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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Spaceflight Decompression Sickness Contingency Plan

A viewgraph presentation on the Decompression Sickness (DCS) Contingency Plan for manned spaceflight is shown. The topics include: 1) Approach; 2) DCS Contingency Plan Overview; 3) Extravehicular Activity (EVA) Cuff Classifications; 4) On-orbit Treatment Philosophy; 5) Long Form Malfunction Procedure (MAL); 6) Medical Checklist; 7) Flight Rules; 8) Crew Training; 9) Flight Surgeon / Biomedical Engineer (BME) Training; and 10) DCS Emergency Landing Site.

Dervay, Joseph P.↗
NASA NTRS2007

Genesis Contingency Planning and Mishap Recovery: The Sample Curation View

Planning for sample preservation and curation was part of mission design from the beginning. One of the scientific objectives for Genesis included collecting samples of three regimes of the solar wind in addition to collecting bulk solar wind during the mission. Collectors were fabricated in different thicknesses for each regime of the solar wind and attached to separate frames exposed to the solar wind during specific periods of solar activity associated with each regime. The original plan to determine the solar regime sampled for specific collectors was to identify to which frame the collector was attached. However, the collectors were dislodged during the hard landing making identification by frame attachment impossible. Because regimes were also identified by thickness of the collector, the regime sampled is identified by measuring fragment thickness. A variety of collector materials and thin films applied to substrates were selected and qualified for flight. This diversity provided elemental measurement in more than one material, mitigating effects of diffusion rates and/or radiation damage. It also mitigated against different material and substrate strengths resulting in differing effects of the hard landing. For example, silicon crystal substrates broke into smaller fragments than sapphire-based substrates and diamond surfaces were more resilient to flying debris damage than gold. The primary responsibility of the curation team for recovery was process documentation. Contingency planning for the recovery phase expanded this responsibility to include not only equipment to document, but also gather, contain and identify samples from the landing area and the recovered spacecraft. The team developed contingency plans for various scenarios as part of mission planning that included topographic maps to aid in site recovery and identification of different modes of transport and purge capability depending on damage. A clean tent, set-up at Utah Test & Training Range to control the environment for processing the sample return capsule and cleanly installing a nitrogen purge to the canister, was used to control the environment for extracting collector fragments from the damaged canister and to document and package over 10,000 collector fragments.

Stansbery, E. K.↗
NASA NTRS2007

Contingency Support Simulation for the Tracking and Data Relay Satellite System (TDRSS)

In March 2006, the Tracking and Data Relay Satellite (TDRS)-3 experienced an unexpected thrusting event, which caused significant changes to its orbit. Recovery from this anomaly was protracted, raising concerns during the Independent Review Team (IRT) investigation of the anomaly regarding the contingency response readiness. The simulations and readiness exercises discussed in this paper were part of the response to the IRT concerns. This paper explains the various levels of simulation needed to enhance the proficiency of the Flight Dynamics Facility (FDF) and supporting elements in recovery from a TDRS contingency situation. The main emergency to address is when a TDRS has experienced uncommanded, unreported, or misreported thrusting, causing a ground station to lose the ability to acquire the spacecraft, as happened in 2006. The following levels of simulation are proposed: 1) Tests that would be performed by the individual support sites to verify that internal procedures and tools are in place and up to date; 2) Tabletop simulations that would involve all of the key support sites talking through their respective operating procedures to ensure that proper notifications are made and communications links are established; and 3) Comprehensive simulations that would be infrequent, but realistic, involving data exchanges between ground sites and voice and electronic communications among the supporting elements.

Dykes, Andy↗
NASA NTRS2010

Development of a Contingency Capillary Wastewater Management Device

The Personal Body .Attached Liquid Liquidator (PBALL) is conceived as a passive, capillary driven contingency wastewater disposal device. In this contingency scenario, the airflow system on the NASA Crew Exploration Vehicle (CEV) is assumed to have failed, leaving only passive hardware and vacuum vent to dispose of the wastewater. To meet these needs, the PBALL was conceived to rely on capillary action and urine wetting design considerations. The PBALL is designed to accommodate a range of wetting conditions, from 0deg < (theta)adv approx. 90deg, be adaptable for both male and female use, collect and retain up to a liter of urine, minimize splash-back, and allow continuous drain of the wastewater to vacuum while minimizing cabin air loss. A sub-scale PBALL test article was demonstrated on NASA's reduced gravity aircraft in April, 2010.

