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A parameter and structure estimation technique for multivariable systems is used to obtain state space representation of open loop dynamics of the Space Shuttle Main Engine (SSME). The parameterization being used is both minimal and unique. The simplified linear models may be used for fault detection studies and control system design and development.
Kharkov modeling is a modeling technique that is widely useful for dependability analysis of complex fault tolerant systems. It is very flexible in the type of systems and system behavior it can model. It is not, however, the most appropriate modeling technique for every modeling situation. The first task in obtaining a reliability or availability estimate for a system is selecting which modeling technique is most appropriate to the situation at hand. A person performing a dependability analysis must confront the question: is Kharkov modeling most appropriate to the system under consideration, or should another technique be used instead? The need to answer this gives rise to other more basic questions regarding Kharkov modeling: what are the capabilities and limitations of Kharkov modeling as a modeling technique? How does it relate to other modeling techniques? What kind of system behavior can it model? What kinds of software tools are available for performing dependability analyses with Kharkov modeling techniques? These questions and others will be addressed in this tutorial.
Probabilistic Risk Assessment (PRA) is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in complex technological systems for the purpose of cost-effectively improving their safety and performance. NASA's objective is to better understand and effectively manage risk, and thus more effectively ensure mission and programmatic success, and to achieve and maintain high safety standards at NASA. NASA intends to use risk assessment in its programs and projects to support optimal management decision making for the improvement of safety and program performance. In addition to using quantitative/probabilistic risk assessment to improve safety and enhance the safety decision process, NASA has incorporated quantitative risk assessment into its system safety assessment process, which until now has relied primarily on a qualitative representation of risk. Also, NASA has recently adopted the Risk-Informed Decision Making (RIDM) process [1-1] as a valuable addition to supplement existing deterministic and experience-based engineering methods and tools. Over the years, NASA has been a leader in most of the technologies it has employed in its programs. One would think that PRA should be no exception. In fact, it would be natural for NASA to be a leader in PRA because, as a technology pioneer, NASA uses risk assessment and management implicitly or explicitly on a daily basis. NASA has probabilistic safety requirements (thresholds and goals) for crew transportation system missions to the International Space Station (ISS) [1-2]. NASA intends to have probabilistic requirements for any new human spaceflight transportation system acquisition. Methods to perform risk and reliability assessment in the early 1960s originated in U.S. aerospace and missile programs. Fault tree analysis (FTA) is an example. It would have been a reasonable extrapolation to expect that NASA would also become the world leader in the application of PRA. That was, however, not to happen. Early in the Apollo program, estimates of the probability for a successful roundtrip human mission to the moon yielded disappointingly low (and suspect) values and NASA became discouraged from further performing quantitative risk analyses until some two decades later when the methods were more refined, rigorous, and repeatable. Instead, NASA decided to rely primarily on the Hazard Analysis (HA) and Failure Modes and Effects Analysis (FMEA) methods for system safety assessment.
An investigation of active control communications sponsored by the NASA Langley Research Center is summarized. Particular attention is given to comparative architectures, for which a common set of requirements is generated as a baseline. Most of the requirements are aircraft functional in nature, such as stability and command augmentation, structural load relief, flight path control, flight control linkage, flight monitoring, management, navigation, engine control, and ground communication; the time element, the hazard environment, and the communications capacity estimation are also important factors. The architectures involve several communication technologies, including dedicated links, broadcast busing, and multiplex busing. The multiplex bus system provides the greatest flexibility and installation efficiency. A future homogeneous network system is also proposed, which would be fault and damage tolerant and would, with advanced technology, avoid the problems of designing a very large and flight critical multiplex bus system.
The existing approaches to reliability modeling are briefly reviewed. An examination of the limitations of the existing approaches in modeling ultrareliable fault-tolerant systems illustrates the need to use decomposition techniques. The notion of behavioral decomposition is introduced for dealing with reliability models with a large number of states, and a series of examples is presented. The CARE (computer-aided reliability estimation) and HARP (hybrid automated reliability predictor) approaches to reliability are discussed.
Marine magnetic profiles from the Gulf of Californa are studied in order to revise the estimate of Pacific-North America motion. It is found that since 3 Ma spreading has averaged 48 mm/yr, consistent with a new global plate motion model derived without any data. The present data suggest that strike-slip motion on faults west of the San Andreas is less than previously thought, reducing the San Andreas discrepancy with geodetic, seismological, and other geologic observations.
