Results for “corrective action management” — Page 5

NASA NTRS2002

Software Assists in Extensive Environmental Auditing

The Base Environmental Management System (BEMS) is a Web-based application program for managing and tracking audits by the Environmental Office of Stennis Space Center in conformity with standard 14001 of the International Organization for Standardization (ISO 14001). (This standard specifies requirements for an environmental-management system.) BEMS saves time by partly automating what were previously manual processes for creating audit checklists; recording and tracking audit results; issuing, tracking, and implementing corrective-action requests (CARs); tracking continuous improvements (CIs); and tracking audit results and statistics. BEMS consists of an administration module and an auditor module. As its name suggests, the administration module is used to administer the audit. It helps administrators to edit the list of audit questions; edit the list of audit locations; assign mandatory questions to locations; track, approve, and edit CARs; and edit completed audits. The auditor module is used by auditors to perform audits and record audit results: it helps the auditors to create audit checklists, complete audits, view completed audits, create CARs, record and acknowledge CIs, and generate reports from audit results.

Callac, Christopher↗

NASA NTRS2003

Software Assists in Extensive Environmental Auditing

The Base Environmental Management System (BEMS) is a Web-based application program for managing and tracking audits by the Environmental Office of Stennis Space Center in conformity with standard 14001 of the International Organization for Standardization (ISO 14001). (This standard specifies requirements for an environmental-management system.) BEMS saves time by partly automating what were previously manual processes for creating audit checklists; recording and tracking audit results; issuing, tracking, and implementing corrective-action requests (CARs); tracking continuous improvements (CIs); and tracking audit results and statistics. BEMS consists of an administration module and an auditor module. As its name suggests, the administration module is used to administer the audit. It helps administrators to edit the list of audit questions; edit the list of audit locations; assign mandatory questions to locations; track, approve, and edit CARs; and edit completed audits. The auditor module is used by auditors to perform audits and record audit results: it helps the auditors to create audit checklists, complete audits, view completed audits, create CARs, record and acknowledge CIs, and generate reports from audit results.

Callac, Christopher↗

NASA NTRS2008

Using Hyperspectral Imagery to Identify Turfgrass Stresses

The use of a form of remote sensing to aid in the management of large turfgrass fields (e.g. golf courses) has been proposed. A turfgrass field of interest would be surveyed in sunlight by use of an airborne hyperspectral imaging system, then the raw observational data would be preprocessed into hyperspectral reflectance image data. These data would be further processed to identify turfgrass stresses, to determine the spatial distributions of those stresses, and to generate maps showing the spatial distributions. Until now, chemicals and water have often been applied, variously, (1) indiscriminately to an entire turfgrass field without regard to localization of specific stresses or (2) to visible and possibly localized signs of stress for example, browning, damage from traffic, or conspicuous growth of weeds. Indiscriminate application is uneconomical and environmentally unsound; the amounts of water and chemicals consumed could be insufficient in some areas and excessive in most areas, and excess chemicals can leak into the environment. In cases in which developing stresses do not show visible signs at first, it could be more economical and effective to take corrective action before visible signs appear. By enabling early identification of specific stresses and their locations, the proposed method would provide guidance for planning more effective, more economical, and more environmentally sound turfgrass-management practices, including application of chemicals and water, aeration, and mowing. The underlying concept of using hyperspectral imagery to generate stress maps as guides to efficient management of vegetation in large fields is not new; it has been applied in the growth of crops to be harvested. What is new here is the effort to develop an algorithm that processes hyperspectral reflectance data into spectral indices specific to stresses in turfgrass. The development effort has included a study in which small turfgrass plots that were, variously, healthy or subjected to a variety of controlled stresses were observed by use of a hand-held spectroradiometer. The spectroradiometer readings in the wavelength range from 350 to 1,000 nm were processed to extract hyperspectral reflectance data, which, in turn, were analyzed to find correlations with the controlled stresses. Several indices were found to be correlated with drought stress and to be potentially useful for identifying drought stress before visible symptoms appear.

