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All sources NASA NTRS DOE OSTI

NASA NTRS1994

Depositional and tectonic setting of the Archean Moodies Group, Barberton Greenstone Belt, South Africa

The 3.22-3.10 Ga old Moodies Group, uppermost unit of the Swaziland Supergroup in the Barberton Greenstone Belt (BGB), is the oldest exposed, well-preserved quartz-rich sedimentary sequence on earth. It is preserved in structurally separate blocks in a heavily deformed fold-and-thrust belt. North of the Inyoka Fault, Moodies strata reach up to 3700 m in thickness. Detailed mapping, correlation of measured sections, and systematic analysis of paleocurrents show that the lower Moodies Group north of the Inyoka Fault forms a deepening- and fining-upward sequence from a basal alluvial conglomerate through braided fluvial, tidal, and deltaic sandstones to offshore sandy shelf deposits. The basal conglomerate and overlying fluvial facies were derived from the north and include abundant detritus eroded from underlying Fig Tree Group dacitic volcanic rocks. Shoreline-parallel transport and extensive reworking dominate overlying deltaic, tidal, and marine facies. The lithologies and arrangement of Moodies Group facies, sandstone petrology, the unconformable relationship between Moodies strata and older deformed rocks, presence of at least one syndepositional normal fault, and presence of basaltic flow rocks and airfall fall tuffs interbedded with the terrestrial strata collectively suggest that the lower Moodies Group was deposited in one or more intramontane basins in an extensional setting. Thinner Moodies sections south of the Inyoka Fault, generally less than 1000 m thick, may be correlative with the basal Moodies Group north of the Inyoka Fault and were probably deposited in separate basins. A northerly derived, southward-thinning fan-delta conglomerate in the upper part of the Moodies Group in the central BGB overlies lower strata with an angular unconformity. This and associated upper Moodies conglomerates mark the beginning of basin shortening by south- to southeast-directed thrust faulting along the northern margin of the BGB and suggest that the upper Moodies Group was deposited in a foreland basin. Timing, orientation, and style of shortening suggest that this deformation eventually incorporated most of the BGB into a major fold-and-thrust belt.

NASA Discipline Exobiology↗

NASA NTRS1988

An approach to solving large reliability models

This paper describes a unified approach to the problem of solving large realistic reliability models. The methodology integrates behavioral decomposition, state trunction, and efficient sparse matrix-based numerical methods. The use of fault trees, together with ancillary information regarding dependencies to automatically generate the underlying Markov model state space is proposed. The effectiveness of this approach is illustrated by modeling a state-of-the-art flight control system and a multiprocessor system. Nonexponential distributions for times to failure of components are assumed in the latter example. The modeling tool used for most of this analysis is HARP (the Hybrid Automated Reliability Predictor).

Boyd, Mark A.↗

NASA NTRS2013

Automated Generation of Fault Management Artifacts from a Simple System Model

Our understanding of off-nominal behavior - failure modes and fault propagation - in complex systems is often based purely on engineering intuition; specific cases are assessed in an ad hoc fashion as a (fallible) fault management engineer sees fit. This work is an attempt to provide a more rigorous approach to this understanding and assessment by automating the creation of a fault management artifact, the Failure Modes and Effects Analysis (FMEA) through querying a representation of the system in a SysML model. This work builds off the previous development of an off-nominal behavior model for the upcoming Soil Moisture Active-Passive (SMAP) mission at the Jet Propulsion Laboratory. We further developed the previous system model to more fully incorporate the ideas of State Analysis, and it was restructured in an organizational hierarchy that models the system as layers of control systems while also incorporating the concept of "design authority". We present software that was developed to traverse the elements and relationships in this model to automatically construct an FMEA spreadsheet. We further discuss extending this model to automatically generate other typical fault management artifacts, such as Fault Trees, to efficiently portray system behavior, and depend less on the intuition of fault management engineers to ensure complete examination of off-nominal behavior.

