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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22

Enhanced CARES Software Enables Improved Ceramic Life Prediction

The NASA Lewis Research Center has developed award-winning software that enables American industry to establish the reliability and life of brittle material (e.g., ceramic, intermetallic, graphite) structures in a wide variety of 21st century applications. The CARES (Ceramics Analysis and Reliability Evaluation of Structures) series of software is successfully used by numerous engineers in industrial, academic, and government organizations as an essential element of the structural design and material selection processes. The latest version of this software, CARES/Life, provides a general- purpose design tool that predicts the probability of failure of a ceramic component as a function of its time in service. CARES/Life was recently enhanced by adding new modules designed to improve functionality and user-friendliness. In addition, a beta version of the newly-developed CARES/Creep program (for determining the creep life of monolithic ceramic components) has just been released to selected organizations.

Janosik, Lesley A.↗

Ceramics Analysis

Lewis Research Center developed the CARES/LIFE software, which predicts the performance of brittle structures over time, such as ceramic compounds. Over 300 companies have used a version of the code, including Philips Display Components Company, AlliedSignal, Solar Turbines Incorporated, and TRW, Inc. for everything from engines to television tubes. The software enables a designer to test a variety of configurations for probability of failure and to adjust the structure's geometry to minimize the predicted failure or maximize durability for the lifetime of the ceramic component.

Source record↗

A Generic Modeling Process to Support Functional Fault Model Development

Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.

Design Analysis↗

The Use of Probabilistic Methods to Evaluate the Systems Impact of Component Design Improvements on Large Turbofan Engines

Probabilistic Structural Analysis (PSA) is now commonly used for predicting the distribution of time/cycles to failure of turbine blades and other engine components. These distributions are typically based on fatigue/fracture and creep failure modes of these components. Additionally, reliability analysis is used for taking test data related to particular failure modes and calculating failure rate distributions of electronic and electromechanical components. How can these individual failure time distributions of structural, electronic and electromechanical component failure modes be effectively combined into a top level model for overall system evaluation of component upgrades, changes in maintenance intervals, or line replaceable unit (LRU) redesign? This paper shows an example of how various probabilistic failure predictions for turbine engine components can be evaluated and combined to show their effect on overall engine performance. A generic model of a turbofan engine was modeled using various Probabilistic Risk Assessment (PRA) tools (Quantitative Risk Assessment Software (QRAS) etc.). Hypothetical PSA results for a number of structural components along with mitigation factors that would restrict the failure mode from propagating to a Loss of Mission (LOM) failure were used in the models. The output of this program includes an overall failure distribution for LOM of the system. The rank and contribution to the overall Mission Success (MS) is also given for each failure mode and each subsystem. This application methodology demonstrates the effectiveness of PRA for assessing the performance of large turbine engines. Additionally, the effects of system changes and upgrades, the application of different maintenance intervals, inclusion of new sensor detection of faults and other upgrades were evaluated in determining overall turbine engine reliability.

Packard, Michael H.↗

Contingency Software in Autonomous Systems

This viewgraph presentation reviews the development of contingency software for autonomous systems. Autonomous vehicles currently have a limited capacity to diagnose and mitigate failures. There is a need to be able to handle a broader range of contingencies. The goals of the project are: 1. Speed up diagnosis and mitigation of anomalous situations.2.Automatically handle contingencies, not just failures.3.Enable projects to select a degree of autonomy consistent with their needs and to incrementally introduce more autonomy.4.Augment on-board fault protection with verified contingency scripts

autonomous systems↗

The application of automated operations at the Institutional Processing Center

The JPL Institutional and Mission Computing Division, Communications, Computing and Network Services Section, with its mission contractor, OAO Corporation, have for some time been applying automation to the operation of JPL's Information Processing Center (IPC). Automation does not come in one easy to use package. Automation for a data processing center is made up of many different software and hardware products supported by trained personnel. The IPC automation effort formally began with console automation, and has since spiraled out to include production scheduling, data entry, report distribution, online reporting, failure reporting and resolution, documentation, library storage, and operator and user education, while requiring the interaction of multi-vendor and locally developed software. To begin the process, automation goals are determined. Then a team including operations personnel is formed to research and evaluate available options. By acquiring knowledge of current products and those in development, taking an active role in industry organizations, and learning of other data center's experiences, a forecast can be developed as to what direction technology is moving. With IPC management's approval, an implementation plan is developed and resources identified to test or implement new systems. As an example, IPC's new automated data entry system was researched by Data Entry, Production Control, and Advance Planning personnel. A proposal was then submitted to management for review. A determination to implement the new system was made and elements/personnel involved with the initial planning performed the implementation. The final steps of the implementation were educating data entry personnel in the areas effected and procedural changes necessary to the successful operation of the new system.

