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At least 1,549 records · Page 86

Introduction to Human Systems Integration (HSI)

This course provides core knowledge of basic HSI principles and resources, describes how to apply HSI to NASA projects, and ensures the HHPC team delivers value by practicing HSI.

Witt, Elton G.↗

Autonomous control

KSC has been developing the Knowledge-Based Autonomous Test Engineer (KATE), which is a tool for performing automated monitoring, diagnosis, and control of electromechanical devices. KATE employs artificial intelligence computing techniques to perform these functions. The KATE system consists of a generic shell and a knowledge base. The KATE shell is the portion of the system which performs the monitoring, diagnosis, and control functions. It is generic in the sense that it is application independent. This means that the monitoring activity, for instance, will be performed with the same algorithms regardless of the particular physical device being used. The knowledge base is the portion of the system which contains specific functional and behavorial information about the physical device KATE is working with. Work is nearing completion on a project at KSC to interface a Texas Instruments Explorer running a LISP version of KATE with a Generic Checkout System (GCS) test-bed to control a physical simulation of a shuttle tanking system (humorously called the Red Wagon because of its color and mobility). The Autonomous Control System (ACS) project supplements and extends the KATE/GCS project by adding three other major activities. The activities include: porting KATE from the Texas Instruments Explorer machine to an Intel 80386-based UNIX workstation in the LISP language; rewriting KATE as necessary to run on the same 80386 workstation but in the Ada language; and investigating software and techniques to translate ANSI Standard Common LISP to Mil Standard Ada. Primary goals of this task are as follows: (1) establish the advantages of using expert systems to provide intelligent autonomous software for Space Station Freedom applications; (2) determine the feasibility of using Ada as the run-time environment for model-based expert systems; (3) provide insight into the advantages and disadvantagesof using LISP or Ada in the run-time environment for expert systems; and (4) compare the performance of the 80386 processor to a symbolic processor as a delivery vehicle for expert systems.

Brown, Barbara↗

Exploring Multiscale Earth System and Human-Earth System Dynamics in the Puget Sound Region

With its mountain-to-coast hydroclimate, strong influence of Pacific Ocean weather systems and climate patterns, and unique land use history with strong rural-to-urban gradients, the Puget Sound region is a natural laboratory for studying a number of complex processes in, and interactions among, different Earth and human systems. A 1-year scoping study was initiated by the Earth and Environmental Systems Modeling program of the Department of Energy’s Office of Science Biological and Environmental Research. It was intended to elucidate and highlight the rich opportunities Puget Sound offers to advance our understanding of and ability to simulate Earth system changes and human-Earth system interactions. A literature review, multi-day community workshop, and external input were used to develop this scoping study report. The report first summarizes scientific understanding and knowledge gaps associated with major regional systems, including atmosphere and climate, the land surface, coastal and marine processes, and human systems, as well as how these systems are changing over time. It then highlights some of the most notable extreme events in the region, including heat waves, atmospheric rivers, droughts, and wildfires. Finally, key research opportunities for Earth and environmental systems modeling in, above, and around Puget Sound are highlighted.

54 ENVIRONMENTAL SCIENCES↗

PSTN-054: Updated estimates of the Rubin system throughput and expected LSST image depth

This document presents updated estimates, as of May 2022, of the Rubin system throughput and compares them to throughput requirements from the LSST Science Requirements Document. In addition, it uses these estimates to forecast LSST's median single-visit and co-added image depths for the current (OpSim v2.0) baseline LSST cadence simulation: (23.8, 24.5, 24.0, 23.4, 22.7, 22.0) and (25.6, 26.9, 26.9, 26.4, 25.6, 24.8) in ugrizy, respectively. In addition, it uses these estimates to forecast LSST’s median single-visit and co-added image depths for the current baseline LSST cadence simulation. Estimated system performance relies on actual measurements of the performance of various system hardware components, and on simulations where measurements are still unavailable. The updated performance estimates meet all the relevant requirements from the LSST Science Requirements Document. As our knowledge of the as-buit system continues to improve, updates to these estimates will continue to be provided.

