Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “risk objectives”

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.

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

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Technology Development Roadmap: A Technology Development Roadmap for a Future Gravitational Wave Mission

Humankind will detect the first gravitational wave (GW) signals from the Universe in the current decade using ground-based detectors. But the richest trove of astrophysical information lies at lower frequencies in the spectrum only accessible from space. Signals are expected from merging massive black holes throughout cosmic history, from compact stellar remnants orbiting central galactic engines from thousands of close contact binary systems in the Milky Way, and possibly from exotic sources, some not yet imagined. These signals carry essential information not available from electromagnetic observations, and which can be extracted with extraordinary accuracy. For 20 years, NASA, the European Space Agency (ESA), and an international research community have put considerable effort into developing concepts and technologies for a GW mission. Both the 2000 and 2010 decadal surveys endorsed the science and mission concept of the Laser Interferometer Space Antenna (LISA). A partnership of the two agencies defined and analyzed the concept for a decade. The agencies partnered on LISA Pathfinder (LPF), and ESA-led technology demonstration mission, now preparing for a 2015 launch. Extensive technology development has been carried out on the ground. Currently, the evolved Laser Interferometer Space Antenna (eLISA) concept, a LISA-like concept with only two measurement arms, is competing for ESA's L2 opportunity. NASA's Astrophysics Division seeks to be a junior partner if eLISA is selected. If eLISA is not selected, then a LISA-like mission will be a strong contender in the 2020 decadal survey. This Technology Development Roadmap (TDR) builds on the LISA concept development, the LPF technology development, and the U.S. and European ground-based technology development. The eLISA architecture and the architecture of the Mid-sized Space-based Gravitational-wave Observatory (SGO Mid)-a competitive design with three measurement arms from the recent design study for a NASA-led mission after 2020-both use the same technologies. Further, NASA participation in an ESA-led mission would likely augment the eLISA architecture with a third arm to become the SGO Mid architecture. For these reasons, this TDR for a future GW mission applies to both designs and both programmatic paths forward. It is adaptable to the different timelines and roles for an ESA-led or a NASA-led mission, and it is adaptable to available resources. Based on a mature understanding of the interaction between technology and risk, the authors of this TDR have chosen a set of objectives that are more expansive than is usual. The objectives for this roadmap are: (1) reduce technical and development risks and costs; (2) understand and, where possible, relieve system requirements and consequences; (3) increase technical insight into critical technologies; and (4) validate the design at the subsystem level. The emphasis on these objectives, particularly the latter two, is driven by outstanding programmatic decisions, namely whether a future GW mission is ESA-led or NASA-led, and availability of resources. The relative emphasis is best understood in the context of prioritization.

Laser Interferometry Space Antenna↗
NASA NTRSDate not supplied

Artemis I: Test Flight Buys Down Risk for Humanity's Return to the Moon

The Artemis program successfully demonstrated its foundational deep space human transportation system during the Artemis I test flight in late 2022. This bold mission put the Artemis program on a course to accomplish increasingly complex missions to return humans to the Moon and to prepare for Mars and other destinations. The Artemis I uncrewed mission tested the Space Launch System (SLS) rocket and the Orion spacecraft using the ground processing, launch and recovery services provided by the Exploration Ground Systems (EGS) program at the Kennedy Space Center (KSC). The Artemis team accomplished key mission priorities that deliberately bought down risk for upcoming crewed missions as part of a build-up flight test strategy. The Artemis I mission priorities were 1) demonstrate Orion heatshield at lunar re-entry conditions; 2) operate systems in flight environment; and 3) retrieve the spacecraft. The successful performance and demonstration of these primary mission objectives from lift-off thru orbital insertion, translunar injection, outbound transit towards the Moon, entry into lunar orbit, coast in the lunar Distant Retrograde Orbit (DRO), exit from lunar orbit, transit back to Earth, atmospheric re-entry, descent, splashdown and recovery successfully showed that NASA has a foundational deep space transportation capability in place for human class missions. In addition to the primary mission objectives, a set of scientific payloads, approved Flight Test Objectives (FTOs) and Development Flight Test Objectives (DFTOs) were incorporated into the nominal mission plan and were designated as secondary, or priority 4, and were considered “bonus objectives” in terms of crewed flight risk buydown. During the mission, the team found itself in a position where it was comfortable achieving even more content than originally planned. As a result, DFTOs were added during the mission to further buy down risk to later crewed test flights. This paper presents an overview of the Artemis I test flight, including mission priorities and key test objectives, the launch campaign and as-flown mission profile, test objectives accomplished over the course of the 25.5- day mission, and implications to the crewed Artemis II and later test flight missions.

