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At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Fault Graph (fg)

This software package offers a novel fault graph modeling language and a simulation tool for executing models specified in the language. The modeling language has three primary features that distinguish it from similar reliability analysis tools. These are (1) a random variable modeling several distinct outcomes of a single fault; (2) chains of faults in which one fault triggers another; and (3) time to fail sampled from probability distributions including positive normal, exponential, Weibull with a minimum, or immediate.

Nutaro, James↗

NASA NTRS2016

Reliability and Maintainability Analysis for the Amine Swingbed Carbon Dioxide Removal System

I have performed a reliability & maintainability analysis for the Amine Swingbed payload system. The Amine Swingbed is a carbon dioxide removal technology that has gone through 2,400 hours of International Space Station on-orbit use between 2013 and 2016. While the Amine Swingbed is currently an experimental payload system, the Amine Swingbed may be converted to system hardware. If the Amine Swingbed becomes system hardware, it will supplement the Carbon Dioxide Removal Assembly (CDRA) as the primary CO2 removal technology on the International Space Station. NASA is also considering using the Amine Swingbed as the primary carbon dioxide removal technology for future extravehicular mobility units and for the Orion, which will be used for the Asteroid Redirect and Journey to Mars missions. The qualitative component of the reliability and maintainability analysis is a Failure Modes and Effects Analysis (FMEA). In the FMEA, I have investigated how individual components in the Amine Swingbed may fail, and what the worst case scenario is should a failure occur. The significant failure effects are the loss of ability to remove carbon dioxide, the formation of ammonia due to chemical degradation of the amine, and loss of atmosphere because the Amine Swingbed uses the vacuum of space to regenerate the Amine Swingbed. In the quantitative component of the reliability and maintainability analysis, I have assumed a constant failure rate for both electronic and nonelectronic parts. Using this data, I have created a Poisson distribution to predict the failure rate of the Amine Swingbed as a whole. I have determined a mean time to failure for the Amine Swingbed to be approximately 1,400 hours. The observed mean time to failure for the system is between 600 and 1,200 hours. This range includes initial testing of the Amine Swingbed, as well as software faults that are understood to be non-critical. If many of the commercial parts were switched to military-grade parts, the expected mean time to failure would be 2,300 hours. Both calculated mean times to failure for the Amine Swingbed use conservative failure rate models. The observed mean time to failure for CDRA is 2,500 hours. Working on this project and for NASA in general has helped me gain insight into current aeronautics missions, reliability engineering, circuit analysis, and different cultures. Prior my internship, I did not have a lot knowledge about the work being performed at NASA. As a chemical engineer, I had not really considered working for NASA as a career path. By engaging in interactions with civil servants, contractors, and other interns, I have learned a great deal about modern challenges that NASA is addressing. My work has helped me develop a knowledge base in safety and reliability that would be difficult to find elsewhere. Prior to this internship, I had not thought about reliability engineering. Now, I have gained a skillset in performing reliability analyses, and understanding the inner workings of a large mechanical system. I have also gained experience in understanding how electrical systems work while I was analyzing the electrical components of the Amine Swingbed. I did not expect to be exposed to as many different cultures as I have while working at NASA. I am referring to both within NASA and the Houston area. NASA employs individuals with a broad range of backgrounds. It has been great to learn from individuals who have highly diverse experiences and outlooks on the world. In the Houston area, I have come across individuals from different parts of the world. Interacting with such a high number of individuals with significantly different backgrounds has helped me to grow as a person in ways that I did not expect. My time at NASA has opened a window into the field of aeronautics. After earning a bachelor's degree in chemical engineering, I plan to go to graduate school for a PhD in engineering. Prior to coming to NASA, I was not aware of the graduate Pathways program. I intend to apply for the graduate Pathways program as positions are opened up. I would like to pursue future opportunities with NASA, especially as my engineering career progresses.

