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Risk reduction methodologies and technologies for the Earth Observing System (EOS) Operations Center (EOC)

This paper will discuss proposed Flight Operations methodologies and technologies for the Earth Observing System (EOS) Operations Center (EOC), to reduce risks associated with the operation of complex multi-instrument spacecraft in a multi-spacecraft environment. The EOC goals are to obtain 100 percent science data capture and maintain 100 percent spacecraft health, for each EOS spacecraft. Operations risks to the spacecraft and data loss due to operator command error, mission degradation due to mis-identification of an anomalous trend in component performance or mis-management of resources, and total mission loss due to improper subsystem configuration or mis-identification of an anomalous condition. This paper discusses automation of routine Flight Operations Team (FOT) responsibilities, Expert systems for real-time non-nominal condition decision support, and Telemetry analysis systems for in-depth playback data analysis and trending.

Hudson, Richard K.↗

A modernized approach to meet diversified earth observing system (EOS) AM-1 mission requirements

From a flight dynamics perspective, the EOS AM-1 mission design and maneuver operations present a number of interesting challenges. The mission design itself is relatively complex for a low Earth mission, requiring a frozen, Sun-synchronous, polar orbit with a repeating ground track. Beyond the need to design an orbit that meets these requirements, the recent focus on low-cost, 'lights out' operations has encouraged a shift to more automated ground support. Flight dynamics activities previously performed in special facilities created solely for that purpose and staffed by personnel with years of design experience are now being shifted to the mission operations centers (MOCs) staffed by flight operations team (FOT) operators. These operators' responsibilities include flight dynamics as a small subset of their work; therefore, FOT personnel often do not have the experience to make critical maneuver design decisions. Thus, streamlining the analysis and planning work required for such a complicated orbit design and preparing FOT personnel to take on the routine operation of such a spacecraft both necessitated increasing the automation level of the flight dynamics functionality. The FreeFlyer(TM) software developed by AI Solutions provides a means to achieve both of these goals. The graphic interface enables users to interactively perform analyses that previously required many parametric studies and much data reduction to achieve the same result In addition, the fuzzy logic engine enables the simultaneous evaluation of multiple conflicting constraints, removing the analyst from the loop and allowing the FOT to perform more of the operations without much background in orbit design. Modernized techniques were implemented for EOS AM-1 flight dynamics support in several areas, including launch window determination, orbit maintenance maneuver control strategies, and maneuver design and calibration automation. The benefits of implementing these techniques include increased fuel available for on-orbit maneuvering, a simplified orbit maintenance process to minimize science data downtime, and an automated routine maneuver planning process. This paper provides an examination of the modernized techniques implemented for EOS AM-1 to achieve these benefits.

Newman, Lauri Kraft↗

A Modernized Approach to Meet Diversified Earth Observing System (EOS) AM-1 Mission Requirements

From a flight dynamics perspective, the EOS AM-1 mission design and maneuver operations present a number of interesting challenges. The mission design itself is relatively complex for a low Earth mission, requiring a frozen, Sun-synchronous, polar orbit with a repeating ground track. Beyond the need to design an orbit that meets these requirements, the recent focus on low-cost, "lights out" operations has encouraged a shift to more automated ground support. Flight dynamics activities previously performed in special facilities created solely for that purpose and staffed by personnel with years of design experience are now being shifted to the mission operations centers (MOCs) staffed by flight operations team (FOT) operators. These operators' responsibilities include flight dynamics as a small subset of their work; therefore, FOT personnel often do not have the experience to make critical maneuver design decisions. Thus, streamlining the analysis and planning work required for such a complicated orbit design and preparing FOT personnel to take on the routine operation of such a spacecraft both necessitated increasing the automation level of the flight dynamics functionality. The FreeFlyer(trademark) software developed by AI Solutions provides a means to achieve both of these goals. The graphic interface enables users to interactively perform analyses that previously required many parametric studies and much data reduction to achieve the same result. In addition, the fuzzy logic engine .enables the simultaneous evaluation of multiple conflicting constraints, removing the analyst from the loop and allowing the FOT to perform more of the operations without much background in orbit design. Modernized techniques were implemented for EOS AM-1 flight dynamics support in several areas, including launch window determination, orbit maintenance maneuver control strategies, and maneuver design and calibration automation. The benefits of implementing these techniques include increased fuel available for on-orbit maneuvering, a simplified orbit maintenance process to minimize science data downtime, and an automated routine maneuver planning process. This paper provides an examination of the modernized techniques implemented for EOS AM-1 to achieve these benefits.

