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At least 181 records · Page 10

Framework for a space shuttle main engine health monitoring system

A framework developed for a health management system (HMS) which is directed at improving the safety of operation of the Space Shuttle Main Engine (SSME) is summarized. An emphasis was placed on near term technology through requirements to use existing SSME instrumentation and to demonstrate the HMS during SSME ground tests within five years. The HMS framework was developed through an analysis of SSME failure modes, fault detection algorithms, sensor technologies, and hardware architectures. A key feature of the HMS framework design is that a clear path from the ground test system to a flight HMS was maintained. Fault detection techniques based on time series, nonlinear regression, and clustering algorithms were developed and demonstrated on data from SSME ground test failures. The fault detection algorithms exhibited 100 percent detection of faults, had an extremely low false alarm rate, and were robust to sensor loss. These algorithms were incorporated into a hierarchical decision making strategy for overall assessment of SSME health. A preliminary design for a hardware architecture capable of supporting real time operation of the HMS functions was developed. Utilizing modular, commercial off-the-shelf components produced a reliable low cost design with the flexibility to incorporate advances in algorithm and sensor technology as they become available.

Hawman, Michael W.↗

Implementing neural nets with programmable logic

Networks of Boolean programmable logic modules are presented as one purely digital class of artificial neural nets. The approach contrasts with the continuous analog framework usually suggested. Programmable logic networks are capable of handling many neural-net applications. They avoid some of the limitations of threshold logic networks and present distinct opportunities. The network nodes are called dynamically programmable logic modules. They can be implemented with digitally controlled demultiplexers. Each node performs a Boolean function of its inputs which can be dynamically assigned. The overall network is therefore a combinational circuit and its outputs are Boolean global functions of the network's input variables. The approach offers definite advantages for VLSI implementation, namely, a regular architecture with limited connectivity, simplicity of the control machinery, natural modularity, and the support of a mature technology.

Vidal, Jacques J.↗

A proposed Applications Information System - Concept, implementation, and growth

This paper describes a newly developed concept within NASA for an Applications Information System (AIS). The AIS would provide the opportunity to the public and private sectors of shared participation in a remote sensing research program directed to a particular set of land-use or environmental problems. Towards this end, the AIS would offer the technological framework and information system resources to overcome many of the deficiencies that end-users have faced over the years such as limited access to data, delay in data delivery, and a limited access to data reduction algorithms and models to convert data to geophysical measurements. In addition, the AIS will take advantage of NASA developments in networking among information systems and use of state of the art technology, such as CD Roms and optical disks for the purpose of increasing the scientific benefits of applied environmental research. The rationale for the establishment of an AIS, a methodology for a step-wise, modular implementation, and the relationship of the AIS to other NASA information systems are discussed.

Mcconnell, Dudley G.↗

Design for Verification: Using Design Patterns to Build Reliable Systems

Components so far have been mainly used in commercial software development to reduce time to market. While some effort has been spent on formal aspects of components, most of this was done in the context of programming language or operating system framework integration. As a consequence, increased reliability of composed systems is mainly regarded as a side effect of a more rigid testing of pre-fabricated components. In contrast to this, Design for Verification (D4V) puts the focus on component specific property guarantees, which are used to design systems with high reliability requirements. D4V components are domain specific design pattern instances with well-defined property guarantees and usage rules, which are suitable for automatic verification. The guaranteed properties are explicitly used to select components according to key system requirements. The D4V hypothesis is that the same general architecture and design principles leading to good modularity, extensibility and complexity/functionality ratio can be adapted to overcome some of the limitations of conventional reliability assurance measures, such as too large a state space or too many execution paths.

Mehlitz, Peter C.↗

Reference Avionics Architecture for Lunar Surface Systems

Developing and delivering infrastructure capable of supporting long-term manned operations to the lunar surface has been a primary objective of the Constellation Program in the Exploration Systems Mission Directorate. Several concepts have been developed related to development and deployment lunar exploration vehicles and assets that provide critical functionality such as transportation, habitation, and communication, to name a few. Together, these systems perform complex safety-critical functions, largely dependent on avionics for control and behavior of system functions. These functions are implemented using interchangeable, modular avionics designed for lunar transit and lunar surface deployment. Systems are optimized towards reuse and commonality of form and interface and can be configured via software or component integration for special purpose applications. There are two core concepts in the reference avionics architecture described in this report. The first concept uses distributed, smart systems to manage complexity, simplify integration, and facilitate commonality. The second core concept is to employ extensive commonality between elements and subsystems. These two concepts are used in the context of developing reference designs for many lunar surface exploration vehicles and elements. These concepts are repeated constantly as architectural patterns in a conceptual architectural framework. This report describes the use of these architectural patterns in a reference avionics architecture for Lunar surface systems elements.

