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NASA NTRS2011

NASA Mission Operations Directorate Preparations for the COTS Visiting Vehicles

With the retirement of the Space Shuttle looming, a series of new spacecraft is under development to assist in providing for the growing logistical needs of the International Space Station (ISS). Two of these vehicles are being built under a NASA initiative known as the Commercial Orbital Transportation Services (COTS) program. These visiting vehicles ; Space X s Dragon and Orbital Science Corporation s Cygnus , are to be domestically produced in the United States and designed to add to the capabilities of the Russian Progress and Soyuz workhorses, the European Automated Transfer Vehicle (ATV) and the Japanese H-2 Transfer Vehicle (HTV). Most of what is known about the COTS program has focused on the work of Orbital and SpaceX in designing, building, and testing their respective launch and cargo vehicles. However, there is also a team within the Mission Operations Directorate (MOD) at NASA s Johnson Space Center working with their operational counterparts in these companies to provide operational safety oversight and mission assurance via the development of operational scenarios and products needed for these missions. Ensuring that the operational aspect is addressed for the initial demonstration flights of these vehicles is the topic of this paper. Integrating Dragon and Cygnus into the ISS operational environment has posed a unique challenge to NASA and their partner companies. This is due in part to the short time span of the COTS program, as measured from initial contract award until first launch, as well as other factors that will be explored in the text. Operational scenarios and products developed for each COTS vehicle will be discussed based on the following categories: timelines, on-orbit checkout, ground documentation, crew procedures, software updates and training materials. Also addressed is an outline of the commonalities associated with the operations for each vehicle. It is the intent of the authors to provide their audience with a better understanding of the mission assurance that MOD brings to commercial ventures to the ISS

Shull, Sarah A.↗

NASA NTRS2018

Innovative Development of a Cross-Center Timeline Planning Tool

The Payload Operations Integration Center (POIC) at Marshall Space Flight Center (MSFC) supports planning, coordination and scheduling of science activities for the International Space Station (ISS) in coordination with other NASA centers, international partners, and payload developers. The ability to efficiently plan and re-plan in response to change is critical to the flight planning teams. With the achievement of supporting a fourth crew member aboard the ISS and an increasing amount of payload science activities, came the need for a dynamic, more efficient way of building timeline planning reports that could be readily updated as fast as payload science plans could change. This paper addresses software architecture considerations in the successful cross-center development of an automated planning tool with multiple data sources. It also discusses the practical implementation of a time-boxed, hybrid Agile Software Development (ASD) approach to deliver customer-driven value despite changing requirements with respect to low-Earth orbit operational planning activities. The goal of this paper is to open discussion with members of the international community and trade effective strategies for cross-center architectural and customer-developer driven collaborations, to support increasing utilization of planning and conducting science activities in space.

Pedoto, Ramon W.↗

NASA NTRS2005

A Review of Diagnostic Techniques for ISHM Applications

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Patterson-Hine, Ann↗

NASA NTRS2014

Avionics Architectures for Exploration: Building a Better Approach for (Human) Spaceflight Avionics

The field of Avionics is advancing far more rapidly in terrestrial applications than in space flight applications. Spaceflight Avionics are not keeping pace with expectations set by terrestrial experience, nor are they keeping pace with the need for increasingly complex automation and crew interfaces as we move beyond Low Earth Orbit. NASA must take advantage of the strides being made by both space-related and terrestrial industries to drive our development and sustaining costs down. This paper describes ongoing efforts by the Avionics Architectures for Exploration (AAE) project chartered by NASA's Advanced Exploration Systems (AES) Program to evaluate new avionic architectures and technologies, provide objective comparisons of them, and mature selected technologies for flight and for use by other AES projects. Results from the AAE project's FY13 efforts are discussed, along with the status of FY14 efforts and future plans.

Goforth, Montgomery B.↗

NASA NTRS2017

MIDAS-FAST: Design and Validation of a Model-Based Tool to Predict Operator Performance with Robotic Arm Automation

The Coalition for Aerospace and Science (CAS) is hosting an exhibition on Capitol Hill on June 14, 2017, to highlight the contributions of CAS members to NASAs portfolio of activities. This exhibition represents an opportunity for an HFES members ground breaking work to be displayed and to build on support within Congress for NASAs human research program including in those areas that are of specific interest to the HFE community. The intent of this poster presentation is to demonstrate the positive outcome that comes from funding HFE related research on a project like the one exemplified by MIDAS-FAST.