Newman, Lauri Kraft↗

Trajectory-Based Performance Assessment for Aviation Weather Information

Based on an analysis of aviation decision-makers' time-related weather information needs, an abstraction of the aviation weather decision task was developed, that involves 4-D intersection testing between aircraft trajectory hypertubes and hazardous weather hypervolumes. The framework builds on the hypothesis that hazardous meteorological fields can be simplified using discrete boundaries of surrogate threat attributes. The abstractions developed in the framework may be useful in studying how to improve the performance of weather forecasts from the trajectory-centric perspective, as well as for developing useful visualization techniques of weather information.

Vigeant-Langlois, Laurence↗

Towards Risk Based Design for NASA's Missions

This paper describes the concept of Risk Based Design in the context of NASA s low volume, high cost missions. The concept of accounting for risk in the design lifecycle has been discussed and proposed under several research topics, including reliability, risk analysis, optimization, uncertainty, decision-based design, and robust design. This work aims to identify and develop methods to enable and automate a means to characterize and optimize risk, and use risk as a tradeable resource to make robust and reliable decisions, in the context of the uncertain and ambiguous stage of early conceptual design. This paper first presents a survey of the related topics explored in the design research community as they relate to risk based design. Then, a summary of the topics from the NASA-led Risk Colloquium is presented, followed by current efforts within NASA to account for risk in early design. Finally, a list of "risk elements", identified for early-phase conceptual design at NASA, is presented. The purpose is to lay the foundation and develop a roadmap for future work and collaborations for research to eliminate and mitigate these risk elements in early phase design.

Tumer, Irem Y.↗

FootFall: A Ground Based Operations Toolset Enabling Walking for the ATHLETE Rover

The ATHLETE (All-Terrain Hex-Limbed Extra-Terrestrial Explorer) vehicle consists of six identical, six degree of freedom limbs. FootFall is a ground tool for ATHLETE intended to provide an operator with integrated situational awareness, terrain reconstruction, stability and safety analysis, motion planning, and decision support capabilities to enable the efficient generation of flight software command sequences for walking. FootFall has been under development at NASA Ames for the last year, and having accomplished the initial integration, it is being used to generate command sequences for single footfalls. In this paper, the architecture of FootFall in its current state will be presented, results from the recent Human Robotic Systems Project?s Integrated Field Test (Moses Lake, Washington, June, 2008) will be discussed, and future plans for extending the capabilities of FootFall to enable ATHLETE to walk across a boulder field in real time will be described.

SunSpiral, Vytas↗

An Altair Overview: Designing a Lunar Lander for 21st Century Human Space Exploration

Altair, the lunar lander element of NASA's Constellation program, was conducted in a different design environment than many other NASA projects of similar scope. Because of this relatively unique approach, there are a number of significant success stories that should be considered during the development of any future lunar landers or human spacecraft. This paper is divided into two separate themes; the first is the approach used during the conceptual design studies, including the systematic analysis cycles and the decision making process associated with each: and the second is a summary of the resulting lessons learned that were compiled after looking back at the lifetime of the Project. Altair was terminated before entering Phase B of its design, and was often criticized for being a very heavy and very large vehicle. While there was specific rationale for all of the decisions that led up to that configuration, future design cycles were specifically planned to re-address the mass challenge. Had the project continued, the deliberate, stepwise design process would have converged on an optimized lander design that balanced mass, risk, cost and capabilities. Some of the specific items that will be addressed in this paper include project development strategy, organizational approach and team dynamics, risk-informed design process, mission architecture constraints, mission key driving requirements, model-based systems engineering process, configuration studies, contingency considerations, subsystem overviews and key trade studies. The paper will conclude with a summary of the lessons identified during the Altair project and make suggestions for application to future studies.

