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At least 1,081 records · Page 60

Analysis of Surface Charging for a Candidate Solar Sail Mission Using Nascap-2k

The characterization of the electromagnetic interaction for a solar sail in the solar wind environment, and identification of viable charging mitigation strategies, is a critical solar sail mission design task, as spacecraft charging has important implications both for science applications and for sail lifetime. To that end, we have pexformed some preliminary surface charging calculations of a candidate 150 meter class solar sail spacecraft for the 0.5 AU solar polar orbit and a 1.0 AU L1 orbit. We construct a model of the spacecraft with candidate materials having appropriate electrical properties using Object Toolkit and perform the spacecraft charging analysis using Nascap-2k, the NASA/AFRL sponsored spacecraft charging analysis tool. We use mean and extreme solar wind environments appropriate for the 0.5 AU and 1.0 AU missions to establish current collection of solar wind ions and electrons. In addition, we include a geostationary orbit case to demonstrate a bounding example of extreme (negative) charging of a solar sail spacecraft in the geostationary orbit environment. Results from the charging analysis demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as expected. Examples with dielectric materials exposed to the space environment exhibit differential potentials ranging from a few volts to extreme potentials in the kilovolt range. Recommendations for further analyses include calculations of wake effects, surface current densities, and environments effects on conductivities.

Neergaard, Linda F.↗

The analysis of Gemini 7 EEG data by three different computer oriented methods

The problem in assessment of electroencephalograms has been the subject element in visual evaluations of such records as well as the need for extensive training (2 or 3 years) before suitable candidate is capable to perform this task. There have been variety of computer type analyses of EEG during the past ten years or more, and we are still searching for a reliable, inexpensive, online data processing procedure for this task. We are aware our Soviet colleagues are routinely using computer assessment of EEGs, using relatively inexpensive hardware. In our report we endeavor to show how four different assessment procedures (visual assessment, zero crossing technique, smoothing and peak counting technique, and Weibull Statistic) may be utilized, and indicate the advantages and disadvantages peculiar to each. We wish to point out that in the Gemini 7 EEG analog records supplied to the Henry Ford Hospital, Channel II (mid-line central to mid-line occipital electrodes) could not be assessed reliably after approximately 26 hours of flight. Channel I (left central to left occipital electrodes) provided the more assessable EEG up to approximately 54 hours of flight. These channels were compared during the first 26 hours of flight, and no significant difference was found by our various assessment procedures. We, therefore, have limited this report to the findings on the analyses of Channel I during its approximate 54 hours of flight.

Proctor, L. D.↗

A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations

Phase field (PF) simulations are computationally expensive but remain a key analysis tool to understand the complex mechanisms of additive manufacturing (AM) processes. Each PF simulation-aided analysis requires thousands of node hours on leadership-class supercomputers. One of the main goals of these analyses is the study of microstructure evolution during the build process which begins with the onset of nucleation. Nucleation occurs under certain thermomechanical conditions which are not known a priori and many PF simulations are required to identify ranges of input thermo-mechanical parameters that can result in the onset of nucleation. Since many of the simulations do not result in nucleation, an analysis campaign often ends up wasting tremendous amounts of precious computing resources executing nucleation-absent simulations. The goal of this work is to design and train deep learning models to inform a PF simulation about the likelihood of the occurrence of nucleation in a future simulation time-step based on the state summary over a finite number of past time-steps of a running simulation. If the prediction determines that the running simulation is unlikely to reach nucleation in the allotted time, then its execution is stopped immediately ultimately resulting in vast reduction in wasted computations when accrued over all the PF simulations typically performed in a single or multiple analysis campaign(s). The paper presents the performance of a machine learning pipeline that uses a convolutional neural network (CNN) model to learn an embedding which is then used with a self-attention network to build a multi-task deep learning model to predict the likelihood of nucleation. The model also predicts the input parameters used in a simulation. Performance is compared with a baseline pipeline that uses an off-the-shelf LeNet-5 model to learn the initial embedding. Despite their smaller size, performance results indicate significant improvement in accuracy of the proposed models compared to the larger baseline models.

Kannan, Ramakrishnan {ramki}↗

Quantification of morphological change in materials based on image data utilizing machine learning techniques

Computed tomography (CT) resolution has become high enough to monitor morphological changes due to aging in materials in long-term applications. We explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images visually reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect. Both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗

Diurnal rhythms of visual accommodation and blink responses - Implication for flight-deck visual standards

Possible 24-h variations in accommodation responses were investigated. A recently developed servo-controlled optometer and focus stimulator were used to obtain monocular accommodation response data on four college-age subjects. No 24-h rhythm in accommodation was shown. Heart rate and blink rate also were measured and periodicity analysis showed a mean 24-h rhythm for both; however, blink rate periodograms were significant for only two of the four subjects. Thus, with the qualifications that college students were tested instead of pilots and that they performed monocular laboratory tasks instead of binocular flight-deck tasks, it is concluded that 24-h rhythms in accommodation responses need not be considered in setting visual standards for flight-deck tasks.

