proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS): mechanisms, transmission effects, and instrument-to-instrument variability

Abstract. Proton-transfer-reaction mass spectrometry (PTR-MS) using hydronium ion (H3O+) ionization is widely used for the measurement of volatile organic compounds (VOCs) both indoors and outdoors. H3O+ ionization, as well as the associated chemistry in an ion–molecule reactor, is known to generate product ion distributions (PIDs) that include other product ions besides the proton-transfer product. We present a method, using gas-chromatography pre-separation, for quantifying PIDs from PTR-MS measurements of nearly 100 VOCs of different functional types including alcohols, ketones, aldehydes, acids, aromatics, organohalides, and alkenes. We characterize instrument configuration effects on PIDs and find that reactor reduced electric field strength (E/N), ion optic voltage gradients, and quadrupole settings have the strongest impact on measured PIDs. Through an interlaboratory comparison of PIDs measured from calibration cylinders, we characterized the variability of PID production from the same model of PTR-MS across seven participating laboratories. Product ion variability was generally smaller (e.g., < 20 %) for ions with larger contributions to the PIDs (e.g., > 0.30) but less predictable for product ions formed through O2+ and NO+ reactions. We present a publicly available library of H3O+ PTR-MS PIDs that will be updated periodically with user-provided data for the continued investigation into instrument-to-instrument variability of PIDs.

Link, Michael F. (ORCID:0000000218412455)↗

NASA NTRS1982

Adaptive identification for the dynamics of large space structures

A new approach for identifying the dynamics of large space structures using noisy measurements is presented. In this approach, a modal system description is avoided and, hence, the a priori specification of model order. Instead, the system's order is recursively determined on-line, along with its parameters, using recursive lattice filters which are widely used in adaptive signal processing. The order determination is carried out based on statistical hypothesis testing theory. The approach is illustrated for the problem of identifying the structural dynamic characteristics of a free-free beam. Results on the effectiveness and accuracy of the identification scheme with respect to noise levels, sampling rates, and data window sizes are presented

Sundararajan, N.↗

NASA NTRS1987

Control considerations for high frequency, resonant, power processing equipment used in large systems

Addressed is a class of resonant power processing equipment designed to be used in an integrated high frequency (20 KHz domain), utility power system for large, multi-user spacecraft and other aerospace vehicles. It describes a hardware approach, which has been the basis for parametric and physical data used to justify the selection of high frequency ac as the PMAD baseline for the space station. This paper is part of a larger effort undertaken by NASA and General Dynamics to be sure that all potential space station contractors and other aerospace power system designers understand and can comfortably use this technology, which is now widely used in the commercial sector. In this paper, we will examine control requirements, stability, and operational modes; and their hardware impacts from an integrated system point of view. The current space station PMAD system will provide the overall requirements model to develop an understanding of the performance of this type of system with regard to: (1) regulation; (2) power bus stability and voltage control; (3) source impedance; (4) transient response; (5) power factor effects, and (6) limits and overloads.

Mildice, J. W.↗

NASA NTRS1987

Control considerations for high frequency, resonant, power processing equipment used in large systems

Mildice, J. W.↗

NASA NTRS1993

Stagnation flowfield analysis for an aeroassisted vehicle

Hypersonic reactive flowfield results are presented for the flow about an axisymmetric representation of a three-dimensional aeroassisted vehicle using the viscous shock-layer (VSL) and Navier-Stokes (NS) equations for low- and high-altitude entry conditions, respectively. Solutions are limited to the stagnation region. The NS results have been obtained by employing the surface recombination boundary condition for an 11-species air model, whereas the VSL calculations are carried out by using a 5-species model. Three widely used surface recombination rate models are implemented with these two flowfield calculation procedures. The low-density (or high altitude) NS solutions are obtained with surface slip equations and compare quite well with the direct simulation Monte Carlo predictions. For higher densities (or lower altitudes), the no-slip VSL solutions are considered adequate. Results from this study highlight the effect of surface catalyticity on surface heating and electron number density.

