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NASA NTRSDate not supplied

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

This paper presents a technical approach to improve the confidence in the systems analysis process by integrating Uncertainty Quantification (UQ) techniques within a Model-Based Systems Analysis and Engineering (MBSA&E) framework. The MBSA&E architecture uses system models and multidisciplinary analytical solutions as central artifacts for system design and analysis. The integration of UQ enables engineers to assess and mitigate uncertainties associated with a system model, design parameters, and constraint inputs, leading to more complete design studies and further informed decision-making processes. The proposed approach leverages the strengths of MBSA&E and extends it with a UQ methodology to quantify uncertainties in the input parameters and to trace the uncertainties as they propagate throughout the system model. To demonstrate the effectiveness of an integrated MBSA&E-UQ approach, a case study involving a simplified analysis of a Transonic Truss-Braced Wing (TTBW) concept vehicle is performed. This integration enables a more comprehensive evaluation of system performance and behavior under uncertainty and a more robust approach for system design and analysis. Lastly, the paper addresses the challenges and considerations associated with integrating UQ into an MBSA&E framework.

systems analysis↗

NASA NTRSDate not supplied

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

systems analysis↗

NASA NTRSDate not supplied

A21I-1875: Leveraging TEMPO Formaldehyde Observations to Assess Surface Air Quality

Surface ozone (O3) pollution is detrimental to human health, crop yields, and ecosystem productivity. Ground-based ozone observations are sparse and surface ozone retrievals from space are challenging. The process of producing ozone from the oxidation of volatile organic compounds (VOCs) in the presence of nitrogen oxides (NOx) results in formaldehyde (HCHO), which can be observed from satellite and by surface-based remote sensing. From limited field campaign observations, column formaldehyde has been shown to exhibit a strong relationship with surface ozone and, therefore, could be an useful proxy for detecting unmonitored regions of elevated ozone pollution. The spatiotemporal characteristics of this relationship are explored using ground-based Pandora spectrometers and airborne remote sensing data with surface ozone monitors across the United States during recent field campaigns over major cities (TRACER-AQ and STAQS). We extend our analysis to take advantage of HCHO column observations from recently launched Tropospheric Emissions: Monitoring of Pollution (TEMPO), a geostationary satellite over North America. TEMPO observations show preliminary promise in mapping regions of elevated surface ozone from space using column HCHO. We demonstrate the use of column HCHO in assessing the strength of the surface monitoring network, and in detecting the extent of regional ozone exceedances.

Prajjwal Rawat↗

NASA NTRS2000

Assessment of Low Cycle Fatigue Behavior of Powder Metallurgy Alloy U720

The fatigue lives of modem powder metallurgy disk alloys are influenced by variabilities in alloy microstructure and mechanical properties. These properties can vary as functions of variables the different steps of materials/component processing: powder atomization, consolidation, extrusion, forging, heat treating, and machining. It is important to understand the relationship between the statistical variations in life and these variables, as well as the change in life distribution due to changes in fatigue loading conditions. The objective of this study was to investigate these relationships in a nickel-base disk superalloy, U720, produced using powder metallurgy processing. Multiple strain-controlled fatigue tests were performed at 538 C (1000 F) at limited sets of test conditions. Analyses were performed to: (1) assess variations of microstructure, mechanical properties, and LCF failure initiation sites as functions of disk processing and loading conditions; and (2) compare mean and minimum fatigue life predictions using different approaches for modeling the data from assorted test conditions. Significant variations in life were observed as functions of the disk processing variables evaluated. However, the lives of all specimens could still be combined and modeled together. The failure initiation sites for tests performed at a strain ratio R(sub epsilon) = epsilon(sub min)/epsilon(sub max) of 0 were different from those in tests at a strain ratio of -1. An approach could still be applied to account for the differences in mean and maximum stresses and strains. This allowed the data in tests of various conditions to be combined for more robust statistical estimates of mean and minimum lives.