Artemis↗
NASA NTRS2005

Assessing Malaria Risks in Greater Mekong Subregion based on Environmental Parameters

At 4,200 km, the Mekong River is the tenth longest river in the world. It directly and indirectly influences the lives of hundreds of millions of inhabitants in its basin. The riparian countries - Thailand, Myanmar, Cambodia, Laos, Vietnam, and a small part of China - form the Greater Mekong Subregion (GMS). This geographical region has the misfortune of being the world's epicenter of falciparum malaria, which is the most severe form of malaria caused by Plasmodium falciparum. Depending on the country, approximately 50 to 90% of all malaria cases are due to this species. In the Malaria Modeling and Surveillance Project, we have been developing techniques to enhance public health s decision capability for malaria risk assessments and controls. The main objectives are: 1) identifying the potential breeding sites for major vector species; 2) implementing a malaria transmission model to identify the key factors that sustain or intensify malaria transmission; and 3) implementing a risk algorithm to predict the occurrence of malaria and its transmission intensity. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Socioeconomic factors that may influence malaria transmissions will also be incorporated into the predictive models.

Kiang, Richard↗
NASA NTRS2005

Malaria Modeling and Surveillance for the Greater Mekong Subregion

At 4,200 km, the Mekong River is the tenth longest river in the world. It directly and indirectly influences the lives of hundreds of millions of inhabitants in its basin. The riparian countries - Thailand, Myanmar, Cambodia, Laos, Vietnam, and a small part of China - form the Greater Mekong Subregion (GMS). This geographical region has the misfortune of being the world's epicenter of falciparum malaria, which is the most severe form of malaria caused by Plasmodium falciparum. Depending on the country, approximately 50 to 90% of all malaria cases are due to this species. In the Malaria Modeling and Surveillance Project, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) Identifying the potential breeding sites for major vector species; 2) Implementing a malaria transmission model to identify the key factors that sustain or intensify malaria transmission; and 3) Implementing a risk algorithm to predict the occurrence of malaria and its transmission intensity. The potential benefits are: 1) Increased warning time for public health organizations to respond to malaria outbreaks; 2) Optimized utilization of pesticide and chemoprophylaxis; 3) Reduced likelihood of pesticide and drug resistance; and 4) Reduced damage to environment. Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. These parameters are extracted from NASA Earth science data sets. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records.

Kiang, Richard↗
NASA NTRS2012

Impact of Non-Gaussian Error Volumes on Conjunction Assessment Risk Analysis

An understanding of how an initially Gaussian error volume becomes non-Gaussian over time is an important consideration for space-vehicle conjunction assessment. Traditional assumptions applied to the error volume artificially suppress the true non-Gaussian nature of the space-vehicle position uncertainties. For typical conjunction assessment objects, representation of the error volume by a state error covariance matrix in a Cartesian reference frame is a more significant limitation than is the assumption of linearized dynamics for propagating the error volume. In this study, the impact of each assumption is examined and isolated for each point in the volume. Limitations arising from representing the error volume in a Cartesian reference frame is corrected by employing a Monte Carlo approach to probability of collision (Pc), using equinoctial samples from the Cartesian position covariance at the time of closest approach (TCA) between the pair of space objects. A set of actual, higher risk (Pc >= 10 (exp -4)+) conjunction events in various low-Earth orbits using Monte Carlo methods are analyzed. The impact of non-Gaussian error volumes on Pc for these cases is minimal, even when the deviation from a Gaussian distribution is significant.

Ghrist, Richard W.↗
NASA NTRS2014

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.

Luxhoj, J. T.↗
NASA NTRS2018

Occluded Object Reconstruction for First Responders with Augmented Reality Glasses Using Conditional Generative Adversarial Networks

Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts. Our system then reconstructed an image of a new flammable object. Finally, the reconstructed image was superimposed on the input image to provide "transparency". The system imitates human learning about the laws of physics through experience by learning the shape of flammable objects and the flame characteristics.

