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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Comparative Analysis of Static and Dynamic Probabilistic Risk Assessment

Implementation of risk-informed design allows the design team to thoroughly explore the risks of a system while iterating the operations concept, design, and requirements until the system meets mission objects and is achievable within constraints. To arrive at a space system design that is likely to meet all constraints placed upon mass, cost, performance and risk, the system requirements must be understood and traded against each other as early as the conceptual design phase. Depending on the project phase and the goals of the risk analysis, various PRA methodologies could be used to produce quantitative risk estimates to enable such a process. In order to better understand the applicability, advantages, and limitations of various PRA methodologies, a comparative analysis of three bottom-up, component-based PRA approaches was performed. The three methods examined are a traditional static fault tree, a fault tree hybrid, and a dynamic Monte Carlo simulation. Each approach was used to assess a generic reaction control system (RCS) thruster pod and mission. The methods are assessed in terms of the process of modeling a system, the actionable information produced for the design team, and the overall fidelity of the quantitative risk evaluation generated. The paper also discusses the applicability of each methodology to the different phases of system development.

Probablistic↗
NASA NTRS2019

Method for Tracking and Communicating Aggregate Risk Through the Use of Model-Based Systems Engineering (MBSE) Tools

Large, complex projects can identify a significant number and variety of risks, throughout the project life cycle. These risks are analyzed, mitigated, closed or accepted as independent uncertainties. Once closed or accepted, it is easy for projects to lose awareness of their impact. In reality, each of these risks contributes some amount to the overall risk posture of the project. The ability to track and effectively communicate this aggregate risk has represented a challenge to project management. There have been previous attempts to create a schema to communicate the aggregate effect of risks, without notable success. Most of these attempts have centered on some additive metric derived from the scoring of likelihood and consequence values. This, in and of itself, is a logical approach, but all too often the scores were then aggregated to a level where all context was lost. One weakness has been a lack of attempt to create linkages or logical groups of the risks upon which useful aggregation could then occur. The overall move to model-based (systems) engineering (MBSE) has opened up a vast frontier of opportunities to better integrate all project data. MBSE provides an underlying layer that links data items to each other. Objectives link to requirements, which then link to functions, functions to physical architecture items, and so on, as far down as projects want to model. While it started with a focus on modeling requirements based on things like use cases, efforts are now underway to integrate safety and mission assurance (S&MA) information and analyses, such as risks. This effort, called Model Based Mission Assurance (MBMA), is yielding models that are more useful and are a more accurate representations of the systems. MBSE models, with this ability to link related items, provide a new means of tracking and communicating aggregate risks. In the proposed method, risks are added into the models as distinct items, having attributes that communicate a scoring derived from the likelihood and consequence values as charted on the standard NASA 5x5 risk matrix. Like earlier efforts, each box in the 5x5 has an associated scoring, which may include both a current score and potential post-mitigation/control score. The risk items are then linked to elements of the model, such as system objectives/goals, requirements, functions, or physical architecture items, with "Risk to" relationships. These risks will then be communicated by use of reports generated from the model, detailing all risks and/or hazards linked to model elements. These reports can include aggregate impacts, including a current scoring and potential future state scoring based on the planned mitigations and/or controls. These reports will show all risks, open, accepted, and closed, linked to project objectives or requirements. When run as part of an upcoming risk acceptance discussion, these reports will serve to remind the team of all previous risks that relate to the effected portion of the system. When included as part of periodic program or project reviews, risk reviews, and safety reviews, this method can improve the overall understanding of the system's true risk posture. This proposed method takes full advantage of the advances that modern modeling techniques provide, with a minimal investment of additional time. Utilizing the model environment also enables a near constant access to current state of aggregate risks.

model based mission assurance↗
NASA NTRS2017

High-Fidelity Multi-Rotor Unmanned Aircraft System Simulation Development for Trajectory Prediction Under Off-Nominal Flight Dynamics