Barr, Thomas H.↗

Integration of the Remote Agent for the NASA Deep Space One Autonomy Experiment

This paper describes the integration of the Remote Agent (RA), a spacecraft autonomy system which is scheduled to control the Deep Space 1 spacecraft during a flight experiment in 1999. The RA is a reusable, model-based autonomy system that is quite different from software typically used to control an aerospace system. We describe the integration challenges we faced, how we addressed them, and the lessons learned. We focus on those aspects of integrating the RA that were either easier or more difficult than integrating a more traditional large software application because the RA is a model-based autonomous system. A number of characteristics of the RA made integration process easier. One example is the model-based nature of RA. Since the RA is model-based, most of its behavior is not hard coded into procedural program code. Instead, engineers specify high level models of the spacecraft's components from which the Remote Agent automatically derives correct system-wide behavior on the fly. This high level, modular, and declarative software description allowed some interfaces between RA components and between RA and the flight software to be automatically generated and tested for completeness against the Remote Agent's models. In addition, the Remote Agent's model-based diagnosis system automatically diagnoses when the RA models are not consistent with the behavior of the spacecraft. In flight, this feature is used to diagnose failures in the spacecraft hardware. During integration, it proved valuable in finding problems in the spacecraft simulator or flight software. In addition, when modifications are made to the spacecraft hardware or flight software, the RA models are easily changed because they only capture a description of the spacecraft. one does not have to maintain procedural code that implements the correct behavior for every expected situation. On the other hand, several features of the RA made it more difficult to integrate than typical flight software. For example, the definition of correct behavior is more difficult to specify for a system that is expected to reason about and flexibly react to its environment than for a traditional flight software system. Consequently, whenever a change is made to the RA it is more time consuming to determine if the resulting behavior is correct. We conclude the paper with a discussion of future work on the Remote Agent as well as recommendations to ease integration of similar autonomy projects.

Dorais, Gregory A.↗

Software Measurement Guidebook

This Software Measurement Guidebook is based on the extensive experience of several organizations that have each developed and applied significant measurement programs over a period of at least 10 years. The lessons derived from those experiences reflect not only successes but also failures. By applying those lessons, an organization can minimize, or at least reduce, the time, effort, and frustration of introducing a software measurement program. The Software Measurement Guidebook is aimed at helping organizations to begin or improve a measurement program. It does not provide guidance for the extensive application of specific measures (such as how to estimate software cost or analyze software complexity) other than by providing examples to clarify points. It does contain advice for establishing and using an effective software measurement program and for understanding some of the key lessons that other organizations have learned. Some of that advice will appear counterintuitive, but it is all based on actual experience. Although all of the information presented in this guidebook is derived from specific experiences of mature measurement programs, the reader must keep in mind that the characteristics of every organization are unique. Some degree of measurement is critical for all software development and maintenance organizations, and most of the key rules captured in this report will be generally applicable. Nevertheless, each organization must strive to understand its own environment so that the measurement program can be tailored to suit its characteristics and needs.

Source record↗

Progressive Failure Analysis of Composite Stiffened Panels

A new progressive failure analysis capability for stiffened composite panels has been developed based on the combination of the HyperSizer stiffened panel design/analysis/optimization software with the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC). MAC/GMC discretizes a composite material s microstructure into a number of subvolumes and solves for the stress and strain state in each while providing the homogenized composite properties as well. As a result, local failure criteria may be employed to predict local subvolume failure and the effects of these local failures on the overall composite response. When combined with HyperSizer, MAC/GMC is employed to represent the ply level composite material response within the laminates that constitute a stiffened panel. The effects of local subvolume failures can then be tracked as loading on the stiffened panel progresses. Sample progressive failure results are presented at both the composite laminate and the composite stiffened panel levels. Deformation and failure model predictions are compared with experimental data from the World Wide Failure Exercise for AS4/3501-6 graphite/epoxy laminates.

Bednarcyk, Brett A.↗

The Soil Moisture Acttive Passive Mission: Fault Protection Performance and Lessons Learned

Fault protection as a discipline involves a collection of flight software logic and operational processes for detecting unacceptable anomalous behavior, responding prior to reaching criticality, restricting the propagation of a failure beyond a fault containment region, and recovering the vehicle back to full or degraded functionality if possible. The System Fault Protection (SFP) design for the SMAP Earth orbiter was put to the test during its 90-day vehicle commissioning activities. During this time, the SFP software autonomously protected the vehicle from multiple faults to critical hardware, and the operations team successfully returned the observatory to its science state. The SFP also performed well in the presence of anomalous behavior below true safety limits by not taking unnecessary response actions, instead allowing the operations team time to monitor the behavior. Certain aspects of the SFP design were modified during operations via both parameter updates and a full flight software update in order to better match the vehicle behavior in the flight environment. An evaluation of the SMAP SFP performance during vehicle Commissioning will be provided in this paper, as well as a set of lessons learned largely focused on visibility, SFP mutability in operations, responses to peripheral device faults, and Safe Mode recovery and design. By capturing some of the knowledge gained during SMAP Commissioning, it is intended that this paper provide guidance for making future System Fault Protection designs more robust and supportive of operations.

