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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5

A Simulation Based Approach for Contingency Planning for Aircraft Turnaround Operation System Activities in Airline Hubs

Commercial aircraft undergo a significant number of maintenance and logistical activities during the turnaround operation at the departure gate. By analyzing the sequencing of these activities, more effective turnaround contingency plans may be developed for logistical and maintenance disruptions. Turnaround contingency plans are particularly important as any kind of delay in a hub based system may cascade into further delays with subsequent connections. The contingency sequencing of the maintenance and logistical turnaround activities were analyzed using a combined network and computer simulation modeling approach. Experimental analysis of both current and alternative policies provides a framework to aid in more effective tactical decision making.

Adeleye, Sanya↗

Contingency Management Requirements Document: Preliminary Version. Revision F

This is the High Altitude, Long Endurance (HALE) Remotely Operated Aircraft (ROA) Contingency Management (CM) Functional Requirements document. This document applies to HALE ROA operating within the National Airspace System (NAS) limited at this time to enroute operations above 43,000 feet (defined as Step 1 of the Access 5 project, sponsored by the National Aeronautics and Space Administration). A contingency is an unforeseen event requiring a response. The unforeseen event may be an emergency, an incident, a deviation, or an observation. Contingency Management (CM) is the process of evaluating the event, deciding on the proper course of action (a plan), and successfully executing the plan.

Source record↗

Suited Contingency Ops Food - 2

The contingency scenario for an emergency cabin depressurization event may require crewmembers to subsist in a pressurized suit for up to 144 hours. This scenario requires the capability for safe nutrition delivery through a helmet feed port against a 4 psi pressure differential to enable crewmembers to maintain strength and cognition to perform critical tasks. Two nutritional delivery prototypes were developed and analyzed for compatibility with the helmet feed port interface and for operational effectiveness against the pressure differential. The bag-in-bag (BiB) prototype, designed to equalize the suit pressure with the beverage pouch and enable a crewmember to drink normally, delivered water successfully to three different subjects in suits pressurized to 4 psi. The Boa restrainer pouch, designed to provide mechanical leverage to overcome the pressure differential, did not operate sufficiently. Guidelines were developed and compiled for contingency beverages that provide macro-nutritional requirements, a minimum one-year shelf life, and compatibility with the delivery hardware. Evaluation results and food product parameters have the potential to be used to improve future prototype designs and develop complete nutritional beverages for contingency events. These feeding capabilities would have additional use on extended surface mission EVAs, where the current in-suit drinking device may be insufficient.

Glass, J. W.↗

LADEE Preparations for Contingency Operations for the Lunar Orbit Insertion Maneuver

The Lunar Atmosphere and Dust Environment Explorer (LADEE) spacecraft was launched on September 6, 2013, and completed its mission on April 17, 2014 with a directed impact to the Lunar Surface. Its primary goals were to examine the lunar atmosphere, measure lunar dust, and to demonstrate high rate laser communications. The LADEE mission was a resounding success, achieving all mission objectives, much of which can be attributed to careful planning and preparation. This paper discusses the specific preparations for fault conditions that could occur during a highly-critical phase of the mission. To get to the Moon, the spacecraft traversed multiple phasing loops around the Earth, and then executed a breaking maneuver to achieve lunar orbit. This Lunar Orbit Insertion (LOI) maneuver was perhaps the most time-critical phase of the entire mission. The LOI maneuver had to occur within a twenty minute window in order to achieve lunar orbit with an acceptable amount of propellant remaining. Missing this window would have likely resulted in a loss of the entire mission. An additional challenge of the maneuver was that spacecraft was out of view for approximately one hour prior to the main thruster burn, with the burn needing to occur within five minutes after coming into view. These conditions resulted in unique challenges for ground operations and the fault management system. Early in the planning stages of the mission, the criticality and challenges of this maneuver were evident to the system designers. The major concern was that any triggering of the on-board fault management system, whether it is in response to a true fault or a false positive, would result in an unacceptable delay to the burn. Therefore the flight software was designed with a flexible fault management system, such that any or all of the fault management responses could be disabled for the lead up and execution of the maneuver. Later, a triage was conducted to develop a list of fault responses, mapped to various parts of the timeline of the maneuver. Some of these contingency responses were solely ground-based if the time to detect, diagnose, and respond were adequate. Other responses were automated on-board if the response time from the ground would have been inadequate. For instance, in order to recover from a system reboot, on-board automation would have automatically reconfigured the spacecraft for the burn and reoriented the spacecraft to the burn attitude.These contingency responses were practiced, over and over, during numerous rehearsals. Although the LOI maneuver was executed without having to use any of these contingencies, the LADEE team was adequately prepared for this highly critical phase of the mission.