Gupta, Roop N.↗

NASA NTRS1982

Spinoff from Space Fuel

In 1963, under contract with NASA, Air Products and Chemicals, Inc. built a 32 1/2 ton-a-day plant to meet the soaring demand for liquid hydrogen created by the Apollo missions and J-2 ground testing. Air Product's experience in government research, development and production of liquid hydrogen served as the springboard for a broad variety of practical, Earth-use applications. Today, liquid hydrogen is widely used among many industries including petroleum refineries in gasoline production and chemical and pharmaceutical firms in the manufacturing of fertilizers and drugs. New commercial applications are growing at the rate of about ten percent per year. Input from government research, Air Product's own technology development, and the large space program requirements combined to make the company the prime manufacturer of liquid hydrogen and enabled them to add a new 30-ton plant near New Orleans.

Source record↗

NASA NTRS2011

Development and Progress in Enabling the Photocatalyst Ti02 Visible-Light-Active

Photocatalytic oxidation (PCO) of organic contaminants is a promising air and water quality management approach which offers energy and cost savings compared to thermal catalytic oxidation (TCO). The most widely used photocatalyst, anatase TiO2, has a wide band gap (3.2 eV) and is activated by UV photons. Since solar radiation consists of less than 4% UV, but contains 45% visible light, catalysts capable of utilizing these visible photons need to be developed to make peo approaches more efficient, economical, and safe. Researchers have attempted various approaches to enable TiO2 to be visible-light-active with varied degrees of success'. Strategies attempted thus far fall into three categories based on their electrochemical' mechanisms: 1) narrowing the band gap of TiO2 by implantation of transition metal elements or nonmetal elements such as N, S, and C, 2) modifying electron-transfer processes during PCO by adsorbing sensitizing dyes, and 3) employing light-induced interfacial electron transfer in the heteronanojunction systems consisting of narrow band gap semiconductors represented by metal sulfides and TiO2. There are diverse technical approaches to implement each of these strategies. This paper presents a review of these approaches and results of the photocatalytic activity and photonic efficiency of the end .products under visible light. Although resulting visible-light-active (VLA) photocatalysts show promise, there is often no comparison with unmodified TiO2 under UV. In a limited number of studies where such comparison was provided, the UV-induced catalytic activity of bare TiO2 is much greater than the visible-light-induced catalytic activity of the VLA catalyst. Furthermore, VLA-catalysts have much lower quantum efficiency compared to the approx.50% quantum efficiency of UV-catalysts. This stresses the need for continuing research in this area.

Levine, Lanfang H.↗

NASA NTRS2013

Enabling a Better Aft Heat Shield Solution for Future Mars Science Laboratory Class Vehicles

System studies are described that compare masses and estimated manufacturing costs of options for the as‐flown Mars Science Laboratory (MSL) aft body Thermal Light Weight Ablator (SLA) 561‐V and its thickness was not optimized using the standard TPS Sizer Tool widely used for heat shield design. Use of the TPS sizing tool suggests that optimization of the SLA thickness could reduce the aft heat shield mass by 40 percent. Analysis of the predicted aft‐shell aerothermodynamics suggests that the bulk of MSL class entry vehicle heat shields could incorporate Advanced Flexible Reusable Surface Insulation (AFRSI). AFRSI has a wellestablished record of relatively inexpensive manufacturing and flight certification based on its use on the lee side of the Space Shuttle. Runs with the TPS Sizer show that the AFRSI solution would be 60 percent lighter than the as‐flown SLA. The issue of Reaction Control System (RCS) heating on the aft shell could be addressed by locally impregnating the AFRSI with silicone to enhance its robustness to short bursts ofheating. Stagnation point arcjet testing has shown that silicone impregnated AFRSI performs well at heat rates of 115 W/cm2 and 0.1 atmospheres for a duration of 40 seconds, far beyond conditions that are expected for MSL class vehicles. The paper concludes with a discussion of manufacturing processes for AFRSI, impregnation approaches and relative cost comparisons to the SLA solution.