The NASA Unmanned Aircraft System (UAS) Traffic Management (UTM) project is conducting research to enable civilian low-altitude airspace and UAS operations. A goal of this project is to develop probabilistic methods to quantify risk during failures and off nominal flight conditions. An important part of this effort is the reliable prediction of feasible trajectories during off-nominal events such as control failure, atmospheric upsets, or navigation anomalies that can cause large deviations from the intended flight path or extreme vehicle upsets beyond the normal flight envelope. Few examples of high-fidelity modeling and prediction of off-nominal behavior for small UAS (sUAS) vehicles exist, and modeling requirements for accurately predicting flight dynamics for out-of-envelope or failure conditions are essentially undefined. In addition, the broad range of sUAS aircraft configurations already being fielded presents a significant modeling challenge, as these vehicles are often very different from one another and are likely to possess dramatically different flight dynamics and resultant trajectories and may require different modeling approaches to capture off-nominal behavior. NASA has undertaken an extensive research effort to define sUAS flight dynamics modeling requirements and develop preliminary high fidelity six degree-of-freedom (6-DOF) simulations capable of more closely predicting off-nominal flight dynamics and trajectories. This research has included a literature review of existing sUAS modeling and simulation work as well as development of experimental testing methods to measure and model key components of propulsion, airframe and control characteristics. The ultimate objective of these efforts is to develop tools to support UTM risk analyses and for the real-time prediction of off-nominal trajectories for use in the UTM Risk Assessment Framework (URAF). This paper focuses on modeling and simulation efforts for a generic quad-rotor configuration typical of many commercial vehicles in use today. An overview of relevant off-nominal multi-rotor behaviors will be presented to define modeling goals and to identify the prediction capability lacking in simplified models of multi-rotor performance. A description of recent NASA wind tunnel testing of multi-rotor propulsion and airframe components will be presented illustrating important experimental and data acquisition methods, and a description of preliminary propulsion and airframe models will be presented. Lastly, examples of predicted off-nominal flight dynamics and trajectories from the simulation will be presented.

Foster, John V.↗
NASA NTRSDate not supplied

Mars Sample Return: Risk Management & Sample Safety Assessment

Returning samples from Mars has long been a major planetary science objective due to the high scientific value and transformative potential of the resulting data. An exciting dimension of this objective is the potential for the detection of ancient microbiological life, and the possibility of improving our understanding of the evolution of habitable environments on Mars and the development of life on Earth. To ensure that returned samples meet stringent planetary protection requirements and do not expose Earth to potential biohazards, the joint NASA/ESA Sample Receiving Project (SRP) assembled the Sample Safety Assessment Protocol Tiger Team (SSAP-TT). Members were recruited with the specific goal of creating a multi-disciplinary and internationally distributed team of experts in their respective fields across the federal government, academia, and private industry. This team was chartered with reassessing previous sample safety assessment strategies, defining what constitutes a biological hazard, developing a protocol to test for potential biohazards, and establishing a statistical framework to determine if samples are “safe” for release. The team developed a three-step protocol, supported by a Bayesian statistical framework, to assess whether returned samples contain potential biohazards that could present a risk to Earth’s biosphere. Initial conclusions indicated that an effective and comprehensive safety assessment protocol is feasible using modern techniques and does not require an excessive amount of sample consumption or traditional microbiological detection methodology. Herein, we will present an overview of the MSR SRP, the proposed safety assessment protocol, and how aspects of this novel approach can be applied to biological assessment in healthcare product manufacturing practices.

Alvin L Smith↗
DOE OSTI2023

Adaptive sampling for accelerating neutron diffraction-based strain mapping *

Abstract Neutron diffraction is a useful technique for mapping residual strains in dense metal objects. The technique works by placing an object in the path of a neutron beam, measuring the diffracted signals and inferring the local lattice strain values from the measurement. In order to map the strains across the entire object, the object is stepped one position at a time in the path of the neutron beam, typically in raster order, and at each position a strain value is estimated. Typical dwell times at neutron diffraction instruments result in an overall measurement that can take several hours to map an object that is several tens of centimeters in each dimension at a resolution of a few millimeters, during which the end users do not have an estimate of the global strain features and are at risk of incomplete information in case of instruments outages. In this paper, we propose an object adaptive sampling strategy to measure the significant points first. We start with a small initial uniform set of measurement points across the object to be mapped, compute the strain in those positions and use a machine learning technique to predict the next position to measure in the object. Specifically, we use a Bayesian optimization based on a Gaussian process regression method to infer the underlying strain field from a sparse set of measurements and predict the next most informative positions to measure based on estimates of the mean and variance in the strain fields estimated from the previously measured points. We demonstrate our real-time measure-infer-predict workflow on additively manufactured steel parts—demonstrating that we can get an accurate strain estimate even with 30%–40% of the typical number of measurements—leading the path to faster strain mapping with useful real-time feedback. We emphasize that the proposed method is general and can be used for fast mapping of other material properties such as phase fractions from time-consuming point-wise neutron measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2019