Cannon, Howard↗

Model-based System Health Management and Contingency Planning for Autonomous UAS

Safe autonomous operations of an Unmanned Aerial System (UAS) requires that the UAS can react to unforeseen circumstances, for example, after a failure has occurred. In this paper we describe a model-based run-time architecture for autonomous on-board diagnosis, system health management, and contingency management. This architecture is being instantiated on top of NASA's Core Flight System (cFS/cFE) as amajor component of the on-board AutonomousOperating System (AOS). We will describe our diagnosis and monitoring components, which continuously provide system health status. Automated reasoning with constraint satisfaction form the core of our decision-making component, which assesses the current situation, aids in failure disambiguation, and constructs a contingency plan to mitigate the failure(s) and allow for a safe end of the mission. We will illustrate our contingency management system with two case studies, one for a fixed-wing aircraft in simulation, and one for an autonomous DJI S1000+ octo-copter.

Schumann, Johann M.↗

Assured Contingency Landing Management for Advanced Air Mobility

Advanced Air Mobility (AAM) is quickly developing as a new air transportation system that moves people and packages in the regions previously not / less served by the current aviation systems. Such AAM must operate safely despite the potential to encounter hazards and experience anomalies and failures in-flight. It becomes especially important to have systematic auto-mitigation strategies to perform safe contingency actions in AAM flight operations, as pilots have limited Situational Awareness (SA) and limited time to make prompt decisions when encountering failures/anomalies in high-density low altitude airspace. This paper presents Assured Contingency Landing Management (ACLM) with an online landing strategy selection to decide between the following three options when a contingency landing is required: (1) Return-to-launch landing site, (2) Land immediately at a nearby clear but unprepared site, (3) Land at a prepared landing site from the approximate footprint. Our presented algorithm shows a real-time auto-mitigation loop with multiple threads that run simultaneously to check controllability, reachability, and intermediate decisions to hold/ loiter or continue the flight plan as the landing strategy solution is being computed. Case study simulation is demonstrated with the safety-critical propulsion system and battery system and shows how different failure scenarios impact the landing strategy selection.

Autonomous Mitigation↗

Data Augmentation for Intelligent Contingency Management Using Generative Adversarial Neural Networks

Artificial intelligence (AI)-based techniques for intelligent contingency management (ICM) require that intelligent agents learn various aspects of system dynamics to create and execute contingencies. For high assurance contingency management, agents achieve the most compelling results through supervised or semi-supervised machine learning, for which agents require large datasets to learn the dynamics of the system. Unfortunately, data collection in aerospace applications can be costly, due to both time and resources. Presented work describes a framework for data augmentation of ICM databases containing training data for machine learning models. This framework populates the database with the outputs of generative adversarial network (GAN) models that were trained on flight data. Methods for evaluating the suitability of these models based on the equations of motion, as well as other physical constraints, are discussed. The paper demonstrates the utility of this database for training intelligent agents on the NASA T2 generic transport aircraft model and experimental vertical takeoff and landing (VTOL) simulation model.

Generative Machine Learning↗

Data Augmentation for Intelligent Contingency Management Using Generative Adversarial Neural Networks

Artificial intelligence (AI)-based techniques for intelligent contingency management (ICM) require that intelligent agents learn various aspects of system dynamics to create and execute contingencies. For high assurance contingency management, agents achieve the most compelling results through supervised or semi-supervised machine learning, for which agents require large datasets to learn the dynamics of the system. Unfortunately, data collection in aerospace applications can be costly, due to both time and resources. Presented work describes a framework for data augmentation of ICM databases containing training data for machine learning models. This framework populates the database with the outputs of generative adversarial network (GAN) models that were trained on flight data. Methods for evaluating the suitability of these models based on the equations of motion, as well as other physical constraints, are discussed. The paper demonstrates the utility of this database for training intelligent agents on the NASA T2 generic transport aircraft model and experimental vertical takeoff and landing (VTOL) simulation model.

Generative Machine Learning↗

Effect of Carbon Dioxide Exposure on Physical and Cognitive Performance in A Simulated Spaceflight Contingency Scenario

INTRODUCTION: Carbon dioxide (CO2) produced by astronauts inside space suits can accumulate to levels that may affect health and performance. The human health and performance risks associated with different levels of CO2 exposure in the flight environment remain an area of debate. The purpose of this study is to characterize the limit of acceptable performance (cognitive and physical) decrements and symptom severity for mission operations when subjected to elevated inspired CO2 levels in simulated contingency lunar extravehicular activity (EVA) scenarios. METHODS: This study will create a simulation of a 1-hour, ~2km contingency EVA walk back to a habitat, incorporating a passive treadmill and a fully immersive virtual reality (VR) simulation of a lunar EVA environment. Subjects will be asked to walk on a treadmill while breathing partial pressures of CO2 of 0, 5, 10, 15, 20, 25, 30mmHg for 1 hour at a time. Cognitive performance will be quantified using validated cognitive tests and measures of functional task performance embedded within the VR environment. Test subject symptoms and self-assessment of performance will be evaluated via survey. RESULTS: This study currently has approval from NASA’s Institutional Review Board and has completed the Test Readiness Review process. Next steps for this research study include test subject recruitment, data collection, and analysis. Data collection is planned for calendar year 2023 and 2024. DISCUSSION: This study will provide valuable information regarding how various partial pressures of CO2 exposure impact acute health, as well as cognitive and physical performance during simulated contingency lunar EVA. This information will enable assessment of health and performance risk associated with spacesuit systems and operations concepts for future exploration missions as well as informing definition of future standards and requirements.

