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At least 253 records · Page 14

NASA/MOD Operations Impacts from Shuttle Program

Operations plays a pivotal role in the success of any human spaceflight program. This paper will highlight some of the core tenets of spaceflight operations from a systems perspective and use several examples from the Space Shuttle Program to highlight where the success and safety of a mission can hinge upon the preparedness and competency of the operations team. Further, awareness of the types of operations scenarios and impacts that can arise during human crewed space missions can help inform design and mission planning decisions long before a vehicle gets into orbit. A strong operations team is crucial to the development of future programs; capturing the lessons learned from the successes and failures of a past program will allow for safer, more efficient, and better designed programs in the future. No matter how well a vehicle is designed and constructed, there are always unexpected events or failures that occur during space flight missions. Preparation, training, real-time execution, and troubleshooting are skills and values of the Mission Operations Directorate (MOD) flight controller; these operational standards have proven invaluable to the Space Shuttle Program. Understanding and mastery of these same skills will be required of any operations team as technology advances and new vehicles are developed. This paper will focus on individual Space Shuttle mission case studies where specific operational skills, techniques, and preparedness allowed for mission safety and success. It will detail the events leading up to the scenario or failure, how the operations team identified and dealt with the failure and its downstream impacts. The various options for real-time troubleshooting will be discussed along with the operations team final recommendation, execution, and outcome. Finally, the lessons learned will be summarized along with an explanation of how these lessons were used to improve the operational preparedness of future flight control teams.

Fitzpatrick, Michael↗

The Contribution of Pilots to Resilience in Normal Operations: A Survey Approach

Much of our knowledge about human performance in flight safety has come from the analysis of undesired events, whether accidents, incidents, or crew behaviors identified via flight exceedance monitoring or observational techniques. In recent years, there has been an acknowledgement that operational personnel are not merely sources of “human error”, but also make a unique human contribution to safe outcomes. In a few celebrated cases, this takes the form of “heroic saves”, but on many more occasions, operational personnel contribute to safety through everyday, often-unnoticed actions that turn potentially hazardous situations into non-events. An emerging approach to safety, frequently referred to as “Safety II,” proposes that the positive human contribution is an important and largely untapped source of safety information. Some airlines have successfully trained observers to identify and record the positive behaviors exhibited by the crew over the course of a flight. In other cases, flight crew are interviewed about good practices or positive behaviors. However, each of these methods are relatively limited in scale and resource intensive. A survey could provide a relatively low-cost approach to systematically gather this information on a larger scale. The primary purpose of the research was to develop and assess a surveys methodology for assessing crews' activities in normal flights and the operational perturbations encountered during normal operations. We hope that such a survey could be both a research tool as well as a safety management aid for the aviation industry. We collected responses concerning revenue flights from two groups of airline pilots (N = 25 & N= 65). The results indicated that relatively few flights proceeded exactly as in the original flight plan. Pilots routinely anticipated and adapted to changing circumstances. We will review the challenges encountered in developing the survey and summarize preliminary findings from two administrations of the survey to airline pilots.

human contribution safety↗

The Contribution of Pilots to Resilience in Normal Operations. Part II: A closer look at briefings: Anticipation and Monitoring Also Known as Planning and Coordination

Much of our knowledge about human performance in flight safety has come from the analysis of undesired events, whether accidents, incidents, or crew behaviors identified via flight exceedance monitoring or observational techniques. In recent years, there has been an acknowledgement that operational personnel are not merely sources of “human error”, but also make a unique human contribution to safe outcomes. In a few celebrated cases, this takes the form of “heroic saves”, but on many more occasions, operational personnel contribute to safety through everyday, often-unnoticed actions that turn potentially hazardous situations into non-events. An emerging approach to safety, frequently referred to as “Safety II,” proposes that the positive human contribution is an important and largely untapped source of safety information. Some airlines have successfully trained observers to identify and record the positive behaviors exhibited by the crew over the course of a flight. In other cases, flight crew are interviewed about good practices or positive behaviors. However, each of these methods are relatively limited in scale and resource intensive. A survey could provide a relatively low-cost approach to systematically gather this information on a larger scale. The primary purpose of the research was to develop and assess a surveys methodology for assessing crews' activities in normal flights and the operational perturbations encountered during normal operations. We hope that such a survey could be both a research tool as well as a safety management aid for the aviation industry. We collected responses concerning revenue flights from two groups of airline pilots (N = 25 & N= 65). The results indicated that relatively few flights proceeded exactly as in the original flight plan. Pilots routinely anticipated and adapted to changing circumstances. We will review the challenges encountered in developing the survey and summarize preliminary findings from two administrations of the survey to airline pilots.

human contribution safety↗

Systems Health Management and Prognostics Approaches for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto 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 the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously published information.

