SEARCH · Engineering Papers

Results for “Contingency planning”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19

All sources NASA NTRS DOE OSTI

DOE OSTI2022

A Multi-Model Framework for Assessing Long- and Short-Term Climate Influences on the Electric Grid

Climate change influences many aspects of the electric grid, but prior work and industry practices often ignore the potential effects of changing climate, or they only consider a single effect or individual effects in isolation. Challenges vary with each grid and include adapting to long-term trends such as changing temperature and precipitation or shorter-term events such as drought or storms that could increase in frequency or intensity. Here we present a multi-model framework designed to analyze the effects of long and short-term climate impacts in combination. This framework couples capacity expansion and production cost models with hydrologic models and future climate scenario data to analyze alternative climate and energy futures at high spatial, temporal, and process resolutions. Furthermore, we constructed and evaluated the results of a suite of simulated scenarios exploring climate impacts on capacity investment and stress-tested the resulting future infrastructures using hourly dispatch modeling under alternative drought and load conditions. We demonstrate the approach through a case study of the U.S. Western Interconnection, where climate impacts depend on interactions between temperature-induced load, water availability for hydropower, technology competitiveness, and demand flexibility. Changes in 2038 generating capacity range from -8.5-16.6 GW, and changes in 2038 transmission capacity range from -1-2 GW. Capacity increases are driven by higher load from higher temperatures, while capacity reductions can be achieved in scenarios with higher future hydropower availability and increased demand flexibility. Scenarios requiring additional capacity cost an additional $\$5$-$\$17$ billion (discounted) from 2018 to 2038; however, scenarios with capacity reductions cost $\$1$-$\$18$ billion less. Stress tests on four 2038 infrastructures demonstrated that the identified systems were able to serve at least 99.999% of load and 99.96% of reserves. However, drought and unexpected high-load conditions can result in reduced capacity to respond to contingency events we did not model. Although these results are system and scenario specific, they highlight the importance of considering multiple climate change impacts simultaneously in long-term planning efforts and demonstrate a multi-model, multiscale approach that can be flexibly applied to any system and set of climate change concerns.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1973

A vehicle scheduling algorithm using non-serial discrete dynamic programming with space shuttle applications

Description of the development and operation of a vehicle-scheduling algorithm which has applications to the NASA problem of assigning payloads to space delivery vehicles. The algorithm is based on a discrete, integer-valued, nonserial, dynamic-programming solution to the classical problem of developing resource utilization plans with limited resources. The algorithm places special emphasis on incorporating interpayload (precedence) relationships; maintaining optimal alternate schedule definitions (a unique feature of dynamic programming) in the event of contingencies (namely, resource inventory changes) without problem resolution; and, by using a special information storage technique, reducing the computational complexity of solving realistic problems.

Dupnick, E.↗

NASA NTRS1979

Construction in space - Toward a fresh definition of the man/machine relation

The EVA (extravehicular activity) project forming part of the space construction process is reviewed. The manual EVA constuction, demonstrated by the crew of Skylab 3 by assembling a modest space structure in the form of the twin-pole sunshade, is considered, indicating that the experiment dispelled many doubts about man's ability to execute routine and contingency EVA operations. Tests demonstrating the feasibility of remote teleoperator rendezvous, station keeping, and docking operations, using hand controllers for direct input and television for feedback, are noted. Future plans for designing space construction machines are mentioned.