Spinup and Orient↗

NASA NTRS1989

A design philosophy for multi-layer neural networks with applications to robot control

A system is proposed which receives input information from many sensors that may have diverse scaling, dimension, and data representations. The proposed system tolerates sensory information with faults. The proposed self-adaptive processing technique has great promise in integrating the techniques of artificial intelligence and neural networks in an attempt to build a more intelligent computing environment. The proposed architecture can provide a detailed decision tree based on the input information, information stored in a long-term memory, and the adapted rule-based knowledge. A mathematical model for analysis will be obtained to validate the cited hypotheses. An extensive software program will be developed to simulate a typical example of pattern recognition problem. It is shown that the proposed model displays attention, expectation, spatio-temporal, and predictory behavior which are specific to the human brain. The anticipated results of this research project are: (1) creation of a new dynamic neural network structure, and (2) applications to and comparison with conventional multi-layer neural network structures. The anticipated benefits from this research are vast. The model can be used in a neuro-computer architecture as a building block which can perform complicated, nonlinear, time-varying mapping from a multitude of input excitory classes to an output or decision environment. It can be used for coordinating different sensory inputs and past experience of a dynamic system and actuating signals. The commercial applications of this project can be the creation of a special-purpose neuro-computer hardware which can be used in spatio-temporal pattern recognitions in such areas as air defense systems, e.g., target tracking, and recognition. Potential robotics-related applications are trajectory planning, inverse dynamics computations, hierarchical control, task-oriented control, and collision avoidance.

Vadiee, Nader↗

NASA NTRS1996

Mapping Volcanic Gas Emissions in the Mammoth Mountain Area Using AVIRIS

The Long Valley Caldera located in the eastern Sierra Nevada (California) shows new signs of volcanic activity. This renewed activity is expressed by gas emissions, hydrothermal activity and frequent earthquakes. Analysis of the gas composition regarding the percentage biogenic carbon and the He-3/He-4 ratio revealed that the gas source is the magma body approximately 7 km beneath the Long Valley Caldera. The gas from the magma body surfaces not only via the fumaroles but also emerges along geological faults. Some of the spots where gas surfaces are marked by dead or stressed trees. Other spots may not yet be identified. It is only recently known, from research at 'Vulcano Island' in southern Italy, that volcanoes release abundant carbon dioxide from their flanks as diffuse soil emanations. Mammoth Mountain seems to behave in a similar manner. The research described in this paper is designed to determine whether AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) can be used to identify areas of volcanic gas emissions.

deJong, Steven M.↗

NASA NTRS1989

NETRA: A parallel architecture for integrated vision systems. 1: Architecture and organization

Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is considered to be a system that uses vision algorithms from all levels of processing for a high level application (such as object recognition). A model of computation is presented for parallel processing for an IVS. Using the model, desired features and capabilities of a parallel architecture suitable for IVSs are derived. Then a multiprocessor architecture (called NETRA) is presented. This architecture is highly flexible without the use of complex interconnection schemes. The topology of NETRA is recursively defined and hence is easily scalable from small to large systems. Homogeneity of NETRA permits fault tolerance and graceful degradation under faults. It is a recursively defined tree-type hierarchical architecture where each of the leaf nodes consists of a cluster of processors connected with a programmable crossbar with selective broadcast capability to provide for desired flexibility. A qualitative evaluation of NETRA is presented. Then general schemes are described to map parallel algorithms onto NETRA. Algorithms are classified according to their communication requirements for parallel processing. An extensive analysis of inter-cluster communication strategies in NETRA is presented, and parameters affecting performance of parallel algorithms when mapped on NETRA are discussed. Finally, a methodology to evaluate performance of algorithms on NETRA is described.

Choudhary, Alok N.↗

NASA NTRS2001

Analysis of the Westland Data Set

The "Westland" set of empirical accelerometer helicopter data with seeded and labeled faults is analyzed with the aim of condition monitoring. The autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; and it has also been found that augmentation of these by harmonic and other parameters call improve classification significantly. Several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior oil training data and is thus able to quantify probability of error in all exact manner, such that features may be discarded or coarsened appropriately.

Wen, Fang↗

NASA NTRS1993

Experimental evaluation of the certification-trail method

Certification trails are a recently introduced and promising approach to fault-detection and fault-tolerance. A comprehensive attempt to assess experimentally the performance and overall value of the method is reported. The method is applied to algorithms for the following problems: huffman tree, shortest path, minimum spanning tree, sorting, and convex hull. Our results reveal many cases in which an approach using certification-trails allows for significantly faster overall program execution time than a basic time redundancy-approach. Algorithms for the answer-validation problem for abstract data types were also examined. This kind of problem provides a basis for applying the certification-trail method to wide classes of algorithms. Answer-validation solutions for two types of priority queues were implemented and analyzed. In both cases, the algorithm which performs answer-validation is substantially faster than the original algorithm for computing the answer. Next, a probabilistic model and analysis which enables comparison between the certification-trail method and the time-redundancy approach were presented. The analysis reveals some substantial and sometimes surprising advantages for ther certification-trail method. Finally, the work our group performed on the design and implementation of fault injection testbeds for experimental analysis of the certification trail technique is discussed. This work employs two distinct methodologies, software fault injection (modification of instruction, data, and stack segments of programs on a Sun Sparcstation ELC and on an IBM 386 PC) and hardware fault injection (control, address, and data lines of a Motorola MC68000-based target system pulsed at logical zero/one values). Our results indicate the viability of the certification trail technique. It is also believed that the tools developed provide a solid base for additional exploration.