MIDAS↗

NASA NTRS2019

Seeker Free-Flying Inspector GNC System Overview

Seeker is an ultra-low cost approach to highly automated extravehicular inspection of crewed or uncrewed spacecraft that has been designed and built in-house at the NASA Johnson Space Center (JSC). The first version of Seeker is intended to be an incremental development towards an advanced inspection capability. This effort builds on past free-flying inspector development efforts such as the Autonomous Extravehicular Activity Robotic Camera Sprint (AERCam Sprint) and Mini AERCam. Seeker was funded as an International Space Station (ISS) "X-by" Project, which required delivery of the vehicle approximately one year after authority to proceed and within the budget of $1.8 million. Seeker will fly onboard the NG-11 Cygnus mission in 2019 and will deploy after Cygnus' primary mission is completed. Seeker will perform inspection-like maneuvers within 50 meters of the target vehicle (Cygnus) and then dispose itself. The Seeker Guidance, Navigation, and Control (GNC) system is composed entirely of commercial off-the-shelf (COTS) and space-rated COTS items, an inertial-relative Multiplicative Extended Kalman Filter (MEKF), point-to-point guidance (with various additional modes such as stationkeeping), proportional-integral translational control, phase plane rotational control, and a state machine for automated mission moding with minimal ground input.

Navigation↗

NASA NTRS2016

Unmanned Aerial Systems Traffic Management (UTM): Safely Enabling UAS Operations in Low-Altitude Airspace

Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS flight operations. Given this, and understanding that the FAA faces a mandate to modernize the present air traffic management system through computer automation and significantly reduce the number of air traffic controllers by FY 2020, the FAA maintains that a comprehensive, yet fully automated UAS traffic management (UTM) system for low-altitude airspace is needed. The concept of UTM is to begin by leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today. Building on its legacy of work in air traffic management (ATM), NASA is working with industry to develop prototype technologies for a UAS Traffic Management (UTM) system that would evolve airspace integration procedures for enabling safe, efficient low-altitude flight operations that autonomously manage UAS operating in an approved low-altitude airspace environment. UTM is a cloud-based system that will autonomously manage all traffic at low altitudes to include UASs being operated beyond visual line of sight of an operator. UTM would thus enable safe and efficient flight operations by providing fully integrated traffic management services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning re-routing, separation management, sequencing spacing, and contingency management. UTM removes the need for human operators to continuously monitor aircraft operating in approved areas. NASA envisions concepts for two types of UTM systems. The first would be a small portable system, which could be moved between geographical areas in support of operations such as precision agriculture and public safety. The second would be a Persistent system, which would support low-altitude operations in an approved area by providing continuous automated coverage. Both would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. UTM is creating an airspace management tool that allows the ATM system to accommodate the number of UAS that will operate in the low altitude airspace. The analogy is just because we have a car, whether its autonomous or someone is driving, does not diminish the need for a road or road signs or rules of the road.

traffic management↗

NASA NTRS1990

Inductive knowledge acquisition experience with commercial tools for space shuttle main engine testing

Since 1984, an effort has been underway at Rocketdyne, manufacturer of the Space Shuttle Main Engine (SSME), to automate much of the analysis procedure conducted after engine test firings. Previously published articles at national and international conferences have contained the context of and justification for this effort. Here, progress is reported in building the full system, including the extensions of integrating large databases with the system, known as Scotty. Inductive knowledge acquisition has proven itself to be a key factor in the success of Scotty. The combination of a powerful inductive expert system building tool (ExTran), a relational data base management system (Reliance), and software engineering principles and Computer-Assisted Software Engineering (CASE) tools makes for a practical, useful and state-of-the-art application of an expert system.

Modesitt, Kenneth L.↗

NASA NTRS2017

The Underpinnings of Workload in Unmanned Vehicle Systems

This paper identifies and characterizes factors that contribute to operator workload in unmanned vehicle systems. Our objective is to provide a basis for developing models of workload for use in design and operation of complex human-machine systems. In 1986, Hart developed a foundational conceptual model of workload, which formed the basis for arguably the most widely used workload measurement technique—the NASA Task Load Index. Since that time, however, there have been many advances in models and factor identification as well as workload control measures. Additionally, there is a need to further inventory and describe factors that contribute to human workload in light of technological advances, including automation and autonomy. Thus, we propose a conceptual framework for the workload construct and present a taxonomy of factors that can contribute to operator workload. These factors, referred to as workload drivers, are associated with a variety of system elements including the environment, task, equipment and operator. In addition, we discuss how workload moderators, such as automation and interface design, can be manipulated in order to influence operator workload. We contend that workload drivers, workload moderators, and the interactions among drivers and moderators all need to be accounted for when building complex, human-machine systems.