Watters, H. H.↗

NASA NTRS2007

Automated Target Planning for FUSE Using the SOVA Algorithm

The SOVA algorithm was originally developed under the Resilient Systems and Operations Project of the Engineering for Complex Systems Program from NASA s Aerospace Technology Enterprise as a conceptual framework to support real-time autonomous system mission and contingency management. The algorithm and its software implementation were formulated for generic application to autonomous flight vehicle systems, and its efficacy was demonstrated by simulation within the problem domain of Unmanned Aerial Vehicle autonomous flight management. The approach itself is based upon the precept that autonomous decision making for a very complex system can be made tractable by distillation of the system state to a manageable set of strategic objectives (e.g. maintain power margin, maintain mission timeline, and et cetera), which if attended to, will result in a favorable outcome. From any given starting point, the attainability of the end-states resulting from a set of candidate decisions is assessed by propagating a system model forward in time while qualitatively mapping simulated states into margins on strategic objectives using fuzzy inference systems. The expected return value of each candidate decision is evaluated as the product of the assigned value of the end-state with the assessed attainability of the end-state. The candidate decision yielding the highest expected return value is selected for implementation; thus, the approach provides a software framework for intelligent autonomous risk management. The name adopted for the technique incorporates its essential elements: Strategic Objective Valuation and Attainability (SOVA). Maximum value of the approach is realized for systems where human intervention is unavailable in the timeframe within which critical control decisions must be made. The Far Ultraviolet Spectroscopic Explorer (FUSE) satellite, launched in 1999, has been collecting science data for eight years.[1] At its beginning of life, FUSE had six gyros in two IRUs and four reaction wheels. Over time through various failures, the satellite has been left with one reaction wheel on the vehicle skew axis and two gyros. To remain operational, a control scheme has been implemented using the magnetic torque rods and the remaining momentum wheel.[2] As a consequence, there are attitude regions where there is insufficient torque authority to overcome environmental disturbances (e.g. gravity gradient torques). The situation is further complicated by the fact that these attitude regions shift inertially with time as the spacecraft moves through earth s magnetic field during the course of its orbit. Under these conditions, the burden of planning targets and target-to-target slew maneuvers has increased significantly since the beginning of the mission.[3] Individual targets must be selected so that the magnetic field remains roughly aligned with the skew wheel axis to provide enough control authority to the other two orthogonal axes. If the field moves too far away from the skew axis, the lack of control authority allows environmental torques to pull the satellite away from the target and can potentially cause it to tumble. Slew maneuver planning must factor the stability of targets at the beginning and end, and the torque authority at all points along the slew. Due to the time varying magnetic field geometry relative to any two inertial targets, small modifications in slew maneuver timing can make large differences in the achievability of a maneuver.

Heatwole, Scott↗

DOE OSTI2025

Artificial Intelligence and Machine Learning Applications in Modern Power Systems

Machine learning (ML) and artificial intelligence (AI) algorithms offer valuable tools for the analysis and interpretation of large datasets. These tools have the capability to uncover insights that may not be readily apparent within these datasets. In recent years, the integration of ML and AI has become increasingly prevalent in various applications within the power system domain. One of the earliest instances of machine learning in power systems can be traced back to demand forecasting, where artificial neural networks were employed for short-term load forecasting. In contemporary power systems, an abundance of high-resolution geospatial and temporal data is generated at various time intervals, ranging from sub-seconds (Phasor Measurement Units or PMUs) to seconds (Supervisory Control and Data Acquisition or SCADA), minutes (Process Information or PI), and extending to days, months, and years. These datasets contain valuable information concerning system reliability and performance. This information holds the potential to offer critical insights into system operations, as well as solutions for predicting and mitigating contingencies to prevent cascading outages. Despite the immense power of machine learning tools, system operators, planners, and utilities often exhibit hesitancy in fully embracing AI-enabled system operations and planning. This cautious approach persists, even as numerous diverse applications of machine learning continue to emerge in the realm of power systems. In this chapter, our focus will delve deep into ML and AI applications tailored for power systems. These applications aim to furnish system operators with enhanced situational awareness and augment their decision-making capabilities, especially during challenging operating conditions. Specific areas of interest encompass root cause analyses of electricity market datasets and the strategic selection of representative samples from vast power system databases for training ML/AI models. Finally, the chapter will conclude with a short discussion on the future of ML/AI in power systems and possible directions that the industry is moving towards.

power system applications, machine learning (ML), ↗

NASA NTRS2003

One Way or Another

Even experienced project managers can t anticipate every potential problem. Part of planning ahead should include allowing oneself the flexibility to rethink the plan and improvise if necessary. Unique solutions to problems sometimes create a set of new problems unique in nature as well. In dealing with sudden changes in planning, try to consider what other elements of the project will be affected, but don t second guess yourself into a state of inaction because you can t anticipate every contingency.

