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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

ROAM: A Remotely Operated Accelerator Monitor

Monitoring accelerators in operation is a well known challenge due to the radiation environment. However, there are significant benefits in being able to deploy particular sensors in specific locations of accelerator enclosures for monitoring or troubleshooting purposes. Learning from experience at other labs, we used Commercial Off The Shelf (COTS) components and an open source robot control software framework (ROS) to build a remotely controlled robot platform including a standard suite of instruments such as cameras, LIDAR, and ultrasound, with the ability to incorporate other ad-hoc sensors for specific measurements, such as a Gamma radiation monitor. Special attention was given to the robot's ability to maintain safety in the high risk environment of an accelerator, with multiple failure contingencies in place to ensure collision free operation. Testing was performed to prove the platform's viability and showcase its capability for accelerator monitoring.

Thayer, Thomas C.↗
NASA NTRS1991

Software reliability through fault-avoidance and fault-tolerance

Twenty independently developed but functionally equivalent software versions were used to investigate and compare empirically some properties of N-version programming, Recovery Block, and Consensus Recovery Block, using the majority and consensus voting algorithms. This was also compared with another hybrid fault-tolerant scheme called Acceptance Voting, using dynamic versions of consensus and majority voting. Consensus voting provides adaptation of the voting strategy to varying component reliability, failure correlation, and output space characteristics. Since failure correlation among versions effectively reduces the cardinality of the space in which the voter make decisions, consensus voting is usually preferable to simple majority voting in any fault-tolerant system. When versions have considerably different reliabilities, the version with the best reliability will perform better than any of the fault-tolerant techniques.

Vouk, Mladen A.↗
NASA NTRS2003

Flight Test of an Intelligent Flight-Control System

The F-15 Advanced Controls Technology for Integrated Vehicles (ACTIVE) airplane (see figure) was the test bed for a flight test of an intelligent flight control system (IFCS). This IFCS utilizes a neural network to determine critical stability and control derivatives for a control law, the real-time gains of which are computed by an algorithm that solves the Riccati equation. These derivatives are also used to identify the parameters of a dynamic model of the airplane. The model is used in a model-following portion of the control law, in order to provide specific vehicle handling characteristics. The flight test of the IFCS marks the initiation of the Intelligent Flight Control System Advanced Concept Program (IFCS ACP), which is a collaboration between NASA and Boeing Phantom Works. The goals of the IFCS ACP are to (1) develop the concept of a flight-control system that uses neural-network technology to identify aircraft characteristics to provide optimal aircraft performance, (2) develop a self-training neural network to update estimates of aircraft properties in flight, and (3) demonstrate the aforementioned concepts on the F-15 ACTIVE airplane in flight. The activities of the initial IFCS ACP were divided into three Phases, each devoted to the attainment of a different objective. The objective of Phase I was to develop a pre-trained neural network to store and recall the wind-tunnel-based stability and control derivatives of the vehicle. The objective of Phase II was to develop a neural network that can learn how to adjust the stability and control derivatives to account for failures or modeling deficiencies. The objective of Phase III was to develop a flight control system that uses the neural network outputs as a basis for controlling the aircraft. The flight test of the IFCS was performed in stages. In the first stage, the Phase I version of the pre-trained neural network was flown in a passive mode. The neural network software was running using flight data inputs with the outputs provided to instrumentation only. The IFCS was not used to control the airplane. In another stage of the flight test, the Phase I pre-trained neural network was integrated into a Phase III version of the flight control system. The Phase I pretrained neural network provided realtime stability and control derivatives to a Phase III controller that was based on a stochastic optimal feedforward and feedback technique (SOFFT). This combined Phase I/III system was operated together with the research flight-control system (RFCS) of the F-15 ACTIVE during the flight test. The RFCS enables the pilot to switch quickly from the experimental- research flight mode back to the safe conventional mode. These initial IFCS ACP flight tests were completed in April 1999. The Phase I/III flight test milestone was to demonstrate, across a range of subsonic and supersonic flight conditions, that the pre-trained neural network could be used to supply real-time aerodynamic stability and control derivatives to the closed-loop optimal SOFFT flight controller. Additional objectives attained in the flight test included (1) flight qualification of a neural-network-based control system; (2) the use of a combined neural-network/closed-loop optimal flight-control system to obtain level-one handling qualities; and (3) demonstration, through variation of control gains, that different handling qualities can be achieved by setting new target parameters. In addition, data for the Phase-II (on-line-learning) neural network were collected, during the use of stacked-frequency- sweep excitation, for post-flight analysis. Initial analysis of these data showed the potential for future flight tests that will incorporate the real-time identification and on-line learning aspects of the IFCS.

