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At least 181 records · Page 10

A Concept of Operations (ConOps) of an In-time Aviation Safety Management System (IASMS) for Advanced Air Mobility (AAM)

The growth of new emerging operations involving Advanced Air Mobility (AAM) necessitates developing a perspective for an In-time Aviation Safety Management System (IASMS). This perspective advances from the National Academies report on IASMS and its recommendation for developing a Concept of Operations (ConOps) for IASMS. A ConOps has been developed for In-time System-Wide Safety Assurance (ISSA) from which the IASMS ConOps pivots to provide a robust scope commensurate with the broad vision defined by the National Academies. The IASMS ConOps focuses on emerging operations and spans innovations in Unmanned Aircraft System (UAS) and an increasingly complex ecosystem comprised of a widening mix of vehicles and technologies, Urban Air Mobility (UAM) with industry-federated services, traditional operations, as well as new supersonic aircraft and space launch systems.The challenge for the IASMS ConOps is to be broad to encompass innovations in the coming years and decades while agile to ensure levels of safety compatible with operational and certification requirements of the National Airspace System (NAS). The IASMS ConOps interweaves increasing complexity of operational safety capabilities and unlocking UAS Maturity Levels (UMLs). The relationships between increased complexity of automation and automated systems, fewer operators who are not as traditionally higher skilled, more complex operational environments, and aviation operations management with mixed aircraft and equipage pose a multi-dimensional space for IASMS capabilities essential for safety assurance and risk management. Instantiating IASMS capabilities and how they would be integral to AAM operations and increasing maturity of UAM could be accomplished through a series of Safety Demonstrators. These Safety Demonstrators could provide increased understanding and insight into use of controls for risk mitigation, means of compliance for certification, and operational experience with safety services such as in relation to contingency management. The IASMS capabilities can be viewed as initially residing with the vehicle, airspace, and Supplemental Data Service Provider (SDSP). For example, vehicle capabilities include communications including the command and control link, Remote Identification (ID), conflict advisory/alerting, and UAS system monitoring. These capabilities monitor and assess data such as battery health, aircraft state, and human performance. Complexity of ISAMS capabilities depends on a number of factors. These factors are intendedonly as a notional categorization with the purpose being to reflect the complexity of the AAM ecosystem that would drive up the complexity of ISSA capabilities including systems, sensors, models, standards, and controls. Factors could include the Vehicle Flight Management, Environment, Airspace, and Contingency Management. Each of these factors can be comprised of multiple sub-factors that contribute to increasing complexity. For example, Airspace at a lower level of complexity could be dedicated to UTM operations that are unmonitored, and at a higher level of complexity could involve mixed UTM and ATM operations. The IASMS concept includes safety services that provide data and information to different participants in AAM. The roles and responsibilities of participants can be defined using the Responsible-Accountable-Consulted-Informed (RACI) analysis. For example, for the safety service involving the Remote ID, the Operator would be accountable for providing the data, the Vehicle would be responsible for transmitting it, and the USS, SDSP, Vertiports, FIMS (FAA), and Public Entities such as safety services would be informed by receiving the data. The IASMS ConOps identifies the capabilities needed for risk mitigation and safety assurance in the increasingly complex national airspace. The ConOps serves as a pathway for engaging with industry to gain operational experience including through the Safety Demonstrator series, the RACI analysis, and operational complexity factors. The ConOps serves to integrate these different perspectives to build a cohesive and cogent approach to an AAM safety management system.