Brown, Kendall K.↗

Feasibility of Using Remotely Sensed Data to Aid in Long-Term Monitoring of Biodiversity

Remote sensing is defined as making observations of an event or phenomena without physically sampling it. Typically this is done with instruments and sensors mounted on anything from poles extended over a cornfield,to airplanes,to satellites orbiting the Earth The sensors have characteristics that allow them to detect and record information regarding the emission and reflectance of electromagnetic energy from a surface or object. That information can then be represented visually on a screen or paper map or used in data analysis to inform decision-making.

Biodiversity↗

SLS Test Stand Site Selection

Test site selection is a critical element of the design, development and production of a new system. With the advent of the new Space Launch System (SLS), the National Aeronautics and Space Administration (NASA) had a number of test site selection decisions that needed to be made early enough in the Program to support the planned Launch Readiness Date (LRD). This case study focuses on decisions that needed to be made in 2011 and 2012 in preparation for the April 2013 DPMC decision about where to execute the Main Propulsion Test that is commonly referred to as "Green Run." Those decisions relied upon cooperative analysis between the Program, the Test Lab and Center Operations. The SLS is a human spaceflight vehicle designed to carry a crew farther into space than humans have previously flown. The vehicle consists of four parts: the crew capsule, the upper stage, the core stage, and the first stage solid rocket boosters. The crew capsule carries the astronauts, while the upper stage, the core stage, and solid rocket boosters provide thrust for the vehicle. In other words, the stages provide the "lift" part of the lift vehicle. In conjunction with the solid rocket boosters, the core stage provides the initial "get-off-the-ground" thrust to the vehicle. The ignition of the four core stage engines and two solid rocket boosters is the first step in the launch portion of the mission. The solid rocket boosters burn out after about 2 minutes of flight, and are then jettisoned. The core stage provides thrust until the vehicle reaches a specific altitude and speed, at which point the core stage is shut off and jettisoned, and the upper stage provides vehicle thrust for subsequent mission trajectories. The integrated core stage primarily consists of a liquid oxygen tank, a liquid hydrogen tank, and the four core stage engines. For the SLS program, four RS-25 engines were selected as the four core stage engines. The RS-25 engine is the same engine that was used for Space Shuttle. The test plan for the integrated core stage was broken down into several segments: Component testing, system level testing, and element level testing. In this context, components are items such as valves, controllers, sensors, etc. Systems are items such as an entire engine, a tank, or the outer stage body. The core stage itself is considered to be an element. The rocket engines are also considered an element. At the program level, it was decided to perform a single green run test on the integrated core stage prior to shipment of it to Kennedy Space Center (KSC) for use in the EM-1 test flight of the SLS vehicle. A green run test is the first live fire of the new integrated core stage and engine elements - without boosters of course. The SLS Program had to decide where to perform SLS green run testing.

Crowe, Kathryn↗

Data Mining and Knowledge Discover - IBM Cognitive Alternatives for NASA KSC

Skillful tools in cognitive computing to transform industries have been found favorable and profitable for different Directorates at NASA KSC. In this study is shown how cognitive computing systems can be useful for NASA when computers are trained in the same way as humans are to gain knowledge over time. Increasing knowledge through senses, learning and a summation of events is how the applications created by the firm IBM empower the artificial intelligence in a cognitive computing system. NASA has explored and applied for the last decades the artificial intelligence approach specifically with cognitive computing in few projects adopting similar models proposed by IBM Watson. However, the usage of semantic technologies by the dedicated business unit developed by IBM leads these cognitive computing applications to outperform the functionality of the inner tools and present outstanding analysis to facilitate the decision making for managers and leads in a management information system.

