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At least 811 records · Page 45

Development of a Space Station Operations Management System

To enhance the productivity of operations aboard the Space Station, a means must be provided to augment, and frequently to supplant, human effort in support of mission operations and management, both on the ground and onboard. The Operations Management System (OMS), under development at the Johnson Space Center, is one such means. OMS comprises the tools and procedures to facilitate automation of station monitoring, control, and mission planning tasks. OMS mechanizes, and hence rationalizes, execution of tasks traditionally performed by mission planners, the mission control center team, onboard System Management software, and the flight crew.

Brandli, A. E.↗

NOUS: A Knowledge Graph Management System

Knowledge graphs represent information as entities and relationships between them. For tasks such as natural language question answering or automated analysis of text, a knowledge graph provides valuable context to establish the specific type of entities being discussed. It allow us to derive better context about newly arriving information and leads to intelligent reasoning capabilities. We address two primary needs: A) Automated construction of knowledge graphs is a technically challenging, expensive process; and B) The ability to synthesize new information by monitoring newly emerging knowledge is a transformational capability that does not exist in state of the art systems.

Source record↗

NOUS: A Knowledge Graph Management System

Knowledge graphs represent information as entities and relationships between them. For tasks such as natural language question answering or automated analysis of text, a knowledge graph provides valuable context to establish the specific type of entities being discussed. It allow us to derive better context about newly arriving information and leads to intelligent reasoning capabilities. We address two primary needs: A) Automated construction of knowledge graphs is a technically challenging, expensive process; and B) The ability to synthesize new information by monitoring newly emerging knowledge is a transformational capability that does not exist in state of the art systems.

Source record↗

Preliminary Concept of Operations for the Spent Fuel Management System+ - 17134

The Nuclear Fuels Storage and Transportation Planning Project (NFST) within the US Department of Energy's Office of Nuclear Energy is tasked with identifying, planning, and conducting activities for developing interim storage and transportation capabilities in support of an integrated waste management system (IWMS). The IWMS is expected to transport Spent Nuclear Fuel (SNF) from a reactor and deliver it to a repository in a suitable container, with the possibility of interim storage. The system will be composed of multiple subsystems including possible interim storage facilities (ISFs), one or more repositories, facilities to package and/or repackage SNF, and transportation. The project team is analyzing options for an IWMS to identify viable options. To support analysis, the project team has developed a concept of operations framework for SNF related components of the potential integrated system and the interdependencies between those components. A goal of this work is to aid system analysts in developing consistent models across the project. The concept of operations framework will be updated periodically as new developments emerge. At a high level, SNF is expected to be transported from reactor sites to a repository. Initially, SNF is unloaded from reactors and placed in spent fuel pools (SFPs) for wet storage at utility sites. To maintain space in SFPs, SNF is placed in containers at reactor sites for storage and/or transportation only after the SNF has cooled enough to satisfy loading limits. Once transportation requirements are met, the SNF may be transported to an ISF, where it is stored until a repository is developed, or it is transported directly to a repository if one is available.While the high level operation of the system is straightforward, analysts must evaluate numerous alternatives, such as the number of ISFs (if any), ISF design, the stage at which SNF repackaging occurs (if needed), repackaging technology, types of containers used, repository design, component sizing, and timing of events. These alternatives arise due to technological, economic, or policy considerations. This paper provides an overview of the potential alternatives identified in the concept of operations framework at a conceptual level. (authors)

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Planning the FUSE Mission Using the SOVA Algorithm

Three documents discuss the Sustainable Objective Valuation and Attainability (SOVA) algorithm and software as used to plan tasks (principally, scientific observations and associated maneuvers) for the Far Ultraviolet Spectroscopic Explorer (FUSE) satellite. SOVA is a means of managing risk in a complex system, based on a concept of computing the expected return value of a candidate ordered set of tasks as a product of pre-assigned task values and assessments of attainability made against qualitatively defined strategic objectives. For the FUSE mission, SOVA autonomously assembles a week-long schedule of target observations and associated maneuvers so as to maximize the expected scientific return value while keeping the satellite stable, managing the angular momentum of spacecraft attitude- control reaction wheels, and striving for other strategic objectives. A six-degree-of-freedom model of the spacecraft is used in simulating the tasks, and the attainability of a task is calculated at each step by use of strategic objectives as defined by use of fuzzy inference systems. SOVA utilizes a variant of a graph-search algorithm known as the A* search algorithm to assemble the tasks into a week-long target schedule, using the expected scientific return value to guide the search.