Zazzali, Christian↗

NASA NTRS2015

LADEE Preparations for Contingency Operations for the Lunar Orbit Insertion Maneuver

The Lunar Atmosphere and Dust Environment Explorer (LADEE) spacecraft was launched on September 7, 2013 UTC, and completed its mission on April 17, 2014 UTC 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 mission objectives, much of which can be attributed to careful LADEE mission was a resounding success, achieving all planning and preparation. This paper discusses the specific preparations for fault conditions that could occur during a highly-critical phase of the mission, the Lunar Orbit Insertion (LOI). highly critical phase of the mission.

failure analysis↗

NASA NTRS1992

Setting Spacecraft Maximum Allowable Concentrations for 1 hour or 24 hour contingency exposures to airborne chemicals

Since the early years of the manned space program, NASA has developed and used exposure limits called Spacecraft Maximum Allowable Concentrations (SMACs) to help protect astronauts from airborne toxicants. Most of these SMACS are based on an exposure duration of 7 days, since this is the duration of a 'typical' mission. A set of 'contingency SMACs' is also being developed for scenarios involving brief (1-hour or 24- hour) exposures to relatively high levels of airborne toxicants from event-related 'contingency' releases of contaminants. The emergency nature of contingency exposures dictates the use of different criteria for setting exposure limits. The NASA JSC Toxicology Group recently began a program to document the rationales used to set new SMACs and plans to review the older, 7-day SMACs. In cooperation with the National Research Council's Committee on Toxicology, a standard procedure has been developed for researching, setting, and documenting SMAC values.

Garcia, Hector D.↗

NASA NTRS2007

Volatile Organic Analyzer (VOA) in 2006: Repair, Revalidation, and Restart of Elektron Event

The Volatile Organic Analyzer (VOA) was launched to the International Space Station (ISS) in August 2001 and was the first instrument to provide near real-time measurement of volatile organic compounds in a spacecraft atmosphere. The VOA performed an analysis of the ISS air approximately twice a month for most of its operation through May 2003. This intermittent operation, caused by a software interface issue with the ISS communication bus, slowed the validation of the VOA. However, operational validation was completed in 2003 when analysis of air samples collected in grab sample containers (GSCs) compared favorably with simultaneous VOA runs (1). The VOA has two channels that provide redundant function, albeit at slightly reduced performance, when only one channel is operating (2). Most target compounds can be detected on both channels. In January 2003, the VOA identified a malfunction in the channel 2 preconcentrator and it shut down that channel. The anomaly profile suggested that a fuse might have failed, but the root cause could not be determined. In May 2003, channel 1 was shut down when the detector s elevated temperature could not longer be maintained. Since both VOA channels were now deactivated, VOA operations ended until an in-flight repair could be planned and executed. This paper describes the process to repair the VOA and to revalidate it for operations, and then an account is given of the VOA s contribution following a contingency event on ISS.

Limero, Thomas↗

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 NTRS2004

International Space Station (ISS) Oxygen High Pressure Storage Management

High pressure oxygen onboard the ISS provides support for Extra Vehicular Activities (EVA) and contingency metabolic support for the crew. This high pressure 02 is brought to the ISS by the Space Shuttle and is transferred using the Oxygen Recharge Compressor Assembly (ORCA). There are several drivers that must be considered in managing the available high pressure 02 on the ISS. The amount of O2 the Shuttle can fly up is driven by manifest mass limitations, launch slips, and on orbit Shuttle power requirements. The amount of 02 that is used from the ISS high pressure gas tanks (HPGT) is driven by the number of Shuttle docked and undocked EVAs, the type of EVA prebreath protocol that is used and contingency use of O2 for metabolic support. Also, the use of the ORCA must be managed to optimize its life on orbit and assure that it will be available to transfer the planned amount of O2 from the Shuttle. Management of this resource has required long range planning and coordination between Shuttle manifest on orbit plans. To further optimize the situation hardware options have been pursued.