Somervill, Kevin M.↗

A Partitioned - Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a platform for multiscale modeling of composites which can perform analysis of materials with any arbitrary number of length scales. The platform supports modularity, scalability, and interoperability using recursive procedures and data structures. A Macro solver driven parallelization scheme often limits the capability of NASMAT to scale as it has access to limited memory and number of cores (often one core/thread) and often forces to implement macro solver specific changes to the platform. In this work, a partitioned task-parallel approach is adopted, where the parallelization strategy adopted for NASMAT is independent of the macro solver and the computational resources are managed independently. The programming architecture takes into account the hierarchy of multiple scales (task-dependence) and the heterogeneous nature (dynamic load balancing) of computation through implementation of a hierarchy-informed task parallel model. The partitioned nature of the framework further extends the “plug and play” capability of NASMAT. preCICE, an open-source library for coupling multiphysics solver in a partitioned manner, is adopted to integrate NASMAT with an external macro solver by implementing a NASMAT adapter for preCICE. Speedup and scalability of the framework is studied for micromechanical models of varying size.

task-parallel↗

A programming environment for distributed complex computing. An overview of the Framework for Interdisciplinary Design Optimization (FIDO) project. NASA Langley TOPS exhibit H120b

The Framework for Interdisciplinary Design Optimization (FIDO) is a general programming environment for automating the distribution of complex computing tasks over a networked system of heterogeneous computers. For example, instead of manually passing a complex design problem between its diverse specialty disciplines, the FIDO system provides for automatic interactions between the discipline tasks and facilitates their communications. The FIDO system networks all the computers involved into a distributed heterogeneous computing system, so they have access to centralized data and can work on their parts of the total computation simultaneously in parallel whenever possible. Thus, each computational task can be done by the most appropriate computer. Results can be viewed as they are produced and variables changed manually for steering the process. The software is modular in order to ease migration to new problems: different codes can be substituted for each of the current code modules with little or no effect on the others. The potential for commercial use of FIDO rests in the capability it provides for automatically coordinating diverse computations on a networked system of workstations and computers. For example, FIDO could provide the coordination required for the design of vehicles or electronics or for modeling complex systems.

Townsend, James C.↗

Implementing Access to Data Distributed on Many Processors

A reference architecture is defined for an object-oriented implementation of domains, arrays, and distributions written in the programming language Chapel. This technology primarily addresses domains that contain arrays that have regular index sets with the low-level implementation details being beyond the scope of this discussion. What is defined is a complete set of object-oriented operators that allows one to perform data distributions for domain arrays involving regular arithmetic index sets. What is unique is that these operators allow for the arbitrary regions of the arrays to be fragmented and distributed across multiple processors with a single point of access giving the programmer the illusion that all the elements are collocated on a single processor. Today's massively parallel High Productivity Computing Systems (HPCS) are characterized by a modular structure, with a large number of processing and memory units connected by a high-speed network. Locality of access as well as load balancing are primary concerns in these systems that are typically used for high-performance scientific computation. Data distributions address these issues by providing a range of methods for spreading large data sets across the components of a system. Over the past two decades, many languages, systems, tools, and libraries have been developed for the support of distributions. Since the performance of data parallel applications is directly influenced by the distribution strategy, users often resort to low-level programming models that allow fine-tuning of the distribution aspects affecting performance, but, at the same time, are tedious and error-prone. This technology presents a reusable design of a data-distribution framework for data parallel high-performance applications. Distributions are a means to express locality in systems composed of large numbers of processor and memory components connected by a network. Since distributions have a great effect on the performance of applications, it is important that the distribution strategy is flexible, so its behavior can change depending on the needs of the application. At the same time, high productivity concerns require that the user be shielded from error-prone, tedious details such as communication and synchronization.