Lanzi, James↗

Integrating Safety Assessment Methods using the Risk Informed Safety Margins Characterization (RISMC) Approach

Safety is central to the design, licensing, operation, and economics of nuclear power plants (NPPs). As the current light water reactor (LWR) NPPs age beyond 60 years, there are possibilities for increased frequency of systems, structures, and components (SSC) degradations or failures that initiate safety significant events, reduce existing accident mitigation capabilities, or create new failure modes. Plant designers commonly “over-design” portions of NPPs and provide robustness in the form of redundant and diverse engineered safety features to ensure that, even in the case of well-beyond design basis scenarios, public health and safety will be protected with a very high degree of assurance. This form of defense-in-depth is a reasoned response to uncertainties and is often referred to generically as “safety margin.” Historically, specific safety margin provisions have been formulated primarily based on engineering judgment backed by a set of conservative engineering calculations. The ability to better characterize and quantify safety margin is important to improved decision making about LWR design, operation, and plant life extension. A systematic approach to characterization of safety margins and the subsequent margin management options represents a vital input to the licensee and regulatory analysis and decision making that will be involved. In addition, as research and development (R&D) in the LWR Sustainability (LWRS) Program and other collaborative efforts yield new data, sensors, and improved scientific understanding of physical processes that govern the aging and degradation of plant SSCs needs and opportunities to better optimize plant safety and performance will become known. To support decision making related to economics, readability, and safety, the RISMC Pathway provides methods and tools that enable mitigation options known as margins management strategies. The purpose of the RISMC Pathway R&D is to support plant decisions for risk-informed margin management with the aim to improve economics, reliability, and sustain safety of current NPPs. As the lead Department of Energy (DOE) Laboratory for this Pathway, the Idaho National Laboratory (INL) is tasked with developing and deploying methods and tools that support the quantification and management of safety margin and uncertainty.

97 MATHEMATICS AND COMPUTING↗

Risk Management Implementation Tool

Continuous Risk Management (CM) is a software engineering practice with processes, methods, and tools for managing risk in a project. It provides a controlled environment for practical decision making, in order to assess continually what could go wrong, determine which risk are important to deal with, implement strategies to deal with those risk and assure the measure effectiveness of the implemented strategies. Continuous Risk Management provides many training workshops and courses to teach the staff how to implement risk management to their various experiments and projects. The steps of the CRM process are identification, analysis, planning, tracking, and control. These steps and the various methods and tools that go along with them, identification, and dealing with risk is clear-cut. The office that I worked in was the Risk Management Office (RMO). The RMO at NASA works hard to uphold NASA s mission of exploration and advancement of scientific knowledge and technology by defining and reducing program risk. The RMO is one of the divisions that fall under the Safety and Assurance Directorate (SAAD). I worked under Cynthia Calhoun, Flight Software Systems Engineer. My task was to develop a help screen for the Continuous Risk Management Implementation Tool (RMIT). The Risk Management Implementation Tool will be used by many NASA managers to identify, analyze, track, control, and communicate risks in their programs and projects. The RMIT will provide a means for NASA to continuously assess risks. The goals and purposes for this tool is to provide a simple means to manage risks, be used by program and project managers throughout NASA for managing risk, and to take an aggressive approach to advertise and advocate the use of RMIT at each NASA center.