Systems Health Managent↗

Health Monitoring and Prognostics for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto 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 the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously approved and published information.

Systems Health Managent↗

Implementation of COTs Hardware in Non-Critical Space Applications: A Brief Tutorial

Approaches used for manned applications include limited items such as CD-players evaluated for safety to high criticality applications where the COTs hardware is evaluated on a case-by-case basis for the application and commensurate screening and qualification testing. COTS hardware is successfully implemented in both the International Space Station and Space Shuttle but requires evaluation and modifications for the application. Screening and qualification of COTs hardware used in critical applications may need to be more extensive and stringent than traditional military screening. Evaluation for: a) Suitability for the application; b) Safety; c) Reliability and maintainability; and d) Workmanship.

Yoder, Geoffrey L.↗

Statistical learning framework for safety and failure analysis of a DNN-based autonomous aircraft system

Deep Neural Networks (DNNs) and Machine Learning technology is increasingly used for safety-critical applications in the Aerospace domain. To ensure safe operations, the DNN and the system must undergo rigorous verification and validation, including advanced statistical analyses. Performance and safety of the DNN and system behavior must not only be analyzed for the nominal case, but under numerous off-nominal and failure cases. In this paper we will describe how our statistical learning framework SYSAI can efficiently perform such analyses using the tool’s unique combination of advanced learning modeling and statistical analysis techniques. SYSAI can effectively explore the high-dimensional state and failure space of the system under test; geometrical shape detection of safety regions and boundaries support explainability of the results to the designer. In this paper, we report experiments and results obtained with a vision-based DNN control system (ACT) that is capable of autonomously steering an aircraft down a runway.

Yuning He↗

System and Safety Analysis with SysAI A Statistical Learning Framework

This is a tutorial on how to use the SYSAI (System Analysis using Statistical AI), a flexible statistical learning framework for the V&V and analysis of complex and high-dimensional Aerospace systems with DNN and AI components. SYSAI provides functionality for a variety of analyses and V&V tasks, including statistical data analysis, high dimensional safety-envelope and time-series analysis, property checking, as well as intelligent test-case generation. The tutorial will demonstrate SYSAI with our industrial partner’s Autonomous Centerline Tracking system, which uses a DNN to enable autonomous aircraft taxiing as an example. Video & Tutorial

Statistical V&V for Complex safety-critical system↗

Informing NLP Learning Tasks by Tracking User Features: An ASRS Use Case using Kaona

There has been growing interest in utilizing natural language processing (NLP) algorithms in Aviation Safety. This interest has extended to leveraging the decades of records publicly available on the Aviation Safety Reporting System (ASRS). While related literature has given more emphasis in lessons learned from the narratives, our prior work has focused on using NLP to support narrative search in the ASRS. Specifically, we evaluated if the use of alternative search mechanisms to keyword search, such as the retrieval of related narratives even without matching keywords could improve narrative discovery. A difficulty in experimenting alternative search mechanisms in any information retrieval task is the lack of ground truth. To address this limitation, we propose Kaona, a lightweight interface which enables the prototyping of alternative search retrieval tasks, by tracking user experience both explicitly (user-specified feedback), or implicitly (user navigation through interface affordances). Differently from distracting requests for feedback during user navigation, Kaona collects explicit feedback from users by mapping them to affordances which support the user workflow, while obtaining ground truth information for learning tasks.

human-computer-interaction↗

Structural dynamics model and response of the deployable reference configuration space station

The analytical models and results of a structural dynamics investigation of the reference initial operation and evolutionary configurations of the nine foot bay space station are presented. This investigation was carried out between April and August 1984 as part of a team effort to define a reference configuration for the first U.S. manned space station. The results presented herein serve as a guide, a point of departure and a standard for future NASA and contractor studies leading to the design of the Space Station. The reference initial operation configuration of the nine foot bay station was found to be very flexible, with its lowest mode between 0.096 and 0.138 Hertz depending on station attachments. However, for the transient load cases which were then available, internal member loads had positive margins of safety and preliminary results indicate that laboratory experiments which require quiescent conditions can be satisfied down to the order of 0.0001 g's.

