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NASA NTRSDate not supplied

Uncovering Hazards Using a Multi-Objective Optimization to Explore the Faulty State-Space

Considering resilience when designing complex engineered systems is crucial to ensure the system is safe under unexpected hazardous scenarios. Traditional risk-based approaches, such as Failure Modes and Effects Analysis (FMEA) are useful for designing the system to mitigate hazardous scenarios that can be identified by the designer, but often require experience or prior knowledge of system failures to generate. More recently, researchers have developed simulation tools that enable the designer to model large sets of hazardous scenarios (driven by both internal faults and external factors) through simulation. While these tools enable a wider scope of fault modes to be evaluated (e.g., by injecting combined set of fault modes or injecting modes at different times), the resulting assessments (like FMEA) still require knowledge of the specific modes to be evaluated. However, failure to analyze a wide variety of fault scenarios can lead to an incomplete picture of the system resilience, especially to "surprise events'' which may be difficult for the designer to identify and predict beforehand. To overcome this challenge, previous work developed a fault sampling approach for resilience simulations which would procedurally-generate a wide variety of potential faults by systematically perturbing the health states of the system. While the resulting fault modes generated covered a much larger space hazards than would be otherwise considered (and identified many unique failure trajectories which would not have otherwise been identified), it also significantly increased the computational cost of the analysis and resulted in the simulation and analysis of a large set of essentially duplicate scenarios. Additionally, as the number of dimensions in the faulty state-space increases, the full elaboration of possible modes becomes computationally infeasible, justifying the use of a more targeted search. To resolve this limitation, this work proposes the use of a multiobjective optimization algorithm to search the health state space for potential fault modes that are both (1) hazardous and (2) unique. To solve this type of problem, this work proposes the use of a cooperative co-evolutionary algorithm. To demonstrate this approach, it will be applied to a model of an autonomous rover which uses line markings to navigate, focusing on potential hazards in the drive system which could cause the rover to crash. To determine the merit of the approach, it will further be compared with the previously-presented range elaboration approach and a random mode generation approach on the basis of computational efficiency and found modes.

Resilience↗

NASA NTRS1992

Debris hazard for the Earth Observing System

The scientific mission of the Earth Observing System (EOS) is modeled to analyze the potential hazard of space debris and its impact on the effectiveness of the program. Specific attention is given to the hazard posed by untrackable debris and the velocities and impact rates of such debris. The NASA Debris Flux Model (DFM) is utilized, and the results are compared to those of the Frag model which predicts the background environment from known parameters and the Screen model for estimating collision probabilities. The probability of damaging impacts is shown to be significant and to increase over time; an EOS spacecraft has a 10 percent chance of being struck by a 1-cm object traveling at 14 km/s. The present analyses demonstrate the need to design the EOS spacecraft for a LEO environment in which collisions with debris are very likely.

Madler, Ronald A.↗

NASA NTRS1982

Environmentally induced discharges on satellites

The problem of assessing hazards to geosynchronous satellite systems from geomagnetic substorm encounters is investigated. The available space flight data, coupled with analytical modeling studies, show that only relatively low differential charging is possible from environmental encounters. Using an analytical study of a discharge event on SCATHA, a discharge process is postulated where a small amount of charge is lost to space. These characteristics could then be used as inputs to a coupling model to determine the hazard to a spacecraft. The procedure is applied to a three axis stabilized satellite design.

Stevens, N. J.↗

NASA NTRS1964

Effect of Thrustor Arcing on Ion Rocket System Design

Arcing between the electrodes of an ion rocket thrustor is investigated for the effect it will have on the overall design of ion rocket systems. The effect of generator, transformer, and inserted impedances on system stability and efficiency, and on operating lifetime of thrustor components are considered. Rate of arcing, preferential arc paths, speed of arc interruption, and response of thrustors to voltage transients are also discussed. The study indicates that arcing is a system hazard and that arcing rates are of prime importance in the design and development of thrustors, thrustor arrays, and system components. Two system models for reducing the hazard are proposed, based on principles developed herein, published data, and experience available from operation of nine-module electron-bombardment thrustor array. Experimental investigation of these models is presently underway.