Hutto, Kendall↗

NASA NTRS2021

Earned Value Management (EVM) Implementation Handbook

The purpose of this handbook is to provide EVM guidance for the effective application, implementation, and utilization of EVM on NASA programs, projects, major contracts, and subcontracts in a consolidated reference document. EVM is a project management process that effectively integrates a project’s scope of work with schedule and cost elements for optimum project planning and control. The goal is to achieve timely and accurate quantification of progress that will facilitate management by exception and enable early visibility into the nature and the magnitude of technical, cost and schedule problems as well as the intended course and success of corrective actions.

Christopher Lewis Sadler↗

NASA NTRS2024

Interim Measure Report South Water Pump Station Potential Release Location 213 – Location of Concern 2 Kennedy Space Center, Florida

This report presents a summary of the polychlorinated biphenyl (PCB) interim measure (IM) activities that occurred in December 2022 and March 2023 at Location of Concern (LOC) 2 – Electrical Equipment Area associated with the South Water Pump Station (SWPS) Potential Release Location (PRL) 213, located at the John F. Kennedy Space Center (KSC), Florida. The SWPS site is monitored under KSC’s Resource Conservation and Recovery Act Corrective Action Program, which also meets the requirements of Chapter 62-780, Florida Administrative Code. Assessment activities have previously been performed at six SWPS LOCs identified during a Solid Waste Management Unit assessment in 2013. Based on the data collected during these assessments, it was determined that IM activities would be completed at one of the LOCs, LOC 2 – Electrical Equipment Area, and an IM Work Plan was prepared and approved. In 2019, demolition of the SWPS buildings and structures was completed, allowing for additional assessment at LOC 2, and it was determined that soil excavation to remove PCB-impacted soils was no longer required for LOC 2. The IM activities conducted following demolition are presented in this report and include shallow soil sample collection, conducted in December 2022, and monitoring well installation and groundwater sampling, both conducted in March 2023. AECOM Technical Services, Inc. (AECOM) personnel collected two soil samples from two boring locations, SWPS-SB0005 and SWPS-SB0018. The samples were collected at 0 to 0.5 feet below land surface (bls). AECOM also conducted oversight of one monitoring well installation, SWPS-MW0001 screened from 4 to 14 feet bls, and then subsequently collected one groundwater sample from SWPS-MW0001. The samples were submitted to a fixed-based laboratory for analysis by United States Environmental Protection Agency Method 8082A for total PCBs. There were no detections of PCBs in soil or groundwater during the reporting period.

Chadwick Sloan Lee↗

NASA NTRS2011

Solid Rocket Booster (SRB) - Evolution and Lessons Learned During the Shuttle Program

The Solid Rocket Booster (SRB) element integrates all the subsystems needed for ascent flight, entry, and recovery of the combined Booster and Motor system. These include the structures, avionics, thrust vector control, pyrotechnic, range safety, deceleration, thermal protection, and retrieval systems. This represents the only human-rated, recoverable and refurbishable solid rocket ever developed and flown. Challenges included subsystem integration, thermal environments and severe loads (including water impact), sometimes resulting in hardware attrition. Several of the subsystems evolved during the program through design changes. These included the thermal protection system, range safety system, parachute/recovery system, and others. Obsolescence issues occasionally required component recertification. Because the system was recovered, the SRB was ideal for data and imagery acquisition, which proved essential for understanding loads and system response. The three main parachutes that lower the SRBs to the ocean are the largest parachutes ever designed, and the SRBs are the largest structures ever to be lowered by parachutes. SRB recovery from the ocean was a unique process and represented a significant operational challenge; requiring personnel, facilities, transportation, and ground support equipment. The SRB element achieved reliability via extensive system testing and checkout, redundancy management, and a thorough postflight assessment process. Assembly and integration of the booster subsystems was a unique process and acceptance testing of reused hardware components was required for each build. Extensive testing was done to assure hardware functionality at each level of stage integration. Because the booster element is recoverable, subsystems were available for inspection and testing postflight, unique to the Shuttle launch vehicle. Problems were noted and corrective actions were implemented as needed. The postflight assessment process was quite detailed and a significant portion of flight operations. The SRBs provided fully redundant critical systems including thrust vector control, mission critical pyrotechnics, avionics, and parachute recovery system. The design intent was to lift off with full redundancy. On occasion, the redundancy management scheme was needed during flight operations. This paper describes some of the design challenges, how the design evolved with time, and key areas where hardware reusability contributed to improved system level understanding.