Sullivan, Gregory F.↗

NASA NTRS1991

Logic flowgraph methodology - A tool for modeling embedded systems

The logic flowgraph methodology (LFM), a method for modeling hardware in terms of its process parameters, has been extended to form an analytical tool for the analysis of integrated (hardware/software) embedded systems. In the software part of a given embedded system model, timing and the control flow among different software components are modeled by augmenting LFM with modified Petrinet structures. The objective of the use of such an augmented LFM model is to uncover possible errors and the potential for unanticipated software/hardware interactions. This is done by backtracking through the augmented LFM mode according to established procedures which allow the semiautomated construction of fault trees for any chosen state of the embedded system (top event). These fault trees, in turn, produce the possible combinations of lower-level states (events) that may lead to the top event.

Muthukumar, C. T.↗

NASA NTRS1992

Intelligent alarming

This talk discusses the importance of providing a process operator with concise information about a process fault including a root cause diagnosis of the problem, a suggested best action for correcting the fault, and prioritization of the problem set. A decision tree approach is used to illustrate one type of approach for determining the root cause of a problem. Fault detection in several different types of scenarios is addressed, including pump malfunctions and pipeline leaks. The talk stresses the need for a good data rectification strategy and good process models along with a method for presenting the findings to the process operator in a focused and understandable way. A real time expert system is discussed as an effective tool to help provide operators with this type of information. The use of expert systems in the analysis of actual versus predicted results from neural networks and other types of process models is discussed.

Braden, W. B.↗

NASA NTRS2011

Risk Acceptance Personality Paradigm: How We View What We Don't Know We Don't Know

The purpose of integrated hazard analyses, probabilistic risk assessments, failure modes and effects analyses, fault trees and many other similar tools is to give managers of a program some idea of the risks associated with their program. All risk tools establish a set of undesired events and then try to evaluate the risk to the program by assessing the severity of the undesired event and the likelihood of that event occurring. Some tools provide qualitative results, some provide quantitative results and some do both. However, in the end the program manager and his/her team must decide which risks are acceptable and which are not. Even with a wide array of analysis tools available, risk acceptance is often a controversial and difficult decision making process. And yet, today's space exploration programs are moving toward more risk based design approaches. Thus, risk identification and good risk assessment is becoming even more vital to the engineering development process. This paper explores how known and unknown information influences risk-based decisions by looking at how the various parts of our personalities are affected by what they know and what they don't know. This paper then offers some criteria for consideration when making risk-based decisions.

Massie, Michael J.↗

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 NTRS1993

Development of a software safety process and a case study of its use

The goal of this research is to continue the development of a comprehensive approach to software safety and to evaluate the approach with a case study. The case study is a major part of the project, and it involves the analysis of a specific safety-critical system from the medical equipment domain. The particular application being used was selected because of the availability of a suitable candidate system. We consider the results to be generally applicable and in no way particularly limited by the domain. The research is concentrating on issues raised by the specification and verification phases of the software lifecycle since they are central to our previously-developed rigorous definitions of software safety. The theoretical research is based on our framework of definitions for software safety. In the area of specification, the main topics being investigated are the development of techniques for building system fault trees that correctly incorporate software issues and the development of rigorous techniques for the preparation of software safety specifications. The research results are documented. Another area of theoretical investigation is the development of verification methods tailored to the characteristics of safety requirements. Verification of the correct implementation of the safety specification is central to the goal of establishing safe software. The empirical component of this research is focusing on a case study in order to provide detailed characterizations of the issues as they appear in practice, and to provide a testbed for the evaluation of various existing and new theoretical results, tools, and techniques. The Magnetic Stereotaxis System is summarized.

