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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 721 records · Page 40

Vertiport Management from Simulation to Flight: Continued Human Factors Assessment of Vertiport Operations

The Urban Air Mobility concept envisions a new future for transportation in urban environments, primarily focused around vertiport operations. A vertiport refers to an identifiable ground or elevated area used for the vertical takeoff and landing of an aircraft. One critical role within vertiport operations that has been proposed but is under-researched is the vertiport manager. The vertiport manager is expected to manage the ground-to-air operations at the vertiport, but their precise responsibilities, tasks, and challenges are currently undefined. The High Density Vertiplex Subproject at NASA is responsible for developing and testing technologies, concepts, and architectures that will support the infrastructure needed for terminal environments around vertiports. Our previous work investigated ground control station operators performing simulated and live flight operations within a remote operations environment. In the current study, we extended from our previous work to explore the role of a vertiport manager. Specifically, we investigated five participants serving as a vertiport manager across both simulated and live flight operations. We performed multiple knowledge elicitation techniques, a thematic content analysis of qualitative data, and naturalistic observations to create a list of insights, design and training recommendations, and a simplified cognitive task diagram of the vertiport manager’s primary task. Findings from this study are discussed within the context of the current debate on the degree to which this role should be automated. A third alternative is suggested to allow a human vertiport manager to be successful by teaming with increasingly autonomous systems, designing the role to improve safety and efficiency of Urban Air Mobility operations.

AAM↗

SU-E-J-248: Contributions of Tumor and Stroma Phenotyping in Computer-Aided Diagnosis

Purpose: To gain insight into the role of parenchyma stroma in the characterization of breast tumors by incorporating computerized mammographic parenchyma assessment into breast CADx in the task of distinguishing between malignant and benign lesions. Methods: This study was performed on 182 biopsy-proven breast mass lesions, including 76 benign and 106 malignant lesions. For each full-field digital mammogram (FFDM) case, our quantitative imaging analysis was performed on both the tumor and a region-of-interest (ROI) from the normal contralateral breast. The lesion characterization includes automatic lesion segmentation and feature extraction. Radiographic texture analysis (RTA) was applied on the normal ROIs to assess the mammographic parenchymal patterns of these contralateral normal breasts. Classification performance of both individual computer extracted features and the output from a Bayesian artificial neural network (BANN) were evaluated with a leave-one-lesion-out method using receiver operating characteristic (ROC) analysis with area under the curve (AUC) as the figure of merit. Results: Lesion characterization included computer-extracted phenotypes of spiculation, size, shape, and margin. For parenchymal pattern characterization, five texture features were selected, including power law beta, contrast, and edge gradient. Merging of these computer-selected features using BANN classifiers yielded AUC values of 0.79 (SE=0.03) and 0.67 (SE=0.04) in the task of distinguishing between malignant and benign lesions using only tumor phenotypes and texture features from the contralateral breasts, respectively. Incorporation of tumor phenotypes with parenchyma texture features into the BANN yielded improved classification performance with an AUC value of 0.83 (SE=0.03) in the task of differentiating malignant from benign lesions. Conclusion: Combining computerized tumor and parenchyma phenotyping was found to significantly improve breast cancer diagnostic accuracy highlighting the need to consider both tumor and stroma in decision making. Funding: University of Chicago Dean Bridge Fund, NCI U24-CA143848-05, P50-CA58223 Breast SPORE program, and Breast Cancer Research Foundation. COI: MLG is a stockholder in R2 technology/Hologic and receives royalties from Hologic, GE Medical Systems, MEDIAN Technologies, Riverain Medical, Mitsubishi, and Toshiba. MLG is a cofounder and stockholder in Quantitative Insights.

60 APPLIED LIFE SCIENCES↗

Continued Analysis of EUVE Solar System Observations

This is the final report for this project. We proposed to continue our work on extracting important results from the EUVE (Extreme UltraViolet Explorer) archive of lunar and jovian system observations. In particular, we planned to: (1) produce several monochromatic images of the Moon at the wavelengths of the brightest solar EUV emission lines; (2) search for evidence of soft X-ray emissions from the Moon and/or X-ray fluorescence at specific EUV wavelengths; (3) search for localized EUV and soft X-ray emissions associated with each of the Galilean satellites; (4) search for correlations between localized Io Plasma Torus (IPT) brightness and volcanic activity on Io; (5) search for soft X-ray emissions from Jupiter; and (6) determine the long term variability of He 58.4 nm emissions from Jupiter, and relate these to solar variability. However, the ADP review panel suggested that the work concentrate on the Jupiter/IPT observations, and provided half the requested funding. Thus we have performed no work on the first two tasks, and instead concentrated on the last three. In addition we used funds from this project to support reduction and analysis of EUVE observations of Venus. While this was not part of the original statement of work, it is entirely in keeping with extracting important results from EUVE solar system observations.