79 ASTRONOMY AND ASTROPHYSICS↗

Adaptive Control Of Remote Manipulator

Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

Seraji, Homayoun↗

System Analysis Modeling and Intermodal Transportation for Commercial Spent Nuclear Fuel

The United States Department of Energy (DOE) Office of Nuclear Energy is applying knowledge and understanding in the areas of systems level engineering, analysis, and decision making to better inform the waste management pathways for U.S. spent nuclear fuel (SNF). Currently there are 93 operating and 23 shutdown commercial nuclear reactors in the United States. SNF at most of these locations is being stored in spent fuel pools, dry storage, or both [1, 2]. This paper initially goes over the basics of the agent-based simulation tool known as the Next Generation System Analysis Model (NGSAM) that has the capability to model interaction and movements of individual components or groups like casks, railcars etc. The next section covers some of the methods implemented in the Java Transportation Operations Model (JTOM) to facilitate the movement of assemblies, casks, railcars etc. and the various intermodal transfer options. This section also covers the current cask loading and intermodal transfer times implemented in NGSAM. The last section goes over the proposed values for intermodal transportation, and cask transfer/loading operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Enabling Innovation and Collaboration Across Geography and Culture: A Case Study of NASA's Systems Engineering Community of Practice

In 2004, NASA faced major knowledge sharing challenges due to geographically isolated field centers that inhibited personnel from sharing experiences and ideas. Mission failures and new directions for the agency demanded better collaborative tools. In addition, with the push to send astronauts back to the moon and to Mars, NASA recognized that systems engineering would have to improve across the agency. Of the ten field centers, seven had not built a spacecraft in over 30 years, and had lost systems engineering expertise. The Systems Engineering Community of Practice came together to capture the knowledge of its members using the suite of collaborative tools provided by the NASA Engineering Network (NEN.) The NEN provided a secure collaboration space for over 60 practitioners across the agency to assemble and review a NASA systems engineering handbook. Once the handbook was complete, they used the open community area to disseminate it. This case study explores both the technology and the social networking that made the community possible, describes technological approaches that facilitated rapid setup and low maintenance, provides best practices that other organizations could adopt, and discusses the vision for how this community will continue to collaborate across the field centers to benefit the agency as it continues exploring the solar system.

NEN↗

Artificial Intelligence Research Branch future plans

This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems.

Stewart, Helen↗

Droplet Entrainment in Steam Supply System of Water-Cooled Small Modular Reactors: Experiment and Modeling Approaches

Droplet entrainment in steam-flow is a prominent phenomenon that needs adequate safety and risk analysis of postulated transient and accident scenarios—including experimental investigation and representative modeling and simulation (M&S)—for small modular reactor (SMR) system design and demonstration. This study identifies knowledge gaps by evaluating experimental and computational fluid dynamics modeling approaches to support early-stage reactor system design, testing, and model evaluation. Previous studies reported in the literature for steam-flow entrainment primarily focused on gigawatt capacity pressurized water reactor (PWR) systems. However, entrainment phenomena are even more prominent for PWR-type SMRs due to their more compact integrated designs, which need further research and development. To fill the research gaps, this study provides insight by specifying the phenomena of interest by leveraging the lessons learned from past research, adopting advanced M&S techniques and advanced instrumentation and control. The findings and recommendations are applicable for evaluating steam-flow entrainment models and for designing integral effect test and separate effect test facilities for gaining reactor design approvals.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Data exploration systems for databases

Data exploration systems apply machine learning techniques, multivariate statistical methods, information theory, and database theory to databases to identify significant relationships among the data and summarize information. The result of applying data exploration systems should be a better understanding of the structure of the data and a perspective of the data enabling an analyst to form hypotheses for interpreting the data. This paper argues that data exploration systems need a minimum amount of domain knowledge to guide both the statistical strategy and the interpretation of the resulting patterns discovered by these systems.

Greene, Richard J.↗

Garbage Collection in a Distributed Object-Oriented System

An algorithm is described in this paper for garbage collection in distributed systems with object sharing across processor boundaries. The algorithm allows local garbage collection at each node in the system to proceed independently of local collection at the other nodes. It requires no global synchronization or knowledge of the global state of the system and exhibits the capability of graceful degradation. The concept of a specialized dump node is proposed to facilitate the collection of inaccessible circular structures. An experimental evaluation of the algorithm is also described. The algorithm is compared with a corresponding scheme that requires global synchronization. The results show that the algorithm works well in distributed processing environments even when the locality of object references is low.