Kanner, Howard S.↗

NASA NTRS2009

Lessons Learned for Cx PRACA. Constellation Program Problem Reporting, Analysis and Corrective Action Process and System

This slide presentation reviews the Constellation Program Problem Reporting, Analysis and Corrective Action Process and System (Cx PRACA). The goal of the Cx PRACA is to incorporate Lessons learned from the Shuttle, ISS, and Orbiter programs by creating a single tool for managing the PRACA process, that clearly defines the scope of PRACA applicability and what must be reported, and defines the ownership and responsibility for managing the PRACA process including disposition approval authority. CxP PRACA is a process, supported by a single information gathering data module which will be integrated with a single CxP Information System, providing interoperability, import and export capability making the CxP PRACA a more effective and user friendly technical and management tool.

Kelle, Pido I.↗

NASA NTRS2012

A Systems Modeling Approach for Risk Management of Command File Errors

The main cause of commanding errors is often (but not always) due to procedures. Either lack of maturity in the processes, incompleteness of requirements or lack of compliance to these procedures. Other causes of commanding errors include lack of understanding of system states, inadequate communication, and making hasty changes in standard procedures in response to an unexpected event. In general, it's important to look at the big picture prior to making corrective actions. In the case of errors traced back to procedures, considering the reliability of the process as a metric during its' design may help to reduce risk. This metric is obtained by using data from Nuclear Industry regarding human reliability. A structured method for the collection of anomaly data will help the operator think systematically about the anomaly and facilitate risk management. Formal models can be used for risk based design and risk management. A generic set of models can be customized for a broad range of missions.

probabilistic risk↗

NASA NTRS2011

Solid Rocket Booster (SRB) Flight System Integration at Its Best

The Solid Rocket Booster (SRB) element integrates all the subsystems needed for ascent flight, entry, and recovery of the combined Booster and Motor system. These include the structures, avionics, thrust vector control, pyrotechnic, range safety, deceleration, thermal protection, and retrieval systems. This represents the only human-rated, recoverable and refurbishable solid rocket ever developed and flown. Challenges included subsystem integration, thermal environments and severe loads (including water impact), sometimes resulting in hardware attrition. Several of the subsystems evolved during the program through design changes. These included the thermal protection system, range safety system, parachute/recovery system, and others. Because the system was recovered, the SRB was ideal for data and imagery acquisition, which proved essential for understanding loads, environments and system response. The three main parachutes that lower the SRBs to the ocean are the largest parachutes ever designed, and the SRBs are the largest structures ever to be lowered by parachutes. SRB recovery from the ocean was a unique process and represented a significant operational challenge; requiring personnel, facilities, transportation, and ground support equipment. The SRB element achieved reliability via extensive system testing and checkout, redundancy management, and a thorough postflight assessment process. However, the in-flight data and postflight assessment process revealed the hardware was affected much more strongly than originally anticipated. Assembly and integration of the booster subsystems required acceptance testing of reused hardware components for each build. Extensive testing was done to assure hardware functionality at each level of stage integration. Because the booster element is recoverable, subsystems were available for inspection and testing postflight, unique to the Shuttle launch vehicle. Problems were noted and corrective actions were implemented as needed. The postflight assessment process was quite detailed and a significant portion of flight operations. The SRBs provided fully redundant critical systems including thrust vector control, mission critical pyrotechnics, avionics, and parachute recovery system. The design intent was to lift off with full redundancy. On occasion, the redundancy management scheme was needed during flight operations. This paper describes some of the design challenges and technical issues, how the design evolved with time, and key areas where hardware reusability contributed to improved system level understanding.