THRUSTOR↗

NASA NTRS1982

Lithium-thionyl chloride battery safety

Primary lithium cells which use LiAlCl4/SOCl2 electrolyte exhibit high energy density and long life. Currently these cells pose a safety problem since they have been found to vent or explode. This paper summarizes experiments to resolve the safety problem of Li-SOCl2 cells by thermal modeling and identification of possibly hazardous intermediates formed during discharge of these cells. A thermal model and mechanism for the reduction of SOCl2 are presented, as well as a discussion of their application to Li-SOCl2 cell safety.

Carter, B.↗

NASA NTRS2021

Investigating the potential of a global precipitation forecast to inform landslide prediction

Extreme rainfall events within landslide-prone areas can be catastrophic, resulting in loss of property, infrastructure, and life. A global Landslide Hazard Assessment for Situational Awareness (LHASA) model provides routine near-real time estimates of landslide hazard using Integrated Multi-Satellite Precipitation Retrievals for the Global Precipitation Mission (IMERG). However, it does not provide information on potential landslide hazard in the future. Forecasting potential landslide events at a global scale presents an area of open research. This study compares a global precipitation forecast provided by NASA's Goddard Earth Observing System (GEOS) with near-real time satellite precipitation estimates. The Multi-Radar Multi-Sensor gauge corrected (MRMS-GC) reference is used to assess the performance of both satellite and model-based precipitation products over the contiguous United States (CONUS). The forecast lead time of 24hrs is considered, with a focus on extreme precipitation events. The performance of IMERG and GEOS-Forecast products is assessed in terms of the probability of detection, success ratio, critical success index and hit bias as well as continuous statistics. The results show that seasonality influences the performance of both satellite and model-based precipitation products. Comparison of IMERG and GEOS-Forecast globally as well as in several event case studies (Colombia, southeast Asia, and Tajikistan) reveals that GEOS-Forecast detects extreme rainfall more frequently relative to IMERG for these specific analyses. For recent landslide points across the globe, the 24hr accumulated precipitation forecast >100 mm corresponds well with near-real time daily accumulated IMERG precipitation estimates. GEOS-Forecast and IMERG precipitation match more closely for tropical cyclones than for other types of storms. The main intention of this study is to assess the viability of using a global forecast for landslide predictions and understand the extent of the variability between these products to inform where we would expect the landslide modeling results to most prominently diverge. Results of this study will be used to inform how forecasted precipitation estimates can be incorporated into the LHASA model to provide the first global predictive view of landslide hazards.

S. Khan↗

NASA NTRS2021

Investigating the Potential of A Global Precipitation Forecast to Inform Landslide Prediction

Extreme rainfall events within landslide-prone areas can be catastrophic, resulting in loss of property, infra-structure, and life. A global Landslide Hazard Assessment for Situational Awareness (LHASA) model provides routine near-real time estimates of landslide hazard using Integrated Multi-Satellite Precipitation Retrievals for the Global Precipitation Mission (IMERG). However, it does not provide information on potential landslide hazard in the future. Forecasting potential landslide events at a global scale presents an area of open research. This study compares a global precipitation forecast provided by NASA’s Goddard Earth Observing System (GEOS) with near-real time satellite precipitation estimates. The Multi-Radar Multi-Sensor gauge corrected (MRMS-GC) reference is used to assess the performance of both satellite and model-based precipitation products over the contiguous United States (CONUS). The forecast lead time of 24hrs is considered, with a focus on extreme precipitation events. The performance of IMERG and GEOS-Forecast products is assessed in terms of the probability of detection, success ratio, critical success index and hit bias as well as continuous statistics. The results show that seasonality influences the performance of both satellite and model-based precipitation products. Comparison of IMERG and GEOS-Forecast globally as well as in several event case studies (Colombia, southeast Asia, and Tajikistan) reveals that GEOS-Forecast detects extreme rainfall more frequently relative to IMERG for these specific analyses. For recent landslide points across the globe, the 24hr accumulated precipitation forecast >100 mm corresponds well with near-real time daily accumulated IMERG precipitation estimates. GEOS-Forecast and IMERG precipitation match more closely for tropical cyclones than for other types of storms. The main intention of this study is to assess the viability of using a global forecast for landslide predictions and understand the extent of the variability between these products to inform where we would expect the landslide modeling results to most prominently diverge. Results of this study will be used to inform how forecasted precipitation estimates can be incorporated into the LHASA model to provide the first global predictive view of landslide hazards.