Gupta, Aloke↗

Health Monitoring and Prognostics for More Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining flying time/distance (for aircraft). This information is important, particularly in the case of unmanned vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing remaining flying time is also safety-critical, since an aircraft that runs out of battery charge while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem.For electric aircraft, propulsion is based on power generated from batteries. Thus, it is critical to monitor battery state charge and to estimate the ability of the battery to support mission activities as it is being discharged during flight operation. The ability of the vehicle to complete its given mission very much depends on the charge left in the batteries based on its operational route, maneuvering, weather conditions along with aging health of the batteries. Hence, for the purpose this discussion, consider the scenario of an unmanned electric aircraft that has some planned sequence of waypoints to reach throughout its mission. In such a scenario, for this particular aircraft, and within the region it is flown, at most two minutes are required to safely land the aircraft. Thus, it is desired to predict at which point in time the aircraft must begin to head to the runway and land.

Goebel, Kai↗

Applying Cyber-Informed Engineering to Power System Operations

This presentation covers the interaction of the discipline of system operations with the growing body of knowledge around Cyber-Informed Engineering (CIE). First is discussion of a number of fundamental concepts for system operators - organizational division of responsibilities, human and machine cooperation, goals, and priorities. The next section covers the reasons why CIE was developed, what it is, and the key design and operational, and organizational principles of CIE. Finally, some thoughts on how CIE can be applied to power system operations are offered, along with some examples of how an organization can approach applying CIE principles in their particular circumstances.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The environmental control and life support system advanced automation project. Phase 1: Application evaluation

The Environmental Control and Life Support System (ECLSS) is a Freedom Station distributed system with inherent applicability to advanced automation primarily due to the comparatively large reaction times of its subsystem processes. This allows longer contemplation times in which to form a more intelligent control strategy and to detect or prevent faults. The objective of the ECLSS Advanced Automation Project is to reduce the flight and ground manpower needed to support the initial and evolutionary ECLS system. The approach is to search out and make apparent those processes in the baseline system which are in need of more automatic control and fault detection strategies, to influence the ECLSS design by suggesting software hooks and hardware scars which will allow easy adaptation to advanced algorithms, and to develop complex software prototypes which fit into the ECLSS software architecture and will be shown in an ECLSS hardware testbed to increase the autonomy of the system. Covered here are the preliminary investigation and evaluation process, aimed at searching the ECLSS for candidate functions for automation and providing a software hooks and hardware scars analysis. This analysis shows changes needed in the baselined system for easy accommodation of knowledge-based or other complex implementations which, when integrated in flight or ground sustaining engineering architectures, will produce a more autonomous and fault tolerant Environmental Control and Life Support System.

Dewberry, Brandon S.↗

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Update and Future Direction

NASA’s Small Satellite Reliability Initiative (SSRI), in conjunction with NASA’s Small Spacecraft Systems Virtual Institute (S3VI), has developed the SSRI Knowledge Base to improve mission confidence for small spacecraft. The SSRI Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small satellite missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat community at: NASA SSRI Knowledge Base | Explore. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small satellite missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. All 58 of the planned topic pages that comprise the SSRI Knowledge Base have been recently completed and include over 450 unique resources that are now available for review. Over the past several months significant enhancements to the tool’s capabilities have been developed and implemented. These enhancements consist of the completed baseline content; development of an Application Programming Interface (API); improved user interfaces; scalable and searchable Best Practices and Lessons Learned (BPLL) lists with ratings; and custom website analytics. This presentation and paper will discuss the motivation for and development of the SSRI Knowledge Base, demonstrate the existing tool, and outline plans for further development. The SSRI is a collaborative activity with broad participation from civil, Department of Defense, and both national and international commercial space systems providers and stakeholders. The S3VI is jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate.