Davidson, Ron↗
NASA NTRS2016

Simulation of Malfunctions for the ISS Double-Gimbal Control Moment Gyroscope

This paper presents a simplified approach to simulation of malfunctions of the Control Moment Gyroscope (CMG) on board the International Space Station (ISS). These malfunctions will be used as part of flight training of CMG failure scenarios in the guidance navigation control (GNC) subsystem of the Training Systems for 21st Century (TS21) simulator. The CMG malfunctions are grouped under mechanical, thermal and electrical categories. A malfunction can be as simple as one which only affects the telemetry or a complex one that changes the state and behavior of the CMG model. In both cases, the ISS GNC flight software will read the telemetry and respond accordingly. The user executes these malfunctions by supplying conditional data which modify internal model states and then elicit a response as seen on the user displays. Ground operators and crew on board the ISS use CMG malfunction procedures to better understand and respond to anomalies observed within the CMG subsystem.

Inampudi, Ravi↗
NASA NTRS2016

Stochastic-Strength-Based Damage Simulation of Ceramic Matrix Composite Laminates

The Finite Element Analysis-Micromechanics Analysis Code/Ceramics Analysis and Reliability Evaluation of Structures (FEAMAC/CARES) program was used to characterize and predict the progressive damage response of silicon-carbide-fiber-reinforced reaction-bonded silicon nitride matrix (SiC/RBSN) composite laminate tensile specimens. Studied were unidirectional laminates [0] (sub 8), [10] (sub 8), [45] (sub 8), and [90] (sub 8); cross-ply laminates [0 (sub 2) divided by 90 (sub 2),]s; angled-ply laminates [plus 45 (sub 2) divided by -45 (sub 2), ]s; doubled-edge-notched [0] (sub 8), laminates; and central-hole laminates. Results correlated well with the experimental data. This work was performed as a validation and benchmarking exercise of the FEAMAC/CARES program. FEAMAC/CARES simulates stochastic-based discrete-event progressive damage of ceramic matrix composite and polymer matrix composite material structures. It couples three software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/Life), and (3) the Abaqus finite element analysis program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating-unit-cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC, and Abaqus is used to model the overall composite structure. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events that incrementally progress until ultimate structural failure.

composite structures↗
NASA NTRS1991

Proximity operations considerations affecting spacecraft design

Proximity operations can be defined as the maneuvering of two or more spacecraft within 1 nautical mile range, with relative velocity less than 10 feet per second. The passive vehicle is nontranslating and should provide for maintenance of the desired approach attitude. It must accommodate the active (translating) vehicle induced structural loads and performance characteristics (mating hardware tolerances), and support sensor compatibility (transponder, visual targets, etc.). The active vehicle must provide adequate sensor systems (relative state information, field-of-view, redundancy), flight control hardware (thruster sizing, minimal cross-coupling, performance margins, redundancy) and software (reconfigurable, attitude/rate modes, translation and rotation fine control authority) characteristic, and adequate non-propulsive consumables such as power. Operational concerns must be considered. These include the following: (1) the desired approach trajectory and relative orientation; (2) the active vehicle thruster plume effects (forces, torques, contamination) on the passive vehicle; and (3) procedures for contingencies such as loss of communications, sensor or propulsion failures, and target vehicle loss of control.

Staas, Steven K.↗
NASA NTRS2003

Software Reliability 2002

In FY01 we learned that hardware reliability models need substantial changes to account for differences in software, thus making software reliability measurements more effective, accurate, and easier to apply. These reliability models are generally based on familiar distributions or parametric methods. An obvious question is 'What new statistical and probability models can be developed using non-parametric and distribution-free methods instead of the traditional parametric method?" Two approaches to software reliability engineering appear somewhat promising. The first study, begin in FY01, is based in hardware reliability, a very well established science that has many aspects that can be applied to software. This research effort has investigated mathematical aspects of hardware reliability and has identified those applicable to software. Currently the research effort is applying and testing these approaches to software reliability measurement, These parametric models require much project data that may be difficult to apply and interpret. Projects at GSFC are often complex in both technology and schedules. Assessing and estimating reliability of the final system is extremely difficult when various subsystems are tested and completed long before others. Parametric and distribution free techniques may offer a new and accurate way of modeling failure time and other project data to provide earlier and more accurate estimates of system reliability.