McGuire, Mary K.↗

DOE OSTI2026

Thermal Performance of Spandrel Assemblies in Glazed Wall Systems: Laboratory Test Design – Challenges and Test Results

Accurate thermal performance calculation procedures for opaque spandrel areas in curtain wall and window wall systems are essential for rating systems when comparing spandrel systems. However, there is a lack of consensus in thermal modeling needed for accurately characterizing heat transfer through spandrel assemblies due to the complex arrangement of materials and structural components. Several studies indicate that conventional 2D thermal simulations may overestimate R-values by 30% compared to physical testing and 3D simulations. Detailed simulations and well-curated laboratory test data are necessary to build confidence in simulation models, which will later be used to develop correlations to improve widely used conventional 2D thermal simulations. This study aims to experimentally test heat transfer through various spandrel assemblies to validate 3D simulation models. Also, the challenges of conducting a thorough testing design along with the solutions would be documented. The team developed a design for testing spandrel assemblies, making appropriate modifications to the existing heat, air, and moisture (HAM) chamber to accommodate the testing needs. Two moveable baffles were designed and fabricated to guide airflow direction parallel to the test article surface. The data acquisition capabilities in the chamber were upgraded to add more than two hundred sensors to the climate and indoor side of the chamber. The goal is to provide a quality dataset for validating complex 3D modeling simulations, which will be used to develop improved thermal simulation techniques that more accurately represent the thermal behavior of spandrel assemblies and their integration within the building envelope. This paper will summarize the results for the boundary conditions of the testing and the temperature variation across different locations of the spandrel assemblies.

Kunwar, Niraj [ORNL] (ORCID:0000000263457652)↗

DOE OSTI2024

Autonomous convergence of STM control parameters using Bayesian optimization

Scanning tunneling microscopy (STM) is a widely used tool for atomic imaging of novel materials and their surface energetics. However, the optimization of the imaging conditions is a tedious process due to the extremely sensitive tip–surface interaction, thus limiting the throughput efficiency. In this paper, we deploy a machine learning (ML)-based framework to achieve optimal atomically resolved imaging conditions in real time. The experimental workflow leverages the Bayesian optimization (BO) method to rapidly improve the image quality, defined by the peak intensity in the Fourier space. The outcome of the BO prediction is incorporated into the microscope controls, i.e., the current setpoint and the tip bias, to dynamically improve the STM scan conditions. We present strategies to either selectively explore or exploit across the parameter space. As a result, suitable policies are developed for autonomous convergence of the control parameters. The ML-based framework serves as a general workflow methodology across a wide range of materials.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Analysis of the laser welding keyhole using inline coherent imaging

Laser beam welding is a widely used fusion welding process in many industrial applications such as automotive, aerospace, energy, defense, and medical products. Industry has a fundamental need to model the laser welding process to minimize experimental testing and improve confidence in production welds. However, computational models attempting to predict weld formation are limited by an incomplete understanding of the beam-material interactions. As a consequence, these models do not accurately predict the mechanisms associated with laser weld formation. To improve the current state of prediction capabilities, it is vital to better detect/measure the physical aspects of the weld pool during high energy density welding. In this work, a novel real-time laser weld monitoring device using inline coherent imaging (ICI) was used to provide a fundamental understanding of laser weld formation via vaporization. The objective of this work was to investigate and quantify the relationship relating laser weld parameters and the vapor capillary (keyhole) through a state-of-the-art measurement technique. Bead-on-plate laser beam welds were produced with partial penetration on 304L stainless steel, 2205 duplex stainless steel, and Ti-6Al-4V. Keyhole monitoring was performed using a commercially available ICI system to collect keyhole penetration data in real time. These measurements were reconstructed to generate the vapor capillary shape at different welding parameters. Process parameters significantly influenced the keyhole shape and the keyhole root position relative to the process beam. Finally, the keyhole geometry showed distinct differences between the stainless steel alloys and Ti-6Al-4V.