Housner, J. M.↗

Alternate vehicles for engine/vehicle optimization

The space shuttle main engine, full flow staged combustion, integrated modular engine concept, split expander, and expander bleed rocket engine cycles were studied for use on Single-Stage-to-Orbit fully reusable vehicles. The vehicle uses vertical take-off and horizontal landing and liquid hydrogen rockets for propulsion. The PROPSIZE computer code was modified for use on the available computers. Vehicle sizing was done after trajectory optimization for various engine designs. The various rocket engine cycles were compared and it was found that the full flow staged combustion cycle had the lowest vehicle dry mass. The split expander cycle could have advantages in safety and cooling which could make it the preferred choice in some cases. Comparison to previous work with two-stage heavy-lift vehicles showed that the same ranking of the cycles was found for both vehicle concepts.

Venkatasubramanyam, G.↗

Defining the performance gap: Conducting a self-assessment

This paper presents two different approaches to performing self-assessments of continuous improvement activities. Case Study 1 describes the activities performed by JSC to assess the implementation of continuous improvement efforts at the NASA Center. The JSC approach included surveys administered to randomly selected NASA personnel and personal interviews with NASA and contractor management personnel. Case Study 2 describes the continuous improvement survey performed by the JSC Safety, Reliability, and Quality Assurance (SR&QA) organization. This survey consisted of a short questionnaire (50 questions) administered to all NASA and contractor SR&QA personnel. The questionnaire is based on the eight categories of the President's Award for Quality and Productivity Improvement. It is designed to objectively determine placement on the TQ benchmark and identify a roadmap for improvement.

Braymer, Susan A.↗

Fabrication end Deployment Testing of Meter Solar Sail Quadrants for a Scaleable Square Solar Sail Ground Test System

In order for solar sail propulsion technologies to be considered as a viable option for a wide range of near term practical missions a predictable, stable, reliable, manufactureable, scaleable, and cost effective system must be developed and tested first on earth and then on orbit. The design and development of a Scaleable Square Solar Sail System (S^4) is well underway a t AEC-Able Engineering Co. Inc., and the design and production of the Solar Sails for this system is being carried out by SRS Technologies. In April and May of 2004 a single quadrant 10-meter system was tested at NASA LARC's vacuum chamber and a four quadrant 20-meter system has been designed and built for deployment and testing in the Spring of 2005 at NASA/Glenn Research Center's Plumb Brook Facility. SRS has developed an effective and efficient design for triangular sail quadrants that are supported are three points and provide a flat reflective surface with a high fill factor. This sail design is robust enough for deployments in a one atmosphere, one gravity environment and incorporates several advanced features including adhesiveless seaming of membrane strips, compliant edge borders to allow for film membrane cord strain mismatch without causing wrinkling and low mass (3% of total sail mass) ripstop. This paper will outline the sail design and fabrication process, the lessons learned and the resulting mature production, packaging and deployment processes that have been developed. It will also highlight the scalability of the equipment and processes that were developed to fabricate and package the sails. Based on recent experience, SRS is confidant that flight worthy solar sails in the 40-120-meter size range with areal density in the 4-5g/sq m (sail minus structure) range can be produced with existing technology. Additional film production research will lead to further reductions in film thickness to less than 1 micron enabling production of sails with areal densities as low as 20 g/sq m using the current design resulting in a system areal density of as low as 5.3g/sq m. These areal densities are low enough to allow nearly all of the Solar Sail missions that have been proposed by the scientific community and the fundamental technology required to produce these sails has been demonstrated on the ground test sails that have recently been built. These demonstrations have shown that the technology is mature enough to build sails needed to support critical science missions. Solar Sails will be an enabling technology for NASA's Vision for Space Exploration by allowing communication satellite orbits that can maintain continuous communication with the polar regions of the Moon and Mars and to support solar weather monitoring to provide early warning of solar flares and storms that could threaten the safety of astronauts and other spacecraft.

