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NASA NTRS2014

Microbiology and Crew Medical Events on the International Space Station

The closed environment of the International Space Station (ISS) creates an ideal environment for microbial growth. Previous studies have identified the ubiquitous nature of microorganisms throughout the space station environment. To ensure safety of the crew, microbial monitoring of air and surface within ISS began in December 2000 and continues to be monitored on a quarterly basis. Water monitoring began in 2009 when the potable water dispenser was installed on ISS. However, it is unknown if high microbial counts are associated with inflight medical events. The microbial counts are determined for the air, surface, and water samples collected during flight operations and samples are returned to the Microbiology laboratory at the Johnson Space Center for identification. Instances of microbial counts above the established microbial limit requirements were noted and compared inflight medical events (any non-injury event such as illness, rashes, etc.) that were reported during the same calendar-quarter. Data were analyzed using repeated measures logistic regression for the forty-one US astronauts flew on ISS between 2000 and 2012. In that time frame, instances of microbial counts being above established limits were found for 10 times for air samples, 22 times for surface samples and twice for water. Seventy-eight inflight medical events were reported among the astronauts. A three times greater risk of a medical event was found when microbial samples were found to be high (OR = 3.01; p =.007). Engineering controls, crew training, and strict microbial limits have been established to mitigate the crew medical events and environmental risks. Due to the timing issues of sampling and the samples return to earth, identification of particular microorganisms causing a particular inflight medical event is difficult. Further analyses are underway.

Oubre, Cherie M.↗

NASA NTRS2012

Entry, Descent, and Landing Communications for the 2011 Mars Science Laboratory

The Mars Science Laboratory (MSL), established as the most advanced rover to land on the surface of Mars to date, launched on November 26th, 2011 and arrived to the Martian Gale Crater during the night of August 5th, 2012 (PDT). MSL will investigate whether the landing region was ever suitable to support carbon-based life, and examine rocks, soil, and the atmosphere with a sophisticated suite of tools. This paper addresses the flight system requirement by which the vehicle transmitted indications of the following events using both X-band tones and UHF telemetry to allow identification of probable root causes should a mission anomaly have occurred: Heat-Rejection System (HRS) venting, completion of the cruise stage separation, turn to entry attitude, atmospheric deceleration, bank angle reversal commanded, parachute deployment, heatshield separation, radar ground acquisition, powered descent initiation, rover separation from the descent stage, and rover release. During Entry, Descent, and Landing (EDL), the flight system transmitted a UHF telemetry stream adequate to determine the state of the spacecraft (including the presence of faults) at 8 kbps initiating from cruise stage separation through at least one minute after positive indication of rover release on the surface of Mars. The flight system also transmitted X-band semaphore tones from Entry to Landing plus one minute although since MSL was occulted, as predicted, by Mars as seen from the Earth, Direct-To-Earth (DTE) communications were interrupted at approximately is approx. 5 min after Entry ( approximately 130 prior to Landing). The primary data return paths were through the Deep Space Network (DSN) for DTE and the existing Mars network of orbiting assets for UHF, which included the Mars Reconnaissance Orbiter (MRO), Mars Odyssey (ODY), and Mars Express (MEX) elements. These orbiters recorded the telemetry data stream and returned it back to Earth via the DSN. The paper also discusses the total power received during EDL and the robustness of the telecom design strategy used to ensure EDL communications coverage.

relay operations↗

NASA NTRSDate not supplied

Features for a Modern Strain-Gage Balance Data Analysis Software Tool

Required, recommended, and optional features are discussed that benefit preparation and evaluation of the load prediction equations in a strain-gage balance data analysis tool. First, milestones in the evolution of load prediction methods are reviewed so that suggested features can be put into a historical context. Afterwards, independent and dependent variable choices for the balance data analysis are discussed. Then, it is illustrated how three different metrics may be used for the identification of the root cause of an unwanted divergence of the load iterations that may be observed during an iterative load prediction. Finally, a list of features is provided to guide software development efforts.

wind tunnel test↗

DOE OSTI2023

Development of Analysis Methods that Integrate Numeric and Textual Equipment Reliability Data