Clark, Jessica↗

A real-time implementation of an advanced sensor failure detection, isolation, and accommodation algorithm

A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation.

Delaat, J. C.↗

A real-time implementation of an advanced sensor failure detection, isolation, and accommodation algorithm

A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation. Previously announced in STAR as N84-13140

Delaat, J. C.↗

Tools for distributed application management

Distributed application management consists of monitoring and controlling an application as it executes in a distributed environment. It encompasses such activities as configuration, initialization, performance monitoring, resource scheduling, and failure response. The Meta system (a collection of tools for constructing distributed application management software) is described. Meta provides the mechanism, while the programmer specifies the policy for application management. The policy is manifested as a control program which is a soft real-time reactive program. The underlying application is instrumented with a variety of built-in and user-defined sensors and actuators. These define the interface between the control program and the application. The control program also has access to a database describing the structure of the application and the characteristics of its environment. Some of the more difficult problems for application management occur when preexisting, nondistributed programs are integrated into a distributed application for which they may not have been intended. Meta allows management functions to be retrofitted to such programs with a minimum of effort.

Marzullo, Keith↗

Ten steps to successful software process improvement

This paper identifies ten steps for managing change that address organizational and cultural issues. Four of these steps are critical, that if not done, will almost guarantee failure. This ten-step program emphasizes the alignment of business goals, change process goals, and the work performed by the employees of an organization.

software process improvement↗

Antenna Technology and other Radio Frequency (RF) Communications Activities at the Glenn Research Center in Support of NASA's Exploration Vision

NASA s Vision for Space Exploration outlines a very ambitious program for the next several decades of the Space Agency endeavors. Ahead is the completion of the International Space Station (ISS); safely flight the shuttle (STS) until 2010; develop and fly the Crew Exploration Vehicle (Orion) by no later than 2014; return to the moon by no later than 2020; extend human presence across the solar system and beyond; implement a sustainable and affordable human and robotic program; develop supporting innovative technologies, knowledge and infrastructure; and promote international and commercial participation in exploration. To achieve these goals, a series of enabling technologies must be developed or matured in a timely manner. Some of these technologies are: spacecraft RF technology (e.g., high power sources and large antennas which using surface receive arrays can get up to 1 Gbps from Mars), uplink arraying (reduce reliance on large ground-based antennas and high operation costs; single point of failure; enable greater data-rates or greater effective distance; scalable, evolvable, flexible scheduling), software define radio (i.e., reconfigurable, flexible interoperability allows for in flight updates open architecture; reduces mass, power, volume), and optical communications (high capacity communications with low mass/power required; significantly increases data rates for deep space). This presentation will discuss some of the work being performed at the NASA Glenn Research Center, Cleveland, Ohio, in antenna technology as well as other on-going RF communications efforts.

Miranda, Felix A.↗

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments.

Iverson, David L.↗

Comparison of Test Methods to Determine Failure Parameters for MAT162 Calibration

MAT162, a laminated composite failure material model developed by The Material Sciences Corporation for the commercial finite element software LS-Dyna, is widely used within the aerospace industry to predict damage events under a range of dynamic conditions. The material model involves numerous inputs consisting of both physical material properties and numerical calibration parameters. Due to the large number material card inputs, often there is a lack of uniqueness to MAT162 material cards that limits the predictive capability to only the directly calibrated space. To expand this space, MAT162 requires a prudent and robust calibration process in which significant parameters are calibrated to high confidence damage events observed in experiment. Critical to this success is fully defining the material properties correctly, namely the fiber crush (SFC) and fiber shear (SFS) values, prior to calibrating the numerical parameters. In this paper, the effect of the determination of SFS and SFC on subsequent calibration steps is examined using two different experimental techniques.

Molitor, Matthew↗

BioSentinel Avionics Design Approach with COTS Parts

This presentation focuses on ARC's avionics design approach using Commercial Off-The-Shelf (COTS) parts for high-risk, high-reward missions. Examples of ARC's past missions in small spacecraft, nano-satellites, and Class D payloads are highlighted, emphasizing the benefits of COTS, such as wider selections, faster development schedules, and lower costs. The challenges and limitations of traditional Qualified Parts List (QPL) approaches are discussed, along with observations from ARC missions, which show that design and workmanship issues are more significant than component failures. Mitigations for radiation risks associated with COTS are proposed, emphasizing risk awareness, proper software and hardware design, and careful parts selection. The success of ARC's 30+ projects using COTS over the past 17 years underscores its viability for high-risk missions.

BioSentinel↗