Laue, Greg↗

Fabrication and Deployment Testing of Solar Sail Quadrants for a 20-Meter Solar Sail Ground Test System Demonstration

A 20-meter Scalable Square Solar Sail (S(sup 4)) System was produced and successfully completed functional vacuum testing in NASA Glenn's Space Power Facility at Plum Brook Station Ohio in May 2005. The S(sup 4) system was designed and developed by ATK Space Systems, and the design and production of the Solar Sails for this system was carried out by SRS Technologies. The S(sup 4) system consists of a central structure with four deployable carbon fiber masts that support four triangular sails. SRS has developed an effective and efficient design for triangular sail quadrants that are supported at three points and provide a flat reflective surface with a high fill factor. This sail design is robust enough for deployments in a one atmosphere, one gravity environment and incorporates several advanced features including adhesiveless seaming of membrane strips, compliant edge borders to allow for film membrane cord strain mismatch without causing wrinkling and low mass (3% of total sail mass) ripstop. This paper will outline some of the sail design and fabrication processes and the mature production, packaging and deployment processes that have been developed. This paper will also detail the successful ambient and vacuum testing of the sails and the ATK spacecraft structure. Based on recent experience and testing, SRS is confidant that high Technology Readiness Level (TRL) 5-6 solar sails in the 40-120-meter size range with areal density in the 4-5 grams per square meters (sail minus structure) range can be produced with existing technology. Additional film production research will lead to further reductions in film thickness to less than 1 micron enabling production of sails with areal densities as low as 2.0 grams per square meters using the current design, resulting in a system areal densities as low as 5.3 grams per square meters (sail and structure). These areal densities are low enough to allow nearly all of the Solar Sail missions that have been proposed by the scientific community. The fundamental technologies required to produce these systems has been demonstrated on the 20-meter S(sup 4) sails that have recently completed ground testing demonstrating a mature and technology suitable for incorporation into future flight validation and future mission. Solar Sails can support NASA's Vision for Space Exploration by allowing communication satellite orbits that can maintain continuous communication with the polar regions of the Moon and Mars and to support solar weather monitoring to provide early warning of solar flares and storms that could threaten the safety of astronauts and other spacecraft.

Laue, Greg↗

Element Load Data Processor (ELDAP) Users Manual

Often, the shear and tensile forces and moments are extracted from finite element analyses to be used in off-line calculations for evaluating the integrity of structural connections involving bolts, rivets, and welds. Usually the maximum forces and moments are desired for use in the calculations. In situations where there are numerous structural connections of interest for numerous load cases, the effort in finding the true maximum force and/or moment combinations among all fasteners and welds and load cases becomes difficult. The Element Load Data Processor (ELDAP) software described herein makes this effort manageable. This software eliminates the possibility of overlooking the worst-case forces and moments that could result in erroneous positive margins of safety and/or selecting inconsistent combinations of forces and moments resulting in false negative margins of safety. In addition to forces and moments, any scalar quantity output in a PATRAN report file may be evaluated with this software. This software was originally written to fill an urgent need during the structural analysis of the Ares I-X Interstage segment. As such, this software was coded in a straightforward manner with no effort made to optimize or minimize code or to develop a graphical user interface.

Ramsey, John K., Jr.↗

Prognostics for Systems Health Management - Model and Hybrid Based Approaches. Where are We Heading?

To facilitate and solve the prediction problem, awareness of the current state and health of the system is key, since it is necessary to perform condition-based system health predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditional. In case of next generation electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (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 health state 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 operational conditions and flight profiles for accurate estimation of end-of-discharge (EOD) for the batteries. Similar framework can be implemented to other complex systems and subsystems. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system, subsystem swell as component levels. Given models of the current and future system behavior, a general approach of model-based prognostics is discussed as a solution to the prediction problem and further for decision making. Data driven prognostics approaches have been equally used with good results in the past, where respective approaches have their own challenges to tackle. This limits their applicability to complex real-world domains: (a) high complexity or incompleteness of physics-based models and (b) limited representativeness of the training dataset for data-driven models. With the advent of internet of things for data collection and increased use of ML algorithms, hybrid approaches are the next avenue to reduce the challenges and achieve better results. An hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, we use physics-based performance models to infer unobservable model parameters related to the system's components health solving a calibration problem.