Thomas, Evan A.↗
NASA NTRS2010

NASA Contingency Shuttle Crew Support (CSCS) Medical Operations

The genesis of the space shuttle began in the 1930's when Eugene Sanger came up with the idea of a recyclable rocket plane that could carry a crew of people. The very first Shuttle to enter space was the Shuttle "Columbia" which launched on April 12 of 1981. Not only was "Columbia" the first Shuttle to be launched, but was also the first to utilize solid fuel rockets for U.S. manned flight. The primary objectives given to "Columbia" were to check out the overall Shuttle system, accomplish a safe ascent into orbit, and to return back to earth for a safe landing. Subsequent to its first flight Columbia flew 27 more missions but on February 1st, 2003 after a highly successful 16 day mission, the Columbia, STS-107 mission, ended in tragedy. With all Shuttle flight successes come failures such as the fatal in-flight accident of STS 107. As a result of the STS 107 accident, and other close-calls, the NASA Space Shuttle Program developed contingency procedures for a rescue mission by another Shuttle if an on-orbit repair was not possible. A rescue mission would be considered for a situation where a Shuttle and the crew were not in immediate danger, but, was unable to return to Earth or land safely. For Shuttle missions to the International Space Station (ISS), plans were developed so the Shuttle crew would remain on board ISS for an extended period of time until rescued by a "rescue" Shuttle. The damaged Shuttle would subsequently be de-orbited unmanned. During the period when the ISS Crew and Shuttle crew are on board simultaneously multiple issues would need to be worked including, but not limited to: crew diet, exercise, psychological support, workload, and ground contingency support

Adams, Adrien↗
NASA NTRS2012

An Examination of Coarse Sun Sensor Contingencies in Attitude Determination and the Sun Vector Calculation

Satellite pointing is vital to the success of a mission. One element of that entails describing the position of the sun relative to the frame of the satellite. Coarse Sun Sensors (CSS) are typically used to provide the information to calculate the sun's position in Safe Modes or contingency operations. In the OCO-2 configuration there are 13 CSS total, which provide redundant 4 celestial coverage. Failures of the individual CSS elements can introduce holes in the celestial coverage resulting in potential loss of sun knowledge. These failures must be analyzed to determine if the contingency plan is sufficient to assure mission success. First the static case was looked at and determined that at a maximum, 3 CSS failures can be sustained on the body and 1 on the array without causing coverage holes. Also array sensors are more important to mission success. The Sun Vector calculation has been transcribed to MATLAB code and failure scenarios are being examined to determine the maximum error given a set of failure scenarios. This activity indicated that if there is a loss of the sun, the sun-searching algorithm could be modified to use XZ rotation as that is guaranteed to find it whereas the design using the YZ rotation misses the sun if it is at the + or - Y orientation.

celestial bodies↗
NASA NTRS2016

Experiences with Extra-Vehicular Activities in Response to Critical ISS Contingencies

The maturation of the International Space Station (ISS) design from the proposed Space Station Freedom to today's current implementation resulted in external hardware redundancy vulnerabilities in the final design. Failure to compensate for or respond to these vulnerabilities could put the ISS in a posture to where it could no longer function as a habitable space station. In the first years of ISS assembly, these responses were to largely be addressed by the continued resupply and Extra-Vehicular Activity (EVA) capabilities of the Space Shuttle. Even prior to the decision to retire the Space Shuttle, it was realized that ISS needed to have its own capability to be able to rapidly repair or replace external hardware without needing to wait for the next cargo resupply mission. As documented in a previous publicatoin5, in 2006 development was started to baseline Extra- Vehicular Activity (EVA, or spacewalk) procedures to replace hardware components whose failure would expose some of the ISS vulnerabilities should a second failure occur. This development work laid the groundwork for the onboard crews and the ground operations and engineering teams to be ready to replace any of this failed hardware. In 2010, this development work was put to the test when one of these pieces of hardware failed. This paper will provide a brief summary of the planning and processes established in the original Contingency EVA development phase. It will then review how those plans and processes were implemented in 2010, highlighting what went well as well as where there were deficiencies between theory and reality. This paper will show that the original approach and analyses, though sound, were not as thorough as they should have been in the realm of planning for next worse failures, for documenting Programmatic approval of key assumptions, and not pursuing sufficient engineering analysis prior to the failure of the hardware. The paper will further highlight the changes made to the Contingency EVA preparation team structure, approach, goals, and the resources allocated to its work after the 2010 events. Finally, the authors will overview the implementation of these updates in addressing failures onboard the ISS in 2012, 2013, and 2014. The successful use of the updated approaches, and the application of the approaches to other spacewalks, will demonstrate the effectiveness of this additional work and make a case for putting significant time and resources into pre-failure planning and analysis for critical hardware items on human-tended spacecraft.