Gladstone, G. Randall↗

Nonnegative tensor factorization for contaminant source identification

Unsupervised Machine Learning (ML) is becoming increasingly popular for solving various types of data analytics problems including feature extraction, blind source separation, exploratory analyses, model diagnostics, etc. In this work, we have developed a new unsupervised ML method based on Nonnegative Tensor Factorization (NTF) for identification of the original groundwater types (including contaminant sources) present in geochemical mixtures observed in an aquifer. Frequently, groundwater types with different geochemical signatures are related to different background and/or contamination sources. The characterization of groundwater mixing processes is a challenging but very important task critical for any environmental management project aiming to characterize the fate and transport of contaminants in the subsurface and perform contaminant remediation. This task typically requires solving complex inverse models representing groundwater flow and geochemical transport in the aquifer, where the inverse analysis accounts for available site data. Usually, the model is calibrated against the available data characterizing the spatial and temporal distribution of the observed geochemical types. Numerous different geochemical constituents and processes may need to be simulated in these models which further complicates the analyses. Additionally, the application of inverse methods may introduce biases in the analyses through the assumptions made in the model development process. Here, we substitute the model inversion with unsupervised ML analysis. The ML analysis does not make any assumptions about underlying physical and geochemical processes occurring in the aquifer. Our ML methodology, called NTFk, is capable of identifying (1) the unknown number of groundwater types (contaminant sources) present in the aquifer, (2) the original geochemical concentrations (signatures) of these groundwater types and (3) spatial and temporal dynamics in the mixing of these groundwater types. These results are obtained only from the measured geochemical data without any additional site information. In general, the NTFk methodology allows for interpretation of large high-dimensional datasets representing diverse spatial and temporal components such as state variables and velocities. NTFk has been tested on synthetic and real-world site three-dimensional datasets. Finally, the NTFk algorithm is designed to work with geochemical data represented in the form of concentrations, ratios (of two constituents; for example, isotope ratios), and delta notations (standard normalized stable isotope ratios).

58 GEOSCIENCES↗

Considerations for Corridor and Community DC Fast Charging Complex System Design

The Idaho National Laboratory (INL), a U.S. Department of Energy (DOE) national laboratory located in Idaho Falls, Idaho, has been DOE’s lead laboratory for the field testing of light-duty plug-in electric vehicles (PEVs), charging infrastructure, and other alternative vehicle technologies for 25 years. INL has tested and collected data from more than 17,000 charging stations, documenting efficiencies, charge profiles, and PEV drivers’ behaviors when using charging infrastructure. Based on the experience of INL staff and support personnel, DOE requested that INL perform three tasks: • Identify pertinent lessons learned from previous direct current (DC) fast charger (DCFC) deployment and data collection activities in order to perform an analysis of the experience to date with DC fast charging systems • Establish the criteria for siting DC fast charging systems, including access to current or future sizeable penetrations of PEVs and existing power, the potential to be used by local (intracity) as well as pass-through (intercity) PEV drivers, expandability, and accessible to the federal highway system • Develop a draft system specification that lists the components that will be incorporated in a DC fast charging complexes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enhancement of Eye Tracking for Highly Dynamic Displays

Eye-Tracking and Sandia have established a collaborative arrangement whereby the two entities worked in a no-funds arrangement to study and share information about interface, software and algorithmic capabilities for dynamic, user-driven workflows. Sandia researchers developed the GazeAppraise algorithm for analysis of so-called “smooth pursuit” eye tracking datasets and used Eye Tracking, Inc’s experimental tasks and data to evaluate algorithmic performance. Although the results were quite positive, the partners ultimately decided it did not fit Eye Tracking’s market niche, and Sandia is pursuing opensource alternatives for disseminating the Gaze Appraise algorithms.

McNamara, Laura A.↗

Evaluation methodologies for an advanced information processing system

The system concept and requirements for an Advanced Information Processing System (AIPS) are briefly described, but the emphasis of this paper is on the evaluation methodologies being developed and utilized in the AIPS program. The evaluation tasks include hardware reliability, maintainability and availability, software reliability, performance, and performability. Hardware RMA and software reliability are addressed with Markov modeling techniques. The performance analysis for AIPS is based on queueing theory. Performability is a measure of merit which combines system reliability and performance measures. The probability laws of the performance measures are obtained from the Markov reliability models. Scalar functions of this law such as the mean and variance provide measures of merit in the AIPS performability evaluations.