James, Mark↗

SPARTAN: A High-Fidelity Simulation for Automated Rendezvous and Docking Applications

bd Systems (a subsidiary of SAIC) has developed the Simulation Package for Autonomous Rendezvous Test and ANalysis (SPARTAN), a high-fidelity on-orbit simulation featuring multiple six-degree-of-freedom (6DOF) vehicles. SPARTAN has been developed in a modular fashion in Matlab/Simulink to test next-generation automated rendezvous and docking guidance, navigation,and control algorithms for NASA's new Vision for Space Exploration. SPARTAN includes autonomous state-based mission manager algorithms responsible for sequencing the vehicle through various flight phases based on on-board sensor inputs and closed-loop guidance algorithms, including Lambert transfers, Clohessy-Wiltshire maneuvers, and glideslope approaches The guidance commands are implemented using an integrated translation and attitude control system to provide 6DOF control of each vehicle in the simulation. SPARTAN also includes high-fidelity representations of a variety of absolute and relative navigation sensors that maybe used for NASA missions, including radio frequency, lidar, and video-based rendezvous sensors. Proprietary navigation sensor fusion algorithms have been developed that allow the integration of these sensor measurements through an extended Kalman filter framework to create a single optimal estimate of the relative state of the vehicles. SPARTAN provides capability for Monte Carlo dispersion analysis, allowing for rigorous evaluation of the performance of the complete proposed AR&D system, including software, sensors, and mechanisms. SPARTAN also supports hardware-in-the-loop testing through conversion of the algorithms to C code using Real-Time Workshop in order to be hosted in a mission computer engineering development unit running an embedded real-time operating system. SPARTAN also contains both runtime TCP/IP socket interface and post-processing compatibility with bdStudio, a visualization tool developed by bd Systems, allowing for intuitive evaluation of simulation results. A description of the SPARTAN architecture and capabilities is provided, along with details on the models and algorithms utilized and results from representative missions.

Turbe, Michael A.↗

NASA Tech Briefs, April 2012

Topics include: Computational Ghost Imaging for Remote Sensing; Digital Architecture for a Trace Gas Sensor Platform; Dispersed Fringe Sensing Analysis - DFSA; Indium Tin Oxide Resistor-Based Nitric Oxide Microsensors; Gas Composition Sensing Using Carbon Nanotube Arrays; Sensor for Boundary Shear Stress in Fluid Flow; Model-Based Method for Sensor Validation; Qualification of Engineering Camera for Long-Duration Deep Space Missions; Remotely Powered Reconfigurable Receiver for Extreme Environment Sensing Platforms; Bump Bonding Using Metal-Coated Carbon Nanotubes; In Situ Mosaic Brightness Correction; Simplex GPS and InSAR Inversion Software; Virtual Machine Language 2.1; Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction; Pandora Operation and Analysis Software; Fabrication of a Cryogenic Bias Filter for Ultrasensitive Focal Plane; Processing of Nanosensors Using a Sacrificial Template Approach; High-Temperature Shape Memory Polymers; Modular Flooring System; Non-Toxic, Low-Freezing, Drop-In Replacement Heat Transfer Fluids; Materials That Enhance Efficiency and Radiation Resistance of Solar Cells; Low-Cost, Rugged High-Vacuum System; Static Gas-Charging Plug; Floating Oil-Spill Containment Device; Stemless Ball Valve; Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs; Oxygen-Methane Thruster; Lunar Navigation Determination System - LaNDS; Launch Method for Kites in Low-Wind or No-Wind Conditions; Supercritical CO2 Cleaning System for Planetary Protection and Contamination Control Applications; Design and Performance of a Wideband Radio Telescope; Finite Element Models for Electron Beam Freeform Fabrication Process Autonomous Information Unit for Fine-Grain Data Access Control and Information Protection in a Net-Centric System; Vehicle Detection for RCTA/ANS (Autonomous Navigation System); Image Mapping and Visual Attention on the Sensory Ego-Sphere; HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis; and IMAGESEER - IMAGEs for Education and Research.