Small Spacecraft↗

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Update and Future Direction

NASA’s Small Satellite Reliability Initiative (SSRI), in conjunction with NASA’s Small Spacecraft Systems Virtual Institute (S3VI), has developed the SSRI Knowledge Base to improve mission confidence for small spacecraft. The SSRI Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small satellite missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat community at: NASA SSRI Knowledge Base | Explore. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small satellite missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. All 58 of the planned topic pages that comprise the SSRI Knowledge Base have been recently completed and include over 450 unique resources that are now available for review. Over the past several months significant enhancements to the tool’s capabilities have been developed and implemented. These enhancements consist of the completed baseline content; development of an Application Programming Interface (API); improved user interfaces; scalable and searchable Best Practices and Lessons Learned (BPLL) lists with ratings; and custom website analytics. This presentation and paper will discuss the motivation for and development of the SSRI Knowledge Base, demonstrate the existing tool, and outline plans for further development. The SSRI is a collaborative activity with broad participation from civil, Department of Defense, and both national and international commercial space systems providers and stakeholders. The S3VI is jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate.

Small Spacecraft↗

Autonomous Inversion of In Situ Deformation Measurement Data for Injection-Induced Stress Change

Geologic carbon storage (GCS) is likely to play a key part of the global effort to dramatically reduce CO2 emissions and perhaps even reduce atmospheric CO2 concentrations through carbon negative operations. A critical part of effort to commercialize and widely deploy this technology is developing the capability to rapidly assimilate real-time monitoring data into a form that will enable site operators to make decisions to manage the safe and efficient operations. Two of the risks associate with GCS are the risk of inducing fractures in the sealing formations that can create leakage pathways and the risk of inducing earthquakes of sufficient magnitude to cause public concern, property damage, or safety risks. To properly manage these risks the site operator needs to know the initial state of stress, the change in stress induced by injection, and the relationship between operational parameters such as injection rate and pressure and the change in stress. Current methods of estimating the change in stress require choosing the type of constitutive model and the model parameters based on core, log, and geophysical data during the characterization phase, with little feedback from operational observations to validate or refine these choices. These characterization methods interrogate the geologic formations using length scales, loading rates or magnitudes that are quite different from those encountered by the actual storage system. It is shown that errors in the assumed constitutive response, even when informed by laboratory tests on core samples, are likely to be common, large, and underestimate the magnitude of stress change caused by injection. Recent advances in borehole-based strain instruments and borehole and surface-based tilt and displacement instruments have now enabled monitoring of the deformation of the storage system throughout its operational lifespan. This data can enable validation and refinement of the knowledge of the geomechanical properties and state of the system, but brings with it a challenge to transform the raw data into actionable knowledge. We demonstrate a method that uses automatic differentiation and a finite-element based geomechanical model perform a gradient-based deterministic inversion of geomechanical monitoring data. This approach allows autonomous integration of the instrument data without the need for time consuming manual interpretation and selection of updated model parameters. Furthermore, only isotropic linear elasticity is considered in this paper, the approach presented is very flexible as to what type of geomechanical constitutive response can be used. The approach is easily adaptable to nonlinear physics-based constitutive models to account for common rock behaviors such as creep and plasticity. The approach also enables training of machine learning-based constitutive models by allowing back propagation of errors through the finite element calculations. This enables strongly enforcing known physics, such as conservation of momentum and continuity, while allowing data-driven models to learn the truly unknown physics such as the constitutive or petrophysical responses.

Burghardt, Jeffrey A.↗

State Estimation of International Space Station Centrifuge Rotor With Incomplete Knowledge of Disturbance Inputs

This thesis develops a state estimation algorithm for the Centrifuge Rotor (CR) system where only relative measurements are available with limited knowledge of both rotor imbalance disturbances and International Space Station (ISS) thruster disturbances. A Kalman filter is applied to a plant model augmented with sinusoidal disturbance states used to model both the effect of the rotor imbalance and the 155 thrusters on the CR relative motion measurement. The sinusoidal disturbance states compensate for the lack of the availability of plant inputs for use in the Kalman filter. Testing confirms that complete disturbance modeling is necessary to ensure reliable estimation. Further testing goes on to show that increased estimator operational bandwidth can be achieved through the expansion of the disturbance model within the filter dynamics. In addition, Monte Carlo analysis shows the varying levels of robustness against defined plant/filter uncertainty variations.

SINUSOIDAL DISTURBANCE STATES↗