Chow, Edward↗
NASA NTRS1998

Program Risk Planning with Risk as a Resource

The current focus of NASA on cost effective ways of achieving mission objectives has created a demand for a change in the risk management process of a program. At present, there is no guidelines as to when risk taking is justified due to high cost for a marginal improvement in risk. As a remedial step, Dr. Greenfield of NASA, developed a concept of risk management with risk as a resource. In the report, the following topics are addressed: (1) the risk management approach; (2) planning risk and program life cycle; (3) key components of a typical program; (4) the risk trading methodology; (5) review and decision process; (6) merits of the proposed risk planning approach; and (7) recommendations.

Ray, Paul S.↗
NASA NTRSDate not supplied

NASA Conjunction Assessment Risk Analysis (CARA) Ground Systems, Software and Operations Infrastructure Cloud Implementation

The growing number of large-scale constellations and the improvements made in the tracking and detection of resident space objects have contributed to the increase of satellite conjunction events. As a result of the increase of objects in Earth orbit, the timeline for risk analysis computations for satellite collision avoidance is more urgent when conjunctions occur. It is imperative NASA maintains a space environment safety functionality for the agency that allows CARA remote access to the ground system while maintaining redundancy. CARA’s On-premises (On-prem) ground system would no longer be able to meet these access and redundancy requirements, hence the investigation and eventual implementation of a Cloud-based ground station infrastructure as a viable solution. This paper will provide an overview of the principal parts of the Conjunction Assessment (CA) risk analysis process used at CARA, summarize the key drivers towards the Cloud solution, and share key lessons learned that are significant for any operational entity considering a cloud solution for real-time satellite operations to ensure a sustainable space traffic environment for all.

Sustainability↗
NASA NTRS2017

An Overview of the Orbital Debris and Meteoroid Environments, Their Effects on Spacecraft, and What Can We Do About It?

Because of the high speeds needed for orbital space flight, hypervelocity impacts with objects in space are a constant risk to spacecraft. This includes natural debris - meteoroids - and the debris remnants of our own activities in space. A number of space surveillance assets are used to measure and track spacecraft, used upper stages, and breakup debris. However, much of the debris and meteoroids encountered by spacecraft in Earth orbit is not easily measured or tracked. For every man-made object that we can track, there are hundreds of small debris that are too small to be tracked but still large enough to damage spacecraft. In addition, even if we knew today's environment with perfect knowledge, the debris environment is dynamic and would change tomorrow. This means that much of the risk from both meteoroids and anthropogenic debris is statistical in nature. NASA uses and maintains a number of instruments to statistically monitor the meteoroid and orbital debris environments, and uses this information to compute statistical models for use by spacecraft designers and operators. Because orbital debris is a result of human activities, NASA has led the US government in formulating national and international strategies that space users can employ to limit the growth of debris in the future. This talk will summarize the history and current state of meteoroid and space debris measurements and modeling, how the environment influences spacecraft design and operations, how we are designing the experiments of tomorrow to improve our knowledge, and how we are working internationally to preserve the space environment for the future.

Matney, Mark↗
NASA NTRS2007

Improvements to NASA's Debris Assessment Software

NASA's Debris Assessment Software (DAS) has been substantially revised and expanded. DAS is designed to assist NASA programs in performing orbital debris assessments, as described in NASA s Guidelines and Assessment Procedures for Limiting Orbital Debris. The extensive upgrade of DAS was undertaken to reflect changes in the debris mitigation guidelines, to incorporate recommendations from DAS users, and to take advantage of recent software capabilities for greater user utility. DAS 2.0 includes an updated environment model and enhanced orbital propagators and reentry-survivability models. The ORDEM96 debris environment model has been replaced by ORDEM2000 in DAS 2.0, which is also designed to accept anticipated revisions to the environment definition. Numerous upgrades have also been applied to the assessment of human casualty potential due to reentering debris. Routines derived from the Object Reentry Survival Analysis Tool, Version 6 (ORSAT 6), determine which objects are assessed to survive reentry, and the resulting risk of human casualty is calculated directly based upon the orbital inclination and a future world population database. When evaluating reentry risks, the user may enter up to 200 unique hardware components for each launched object, in up to four nested levels. This last feature allows the software to more accurately model components that are exposed below the initial breakup altitude. The new DAS 2.0 provides an updated set of tools for users to assess their mission s compliance with the NASA Safety Standard and does so with a clear and easy-to-understand interface. The new native Microsoft Windows graphical user interface (GUI) is a vast improvement over the previous DOS-based interface. In the new version, functions are more-clearly laid out, and the GUI includes the standard Windows-style Help functions. The underlying routines within the DAS code are also improved.