Source record↗

Towards an Open, Distributed Software Architecture for UxS Operations

To address the growing need to evaluate, test, and certify an ever expanding ecosystem of UxS platforms in preparation of cultural integration, NASA Langley Research Center's Autonomy Incubator (AI) has taken on the challenge of developing a software framework in which UxS platforms developed by third parties can be integrated into a single system which provides evaluation and testing, mission planning and operation, and out-of-the-box autonomy and data fusion capabilities. This software framework, named AEON (Autonomous Entity Operations Network), has two main goals. The first goal is the development of a cross-platform, extensible, onboard software system that provides autonomy at the mission execution and course-planning level, a highly configurable data fusion framework sensitive to the platform's available sensor hardware, and plug-and-play compatibility with a wide array of computer systems, sensors, software, and controls hardware. The second goal is the development of a ground control system that acts as a test-bed for integration of the proposed heterogeneous fleet, and allows for complex mission planning, tracking, and debugging capabilities. The ground control system should also be highly extensible and allow plug-and-play interoperability with third party software systems. In order to achieve these goals, this paper proposes an open, distributed software architecture which utilizes at its core the Data Distribution Service (DDS) standards, established by the Object Management Group (OMG), for inter-process communication and data flow. The design decisions proposed herein leverage the advantages of existing robotics software architectures and the DDS standards to develop software that is scalable, high-performance, fault tolerant, modular, and readily interoperable with external platforms and software.

Cross, Charles D.↗

Forced Response Aeromechanics Analysis in MATLAB®-Based Environment Code With Application to Distortion-Tolerant Fan R24 Blade Geometry

Researchers at the NASA Glenn Research Center have developed a research-level code for forced response analysis for turbomachinery that provides a streamlined framework for aeromechanics analysis, as well as for generating Goodman diagrams. The Forced Response Aeromechanics Analysis in a MATLAB-Based Environment (FRAAME, Version 1) code is designed to accept blade surface unsteady pressure time histories generated by three-dimensional (3D) Unsteady Reynolds-Averaged Navier-Stokes (URANS) code TURBO and modal displacements, modal stresses, and static stresses generated via expanded ANSYS® (Ansys, Inc.) cyclic symmetry analysis. The code’s looping structure allows for largescale analyses, including many blade surface pressure files, modal displacements, and modal stress files for full annulus forced response analysis, including a modal summation method for multiple engine orders and modes. This code is applied to the R24 fan geometry for the Boundary Layer Ingesting Inlet/Distortion-Tolerant Fan (BLI2DTF) project, a propulsion system being developed to increase the fuel efficiency of future aircraft, to serve as validation of experimental data as well as external simulation results. This tool’s functional, modular form is intended to allow users to make modifications easily. Those modifications can include requests for information for any step in the analysis process, as well as adding various functions to compute additional information of interest. It is also written, given sufficient input information, as a general blade geometry forced response solver that is not necessarily specific to the R24 geometry but is used here for verification of code functionality and accuracy. Although forced response analysis tools are also available in commercially available code packages, the post-processing FRAAME code offers reliable, fast, and scalable forced response analysis and Goodman diagram generation for large cases utilizing, specifically, TURBO and ANSYS® results information in an effort to streamline forced response and high cycle fatigue analyses.

Aeromechanics↗

A Model-Based Framework for NASA Science Mission Formulation

This paper details an effort to implement NASA systems engineering standards and practices using a Digital System Model (DSM), which we also refer to as the system architecture model (SAM). Creating a SAM at the beginning of a design effort helps systems engineer identify errors, inconsistencies, and miscommunications as early as possible. Such issues can then be resolved before it becomes costly and requires significant rework to do so. A pre-formulation SAM also enables advanced trade studies at the earliest stage of concept development. This results in “win-wins” where architecture changes can reduce cost without decreasing effectiveness, or increase effectiveness without increasing cost. SAMs also streamline the creation of project documentation and facilitate superior dialogue between science, engineering, and management stakeholders. Common artifacts such as Master Equipment Lists (MELs), Science Traceability Matrices (STMs), and Mission Traceability Matrices (MTMs), can be automatically maintained through requirements and structural models in the SAM. Key performance parameters (and changes to them) can be tied to simulations in the SAM, allowing far more rapid and extensive trade space exploration. As will be shown in this work, these advantages have been realized for the first time in an actual NASA Goddard Space Flight Center (GSFC) pre-phase A and phase A concept study. Modelbased design tools have been developed in a general, modular manner to maximize reuse on future programs. Focus is placed on structural and requirements architecture modeling. Data is ingested into the SAM from existing discipline model outputs (e.g. MS Excel spreadsheets) and used to update a SysML structural model. A mission requirements model is created within the SAM, containing mission specific as well as standard GSFC mission requirements. With the linked requirements model and structural model, automated compliance checking will be performed as mission parameters evolve without the need for discipline engineers to work directly with the SAM in SysML.