Dunbar, Tyler↗

NASA NTRS1999

Integrated Computational System for Aerodynamic Steering and Visualization

In February of 1994, an effort from the Fluid Dynamics and Information Sciences Divisions at NASA Ames Research Center with McDonnel Douglas Aerospace Company and Stanford University was initiated to develop, demonstrate, validate and disseminate automated software for numerical aerodynamic simulation. The goal of the initiative was to develop a tri-discipline approach encompassing CFD, Intelligent Systems, and Automated Flow Feature Recognition to improve the utility of CFD in the design cycle. This approach would then be represented through an intelligent computational system which could accept an engineer's definition of a problem and construct an optimal and reliable CFD solution. Stanford University's role focused on developing technologies that advance visualization capabilities for analysis of CFD data, extract specific flow features useful for the design process, and compare CFD data with experimental data. During the years 1995-1997, Stanford University focused on developing techniques in the area of tensor visualization and flow feature extraction. Software libraries were created enabling feature extraction and exploration of tensor fields. As a proof of concept, a prototype system called the Integrated Computational System (ICS) was developed to demonstrate CFD design cycle. The current research effort focuses on finding a quantitative comparison of general vector fields based on topological features. Since the method relies on topological information, grid matching and vector alignment is not needed in the comparison. This is often a problem with many data comparison techniques. In addition, since only topology based information is stored and compared for each field, there is a significant compression of information that enables large databases to be quickly searched. This report will (1) briefly review the technologies developed during 1995-1997 (2) describe current technologies in the area of comparison techniques, (4) describe the theory of our new method researched during the grant year (5) summarize a few of the results and finally (6) discuss work within the last 6 months that are direct extensions from the grant.

Hesselink, Lambertus↗

NASA NTRS2015

Reliability and Probabilistic Risk Assessment - How They Play Together

PRA methodology is one of the probabilistic analysis methods that NASA brought from the nuclear industry to assess the risk of LOM, LOV and LOC for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability and statistical data to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: What can go wrong? How likely is it? What is the severity of the degradation? Since 1986, NASA, along with industry partners, has conducted a number of PRA studies to predict the overall launch vehicles risks. Planning Research Corporation conducted the first of these studies in 1988. In 1995, Science Applications International Corporation (SAIC) conducted a comprehensive PRA study. In July 1996, NASA conducted a two-year study (October 1996 - September 1998) to develop a model that provided the overall Space Shuttle risk and estimates of risk changes due to proposed Space Shuttle upgrades. After the Columbia accident, NASA conducted a PRA on the Shuttle External Tank (ET) foam. This study was the most focused and extensive risk assessment that NASA has conducted in recent years. It used a dynamic, physics-based, integrated system analysis approach to understand the integrated system risk due to ET foam loss in flight. Most recently, a PRA for Ares I launch vehicle has been performed in support of the Constellation program. Reliability, on the other hand, addresses the loss of functions. In a broader sense, reliability engineering is a discipline that involves the application of engineering principles to the design and processing of products, both hardware and software, for meeting product reliability requirements or goals. It is a very broad design-support discipline. It has important interfaces with many other engineering disciplines. Reliability as a figure of merit (i.e. the metric) is the probability that an item will perform its intended function(s) for a specified mission profile. In general, the reliability metric can be calculated through the analyses using reliability demonstration and reliability prediction methodologies. Reliability analysis is very critical for understanding component failure mechanisms and in identifying reliability critical design and process drivers. The following sections discuss the PRA process and reliability engineering in detail and provide an application where reliability analysis and PRA were jointly used in a complementary manner to support a Space Shuttle flight risk assessment.

Safie, Fayssal M.↗

DOE OSTI2020

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗

NASA NTRS1994

Program Finds Minimal Cut Sets

CUTSETS computer program identifies all minimal cut sets for given node. Software package contains subprograms that solve for minimal cut sets of fault trees and digraphs by use of object-oriented programming techniques. Cut-set codes used to solve graph models for reliability analysis and identify potential single-point failures in modeled system. Includes utility subprogram that converts popular COD-format diagraph-model-description files into text input files suitable for use with other CUT-SETS subprograms. FEAT (MSC-21873) and FIRM (MSC-21860). Written in C language.

Iverson, D. L.↗

NASA NTRS2019

Adaptations of guidance, navigation, and control verification and validation philosophies for small spacecraft

Decades of experience developing increasingly capable and more complex space-craft have resulted in a set of accepted practices and philosophies to verify and validate (V&V) guidance, navigation, and control (GN&C) subsystems. Until recently, small, low-cost spacecraft have had very simple or non-existent GN&C subsystems requiring minimal or no subsystem testing. As the next generation of small spacecraft take on more challenging GN&C requirements, the GN&C community is struggling with how to scale the subsystem V&V effort to produce spacecraft approaching the reliability of flagship-class missions while staying within the reduced resources of a small satellite project.For this paper, we will examine five aspects of GN&C V&V (requirements definition, software testing and analysis, hardware component testing, integrated vehicle testing, and in-flight V&V) and compare the V&V campaign of a flagship-class mission (Mars 2020) to that of two recent, successful CubeSat missions: ASTERIA and MarCO. Experiences from the development of these CubeSats yield valuable lessons learned and guidelines for future small spacecraft designers.