2205↗

DOE OSTI2025

Text-mined dataset of solid-state syntheses with impurity phases using Large Language Model

Solid-state synthesis is widely used to obtain various inorganic materials, such as battery materials and bulk thermoelectrics. Despite its prevalence, the process remains challenging due to the lack of a general theory and well-understood underlying reaction mechanisms. While prior works have successfully extracted structured datasets from literature, they often neglect product phase purity or yield. In this work, we construct a solid-state synthesis dataset consisting of 80,806 syntheses extracted with a large language model (LLM), including 18,869 reactions with impurity phase(s). Our dataset not only validates expected thermodynamic trends for impurity phase formation but also identifies challenging cases where impurity phases emerge even when the target phase is significantly more stable.

Lee, Sanghoon↗

DOE OSTI2021

Bennett-Brassard 1984 quantum key distribution using conjugate homodyne detection

Optical homodyne detection has been widely used in continuous-variable (CV) quantum information processing for measuring field quadrature. In this paper we explore the possibility of operating a conjugate homodyne detection system in “photon counting” mode to implement discrete-variable (DV) quantum key distribution (QKD). A conjugate homodyne detection system, which consists of a beam splitter followed by two optical homodyne detectors, can simultaneously measure a pair of conjugate quadratures X and P of the incoming quantum state. In classical electrodynamics, X 2 + P 2 is proportional to the energy (the photon number) of the input light. In quantum optics, X and P do not commute and thus the above photon-number measurement is intrinsically noisy. This implies that a blind application of standard security proofs of QKD could result in pessimistic performance. We overcome this obstacle by taking advantage of two special features of the proposed detection scheme. First, the fundamental detection noise associated with vacuum fluctuations cannot be manipulated by an external adversary. Second, the ability to reconstruct the photon number distribution at the receiver's end can place additional constraints on possible attacks from the adversary. As an example, we study the security of the BB84 QKD using conjugate homodyne detection and evaluate its performance through numerical simulations. This study may open the door to a family of QKD protocols, complementary to the well-established DV-QKD based on single-photon detection and CV-QKD based on coherent detection.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Materials characterization: Can artificial intelligence be used to address reproducibility challenges?

Material characterization techniques are widely used to characterize the physical and chemical properties of materials at the nanoscale and, thus, play central roles in material scientific discoveries. However, the large and complex datasets generated by these techniques often require significant human effort to interpret and extract meaningful physicochemical insights. Artificial intelligence (AI) techniques such as machine learning (ML) have the potential to improve the efficiency and accuracy of surface analysis by automating data analysis and interpretation. In this perspective paper, we review the current role of AI in surface analysis and discuss its future potential to accelerate discoveries in surface science, materials science, and interface science. We highlight several applications where AI has already been used to analyze surface analysis data, including the identification of crystal structures from XRD data, analysis of XPS spectra for surface composition, and the interpretation of TEM and SEM images for particle morphology and size. We also discuss the challenges and opportunities associated with the integration of AI into surface analysis workflows. These include the need for large and diverse datasets for training ML models, the importance of feature selection and representation, and the potential for ML to enable new insights and discoveries by identifying patterns and relationships in complex datasets. Most importantly, AI analyzed data must not just find the best mathematical description of the data, but it must find the most physical and chemically meaningful results. In addition, the need for reproducibility in scientific research has become increasingly important in recent years. The advancement of AI, including both conventional and the increasing popular deep learning, is showing promise in addressing those challenges by enabling the execution and verification of scientific progress. By training models on large experimental datasets and providing automated analysis and data interpretation, AI can help to ensure that scientific results are reproducible and reliable. Although integration of knowledge and AI models must be considered for the transparency and interpretability of models, the incorporation of AI into the data collection and processing workflow will significantly enhance the efficiency and accuracy of various surface analysis techniques and deepen our understanding at an accelerated pace.