Lewis, John R.↗

NASA NTRSDate not supplied

OSIRIS-REx Screening Experience & Lessons Learned

On September 24, 2023, the NASA OSIRIS-REx spacecraft returned a sample of asteroid Bennu, approaching on a hyperbolic impact trajectory relative to Earth. At approximately 108,000 km altitude and four hours prior to hitting the top of the atmosphere, the Sample Return Capsule (SRC) separated from the spacecraft bus, targeting the Utah Test and Training Range. Twenty minutes later, the bus performed a large divert maneuver to fly by at a perigee altitude of ~780 km. Given the immense scientific value of the sample, substantial efforts were undertaken by NASA CARA and the OSIRIS-REx mission to ensure safe passage of the objects from GEO through LEO. This presentation provides an overview of collision avoidance maneuver (CAM) options, results of screenings, coordination with DoD for contingency observations, and lessons learned for screening future Earth flyby and entry trajectories. Two particular challenges included screening two objects using a much larger than normal 250 km spherical monitor volume and decision planning for a single CAM while the SRC was still attached that would alter both trajectories. The larger, non-standard screening volume resulted in custom procedures that CARA personnel had to run manually for each screening, and the initial long propagation times while the objects were more than a week out required significant computing resources. With a single CAM opportunity at 13 hours out, the decision to execute a maneuver had to consider the risk to both objects, where one could imagine a situation where the maneuver would clear a high-risk conjunction for one object and introduce one for the other – begging the question of relative risk posture between the SRC and bus. These among other unique aspects of Earth flyby and entry missions led to novel planning and implementation procedures to support future missions of this type.

Dolan E. Highsmith↗

NASA NTRS1979

Contingency study for the third international Sun-Earth Explorer (ISEE-3) satellite

The third satellite of the international Sun-Earth Explorer program was inserted into a periodic halo orbit about L sub 1, the collinear libration point between the Sun and the Earth-Moon barycenter. A plan is presented that was developed to enable insertion into the halo orbit in case there was a large underperformance of the Delta second or third stage during the maneuver to insert the spacecraft into the transfer trajectory. After one orbit of the Earth, a maneuver would be performed near perigee to increase the energy of the orbit. A relatively small second maneuver would put the spacecraft in a transfer trajectory to the halo orbit, into which it could be inserted for a total cost within the fuel budget. Overburns (hot transfer trajectory insertions) were also studied.

Dunham, D. W.↗

DOE OSTI2023

Reserve and energy scarcity pricing in United States power markets: A comparative review of principles and practices

Here, errors in forecasting load and renewable-based generation in restructured power systems mean that independent system operators (ISOs) must procure sufficient operating reserves to keep the real-time operation of the system reliable and secure. But when procured reserves turn out to be insufficient in real-time due to the lack of resource capacity or ramp capability, operators often set higher prices for reserves and energy to encourage more supply, and to motivate consumers to decrease usage or shift it to other times. This procedure, which is called scarcity or shortage pricing, is a core feature of U.S. electricity markets. It is receiving increased attention from market designers and stakeholders because scarcity will become more important for spot price formation in the future with the increased penetration of zero-marginal cost renewables, and the shrinking role of fuel costs in setting prices. Scarcity pricing is implemented in various ways by different ISOs. These differences have practical implications for the level of prices and incentives for investment, operations, and demand modification. In this paper, general approaches and specific calculation procedures for reserve and energy scarcity pricing practices and calculations across the seven ISO-based U.S. power markets are reviewed and compared. A consistent terminology is used to facilitate the comparison. Current scarcity pricing practices are grouped into three approaches: (1) imposing an adder after the spot market is run; (2) including stepwise demand curves within market clearing procedures for non-contingency reserve products (e.g., the novel flexiramp product), which tends to yield longer right tails for energy scarcity premium curves; and (3) having stepwise demand curves for traditional contingency reserve products only, which results in shorter right tails in energy scarcity curves. A generic numerical example is presented to highlight the large practical differences among the reserve scarcity pricing approaches and specific implementations. To further investigate factors that contribute the most to demand curves differences among ISOs, a sensitivity analysis is performed. This analysis shows that the largest source of differences among the curves is the scarcity prices assumed in the case of severe scarcity, while the number of steps used and whether flexiramp is considered also yields important differences in scarcity prices. As renewable penetration increases, it will become increasingly crucial to employ administrative demand curves so that spot prices more effectively motivate supply and demand adjustments exactly when and where they are needed. This study shows that the different assumptions yield very different scarcity premiums for reserves and energy, and are likely to provide divergent incentives for resources to respond to shortages. It is concluded that to promote market efficiency, a reserve shortage demand curve should have at least three features: inclusion of the marginal value of reserve products at each shortage level, consideration of the magnitude and probability of supply contingencies, and avoidance of abrupt price discontinuities that can cause excessively volatile market outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