Cognitive computing↗

Uncertainty Quantification for JPL Retrievals

We define the notions of verification, validation, and uncertainty quantification (VVUQ), and place them in the context of retrievals of Earth science data. Uncertainty quantification (UQ) is the process of characterizing the uncertainty of a measurement system relative to the true, physical quantity it measures. UQ is needed when measurements are used for scientific inference, assimilated into models with other data, and used for decision-making and risk analysis. Many measurements come with measures of standard error and bias, but these uncertainty measures are often inaccurate, due to the operational need to assume crisp values for parameters which are in fact uncertain, as well as the failure of technical assumptions needed by operational error-estimation approaches. UQ provides a way to study which assumptions fail to hold, and a tool to improve the measurement. We describe a particular, broadly-applicable UQ setup that has been successful for JPL retrievals including OCO-2, and provide recommendations for furthering the UQ state of the practice at JPL.

Turmon, Michael↗

Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data

Forest structure and composition regulate a range of ecosystem services, including biodiversity, water and nutrient cycling, and wood volume for resource extraction. Forest type is an important metric measured in the US Forest Service Forest Inventory and Analysis (FIA) program, the national forest inventory of the USA. Forest type information can be used to quantify carbon and other forest resources within specific domains to support ecological analysis and forest management decisions, such as managing for disease and pests. In this study, we developed a methodology that uses a combination of airborne hyperspectral and lidar data to map FIA-defined forest type between sparsely sampled FIA plot data collected in interior Alaska. To determine the best classification algorithm and remote sensing data for this task, five classification algorithms were tested with six different combinations of raw hyperspectral data, hyperspectral vegetation indices, and lidar-derived canopy and topography metrics. Models were trained using forest type information from 632 FIA subplots collected in interior Alaska. Of the thirty model and input combinations tested, the random forest classification algorithm with hyperspectral vegetation indices and lidar-derived topography and canopy height metrics had the highest accuracy (78% overall accuracy). This study supports random forest as a powerful classifier for natural resource data. It also demonstrates the benefits from combining both structural (lidar) and spectral (imagery) data for forest type classification.

random forest↗

Unconservatism of Linear-Elastic Fracture Mechanics (LEFM) Analysis Post Autofrettage

The scope of the NASA Engineering and Safety Center (NESC) Unconservatism of Linear-Elastic Fracture Mechanics (LEFM) Analysis Post Autofrettage assessment was to evaluate the influence of the elastic-plastic autofrettage cycle on elastic cycles post autofrettage and generate data to support damage tolerance life analysis verification approach. The decision to include an elastic-plastic autofrettage cycle is informed by other factors beyond damage tolerance, including manufacturing and fatigue crack initiation. The results of the NESC assessment are contained in this report.

Linear-Elastic Fracture Mechanics↗

Value of Information in Fuel Cycle Decision-making

Transitions between nuclear fuel cycles with uncertain key parameters (e.g., SNF and HLW disposal costs, fast reactor capital costs) have been examined using a decision-making under uncertainty methodology. The methodology explicitly incorporates uncertainties in key parameters into the decision-making process by constructing a stochastic model and embedding uncertainties as bifurcations in the decision-tree. The framework of this methodology allows for interpretation using a real options valuation or game theoretic approach, reviewed in. The work presented here extends the decision-making under uncertainty framework to calculate the value of information, which may be used to inform a game against nature. These games against nature have been applied to resource allocation problems, where scarce resources are allocated to maximize expected payoffs. More broadly, the value of developing alternative technologies may be considered under the same framework, where an investment portfolio for technology deployment may be developed. Here, the value of information is taken as the value of reducing uncertainty in key parameters, and these values may be substituted for the traditional payoff matrix when considering allocating scarce resources. Games against nature may provide a unique perspective on R and D funding decisions when considering transitions between nuclear fuel cycles. By determining the value of reducing uncertainties (of gaining information on probability distributions) scarce resources may be allocated in such a way to maximize their utility. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A GIS-Based Suitability Analysis of a Phytomanagment Strategy for TCE in Groundwater and Soil Niagara Falls Storage Site, New York - 19385

