Results for “threat analysis” — Page 13

NASA NTRS2013

The Regolith Biters: A Divide-And-Conquer Architecture for Sample-Return Missions

The collective interaction of simple systems can be leveraged to attain complex goals. Based on this principle, we envision space system architectures where the core functional components are decoupled, autonomous, and cooperative. We aim to pursue this vision in the context of small-body sample-return missions. After all, no experimental study sheds more light into our understanding of the origin and evolution of the Solar System than the analysis of samples from asteroids and comets. We also believe that their study is important from a strategic perspective: meteorite impacts pose a direct and credible threat to life on Earth, and the development of contingency small-body deflection missions presupposes some knowledge of the target body. The current architectural paradigm for sample-return missions is centered around a design where spacecraft and sampling device are merged into a single, complex system. We argue that this monolithic approach couples the navigation and sample-collection problems, making both more difficult. In contrast, we propose a decoupled system based on the coordinated interaction between a spacecraft and a collective of small, simple devices - the Regolith Biters (RBs). A spacecraft carrying a number of RBs would travel to the vicinity of a small body. From a favorable vantage point, and while remaining within a safe distance in a non-colliding trajectory, it would release the RBs towards the target body. Upon encountering the body, they would bite the regolith (thus retaining a sample), and eject back to orbit. The spacecraft, being endowed with appropriate navigation and tracking capabilities, would rendezvous with and collect those RBs within its reach, and bring them back to Earth. Separating the navigation and sampling concerns removes the need for proximity operations with the small body-the stage in current architectures that carries the most challenges and risks. Eliminating the need for proximity operations brings back to the discussion the exploration of exciting prospects, like highly active comets, fast-rotating bodies, and binary systems. Distributing the sampling problem among a collective of agents provides the opportunity to sample multiple regions in a single mission. It also provides robustness to various environmental conditions, and may enable the distributed, in situ characterization of the body. In the search for reliability, current architectures rely on complexity: an elaborate system should succeed at once. We rely on numbers: a given agent may fail at any stage, but success is attained by the collective.

Asteroids↗

NASA NTRS2022

Impacts of Climate Change on Global Food Trade Networks

Countries' reliance on global food trade networks implies that regionally different climate change impacts on crop yields will be transmitted across borders. This redistribution constitutes a significant challenge for climate adaptation planning and may affect how countries engage in cooperative action. This paper investigates the long-term (2070–2099) potential impacts of climate change on global food trade networks of three key crops: wheat, rice and maize. We propose a simple network model to project how climate change impacts on crop yields may be translated into changes in trade. Combining trade and climate impact data, our analysis proceeds in three steps. First, we use network community detection to analyse how the concentration of global production in present-day trade communities may become disrupted with climate change impacts. Second, we study how countries may change their network position following climate change impacts. Third, we study the total climate-induced change in production plus import within trade communities. Results indicate that the stability of food trade network structures compared to today differs between crops, and that countries' maize trade is least stable under climate change impacts. Results also project that threats to global food security may depend on production change in a few major global producers, and whether trade communities can balance production and import loss in some vulnerable countries. Overall, our model contributes a baseline analysis of cross-border climate impacts on food trade networks.

climate change↗

DOE OSTI2025

Capability Building Progression of an Insider Threat Mitigation Program at an International Research Reactor