In-Time Aviation Safety Management System↗

Phase 1 Study for the Phobos L1 Operational Tether Experiment (PHLOTE)

NASA's Innovative Advanced Concepts (NIAC) program selected the PHLOTE mission proposal for a 2017 Phase 1 study. This PHLOTE study provides a credible example of an innovative mission architecture that can be used to enable many future missions throughout the solar system.One of the key Phase 1 deliverables identified in the PHLOTE proposal is this Study Report which is derived from the PHLOTE Concept of Operations (ConOps) Document developed during the study. The PHLOTE ConOps describes the PHLOTE mission and also provides a key systems engineering document to support future mission development.Since this report was produced as part of a NIAC feasibility study, it is intended to be publicly released at the completion of the NIAC study. Significant support was provided through the collaboration of NASA and PHLOTE team members from Space Technology And Research (STAR) Inc. and from the Clouds Architecture Office (Clouds AO). The NASA team was supported by summer and fall interns from five separate universities.

Kempton, Kevin↗

Applications of Doppler radar to aviation operations - JAWS experiences

The field phase of the Joint Airport Weather Studies (JAWS) Project was conducted in the vicinity of Denver's Stapleton International Airport from 15 May to 13 August 1982. The primary collection systems were three Doppler radars, a 27-station, closely spaced (4 km) network of surface stations, and five research aircraft. The program was specifically planned to observe wind shear phenomena with high time and space resolution that would be dangerous to aircraft operations. The program was successful in observing a large number of such events. Preliminary conclusions are presented on the effectiveness of several wind shear detection systems to warn of wind shear events critical to aviation safety.

Mccarthy, J.↗

Learning from Automation Surprises and "Going Sour" Accidents: Progress on Human-Centered Automation

Advances in technology and new levels of automation on commercial jet transports has had many effects. There have been positive effects from both an economic and a safety point of view. The technology changes on the flight deck also have had reverberating effects on many other aspects of the aviation system and different aspects of human performance. Operational experience, research investigations, incidents, and occasionally accidents have shown that new and sometimes surprising problems have arisen as well. What are these problems with cockpit automation, and what should we learn from them? Do they represent over-automation or human error? Or instead perhaps there is a third possibility - they represent coordination breakdowns between operators and the automation? Are the problems just a series of small independent glitches revealed by specific accidents or near misses? Do these glitches represent a few small areas where there are cracks to be patched in what is otherwise a record of outstanding designs and systems? Or do these problems provide us with evidence about deeper factors that we need to address if we are to maintain and improve aviation safety in a changing world? How do the reverberations of technology change on the flight deck provide insight into generic issues about developing human-centered technologies and systems (Winograd and Woods, 1997)? Based on a series of investigations of pilot interaction with cockpit automation (Sarter and Woods, 1992; 1994; 1995; 1997a, 1997 b), supplemented by surveys, operational experience and incident data from other studies (e.g., Degani et al., 1995; Eldredge et al., 1991; Tenney et al., 1995; Wiener, 1989), we too have found that the problems that surround crew interaction with automation are more than a series of individual glitches. These difficulties are symptoms that indicate deeper patterns and phenomena concerning human-machine cooperation and paths towards disaster. In addition, we find the same kinds of patterns behind results from studies of physician interaction with computer-based systems in critical care medicine (e.g., Moll van Charante et al., 1993; Obradovich and Woods, 1996; Cook and Woods, 1996). Many of the results and implications of this kind of research are synthesized and discussed in two comprehensive volumes, Billings (1996) and Woods et al. (1994). This paper summarizes the pattern that has emerged from our research, related research, incident reports, and accident investigations. It uses this new understanding of why problems arise to point to new investment strategies that can help us deal with the perceived "human error" problem, make automation more of a team player, and maintain and improve safety.

Woods, David D.↗

Summary Report of Mission Acceleration Measurements for STS-75, Launched February 22, 1996