Gabb, Tomothy P.↗

NASA NTRS2021

Agricultural Breadbaskets Shift Poleward Given Adaptive Farmer Behavior Under Climate Change

Modern food production is spatially concentrated in global “breadbaskets”. A major unresolved question is whether these peak production regions will shift poleward as the climate warms, allowing some recovery of potential climaterelated losses. While agricultural impacts studies to date have focused on currently cultivated land, the Global Gridded Crop Model Intercomparison Project (GGCMI) Phase 2 experiment allows us to assess changes in both yields and the location of peak productivity regions under warming. We examine crop responses under projected end-of-century warming using 7 process-based models simulating 5 major crops (maize, rice, soybeans, and spring and winter wheat) with a variety of adaptation strategies. We find that in no-adaptation cases, when planting date and cultivar choices are held fixed, regions of peak production remain stationary and yield losses can be severe, since growing seasons contract strongly with warming. When adaptations in management practices are allowed (cultivars that retain growing season length under warming and modified planting dates), peak productivity zones shift poleward and yield losses are largely recovered. While most growing-zone shifts are ultimately limited by geography, breadbaskets studied here move poleward over 600 km on average by end of the century under RCP8.5. These results suggest that agricultural impacts assessments can be strongly biased if restricted in spatial area or in the scope of adaptive behavior considered. Accurate evaluation of food security under climate change requires global modeling and careful treatment of adaptation strategies.

adaptation↗

NASA NTRS2017

A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data

The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice.

Koslovsky, Matthew↗

NASA NTRS2024

How the INCOSE Model-Based Capability Matrix Has Steered Model-Based Systems Engineering Transformation at NASA

The National Aeronautics and Space Administration (NASA) is embarking on new, complex, and diverse missions to accomplish its scientific and exploration objectives, and it views digital transformation as a key enabler for those missions. The NASA Model-Based Systems Engineering (MBSE) Lead-ership Team (MLT) is leading the charge in the digital transformation of the systems engineering domain at NASA, and it is using the INCOSE Model-Based Capability Matrix (MBCM) as a roadmap. This paper discusses the modifications and tailoring of the INCOSE MBCM (Hale & Hoheb, 2020) for use at NASA, the process the team has taken on multiple rounds of assessment, findings to date, and work products that have been generated as a result of the assessment. The paper will also discuss findings and potential changes that should be made to the original product.

MBSE↗

NASA NTRS1980

PROCRU: A model for analyzing crew procedures in approach to landing

A model for analyzing crew procedures in approach to landing is developed. The model employs the information processing structure used in the optimal control model and in recent models for monitoring and failure detection. Mechanisms are added to this basic structure to model crew decision making in this multi task environment. Decisions are based on probability assessments and potential mission impact (or gain). Sub models for procedural activities are included. The model distinguishes among external visual, instrument visual, and auditory sources of information. The external visual scene perception models incorporate limitations in obtaining information. The auditory information channel contains a buffer to allow for storage in memory until that information can be processed.

Baron, S.↗

NASA NTRS1979

Position paper on the potential of inadvertent weather modification of the Florida Peninsula resulting from neutralization of space shuttle solid rocket booster exhaust clouds

A concept of injecting compounds into the exhaust cloud was proposed to neutralize the acidic nature of the low-level stabilized ground cloud (SGC) was studied. The potential Inadvertent Weather Modification caused by exhaust cloud characteristics from three hours to seven days after launch was studied. Possible effects of the neutralized SGC in warm and cloud precipitation processes were discussed. Based on a detailed climatology of the Florida Peninsula, the risk for weather modification under a variety of weather situations was assessed.

Bollay, E.↗

NASA NTRS1987

Diet and the role of lipoproteins, lipases, and thyroid hormones in coronary lesion growth

The relationships between the coronary lesion growth and the blood contents of lipoprotein fractions, thyroic hormones, and the lipoprotein lipase activity were investigated in male patients with severe coronary atherosclerosis, who participated in a lipid-lowering dietary intervention program. A quantitative computer-assisted image-processing technique was used to assess the severity of coronary obstructions at the beginning of the program and at its termination two years later. Based on absolute coronary scores, patients were divided into a no-lesion growth group (14 patients) and a progression group (21 paients). At the end of the trial, the very-low-density lipoprotein cholesterol and triglycerides were found to be significantly higher, while the high-density lipoprotein cholesterol and hepatic lipase (HL) were lower in the progression group. Multivariate regression analysis showed HL to be the most important determinant of changes in coronary atherosclerotic lesions.