Wright, Shayla L.↗

DCS: A Case Study of Identification of Knowledge and Disposition Gaps Using Principles of Continuous Risk Management

The Human Research Program (HRP) is formulated around the program architecture of Evidence-Risk-Gap-Task-Deliverable. Review of accumulated evidence forms the basis for identification of high priority risks to human health and performance in space exploration. Gaps in knowledge or disposition are identified for each risk, and a portfolio of research tasks is developed to fill them. Deliverables from the tasks inform the evidence base with the ultimate goal of defining the level of risk and reducing it to an acceptable level. A comprehensive framework for gap identification, focus, and metrics has been developed based on principles of continuous risk management and clinical care. Research towards knowledge gaps improves understanding of the likelihood, consequence or timeframe of the risk. Disposition gaps include development of standards or requirements for risk acceptance, development of countermeasures or technology to mitigate the risk, and yearly technology assessment related to watching developments related to the risk. Standard concepts from clinical care: prevention, diagnosis, treatment, monitoring, rehabilitation, and surveillance, can be used to focus gaps dealing with risk mitigation. The research plan for the new HRP Risk of Decompression Sickness (DCS) used the framework to identify one disposition gap related to establishment of a DCS standard for acceptable risk, two knowledge gaps related to DCS phenomenon and mission attributes, and three mitigation gaps focused on prediction, prevention, and new technology watch. These gaps were organized in this manner primarily based on target for closure and ease of organizing interim metrics so that gap status could be quantified. Additional considerations for the knowledge gaps were that one was highly design reference mission specific and the other gap was focused on DCS phenomenon.

Norcross, Jason↗

INTEGRATED WORKFLOW MANAGEMENT FOR PARTICLE ACCELERATOR SIMULATION

Supercomputing systems are used for a wide range of computationally demanding tasks in many fields of science and engineering. They play a key role in numerical simulation, in which mathematical models are computed in order to simulate the behavior of physical systems. Scientists and engineers that use supercomputers for numerical simulation often have their productivity limited by the need to manually organize and manage extremely large amounts of data that are often produced and consumed by the software programs run on these systems. Recognizing these limitations, Kitware Inc. (Clifton Park, NY) and SLAC National Accelerator Laboratory (Menlo Park, CA) are developing an advanced software platform that can reduce the cognitive overhead required by knowledge workers when using supercomputers for numerical simulation. Phase I of the project is complete and includes the development of new capabilities for organizing simulation project files, improvements to the user interface and overall usability, and deployment of a “middle tier” server to sit between user desktop machines and supercomputers to offload much of the data management workload. The project also developed prototype software for executing sequences of numerical simulations, and a prototype for migrating supercomputing software to cloud-based computing systems to provide a potential alternative to supercomputers with different logistical and price-to-performance tradeoffs.

Tourtellott, John↗

Utility functions and resource management in an oversubscribed heterogeneous computing environment

We model an oversubscribed heterogeneous computing system where tasks arrive dynamically and a scheduler maps the tasks to machines for execution. The environment and workloads are based on those being investigated by the Extreme Scale Systems Center at Oak Ridge National Laboratory. Utility functions that are designed based on specifications from the system owner and users are used to create a metric for the performance of resource allocation heuristics. Each task has a time-varying utility (importance) that the enterprise will earn based on when the task successfully completes execution. We design multiple heuristics, which include a technique to drop low utility-earning tasks, to maximize the total utility that can be earned by completing tasks. The heuristics are evaluated using simulation experiments with two levels of oversubscription. The results show the benefit of having fast heuristics that account for the importance of a task and the heterogeneity of the environment when making allocation decisions in an oversubscribed environment. Furthermore, the ability to drop low utility-earning tasks allow the heuristics to tolerate the high oversubscription as well as earn significant utility.