Two accelerometers provided acceleration data during the STS-75 mission in support of the third United States Microgravity Payload (USMP-3) experiments. The Orbital Acceleration Research Experiment (OARE) and the Space Acceleration Measurement System (SAMS) provided a measure of the microgravity environment of the Space Shuttle Columbia. The OARE provided investigators with quasi-steady acceleration measurements after about a six hour time lag dictated by downlink constraints. SAMS data were downlinked in near-real-time and recorded on-board for post-mission analysis. An overview of the mission is provided as are brief discussions of these two accelerometer systems. Data analysis techniques used to process SAMS and OARE data are discussed Using a combination of these techniques, the microgravity environment related to several different Orbiter, crew, and experiment operations is presented and interpreted. The microgravity environment represented by SAMS and OARE data is comparable to the environments measured by the instruments on earlier microgravity science missions. The OARE data compared well with predictions of the quasi-steady environment. The SAMS data show the influence of thruster firings and crew motion (transient events) and of crew exercise, Orbiter systems, and experiment operations (oscillatory events). Thruster activity on this mission appears to be somewhat more frequent than on other microgravity missions with the combined firings of the F5L and F5R jets producing significant acceleration transients. The specific crew activities performed in the middeck and flight deck, the SPREE table rotations, the waste collection system compaction, and the fuel cell purge had negligible effects on the microgravity environment of the USMP-3 carriers. The Ku band antenna repositioning activity resulted in a brief interruption of the ubiquitous 17 Hz signal in the SAMS data. In addition, the auxiliary power unit operations during the Flight Control System checkout appeared to have a significant impact on the microgravity environment.

Rogers, Melissa J. B.↗

Recent Shuttle EVA operations and experience

This paper describes the hardware used and the experience gained during the Space Shuttle extravehicular activities (EVAs) or 'spacewalks' of 1984. Seven EVAs on four missions were conducted with objectives including hardware verification, satellite repair, hydrazine transfer, and satellite retrieval. The hardware used on these flights fall into two categories - general EVA hardware (e.g. the Manned Maneuvering Unit) and mission-unique hardware (e.g. apogee kick motor capture device, used to retrieve the WESTAR VI and PALAPA B-2 satellites). The successful completion of the mission objectives resulted in an increased knowledge of EVA operations and a broader base of Space Shuttle capabilities which are applicable to future operations.

Rogers, L. J. A.↗

Application of Objectives-Driven Assurance Cases to System Development in an Evolving Acquisition Model

System properties such as “safety” and “dependability” cannot, in practice, be proven, and must be argued in an “assurance case” aimed at supporting risk-acceptance decisions that have to be made by system acquirers and/or regulatory authorities. The paper is concerned with applications of the “assurance case” idea early in design and development of new systems, when (apart from dedicated testing) the only available operating experience information derives from previous (non-identical) systems. Much of the discussion is based on an evolving acquisition model at the US National Aeronautics and Space Administration; previously, most major systems were developed in-house, but some major systems will now be developed by and acquired from commercial providers. Key points discussed include the following. (1) By promoting a particular kind of focused discussion between acquirers and providers, the use of assurance cases should be particularly valuable under the new acquisition model. (2) In principle, objectives-driven (sometimes called “performance-based”) approaches to assurance of performance have significant advantages in cases where they are applicable. (3) For truly novel systems, completeness of the safety analysis is a significant issue; it is important for the assurance case to include a commitment by the provider (or applicant) to seriously pursue analysis of operating experience, so that previously unrecognized hazards can be identified and addressed. (4) Inquiries into major accidents often point to deficiencies in management oversight in all parts of the life cycle; management processes need to be addressed in the formulation and the implementation of an assurance case. Under the new acquisition model, these considerations imply a serious reconsideration of the way in which the development process is managed by both providers and acquirers.

Objectives-driven↗

Final results of an experiment in operational forecasting of sea breeze thunderstorms using a mesoscale numerical model

Sea breeze thunderstorms during quiescent synoptic conductions account for 40 percent of Florida rainfall, and are the dominant feature of April-October weather at the Kennedy Space Center (KSC). An effort is presently made to assess the feasibility of a mesoscale numerical model in improving the point-specific thunderstorm forecasting accuracy at the KSC, in the 2-12 hour time frame. Attention is given to the Applied Regional Atmospheric Modeling System.

