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We propose a method for the application of single event upset (SEU) data towards the analysis of complex systems using transformed reliability models (from the time domain to the particle fluence domain) and space environment data.
Orbital Acceleration Research Experiment (OARE) data on Space Transportation System (STS)-50 have been examined in detail during a 2-day time period. Absolute acceleration levels have been derived at the OARE location, the orbiter center-of-gravity, and at the STS-50 spacelab Crystal Growth Facility. During the interval, the tri-axial OARE raw telemetered acceleration measurements have been filtered using a sliding trimmed mean filter in order to remove large acceleration spikes (e.g., thrusters) and reduce the noise. Twelve OARE measured biases in each acceleration channel during the 2-day interval have been analyzed and applied to the filtered data. Similarly, the in situ measured x-axis scale factors in the sensor's most sensitive range were also analyzed and applied to the data. Due to equipment problem(s) on this flight, both y- and z-axis sensitive range scale factors were determined in a separate process using orbiter maneuvers and subsequently applied to the data. All known significant low-frequency corrections at the OARE location (i.e., both vertical and horizontal gravity-gradient, and rotational effects) were removed from the filtered data in order to produce the acceleration components at the orbiter center-of-gravity, which are the aerodynamic signals along each body axis. Results indicate that there is a force being applied to the Orbiter in addition to the aerodynamic forces. The OARE instrument and all known gravitational and electromagnetic forces have been reexamined, but none produces the observed effect. Thus, it is tentatively concluded that the orbiter is creating the environment observed. At least part of this force is thought to be due to the Flash Evaporator System.
This talk focuses on the determination of state-space models for large space systems using only the output data. The output data could be generated by the unknown or deliberate initial conditions of the space structure in question. We shall review some relevant fundamental work on the state-space modeling of sequential output data that is potentially applicable to large space structures. If formulated in terms of some generalized Markov parameters, this approach is in some sense similar to, but much simpler than, the Juang-Pappa Eigensystem Realization Algorithm (ERA) and the Ho-Kalman construction procedure.
The Software Cost and Quality Engineering methodology developed over the last two decades at IBM Federal Sector Div. is used to plan the NASA Space Station Data Management System (DMS). An ongoing project to capture this methodology, which is built on a foundation of experiences and lessons learned, has resulted in the development of a PC-based tool that integrates cost and quality forecasting methodologies and data in a consistent manner. This tool, Software Cost and Quality Engineering Starter Set (SCQESS), is being used to assist in the DMS costing exercises. At the same time, DMS planning serves as a forcing function and provides a platform for the continuing, iterative development, calibration, and validation and verification of SCQESS. The data that forms the cost and quality engineering data base is derived from more than 17 years of development of NASA Space Shuttle software, ranging from low criticality, low complexity support tools to highly complex and highly critical onboard software.
The results are presented of a study to generate a functional system design of a multiprocessing computer system capable of satisfying the computational requirements of a space station. These data management system requirements were specified to include: (1) real time control, (2) data processing and storage, (3) data retrieval, and (4) remote terminal servicing.
Automated Reliability/Availability/Maintainability (ARAM) computer program one of software tools designed to assess candidate architectures of data-management system of the Space Station. Evaluates reliability, availability, and maintainability characteristcs of conceptual system. Uses data representing redundancy and maintainability characteristics of system, and reliability parameters of components of equipment. Design based upon simulation of failures and possible subsequent repairs of each unit of equipment included in system. Analyzes effects of failures and repairs on system and maintains statistics of behavior of system from which results of simulation obtained. Written for IBM PC XT/AT or compatible computer.
This paper describes a new algorithm, called SourceDoubls, which efficiently solves for singletons and doubletons of a digraph reliability model. Compared with previous methods, the SourceDoubls algorithm provides up to a two order of magnitude reduction in the amount of time required to solve large digraph models. This significant increase in model solution speed allows complex digraphs containing thousands of nodes to be used as knowledge bases for real time automated monitoring and diagnosis applications. Currently, an application to provide monitoring and diagnosis of the Space Station Freedom Data Management System is under development at NASA/Ames Research Center and NASA/Johnson Space Center. This paper contains an overview of this system and provides details of how it will use digraph models processed by the SourceDoubls algorithm to accomplish its task.