Schabowsky, R. S., Jr.↗

Computational unsteady aerodynamics for aeroelastic analysis

This report summarizes the status of computational unsteady aerodynamics methods for aeroelastic analysis and makes recommendations for future research activities. The flight conditions for which various types of flows exist are described and the aeroelastic phenomena that can occur in those flight regimes are discussed. Some important aeroelastic problems of current interest are described, and the aerodynamic methods needed to analyze them are presented. The capabilities and limitations of existing unsteady aerodynamics methods are discussed. Computer resources required to perform aeroelastic analysis of various flight vehicle configurations are presented. Recommendations for future research are made, and schedules for completion of proposed research tasks are presented.

Whitlow, Woodrow, Jr.↗

Synthesis of high performance ceramic fibers by chemical vapor deposition for advanced metallics reinforcing

The chemical vapor deposition (CVD) synthesis of fibers capable of effectively reinforcing intermetallic matrices at elevated temperatures which can be used for potential applications in high temperature composite materials is described. This process was used due to its advantage over other fiber synthesis processes. It is extremely important to produce these fibers with good reproducible and controlled growth rates. However, the complex interplay of mass and energy transfer, blended with the fluid dynamics makes this a formidable task. The design and development of CVD reactor assembly and system to synthesize TiB2, CrB, B4C, and TiC fibers was performed. Residual thermal analysis for estimating stresses arising form thermal expansion mismatch were determined. Various techniques to improve the mechanical properties were also performed. Various techniques for improving the fiber properties were elaborated. The crystal structure and its orientation for TiB2 fiber is discussed. An overall view of the CVD process to develop CrB2, TiB2, and other high performance ceramic fibers is presented.

Revankar, Vithal↗

Atomic Oxygen Task

This report details work performed by the Center for Applied Optics (CAO) at the University of Alabama in Huntsville (UAH) on the contract entitled 'Atomic Oxygen Task' for NASA's Marshall Space Flight Center (contract NAS8-38609, Delivery Order 109, modification number 1). Atomic oxygen effects on exposed materials remain a critical concern in designing spacecraft to withstand exposure in the Low Earth Orbit (LEO) environment. The basic objective of atomic oxygen research in NASA's Materials & Processes (M&P) Laboratory is to provide the solutions to material problems facing present and future space missions. The objective of this work was to provide the necessary research for the design of specialized experimental test configurations and development of techniques for evaluating in-situ space environmental effects, including the effects of atomic oxygen and electromagnetic radiation on candidate materials. Specific tasks were performed to address materials issues concerning accelerated environmental testing as well as specifically addressing materials issues of particular concern for LDEF analysis and Space Station materials selection.

Hadaway, James B.↗

Technology Development for a Stirling Radioisotope Power System

NASA Glenn Research Center and the Department of Energy are developing a Stirling convertor for an advanced radioisotope power system to provide spacecraft on-board electric power for NASA deep space missions. NASA Glenn is addressing key technology issues through the use of two NASA Phase II SBIRs with Stirling Technology Company (STC) of Kennewick, WA. Under the first SBIR, STC demonstrated a synchronous connection of two thermodynamically independent free-piston Stirling convertors and a 40 to 50 fold reduction in vibrations compared to an unbalanced convertor. The second SBIR is for the development of an Adaptive Vibration Reduction System (AVRS) that will essentially eliminate vibrations over the mission lifetime, even in the unlikely event of a failed convertor. This paper presents the status and results for these two SBIR projects and also discusses a new NASA Glenn in-house project to provide supporting technology for the overall Stirling radioisotope power system development. Tasks for this new effort include convertor performance verification, controls development, heater head structural life assessment, magnet characterization and thermal aging tests, FEA analysis for a lightweight alternator concept, and demonstration of convertor operation under launch and orbit transfer load conditions.

Thieme, Lanny G.↗

Representation of the Physiological Factors Contributing to Postflight Changes in Functional Performance Using Motion Analysis Software

Astronauts experience changes in multiple physiological systems due to exposure to the microgravity conditions of space flight. To understand how changes in physiological function influence functional performance, a testing procedure has been developed that evaluates both astronaut postflight functional performance and related physiological changes. Astronauts complete seven functional and physiological tests. The objective of this project is to use motion tracking and digitizing software to visually display the postflight decrement in the functional performance of the astronauts. The motion analysis software will be used to digitize astronaut data videos into stick figure videos to represent the astronauts as they perform the Functional Tasks Tests. This project will benefit NASA by allowing NASA scientists to present data of their neurological studies without revealing the identities of the astronauts.