Wallace, Dolores R.↗
NASA NTRS2011

Structural health monitoring apparatus and methodology

Disclosed is an apparatus and methodology for structural health monitoring (SHM) in which smart devices interrogate structural components to predict failure, expedite needed repairs, and thus increase the useful life of those components. Piezoelectric wafer active sensors (PWAS) are applied to or integrated with structural components and various data collected there from provide the ability to detect and locate cracking, corrosion, and disbanding through use of pitch-catch, pulse-echo, electro/mechanical impedance, and phased array technology. Stand alone hardware and an associated software program are provided that allow selection of multiple types of SHM investigations as well as multiple types of data analysis to perform a wholesome investigation of a structure.

Giurgiutiu, Victor↗
NASA NTRS2016

Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix and Polymer Matrix Composite Structures

Stochastic-based, discrete-event progressive damage simulations of ceramic-matrix composite and polymer matrix composite material structures have been enabled through the development of a unique multiscale modeling tool. This effort involves coupling three independently developed software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/ Life), and (3) the Abaqus finite element analysis (FEA) program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating unit cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC. Abaqus is used at the global scale to model the overall composite structure. An Abaqus user-defined material (UMAT) interface, referred to here as "FEAMAC/CARES," was developed that enables MAC/GMC and CARES/Life to operate seamlessly with the Abaqus FEA code. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events, which incrementally progress and lead to ultimate structural failure. This report describes the FEAMAC/CARES methodology and discusses examples that illustrate the performance of the tool. A comprehensive example problem, simulating the progressive damage of laminated ceramic matrix composites under various off-axis loading conditions and including a double notched tensile specimen geometry, is described in a separate report.

composite structures↗
NASA NTRS2019

Demisability of GFRP and CFRP Components of Reentering Orbital Debris: Phase I Test Results

Observations of surviving reentry debris on the ground and research performed by Hyperschall Technologie Göttingen (HTG) [1] indicated that significantly more glass fiber-reinforced polymer (GFRP) and carbon fiber-reinforced polymer (CFRP) components survive reentry than current models predict. NASA’s Orbital Debris Program Office conducted a series of tests to evaluate the accuracy of material demise models for reentering orbital debris used in NASA’s Object Reentry Survival Analysis Tool (ORSAT) and Debris Assessment Software (DAS). Testing is planned in a multi-phase series to allow for quick quantification of results as well as refinement of methods resulting from lessons learned during early phases. The Phase 1 tests discussed here validated ORSAT models for homogeneous metals, provided an efficient quantification of composite material demisability properties like mass loss rate and overall time to demise, and identified potential failure modes, which are currently not well understood. Phase 2 tests will be used to further understand mass loss rates and modes of both thermal and mechanical failure in composite materials. The authors exposed 95 samples of aluminum, CFRP, Kevlar fiber-reinforced polymer, GFRP, and sheets of G10 fiberglass to conditions approximating the reentry environment using an inductively coupled plasma (ICP) torch facility. The cylindrical CFRP samples were exposed to the atmospheric pressure plasma, at both the end and the midpoint, to investigate the difference in demisability between parts with exposed edges, like panels, and parts with no edges, such as carbonoverwrapped pressure vessels (COPVs). In a non-oxidative environment, no composite materials demised within the 5-minute test time. In the oxidative, elevated heat flux environment, CFRP samples demised between 210 s and 270 s. For the first 100 s of insertion time, most of the mass loss was due to pyrolysis of resin, creating an approximately bi-linear mass-loss rate curve with time. In a non-oxidative environment, carbon filaments were observed to unravel from some of the CFRP end-burned samples; however, this effect did not seem to affect the overall time to demise for the samples significantly. These results indicate that both GFRP and CFRP components survive reentry with significantly more remaining mass than current models predict.