The Safety and Mission Assurance (S&MA) Directorate is responsible for mitigating risk, providing system safety, and lowering risk for space programs from ground to space. The S&MA is divided into 4 divisions: The Space Exploration Division (NC), the International Space Station Division (NE), the Safety & Test Operations Division (NS), and the Quality and Flight Equipment Division (NT). The interns, myself and Arun Aruljothi, will be working with the Risk & Reliability Analysis Branch under the NC Division's. The mission of this division is to identify, characterize, diminish, and communicate risk by implementing an efficient and effective assurance model. The team utilizes Reliability and Maintainability (R&M) and Probabilistic Risk Assessment (PRA) to ensure decisions concerning risks are informed, vehicles are safe and reliable, and program/project requirements are realistic and realized. This project pertains to the Orion mission, so it is geared toward a long duration Human Space Flight Program(s). For space missions, payload is a critical concept; balancing what hardware can be replaced by components verse by Orbital Replacement Units (ORU) or subassemblies is key. For this effort a database was created that combines mass and reliability data, called Mass and Reliability System or MaRS. The U.S. International Space Station (ISS) components are used as reference parts in the MaRS database. Using ISS components as a platform is beneficial because of the historical context and the environment similarities to a space flight mission. MaRS uses a combination of systems: International Space Station PART for failure data, Vehicle Master Database (VMDB) for ORU & components, Maintenance & Analysis Data Set (MADS) for operation hours and other pertinent data, & Hardware History Retrieval System (HHRS) for unit weights. MaRS is populated using a Visual Basic Application. Once populated, the excel spreadsheet is comprised of information on ISS components including: operation hours, random/nonrandom failures, software/hardware failures, quantity, orbital replaceable units (ORU), date of placement, unit weight, frequency of part, etc. The motivation for creating such a database will be the development of a mass/reliability parametric model to estimate mass required for replacement parts. Once complete, engineers working on future space flight missions will have access a mean time to failures and on parts along with their mass, this will be used to make proper decisions for long duration space flight missions
A hybrid state-space controller is developed for suboptimal digital control of multirate multiloop multivariable continuous-time systems. First, an LQR is designed for a continuous-time subsystem which has a large bandwidth and is connnected in the inner loop of the overall system. The designed LQR would optimally place the eigenvalues of a closed-loop subsystem in the common region of an open sector bounded by sector angles + or - pi/2k for k = 2 or 3 from the negative real axis and the left-hand side of a vertical line on the negative real axis in the s-plane. Then, the developed continuous-time state-feedback gain is converted into an equivalent fast-rate discrete-time state-feedback gain via a digital redesign technique (Tsai et al. 1989, Shieh et al. 1990) reviewed here. A real state reconstructor is redeveloped utilizing the fast-rate input-output data of the system of interest. The design procedure of multiloop multivariable systems using multirate samplers is shown, and a terminal homing missile system example is used to demonstrate the effectiveness of the proposed method.
The Space Station Data Management System (DMS), associated computing subsystems, and applications have varying degrees of reliability associated with their operation. A model has been developed (McKay '86) which allows the DMS runtime environment to appear as an Ada virtual machine to applications executing within it. This model is modular, flexible, and dynamically configurable to allow for evolution and growth over time. Support for Fault-tolerant computing is included within this model. The basic primitive involved in this support is based on atomic actions (Grey '78). An atomic action possesses two fundamental properties: (1) it is indivisible with respect to concurrent actions, and (2) it is indivisible with respect to failure. A transaction is a collection of atomic actions which collectively appear to be one action. Transactions may be nested, providing even more powerful support for reliability. A proposed approach is described for providing support for nested atomic transactions within the Ada runtime model developed for the Space Station environment. The level of support is modular, flexible and dynamically configurable just like the overall runtime support environment.