Knight, John C.↗

NASA NTRS1984

Pinacate-gran Desierto Region, Mexico: SIR-A Data Analysis

Radar images (SIR-A) from the Columbia space shuttle were used to assess the radar returns of terrain shaped by volcanic, aeolian, and fluvial processes in northwest Sonora. Field studies and photointerpretation show that sand dunes are poorly imaged by SIR-A, in contrast to SEASAT, evidently a consequence of the greater SIR-A incidence angle; star dunes are visible only as small bright spots representing merging arms at dune apices which may act as corner reflectors. Desert grasses and bushes (approx. 2 m high) have little effect on radar brightness. Only larger trees with woody trunks approx. 0.5 m across are effective radar reflectors; their presence contributes to radar bright zones along some arroyos. The radar brightness of lava flows decreases with surface roughness and presence of mantling windblown sediments and weathering products; however, old uplifted (faulted) flows are of equal brightness to fresh, unmantled aa flows. Maar craters display circular patterns of varying radar brightness which represent a combination of geometry, slope, and distribution of surface materials. Some radar bright rings in the Pinacates resemble craters on radar but are observed to be playas encircled by trees.

Christensen, P.↗

NASA NTRS2011

Feature Acquisition with Imbalanced Training Data

This work considers cost-sensitive feature acquisition that attempts to classify a candidate datapoint from incomplete information. In this task, an agent acquires features of the datapoint using one or more costly diagnostic tests, and eventually ascribes a classification label. A cost function describes both the penalties for feature acquisition, as well as misclassification errors. A common solution is a Cost Sensitive Decision Tree (CSDT), a branching sequence of tests with features acquired at interior decision points and class assignment at the leaves. CSDT's can incorporate a wide range of diagnostic tests and can reflect arbitrary cost structures. They are particularly useful for online applications due to their low computational overhead. In this innovation, CSDT's are applied to cost-sensitive feature acquisition where the goal is to recognize very rare or unique phenomena in real time. Example applications from this domain include four areas. In stream processing, one seeks unique events in a real time data stream that is too large to store. In fault protection, a system must adapt quickly to react to anticipated errors by triggering repair activities or follow- up diagnostics. With real-time sensor networks, one seeks to classify unique, new events as they occur. With observational sciences, a new generation of instrumentation seeks unique events through online analysis of large observational datasets. This work presents a solution based on transfer learning principles that permits principled CSDT learning while exploiting any prior knowledge of the designer to correct both between-class and withinclass imbalance. Training examples are adaptively reweighted based on a decomposition of the data attributes. The result is a new, nonparametric representation that matches the anticipated attribute distribution for the target events.

Thompson, David R.↗

NASA NTRS2021

System Validation on the Europa Clipper mission in Early Implementation Phase

NASA’s next flag-ship mission - Europa Clipper, will embark on a journey to Jupiter’s icy moon Europa in 2024 to assess its environment and habitability with a highly capable spacecraft. Post Jupiter-Orbit-Insertion, the spacecraft will be commanded to perform intricate, yet meticulously planned Europa flybys to perform science investigations using a suite of instruments, while withstanding Jupiter’s harsh radiation environment. The success of this mission is dependent on a well-coordinated project and its elements such as the flight hardware and software, the ground support and mission operations teams, procedures and other cross-cutting elements. The Europa Clipper project needs to ensure that these elements are realized at a reasonable confidence level prior to launch and other mission critical events. System Validation test and analysis activities exercise and confirm the integrity of the system of all project elements in the expected flight environment with reasonable stressing conditions. These activities go beyond system design requirements verification and are driven by validation objectives that describe the end-to-end functional and operational capabilities required during nominal and off-nominal flight-like scenarios and critical events. The challenges associated with validating that the Europa Clipper project as a whole can function and perform correctly to meet the intended mission objectives with the as-delivered capabilities of all of its elements are daunting. This paper discusses the systematic methodology established in the early implementation phase of the Europa Clipper project for developing System Validation activities and their validation objectives, and addressing any validation-related challenges on the project. Approaches include decomposition of mission objectives using activity timelines in the Mission Design plan for developing nominal scenarios, use of fault trees for exploring off-nominal cases and system boundaries, and use of Model-based Systems Engineering (MBSE) tools for planning and prioritizing these activities.

