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At least 343 records · Page 19

On the initiation of subduction

Estimates of shear resistance associated with lithospheric thrusting and convergence represent lower bounds on the force necessary to promote trench formation. Three environments proposed as preferential sites of incipient subduction are investigated: passive continental margins, transform faults/fracture zones, and extinct ridges. None of these are predicted to convert into subduction zones simply by the accumulation of local gravitational stresses. Subduction cannot initiate through the foundering of dense oceanic lithosphere immediately adjacent to passive continental margins. The attempted subduction of buoyant material at a mature trench can result in large compressional forces in both subducting and overriding plates. This is the only tectonic force sufficient to trigger the nucleation of a new subduction zone. The ubiquitous distribution of transform faults and fracture zones, combined with the common proximity of these features to mature subduction complexes, suggests that they may represent the most likely sites of trench formation if they are even marginally weaker than normal oceanic lithosphere.

Mueller, Steve↗

Dislocation mechanism based model for stage II fatigue crack propagation rate

Repeated plastic deformation, which of course depends on dislocation mechanism, at or near the crack tip leads to the fatigue crack propagation. By involving the theory of thermally activated flow and the cumulative plastic strain criterion, an effort is made here to model the stage II fatigue crack propagation rate in terms of the dislocation mechanism. The model, therefore, provides capability to ascertain: (1) the dislocation mechanism (and hence the near crack tip microstructures) assisting the crack growth, (2) the relative resistance of dislocation mechanisms to the crack growth, and (3) the fracture surface characteristics and its interpretation in terms of the dislocation mechanism. The local microstructure predicted for the room temperature crack growth in copper by this model is in good agreement with the experimental results taken from the literature. With regard to the relative stability of such dislocation mechanisms as the cross-slip and the dislocation intersection, the model suggests an enhancement of crack growth rate with an ease of cross-slip which in general promotes dislocation cell formation and is common in material which has high stacking fault energy (produces wavy slips). Cross-slip apparently enhances crack growth rate by promoting slip irreversibility and fracture surface brittleness to a greater degree.

Mazumdar, P. K.↗

Satellite Detection of the Convection Generated Stresses in Earth

We review research developments on satellite detection of the convection generated stresses in the Earth for seismic hazard assessment and Earth resource survey. Particular emphasis is laid upon recent progress and results of stress calculations from which the origin and evolution of the tectonic features on Earth's surface can be scientifically addressed. An important aspect of the recent research development in tectonic stresses relative to earthquakes is the implications for earthquake forecasting and prediction. We have demonstrated that earthquakes occur on the ring of fire around the Pacific in response to the tectonic stresses induced by mantle convection. We propose a systematic global assessment of the seismic hazard based on variations of tectonic stresses in the Earth as observed by satellites. This space geodynamic approach for assessing the seismic hazard is unique in that it can pinpoint the triggering stresses for large earthquakes without ambiguities of geological structures, fault geometries, and other tectonic properties. Also, it is distinct from the probabilistic seismic hazard assessment models in the literature, which are based only on extrapolations of available earthquake data.

Liu, Han-Shou↗

Lessons Learned from using a Livingstone Model to Diagnose a Main Propulsion System

NASA researchers have demonstrated that qualitative, model-based reasoning can be used for fault detection in a Main Propulsion System (MPS), a complex, continuous system. At the heart of this diagnostic system is Livingstone, a discrete, propositional logic-based inference engine. Livingstone comprises a language for specifying a discrete model of the system and a set of algorithms that use the model to track the system's state. Livingstone uses the model to test assumptions about the state of a component - observations from the system are compared with values predicted by the model. The intent of this paper is to summarize some advantages of Livingstone seen through our modeling experience: for instance, flexibility in modeling, speed and maturity. We also describe some shortcomings we perceived in the implementation of Livingstone, such as modeling continuous dynamics and handling of transients. We list some upcoming enhancements to the next version of Livingstone that may resolve some of the current limitations.