Lyons, Walter A.↗

Physics of Colloids in Space (PCS): Microgravity Experiment Completed Operations on the International Space Station

Immediately after mixing, the two-phase-like colloid-polymer critical point sample begins to phase separate, or de-mix, into two phases-one that resembles a gas and one that resembles a liquid, except that the particles are colloids and not atoms. The colloid-poor black regions (colloidal gas) grow bigger, and the colloid-rich white regions (colloidal liquid) become whiter as the domains further coarsen. Finally, complete phase separation is achieved, that is, just one region of each colloid-rich (white) and colloid-poor (black) phase. This process was studied over four decades of length scale, from 1 micrometer to 1 centimeter.

Doherty, Michael P.↗

SAMS Acceleration Measurements on Mir from June to November 1995

The NASA Microgravity Science and Applications Division (MSAD) sponsors science experiments on a variety of microgravity carriers, including sounding rockets, drop towers, parabolic aircraft, and Orbiter missions. The MSAD sponsors the Space Acceleration Measurement System (SAMS) to support microgravity science experiments with acceleration measurements to characterize the microgravity environment to which the experiments were exposed. The Principal Investigator Microgravity Services project at the NASA Lewis Research Center supports principal investigators of microgravity experiments as they evaluate the effects of varying acceleration levels on their experiments. In 1993, a cooperative effort was started between the United States and Russia involving science utilization of the Russian Mir space station by scientists from the United States and Russia. MSAD is currently sponsoring science experiments participating in the Shuttle-Mir Science Program in cooperation with the Russians on the Mir space station. Included in the complement of MSAD experiments and equipment is a SAMS unit In a manner similar to Orbiter mission support, the SAMS unit supports science experiments from the U.S. and Russia by measuring the microgravity environment during experiment operations. The initial SAMS supported experiment was a Protein Crystal Growth (PCG) experiment from June to November 1995. SAMS data were obtained during the PCG operations on Mir in accordance with the PCG Principal Investigator's requirements. This report presents an overview of the SAMS data recorded to support this PCG experiment. The report contains plots of the SAMS 100 Hz sensor head data as an overview of the microgravity environment, including the STS-74 Shuttle-Mir docking.

DeLombard, Richard↗

Space processing economics

Two types of space processing operations may be considered economically justified; they are manufacturing operations that make profits and experiment operations that provide needed applied research results at lower costs than those of alternative methods. Some examples from the Skylab experiments suggest that applied research should become cost effective soon after the space shuttle and Spacelab become operational. In space manufacturing, the total cost of space operations required to process materials must be repaid by the value added to the materials by the processing. Accurate estimates of profitability are not yet possible because shuttle operational costs are not firmly established and the markets for future products are difficult to estimate. However, approximate calculations show that semiconductor products and biological preparations may be processed on a scale consistent with market requirements and at costs that are at least compatible with profitability using the Shuttle/Spacelab system.

Bredt, J. H.↗

Small-Body Proximity Operations & TAG: Navigation Experiences & Lessons Learned from the OSIRIS-REx Mission

On October 20th, 2020, the nearly two-year proximity operations campaign for the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx)mission at the near-Earth asteroid (101955) Bennu culminated in a successful Touch-and-Go (TAG) sample collection event. Navigation performance was a significant driver for flight activities at Bennu, which consisted of multiple phases geared towards characterizing the asteroid, selecting a sample site, and safely guiding the spacecraft to and from the surface in order to collect at least 60 g of pristine regolith. The entire operations team gained a tremendous amount of experience operating in the challenging small body environment and overcame many challenges. In this paper, we summarize navigation-focused experiences and lessons learned from OSIRIS-REx proximity operations at Bennu that are applicable to future missions to small asteroids, comets, and planetary moons. Areas of focus include staffing and organization, ground system infrastructure, mission phase planning, navigation operations, and spacecraft and payload considerations.