Greene, Benton R.↗
DOE OSTI2015

FireWorks: a Dynamic Workflow System Designed for High-Throughput Applications

This work introduces FireWorks, a workflow software for running high-throughput calculation workflows at supercomputing centers. FireWorks has been used to complete over 50 million CPU-hours worth of computational chemistry and materials science calculations at the National Energy Research Supercomputing Center. It has been designed to serve the demanding high-throughput computing needs of these applications, with extensive support for (i) concurrent execution through job packing, (ii) failure detection and correction, (iii) provenance and reporting for long-running projects, (iv) automated duplicate detection, and (v) dynamic workflows (i.e., modifying the workflow graph during runtime). We have found that these features are highly relevant to enabling modern data-driven and high-throughput science applications, and we discuss our implementation strategy that rests on Python and NoSQL databases (MongoDB). Finally, we present performance data and limitations of our approach along with planned future work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

NSTX-U Advances in Real-Time C++11 on Linux

Programming languages like C and Ada combined with proprietary embedded operating systems have dominated the real-time application space for decades. The new C++11standard includes native, language-level support for concurrency, a required feature for any nontrivial event-oriented real-time software. Threads, Locks, and Atomics now exist to provide the necessary tools to build the structures that make up the foundation of a complex real-time system. The National Spherical Torus Experiment Upgrade (NSTX-U) at the Princeton Plasma Physics Laboratory (PPPL) is breaking new ground with the language as applied to the needs of fusion devices. A new Digital Coil Protection System (DCPS) will serve as the main protection mechanism for the magnetic coils, and it is written entirely in C++11 running on Concurrent Computer Corporation's real-time operating system, RedHawk Linux. It runs over 600 algorithms in a 5 kHz control loop that determine whether or not to shut down operations before physical damage occurs. To accomplish this, NSTX-U engineers developed software tools that do not currently exist elsewhere, including real-time atomic synchronization, real-time containers, and a real-time logging framework. Together with a recent (and carefully configured) version of the GCC compiler, these tools enable data acquisition, processing, and output using a conventional operating system to meet a hard real-time deadline (that is, missing one periodic is a failure) of 200 microseconds.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2014

Data Fusion Tool for Spiral Bevel Gear Condition Indicator Data

Tests were performed on two spiral bevel gear sets in the NASA Glenn Spiral Bevel Gear Fatigue Test Rig to simulate the fielded failures of spiral bevel gears installed in a helicopter. Gear sets were tested until damage initiated and progressed on two or more gear or pinion teeth. During testing, gear health monitoring data was collected with two different health monitoring systems. Operational parameters were measured with a third data acquisition system. Tooth damage progression was documented with photographs taken at inspection intervals throughout the test. A software tool was developed for fusing the operational data and the vibration based gear condition indicator (CI) data collected from the two health monitoring systems. Results of this study illustrate the benefits of combining the data from all three systems to indicate progression of damage for spiral bevel gears. The tool also enabled evaluation of the effectiveness of each CI with respect to operational conditions and fault mode.

health monitoring↗
DOE OSTI2017

Assembling Multiple Models Within the RAVEN Framework

RAVEN (Risk Analysis Virtual Environment) is an INL-developed software tool that can be used to identify and increase the safety margin in complex systems. As a generic software framework, RAVEN is designed to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is capable of investigating the system response as well as the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. RAVEN is currently able to construct multi-targets Reduced Order Models (ROMs), which are aimed to represent the response of a system (in a fixed configuration) for multiple Figures of Merits (FOMs) and time-dependent ROMs. These capabilities represent the initial steps for a larger implementation about the interaction of multiple models. In fact, in several cases, multiple models need to interface with each other since the initial conditions of one are dependent on the outcomes of another. To better understand the problem that here is solved, it is useful to consider a simple example: The following problem is considered: a weather forecast simulation code 'a' is used to compute the external (i.e. ambient) temperature in a certain location. A second model 'b' is inquired to compute the average temperature in a room having as boundary condition, among several others, the external ambient temperature. The response of the model 'b' depends on the outcome of the model 'a'. The reported example is only aimed to illustrate the reason why the creation of a framework to make interact different models is a key development for the advancement of RAVEN as a comprehensive calculation flow driver. Before reporting how the ensemble-models have been implemented, it is necessary to briefly describe the representative Model 'entities' that are available in RAVEN.