Sweet, Adam↗

Generating Scenarios When Data Are Missing

The Hypothetical Scenario Generator (HSG) is being developed in conjunction with other components of artificial-intelligence systems for automated diagnosis and prognosis of faults in spacecraft, aircraft, and other complex engineering systems. The HSG accepts, as input, possibly incomplete data on the current state of a system (see figure). The HSG models a potential fault scenario as an ordered disjunctive tree of conjunctive consequences, wherein the ordering is based upon the likelihood that a particular conjunctive path will be taken for the given set of inputs. The computation of likelihood is based partly on a numerical ranking of the degree of completeness of data with respect to satisfaction of the antecedent conditions of prognostic rules. The results from the HSG are then used by a model-based artificial- intelligence subsystem to predict realistic scenarios and states.

Mackey, Ryan↗

Characterization of Aircraft Structural Damage Using Guided Wave Based Finite Element Analysis for In-Flight Structural Health Management

The development of multidisciplinary Integrated Vehicle Health Management (IVHM) tools will enable accurate detection, diagnosis and prognosis of damage under normal and adverse conditions during flight. The adverse conditions include loss of control caused by environmental factors, actuator and sensor faults or failures, and structural damage conditions. A major concern is the growth of undetected damage/cracks due to fatigue and low velocity foreign object impact that can reach a critical size during flight, resulting in loss of control of the aircraft. To avoid unstable catastrophic propagation of damage during a flight, load levels must be maintained that are below the load-carrying capacity for damaged aircraft structures. Hence, a capability is needed for accurate real-time predictions of safe load carrying capacity for aircraft structures with complex damage configurations. In the present work, a procedure is developed that uses guided wave responses to interrogate damage. As the guided wave interacts with damage, the signal attenuates in some directions and reflects in others. This results in a difference in signal magnitude as well as phase shifts between signal responses for damaged and undamaged structures. Accurate estimation of damage size and location is made by evaluating the cumulative signal responses at various pre-selected sensor locations using a genetic algorithm (GA) based optimization procedure. The damage size and location is obtained by minimizing the difference between the reference responses and the responses obtained by wave propagation finite element analysis of different representative cracks, geometries and sizes.

Seshadri, Banavara R.↗

A hierarchical approach to reliability modeling of fault-tolerant systems

A methodology for performing fault tolerant system reliability analysis is presented. The method decomposes a system into its subsystems, evaluates vent rates derived from the subsystem's conditional state probability vector and incorporates those results into a hierarchical Markov model of the system. This is done in a manner that addresses failure sequence dependence associated with the system's redundancy management strategy. The method is derived for application to a specific system definition. Results are presented that compare the hierarchical model's unreliability prediction to that of a more complicated tandard Markov model of the system. The results for the example given indicate that the hierarchical method predicts system unreliability to a desirable level of accuracy while achieving significant computational savings relative to component level Markov model of the system.

Gossman, W. E.↗

Initial SEE Testing of Maestro

We have reported on initial SEE sensitivity of the full 49-core Maestro device. Supporting the low-level structures and qualitative system observation goals of phase 1 of testing. Observed sensitivities found to be consistent with Boeing predictions. Highlighted by the L1 data cache sensitivity which drives the rates on the current Maestro device. Presented details to the hardware and software setups that show where the limitations - highlighting future work. Key future work includes testing with memory and IO ports.