MBSE↗

Toward Coupled Data Assimilation in NASA’s GEOS: Developments in the Ocean Context

The Global Modeling & Assimilation Office (GMAO) at NASA GSFC produces analyses and predictions of the Earth system using various configurations of the Goddard Earth Observing System (GEOS) model and assimilation system. The current sub-seasonal-to-seasonal prediction system (GEOS-S2S) is based on a coupled atmosphere-ocean-land-ice configuration of GEOS which includes the Modular Ocean Model version 5 (MOM5) run at approximately 50-km resolution and a de-coupled OI-based ocean analysis that uses an initialization of MOM5 forced by the MERRA-2 reanalysis. GMAO will soon implement an updated GEOS-S2S system that will run at 25-km resolution and adopt aspects of the hybrid four-dimensional ensemble-variational (H4DEnVar) system already running in the production-version atmospheric analysis system, including a Local Ensemble Transform Kalman Filter (LETKF) to provide initial conditions for the oceanic state. This presentation will focus on developments to sustain the GMAO's systems on longer time horizons, where more radical transformations will be required to adapt to advanced computing environments, higher resolution and more diverse model components, and new observations for the Earth system. Results will describe progress toward a version of the GEOS coupled system that will be based around the Joint Effort for Data assimilation Integration (JEDI) framework being developed within Joint Center for Satellite Data Assimilation (JCSDA) and include an updated ocean model, MOM6. Discussion will focus specifically on the use of a Unified Forward Operator (UFO) for simulating observations and the Object Oriented Prediction System (OOPS) for providing the state estimate. These features are being developed as a multi-agency effort under the auspices of the JCSDA and are being adopted in the GMAO for all its applications of coupled data assimilation including S2S, numerical weather prediction, and reanalysis.

Mahajan, Rahul↗

Cislunar space infrastructure: Lunar technologies

Continuing its emphasis on the creation of a cisluar infrastructure as an appropriate and cost-effective method of space exploration and development, the University of Colorado explores the technologies necessary for the creation of such an infrastructure, namely (1) automation and robotics; (2) life support systems; (3) fluid management; (4) propulsion; and (5) rotating technologes. The technological focal point is on the development of automated and robotic systems for the implementation of a Lunar Oasis produced by automation and robotics (LOARS). Under direction from the NASA Office of Exploration, automation and robotics have been extensively utilized as an initiating stage in the return to the Moon. A pair of autonomous rovers, modular in design and built from interchangeable and specialized components, is proposed. Utilizing a 'buddy system', these rovers will be able to support each other and to enhance their individual capabilities. One rover primarily explores and maps while the second rover tests the feasibility of various materials-processing techniques. The automated missions emphasize availability and potential uses of lunar resources and the deployment and operations of the LOAR program. An experimental bio-volume is put into place as the precursor to a Lunar Environmentally Controlled Life Support System. The bio-volume will determine the reproduction, growth and production characteristics of various life forms housed on the lunar surface. Physiochemical regenerative technologies and stored resources will be used to buffer biological disturbances of the bio-volume environment. The in situ lunar resources will be both tested and used within this bio-volume. Second phase development on the lunar surface calls for manned operations. Repairs and reconfiguration of the initial framework will ensue. An autonomously initiated, manned Lunar Oasis can become an essential component of the United States space program. The Lunar Oasis will provide support to science, technology, and commerce. It will enable more cost-effective space exploration to the planets and beyond.