Satellite Conjunction Assessment Risk Analysis for "Dilution Region" Events: Issues and Operational Approaches

An important activity within Space Traffic Management is the detection and prevention of possible on-orbit collisions between space objects. The principal parameter for assessing collision likelihood is the probability of collision, which is widely accepted among conjunction assessment practitioners; but it possesses a known deficiency in that it can produce a false sense of safety when the orbital position uncertainties for the conjuncting objects are high. The probability of collision is said to be “diluted” in such a situation and to understate the possible risk; certain approaches have been recommended by researchers to provide (largely conservative) risk estimates and remediation methodologies in these cases. The present analysis explores two of the main proposals for quantifying and remediating possible risk in the dilution region and quantifies their operational implications. These implications with regard to imputed additional workload are considerable, especially in anticipating the conjunction event levels expected with the deployment of the USAF Space Fence radar. This effort has been undertaken as part of a larger enterprise that seeks to clarify the philosophical and statistical underpinnings of the conjunction risk assessment process. The analysis presented herein argues that a form of hypothesis testing is implicitly used in conjunction assessment risk analysis, and that there are a number of conceptual and practical reasons for constructing the associated null hypothesis to counsel against a satellite conjunction remediation action. In short, it is concluded that, for the purposes of determining whether a conjunction remediation action should be pursued, dilution-region probabilities of collision should be treated no differently from those produced under other circumstances.

Probability of collision↗
NASA NTRS2022

Evidence Report: Risk of Injury and Compromised Performance due to EVA Operations

During future missions to the Moon and Mars, each crewmember will most likely perform up to 24 hours a week of extravehicular activity (EVA) in support of exploration, science, construction, and maintenance tasks. Achieving mission objectives will require EVA systems and operations concepts that maximize human performance and efficiency while minimizing health and safety risks for crewmembers. Currently, over 450 EVAs have been performed in microgravity using the Extravehicular Mobility Unit (EMU). The EMU space suit has enabled the successful assembly and maintenance of the International Space Station (ISS) for over 20 years, as well as deployment of payload experiments, solar arrays, satellite launches and repairs. This EVA work was accomplished at a slower cadence than is expected for Moon and Mars, with ISS crewmembers performing no more than 7 EVAs during a single mission and without any back-to-back EVAs. Despite their success, ISS EVAs have resulted in more injury to EVA crewmembers than may be acceptable for long-duration exploration missions. The Apollo astronauts completed EVA tasks in suits that were designed for their short-duration lunar missions, although suit mobility problems were evident. The more frequent EVAs and more varied EVA tasks that are anticipated during the future longer-duration exploration missions will require EVA suits and systems that are better oriented to human health and performance than those used during the Apollo Program. Many of the problems that were encountered with the Apollo EVA suits (e.g., limited mobility and dexterity, high and aft center of gravity, and other features requiring significant crew compensation) will need to be corrected or mitigated to optimize EVA objectives of exploration missions. It is critical that we understand how EVA system design variables such as suit pressure, weight/mass, center-of-gravity location, joint ranges of motion, and biomedical monitoring, affects the ability of astronauts to perform safe, efficient, and effective EVAs. To achieve this understanding, EVA researchers will need to develop and execute an integrated human testing program across multiple environments. The research will provide objective data that will enable informed design decisions and crewmember standards, thereby ensuring EVA systems that optimize crewmember health, safety, efficiency, and performance. This report describes the risks to crew health, safety, performance, and efficiency caused by EVA operations, and it provides the evidence base to substantiate the importance of the risk.

EVA↗
DOE OSTI2020

Cybersecurity Resiliency of Marine Renewable Energy Systems-Part 1: Identifying Cybersecurity Vulnerabilities and Determining Risk