42 ENGINEERING↗
NASA NTRS2018

Utilizing Testing Frameworks for Launch Control Systems Continuous Integration

Command and control software is an integral part of the launch procedure. The most important part of this type of software is its ability to communicate well with the user and relay information in a correctly formatted way such that the user can understand the data. There is a tool that aides the communication between the different parts of the system, and effectively, the user. This instrument is capable of taking several complex values and ensuring that they are correctly sorted into their distinctive message values and distributed properly among the different facets of the system. This tool will easily translate and publish the data inside of messages in the system to something that is readable and understandable. The tool also allows for transmission of the recorded data to the user, effectively ensuring the communication between different components of the system. As well as keeping track of messages and ensuring that the information contained within each of them reaches the correct location, this tool has the ability to keep track of its own statistics and determine how many messages passed in were erroneous and how many were successfully transmitted. It is able to check and see what the total message failure count is when an invalid message is given, as well as the number of different messages and their respective types passed into the tool. This tool is of great value to the new Space Launch System (SLS). As such, the tool must be thoroughly tested with test cases that, although improbable, are possible, where the tool may not function properly. Testing an interface this complex is necessary to ensure mission safety and create unlikely scenarios where the tool would work as intended, and stretch its limits to test that even under the most uncommon conditions it would still continue to function. This software will be an important part of the control system for the newest spacecraft which will fly deeper into space than humans have ever travelled. It will fly beyond the moon, into deep space to Mars and perhaps set the groundwork for a manned mission even further to create more opportunities for interplanetary and even interstellar travel by humans. This mission relies heavily on software and hardware to ensure the safety of the humans that will be on board and therefore must be checked, exhausting each and every different situation, such that there is not a doubt surrounding the well-being of the humans aboard the rocket. That is why testing is such an important part of the mission. It provides evidence that the systems aboard the rocket and on the launch pad are safe.

Unit Testing↗
DOE OSTI2014

The Coal-Seq III Consortium. Advancing the Science of CO 2 Sequestration in Coal Seam and Gas Shale Reservoirs

The Coal-Seq consortium is a government-industry collaborative that was initially launched in 2000 as a U.S. Department of Energy sponsored investigation into CO2 sequestration in deep, unmineable coal seams. The consortium’s objective aimed to advancing industry’s understanding of complex coalbed methane and gas shale reservoir behavior in the presence of multi-component gases via laboratory experiments, theoretical model development and field validation studies. Research from this collaborative effort was utilized to produce modules to enhance reservoir simulation and modeling capabilities to assess the technical and economic potential for CO2 storage and enhanced coalbed methane recovery in coal basins. Coal-Seq Phase 3 expands upon the learnings garnered from Phase 1 & 2, which has led to further investigation into refined model development related to multicomponent equations-of-state, sorption and diffusion behavior, geomechanical and permeability studies, technical and economic feasibility studies for major international coal basins the extension of the work to gas shale reservoirs, and continued global technology exchange. The first research objective assesses changes in coal and shale properties with exposure to CO2 under field replicated conditions. Results indicate that no significant weakening occurs when coal and shale were exposed to CO2, therefore, there was no need to account for mechanical weakening of coal due to the injection of CO2 for modeling. The second major research objective evaluates cleat, Cp, and matrix, Cm, swelling/shrinkage compressibility under field replicated conditions. The experimental studies found that both Cp and Cm vary due to changes in reservoir pressure during injection and depletion under field replicated conditions. Using laboratory data from this study, a compressibility model was developed to predict the pore-volume compressibility, Cp, and the matrix compressibility, Cm, of coal and shale, which was applied to modeling software to enhance model robustness. Research was also conducted to improve algorithms and generalized adsorption models to facilitate realistic simulation of CO2 sequestration in coal seams and shale gas reservoirs. The interaction among water and the adsorbed gases, carbon dioxide (CO2), methane (CH4), and nitrogen (N2) in coalbeds is examined using experimental in situ laboratory techniques to comprehensively model CBM production and CO2 sequestration in coals. An equation of state (EOS) module was developed which is capable of predicting the density of pure components and mixtures involving the wet CBM gases CH4, CO2, and N2 at typical reservoir condition, and is used to inform CO2 injection models. The final research objective examined the effects adsorbed CO2 has on coal strength and permeability. This research studied the weakening or failure of coal by the adsorption of CO2 from empirically derived gas production data to develop models for advanced modeling of permeability changes during CO2 sequestration. The results of this research effort have been used to construct a new and improved model for assessing changes in permeability of coal reservoirs due CO2 injection. The modules developed from these studies and knowledge learned are applied to field validation and basin assessment studies. These data were used to assess the flow and storage of CO2 in a shale reservoir, test newly developed code against large-scale projects, and conduct a basin-oriented review of coal storage potential in the San Juan Basin. The storage potential and flow of CO2 was modeled for shale sequestration of a proprietary Marcellus Shale horizontal gas production well using COMET3 simulation software. Simulation results from five model runs indicate that stored CO2 quantities are linked to the duration of primary production preceding injection. Matrix CO2 saturation is observed to increase in each shale zone after injection with an increase in primary production, and the size of the CO2 plume is also observed to increase in size the longer initial production is sustained. The simulation modules developed around the Coal-Seq experimental work are also incorporated into a pre-existing large-scale numerical simulation model of the Pump Canyon CO2-ECBM pilot in the San Juan Basin. The new model was applied to re-history match the data set to explore the improvements made in permeability prediction against previously published data sets and to validate this module. The assessment of the new data, however, indicates that the impact of the variable Cp is negligible on the overall behavior of the coal for CO2 storage purposes. Applying these new modules, the San Juan Basin and the Marcellus Shale are assessed for their technical ECBM/AGR and CO2 storage potential and the economic potential of these operations. The San Juan Basin was divided into 4 unique geographic zones based on production history, and the Marcellus was divided into nine. Each was assessed based upon each zone’s properties, and simulations were run to assess the potential of full Basin development. Models of a fully developed San Juan Basin suggest the potential for up to 104 Tcf of CO2 storage, and 12.3 Tcf of methane recovery. The Marcellus models suggest 1,248 Tcf of CO2 storage and 924 Tcf of AGR. The economics are deemed favorable where credits cover the cost of CO2 in the San Juan Basin, and in many cases in the Marcellus, but to maximize storage potential, credits need to extend to pay the operator to store CO2.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2003