The nuclear industry recognizes the difficulties involved in developing effective managerial and leadership skills in a highly technical and proficient workforce such as that found in nuclear facilities. Implementing an insider threat mitigation program (ITMP) within the nuclear industry is a complex and ongoing process that demands a comprehensive understanding of human behavior, an organization’s security culture, and rigorous regulatory requirements yet also accounts for facility characteristics, physical security, material flow, and activities involving nuclear material. Given the high-consequence nature of research reactor operations, even minor lapses can lead to safety, security, and reputational risks. An effective ITMP requires a defense-in-depth approach that incorporates behavioral analysis, robust vetting procedures, continuous monitoring, and cross-disciplinary coordination. It must also promote a culture of vigilance and accountability at all levels up to and including executive leadership but be flexible enough to adapt to evolving global threats and technological advances. Insider threat mitigation is not a one-time effort but rather a sustained commitment to excellence in safety and security. Establishing a culture in which personnel proactively report incidents and issues that could affect nuclear safety and security is vital to maintaining a safe and secure operational environment. This document was developed to guide senior management and research reactor organizations in creating comprehensive programs to effectively manage and mitigate insider threat behaviors and actions. It focuses on the key pillars of an effective ITMP, including the national legal framework, security culture, preventive and protective measures, cyber security, and performance evaluation. By using a systematic approach during implementation, facilities can foster environments conducive to insider threat detection and support long-term program sustainability. The document also provides strategies for improving communication across all levels of an organization, helping to eliminate barriers that hinder the development of robust ITMPs and enhance overall security culture. In today’s organizations, the concept of leveraging safety and security culture lessons to facilitate knowledge transfer is rapidly evolving to expedite insider threat management and security culture improvements. This document outlines the rationale for evaluating an ITMP based on national customs, culture, and stakeholders. The elements are all germane to reliability and trustworthiness and relate to security concerns that states may encounter. The document focuses not only on individual perceptions regarding security issues and capability building but also on team building and how to resolve concerns. The implementers of a facility’s ITMP may zero in on indicators of insider threats within their enterprise. This material will benefit organizations when it is applied using a systematic and structured approach as demonstrated throughout the document.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2024

Attack Surface of Wind Energy Technologies in the United States

Low cost, reliable electrical energy production from wind relies upon automation and control systems, arguably more so than traditional thermal generation. These same systems, however, can serve as the target of adversaries’ cyber-attacks. Idaho National Laboratory (INL), at the request of the Department of Energy’s (DOE’s) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) and Energy Efficiency and Renewable Energy’s (EERE’s) Wind Energy Technologies Office (WETO), evaluated a generalized wind plant architecture to understand the classes of potential threat actors and the vectors that could enable a cyber-attack. This evaluation explores the attack surface of a representative wind plant, identifying potential methods and vectors that an adversary could leverage to conduct a cyber-attack. Included in this assessment are some recommended mitigations and approaches. Each recommendation requires a full security evaluation, cost/benefit analysis, and risk analysis by each owner and operator.

17 WIND ENERGY↗

NASA NTRS2008

ISS Charging Hazards and Low Earth Orbit Space Weather Effects

Current collection by high voltage solar arrays on the International Space Station (ISS) drives the vehicle to negative floating potentials in the low Earth orbit daytime plasma environment. Pre-flight predictions of ISS floating potentials Phi greater than |-100 V| suggested a risk for degradation of dielectric thermal control coatings on surfaces in the U.S. sector due to arcing and an electrical shock hazard to astronauts during extravehicular activity (EVA). However, hazard studies conducted by the ISS program have demonstrated that the thermal control material degradation risk is effectively mitigated during the lifetime of the ISS vehicle by a sufficiently large ion collection area present on the vehicle to balance current collection by the solar arrays. To date, crew risk during EVA has been mitigated by operating one of two plasma contactors during EVA to control the vehicle potential within Phi less than or equal to |-40 V| with a backup process requiring reorientation of the solar arrays into a configuration which places the current collection surfaces into wake. This operation minimizes current collection by the solar arrays should the plasma contactors fail. This paper presents an analysis of F-region electron density and temperature variations at low and midlatitudes generated by space weather events to determine what range of conditions represent charging threats to ISS. We first use historical ionospheric plasma measurements from spacecraft operating at altitudes relevant to the 51.6 degree inclination ISS orbit to provide an extensive database of F-region plasma conditions over a variety of solar cycle conditions. Then, the statistical results from the historical data are compared to more recent in-situ measurements from the Floating Potential Measurement Unit (FPMU) operating on ISS in a campaign mode since its installation in August, 2006.