Opiela, J.↗
NASA NTRS1996

Cassini tour cost reductions

The original design of the Cassini tour violated the cost constraint for the mission operations and data analysis by more than 30 percent. This challenge was addressed by performing tradeoffs in order to establish a modified risk and performance posture for the operations organization. This new posture accepted more data acquisition risk with minimal impact to the mission objectives, and brought the operation costs to within the program's constraints. The methodology employed within the Cassini program in order to address the tour cost, risk and performance parameters is presented.

Duxbury, J. H.↗
NASA NTRS2019

The Updated GEO Population for ORDEM 3.1

The limited availability of data for satellite fragmentations and debris in the geosynchronous orbit (GEO) region creates challenges to building accurate models for the orbital debris environment at such altitudes. Updated methods to properly incorporate and extrapolate measurement data have become a cornerstone of the GEO component in the newest version of the NASA Orbital Debris Engineering Model (ORDEM), ORDEM 3.1. For the GEO region, the Space Surveillance Network (SSN) catalog provides coverage down to a limit of approximately 1 m. A more statistically complete representation of the GEO population for smaller objects, which can pose a high risk to operational spacecraft, is thus dependent on dedicated observations by instruments optimized to observe debris smaller than the SSN cataloging threshold. For ORDEM 3.1, optical data from the Michigan Orbital DEbris Survey Telescope (MODEST) provided the input for building the GEO population down to approximately 30 cm (converting absolute magnitude to size). For smaller sizes, the size distribution of debris in the MODEST dataset was extrapolated down to 10 cm, and orbital parameters were estimated based on the orbits of the larger objects. When compared to previous versions of the model, significant improvements were made to the process of building the GEO population in ORDEM 3.1, both in the assessment of fragmentation debris in the data and assignment of orbital elements within the model. A so-called “debris ring filter,” based on a range of angles between an orbit’s angular momentum vector and that of the stable Laplace plane, was applied to the data to reduce biases from non- GEO objects, such as objects in a GEO-transfer orbit. In addition, a new approach was implemented to assign noncircular mean motions and eccentricities to the fragmentation debris observed by MODEST because the short observation window (5 min) in GEO limits orbit resolution to a circular orbit assumption for assigning orbital parameters. For ORDEM 3.1, non-circular orbital elements were assigned using relationships that were identified between mean motion and the angle between the orbit plane and the stable Laplace plane, as well as between mean motion and eccentricity, based on breakup clouds modeled by the NASA Standard Breakup Model. This approach has yielded a high-fidelity GEO model that has been validated with data from more recent MODEST observation campaigns.

Manis, A.↗
NASA NTRS2011

Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practitioners (Second Edition)

Probabilistic Risk Assessment (PRA) is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in complex technological systems for the purpose of cost-effectively improving their safety and performance. NASA's objective is to better understand and effectively manage risk, and thus more effectively ensure mission and programmatic success, and to achieve and maintain high safety standards at NASA. NASA intends to use risk assessment in its programs and projects to support optimal management decision making for the improvement of safety and program performance. In addition to using quantitative/probabilistic risk assessment to improve safety and enhance the safety decision process, NASA has incorporated quantitative risk assessment into its system safety assessment process, which until now has relied primarily on a qualitative representation of risk. Also, NASA has recently adopted the Risk-Informed Decision Making (RIDM) process [1-1] as a valuable addition to supplement existing deterministic and experience-based engineering methods and tools. Over the years, NASA has been a leader in most of the technologies it has employed in its programs. One would think that PRA should be no exception. In fact, it would be natural for NASA to be a leader in PRA because, as a technology pioneer, NASA uses risk assessment and management implicitly or explicitly on a daily basis. NASA has probabilistic safety requirements (thresholds and goals) for crew transportation system missions to the International Space Station (ISS) [1-2]. NASA intends to have probabilistic requirements for any new human spaceflight transportation system acquisition. Methods to perform risk and reliability assessment in the early 1960s originated in U.S. aerospace and missile programs. Fault tree analysis (FTA) is an example. It would have been a reasonable extrapolation to expect that NASA would also become the world leader in the application of PRA. That was, however, not to happen. Early in the Apollo program, estimates of the probability for a successful roundtrip human mission to the moon yielded disappointingly low (and suspect) values and NASA became discouraged from further performing quantitative risk analyses until some two decades later when the methods were more refined, rigorous, and repeatable. Instead, NASA decided to rely primarily on the Hazard Analysis (HA) and Failure Modes and Effects Analysis (FMEA) methods for system safety assessment.