cache sensitivity↗

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.↗

Another Approach to Enhance Airline Safety: Using Management Safety Tools

The ultimate goal of conducting an accident investigation is to prevent similar accidents from happening again and to make operations safer system-wide. Based on the findings extracted from the investigation, the "lesson learned" becomes a genuine part of the safety database making risk management available to safety analysts. The airline industry is no exception. In the US, the FAA has advocated the usage of the System Safety concept in enhancing safety since 2000. Yet, in today s usage of System Safety, the airline industry mainly focuses on risk management, which is a reactive process of the System Safety discipline. In order to extend the merit of System Safety and to prevent accidents beforehand, a specific System Safety tool needs to be applied; so a model of hazard prediction can be formed. To do so, the authors initiated this study by reviewing 189 final accident reports from the National Transportation Safety Board (NTSB) covering FAR Part 121 scheduled operations. The discovered accident causes (direct hazards) were categorized into 10 groups Flight Operations, Ground Crew, Turbulence, Maintenance, Foreign Object Damage (FOD), Flight Attendant, Air Traffic Control, Manufacturer, Passenger, and Federal Aviation Administration. These direct hazards were associated with 36 root factors prepared for an error-elimination model using Fault Tree Analysis (FTA), a leading tool for System Safety experts. An FTA block-diagram model was created, followed by a probability simulation of accidents. Five case studies and reports were provided in order to fully demonstrate the usefulness of System Safety tools in promoting airline safety.

Lu, Chien-tsug↗

Imaging the Moon's Core with Seismology

Constraining the structure of the lunar core is necessary to improve our understanding of the present-day thermal structure of the interior and the history of a lunar dynamo, as well as the origin and thermal and compositional evolution of the Moon. We analyze Apollo deep moonquake seismograms using terrestrial array processing methods to search for the presence of reflected and converted energy from the lunar core. Although moonquake fault parameters are not constrained, we first explore a suite of theoretical focal spheres to verify that fault planes exist that can produce favorable core reflection amplitudes relative to direct up-going energy at the Apollo stations. Beginning with stacks of event seismograms from the known distribution of deep moonquake clusters, we apply a polarization filter to account for the effects of seismic scattering that (a) partitions energy away from expected components of ground motion, and (b) obscures all but the main P- and S-wave arrivals. The filtered traces are then shifted to the predicted arrival time of a core phase (e.g. PcP) and stacked to enhance subtle arrivals associated with the Moon s core. This combination of filtering and array processing is well suited for detecting deep lunar seismic reflections, since we do not expect scattered wave energy from near surface (or deeper) structure recorded at varying epicentral distances and stations from varying moonquakes at varying depths to stack coherently. Our results indicate the presence of a solid inner and fluid outer core, overlain by a partial-melt-containing boundary layer (Table 1). These layers are consistently observed among stacks from four classes of reflections: P-to-P, S-to-P, P-to-S, and S-to-S, and are consistent with current indirect geophysical estimates of core and deep mantle properties, including mass, moment of inertia, lunar laser ranging, and electromagnetic induction. Future refinements are expected following the successful launch of the GRAIL lunar orbiter and SELENE 2 lunar lander missions.

Weber, Renee C.↗

Predictive Modeling to Assess and Address Challenges and Limitations Associated with Clinical Care and Decision Support in Deep Space

Probabilistic risk assessment (PRA) is a method for assessing and integrating the risk of failure in a multivariate system. While it is often applied by engineers designing complex machines, it could also be applied to humans to assess the probability of a health “failure” treating diseases as the multiple “variables” and the human as the “complex machine.” The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) was developed to apply PRA to assess medical risk for exploration spaceflight and inform the design of medical systems for space flight. The NASA engineering community utilizes event-driven and fault tree probabilistic techniques to classify risk in the space flight environment by leveraging the inherent knowledge of complex space flight system design and testing to quantify risk. However, in harmonizing the risk of human space flight, answering the question of “How do we balance astronaut health, performance and resource risks with other engineering risks on exploration space missions?” remains a profoundly challenging and largely qualitative practice. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is one aspect of the Human Research Program’s efforts to represent space fight human health and performance risks quantitatively.

L Mcintyre↗

Experiences with a prevalidation methodology for designing integrated/propulsion control system architectures

The work described in this paper is supported under NASA contract NAS1-18099, Analysis and Detailed Design of an Integrated Airfame/Propulsion Control System Architecture (IAPSA II). This contract address methodology, analysis and detailed design of integrated control system architectures suitable for high performance aircraft of the 1990's. We have developed methodology, with supporting analytical tools, to provide system designers with the capability to specify candidate architectures and accurately predict their reliability and performance in the early stages of design development. This paper describes experience gained using the prevalidation methodology, including supporting tools.