Minow, Joseph↗

NASA NTRS2022

Delaware Basin Health and Air Quality: Spatiotemporal Analysis of Air Pollutants Collected from Ground and Space Instruments Around the Guadalupe Mountains and Carlsbad Caverns National Parks

Nitrogen dioxide (NO2) is a precursor for secondary air pollutants, which are associated with decreased visibility, and decreased ecosystem and respiratory health. NO2 is a growing threat to national parks within the Delaware Basin where nearby oil and gas activity contributes to deteriorating park conditions, implying adverse effects on the local tourism economy and public health. To demonstrate spatial and temporal patterns of air pollution in the parks, we examined average monthly, seasonal, and annual tropospheric column concentrations of NO2 in Carlsbad Caverns (CAVE) and Guadalupe Mountain (GUMO) National Parks. We used both the NASA Ozone Monitoring Instrument (OMI) and the European Space Agency (ESA) Tropospheric Monitoring Instrument (TROPOMI) to map NO2 tropospheric column densities. Using ground-based emissions values from the Environmental Protection Agency National Emissions Inventory (NEI) for two nearby natural gas processing plants (Indian Basin Gas Plant, South Carlsbad Plant), we extrapolated monthly trends from these point sources and compared seasonal emissions levels with the measurements recorded by OMI and TROPOMI. The NEI data show an 8% increase in flaring from 2013–2021. OMI measured a 38.3% NO2 increase over the Delaware Basin, 15.29% increase over CAVE, and 4.26% decrease over GUMO from 2011–2018. TROPOMI measured a -1% NO2 change over the Delaware Basin, 3% over CAVE, and 7% over GUMO from 2018–2020. The analysis indicates a positive correlation between emissions from fossil fuel exploration and NO2 concentrations above CAVE and GUMO. This information will inform National Park Service air quality monitoring and policy efforts to ensure compliance with the Clean Air Act.

Sean Cusick↗

DOE OSTI2025

Securing Smart Manufacturing: Detection of Cyber-Physical Attacks in CNC-Based Systems

As Industry 4.0 advances, the integration of computer numerical control (CNC) machines and advanced manufacturing technologies is transforming production into smart manufacturing systems that blend physical and digital processes as cyber-physical systems. However, this increased cyber-physical connectivity exposes manufacturing systems to cyber threats that can cause severe operational and financial disruptions. This paper presents a comparative study on cyber attacks and anomaly detection techniques in manufacturing, focusing on network traffic from CNC machines. The data extracted from network packets includes machine commands and control signals exchanged between the machine's interface and control system, crucial for maintaining operational integrity. We explore two types of cyber attacks, design modification and command injection, which pose substantial risks to CNC machine productivity and system integrity. Our investigation involves experiments on a real CNC system, highlighting the urgent need for effective detection mechanisms. To address these threats, we evaluate three anomaly detection methods: dynamic time warping (DTW), rolling average, and a deep learning, long short-term memory (LSTM) time-series-based autoencoder. Each is assessed for its effectiveness in identifying anomalous behaviors caused by the attacks. Our findings demonstrate the unique strengths and limitations of each detection technique, providing a deeper understanding of their applicability in realworld manufacturing environments. The comparative analysis indicates that while certain methods are highly effective against specific attack types, others offer broader applicability across different attacks. This study contributes to the accurate detection of anomalies in CNC machining processes, thereby enhancing the reliability and security of smart manufacturing systems against diverse cyber threats.

Williams, Bethanie [Tennessee Technological Univer↗

DOE OSTI2022

Precursor Analysis Report: Doppelpaymer Ransomware Attack on Petroleos Mexicanos (PEMEX) 2019

The DoppelPaymer Ransomware Attack on Petroleos Mexicanos (PEMEX) 2019 Precursor Analysis Report leverages publicly available information about the PEMEX cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. The 2019 DoppelPaymer ransomware attack on PEMEX, Mexico’s nationalized petroleum corporation, highlights a unique threat that ransomware and cybercriminal extortion poses to Operational Technology (OT) environments in critical infrastructure. The incident began with an employee downloading commodity malware that allowed adversaries to gain initial access to PEMEX’s enterprise environment. After conducting privilege escalation, tool ingress, and data exfiltration, the adversaries deployed DoppelPaymer ransomware throughout the PEMEX enterprise environment, resulting in the company having to take dozens of systems offline for at least several days. Although PEMEX stated that their operations were not affected, the data exfiltrated from PEMEX was made available for download on DoppelPaymer’s leak site, as well as on other illicit criminal forums. This stolen data included not only company information, but also sensitive OT-specific configuration data. This incident showcases how cybercriminal exfiltration and posting of sensitive OT architecture documentation can pose security concerns for the targeted organization for years due to the long lifespan of OT assets and architectures. Researchers and analysts identified 18 unique techniques utilized during the attack with a total of 190 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Fifteen of the identified techniques used during the DoppelPaymer ransomware attack were precursors to the triggering event. Analysis identified 163 observables associated with these precursor techniques, 34 of which were assessed to have an increased likelihood of being perceived in the 60 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2024