Stamatelatos,Michael↗
NASA NTRS2012

Object-Oriented Bayesian Networks (OOBN) for Aviation Accident Modeling and Technology Portfolio Impact Assessment

The concern for reducing aviation safety risk is rising as the National Airspace System in the United States transforms to the Next Generation Air Transportation System (NextGen). The NASA Aviation Safety Program is committed to developing an effective aviation safety technology portfolio to meet the challenges of this transformation and to mitigate relevant safety risks. The paper focuses on the reasoning of selecting Object-Oriented Bayesian Networks (OOBN) as the technique and commercial software for the accident modeling and portfolio assessment. To illustrate the benefits of OOBN in a large and complex aviation accident model, the in-flight Loss-of-Control Accident Framework (LOCAF) constructed as an influence diagram is presented. An OOBN approach not only simplifies construction and maintenance of complex causal networks for the modelers, but also offers a well-organized hierarchical network that is easier for decision makers to exploit the model examining the effectiveness of risk mitigation strategies through technology insertions.

Shih, Ann T.↗
NASA NTRS2014

Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk

Land cover modeling is used to inform land management, but most often via a two-step process where science informs how management alternatives can influence resources and then decision makers can use this to make decisions. A more efficient process is to directly integrate science and decision making, where science allows us to learn to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuels monitoring with decision making focused on dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy, but habitat trajectories suggest tradeoffs. Knowledge about system responses to actions can be informed by applying competing management actions to different land units in the same system state and by ideas about fire behavior. Monitoring and management integration is important to optimize state-specific management decisions and increase knowledge about system responses. We believe this approach has broad utility for and cover modeling programs intended to inform decision making.

adaptive management↗
NASA NTRS2016

Risk Interfaces to Support Integrated Systems Analysis and Development

Objectives for systems analysis capability: Develop integrated understanding of how a complex human physiological-socio-technical mission system behaves in spaceflight. Why? Support development of integrated solutions that prevent unwanted outcomes (Implementable approaches to minimize mission resources(mass, power, crew time, etc.)); Support development of tools for autonomy (need for exploration) (Assess and maintain resilience -individuals, teams, integrated system). Output of this exercise: -Representation of interfaces based on Human System Risk Board (HSRB) Risk Summary information and simple status based on Human Research Roadmap; Consolidated HSRB information applied to support communication; Point-of-Departure for HRP Element planning; Ability to track and communicate status of collaborations. 4

Mindock, Jennifer↗
NASA NTRS2008

Relative Velocity as a Metric for Probability of Collision Calculations

Collision risk assessment metrics, such as the probability of collision calculation, are based largely on assumptions about the interaction of two objects during their close approach. Specifically, the approach to probabilistic risk assessment can be performed more easily if the relative trajectories of the two close approach objects are assumed to be linear during the encounter. It is shown in this analysis that one factor in determining linearity is the relative velocity of the two encountering bodies, in that the assumption of linearity breaks down at low relative approach velocities. The first part of this analysis is the determination of the relative velocity threshold below which the assumption of linearity becomes invalid. The second part is a statistical study of conjunction interactions between representative asset spacecraft and the associated debris field environment to determine the likelihood of encountering a low relative velocity close approach. This analysis is performed for both the LEO and GEO orbit regimes. Both parts comment on the resulting effects to collision risk assessment operations.

Frigm, Ryan Clayton↗