Hooey, Becky L.↗

NASA NTRS2021

Regional Air Mobility: Leveraging Our National Investments to Energize the American Travel Experience

America is home to over 5,000 airports available for public use, yet only 30 of these airports serve over 70% of all travelers.01 Despite this vast network of airports, the majority are underutilized due to air transportation services that have trended towards consolidation by putting more people into fewer, larger aircraft on well-traveled routes. Also, these bigger jet-propelled aircraft can only take off from and land on longer airstrips. Regional Air Mobility (RAM) will fundamentally change how we travel by bringing the convenience, speed, and safety of air travel to all Americans, regardless of their proximity to a travel hub or urban center. We advocate RAM technology investment as complementary to and an accelerator for Advanced Air Mobility (AAM) and other initiatives that aspire to transform the airspace. Through targeted advanced technology investments, such as aircraft automation, enhanced operational models, more efficient aircraft and propulsion systems, and expanded airport renewable energy generation, many of which are already underway, RAM will increase the safety, accessibility, and affordability of regional travel while building on the extensive and underutilized federal, state, and local investment in our nation’s local airports.

Regional Air Mobility↗

NASA NTRS2018

Understanding Risk Tolerance and Building an Effective Safety Culture

Estimates range from 65-90 percent of catastrophic mishaps are due to human error. NASA's human factors-related mishaps causes are estimated at approximately 75 percent. As much as we'd like to error-proof our work environment, even the most automated and complex technical endeavors require human interaction... and are vulnerable to human frailty. Industry and government are focusing not only on human factors integration into hazardous work environments, but also looking for practical approaches to cultivating a strong Safety Culture that diminishes risk. Industry and government organizations have recognized the value of monitoring leading indicators to identify potential risk vulnerabilities. NASA has adapted this approach to assess risk controls associated with hazardous, critical, and complex facilities. NASA's facility risk assessments integrate commercial loss control, OSHA (Occupational Safety and Health Administration) Process Safety, API (American Petroleum Institute) Performance Indicator Standard, and NASA Operational Readiness Inspection concepts to identify risk control vulnerabilities.

Loyd, David↗

NASA NTRS1996

A Model-based Approach to Reactive Self-Configuring Systems

This paper describes Livingstone, an implemented kernel for a self-reconfiguring autonomous system, that is reactive and uses component-based declarative models. The paper presents a formal characterization of the representation formalism used in Livingstone, and reports on our experience with the implementation in a variety of domains. Livingstone's representation formalism achieves broad coverage of hybrid software/hardware systems by coupling the concurrent transition system models underlying concurrent reactive languages with the discrete qualitative representations developed in model-based reasoning. We achieve a reactive system that performs significant deductions in the sense/response loop by drawing on our past experience at building fast prepositional conflict-based algorithms for model-based diagnosis, and by framing a model-based configuration manager as a prepositional, conflict-based feedback controller that generates focused, optimal responses. Livingstone automates all these tasks using a single model and a single core deductive engine, thus making significant progress towards achieving a central goal of model-based reasoning. Livingstone, together with the HSTS planning and scheduling engine and the RAPS executive, has been selected as the core autonomy architecture for Deep Space One, the first spacecraft for NASA's New Millennium program.

Williams, Brian C.↗

NASA NTRS2013

Combined Cycle Engine Large-Scale Inlet for Mode Transition Experiments: System Identification Rack Hardware Design