A validation method for the synchronization subsystem of a fault-tolerant computer system is presented. The high reliability requirement of flight crucial systems precludes the use of most traditional validation methods. The method presented utilizes formal design proof to uncover design and coding errors and experimentation to validate the assumptions of the design proof. The experimental method is described and illustrated by validating an experimental implementation of the Software Implemented Fault Tolerance (SIFT) clock synchronization algorithm. The design proof of the algorithm defines the maximum skew between any two nonfaulty clocks in the system in terms of theoretical upper bounds on certain system parameters. The quantile to which each parameter must be estimated is determined by a combinatorial analysis of the system reliability. The parameters are measured by direct and indirect means, and upper bounds are estimated. A nonparametric method based on an asymptotic property of the tail of a distribution is used to estimate the upper bound of a critical system parameter. Although the proof process is very costly, it is extremely valuable when validating the crucial synchronization subsystem.
Model-based diagnosis is now advanced to the point autonomous systems face some uncertain and faulty situations with success. The next step toward more autonomy is to have the system recovering itself after faults occur, a process known as model-based reconfiguration. After faults occur, given a prediction of the nominal behavior of the system and the result of the diagnosis operation, this paper details how to automatically determine the functional deficiencies of the system. These deficiencies are characterized in the case of uncertain state estimates. A methodology is then presented to determine the reconfiguration goals based on the deficiencies. Finally, a recovery process interleaves planning and model predictive control to restore the functionalities in prioritized order.
During the developmental static fire program for NASAs Reusable Solid Rocket Motor-V (RSRMV), an anomalous erosion condition appeared on the nozzle Carbon Cloth Phenolic nose ring that had not been observed in the space shuttle RSRM program. There were regions of augmented erosion located on the bottom of the forward nose ring (FNR) that measured nine tenths of an inch deeper than the surrounding material. Estimates of heating conditions for the RSRMV nozzle based on limited char and erosion data indicate that the total heat loading into the FNR, for the new five segment motor, is about 40-50% higher than the baseline shuttle RSRM nozzle FNR. Fault tree analysis of the augmented erosion condition has lead to a focus on a thermomechanical response of the material that is outside the existing experience base of shuttle CCP materials for this application. This paper provides a sensitivity study of the CCP material thermo-structural response subject to the design constraints and heating conditions unique to the RSRMV Forward Nose Ring application. Modeling techniques are based on 1-D thermal and porous media calculations where in-depth interlaminar loading conditions are calculated and compared to known capabilities at elevated temperatures. Parameters such as heat rate, in-depth pressures and temperature, degree of char, associated with initiation of the mechanical removal process are quantified and compared to a baseline thermo-chemical material removal mode. Conclusions regarding postulated material loss mechanisms are offered.
During our participation in the NASA Crustal Dynamics Project under NASA contract NAS-27339 and grant NAG5-814 for the period 1982-1991, we published or submitted for publication 30 research papers and 52 abstracts of presentations at scientific meetings. In addition, five M.I.T. Ph.D. students (Eric Bergman, Steven Bratt, Dan Davis, Jeanne Sauber, Anne Sheehan) were supported wholly or in part by this project during their thesis research. Highlights of our research progress during this period include the following: application of geodetic data to determine rates of strain in the Mojave block and in central California and to clarify the relation of such strain to the San Andreas fault and Pacific-North American plate motions; application of geodetic data to infer post seismic deformation associated with large earthquakes in the Imperial Valley, Hebgen Lake, Argentina, and Chile; determination of the state of stress in oceanic lithosphere from a systematic study of the centroid depths and source mechanisms of oceanic intraplate earthquakes; development of models for the state of stress in young oceanic regions arising from the differential cooling of the lithosphere; determination of the depth extent and rupture characteristics of oceanic transform earthquakes; improved determination of earthquake slip vectors in the Gulf of California, an important data set for the estimation of Pacific-North American plate motions; development of models for the state of stress and mechanics of fold-and-thrust belts and accretionary wedges; development of procedures to invert geoid height, residual bathymetry, and differential body wave travel time residuals for lateral variations in the characteristic temperature and bulk composition of the oceanic upper mantle; and initial GPS measurements of crustal deformation associated with the Imperial-Cerro Prieto fault system in southern California and northern Mexico. Full descriptions of the research conducted on these topics may be found in the Semi-Annual status Reports submitted regularly to NASA over the course of this project and in the publications listed.