S. Khan↗

NASA NTRS2024

Machine Learning for the Prediction of Local Asteroid Damages

Risk assessment studies of local asteroid hazards traditionally simulate the physics of meteors with engineering models tailored to analyze tens-of-millions of scenarios. However, these simplified approaches still need to solve time-dependent ODEs to model the entry process and the resulting ground damage. With a computational cost of O(0.01 CPU.s) per scenario, simulating these large numbers of potential entry conditions in risk assessment studies can take several days on local computers. To improve computational efficiency, we propose in this paper an orthogonal approach based on machine learning models to predict the size of damaged areas given a list of entry parameters. We train 5 machine learning methods and compare the predictions to the outputs of the PAIR model, first only with primitive entry condition variables, and then with more advanced features. We find that complex models like neural networks are well-suited to estimate blast hazards, while simpler linear models can accurately assess thermal damage. For both types of hazards, the radii of damaged areas can be predicted with around 10% average errors and a coefficient of determination (R2) of 0.99. The CPU time is decreased by a factor O(10 3 ) compared to the PAIR model, which enables the simulation of millions of scenarios in minutes, on a local computer. We then use the same machine learning approaches for a classification task where the models are trained to predict if an asteroid will produce a given level of damage. Results show that complex models like the gradient boosting classifier and the neural network can perform this task with 98% accuracy. Beyond surrogate models, we finally incorporate the machine learning algorithms to the state-of-the-art Shapley sensitivity analysis and present a ranking of the entry parameters based on their contributions to ground damages.

SMD↗

NASA NTRS2012

Dust Hazard Management in the Outer Solar System

Most robotic missions to the outer solar system must grapple with the hazards posed by the dusty rings of the gas giants. Early assessments of these hazards led simply to ring avoidance due to insufficient data and high uncertainties on the dust population present in such rings. Recent approaches, principal among them the Cassini dust hazard management strategy, provide useful results from detailed modeling of spacecraft vulnerabilities and dust hazard regions, which along with the range of mission trajectories are used to to assess the risks posed by each passage through a zone of potential hazard. This paper shows the general approach used to implement the analysis for Cassini, with recommendations for future outer planet missions.

mission hazards↗

NASA NTRS2010

Positive Voltage Hazard to EMU Crewman from Currents through Plasma

This paper describes the model of the EMU with a human body in the circuit that has been used by NASA to evaluate the low positive voltage hazard. The model utilizes the electron collection characterization from on orbit Langmuir probe data as representative of electron collection to a positive charged surface with a wide range of on orbit plasma temperature and density conditions. The data has been unified according to non-linear theoretical temperature and density variation of the electron saturated probe current collection theory and used as a model for the electron collection at EMU surfaces. Vulnerable paths through the EMU connecting through the crewman s body have been identified along with electrical impedance of the exposed body parts. The body impedance information is merged with the electron collection characteristics in circuit simulation software (SPICE). The assessment shows that currents can be on the order of 20 mA for a 15 V exposure and of order 4 mA at 3V. These currents formally violate NASA protocol for electric current exposures however the human factors associated with subjective consequences of noxious stimuli from low voltage exposure during the stressful conditions of EVA are an area of active inquiry.

Koontz, Steven L.↗

NASA NTRS2008

Information Extraction for System-Software Safety Analysis: Calendar Year 2007 Year-End Report

This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis on the models to identify possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations; 4) perform discrete-time-based simulation on the models to investigate scenarios where these paths may play a role in failures and mishaps; and 5) identify resulting candidate scenarios for software integration testing. This paper describes new challenges in a NASA abort system case, and enhancements made to develop the integrated tool set.