Wood, T. David↗

NASA NTRS2024

Single Drop Cytometry Onboard the International Space Station

Real-time lab analysis is needed to support clinical decision making and research on human missions to the Moon and Mars. Powerful laboratory instruments, such as flow cytometers, are generally too cumbersome for spaceflight. Here, we show that scant test samples can be measured in microgravity, by a trained astronaut, using a miniature cytometry-based analyzer, the rHEALTH ONE, modified specifically for spaceflight. The base device addresses critical spaceflight requirements including minimal resource utilization and alignment-free optics for surviving rocket launch. To fully enable reduced gravity operation onboard the space station, we incorporated bubble-free fluidics, electromagnetic shielding, and gravity-independent sample introduction. We show microvolume flow cytometry from 10 μL sample drops, with data from five simultaneous channels using 10 μs bin intervals during each sample run, yielding an average of 72 million raw data points in approximately 2 minutes. We demonstrate the device measures each test sample repeatably, including correct identification of a sample that degraded in transit to the International Space Station. This approach can be utilized to further our understanding of spaceflight biology and provide immediate, actionable diagnostic information for management of astronaut health without the need for Earth-dependent analysis.

Daniel J. Rea↗

NASA NTRS2008

Integrated Software Systems for Crew Management During Extravehicular Activity in Planetary Terrain Exploration

Initial planetary explorations with the Apollo program had a veritable ground support army monitoring the safety and health of the 12 astronauts who performed lunar surface extravehicular activities (EVAs). Given the distances involved, this will not be possible on Mars. A spacesuit for Mars must be smart enough to replace that army. The next generation suits can do so using 2 software systems serving as virtual companions, LEGACI (Life support, Exploration Guidance Algorithm and Consumable Interrogator) and VIOLET (Voice Initiated Operator for Life support and Exploration Tracking). The system presented in this study integrates data inputs from a suite of sensors into the MIII suit s communications, avionics and informatics hardware for distribution to remote managers and data analysis. If successful, the system has application not only for Mars but for nearer term missions to the Moon, and the next generation suits used on ISS as well. Field tests are conducted to assess capabilities for next generation spacesuits at Johnson Space Center (JSC) as well as the Mars and Lunar analog (Devon Island, Canada). LEGACI integrates data inputs from a suite of noninvasive biosensors in the suit and the astronaut (heart rate, suit inlet/outlet lcg temperature and flowrate, suit outlet gas and dewpoint temperature, pCO2, suit O2 pressure, state vector (accelerometry) and others). In the Integrated Walkback Suit Tests held at NASA-JSC and the HMP tests at Devon Island, communication and informatics capabilities were tested (including routing by satellite from the suit at Devon Island to JSC in Houston via secure servers at VCU in Richmond, VA). Results. The input from all the sensors enable LEGACI to compute multiple independent assessments of metabolic rate, from which a "best" met rate is chosen based on statistical methods. This rate can compute detailed information about the suit, crew and EVA performance using test-derived algorithms. VIOLET gives LEGACI voice activation capability, allowing the crew to query the suit, and receive feedback and alerts that will lead to corrective action. LEGACI and VIOLET can also automatically control the astronaut's cooling and consumable use rate without crew input if desired. These findings suggest that non-invasive physiological and environmental sensors supported with data analysis can allow for more effective management of mission task performance during EVA. Integrated remote and local view of data metrics allow crewmember to receive real time feedback in synch with mission control in preventing performance shortcomings for EVA in exploration missions.