Wang, Xu↗

NASA NTRS2021

Data-driven landslide nowcasting at the global scale

Landslides affect nearly every country in the world each year. To better understand this global hazard, the Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed previously. LHASA version 1 combines satellite precipitation estimates with a global landslide susceptibility map to produce a gridded map of potentially hazardous areas from 60° North-South every 3 h. LHASA version 1 categorizes the world’s land surface into three ratings: high, moderate, and low hazard with a single decision tree that first determines if the last seven days of rainfall were intense, then evaluates landslide susceptibility. LHASA version 2 has been developed with a data-driven approach. The global susceptibility map was replaced with a collection of explanatory variables, and two new dynamically varying quantities were added: snow and soil moisture. Along with antecedent rainfall, these variables modulated the response to current daily rainfall. In addition, the Global Landslide Catalog (GLC) was supplemented with several inventories of rainfall-triggered landslide events. These factors were incorporated into the machine-learning framework XGBoost, which was trained to predict the presence or absence of landslides over the period 2015–2018, with the years 2019–2020 reserved for model evaluation. As a result of these improvements, the new global landslide nowcast was twice as likely to predict the occurrence of historical landslides as LHASA version 1, given the same global false positive rate. Furthermore, the shift to probabilistic outputs allows users to directly manage the trade-off between false negatives and false positives, which should make the nowcast useful for a greater variety of geographic settings and applications. In a retrospective analysis, the trained model ran over a global domain for 5 years, and results for LHASA version 1 and version 2 were compared. Due to the importance of rainfall and faults in LHASA version 2, nowcasts would be issued more frequently in some tropical countries, such as Colombia and Papua New Guinea; at the same time, the new version placed less emphasis on arid regions and areas far from the Pacific Rim. LHASA version 2 provides a nearly real-time view of global landslide hazard for a variety of stakeholders.

XGBoos↗

NASA NTRS2013

Goal-Function Tree Modeling for Systems Engineering and Fault Management

The draft NASA Fault Management (FM) Handbook (2012) states that Fault Management (FM) is a "part of systems engineering", and that it "demands a system-level perspective" (NASAHDBK- 1002, 7). What, exactly, is the relationship between systems engineering and FM? To NASA, systems engineering (SE) is "the art and science of developing an operable system capable of meeting requirements within often opposed constraints" (NASA/SP-2007-6105, 3). Systems engineering starts with the elucidation and development of requirements, which set the goals that the system is to achieve. To achieve these goals, the systems engineer typically defines functions, and the functions in turn are the basis for design trades to determine the best means to perform the functions. System Health Management (SHM), by contrast, defines "the capabilities of a system that preserve the system's ability to function as intended" (Johnson et al., 2011, 3). Fault Management, in turn, is the operational subset of SHM, which detects current or future failures, and takes operational measures to prevent or respond to these failures. Failure, in turn, is the "unacceptable performance of intended function." (Johnson 2011, 605) Thus the relationship of SE to FM is that SE defines the functions and the design to perform those functions to meet system goals and requirements, while FM detects the inability to perform those functions and takes action. SHM and FM are in essence "the dark side" of SE. For every function to be performed (SE), there is the possibility that it is not successfully performed (SHM); FM defines the means to operationally detect and respond to this lack of success. We can also describe this in terms of goals: for every goal to be achieved, there is the possibility that it is not achieved; FM defines the means to operationally detect and respond to this inability to achieve the goal. This brief description of relationships between SE, SHM, and FM provide hints to a modeling approach to provide formal connectivity between the nominal (SE), and off-nominal (SHM and FM) aspects of functions and designs. This paper describes a formal modeling approach to the initial phases of the development process that integrates the nominal and off-nominal perspectives in a model that unites SE goals and functions of with the failure to achieve goals and functions (SHM/FM). This methodology and corresponding model, known as a Goal-Function Tree (GFT), provides a means to represent, decompose, and elaborate system goals and functions in a rigorous manner that connects directly to design through use of state variables that translate natural language requirements and goals into logical-physical state language. The state variable-based approach also provides the means to directly connect FM to the design, by specifying the range in which state variables must be controlled to achieve goals, and conversely, the failures that exist if system behavior go out-of-range. This in turn allows for the systems engineers and SHM/FM engineers to determine which state variables to monitor, and what action(s) to take should the system fail to achieve that goal. In sum, the GFT representation provides a unified approach to early-phase SE and FM development. This representation and methodology has been successfully developed and implemented using Systems Modeling Language (SysML) on the NASA Space Launch System (SLS) Program. It enabled early design trade studies of failure detection coverage to ensure complete detection coverage of all crew-threatening failures. The representation maps directly both to FM algorithm designs, and to failure scenario definitions needed for design analysis and testing. The GFT representation provided the basis for mapping of abort triggers into scenarios, both needed for initial, and successful quantitative analyses of abort effectiveness (detection and response to crew-threatening events).

Patterson, Jonathan D.↗