Malin, Jane T.↗

NASA NTRS1981

A proposal to conduct a Caribbean plate project involving the application of space technology to the study of Caribbean geology

The Caribbean plate project is designed to improve current understanding of geological resources and geological hazards within the Caribbean region. Models of mineral occurrence and genesis (including energy resources) on a regional scale, which contribute to nonrenewable resource investigations. Models of lithospheric stress and strain on a regional scale, which contribute to forecasting geological hazards such as earthquakes and major volcanic eruptions are developed. Geological information is synthesize, and research tools provided by space technology the study of the Earth's crust are used. The project was organized in a thematic fashion, to focus on specific geological aspects of the Caribbean plate which are considered to be key factors in developing the types of models described. The project adopts a synoptic perspective in seeking to characterize the three dimensional structure, composition, state of stress, and evolution of the entire Caribbean plate. Geological information derived from analysis of space acquired data is combined with information provided by conventional methods to obtain insight into the structure, composition, and evolution of the Earth's crust. In addition, very long baseline interferometry and laser ranging techniques, which are also based upon the use of space technology, obtain information concerning crustal motion that, in turn, provides insight into the distribution and localization of crustal stress.

Wadge, G.↗

NASA NTRS2022

A Dynamic Landslide Hazard Monitoring Framework for the Lower Mekong Region

The Lower Mekong region is one of the most landslide-prone areas of the world. Despite the need for dynamic characterization of landslide hazard zones within the region, it is largely understudied for several reasons. Dynamic and integrated understanding of landslide processes requires landslide inventories across the region, which have not been available previously. Computational limitations also hamper regional landslide hazard assessment, including accessing and processing remotely sensed information. Finally, open-source software and modelling packages are required to address regional landslide hazard analysis. Leveraging an open-source data-driven global Landslide Hazard Assessment for Situational Awareness model framework, this study develops a region-specific dynamic landslide hazard system leveraging satellite-based Earth observation data to assess landslide hazards across the lower Mekong region. A set of landslide inventories were prepared from high-resolution optical imagery using advanced image-processing techniques. Several static and dynamic explanatory variables (i.e., rainfall, soil moisture, slope, relief, distance to roads, distance to faults, distance to rivers) were considered during the model development phase. An extreme gradient boosting decision tree model was trained for the monsoon period of 2015–2019 and the model was evaluated with independent inventory information for the 2020 monsoon period. The model performance demonstrated considerable skill using receiver operating characteristic curve statistics, with Area Under the Curve values exceeding 0.95. The model architecture was designed to use near-real-time data, and it can be implemented in a cloud computing environment (i.e., Google Cloud Platform) for the routine assessment of landslide hazards in the Lower Mekong region. This work was developed in collaboration with scientists at the Asian Disaster Preparedness Center as part of the NASA SERVIR Program’s Mekong hub. The goal of this work is to develop a suite of tools and services on accessible open-source platforms that support and enable stakeholder communities to better assess landslide hazard and exposure at local to regional scales for decision making and planning.

Nishan Kumar Biswas↗

NASA NTRS2007

Initial Results from the Floating Potential Measurement Unit aboard the International Space Station

The Floating Potential Measurement Unit (FPMU) is a multi-probe package designed to measure the floating potential of the 1nternational Space Station (ISS) as well as the density and temperature of the local ionospheric plasma environment. The role oj the FPMU is to provide direct measurements of ISS spacecraft charging as continuing construction leads to dramatic changes in ISS size and configuration. FPMU data are used for refinement and validation of the ISS spacecraft charging models used to evaluate the severity and frequency of occurrence of ISS charging hazards. The FPMU data and the models are also used to evaluate the effectiveness of proposed hazard controls. The FPMU consists of four probes: a floating potential probe, two Langmuir probes. and a plasma impedance probe. These probes measure the floating potential of the ISS, plasma density, and electron temperature. Redundant measurements using different probes support data validation by inter-probe comparisons. The FPMU was installed by ISS crewmembers, during an ExtraVehicular Activity, on the starboard (Sl) truss of the ISS in early August 2006, when the ISS incorporated only one 160V US photovoltaic (PV) array module. The first data campaign began a few hours after installation and continued for over five days. Additional data campaigns were completed in 2007 after a second 160V US PV array module was added to the ISS. This paper discusses the general performance characteristics of the FPMU as integrated on ISS, the functional performance of each probe, the charging behavior of the ISS before and after the addition of a second 160V US PV array module, and initial results from model comparisons.