On Earth, mass wasting events such as rock falls and landslides are well known conse-quences of seismic activity. Through a variety of re-mote sensing techniques, tectonic faults have been pos-itively identified on all four of the inner planets, Earth's Moon, several outer planet satellites, and aster-oids. High-resolution imaging has furthermore ena-bled positive identification of mass wasting events on many of these bodies. On Mars, it has been suggested that fallen boulders may be indicative of pale-omarsquakes. On the Moon, meteor impacts and moonquakes have likewise been suggested as potential triggering mechanisms for mass wasting. Indeed, we know from the Apollo era that the Moon experienc-es a wide variety of seismicity. Seismicity estimates play an important role in creat-ing regional geological characterizations, which are useful not only for understanding a planet's formation and evolution, but also of key importance to site selec-tion for landed missions. Here we investigate the re-gional effects of seismicity in planetary environments with the goal of determining whether surface features such as landslides and boulder trails on the Moon, Mars, and Mercury could be triggered by fault motion. We attempt to quantify the amount of near-source ground shaking necessary to mobilize the mate-rial observed in various instances of mass wasting.
Current planning algorithms have difficulty handling the complexity that is due to an increase in domain uncertainty, and especially in the case of multi-dimensional continuous spaces. Therefore, they produce plans that do not take into account numerous situations that can occur at runtime, such as faults or other changes in the planning domain itself. Thus there is a gap between the plan generation and the reality experienced at runtime. Here we present two methods that allow the plan conditionals to be revised w.r.t. uncertainty on the system as estimated at runtime.
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.
The design of the Hybrid Automated Reliability Predictor (HARP), now under development at Duke University, is presented. The HARP approach to reliability prediction is characterized by a decomposition of the overall model into fault-occurrence and fault-handling sub-models. The fault-occurrence model is a non-homogeneous Markov chain which is solved analytically, while the fault-handling model is a Petri Net which is simulated. HARP provides automated analysis of sensitivity to uncertainties in the input parameters and in the initial state specifications. It then produces a predicted reliability band as a function of mission time, as well as estimates of the improvement (narrowing of the band) to be gained by a specified amount of reduction in uncertainty.
ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.
We present a test methodology for estimating system error rates of Field Programmable Gate Arrays (FPGAs) mitigated with Triple Modular Redundancy (TMR). The test methodology is founded in a mathematical model, which is also presented. Accelerator data from 90 nm Xilins Military/Aerospace grade FPGA are shown to fit the model. Fault injection (FI) results are discussed and related to the test data. Design implementation and the corresponding impact of multiple bit upset (MBU) are also discussed.
Across southern Alaska the northwest directed subduction of the Pacific plate is accompanied by accretion of the Yakutat terrane to continental Alaska. This has led to high tectonic strain rates and dramatic topographic relief of more than 5000 meters within 15 km of the Gulf of Alaska coast. The glaciers of this area are extensive and include large glaciers undergoing wastage (glacier retreat and thinning) and surges. The large glacier ice mass changes perturb the tectonic rate of deformation at a variety of temporal and spatial scales. We estimated surface displacements and stresses associated with ice mass fluctuations and tectonic loading by examining GPS geodetic observations and numerical model predictions. Although the glacial fluctuations perturb the tectonic stress field, especially at shallow depths, the largest contribution to ongoing crustal deformation is horizontal tectonic strain due to plate convergence. Tectonic forces are thus the primary force responsible for major earthquakes. However, for geodetic sites located < 10-20 km from major ice mass fluctuations, the changes of the solid Earth due to ice loading and unloading are an important aspect of interpreting geodetic results. The ice changes associated with Bering Glacier s most recent surge cycle are large enough to cause discernible surface displacements. Additionally, ice mass fluctuations associated with the surge cycle can modify the short-term seismicity rates in a local region. For the thrust faulting environment of the study region a large decrease in ice load may cause an increase in seismic rate in a region close to failure whereas ice loading may inhibit thrust faulting.
A parameter and structure estimation technique for multivariable systems is used to obtain a state space representation of open loop dynamics of the space shuttle main engine in alpha-canonical form. The parameterization being used is both minimal and unique. The simplified linear model may be used for fault detection studies and control system design and development.