Kenneth M. Getzandanner↗

A Saturn launched X-ray astronomy experiment. Volume 1: S-027

The S-027 X-Ray Astronomy Experiment originally proposed in early 1966, was developed to detect X-rays in the 2 keV to 10 keV range. Both a prototype unit and flight unit were constructed with the prototype unit also serving as the engineering model, the qualification test unit, and after refurbishment, as the back-up flight unit. Two Ground Support Equipment consoles were built to verify the experiment operation. A photograph of one experiment package with its Ground Support Equipment is shown. The S-027 experiment was scheduled for launch in 1968/69 and although both units were completed and tested to the extent that either would be ready for the scheduled launch, delays in the space program resulted in a launch date slip of several years. When the 1968/69 launch delay became official, provisions were made for storage of the two experiment packages at SCI Electronics in Huntsville, Alabama until a new launch date could be established.

Source record↗

Maximally Expressive Task Modeling

Planning and scheduling systems organize "tasks" into a timeline or schedule. The tasks are defined within the scheduling system in logical containers called models. The dictionary might define a model of this type as "a system of things and relations satisfying a set of rules that, when applied to the things and relations, produce certainty about the tasks that are being modeled." One challenging domain for a planning and scheduling system is the operation of on-board experiment activities for the Space Station. The equipment used in these experiments is some of the most complex hardware ever developed by mankind, the information sought by these experiments is at the cutting edge of scientific endeavor, and the procedures for executing the experiments are intricate and exacting. Scheduling is made more difficult by a scarcity of space station resources. The models to be fed into the scheduler must describe both the complexity of the experiments and procedures (to ensure a valid schedule) and the flexibilities of the procedures and the equipment (to effectively utilize available resources). Clearly, scheduling space station experiment operations calls for a "maximally expressive" modeling schema. Modeling even the simplest of activities cannot be automated; no sensor can be attached to a piece of equipment that can discern how to use that piece of equipment; no camera can quantify how to operate a piece of equipment. Modeling is a human enterprise-both an art and a science. The modeling schema should allow the models to flow from the keyboard of the user as easily as works of literature flowed from the pen of Shakespeare. The Ground Systems Department at the Marshall Space Flight Center has embarked on an effort to develop a new scheduling engine that is highlighted by a maximally expressive modeling schema. This schema, presented in this paper, is a synergy of technological advances and domain-specific innovations.

Japp, John↗

Maximally Expressive Modeling of Operations Tasks

Planning and scheduling systems organize "tasks" into a timeline or schedule. The tasks are defined within the scheduling system in logical containers called models. The dictionary might define a model of this type as "a system of things and relations satisfying a set of rules that, when applied to the things and relations, produce certainty about the tasks that are being modeled." One challenging domain for a planning and scheduling system is the operation of on-board experiments for the International Space Station. In these experiments, the equipment used is among the most complex hardware ever developed, the information sought is at the cutting edge of scientific endeavor, and the procedures are intricate and exacting. Scheduling is made more difficult by a scarcity of station resources. The models to be fed into the scheduler must describe both the complexity of the experiments and procedures (to ensure a valid schedule) and the flexibilities of the procedures and the equipment (to effectively utilize available resources). Clearly, scheduling International Space Station experiment operations calls for a "maximally expressive" modeling schema.

Jaap, John↗

Maximally Expressive Modeling

Planning and scheduling systems organize tasks into a timeline or schedule. Tasks are logically grouped into containers called models. Models are a collection of related tasks, along with their dependencies and requirements, that when met will produce the desired result. One challenging domain for a planning and scheduling system is the operation of on-board experiments for the International Space Station. In these experiments, the equipment used is among the most complex hardware ever developed; the information sought is at the cutting edge of scientific endeavor; and the procedures are intricate and exacting. Scheduling is made more difficult by a scarcity of station resources. The models to be fed into the scheduler must describe both the complexity of the experiments and procedures (to ensure a valid schedule) and the flexibilities of the procedures and the equipment (to effectively utilize available resources). Clearly, scheduling International Space Station experiment operations calls for a maximally expressive modeling schema.

Jaap, John↗