Within the Light Water Reactor Sustainability (LWRS) program, the Risk-Informed Systems Analysis (RISA) Pathway is performing collaborative research on the development and deployment of technologies designed to assist operating nuclear power plants (NPPs) to reduce operating costs improve plant reliability and availability. One of the RISA research areas is focusing on the development of methods and tools designed to optimize plant operations (e.g., maintenance/replacement schedules, optimal maintenance postures for plant structures, systems, and components [SSCs]) in a manner that is more cost effective than current approaches and makes better use of available SSC health data. The Risk-Informed Asset Management (RIAM) project targets this research area by creating a direct bridge between component equipment reliability (ER) data and system engineer decision making regarding maintenance activity scheduling and component aging management. In this respect, one challenge that NPP system engineers are facing is that the amount of ER data being continuously generated is not only extremely large in size, but it comes in different forms: textual (e.g., condition or maintenance reports) and numeric (e.g., generated by monitoring systems). All these data elements provide them with valuable insights and information regarding: 1) the discovery of anomalous behaviors or degradation trends, 2) the identification of the possible causes behind such behaviors/trends, and 3) the prediction of their direct consequences. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers/databases), others are conceptual in nature: data elements come in different formats (e.g., numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). The activities performed by the RIAM project during FY23 directly tackles the need to simultaneously integrate the analysis of ER data in all its forms, numeric and textual. Note that such task has never been performed before due to the complexity of the systems under consideration but, most importantly, because of the technical challenges behind the harmonization of ER data formats and the lack of adequate computational methods to analyze them. Our approach borrows ideas and concepts from the medical field where integration of several data sources is vital to assist medical practitioners to perform correct diagnosis and indicate optimal treatments. In our view a NPP asset is equivalent to a patient in a medical context. The main difference is the complexity of a human body is a magnitude more complex when compared to typical assets commonly present in NPPs (e.g., centrifugal pumps, or motor operated valves). This simplifies our first requirement when analyzing heterogenous ER data formats: to put data into “context”. Context is here intended as the additional piece of information that is needed by ER data analysis tools to understand what these data elements are referring to, i.e., which king of knowledge they are generating. In our context, this knowledge can be translated into models that capture the form and functional architecture of assets/systems, their dependencies, and how they interact. These models actually emulate the knowledge that that NPP system engineers possess about assets and systems; this is their key of success when analyzing ER data, their challenge is ability to handle large amount of data. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional, i.e. cause-effect, relations. Then, ER data elements are processed by identifying first of all which elements of the developed MBSE elements they are referring to. For numeric ER data this task is fairly easy since it is possible to precisely pinpoint what MBSE elements the corresponding sensor are observing (e.g., bearing temperature of a centrifugal pump). Task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process as “knowledge extraction”. Once again, we borrow the experience in the medical field where methods to extract knowledge from textual data have been developed in the past decade. The missing element for us is the availability of a complete dictionary of NPP related concepts (in addition to the MBSE models presented earlier) that can put “text into context”. In FY23, such dictionary has been developed along with all the computational elements required for knowledge extraction. Lastly, once numeric and textual ER data elements have been processed and “understood”, then the last step is the discovery of possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if the

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Model-Based Approaches to Generate Knowledge from Data in a Plant Reliability Context

One challenge that nuclear power plant system engineers are facing is that the amount of equipment reliability (ER) data being continuously generated are extremely large. These data elements come in different forms: textual (e.g., condition reports) and numeric (e.g., generated by monitoring systems) and they provide system engineers with valuable insights and information regarding the discovery of anomalous behaviors or degradation trends, the identification of the possible causes behind such behaviors and trends, and the prediction of their direct consequences. This paper directly targets the generation of knowledge from ER data by putting “data into context”. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional (i.e., cause-effect) relations. ER data elements are processed by identifying first which elements of the developed MBSE elements they are referring to. This task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process “knowledge extraction” where our methods to extract knowledge from textual data. Lastly, once numeric and textual ER data elements have been processed and “understood”, we discover possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if there is a temporal relation among them. The logic and temporal are the two main ingredients to perform “machine reasoning” from ER data.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2017

Advances in Medical Analytics Solutions for Autonomous Medical Operations on Long-Duration Missions

A review will be presented on the progress made under STMDGame Changing Development Program Funding towards the development of a Medical Decision Support System for augmenting crew capabilities during long-duration missions, such as Mars Transit. To create an MDSS, initial work requires acquiring images and developing models that analyze and assess the features in such medical biosensor images that support medical assessment of pathologies. For FY17, the project has focused on ultrasound images towards cardiac pathologies: namely, evaluation and assessment of pericardial effusion identification and discrimination from related pneumothorax and even bladder-induced infections that cause inflammation around the heart. This identification is substantially changed due to uncertainty due to conditions of fluid behavior under space-microgravity. This talk will present and discuss the work-to-date in this Project, recognizing conditions under which various machine learning technologies, deep-learning via convolutional neural nets, and statistical learning methods for feature identification and classification can be employed and conditioned to graphical format in preparation for attachment to an inference engine that eventually creates decision support recommendations to remote crew in a triage setting.