Parks, Kelsey↗

Regional Assessment for the CO 2 Storage Potential in the Northern Niagaran Pinnacle Reef Trend

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. The report describes the regional analysis of the Northern Niagaran Pinnacle Reef Trend (NNPRT) in Northern Michigan as part of the MRCSP programs Regional Assessment goals. The goal of this task was to perform an initial assessment of the geologic storage capacity and injectivity of the Northern Fairway of Michigan’s Niagaran Reef Trend. This was achieved through three main objectives: 1) development of a reef atlas, 2) understanding the regional trends in geology, and 3) estimating CO 2 and CO 2 -EOR resources. Data collected across multiple subtasks were integrated into a mappable database that could be accessed from many of the leading software. The reef atlas was used to map the reefs and associated characteristics across the entire NNPRT. Several methodologies were explored to estimate the CO 2 and CO 2 -EOR resources across the trend which included three scenarios: 1) storage only using fluid substitution and volumetric estimations, 2) CO 2 -EOR which applied proximity analysis concepts and measured performance metrics from the Core Energy reefs to predict performance at all oil reefs, and 3) enhanced storage scenario which combined CO 2 -EOR with fluid substitution to represent maximized storage after completion of CO 2 -EOR.

01 COAL, LIGNITE, AND PEAT↗

Comparison of seven performance measures in a time-delayed manipulation task

Real-time performance data was collected during a pick-up task carried out with a Rancho master-slave manipulator using a minicomputer-based data taker. In addition to the usual task-time measurements, computer algorithms to integrate the energy consumed and to count and time the number of moves were implemented. In addition to these measures, several derived measures such as the fraction of time moving (MRATIO) and mean time per move (MBAR) were obtained in an off-line analysis. Preliminary results of the time delay experiment indicate that two new measures, MRATIO and MBAR, are almost an order of magnitude more sensitive than task time, the conventional measure, in determining performance changes with transmission delays in the range from 0.0 to 1.0s.

Hill, J. W.↗

A model of human decisionmaking in multiple process monitoring situations

It is proposed that human decisionmaking performance in multiple process monitoring situations can be modeled in terms of the detection of process related events and the allocation of attention among processes once events are felt to have occurred. An elementary pattern recognition technique, discriminant analysis, is used to generate estimates of event occurrence probability. A queueing theory framework is then utilized to incorporate these probabilities as well as other task characteristics into the solution of the attention allocation problem. The performance of the model is compared with that of subjects in two experiments.

Greenstein, J. S.↗

Using Computer Vision for Automated Rooftop Modeling and Shading Analysis

The objective of this project was to develop a web-based application (Aurora Envision) that uses sophisticated image recognition and computer vision techniques to perform the following task: given widely available satellite and aerial imagery, with associated geo-coordinates, and proximous weather files, accurately identify the solar potential of a building’s roof.

14 SOLAR ENERGY↗

Development of an Object-Oriented Turbomachinery Analysis Code within the NPSS Framework

During the preliminary or conceptual design phase of an aircraft engine, the turbomachinery designer has a need to estimate the effects of a large number of design parameters such as flow size, stage count, blade count, radial position, etc. on the weight and efficiency of a turbomachine. Computer codes are invariably used to perform this task however, such codes are often very old, written in outdated languages with arcane input files, and rarely adaptable to new architectures or unconventional layouts. Given the need to perform these kinds of preliminary design trades, a modern 2-D turbomachinery design and analysis code has been written using the Numerical Propulsion System Simulation (NPSS) framework. This paper discusses the development of the governing equations and the structure of the primary objects used in OTAC.

Jones, Scott M.↗

Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids

Traditional analysis of highly distorted micro X‐ray diffraction (μ‐XRD) patterns from hydrothermal fluid environments is a time‐consuming process, often requiring substantial data preprocessing and labeled experimental data. Herein, the potential of deep learning with a multitask learning (MTL) architecture to overcome these limitations is demonstrated. MTL models are trained to identify phase information in μ‐XRD patterns, minimizing the need for labeled experimental data and masking preprocessing steps. Notably, MTL models show superior accuracy compared to binary classification convolutional neural networks. Additionally, introducing a tailored cross‐entropy loss function improves MTL model performance. Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieve close performance to models analyzing preprocessed data, with minimal accuracy differences. This work indicates that advanced deep learning architectures like MTL can automate arduous data handling tasks, streamline the analysis of distorted XRD patterns, and reduce the reliance on labor‐intensive experimental datasets.

97 MATHEMATICS AND COMPUTING↗