D. M. Nusbaum↗

Topological Machine Learning Methods for Power System Responses to Contingencies: Preprint

While deep learning tools, coupled with the emerging machinery of topological data analysis, are proven to deliver various performance gains in a broad range of applications, from image classification to biosurveillance to blockchain fraud detection, their utility in areas of high societal importance such as power system modeling and, particularly, resilience quantification in the energy sector yet remain untapped. To provide fast acting synthetic regulation and contingency reserve services to the grid while having minimal disruptions on customer quality of service, we propose a new topologybased system that depends on neural network architecture for impact metrics classification and prediction in power systems. This novel topology-based system allows one to evaluate the impact of three power system contingency types, namely, in conjunction with transmission lines, transformers, and transmission lines combined with transformers. We show that the proposed new neural network architecture equipped with local topological measures facilitates both more accurate classification of unserved load as well as the amount of unserved load. In addition, we are able to learn complex relationships between electrical properties and local topological measurements on the simulated response to contingencies for NREL-SIIP power system.

graph theory↗

Reducing Contingency through Sampling at the Luckey FUSRAP Site - 13186

Typically, the greatest risk in developing accurate cost estimates for the remediation of hazardous, toxic, and radioactive waste sites is the uncertainty in the estimated volume of contaminated media requiring remediation. Efforts to address this risk in the remediation cost estimate can result in large cost contingencies that are often considered unacceptable when budgeting for site cleanups. Such was the case for the Luckey Formerly Utilized Sites Remedial Action Program (FUSRAP) site near Luckey, Ohio, which had significant uncertainty surrounding the estimated volume of site soils contaminated with radium, uranium, thorium, beryllium, and lead. Funding provided by the American Recovery and Reinvestment Act (ARRA) allowed the U.S. Army Corps of Engineers (USACE) to conduct additional environmental sampling and analysis at the Luckey Site between November 2009 and April 2010, with the objective to further delineate the horizontal and vertical extent of contaminated soils in order to reduce the uncertainty in the soil volume estimate. Investigative work included radiological, geophysical, and topographic field surveys, subsurface borings, and soil sampling. Results from the investigative sampling were used in conjunction with Argonne National Laboratory's Bayesian Approaches for Adaptive Spatial Sampling (BAASS) software to update the contaminated soil volume estimate for the site. This updated volume estimate was then used to update the project cost-to-complete estimate using the USACE Cost and Schedule Risk Analysis process, which develops cost contingencies based on project risks. An investment of $1.1 M of ARRA funds for additional investigative work resulted in a reduction of 135,000 in-situ cubic meters (177,000 in-situ cubic yards) in the estimated base volume estimate. This refinement of the estimated soil volume resulted in a $64.3 M reduction in the estimated project cost-to-complete, through a reduction in the uncertainty in the contaminated soil volume estimate and the associated contingency costs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Contingencies in Decommissioning Cost Evaluations - Panel Session 24

Contingency costs apply to unforeseen, uncertain and unpredictable conditions, typically encountered during the decommissioning activities (known unknowns). Outside spent fuel management, the dismantling activities in the controlled area constitute the largest contributor to project risk and decommissioning cost. Using data from previous proven experience on site help minimize the contingencies and provide more accurate cost estimates. Technology improvement leads to cost and contingency reduction.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

UK regulatory review of the double contingency principle in criticality safety - 14379

The UK's regulatory regime is based on Licence Conditions (LCs) attached to a Nuclear Site Licence (NSL) and is non-prescriptive in nature. The law requires licensees to reduce health and safety risks to workers and the public 'so far as is reasonability practicable' (SFAIRP), and this framework provides licensees with flexibility to achieve this. Guidance for inspectors on the assessment of nuclear safety cases has been published in Office for Nuclear Regulation's (ONR) Safety Assessment Principles (SAPs) and supporting Technical Assessment Guides (TAGs). These guidance documents have recently been reviewed in the light of the Fukushima accident. The opportunity has also been taken to reconsider the use of the Double Contingency Principle used in criticality safety cases, an approach commonly regarded as the preferred means of criticality control internationally and featured in the SAPs and TAGs. Licensees in the UK have adopted several approaches in nuclear criticality safety cases based upon a combination of deterministic and probabilistic safety cases using the Double Contingency Principle and Design Basis Analysis. ONR has developed a targeted intervention to sample a number of nuclear safety cases in order to test the adequacy of methodologies used to secure nuclear criticality safety. This paper reports the results of this intervention and considers the need to review the advice currently given by the UK nuclear regulator, including on use of the Double Contingency Principle. (authors)