Medical Decision Support Systems↗

NASA NTRS2007

Investigation of the NOAA N' S Search and Rescue Antenna Inadvertent Deployment: Type C Mishap

The NOAA N' Search and Rescue Antenna (SRA) inadvertently deployed during a spacecraft rotation on April 14,2007. This rotation was part of a normal operation to configure the spacecraft for additional antenna and the solar array boom deployments. This procedure (red flag written) had been modified to look for a lost metal washer and a thermal blanket button. The modification to the procedure was reviewed and approved by the Lockheed Martin Missiles and Space (LMMS) Material Review Board (MRB) per standard procedures. The flag to the procedure introduced a counter clockwise rotation before the normal clockwise rotation. The antenna was temporally stowed and held in place via lacing cord. The lacing cord broke and allowed the SRA to inadvertently deploy during the clockwise rotation. The SRA broke through a hard stop bracket and damaged an instrument optical sensor radiator panel. The satellite damage appears to be minimal and there were no injuries to personnel. The damage to the Advanced Microwave Sounding Unit (AMSU)-A1 instrument has not been fully assessed. Based on mishap site visits, interviews and data analysis, the Mishap Investigation Team (MIT) identified the underlying causes of the mishap. Event and causal factor tree diagrams were developed, resulting in the identification of the proximate (or direct) cause and root causes of the mishap.

Sabelhaus, Phil↗

NASA NTRS1979

On truncated expansion self-tuning regulation of a large AMCD

The one-dimensional wave equation models out of plane displacement of a flexible ring and with appropriate boundary conditions the solution is one of uncoupled modes. Identification and control of the behavior of these modes by means of a self-tuning regulator requires precise measurements of the ring shape. Aliasing of modes occurs from a finite number of sensors along the ring causing interference in the modal identification. Nonuniform sensors spacing allows for reduced aliasing effects but introduces spreading of the modes and provides inconsistent measurements. The homogeneous wave equation solution for modal time behavior aids in the separation of the aliasing effects, but difficulty arises when the ring is spinning past the sensors and control forces are being applied.

Hamm, A. L.↗

NASA NTRS1985

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Pelletier, R. E.↗

NASA NTRS1972

Interpretation of geographic patterns in simulated orbital television imagery of earth resources

In order to better determine the effects of the television imagery characteristics upon the interpretation of geographic patterns obtainable from orbital television sensors, and in order to better evaluate the influences of alternative sensor system parameters such as changes in orbital altitudes or scan line rates, a team of three professional interpreters independently mapped thematically the selected geographic phenomena that they could detect in orbital television imagery produced on a fourteen inch monitor and recorded photographically for analysis. Three thematic maps were compiled by each interpreter. The maps were: (1) transportation patterns; (2) other land use; and (3) physical regions. The results from the three interpreters are compared, agreements noted, and differences analyzed for cause such as disagreement on identification of phenomenon, visual acuity, differences in interpretation techniques, and differing professional backgrounds.

Latham, J. P.↗

NASA NTRS1985

The Development and Prevention of Channel Segregation During Alloy Solidification

During alloy solidification, interdendritic microsegregation causes density differences between entrapped liquid and bulk liquid which provides a driving force for convection. One of the consequences of this effect is the formation of long, nearly vertical liquid channels, rich in solute, flowing through the solid-liquid mushy zone somewhat as a river and tributary system. In ingot castings where the heat flow is vertically downwards and the solute less dense than the solute the convective flow is antiparallel with the flow caused by contraction on freezing. Identification of the mechanisms involved in these two problems is discussed. It is known that certain types of bulk liquid movements can inhibit channel development and the mechanism by which they do so are examined.

Hellawell, A.↗

NASA NTRS1992

Status of the Olympus experiment at CRC

The status of the Olympus Propagation Experiment of the Communications Research Centre in Ottawa, Canada, is briefly summarized. Path attenuation measurements at multiple frequencies correlated with concurrent dual polarized radar data provide a unique method to investigate propagation effects. An experiment of this type is being implemented by the Communications Research Centre (CRC) on the grounds of the National Research Council of Canada in Ottawa. Beacon receivers monitor signals from the Olympus satellite at 12.5, 19.77, and 29.66 GHz at a path elevation angle of 14.2 deg. Sky noise radiometers operating near the same frequencies and pointed along the same path provide additional propagation information. A colocated dual-polarized 9.6-GHz radar probes the precipitation state on the path, permitting identification of precipitation regimes that cause the observed impairments. The Olympus experiment configuration is displayed pictorially. Information on path propagation phenomena can be deduced by correlating the radar, beacon, and sky noise data. Melting layer effects and propagation losses for higher time percentages are prime interests. Data collected by Diversitel Communications during equipment verification tests are presented.