Materials Science↗

DOE OSTI2021

PV Reference Cells for Outdoor Use: An Investigation of Calibration Factors

Reference cells are widely used in the photovoltaic (PV) industry to measure irradiance. For field applications and outdoor use, a variety of products are on the market, and they are often perceived as a low-cost alternative to thermopile radiometers. But reference cell characteristics differ substantially from the latter, therefore measurements made by one category of instrument cannot be substituted for or directly compared with the other. The National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory is currently in a multiyear effort to develop guidance and recommendations for the design and use of outdoor reference cells, with a view to reducing inconsistencies and measurement uncertainty. The core of this effort is the long-term deployment of 39 units of 10 distinct types made by 6 manufacturers. This report compares the calibration factors provided by manufacturers - which most users rely upon - to those measured at a high level of accuracy by NREL's Cell Lab. It also reports on the application of the Broadband Outdoor Radiometer Calibration (BORCAL) method to reference cells. As a group, the factory calibrations for the crystalline silicon cells showed a small positive bias of +0.7%, with a tight distribution around this value. This is a very good result for the manufacturers. The two World Photovoltaic Scale cells constituted outliers, with a mean deviation of -0.8%, which is still within the reported uncertainty ranges. The data collected during the BORCAL procedures show a strong and systematic fluctuation of the apparent responsivity of the reference cells over the course of a day, which was anticipated. Consequently, the standard BORCAL R@45 calibration factors underestimated the reference cell responsivities by 1%-4%. An alternate responsivity indicator was developed, R'@30, incorporating adjustments for temperature response, spectral response, and directional response. This reduced the mean deviation to -0.4% compared to the Cell Lab. Further, two independent BORCAL sessions were able to produce the same values to within ±0.2%. This could be a viable approach for verifying reference cells using existing BORCAL infrastructure, for example, to evaluate their long-term stability. The daily profiles of responsivity obtained during the BORCAL sessions (provided in Appendix A) show clear patterns of differences between models, which provides evidence that their directional responses differ from each other; thus, two sensors that are calibrated correctly might give the same reading at 30° zenith angle but systematically different readings at 60°. The impact of these inconsistencies in field operation will be quantified using the long-term observations started in 2020.

14 SOLAR ENERGY↗

NASA NTRS1999

Physiologic and Functional Responses of MS Patients to Body Cooling Using Commercially Available Cooling Garments

Personal cooling systems are widely used in industrial and aerospace environments to alleviate thermal stress. Increasingly they are also used by heat sensitive multiple sclerosis (HSMS) patients to relieve symptoms and improve quality of life. There are a variety of cooling systems commercially available to the MS community. However, little information is available regarding the comparative physiological changes produced by routine operation of these various systems. The objective of this study was to document and compare the patient response to two passive cooling vests and one active cooling garment. The Life Enhancement Technology, Inc. (LET) lightweight active cooling vest with cap, the MicroClimate Systems (MCS) Change of Phase garment, and the Steele Vest were each used to cool 13 male and 13 female MS subjects (31 to 67 yr.) in this study. The subjects, seated in an upright position at normal room temperature (approximately 22 C), were tested with one of the cooling garments. Oral, fight and left ear temperatures were logged manually every 5 min. An-n, leg, chest and rectal temperatures; heart rate; and respiration were recorded continuously on a U.F.I., Inc. Biolog ambulatory monitor. Each subject was given a series of subjective and objective evaluation tests before and after cooling. The LET and Steele vests test groups had similar, significant (P less than 0.01) cooling effects on oral and ear canal temperature, which decreased approximately 0.4 C, and 0.3 C, respectively. Core temperature increased (N.S.) with all three vests during cooling. The LET vest produced the coldest (P less than 0.01) skin temperature. Overall, the LET vest provided the most improvement on subjective and objective performance measures. These results show that the garment configurations tested do not elicit a similar thermal response in all MS patients. Cooling with the LET active garment configuration resulted in the lowest body temperatures for the MS subjects; cooling with the MCS vest was least effective. For functional responses, the LET test group performed better than the other two vests.

Ku, Yu-Tsuan E.↗

NASA NTRS1997

On the Implementation of a Land Cover Classification System for SAR Images Using Khoros

The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.

Medina Revera, Edwin J.↗