Kuznetz, Lawrence↗

NASA NTRS1975

Apollo experience report: Flight anomaly resolution

The identification of flight anomalies, the determination of their causes, and the approaches taken for corrective action are described. Interrelationships of the broad range of disciplines involved with the complex systems and the team concept employed to ensure timely and accurate resolution of anomalies are discussed. The documentation techniques and the techniques for management of anomaly resolution are included. Examples of specific anomalies are presented in the original form of their progressive documentation. Flight anomaly resolution functioned as a part of the real-time mission support and postflight testing, and results were included in the postflight documentation.

Lobb, J. D.↗

NASA NTRS2026

Spacecraft Water Impurity Monitor, a System for Water Quality Analysis on Exploration Missions Beyond Low Earth Orbit

Exploration missions beyond low-earth-orbit (LEO) will require advanced instrumentation to monitor water quality. Traveling beyond LEO means the transfer of water samples to an Earth-based laboratory for detailed analysis is not feasible. Detailed analysis of water composition during exploration is still necessary, because having the capability to determine the specific organic chemical causing a change in total organic carbon (TOC) or the specific metal or ionic species causing a change in conductivity has the potential to inform the crew health and system management decisions. On a new vehicle such as a lunar or Mars surface habitat or a Mars transit vehicle, finding “new” impurities not seen on ISS should be expected. The key is to identify the impurity so the correct action can be taken. On ISS we can measure TOC, conductivity, and other physical properties but do not have the capability for detailed analysis using vehicle instrumentation. This is acceptable because ISS can send samples down to Earth for further analysis and obtain the detailed composition. The Spacecraft Water Impurity Monitor (SWIM) will provide detailed water quality analysis for missions in which sample down mass is not available. SWIM is a system comprising organic and inorganic analysis modules. For organic chemicals, a gas chromatograph mass spectrometer (GCMS) detects and identifies organic impurities. For inorganic species, a capillary electrophoresis capacitively coupled contactless conductivity detection (CE-C4D) system as well as ion specific electrodes detect and identify metal ions and other inorganic salts / acids. The SWIM technology demonstration project has completed a System Requirements Review (SRR) to finalize detection requirements and is currently working to refine vehicle interface requirements for a future technology demonstration. The project also has begun preliminary flight design activities for the core analyzers in the instrument suite.

Water Monitoring↗

NASA NTRS2026

Spacecraft Water Impurity Monitor, a System for Water Quality Analysis on Exploration Missions Beyond Low Earth Orbit

Exploration missions beyond low-earth-orbit (LEO) will require advanced instrumentation to monitor water quality. Traveling beyond LEO means the transfer of water samples to an Earth-based laboratory for detailed analysis is not feasible. Detailed analysis of water composition during exploration is still necessary, because having the capability to determine the specific organic chemical causing a change in total organic carbon (TOC) or the specific metal or ionic species causing a change in conductivity has the potential to inform the crew health and system management decisions. On a new vehicle such as a lunar or Mars surface habitat or a Mars transit vehicle, finding “new” impurities not seen on ISS should be expected. The key is to identify the impurity so the correct action can be taken. On ISS we can measure TOC, conductivity, and other physical properties but do not have the capability for detailed analysis using vehicle instrumentation. This is acceptable because ISS can send samples down to Earth for further analysis and obtain the detailed composition. The Spacecraft Water Impurity Monitor (SWIM) will provide detailed water quality analysis for missions in which sample down mass is not available. SWIM is a system comprising organic and inorganic analysis modules. For organic chemicals, a gas chromatograph mass spectrometer (GCMS) detects and identifies organic impurities. For inorganic species, a capillary electrophoresis capacitively coupled contactless conductivity detection (CE-C4D) system as well as ion specific electrodes detect and identify metal ions and other inorganic salts / acids. The SWIM technology demonstration project has completed a System Requirements Review (SRR) to finalize detection requirements and is currently working to refine vehicle interface requirements for a future technology demonstration. The project also has begun preliminary flight design activities for the core analyzers in the instrument suite.

Water Monitoring↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRS1995

A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.

Wu, G. Gordon↗