Rogers, David V.↗

NASA NTRS1996

Spectral Irradiance Calibration in the Infrared. 7. 5-14 microns Spectroscopy of the Asteroids Ceres, Vesta, and Pallas

We describe our efforts to seek "closure" in our infrared absolute calibration scheme by comparing spectra of asteroids, absolutely calibrated through reference stars, with "Standard Thermal Models" and "Thermophysical Models" for these bodies. Our use of continuous 5-14 microns airborne spectra provides complete sampling of the rise to, and peak, of the infrared spectral energy distribution and constrains these models. Such models currently support the absolute calibration of ISO-PHOT at far-infrared wave- lengths (as far as 300 microns), and contribute to that of the Mid-Infrared Spectrometer on the "Infrared Telescope in Space" in the 6-12 microns region. The best match to our observed spectra of Ceres and Vesta is a, standard thermal model using a beaming factor of unity. We also report the presence of three emissivity features in Ceres which may complicate the traditional model extrapolation to the far-infrared from contemporaneous ground-based N-band photometry that is used to support calibration of, for example, ISO-PHOT. While identification of specific materials that cause these features is not made, we discuss families of minerals that may be responsible.

Cohen, Martin↗

NASA NTRS1998

Spectral Irradiance Calibration in the Infrared: 5-14 Micron Spectroscopy of the Asteroids Ceres, Vesta, and Pallas - 8

We describe our efforts to seek "closure" in our infrared absolute calibration scheme by comparing spectra of asteroids, absolutely calibrated through reference stars, with "standard thermal models" and "thermophysical models" for these bodies. Our use of continuous 5-14 microns airborne spectra provides complete sampling of the rise to, and peak, of the infrared spectral energy distribution and constrains these models. Such models currently support the absolute calibration of the Infrared Space Observatory Imaging Photopolarimeter (ISOPHOT) at far-infrared wavelengths (as far as 300 microns) and contribute to that of the Mid-Infrared Spectrometer on the Infrared Telescope in Space in the 6 - 12 microns region. The best match to our observed spectra of Ceres and Vesta is a standard thermal model using a beaming factor of unity. We also report the presence of three emissivity features in Ceres that may complicate the traditional model extrapolation to the far-infrared from contemporaneous ground-based N-band photometry that is used to support calibration of, for example, ISOPHOT. While identification of specific materials that cause these features is not made, we discuss families of minerals that may be responsible.

Cohen, Martin↗

NASA NTRS2005

REIMR: A Process for Utilizing Propulsion-Oriented 'Lessons-Learned' to Mitigate Development Risk

This paper is a summary overview of a study conducted a t the NASA Marshall Space Flight Center (MSFC) during the initial phases of the Space Launch Initiative (SLI) program to evaluate a large number of technical problems associated with the design, development, test, evaluation and operation of several major liquid propellant rocket engine systems (i.e., SSME, Fastrac, J-2, F-1). The results of this study was the identification of the "Fundamental Root Causes" that enabled the technical problems to manifest, and practices that can be implemented to prevent them from recurring in future engine development efforts. This paper will discus the Fundamental Root Causes, cite some examples of how the technical problems arose from them, and provide a discussion of how they can be mitigated or avoided.

Ballard, Richard O.↗

NASA NTRS2006

REIMR - A Process for Utilizing Liquid Rocket Propulsion-Oriented 'Lessons Learned' to Mitigate Development Risk in Nuclear Thermal Propulsion

This paper is a summary overview of a study conducted at the NASA Marshall Space Flight Center (NASA MSFC) during the initial phases of the Space Launch Initiative (SLI) program to evaluate a large number of technical problems associated with the design, development, test, evaluation and operation of several major liquid propellant rocket engine systems (i.e., SSME, Fastrac, J-2, F-1). One of the primary results of this study was the identification of the Fundamental Root Causes that enabled the technical problems to manifest, and practices that can be implemented to prevent them from recurring in future propulsion system development efforts, such as that which is currently envisioned in the field of nuclear thermal propulsion (NTF). This paper will discuss the Fundamental Root Causes, cite some examples of how the technical problems arose from them, and provide a discussion of how they can be mitigated or avoided in the development of an NTP system