Barth, Jacques D.↗

NASA NTRS2006

Distributed Computing Framework for Synthetic Radar Application

We are developing an extensible software framework, in response to Air Force and NASA needs for distributed computing facilities for a variety of radar applications. The objective of this work is to develop a Python based software framework, that is the framework elements of the middleware that allows developers to control processing flow on a grid in a distributed computing environment. Framework architectures to date allow developers to connect processing functions together as interchangeable objects, thereby allowing a data flow graph to be devised for a specific problem to be solved. The Pyre framework, developed at the California Institute of Technology (Caltech), and now being used as the basis for next-generation radar processing at JPL, is a Python-based software framework. We have extended the Pyre framework to include new facilities to deploy processing components as services, including components that monitor and assess the state of the distributed network for eventual real-time control of grid resources.

synthetic aperture radar (SAR)↗

NASA NTRS2008

The Integrated Medical Model: Statistical Forecasting of Risks to Crew Health and Mission Success

The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions occurred and decrements the pharmaceuticals and supplies required to diagnose and treat these medical conditions. If supplies are depleted, then the medical condition goes untreated, and crew and mission risk increase. The IMM currently models approximately 30 medical conditions. By the end of FY2008, the IMM will be modeling over 100 medical conditions, approximately 60 of which have been recorded to have occurred during short and long space missions.

Fitts, M. A.↗

NASA NTRSDate not supplied

Datascope to Enable Earth Independent Medical Operations (EIMO)

BACKGROUND: NASA has amassed sixty years of knowledge and experience relevant to maintenance of crew health and performance in low earth orbit. The Apollo Program introduced the importance of ensuring progressively autonomous operational capability. Earth Independent Medical Operations (EIMO) will require a gradual shift in the balance of medical responsibility, management, and authority from terrestrial to space-based assets. Terrestrial assets will continue to be essential for pre-mission screening and planning in addition to maintenance of crew health and performance. However, new capabilities are needed to enable EIMO and the amount of data required to support these systems, and mitigate the impacts of data transmission delays and reduced bandwidth coupled with lack of cloud-like resources and on-board computing capacity that is currently unclear or operationally insufficient. OVERVIEW: The overall goal of EIMO is to develop artificial intelligence (AI)-based solutions to analyze crew health and performance data utilizing a clinical decision support system (CDSS) to provide crew medical officers (CMO) with the equivalent of real-time, on-board medical consults. The EIMO ecosystem is envisioned as a “system of systems” where embedded reference databases and real-time data streams from multiple input vectors continuously and seamlessly assess crew health and performance. EIMO will be designed to make recommendations to the CMO using multi-modal AI-based natural language processing and machine learning methods with interoperability to push/pull data within and between multiple vehicle and habitat architectures. DISCUSSION: Data flows and storage/retrieval capacity are severely constrained during space missions and the challenges will become even greater during exploration missions. Just as each past program from Mercury to the International Space Station (ISS) required rethinking the interaction between ground-based controllers and space-based crew, so too will future missions to the Moon and Mars. While the NASA High-Performance Spaceflight Computing Processor project aims to increase computational capacity by 100 times over current spaceflight computers, the projected deliverable still lags considerably behind what will be needed to enable an AI-driven CDSS. Restrictions in processing speed and data storage capacity, coupled with transmission bottlenecks and delays, necessitate definition and optimization of an integrated data architecture to enable a progressively autonomous medical capability.

Medical operations↗

NASA NTRSDate not supplied

Spaceborne Passive-Microwave Hail Detection: Global Climatologies, Validation, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D. Bang↗

NASA NTRS2018

A Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Create an improved method to calculate reliability of a conceptual launch vehicle system prior to fabrication by using historic data of actual root causes of failures. While failures have unique "proximate causes", there are typically a finite amount of common "root causes". Heretofore launch vehicle reliability evaluation typically hardware-centric statistical analyses, while most root causes of failures are been shown to be human-centric. A method based on human-centric root causes can be used to quantify reliability assessments and focus proposed actions to mitigate problems. Existing methods have been optimistic in their projections of launch vehicle reliability compared to actuals. Hypothesis: reliability of a conceptual launch vehicle can be more accurately evaluated based on a rational, probabilistic approach using past failure assessment teams' findings predicated on human-centric causes."Human Reliability Analysis Methods Selection Guidance for NASA"Chandler F.T., et al., NASA HQ/OSMA study group, July 2006. Outside HRA experts from academia, other federal labs, and the private sector. 50 system reliability methods considered, fourteen selected for further study, four finally selected as best suited for human spaceflight. Probabilistic Risk Analysis (PRA) + Human Reliability Analysis (HRA) enabled incorporating effects and probabilities of human errors. While four down-selected methods deemed appropriate for failure assessment, it did not appear that these methods could be concisely applied to perform major system-wide assessment of probability of failure of a conceptual design without becoming unwieldy."Engineering a Safer World", Detailed, comprehensive study external to NASA Leveson N. G., MIT, 2011.Systems-Theoretic Accident Model and Processes (STAMP). All-encompassing accident model based on systems theory analyzed accidents after they occurred and created approaches to prevent occurrence in developing systems not focused on failure prevention per se, but rather reducing hazards by influencing human behavior through use of constraints, hierarchical control structures, and process models to improve system safetySystem Theoretic Process Analysis (STPA) addresses predictive part of problem (a "hazard analysis"). Includes all causal factors identified in STAMP: "...design errors, software flaws, component interaction accidents, cognitively complex human decision-making errors, and social organizational and management factors contributing to accidents" can guide design process rather than require it to exist before-hand did not appear capable of concise application for system-wide assessment of probability of failure of a conceptual design without becoming unwieldy.