Rocket Engine Health Management: Early Definition of Critical Flight Measurements

The NASA led Space Launch Initiative (SLI) program has established key requirements related to safety, reliability, launch availability and operations cost to be met by the next generation of reusable launch vehicles. Key to meeting these requirements will be an integrated vehicle health management ( M) system that includes sensors, harnesses, software, memory, and processors. Such a system must be integrated across all the vehicle subsystems and meet component, subsystem, and system requirements relative to fault detection, fault isolation, and false alarm rate. The purpose of this activity is to evolve techniques for defining critical flight engine system measurements-early within the definition of an engine health management system (EHMS). Two approaches, performance-based and failure mode-based, are integrated to provide a proposed set of measurements to be collected. This integrated approach is applied to MSFC s MC-1 engine. Early identification of measurements supports early identification of candidate sensor systems whose design and impacts to the engine components must be considered in engine design.

Christenson, Rick L.↗
NASA NTRS2006

Probabilistic Prediction of Lifetimes of Ceramic Parts

ANSYS/CARES/PDS is a software system that combines the ANSYS Probabilistic Design System (PDS) software with a modified version of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) Version 6.0 software. [A prior version of CARES/Life was reported in Program for Evaluation of Reliability of Ceramic Parts (LEW-16018), NASA Tech Briefs, Vol. 20, No. 3 (March 1996), page 28.] CARES/Life models effects of stochastic strength, slow crack growth, and stress distribution on the overall reliability of a ceramic component. The essence of the enhancement in CARES/Life 6.0 is the capability to predict the probability of failure using results from transient finite-element analysis. ANSYS PDS models the effects of uncertainty in material properties, dimensions, and loading on the stress distribution and deformation. ANSYS/CARES/PDS accounts for the effects of probabilistic strength, probabilistic loads, probabilistic material properties, and probabilistic tolerances on the lifetime and reliability of the component. Even failure probability becomes a stochastic quantity that can be tracked as a response variable. ANSYS/CARES/PDS enables tracking of all stochastic quantities in the design space, thereby enabling more precise probabilistic prediction of lifetimes of ceramic components.

Nemeth, Noel N.↗