Chen, George T.↗

DOE OSTI2022

Efficient Implementation of Artificial Neural Networks for Sensor Data Analysis Based on a Genetic Algorithm

The reliability of many industrial processes depends on the sensor system. However, these sensors can be affected by noise, perturbations and failures. Hence, sensor monitoring and diagnosis are fundamental to guarantee the quality of an industrial process. Nowadays, artificial neural networks (ANN) are widely used in sensor signal processing and diagnosis. However, those ANNs usually require many artificial neurons, being difficult to implement in software and hardware due to their high computational costs. This paper presents an optimized implementation of artificial neurons in ANNs for sensor data analysis using a Genetic Algorithm (GA). The objective of GA is to find an adequate segmentation to reduce the activation function approximation error. One of the advantages of the proposed approach is that the cost function used in GA considers the effect of factors such as the ANN architecture or the number of bits used in arithmetic operations. The proposed ANN implementation technique aims to get the best possible approximation for a specific ANN architecture, making easier its implementation in software and hardware. Simulation and experimental results using FPGA (Field Programmable Gate Array) prove the advantages of the proposed approach for implementing sensor data analysis systems based on ANNs.

D estefani, André↗

NASA NTRS2010

Probabilistic Design and Analysis Framework

PRODAF is a software package designed to aid analysts and designers in conducting probabilistic analysis of components and systems. PRODAF can integrate multiple analysis programs to ease the tedious process of conducting a complex analysis process that requires the use of multiple software packages. The work uses a commercial finite element analysis (FEA) program with modules from NESSUS to conduct a probabilistic analysis of a hypothetical turbine blade, disk, and shaft model. PRODAF applies the response surface method, at the component level, and extrapolates the component-level responses to the system level. Hypothetical components of a gas turbine engine are first deterministically modeled using FEA. Variations in selected geometrical dimensions and loading conditions are analyzed to determine the effects of the stress state within each component. Geometric variations include the cord length and height for the blade, inner radius, outer radius, and thickness, which are varied for the disk. Probabilistic analysis is carried out using developing software packages like System Uncertainty Analysis (SUA) and PRODAF. PRODAF was used with a commercial deterministic FEA program in conjunction with modules from the probabilistic analysis program, NESTEM, to perturb loads and geometries to provide a reliability and sensitivity analysis. PRODAF simplified the handling of data among the various programs involved, and will work with many commercial and opensource deterministic programs, probabilistic programs, or modules.

Strack, William C.↗

NASA NTRS2019

Adaptations of Guidance, Navigation and Control Verification and Validation Philosophies for Small Spacecraft

Decades of experience developing increasingly capable and more complex space-craft have resulted in a set of accepted practices and philosophies to verify and validate (V&V) guidance, navigation, and control (GN&C) subsystems. Until recently, small, low-cost spacecraft have had very simple or non-existent GN&C subsystems requiring minimal or no subsystem testing. As the next generation of small spacecraft take on more challenging GN&C requirements, the GN&C community is struggling with how to scale the subsystem V&V effort to produce spacecraft approaching the reliability of flagship-class missions while staying within the reduced resources of a small satellite project. For this paper, we will examine five aspects of GN&C V&V (requirements definition, software testing and analysis, hardware component testing, integrated vehicle testing, and in-flight V&V) and compare the V&V campaign of a flagship-class mission (Mars 2020) to that of two recent, successful CubeSat missions: ASTERIA and MarCO. Experiences from the development of these CubeSats yield valuable lessons learned and guidelines for future small spacecraft designers.

Pong, Christopher M.↗

DOE OSTI2021

Low-latency NuMI Trigger for the CHIPS-5 Neutrino Detector

The CHIPS R&D project aims to develop affordable water Cherenkov detectors for large-scale underwater installations. In 2019, a 5kt prototype detector CHIPS-5 was deployed in northern Minnesota to study neutrinos generated by the nearby NuMI beam. This contribution presents a dedicated low-latency time distribution system for CHIPS-5 that delivers timing signals from the Fermilab accelerator to the detector with sub-nanosecond precision. Exploiting existing NOvA infrastructure, the time distribution system achieves this only with open-source software and conventional network elements. In a time-of-flight study, the presented system has reliably offered a time budget of $610 \pm 330\text{ ms}$ for on-site triggering. This permits advanced analysis in real-time as well as a novel hardware-assisted active triggering mode, which reduces DAQ computing load and network bandwidth outside triggered time windows.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1997