Wright, Kenneth H., Jr.↗

NASA NTRS1995

Initiation-promotion model of tumor prevalence in mice from space radiation exposures

Exposures in space consist of low-level background components from galactic cosmic rays (GCR), occasional intense-energetic solar-particle events, periodic passes through geomagnetic-trapped radiation, and exposure from possible onboard nuclear-propulsion engines. Risk models for astronaut exposure from such diverse components and modalities must be developed to assure adequate protection in future NASA missions. The low-level background exposures (GCR), including relativistic heavy ions (HZE), will be the ultimate limiting factor for astronaut career exposure. We consider herein a two-mutation, initiation-promotion, radiation-carcinogenesis model in mice in which the initiation stage is represented by a linear kinetics model of cellular repair/misrepair, including the track-structure model for heavy ion action cross-sections. The model is validated by comparison with the harderian gland tumor experiments of Alpen et al. for various ion beams. We apply the initiation-promotion model to exposures from galactic cosmic rays, using models of the cosmic-ray environment and heavy ion transport, and consider the effects of the age of the mice prior to and after the exposure and of the length of time in space on predictions of relative risk. Our results indicate that biophysical models of age-dependent radiation hazard will provide a better understanding of GCR risk than models that rely strictly on estimates of the initial slopes of these radiations.

NASA Discipline Radiation Health↗

NASA NTRS1998

Safety Analysis of FMS/CTAS Interactions During Aircraft Arrivals

This grant funded research on human-computer interaction design and analysis techniques, using future ATC environments as a testbed. The basic approach was to model the nominal behavior of both the automated and human procedures and then to apply safety analysis techniques to these models. Our previous modeling language, RSML, had been used to specify the system requirements for TCAS II for the FAA. Using the lessons learned from this experience, we designed a new modeling language that (among other things) incorporates features to assist in designing less error-prone human-computer interactions and interfaces and in detecting potential HCI problems, such as mode confusion. The new language, SpecTRM-RL, uses "intent" abstractions, based on Rasmussen's abstraction hierarchy, and includes both informal (English and graphical) specifications and formal, executable models for specifying various aspects of the system. One of the goals for our language was to highlight the system modes and mode changes to assist in identifying the potential for mode confusion. Three published papers resulted from this research. The first builds on the work of Degani on mode confusion to identify aspects of the system design that could lead to potential hazards. We defined and modeled modes differently than Degani and also defined design criteria for SpecTRM-RL models. Our design criteria include the Degani criteria but extend them to include more potential problems. In a second paper, Leveson and Palmer showed how the criteria for indirect mode transitions could be applied to a mode confusion problem found in several ASRS reports for the MD-88. In addition, we defined a visual task modeling language that can be used by system designers to model human-computer interaction. The visual models can be translated into SpecTRM-RL models, and then the SpecTRM-RL suite of analysis tools can be used to perform formal and informal safety analyses on the task model in isolation or integrated with the rest of the modeled system. We had hoped to be able to apply these modeling languages and analysis tools to a TAP air/ground trajectory negotiation scenario, but the development of the tools took more time than we anticipated.

Nancy G. Leveson↗

NASA NTRS2021

Development of a Computational Framework for the Design of Resilient Space Structures

Cyber-physical testing provides a unique platform to enable the design of resilient space structures. This hybrid approach requires the development of a structural model that accounts for various hazards (e.g., micrometeorite and debris impact) and interacts with physical tests and other sub-system models (e.g., thermal) of the space habitat. A two-dimensional finite element analysis code was developed in MATLAB to facilitate the evaluation of potential designs under operating and unexpected loads and prepare the computational framework for eventually performing cyber-physical testing. The code’s efficiency was enhanced by using an object-oriented programming approach that reduced data transfer between functions. In this study, the code is implemented to predict the response of a dome-style structure made of regolith concrete to impact loading and identify the force magnitude that will cause the tensile strength to be exceeded in domes with different thicknesses.

Tensile strength↗

NASA NTRS1980

An advanced terrain modeler for an autonomous planetary rover

A roving vehicle capable of autonomously exploring the surface of an alien world is under development and an advanced terrain modeler to characterize the possible paths of the rover as hazardous or safe is presented. This advanced terrain modeler has several improvements over the Troiani modeler that include: a crosspath analysis, better determination of hazards on slopes, and methods for dealing with missing returns at the extremities of the sensor field. The results from a package of programs to simulate the roving vehicle are then examined and compared to results from the Troiani modeler.

Hunter, E. L.↗