The large number of complexly contaminated sites throughout the nation has propagated the application of phytoremedial techniques in a wide array of environmental remediation strategies. The use and breeding of vegetation for the in-situ treatment of environmental media (soil, groundwater, sediment) contaminated with organic or inorganic contaminants has shown to provide a low-cost alternative to conventional means of remediating contaminated sites (e.g., groundwater extraction, chemical oxidation or reduction, bioremediation, excavation, etc.). One impediment to effective phytoremediation is the selection of proper plant-species, which is complicated due to the many variables that are required for plant-species viability (i.e. range of soil pH, annual precipitation values, depth to groundwater table, etc.). This study employed the use of a Geographic Information Systems (GIS) to first define the spatial extent of contaminated media (soil and groundwater) at a project site and then support an effective means to optimize phytoremediative techniques to manage these impacts prior to final remediation. Spatial analyses and analytical calculations were coupled to determine an optimal plant species and spacing to maximize the effectiveness of a phytomanagement plan. The incorporation of fuzzy membership functions and fuzzy overlay provide an innovative method to help select the optimal plant-species for phytomanagement planning. Fuzzy membership functions were used to represent the plant growth requirements and provided an intuitive method to represent the uncertainty associated with plant-growth requirements. The fuzzy overlay function then employed a raster-based suitability analysis that together provided decision makers with a scientific solution to optimally design a phytomanagement strategy for site-related volatile organic compound (VOC) impacts. The Niagara Falls Storage Site (NFSS) VOC-impacted groundwater is contained in clayey glacial sediments, which commonly are technically impractical to remediate. Prior on-site studies show that native poplar (cottonwood variants) preferentially translocate or phytoextract the VOCs from the site soils and thus provide a proven mechanism to manage the multi-media impacts. Consequently, the Army Corps of Engineers Buffalo District evaluated phytoremediative approaches as a passive tool to manage the VOCs during the project life cycle prior to final remediation. The fuzzy membership functions and fuzzy overlay modeling of candidate species narrowed the selection to an optimal species and subsequent transpiration modeling estimated the plant spacing for the overall phytomanagement plan. The method employed for this study is easy applied to other phytoremediative and phytomanagement actions derived from hazardous waste decision making. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integrating Predictions for Improving Defect Classification Accuracy in NDT-based Assessment of Concrete - 20229

There is an increasing need to create predictive models for defect classification in concrete using the output of non-destructive testing (NDT) techniques. Recent advancement of machine-learning algorithms has offered several techniques for developing classification models for different types of data sets. However, the performance of these algorithms is very uncertain, mainly when applied to small and noisy datasets. For example, when human access is limited (e.g., nuclear facility), robot-based NDT is preferred. But compared to manual tests with humans present on site, the data sets are small, and more noise can exist. Therefore, it is imperative to develop new approaches to ensure a consistently high classification accuracy for inadequate data sets. This study explores the classification performance on NDT dataset using classifiers from different machine-learning algorithms, namely k-Nearest Neighbor (kNN), Decision Tree, Naive Bayes, Logistic Regression, and Support Vector Machine (SVM). The authors further integrated the predictions from these classifiers using proposed methods. The integration strategy combines the output of the classifiers based on two different measures, accuracy, and performance (ACC and PERF), using equations such as sum, average, and square-root-of-sums-of-squares (SRSS). Our results reveal varying classification accuracies across individual classifiers with different misclassifications across the test data set. The integration strategy provided significant improvement in the classification accuracy compared to the individual classifiers. Furthermore, the results indicate minimal variation across the integration methods as compared to the variation across the individual classifiers. To conclude, prediction integration offers a unique approach for combining the output of multiple classifiers to create redundancies with the potential of achieving high classification performance and improved reliability in predictive models for defect detection in concrete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