Technology innovation, market demand, and the potential impacts of a changing climate are driving the marine renewable energy (MRE) industry to develop market-ready systems to provide low-carbon electricity for emerging, off-grid markets. The advanced operational and information technology devices used in MRE systems create a pathway for a cyber threat actor to gain unauthorized access to data or disrupt operation. To improve the resiliency of MRE systems as a predictable, affordable, and reliable source of energy from oceans and rivers, guidance was developed for an end users' organization that describes a framework for identifying and managing cybersecurity risk. The development of the cybersecurity guidance is based on standards described in the Risk Management Framework and Cybersecurity Framework developed by the National Institute of Standards and Technology (NIST). This paper is the first of a two-part series that describes an approach to determine the cybersecurity risk for MRE systems based on assessing potential cyber threats, identifying vulnerabilities (people, processes, and technology, including physical and operational environment), and evaluating the consequences a cyberattack would have on operation of the MRE system and impact on end users' mission and business objectives. MRE developers and stakeholders can use this approach to assess their current cybersecurity risk posture to incorporate appropriate cybersecurity controls to reduce the consequences and impacts from a cyberattack on MRE systems. This approach can be refined further as MRE systems are deployed and operational configurations are available.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Propulsion Risk Reduction Activities for Nontoxic Cryogenic Propulsion

The Propulsion and Cryogenics Advanced Development (PCAD) Project s primary objective is to develop propulsion system technologies for nontoxic or "green" propellants. The PCAD project focuses on the development of nontoxic propulsion technologies needed to provide necessary data and relevant experience to support informed decisions on implementation of nontoxic propellants for space missions. Implementation of nontoxic propellants in high performance propulsion systems offers NASA an opportunity to consider other options than current hypergolic propellants. The PCAD Project is emphasizing technology efforts in reaction control system (RCS) thruster designs, ascent main engines (AME), and descent main engines (DME). PCAD has a series of tasks and contracts to conduct risk reduction and/or retirement activities to demonstrate that nontoxic cryogenic propellants can be a feasible option for space missions. Work has focused on 1) reducing the risk of liquid oxygen/liquid methane ignition, demonstrating the key enabling technologies, and validating performance levels for reaction control engines for use on descent and ascent stages; 2) demonstrating the key enabling technologies and validating performance levels for liquid oxygen/liquid methane ascent engines; and 3) demonstrating the key enabling technologies and validating performance levels for deep throttling liquid oxygen/liquid hydrogen descent engines. The progress of these risk reduction and/or retirement activities will be presented.

Smith, Timothy D.↗
NASA NTRS2011

Reliability Based Design for a Raked Wing Tip of an Airframe

A reliability-based optimization methodology has been developed to design the raked wing tip of the Boeing 767-400 extended range airliner made of composite and metallic materials. Design is formulated for an accepted level of risk or reliability. The design variables, weight and the constraints became functions of reliability. Uncertainties in the load, strength and the material properties, as well as the design variables, were modeled as random parameters with specified distributions, like normal, Weibull or Gumbel functions. The objective function and constraint, or a failure mode, became derived functions of the risk-level. Solution to the problem produced the optimum design with weight, variables and constraints as a function of the risk-level. Optimum weight versus reliability traced out an inverted-S shaped graph. The center of the graph corresponded to a 50 percent probability of success, or one failure in two samples. Under some assumptions, this design would be quite close to the deterministic optimum solution. The weight increased when reliability exceeded 50 percent, and decreased when the reliability was compromised. A design could be selected depending on the level of risk acceptable to a situation. The optimization process achieved up to a 20-percent reduction in weight over traditional design.

Patnaik, Surya N.↗
NASA NTRS2012

A Briefing on Metrics and Risks for Autonomous Decision-Making in Aerospace Applications

Significant technology advances will enable future aerospace systems to safely and reliably make decisions autonomously, or without human interaction. The decision-making may result in actions that enable an aircraft or spacecraft in an off-nominal state or with slightly degraded components to achieve mission performance and safety goals while reducing or avoiding damage to the aircraft or spacecraft. Some key technology enablers for autonomous decision-making include: a continuous state awareness through the maturation of the prognostics health management field, novel sensor development, and the considerable gains made in computation power and data processing bandwidth versus system size. Sophisticated algorithms and physics based models coupled with these technological advances allow reliable assessment of a system, subsystem, or components. Decisions that balance mission objectives and constraints with remaining useful life predictions can be made autonomously to maintain safety requirements, optimal performance, and ensure mission objectives. This autonomous approach to decision-making will come with new risks and benefits, some of which will be examined in this paper. To start, an account of previous work to categorize or quantify autonomy in aerospace systems will be presented. In addition, a survey of perceived risks in autonomous decision-making in the context of piloted aircraft and remotely piloted or completely autonomous unmanned autonomous systems (UAS) will be presented based on interviews that were conducted with individuals from industry, academia, and government.