Fatigue performance of the Deeply Embedded Ring Anchor

Existing anchor solutions are limited in their applicability to the floating offshore wind industry, which demands prolonged load endurance in extreme weather conditions and varied seabed soils. This limitation restricts project feasibility and increases costs. In order to address these challenges, the Deeply Embedded Ring Anchor (DERA) is proposed to achieve substantial reductions in anchor costs through efficiency enhancements. Ensuring the long-term safety and reliability of the DERA, especially considering a minimum operational period of 25 years, necessitates a comprehensive understanding of fatigue damage. Induced by repetitive loading below material yield strength, fatigue poses a significant threat to structures exposed to waves and currents. Anchors, vital for station keeping, are susceptible to fatigue damage, particularly in the padeye area. This paper conducts a fatigue analysis, focusing on factors such as the wall thickness of the ring anchor, inner stiffeners, and stiffener thickness, to evaluate the performance of DERA in this context. The results showed that the stiffener significantly affects the elongation of the total life of the anchor. In conclusion, this paper focuses on advancing innovations like DERA, enabling the efficient utilization of offshore wind resources, and addressing safety concerns through meticulous fatigue analysis.

17 WIND ENERGY↗

NASA NTRS2011

Time-Accurate Computational Fluid Dynamics Simulation of a Pair of Moving Solid Rocket Boosters

Since the Columbia accident, the threat to the Shuttle launch vehicle from debris during the liftoff timeframe has been assessed by the Liftoff Debris Team at NASA/MSFC. In addition to engineering methods of analysis, CFD-generated flow fields during the liftoff timeframe have been used in conjunction with 3-DOF debris transport methods to predict the motion of liftoff debris. Early models made use of a quasi-steady flow field approximation with the vehicle positioned at a fixed location relative to the ground; however, a moving overset mesh capability has recently been developed for the Loci/CHEM CFD software which enables higher-fidelity simulation of the Shuttle transient plume startup and liftoff environment. The present work details the simulation of the launch pad and mobile launch platform (MLP) with truncated solid rocket boosters (SRBs) moving in a prescribed liftoff trajectory derived from Shuttle flight measurements. Using Loci/CHEM, time-accurate RANS and hybrid RANS/LES simulations were performed for the timeframe T0+0 to T0+3.5 seconds, which consists of SRB startup to a vehicle altitude of approximately 90 feet above the MLP. Analysis of the transient flowfield focuses on the evolution of the SRB plumes in the MLP plume holes and the flame trench, impingement on the flame deflector, and especially impingment on the MLP deck resulting in upward flow which is a transport mechanism for debris. The results show excellent qualitative agreement with the visual record from past Shuttle flights, and comparisons to pressure measurements in the flame trench and on the MLP provide confidence in these simulation capabilities.

Strutzenberg, Louise L.↗

NASA NTRS1974

Hazard analysis of Clostridium perfringens in the Skylab Food System

The Skylab Food System presented unique microbiological problems because food was warmed in null-gravity and because the heat source was limited to 69.4 C (to prevent boiling in null-gravity). For these reasons, the foods were manufactured using critical control point techniques of quality control coupled with appropriate hazard analyses. One of these hazard analyses evaluated the threat from Clostridium perfringens. Samples of food were inoculated with C. perfringens and incubated for 2 h at temperatures ranging from 25 to 55 C. Generation times were determined for the foods at various temperatures. Results of these tests were evaluated taking into consideration: food-borne disease epidemiology, the Skylab food manufacturing procedures, and the performance requirements of the Skylab Food System. Based on this hazard analysis, a limit for C. perfringens of 100/g was established for Skylab foods.