W. Faller↗

CIS-lunar space infrastructure lunar technologies: Executive summary

Technologies necessary for the creation of a cis-Lunar infrastructure, namely: (1) automation and robotics; (2) life support systems; (3) fluid management; (4) propulsion; and (5) rotating technologies, are explored. The technological focal point is on the development of automated and robotic systems for the implementation of a Lunar Oasis produced by Automation and Robotics (LOAR). Under direction from the NASA Office of Exploration, automation and robotics were extensively utilized as an initiating stage in the return to the Moon. A pair of autonomous rovers, modular in design and built from interchangeable and specialized components, is proposed. Utilizing a buddy system, these rovers will be able to support each other and to enhance their individual capabilities. One rover primarily explores and maps while the second rover tests the feasibility of various materials-processing techniques. The automated missions emphasize availability and potential uses of Lunar resources, and the deployment and operations of the LOAR program. An experimental bio-volume is put into place as the precursor to a Lunar environmentally controlled life support system. The bio-volume will determine the reproduction, growth and production characteristics of various life forms housed on the Lunar surface. Physicochemical regenerative technologies and stored resources will be used to buffer biological disturbances of the bio-volume environment. The in situ Lunar resources will be both tested and used within this bio-volume. Second phase development on the Lunar surface calls for manned operations. Repairs and re-configuration of the initial framework will ensue. An autonomously-initiated manned Lunar oasis can become an essential component of the United States space program.

Faller, W.↗

Decentralized Formation Flying Control in a Multiple-Team Hierarchy

This paper presents the prototype of a system that addresses these objectives-a decentralized guidance and control system that is distributed across spacecraft using a multiple-team framework. The objective is to divide large clusters into teams of manageable size, so that the communication and computational demands driven by N decentralized units are related to the number of satellites in a team rather than the entire cluster. The system is designed to provide a high-level of autonomy, to support clusters with large numbers of satellites, to enable the number of spacecraft in the cluster to change post-launch, and to provide for on-orbit software modification. The distributed guidance and control system will be implemented in an object-oriented style using MANTA (Messaging Architecture for Networking and Threaded Applications). In this architecture, tasks may be remotely added, removed or replaced post-launch to increase mission flexibility and robustness. This built-in adaptability will allow software modifications to be made on-orbit in a robust manner. The prototype system, which is implemented in MATLAB, emulates the object-oriented and message-passing features of the MANTA software. In this paper, the multiple-team organization of the cluster is described, and the modular software architecture is presented. The relative dynamics in eccentric reference orbits is reviewed, and families of periodic, relative trajectories are identified, expressed as sets of static geometric parameters. The guidance law design is presented, and an example reconfiguration scenario is used to illustrate the distributed process of assigning geometric goals to the cluster. Next, a decentralized maneuver planning approach is presented that utilizes linear-programming methods to enact reconfiguration and coarse formation keeping maneuvers. Finally, a method for performing online collision avoidance is discussed, and an example is provided to gauge its performance.

Mueller, Joseph .↗

HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis

Hybrid Diagnosis Engine (HyDE) is a general framework for stochastic and hybrid model-based diagnosis that offers flexibility to the diagnosis application designer. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. Several alternative algorithms are available for the various steps in diagnostic reasoning. This approach is extensible, with support for the addition of new modeling paradigms as well as diagnostic reasoning algorithms for existing or new modeling paradigms. HyDE is a general framework for stochastic hybrid model-based diagnosis of discrete faults; that is, spontaneous changes in operating modes of components. HyDE combines ideas from consistency-based and stochastic approaches to model- based diagnosis using discrete and continuous models to create a flexible and extensible architecture for stochastic and hybrid diagnosis. HyDE supports the use of multiple paradigms and is extensible to support new paradigms. HyDE generates candidate diagnoses and checks them for consistency with the observations. It uses hybrid models built by the users and sensor data from the system to deduce the state of the system over time, including changes in state indicative of faults. At each time step when observations are available, HyDE checks each existing candidate for continued consistency with the new observations. If the candidate is consistent, it continues to remain in the candidate set. If it is not consistent, then the information about the inconsistency is used to generate successor candidates while discarding the candidate that was inconsistent. The models used by HyDE are similar to simulation models. They describe the expected behavior of the system under nominal and fault conditions. The model can be constructed in modular and hierarchical fashion by building component/subsystem models (which may themselves contain component/ subsystem models) and linking them through shared variables/parameters. The component model is expressed as operating modes of the component and conditions for transitions between these various modes. Faults are modeled as transitions whose conditions for transitions are unknown (and have to be inferred through the reasoning process). Finally, the behavior of the components is expressed as a set of variables/ parameters and relations governing the interaction between the variables. The hybrid nature of the systems being modeled is captured by a combination of the above transitional model and behavioral model. Stochasticity is captured as probabilities associated with transitions (indicating the likelihood of that transition being taken), as well as noise on the sensed variables.

Narasimhan, Sriram↗