Murphy, M. R.↗

Analysis and Evaluation of Processes and Equipment in Tasks 2 and 4 of the Low-cost Solar Array Project

The significant economic data for the current production multiblade wafering and inner diameter slicing processes were tabulated and compared to data on the experimental and projected multiblade slurry, STC ID diamond coated blade, multiwire slurry and crystal systems fixed abrasive multiwire slicing methods. Cost calculations were performed for current production processes and for 1982 and 1986 projected wafering techniques.

Goldman, H.↗

Vapor Growth of Alloy-Type Semiconductor Crystals

The present effort is part of a continuing research program directed towards the investigation of basic vapor transport phenomena and of crystal growth properties of electronic materials. The primary purpose of ground-based studies is the development and definition of optimum experimental parameters for flight experiments. The ground-based effort includes the investigation of gravity-driven convection effects on mass transport rates and on crystal morphology for different orientations of the density gradient with respect to the gravity vector, and as a function of pressure and of temperature. In addition to the experimental tasks, theoretical efforts involve the quantitative thermodynamic analysis of the systems under investigation, the computation of fluid dynamic parameters, and the consideration of other possible effects on fluid flow under vertical, stabilizing and microgravity conditions. The specific experiments to be performed in a microgravity environment include the investigation of vapor transport and crystal growth phenomena of the GeSe-Xenon system and of the mass flux and growth of bulk and layer-type crystals of Hg sub (1-x) Cd sub x Te using HgI as a transport agent.

Wiedemeier, H.↗

Spectral analysis of sinus arrhythmia - A measure of mental effort

The validity of the spectral analysis of sinus arrhythmia as a measure of mental effort was investigated using a computer simulation of a hovercraft piloted along a river as the experimental task. Strong correlation was observed between the subjective effort-ratings and the heart-rate variability (HRV) power spectrum between 0.06 and 0.14 Hz. Significant correlations were observed not only between subjects but, more importantly, within subjects as well, indicating that the spectral analysis of HRV is an accurate measure of the amount of effort being invested by a subject. Results also indicate that the intensity of effort invested by subjects cannot be inferred from the objective ratings of task difficulty or from performance.

Vicente, Kim J.↗

Design tool for multiprocessor scheduling and evaluation of iterative dataflow algorithms

A graph-theoretic design process and software tool is defined for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described with a dataflow graph and are intended to be executed repetitively on a set of identical processors. Typical applications include signal processing and control law problems. Graph-search algorithms and analysis techniques are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool applies the design process to a given problem and includes performance optimization through the inclusion of additional precedence constraints among the schedulable tasks.

Jones, Robert L., III↗

Influence of Sensory Dependence on Postural Control

The current project is part of an NSBRI funded project, "Development of Countermeasures to Aid Functional Egress from the Crew Exploration Vehicle Following Long-Duration Spaceflight." The development of this countermeasure is based on the use of imperceptible levels of electrical stimulation to the balance organs of the inner ear to assist and enhance the response of a person s sensorimotor function. These countermeasures could be used to increase an astronaut s re-adaptation rate to Earth s gravity following long-duration space flight. The focus of my project is to evaluate and examine the correlation of sensory preferences for vision and vestibular systems. Disruption of the sensorimotor functions following space flight affects posture, locomotion and spatial orientation tasks in astronauts. The Group Embedded Figures Test (GEFT), the Rod and Frame Test (RFT) and the Computerized Dynamic Posturography Test (CDP) are measurements used to examine subjects visual and vestibular sensory preferences. The analysis of data from these tasks will assist in relating the visual dependence measures recognized in the GEFT and RFT with vestibular dependence measures recognized in the stability measures obtained during CDP. Studying the impact of sensory dependence on the performance in varied tasks will help in the development of targeted countermeasures to help astronauts readapt to gravitational changes after long duration space flight.