Prognostics↗

Short Circuiting the Controller – Missteps in Maintenance and Inspection of Process and Wiring in STS-93

The primary objective of the Space Transportation System mission 93 (STS-93) was to deploy the Chandra X-Ray Observatory. Chandra, the world's most powerful X-Ray telescope, allowed scientists from around the world to study some of the most distant and dynamic objects in the universe. Stripped of nearly 7,000 pounds of its own gear to make room for the payload, the orbiter assigned to this mission was Space Shuttle Columbia. Prior to STS-93, Columbia had flown 25 flights and was NASA's oldest and heaviest orbiter. On July 23, 1999, after two prior launch scrubs, Eileen Collins and her crew of four launched from Kennedy Space Center. About five seconds after launch, Mission Control at Johnson Space Center detected a voltage drop on one of Columbia's electrical buses. As a result of this power fluctuation, a primary and back-up Main Engine controller dropped offline. Given design redundancy, the two remaining controllers supported all three engines. If there had been any other AC bus issues, one engine of the three on the Orbiter would have shut down. The redundant set of digital computer units in each engine controller saved Columbia and her crew from a very risky contingency abort. Post-flight inspection revealed soot on a screw head and a hole in an adjacent Kapton insulated wire. The single strand of polyimide wire was located nearly half-way down the payload bay. The Shuttle Independent Assessment Team (SIAT) reported that the wire had rubbed and chaffed against a burred screw head. The burr was later determined to be the result of overtightening of the screw by a technician during a maintenance refurbishment. Alone, the burr may not have been problematic, but later, during another ground processing event, possibly years after, someone inadvertently stepped on the wiring harness. With the pressure and motion of unintended contact, some of the Kapton insulation rubbed off against the burred screw head. The SIAT suspected the wire damage was pre-existing and was caused 4 or 5 years prior to the flight. Finally, the intense vibrations during the launch sequence allowed contact between the exposed conductor and exposed metal area on the burred screw head, resulting in the arcing and shorting of the wire. Due to the quick turnaround times of Space Shuttle Orbiters, wiring issues caused from multiple maintenance events were often overlooked. Additionally, failing to incorporate thorough and early inclusion of human systems integration (HSI) applications as a crucial part of the decision process can result in these types of misshaps. In order to reduce human error associated with integrated manufacturing, maintenance, refurbishment and flight preparations, wire inspection criteria should be refined and standardized, visual inspection processes should be quantified, and technicians should be certified by specially trained instructors. This case, among many others, unveils why human error management and development of safety metrics is a vital piece in the development of complex systems, and why it should be supported aggressively and implemented program wide.

Human Systems Integration↗

Verification of the Generalized Aerospace Simulation in Simulink (R)

NASA uses six-degrees-of-freedom (6-DOF) simulations tools to design, test, develop Guidance Navigation and Control (GN&C) software, and certify vehicle performance prior to flight. Therefore, it is critical that the 6-DOF tools used for vehicle design and certification are validated. The focus of this work is the vali-dation of the NASA Marshall Space Flight Center 6-DOF “GeneraLized Aero-space Simulation in Simulink” (GLASS) framework tool. The GLASS tool framework is currently used to support NASA GN&C insight for the Human Landing System (HLS) project, simulating vehicle dynamics during lunar descent and as-cent. The GLASS framework utilizes the off-the-shelf Mathworks ® Simscape Multibody® toolbox to model vehicle multi-body dynamics. NASA’s Engineering and Safety Center (NESC) provides a set of 6-DOF simulation verification “check cases” that are available to any user needing to verify 6-DOF tools. The check cases contain seventeen atmospheric and twenty-six orbital test scenarios are provided to validate equations of motion, environmental models (e.g., atmosphere, gravitation, and geodesy) and tool propagators. This paper compares GLASS 6-DOF simulation results against the NESC check cases’ results via simulation-to-simulation comparisons. The comparisons demonstrate that GLASS simulation results are “in family” with the outputs of the applicable NASA NESC check cases and verifies the GLASS core framework dynamics and the correct implementation of the check case scenario models.

6-Dof↗