Frost, Susan↗
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 OSTI2020

Mixed-Mechanism Stimulation Enabled Enhanced Geothermal Systems (CRADA FP00007509 Final Report)

In this project, we aimed to develop a robust, novel EGS design that would enable broad deployment of geothermal energy at costs competitive with other sources of renewable energy. The technical objectives included developing reservoir models for synthetic geothermal systems that meet target reservoir performance characteristics, performing a quantitative assessment of selection criteria for candidate geothermal sites, perform proppant studies under relevant geothermal conditions, and complete an induced seismicity risk analysis for potential geothermal development sites. The project team made significant progress towards these objectives. Specifically, we developed a prioritization to rank candidate sites for suitability of our technology based on 10 separate technical, operational, logistic, regulatory, and commercial criteria. The team performed laboratory testing at Lawrence Berkeley National Laboratory to characterize the functionality of several different types of proppant materials at temperatures of up to 200 C for durations of up to 9 weeks. We also created an Induced Seismicity Mitigation Plan for the top two sites selected for our future field demonstrations.

58 GEOSCIENCES↗
DOE OSTI2024

Carbonated Brine Injection for a Pilot Site as a Low-Risk Geologic Carbon Storage Strategy: A Simulation Study

This technical report presents a preliminary study for CBI implementation in the Pena Creek pilot site in Dimmit County, Texas, targeting the Edwards Limestone Formation for SWD, in collaboration with NGL Energy Partners. The objective of this study is to find the conservative CO 2 molality for safe storage and potential risks for CBI at this pilot site. Geomodel was performed to get site-specific reservoir geology information. Reservoir modeling was performed to investigate dissolved CO 2 molality and pressure changes at relevant injection conditions. Wellbore corrosion and compatibility was discussed with corrosion modeling. Dissolved CO 2 long-term fate in the reservoir was examined with reactive transport modeling. This plan would set the scientific foundation as the initial step for future implementation in the field.

58 GEOSCIENCES↗
NASA NTRS2016

Remote Imaging of Exploration Flight Test-1 (EFT-1) Entry Heating Risk Reduction

A Measure of Performance (MOP) identified with an Exploration Flight Test-1 (EFT-1) Multi- Purpose Crew Vehicle (MPCV) Program Flight Test Objective (FTO) (OFT1.091) specified an observation during reentry though external ground-based or airborne assets with thermal detection capabilities. The objective of this FTO was to be met with onboard Developmental Flight Instrumentation (DFI), but the MOP for external observation was intended to provide complementary quantitative data and serve as a risk reduction in the event of anomalous DFI behavior (or failure). Mr. Gavin Mendeck, the Entry, Descent, and Landing (EDL) Phase Engineer for the MPCV Program (Vehicle Integration Office/Systems & Mission Integration) requested a risk-reduction assessment from the NASA Engineering and Safety Center (NESC) to determine whether quantitative imagery could be obtained from remote aerial assets to support the external observation MOP. If so, then a viable path forward was to be determined, risks identified, and an observation pursued. If not, then the MOP for external observation was to be eliminated.

Schuster, David M.↗
NASA NTRS1992

System test approach for the SAX satellite

SAX satellite verification is based on a protoflight approach, in which only one system model is realized at flight standard level, taking into account the utilization of hardware already qualified for other space programs and the necessity to respect the schedule constraints for a scientific objective. In any case, this approach was tailored with some deviations in order to reduce risks inherent in such a choice. The protoflight approach was also pursued at subsystem/unit level in particular for those subsystems and units considered critical from the schedule point of view. Payload Instruments followed the same approach but complete spare units were developed to reduce the risks associated with such an approach. A description of the model philosophy is provided and then, at satellite level, the testing approach and rationale for each model is presented. Finally, a brief description of each test will be given, highlighting objectives, methodologies, and test configurations. Moreover, for the major tests, problems encountered and solutions applied in establishing a correct approach are described.

Giordano, Pietro↗
DOE OSTI2024

Tree mortality after a spring fire: the role of reduced live leaf area in depletion of early growing season bole NSC

Prescribed fire is used as a tool to achieve various ecological objectives in fire-adapted ecosystems (Ryan et al. 2013). These objectives often include targeted mortality of encroaching species to minimize the risk of catastrophic wildfire (Ryan et al. 2013). Achieving mortality of some species while protecting others requires a foundational understanding of how different species respond to different types of fire at different times of year.

59 BASIC BIOLOGICAL SCIENCES↗