Santana, Patricia A.↗

Investigation of Control Inceptor Dynamics and Effect on Human Subject Performance

The control inceptor used in a vehicle simulation is an important part of adequately representing the dynamics of the vehicle. The inceptor characteristics are typically based on a second order spring mass damper system with damping, force gradient, breakout force, and natural frequency parameters. Changing these parameters can have a great effect on pilot control of the vehicle. A quasi transfer of training experiment was performed employing a high fidelity and a low fidelity control inceptor. A disturbance compensatory task was employed which involved a simple horizon line disturbed in roll by a sum of sinusoids presented in an out-the-window display. Vehicle dynamics were modeled as 1/s and 1/s2. The task was to maintain level flight. Twenty subjects were divided between the high and the low fidelity training groups. Each group was trained to a performance asymptote, and then transferred to the high fidelity simulation. RMS tracking error, a PSD analysis, and a workload analysis were performed to quantify the transfer of training effect. Quantitative results of the experiments show that there is no significant difference between the high and low fidelity training groups for 1/s plant dynamics. For 1/s2 plant dynamics there is a greater difference in tracking performance and PSD; and the subjects are less correlated with the input disturbance function

Stanco, Anthony A.↗

Analysis of film cooling in rocket nozzles

This report summarizes the findings on the NASA contract NAG8-212, Task No. 3. The overall project consists of three tasks, all of which have been successfully completed. In addition, some supporting supplemental work, not required by the contract, has been performed and is documented herein. Task 1 involved the modification of the wall functions in the code FDNS (Finite Difference Navier-Stokes) to use a Reynolds Analogy-based method. This task was completed in August, 1992. Task 2 involved the verification of the code against experimentally available data. The data chosen for comparison was from an experiment involving the injection of helium from a wall jet. Results obtained in completing this task also show the sensitivity of the FDNS code to unknown conditions at the injection slot. This task was completed in September, 1992. Task 3 required the computation of the flow of hot exhaust gases through the P&W 40K subscale nozzle. Computations were performed both with and without film coolant injection. This task was completed in July, 1993. The FDNS program tends to overpredict heat fluxes, but, with suitable modeling of backside cooling, may give reasonable wall temperature predictions. For film cooling in the P&W 40K calorimeter subscale nozzle, the average wall temperature is reduced from 1750R to about 1050R by the film cooling. The average wall heat flux is reduced by a factor of 3.

Woodbury, Keith A.↗

URBANopt: An Open-Source Software Development Kit for Community and Urban District Energy Modeling: Preprint

Urban building modeling tools are developing rapidly; these tools use emerging simulation workflows for specific urban environmental design tasks, such as assessing the impacts of energy efficiency technologies at a district scale. However, with the emergence of new environmental design tasks, addressing all possible use cases and tasks is challenging and cannot be covered by a single tool. Urban-scale analysis at this level of complexity often requires linking multiple emerging tools, rather than using a single tool, to adequately evaluate a variety of possible fields in urban environmental design. To achieve this, flexible platforms are needed to support multiple input formats (e.g., geometric and non-geometric building properties), enabling the mapping of such inputs to underlying simulation engines. This paper provides an overview of the open-source URBANopt Software Development Kit (SDK) for modeling high-performance buildings and energy systems at a district scale. URBANopt's flexible SDK is composed of several modules that can be customized to integrate with other tools and generate new workflows to perform urban environmental design tasks, such as capturing interactions between individual buildings, district energy systems, distributed energy resources, and the electric distribution grid. We describe the functionality of the core SDK modules in URBANopt (called Core Gem, GeoJSON Gem, and Scenario Gem) and discuss the flexibility of these modules as a means of integration with a variety of tools. We also document and demonstrate technical details of writing and combining new modules to create customized workflows. Finally, we present a case study that uses the URBANopt SDK to model a hypothetical mixed-use urban project and simulate various scenarios to meet district energy performance goals.

buildings↗

Wabash CarbonSAFE: Detailed Site Characterization Plan, Task 11.0, Technical Report

Wabash CarbonSAFE established that commercial-scale CO 2 storage in the Potosi Dolomite –Maquoketa Group storage complex associated with the Wabash Valley Resources (WVR) plant site near Terre Haute, IN is highly feasible. The CarbonSAFE project team performed this evaluation through extensive data acquisition and analysis including 2D seismic reflection data, wireline logs, well testing, and core/cuttings from the Wabash #1 stratigraphic test well (now plugged and abandoned). This document summarizes work detailed in separate Wabash CarbonSAFE reports and consolidates the geologic characterization, well testing, and storage complex modeling results for the Mt. Simon Sandstone and Potosi Dolomite, two distinct reservoirs characterized at the Wabash CarbonSAFE project site. The report then presents recommendations for the next steps for site characterization, identifies data gaps for future activities, and provides an overall assessment of site potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

This final report has four sections. We first describe the actual scientific results attained by our research team, followed by a description of the high performance computing research enhancing those results and prompted by the scientific tasks being undertaken. Next, we describe our research in data and program visualization motivated by the scientific research and also enabling it. Last, we comment on the indirect effects this research effort has had on our work, in terms of follow up or additional funding, student training, etc.

Schwan, Karsten↗

IMPACTing Medical System Design with a Risk Analysis Tool [“IMPACT” sur la Conception du Système Médical avec un Outil d'Analyse des Risques]

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗

IMPACTing Medical System Design with a Risk Analysis Tool

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