Bourland, C. T.↗

DOE OSTI2025

Host-specific adaptation in Fusarium oxysporum correlates with distinct accessory chromosome content in human and plant pathogenic strains

ABSTRACT Fusarium oxysporumis a cross-kingdom pathogen. While some strains cause disseminated fusariosis and blinding corneal infections in humans, others are responsible for devastating vascular wilt diseases in plants. To better understand the distinct adaptations ofF. oxysporumto animal or plant hosts, we conducted a comparative phenotypic and genetic analysis of two strains: MRL8996 (isolated from a keratitis patient) and Fol4287 (isolated from a wilted tomato [Solanum lycopersicum]). Infection of mouse corneas and tomato plants revealed that, while both strains cause symptoms in both hosts, MRL8996 caused more severe corneal disease in mice, whereas Fol4287 induced more pronounced wilting symptoms in tomato plants.In vitroassays using abiotic stress treatments revealed that the human pathogen MRL8996 was better adapted to elevated temperatures, whereas the plant pathogen Fol4287 was more tolerant to osmotic and cell wall stresses. Both strains displayed broad resistance to antifungal treatment, with MRL8996 exhibiting the paradoxical effect of increased tolerance to higher concentrations of the antifungal caspofungin. We identified a set of accessory chromosomes (ACs) that encode genes with different functions and have distinct transposon profiles between MRL8996 and Fol4287. Interestingly, ACs from both genomes also encode proteins with shared functions, such as chromatin remodeling and post-translational protein modifications. Our phenotypic assays and comparative genomics analyses lay the foundation for future studies correlating genotypes with phenotype and for developing targeted antifungals for agricultural and clinical uses. IMPORTANCE Fusarium oxysporumis a cross-kingdom fungal pathogen that infects both plants and animals. In addition to causing many devastating wilt diseases, this group of organisms was recently recognized by the World Health Organization as a high-priority threat to human health. Climate change has increased the risk ofFusariuminfections, asFusariumstrains are highly adaptable to changing environments. Deciphering fungal adaptation mechanisms is crucial to developing appropriate control strategies. We performed a comparative analysis ofFusariumstrains using an animal (mouse) and plant (tomato) host andin vitroconditions that mimic abiotic stress. We also performed comparative genomics analyses to highlight the genetic differences between human and plant pathogens and correlate their phenotypic and genotypic variations. We uncovered important functional hubs shared by plant and human pathogens, such as chromatin modification, transcriptional regulation, and signal transduction, which could be used to identify novel antifungal targets.

Microbiology↗

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 NTRS2000

An Investigation of EME as a Potential Cause of Fuel Tank Ignition

NASA researchers were tasked to study the potential for radio signals to excite an aircraft fuel quantity indication system (FQIS) enough to cause arcing, sparking or excessive heating within a fuel tank. Computational techniques were used to determine the threat from external high intensity radiated field (HIRF) transmitters nearby, like shipboard and airborne RADAR systems. Experimental methods were used to determine the threat from Portable Electronic Devices (PEDs) carried aboard by passengers. To support this work, unique electromagnetic coupling measurements were performed on a retired Boeing 747 aircraft, and new test and analysis methods were developed that may be applied to other FQIS designs as well as other aircraft electronic systems.

Ely, Jay J.↗

DOE OSTI2020

HAZARD ANALYSIS OF DIGITAL ENGINEERED SAFETY FEATURES ACTUATION SYSTEM IN ADVANCED NUCLEAR POWER PLANTS USING A REDUNDANCY-GUIDED APPROACH

Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. This paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the triggers of potential single points of failure in the design of digital safety systems in advanced plant designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2010

Upgrade Summer Severe Weather Tool in MIDDS

The goal of this task was to upgrade the severe weather database from the previous phase by adding weather observations from the years 2004 - 2009, re-analyze the data to determine the important parameters, make adjustments to the index weights depending on the analysis results, and update the MIDDS GUI. The added data increased the period of record from 15 to 21 years. Data sources included local forecast rules, archived sounding data, surface and upper air maps, and two severe weather event databases covering east-central Florida. Four of the stability indices showed increased severe weather predication. The Total Threat Score (TTS) of the previous work was verified for the warm season of 2009 with very good skill. The TTS Probability of Detection (POD) was 88% and the False alarm rate (FAR) of 8%. Based on the results of the analyses, the MIDDS Severe Weather Worksheet GUI was updated to assist the duty forecaster by providing a level of objective guidance based on the analysis of the stability parameters and synoptic-scale dynamics.

Wheeler, Mark M.↗