42 ENGINEERING↗

Smart Sampling and HPC-based Probabilistic Look-ahead Contingency Analysis Implementation and its Evaluation with Real-world Data

This paper describes a probabilistic look-ahead contingency analysis application that incorporates smart sampling and high-performance computing (HPC) techniques. Smart sampling techniques are implemented to effectively represent the structure and statistical characteristics of uncertainty introduced by different sources in the power system. They can significantly reduce the data set size required for multiple look-ahead contingency analyses, and therefore reduce the time required to compute them. High-performance-computing (HPC) techniques are used to further reduce computational time. These two techniques enable a predictive capability that forecasts the impact of various uncertainties on potential transmission limit violations. The developed package has been tested with real world data from the Bonneville Power Administration. Case study results are presented to demonstrate the performance of the applications developed.

high performance computing↗

Dynamic Contingency Analysis Tool 2.0 User Manual with Test System Examples

This document introduces Version 2 of the Dynamic Contingency Analysis Tool (DCAT) software package developed by Pacific Northwest National Laboratory and serves as a guide for using this package to conduct cascading failure simulations for the electric power system. The DCAT is an open-platform and publicly available software; it is intended to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will support finding mitigating actions to reduce the risk of cascading outages in technically sound and effective ways. This manual provides detailed instructions on how to use this tool on multicore Windows workstations or servers. In the public version of DCAT, several improvements have been made over the previous version: (1) it was modularized; (2) a graphical user interface (GUI) was developed; (3) a new version of the MPjobs parallel processing module was incorporated; and (4) a batch-processing function was added. The features of the DCAT GUI are described, including some examples of how to use the GUI to perform simulations. A full explanation of the DCAT methodology is available in the Phase 1 report.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Contingency Software in Autonomous Systems: Technical Level Briefing

Contingency management is essential to the robust operation of complex systems such as spacecraft and Unpiloted Aerial Vehicles (UAVs). Automatic contingency handling allows a faster response to unsafe scenarios with reduced human intervention on low-cost and extended missions. Results, applied to the Autonomous Rotorcraft Project and Mars Science Lab, pave the way to more resilient autonomous systems.

autonomous systems↗

UAS Contingency Management: The Effect of Different Procedures on ATC in Civil Airspace Operations

Current study examined the impact of four, currently-employed, unmanned aerial system (UAS) contingency procedures on air traffic controller (ATC) workload and performance. Controllers managed a Terminal Radar Approach Control (TRACON) sector while a single UAS passed through their sector. In four of the five scenarios, the UAS was scripted to experience an emergency (e.g., loss of command and control link, sudden drop in oil pressure) and then execute one of four possible contingency maneuvers. The fifth scenario was a baseline and contained no emergency. Results showed no significant differences in performance or workload among the four the study's design discussed.

Contingency Management↗

Effect of Carbon Dioxide Exposure on Physical and Cognitive Performance in a Simulated Spaceflight Contingency Scenario

Introduction: Carbon dioxide (CO2) produced by astronauts inside space suits can accumulate to levels that affect health and performance. The human health and performance risks associated with different levels of CO2 exposure in the flight environment remain an area of debate. The purpose of this study is to characterize the limit of acceptable performance (cognitive and physical) decrements and symptom severity for mission operations when subjected to elevated inspired CO2 levels in the spacesuit during contingency EVA scenarios. Methods: This study will create a simulation of a 1-hour contingency EVA walk back to the habitat, incorporating a passive treadmill and a fully immersive virtual reality (VR) simulation of a lunar EVA. Subjects will be asked to walk on a treadmill while breathing partial pressures of CO2 of 0, 5, 10, 15, 20, 25, 30mmHg for 1 hour at a time. Cognitive performance will be quantified using validated cognitive tests and measures of functional task performance embedded within the VR environment. Test subject symptoms and self-assessment of performance will be evaluated via survey. Results: This study currently has approval from NASA’s Institutional Review Board and has completed the Test Readiness Review process. Next steps for this research study include test subject recruitment, data collection, and analysis. Data collection is planned for calendar year 2022 and 2023. Discussion: This study will provide valuable information regarding how various partial pressures of CO2 exposure impact acute health, as well as cognitive and physical performance during simulated lunar EVA. This information will be vital in the assessment of overall risk associated with current hardware (vehicle and suit) design for upcoming exploration missions. It will also be invaluable for informing future standards and requirements.

carbon dioxide↗