How Can Probabilistic Solar Power Forecasts Be Used to Lower Costs and Improve Reliability in Power Spot Markets? A Review and Application to Flexiramp Requirements

Net load uncertainty in electricity spot markets is rapidly growing. There are five general approaches by which system operators and market participants can use probabilistic forecasts of wind, solar, and load to help manage this uncertainty. These include operator situation awareness, resource risk hedging, reserves procurement, definition of contingencies, and explicit stochastic optimization. We review these approaches, and then provide a case study in which a method for using probabilistic solar forecasts to define needs for reserves is developed and evaluated. The case study has three parts. First, we describe building blocks for enhancing the Watt-Sun solar forecasting system to produce probabilistic irradiance and power forecasts. Second, relationships between Watt-Sun forecasts for multiple sites in California and the system's need for flexible ramp capability (flexiramp) are defined by machine learning and statistical methods. Third, the performance of present methods to defining flexiramp requirements, which are not conditioned on weather and renewables forecasts, is compared with that of probabilistic solar forecast-based requirements, using a multi-timescale production costing model with an 1820-bus representation of the WECC power system. Significant potential savings in fuel and flexiramp procurement costs from using solar-informed reserve requirements are found.

14 SOLAR ENERGY↗

DOE OSTI2020

Bulk Electric System Protection Model Demonstration with 2011 Southwest Blackout in DCAT

Protection equipment modeling is critical to power systems planning and operational studies, it enables more accurate system response when control actions including protection relays and remedial action schemes (RAS) are adequately modeled and assessed. This paper incorporates a generic protection philosophy to the Dynamic Contingency Analysis Tools (DCAT), and demonstrates its effectiveness by modeling 2011 Pacific Southwest Blackout event autonomously.

Bulk Electric System, Protection, Blackout, DCAT↗

NASA NTRS2015

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↗

NASA NTRS2001

Smarter Software For Enhanced Vehicle Health Monitoring and Inter-Planetary Exploration

The existing philosophy for space mission control was born in the early days of the space program when technology did not exist to put significant control responsibility onboard the spacecraft. NASA relied on a team of ground control experts to troubleshoot systems when problems occurred. As computing capability improved, more responsibility was handed over to the systems software. However, there is still a large contingent of both launch and flight controllers supporting each mission. New technology can update this philosophy to increase mission assurance and reduce the cost of inter-planetary exploration. The advent of model-based diagnosis and intelligent planning software enables spacecraft to handle most routine problems automatically and allocate resources in a flexible way to realize mission objectives. The manifests for recent missions include multiple subsystems and complex experiments. Spacecraft must operate at longer distances from earth where communications delays make earthbound command and control impractical. NASA's Ames Research Center (ARC) has demonstrated the utility of onboard diagnosis and planning with the Remote Agent experiment in 1999. KSC has pioneered model-based diagnosis and demonstrated its utility for ground support operations. KSC and ARC are cooperating in research to improve the state of the art of this technology. This paper highlights model-based reasoning applications for Moon and Mars missions including in-situ resource utilization and enhanced vehicle health monitoring.

Larson, William E.↗