Williams, Craig H.↗

NASA NTRS2008

First Human Testing of the Orion Atmosphere Revitalization Technology

An amine-based carbon dioxide (CO2) and water vapor sorbent in pressure-swing regenerable beds has been developed by Hamilton Sundstrand and baselined for the Orion Atmosphere Revitalization System (ARS). In two previous years at this conference, reports were presented on extensive Johnson Space Center (JSC) testing of the technology in a representative environment with simulated human metabolic loads. The next step in developmental testing at JSC was to replace the simulated humans with real humans; this testing was conducted in the spring of 2008. This first instance of human testing of a new Orion ARS technology included several cases in a sealed Orione-quivalent free volume and three cases using emergency breathing masks connected directly to the ARS loop. Significant test results presented in this paper include comparisons between the standard metabolic rates for CO2 and water vapor production published in Orion requirements documents and real-world rate ranges observed with human test subjects. Also included are qualitative assessments of process flow rate and closed-loop pressure-cycling tolerability while using the emergency masks. Recommendations for modifications to the Orion ARS design and operation, based on the test results, conclude the paper.

Lin, Amy↗

NASA NTRS2009

First Human Testing of the Orion Atmosphere Revitalization Technology

An amine-based carbon dioxide (CO2) and water vapor sorbent in pressure-swing regenerable beds has been developed by Hamilton Sundstrand and baselined for the Orion Atmosphere Revitalization System (ARS). In two previous years at this conference, reports were presented on extensive Johnson Space Center (JSC) testing of the technology in a representative environment with simulated human metabolic loads. The next step in developmental testing at JSC was to replace the simulated humans with real humans; this testing was conducted in the spring of 2008. This first instance of human testing of a new Orion ARS technology included several cases in a sealed Orion-equivalent free volume and three cases using emergency breathing masks connected directly to the ARS loop. Significant test results presented in this paper include comparisons between the standard metabolic rates for CO2 and water vapor production published in Orion requirements documents and real-world rate ranges observed with human test subjects. Also included are qualitative assessments of process flow rate and closed-loop pressure-cycling tolerability while using the emergency masks. Recommendations for modifications to the Orion ARS design and operation, based on the test results, conclude the paper.

Lin, Amy↗

NASA NTRS2010

Profiling Transboundary Aerosols over Taiwan and Assessing Their Radiative Effects

A synergistic process was developed to study the vertical distributions of aerosol optical properties and their effects on solar heating using data retrieved from ground-based radiation measurements and radiative transfer simulations. Continuous MPLNET and AERONET observations were made at a rural site in northern Taiwan from 2005 to 2007. The aerosol vertical extinction profiles retrieved from ground-based lidar measurements were categorized into near-surface, mixed, and two-layer transport types, representing 76% of all cases. Fine-mode (Angstrom exponent, alpha, approx.1.4) and moderate-absorbing aerosols (columnar single-scattering albedo approx.0.93, asymmetry factor approx.0.73 at 440 nm wavelength) dominated in this region. The column-integrated aerosol optical thickness at 500 nm (tau(sub 500nm)) ranges from 0.1 to 0.6 for the near-surface transport type, but can be doubled in the presence of upper-layer aerosol transport. We utilize aerosol radiative efficiency (ARE; the impact on solar radiation per unit change of tau(sub 500nm)) to quantify the radiative effects due to different vertical distributions of aerosols. Our results show that the ARE at the top-of-atmosphere (-23 W/ sq m) is weakly sensitive to aerosol vertical distributions confined in the lower troposphere. On the other hand, values of the ARE at the surface are -44.3, -40.6 and -39.7 W/sq m 38 for near-surface, mixed, and two-layer transport types, respectively. Further analyses show that the impact of aerosols on the vertical profile of solar heating is larger for the near-surface transport type than that of two-layer transport type. The impacts of aerosol on the surface radiation and the solar heating profiles have implications for the stability and convection in the lower troposphere.

Wang, Sheng-Hsiang↗