Van Cise, E. A.↗
NASA NTRS2016

Experiences with Extra-Vehicular Activities in Response to Critical ISS Contingencies

The maturation of the International Space Station (ISS) design from the proposed Space Station Freedom to today's current implementation resulted in external hardware redundancy vulnerabilities in the final design. Failure to compensate for or respond to these vulnerabilities could put the ISS in a posture where it could no longer function as a habitable space station. In the first years of ISS assembly, these responses were to largely be addressed by the continued resupply and Extra-Vehicular Activity (EVA) capabilities of the Space Shuttle. Even prior to the decision to retire the Space Shuttle, it was realized that ISS needed to have its own capability to be able to rapidly repair or replace external hardware without needing to wait for the next cargo resupply mission. As documented in a previous publication, in 2006 development was started to baseline Extra-Vehicular Activity (EVA, or spacewalk) procedures to replace hardware components whose failure would expose some of the ISS vulnerabilities should a second failure occur. This development work laid the groundwork for the onboard crews and the ground operations and engineering teams to be ready to replace any of this failed hardware. In 2010, this development work was put to the test when one of these pieces of hardware failed. This paper will provide a brief summary of the planning and processes established in the original Contingency EVA development phase. It will then review how those plans and processes were implemented in 2010, highlighting what went well as well as where there were deficiencies between theory and reality. This paper will show that the original approach and analyses, though sound, were not as thorough as they should have been in the realm of planning for next worse failures, for documenting Programmatic approval of key assumptions, and not pursuing sufficient engineering analysis prior to the failure of the hardware. The paper will further highlight the changes made to the Contingency EVA preparation team structure, approach, goals, and the resources allocated to its work after the 2010 events. Finally, the authors will overview the implementation of these updates in addressing failures onboard the ISS in 2012, 2013, and 2014. The successful use of the updated approaches, and the application of the approaches to other spacewalks, will demonstrate the effectiveness of this additional work and make a case for putting significant time and resources into pre-failure planning and analysis for critical hardware items on human-tended spacecraft.

Van Cise, E. A.↗
NASA NTRS2019

Mid-Course Correction Contingency Analysis for the James Webb Space Telescope

This investigation details two analyses performed as part of an early orbit contingency operations study related to the James Webb Space Telescope’s limited ability to maneuver in a sunward direction. First, contingency planning developed by the Flight Dynamics Team and shared with the Science and Operations Center to quickly assess the available timeline in the event of a delayed mid-course correction maneuver is presented. Second, the methods for recovering from a maneuver over-burn using observatory geometry to exploit the solar radiation pressure perturbation contributions from the large sunshield as well as adjusting the maneuver campaign to recover the observatory are examined.

JWST↗
NASA NTRSDate not supplied

Community Benchmark Problem for Intelligent Contingency Management

This paper introduces a Community Benchmark Problem (CBP) for Intelligent Contingency Management (ICM) for Urban Air Mobility (UAM) aircraft. The CBP aims to provide a common framework for measuring and comparing the progress of autonomy solutions for UAM aircraft in handling emergency situations. The paper proposes a methodology for defining and quantifying five measures of complexity that capture the challenges and requirements of ICM for UAM: Mission, Environmental, Autonomy, Decision-Making, and Mission Fault. In addition, it proposes a methodology for defining and quantifying mission risk acceptability with the same goals: Contingency Management, Mission Success, Operational, Mission Redefinition, and Environmental. We describe how to use these measures to track progress of the development of ICM capability, as well as to create scenarios and evaluate the performance of different autonomy solutions.

autonomy↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learning↗
DOE OSTI2020

Data Requirements for Application of Risk-Based Dynamic Contingency Analysis to Evaluate Hurricane Impact to Electrical Infrastructure in Puerto Rico