The System Identification (SysID) Rack is a real-time hardware-in-the-loop data acquisition (DAQ) and control instrument rack that was designed and built to support inlet testing in the NASA Glenn Research Center 10- by 10-Foot Supersonic Wind Tunnel. This instrument rack is used to support experiments on the Combined-Cycle Engine Large-Scale Inlet for Mode Transition Experiment (CCE‒ LIMX). The CCE‒LIMX is a testbed for an integrated dual flow-path inlet configuration with the two flow paths in an over-and-under arrangement such that the high-speed flow path is located below the lowspeed flow path. The CCE‒LIMX includes multiple actuators that are designed to redirect airflow from one flow path to the other; this action is referred to as "inlet mode transition." Multiple phases of experiments have been planned to support research that investigates inlet mode transition: inlet characterization (Phase-1) and system identification (Phase-2). The SysID Rack hardware design met the following requirements to support Phase-1 and Phase-2 experiments: safely and effectively move multiple actuators individually or synchronously; sample and save effector control and position sensor feedback signals; automate control of actuator positioning based on a mode transition schedule; sample and save pressure sensor signals; and perform DAQ and control processes operating at 2.5 KHz. This document describes the hardware components used to build the SysID Rack including their function, specifications, and system interface. Furthermore, provided in this document are a SysID Rack effectors signal list (signal flow); system identification experiment setup; illustrations indicating a typical SysID Rack experiment; and a SysID Rack performance overview for Phase-1 and Phase-2 experiments. The SysID Rack described in this document was a useful tool to meet the project objectives.

Thomas, Randy↗

NASA NTRS1994

Automating the training development process for mission flight operations

Traditional methods of developing training do not effectively support the changing needs of operational users in a multimission environment. The Automated Training Development System (ATDS) provides advantages over conventional methods in quality, quantity, turnaround, database maintenance, and focus on individualized instruction. The Operations System Training Group at the JPL performed a six-month study to assess the potential of ATDS to automate curriculum development and to generate and maintain course materials. To begin the study, the group acquired readily available hardware and participated in a two-week training session to introduce the process. ATDS is a building activity that combines training's traditional information-gathering with a hierarchical method for interleaving the elements. The program can be described fairly simply. A comprehensive list of candidate tasks determines the content of the database; from that database, selected critical tasks dictate which competencies of skill and knowledge to include in course material for the target audience. The training developer adds pertinent planning information about each task to the database, then ATDS generates a tailored set of instructional material, based on the specific set of selection criteria. Course material consistently leads students to a prescribed level of competency.

Scott, Carol J.↗

NASA NTRS2005

A Testbed Demonstration of an Intelligent Archive in a Knowledge Building System

The last decade's influx of raw data and derived geophysical parameters from several Earth observing satellites to NASA data centers has created a data-rich environment for Earth science research and applications. While advances in hardware and information management have made it possible to archive petabytes of data and distribute terabytes of data daily to a broad community of users, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications in order to realize the full potential of these valuable datasets. In examining what is needed to enable this progress in the data provider environment that exists today and is expected to evolve in the next several years, we arrived at the concept of an Intelligent Archive in context of a Knowledge Building System (IA/KBS). Our prior work and associated papers investigated usage scenarios, required capabilities, system architecture, data volume issues, and supporting technologies. We identified six key capabilities of an IA/KBS: Virtual Product Generation, Significant Event Detection, Automated Data Quality Assessment, Large-Scale Data Mining, Dynamic Feedback Loop, and Data Discovery and Efficient Requesting. Among these capabilities, large-scale data mining is perceived by many in the community to be an area of technical risk. One of the main reasons for this is that standard data mining research and algorithms operate on datasets that are several orders of magnitude smaller than the actual sizes of datasets maintained by realistic earth science data archives. Therefore, we defined a test-bed activity to implement a large-scale data mining algorithm in a pseudo-operational scale environment and to examine any issues involved. The application chosen for applying the data mining algorithm is wildfire prediction over the continental U.S. This paper reports a number of observations based on our experience with this test-bed. While proof-of-concept for data mining scalability and utility has been a major goal for the research reported here, it was not the only one. The other five capabilities of an WKBS named above have been considered as well, and an assessment of the implications of our experience for these other areas will also be presented. The lessons learned through the testbed effort and presented in this paper will benefit technologists, scientists, and system operators as they consider introducing IA/KBS capabilities into production systems.