Ballard, RIchard O.↗

NASA NTRS2015

Next-Generation Angular Distribution Models for Top-of-Atmosphere Radiative Flux Calculation from CERES Instruments: Validation

Radiative fluxes at the top of the atmosphere (TOA) from the Clouds and the Earth's Radiant Energy System (CERES) instrument are fundamental variables for understanding the Earth's energy balance and how it changes with time. TOA radiative fluxes are derived from the CERES radiance measurements using empirical angular distribution models (ADMs). This paper evaluates the accuracy of CERES TOA fluxes using direct integration and flux consistency tests. Direct integration tests show that the overall bias in regional monthly mean TOA shortwave (SW) flux is less than 0.2Wm(exp -2) and the RMSE is less than 1.1Wm(exp -2). The bias and RMSE are very similar between Terra and Aqua. The bias in regional monthly mean TOA LW fluxes is less than 0.5Wm(exp -2) and the RMSE is less than 0.8Wm(exp -)2 for both Terra and Aqua. The accuracy of the TOA instantaneous flux is assessed by performing tests using fluxes inverted from nadir- and oblique-viewing angles using CERES along-track observations and temporally and spatially matched MODIS observations, and using fluxes inverted from multi-angle MISR observations. The averaged TOA instantaneous SW flux uncertainties from these two tests are about 2.3% (1.9Wm(exp -2) over clear ocean, 1.6% (4.5Wm(exp -2) over clear land, and 2.0% (6.0Wm(exp -) over clear snow/ice; and are about 3.3% (9.0Wm(exp -2), 2.7% (8.4Wm(exp -2), and 3.7% (9.9Wm(exp -2) over ocean, land, and snow/ice under all-sky conditions. The TOA SW flux uncertainties are generally larger for thin broken clouds than for moderate and thick overcast clouds. The TOA instantaneous daytime LW flux uncertainties derived from the CERESMODIS test are 0.5% (1.5Wm(exp -2), 0.8% (2.4Wm(exp -2), and 0.7% (1.3Wm(exp -2) over clear ocean, land, and snow/ice; and are about 1.5% (3.5Wm(exp -2), 1.0% (2.9Wm(exp -2), and 1.1% (2.1Wm(exp -2) over ocean, land, and snow/ice under all-sky conditions. The TOA instantaneous nighttime LW flux uncertainties are about 0.5-1% (<2.0Wm(exp -2) for all surface types. Flux uncertainties caused by errors in scene identification are also assessed by using the collocated CALIPSO, CloudSat, CERES and MODIS data product. Errors in scene identification tend to underestimate TOA SW flux by about 0.6Wm(exp -2) and overestimate TOA daytime (nighttime) LW flux by 0.4 (0.2)Wm(exp -2) when all CERES viewing angles are considered.

Su, W.↗

NASA NTRS1993

Turbulence near thunderstorm tops

For several years, scientists at San Jose State University, NASA-Ames, and the University of Arizona have carried out cooperative research programs to understand the causes and effects of severe turbulence. The primary sources of data for this work are Digital Flight Data Recorder (DFDR) tapes from airliners that have been involved in turbulence incidents. A significant result of the analysis of these data has been the identification and quantification of the turbulence causes. Turbulence signatures include breaking Kelvin-Helmholtz waves, large amplitude mountain lee waves, turbulence in and around thunderstorms, and maneuvering. The requirements that must be met for a turbulence incident to be included in the NASA study are rather straightforward: (1) severe or greater turbulence must have been reported (usually with passenger injuries) and (2) the flight data tapes must be available. Despite these rather general criteria, and the fact that our cases are drawn from a wide geographical area over the U.S. and the Atlantic Ocean, we have found an interesting bias in our sample. Of 12 cases at cruise altitude, four were definitely associated with thunderstorms and two are suspected thunderstorm cases. The others were due to mountain waves, CAT, high level windshear/maneuvering, or to causes not yet determined. Although our sample is small, these numbers have raised several questions, not the least of which are: How pervasive is the problem of aircraft encounters with severe turbulence in or near thunderstorm tops (TNTT)? Given the available visible and radar evidence of thunderstorms, Why do such incidents occur? Can anything be done to allevaite the problem? This paper outlines some very preliminary efforts to answer these questions. In the following sections, physical and statistical characteristics of TNTT are discussed (Section 2), TNTT causes are summarized (Section 3), current recommendations for TNTT avoidance are reviewed (Section 4), and some suggestions to ameliorate the problem are given (Section 5).

Lester, Peter F.↗