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Human Research Program Human Health Countermeasures Element Sensorimotor Risk Standing Review Panel (SRP) Final Report

The Sensorimotor Risk Standing Review Panel (SRP) met at the NASA Johnson Space Center on October 4-6, 2009 to discuss the areas of future research targeted by the Human Health Countermeasures (HHC) Element of the Human Research Program (HRP). Using evidence-based knowledge as a background for risks, NASA had identified gaps in knowledge to address those risks. Ongoing and proposed tasks were presented to address the gaps. The charge to the Sensorimotor Risk SRP was to review the gaps, evaluate whether the tasks addressed these gaps and to make recommendations to NASA s HRP Science Management Office regarding the SRP's review. The SRP was requested to evaluate the practicality of the proposed efforts in light of the realistic demands placed on the HRP. In short, all tasks presented in the Integrated Research Plan (IRP) should address specific risks related to the challenges faced by the astronauts as a result of prolonged exposure to microgravity. All tasks proposed to fill the gaps in knowledge should provide applied, translational data necessary to address the specific risks. Several presentations were made to the SRP during the site visit and the SRP spent sufficient time to address the panel charge, either as a group or in separate sessions. The SRP made a final debriefing to the HRP Program Scientist. Taking the evidence and the risk as givens, the SRP reached the following conclusions: 1) the panel is very supportive of and endorses the present activities of the Sensorimotor Risk; and the panel is likewise supportive of the gaps and associated tasks in the IRP; 2) overall, the tasks addressed the gaps in the IRP; 3) there were some gaps and tasks that merit further enhancement and some new gaps/tasks that the SRP recommends.

Peterson, Barry↗

Impact of Data Exchange Provided by ATD2 Tools at Charlotte-Douglas International Airport

Data Exchange and Integration is necessary for progress towards an Integrated Arrival, Departure, and Surface (IADS) traffic management capability. In collaboration with the FAA, NASA has introduced new data exchange elements to Charlotte-Douglas International Airport air traffic facilities, including the American Airlines ramp, as part of the Airspace Technology Demonstration 2 (ATD2). This paper describes the new tools that deliver these elements, and the human factors impact of the tools as measured by post-bank surveys. Workload was unaffected by ATD2 tool use, and situational awareness was improved in the Tower and with Ramp controllers in the second round of surveys. Respondents described their tools as more helpful if they included ATD2 tools 1) in the Tower for insuring compliance for aircraft under a Traffic Management Initiative, 2) in the TRACON when actively used for many TRACON tasks, and 3) in the Ramp in the second round of surveys.

and surface traffic management; human factors asse↗

Thermal Management for FPGA Nodes in HPC Systems

The integration of FPGAs into large-scale computing systems is gaining attention. In these systems, real-time data handling for networking, tasks for scientific computing, and machine learning can be executed with customized datapaths on reconfigurable fabric within heterogeneous compute nodes. At the same time, thermal management, particularly battling the cooling cost and guaranteeing the reliability, is a continuing concern. The introduction of new heterogeneous components into HPC nodes only adds further complexities to thermal modeling and management. The thermal behavior of multi-FPGA systems deployed within large compute clusters is less explored. Here, we first show that the thermal behaviors of different FPGAs of the same generation can vary due to their physical locations in a rack and process variation, even though they are running the same tasks. We present a machine learning–based model to capture the thermal behavior of each individual FPGA in the cluster. We then propose two thermal management strategies guided by our thermal model. First, we mitigate thermal variation and hotspots across the cluster by proactive thermal-aware task placement. Under the tested system and benchmarks, we achieve up to 26.4° C and on average 13.3° C system temperature reduction with no performance penalty. Second, we utilize this thermal model to guide HLS parameter tuning at the task design stage to achieve improved thermal response after deployment.

97 MATHEMATICS AND COMPUTING↗

Cockpit management and Specific Behavioral Objectives (SBOs)

One of the primary tools used to accomplish the task of effective training is the specific behavioral objective (SBO). An SBO is simply a statement which specifically identifies a small segment of the final behavior sought, and a little more. The key word is specific. The company pinpoints exactly what it is it wants the pilot to do after completing training, and what it should evaluate from the point of view of both the program and the pilot. It tells the junior crewmember exactly, specifically, what he should monitor and support insofar as the management function is concerned. It gives greater meaning to the term second in command. And finally, it tells the supervisory pilot exactly what he should observe, evaluate, and instruct, insofar as the management function is concerned.