Ramapriyan, Hampapuram↗

NASA NTRS2023

Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) in Support of Plant-Growth Systems

As the National Aeronautics and Space Association (NASA) begins to pursue long-duration space flights, they will need to be able to provide astronauts with a nutritious and reliable food source. To meet the administration’s goal of traveling to the Moon and Mars, astronauts will need to begin to grow their own food in space. To protect their food source, extensive monitoring will occur to test for the effects of a space flight environment (e.g., radiation) as well as for early pathogen and disease detection. Genomic sequencing allows for both concerns to be tested on a regular basis. However, NASA’s current sequencer is unable to process plant tissues. Therefore, a novel method for plant DNA extraction using microneedle (MN) patches that will be able to feed into NASA’s existing system, but also require minimal human input is proposed. To support this, the design was broken down into four components (1) MN patch fabrication (2) MN patch extraction, (3) automated sampling motion control, and (4) a processing module. The MN patch is fabricated using a custom mold with conically shaped needles. The mold is filled with Polyvinyl alcohol (PVA) solution and placed in a vacuum desiccator. The mold is left in the vacuum overnight until the patch is dry and ready for use. The protocol was tested with varying pressures, drying times, volume amounts, and preparation methods to determine if highquality needles can be produced. A MN is a method of DNA extraction where the patch is applied to a leaf, the needles penetrate the leaf, breaking the rigid plant cell wall to isolate the DNA. A protocol for this method of extraction was tested to ensure the patch could produce the needed yield and purity. The tests varied by the number of patches, number of applications, and plant type. To automate the MN extraction method, motion control will utilize two separate axis tables which move in the x and y directions. The y-axis table will have an end effector that fits a MN patch and will have the ability to apply the patch to the leaf sample. This end effector will also act as a lid for a downstream processing module. The other axis will position the leaf sample and processing container so that the patch can be applied accurately. The Joint Comprehensive Sequencing System (JCSS) module integrates all the components together. The output of this module feeds into the NASA Charged Information-Storage Polymer Preparation System (CHIPPS) for genomic sequencing. The extraction module operates using a series of syringes and tubing to pump the varying reagents needed for the extraction protocol. The results of the study proved that MN patches are a viable method of DNA extraction. While fabrication of high-quality needles was unsuccessful, the protocol was able to be further developed using centrifugation. The integrated design between the motion control and the JCSS enabled the potential for automation with a complete conceptual design and prototype. Future research and development for this study would include (1) further testing for fabrication (2) expanding the range of plant species compatible with the MN patch, and (3) building a working prototype for the integrated system.

Peter Ling↗

NASA NTRS1991

Improved disparity map analysis through the fusion of monocular image segmentations

The focus is to examine how estimates of three dimensional scene structure, as encoded in a scene disparity map, can be improved by the analysis of the original monocular imagery. The utilization of surface illumination information is provided by the segmentation of the monocular image into fine surface patches of nearly homogeneous intensity to remove mismatches generated during stereo matching. These patches are used to guide a statistical analysis of the disparity map based on the assumption that such patches correspond closely with physical surfaces in the scene. Such a technique is quite independent of whether the initial disparity map was generated by automated area-based or feature-based stereo matching. Stereo analysis results are presented on a complex urban scene containing various man-made and natural features. This scene contains a variety of problems including low building height with respect to the stereo baseline, buildings and roads in complex terrain, and highly textured buildings and terrain. The improvements are demonstrated due to monocular fusion with a set of different region-based image segmentations. The generality of this approach to stereo analysis and its utility in the development of general three dimensional scene interpretation systems are also discussed.

Perlant, Frederic P.↗

NASA NTRS2012

Automated Lab-on-a-Chip Electrophoresis System

Capillary electrophoresis is an analytical technique that can be used to detect and quantify extremely small amounts of various biological molecules. In the search for biochemical traces of life on other planets, part of this search involves an examination of amino acids, which are the building blocks of life on Earth. The most sensitive method for detecting amino acids is the use of laser induced fluorescence. However, since amino acids do not, in general, fluoresce, they first must be reacted with a fluorescent dye label prior to analysis. After this process is completed, the liquid sample then must be transported into the electrophoresis system. If the system is to be reused multiple times, samples must be added and removed each time. In typical laboratories, this process is performed manually by skilled human operators using standard laboratory equipment. This level of human intervention is not possible if this technology is to be implemented on extraterrestrial targets. Microchip capillary electrophoresis (CE) combined with laser induced fluorescence detection (LIF) was selected as an extremely sensitive method to detect amino acids and other compounds that can be tagged with a fluorescent dye. It is highly desirable to package this technology into an integrated, autonomous, in situ instrument capable of performing CE-LIF on the surface of an extraterrestrial body. However, to be fully autonomous, the CE device must be able to perform a large number of sample preparation and analysis operations without the direct intervention of a human.

Willis, Peter A.↗