Propulsion control system↗

Constraints on Early Mars Evolution and Dichotomy Origin from Relaxation Modeling of Dichotomy Boundary in the Ismenius Region

The Martian dichotomy is a global feature separating the northern and southern hemispheres. The 3.5 - 4 Gyr old feature is manifested by a topographic difference of 2-6 km and crustal thickness difference of approx. 15 - 30 km between the two hemispheres. In the Ismenius region, sections of the boundary are characterized by a single scarp with a slope of approx. 20 deg. - 23 deg. and are believed to be among the most well preserved parts of the dichotomy boundary. The origin of the dichotomy is unknown. Endogenic hypotheses do not predict the steep slopes (scarps) of the dichotomy boundary. Exogenic models for forming the northern lowlands by impact cratering, associate the scarps along the dichotomy boundary with craters' rims, but are not globally consistent with the topography and gravity. In order to better understand the origin of the Martian dichotomy, it is necessary to know if the steep scarps along the boundary represent the original shape of the dichotomy. Smrekar et al. presented evidence showing that the boundary scarp in Ismenius is a fault along which the highland crust was down faulted. We test whether the relaxation process could produce faulting along the dichotomy boundary and examine the crustal and mantle conditions that would allow for faulting to occur within 1 Gyr and preserve the long wavelength topography over another 3 Gyr. We approach the problem by a combination of numerical and semi-analytical modeling. We test different viscosity profiles and crustal thicknesses by comparing our modeled magnitude, location and timing of plastic strain and displacements to detailed geologic observations in the Ismenius region.

Guest, A.↗

Deep-reasoning fault diagnosis - An aid and a model

The design and evaluation are presented for the knowledge-based assistance of a human operator who must diagnose a novel fault in a dynamic, physical system. A computer aid based on a qualitative model of the system was built to help the operators overcome some of their cognitive limitations. This aid differs from most expert systems in that it operates at several levels of interaction that are believed to be more suitable for deep reasoning. Four aiding approaches, each of which provided unique information to the operator, were evaluated. The aiding features were designed to help the human's casual reasoning about the system in predicting normal system behavior (N aiding), integrating observations into actual system behavior (O aiding), finding discrepancies between the two (O-N aiding), or finding discrepancies between observed behavior and hypothetical behavior (O-HN aiding). Human diagnostic performance was found to improve by almost a factor of two with O aiding and O-N aiding.

Yoon, Wan Chul↗

Biomimetic Models for An Ecological Approach to Massively-Deployed Sensor Networks

Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network.

Jones, Kennie H.↗

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↗

Surrogate oracles, generalized dependency and simpler models

Software reliability models require the sequence of interfailure times from the debugging process as input. It was previously illustrated that using data from replicated debugging could greatly improve reliability predictions. However, inexpensive replication of the debugging process requires the existence of a cheap, fast error detector. Laboratory experiments can be designed around a gold version which is used as an oracle or around an n-version error detector. Unfortunately, software developers can not be expected to have an oracle or to bear the expense of n-versions. A generic technique is being investigated for approximating replicated data by using the partially debugged software as a difference detector. It is believed that the failure rate of each fault has significant dependence on the presence or absence of other faults. Thus, in order to discuss a failure rate for a known fault, the presence or absence of each of the other known faults needs to be specified. Also, in simpler models which use shorter input sequences without sacrificing accuracy are of interest. In fact, a possible gain in performance is conjectured. To investigate these propositions, NASA computers running LIC (RTI) versions are used to generate data. This data will be used to label the debugging graph associated with each version. These labeled graphs will be used to test the utility of a surrogate oracle, to analyze the dependent nature of fault failure rates and to explore the feasibility of reliability models which use the data of only the most recent failures.

Wilson, Larry↗