This paper presents a risk-based dynamic contingency analysis framework that was used to evaluate the hurricane impact to electrical infrastructure in Puerto Rico. PNNL developed a scalable risk-based framework for identifying high-voltage transmission resilience improvements by classifying and prioritizing high-risk power grid contingencies (system failures) under hurricane impact. The risk-based framework is founded on grid outage definitions with their associated probabilities of occurrence from hurricane events, in combination with an impact assessment derived from detailed dynamic cascading failure analysis. This paper focuses on a discussion around data requirements for transmission resilience planning for hurricane events, derived from the development of the risk-based framework and its application to Puerto Rico. This paper launches an important first step in encouraging the engineering community and power system industry to move towards establishing resilience planning as a routine practice. Since actual results for Puerto Rico contain sensitive information, sample simulation results will be used to illustrate the data requirements and risk-based dynamic cascading framework on the Puerto Rico power grid, as well as demonstrate the potential for such a simulation framework. The paper includes a discussion on the lessons learned, importance and need for improved datasets that are not usually considered in traditional power system planning. The paper will also elaborate on how the scalable simulation framework and datasets might be expanded to larger footprints and leveraged for modelling other types of natural disasters.

DCAT, Puerto Rico, hurricane, Power System Stabili↗
DOE OSTI2022

Natural gas maximal load delivery for multi-contingency analysis

An increasing dependence on natural gas has amplified existing vulnerabilities to the power grid, including disruptions to gas transmission networks from natural and man-made disasters. To address the operational challenges arising from these disruptions, we, in this study, consider the problem of estimating the steady-state operating capacity of a damaged gas pipeline network while ensuring the maximal delivery of load. Specifically, we formulate the mixed-integer nonconvex maximal load delivery (MLD) problem, which proves difficult to solve on large-scale networks. To address this challenge, we present a relaxation of the MLD problem and use it to determine bounds on the transport capacity of a gas pipeline system. A rigorous computational evaluation over network models ranging in size from 11 to 4,197 junctions shows that the relaxation-based method is suitable for analyzing the impacts of multi-contingency network disruptions, often converging to the optimal solution of the relaxation in less than ten seconds.

03 NATURAL GAS↗
DOE OSTI2022

Wash Vehicle Fleet Sizing for Contingency Planning Against Dust Storms

Wash vehicles containing either high- or low-pressure water sprayers, a collection of rotating brushes, or a combination of these, are frequently utilized in concentrating solar power (CSP) plants to maintain a high level of optical efficiency in the solar field. In recent years, multiple modeling approaches have been developed to obtain fleet sizes and mirror-washing schedules that optimize the tradeoff of vehicle capital and use costs and labor versus lost revenues due to soiling. These planning models cover normal operating conditions well but do not consider rare events such as dust storms which can cause a significant reduction in receiver productivity, or shut down operations until most or all of the solar field's mirrors have been cleaned. To that end, we propose a methodology that evaluates whether additional capital should be deployed to hedge against these events by weighing the net present value of the expected benefits against the capital costs. The output of this method is a breakeven frequency, a metric we sue to determine whether an additional vehicle should be purchased to address the contingency of dust storms by comparing it to the expected annual storm frequency We develop a small collection of case studies using commercial-scale CSP tower plants and obtain breakeven frequencies that mostly fall between 0.1 and 1.0 storms per year, depending on the existing fleet size and storm severity.

concentrating solar power↗
DOE OSTI2019

The allocation of a variable series reactor considering AC constraints and contingencies

The Variable Series Reactors (VSRs) can efficiently control the power flow through the adjustment of the line reactance. When they are appropriately allocated in the power network, the transmission congestion and generation cost can be reduced. Our work proposes a planning model to optimally allocate VSRs considering AC constraints and multi-scenarios including base case and contingencies. The planning model is originally a non-convex large scale mixed integer nonlinear program (MINLP), which is generally intractable. The proposed Benders approach decomposes the MINLP model into a mixed integer linear program (MILP) master problem and a number of nonlinear subproblems. Numerical case studies based on IEEE 118-bus demonstrate the high performance of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Methodology for Evaluating Operator Usage of Machine Learning Recommendations for Power Grid Contingency Analysis

This work presents the application of a methodology to measure domain expert trust and workload, elicit feedback, and understand the technological usability and impact when a machine learning assistant is introduced into contingency analysis for real-time power grid simulation. The goal of this framework is to rapidly collect and analyze a broad variety of human factors data in order to accelerate the development and evaluation loop for deploying machine learning applications. We describe our methodology and analysis, and we discuss insights gained from a pilot participant about the current usability state of an early technology readiness level (TRL) artificial neural network (ANN) recommender.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