This paper addresses the application of identification techniques to flight data from the Space Shuttle Remote Manipulator System (RMS). A description of the remote manipulator, including structural and control system characteristics, sensors, and actuators is given. A brief overview of system identification procedures is presented, and the practical aspects of implementing system identification algorithms are discussed. In particular, the problems posed by desampling rate, numerical error, and system nonlinearities are considered. Simulation predictions of damping, frequency, and system order are compared with values identified from flight data to support an evaluation of RMS structural and control system models. Finally, conclusions are drawn regarding the application of identification techniques to flight data obtained from a flexible space structure.
We often look "through a glass, darkly" at solar system bodies with tenuous atmospheres and direct surface exposure to the local space environment. Space weathering exposure acts via universal space-surface interaction processes to produce a thin patina of outer material covering, potentially obscuring endogenic surface materials of greatest interest for understanding origins and interior evolution. Examples of obscuring exogenic layers are radiation crusts on cometary nuclei and iogenic components of sulfate hydrate deposits on the trailing hemisphere of Europa. Weathering processes include plasma ion implantation into surfaces, sputtering by charged particles and solar ultraviolet photons, photolytic chemistry driven by UV irradiation, and radiolytic chemistry evolving from products of charged particle irradiation. Regolith structure from impacts, and underlying deeper structures from internal evolution, affects efficacy of certain surface interactions, e.g. sputtering as affected by porosity and surface irradiation dosage as partly attenuated by local topographic shielding. These processes should be regarded for mission science planning as potentially enabling, e.g. since direct surface sputtering, and resultant surface-bound exospheres, can provide in-situ samples of surface composition to ion and neutral mass spectrometers on orbital spacecraft. Sample return for highest sensitivity compOSitional and structural analyses at Earth will usually be precluded by limited range of surface sampling, long times for return, and high cost. Targeted advancements in instrument technology would be more cost efficient for local remote and in-situ sample analysis. More realistic laboratory simulations, e.g. for bulk samples, are needed to interpret mission science observations of weathered surfaces. Space environment effects on mission spacecraft and science operations must also be specified and mitigated from the hourly to monthly changes in space weather and from longer term (e.g., solar cycle) evolution of space climate. Capable instrumentation on planetary missions can and should be planned to contribute to knowledge of interplanetary space environments. Evolving data system technologies such as virtual observatories should be explored for more interdisciplinary application to the science of planetary surface, atmospheric, magnetospheric, and interplanetary interactions.
The Data Systems Program consists of research and technology devoted to controlling, processing, storing, manipulating, and analyzing space-derived data. The objectives are to provide the technology advancements needed to enable affordable utilization of space-derived data, to increase substantially the capability for future missions of on-board processing and recording and to provide high speed and high volume computational systems anticipated for missions such as the evolutionary Space Station and Earth Observing System. The Data Systems Program supports fundamental research in such areas as laser diodes, supports work to select and provide the appropriate on-board processor technology for future NASA missions, and also supports the development of two flight processors with special architectures.
Deep space data return, discussing system function, design, operational interfaces and interplanetary spacecraft data compression methods
Application of self-sequencing data bus techniques for space shuttle data management system
Procedures for development and verification of complex software used in space shuttle data management system
Reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA) are provided. In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other agencies through NASA.
Modern systems such as fly-by-wire aircraft, nuclear power plants, manufacturing facilities, battlefields, etc., are all examples of highly connected network enabled systems. Many of these systems are also mission critical and need to be monitored round the clock. Such systems typically consist of embedded sensors in networked subsystems that can transmit data to central (or remote) monitoring stations. Moreover, many legacy are safety systems were originally not designed for real-time onboard diagnosis, but a critical and would benefit from such a solution. Embedding additional software or hardware in such systems is often considered too intrusive and introduces flight safety and validation concerns. Such systems can be equipped to transmit the sensor data to a remote-processing center for continuous health monitoring. At Qualtech Systems, we are developing a Remote Diagnosis Server (RDS) that can support multiple simultaneous diagnostic sessions from a variety of remote subsystems.