Mudge, R. W.↗

The New International Project on Irradiated Graphite Processing Approaches (GRAPA) - 16559

Developing of strategies and methods for the management of spent nuclear (irradiated) graphite is one of the major task in decommissioning internationally. More than 250.000 Mg of i-graphite have been accumulated worldwide. Having completed in 2014 a comprehensive collaborative research programme on the treatment options for the disposal of i-graphite wastes to meet disposal criteria, the IAEA decided to maintain an active group of international specialists in this area as part of the International Decommissioning Network (IDN). To foster further development in R and D and steps towards industrial applications in i-graphite management this group was requested to propose the terms of reference and work programme for a new IAEA project. The basic concept for this future programme has been formulated by the German Forschungszentrum (Research Centre) Juelich, Institute IEK-6. The initiative has expanded to include representation from UK, USA, France, Italy, Russia, Ukraine and Lithuania. Additional Member States of the IAEA are expected to join the project. The concept presented by the IEK-6 was discussed among the experts and extended on an international meeting at IAEA in Vienna in February 2015. In addition to the development of the terms of reference a number of individual tasks have been identified. The project will combine a comprehensive state-of-the-art study with concerted actions as well as cross-cutting sub-projects. This will include a practical demonstration of the removal, treatment and disposal of highly-irradiated graphite from a decommissioned reactor. Prior to official implementation of this project preparatory work has been started on topic areas where weaknesses in the scientific knowledge or the technology have been identified. The scope of the international project ('Irradiated Graphite Processing Approaches, GRAPA') and its expected development as well as the possible impact of GRAPA on the future international i-graphite research activities will be described in this presentation. The project will be performed jointly by both the IAEA International Decommissioning Network and the new IAEA Pretreatment Network (IMM, under development). (authors)

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Planning and Resource Management in an Intelligent Automated Power Management System

Power system management is a process of guiding a power system towards the objective of continuous supply of electrical power to a set of loads. Spacecraft power system management requires planning and scheduling, since electrical power is a scarce resource in space. The automation of power system management for future spacecraft has been recognized as an important R&D goal. Several automation technologies have emerged including the use of expert systems for automating human problem solving capabilities such as rule based expert system for fault diagnosis and load scheduling. It is questionable whether current generation expert system technology is applicable for power system management in space. The objective of the ADEPTS (ADvanced Electrical Power management Techniques for Space systems) is to study new techniques for power management automation. These techniques involve integrating current expert system technology with that of parallel and distributed computing, as well as a distributed, object-oriented approach to software design. The focus of the current study is the integration of new procedures for automatically planning and scheduling loads with procedures for performing fault diagnosis and control. The objective is the concurrent execution of both sets of tasks on separate transputer processors, thus adding parallelism to the overall management process.

Morris, Robert A.↗

Managed Development Environment Successes for MSFC's VIPA Team

This paper outlines the best practices of the Vehicle Design Team for VIPA. The functions of the VIPA Vehicle Design (VVD) discipline team are to maintain the controlled reference geometry and provide linked, simplified geometry for each of the other discipline analyses. The core of the VVD work, and the approach for VVD s first task of controlling the reference geometry, involves systems engineering, top-down, layout-based CAD modeling within a Product Data Manager (PDM) development environment. The top- down approach allows for simple control of very large, integrated assemblies and greatly enhances the ability to generate trade configurations and reuse data. The second VVD task, model simplification for analysis, is handled within the managed environment through application of the master model concept. In this approach, there is a single controlling, or master, product definition dataset. Connected to this master model are reference datasets with live geometric and expression links. The referenced models can be for drawings, manufacturing, visualization, embedded analysis, or analysis simplification. A discussion of web based interaction, including visualization, between the design and other disciplines is included. Demonstrated examples are cited, including the Space Launch Initiative development cycle, the Saturn V systems integration and verification cycle, an Orbital Space Plane study, and NASA Exploration Office studies of Shuttle derived and clean sheet launch vehicles. The VIPA Team has brought an immense amount of detailed data to bear on program issues. A central piece of that success has been the Managed Development Environment and the VVD Team approach to modeling.

Finckenor, Jeff↗

A characterization of workflow management systems for extreme-scale applications

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compelling case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.

97 MATHEMATICS AND COMPUTING↗