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Jong, Jen-Yi↗

NASA NTRS2013

ISSM: Ice Sheet System Model

In order to have the capability to use satellite data from its own missions to inform future sea-level rise projections, JPL needed a full-fledged ice-sheet/iceshelf flow model, capable of modeling the mass balance of Antarctica and Greenland into the near future. ISSM was developed with such a goal in mind, as a massively parallelized, multi-purpose finite-element framework dedicated to ice-sheet modeling. ISSM features unstructured meshes (Tria in 2D, and Penta in 3D) along with corresponding finite elements for both types of meshes. Each finite element can carry out diagnostic, prognostic, transient, thermal 3D, surface, and bed slope simulations. Anisotropic meshing enables adaptation of meshes to a certain metric, and the 2D Shelfy-Stream, 3D Blatter/Pattyn, and 3D Full-Stokes formulations capture the bulk of the ice-flow physics. These elements can be coupled together, based on the Arlequin method, so that on a large scale model such as Antarctica, each type of finite element is used in the most efficient manner. For each finite element referenced above, ISSM implements an adjoint. This adjoint can be used to carry out model inversions of unknown model parameters, typically ice rheology and basal drag at the ice/bedrock interface, using a metric such as the observed InSAR surface velocity. This data assimilation capability is crucial to allow spinning up of ice flow models using available satellite data. ISSM relies on the PETSc library for its vectors, matrices, and solvers. This allows ISSM to run efficiently on any parallel platform, whether shared or distrib- ISSM: Ice Sheet System Model NASA's Jet Propulsion Laboratory, Pasadena, California uted. It can run on the largest clusters, and is fully scalable. This allows ISSM to tackle models the size of continents. ISSM is embedded into MATLAB and Python, both open scientific platforms. This improves its outreach within the science community. It is entirely written in C/C++, which gives it flexibility in its design, and the power/speed that C/C++ allows. ISSM is svn (subversion) hosted, on a JPL repository, to facilitate its development and maintenance. ISSM can also model propagation of rifts using contact mechanics and mesh splitting, and can interface to the Dakota software. To carry out sensitivity analysis, mesh partitioning algorithms are available, based on the Scotch, Chaco, and Metis partitioners that ensure equal area mesh partitions can be done, which are then usable for sampling and local reliability methods.

Larour, Eric↗

NASA NTRS2018

Failure Analysis and Products in a Model-Based Environment

The work presented in this paper describes an approach, including a methodology and tools, which allows system engineers to capture failure-related information in a model and generate automatically key failure analysis products: the Failure Modes, Effects and Criticality Analysis (FMECA) and the Fault Tree Analysis (FTA). The work has been developed by Tietronix Software, Inc. and the NASA’s Jet Propulsion Laboratory (JPL), and the resulting auto-generated artifacts shown in this paper demonstrate the ability to obtain powerful reliability and fault management products in a model-based environment.

Castet, Jean-Francois↗

NASA NTRS1983

Current research in the Software Engineering Laboratory (SEL)

The basic goal of software engineering is to produce the best possible software at the lowest possible cost. Many practices, tools, and techniques (collectively referred to as technologies) were developed that purport to help do this, some of which have become widely accepted in the software industry. However, few of these technologies were effectively evaluated experimentally. This is due in large part to an insufficient understanding of the software development process, a lack of recognized standards for measurement, and the prohibitive cost of large-scale controlled experiments. The analysis described addresses some of these issues. The specific objectives of this study were to: measure technology use in a production environment; develop a model for evaluating software engineering technologies; and evaluate the effects of productivity and reliability of some specific technologies.

Card, D.↗

NASA NTRS1989

Determination of Earth orientation using the Global Positioning System

Modern spacecraft tracking and navigation require highly accurate Earth-orientation parameters. For near-real-time applications, errors in these quantities and their extrapolated values are a significant error source. A globally distributed network of high-precision receivers observing the full Global Positioning System (GPS) configuration of 18 or more satellites may be an efficient and economical method for the rapid determination of short-term variations in Earth orientation. A covariance analysis using the JPL Orbit Analysis and Simulation Software (OASIS) was performed to evaluate the errors associated with GPS measurements of Earth orientation. These GPS measurements appear to be highly competitive with those from other techniques and can potentially yield frequent and reliable centimeter-level Earth-orientation information while simultaneously allowing the oversubscribed Deep Space Network (DSN) antennas to be used more for direct project support.

Freedman, A. P.↗

DOE OSTI2025

MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8) for advanced open-source tritium transport and fuel cycle modeling

Tritium management is critical for the safety, sustainability, and economics of fusion energy systems, and advanced and reliable modeling tools help accelerate the development of tritium technologies. This paper presents the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source, MOOSE-based application developed to provide state-of-the-art tritium transport and fuel cycle modeling capabilities. TMAP8 aims to expand the capabilities of previous versions (i.e., TMAP4 and TMAP7) by leveraging modern computational techniques, ensuring high software quality assurance standards (key to building trust), and enabling multispecies, multiscale, and multiphysics simulations for integrated tritium transport modeling in complex geometries. This paper outlines TMAP8’s scope and rigorous development practices, emphasizing its transparency, accessibility, modularity, and reliability. We present the current suite of verification and validation cases based on those from TMAP4, demonstrating TMAP8’s accuracy and reliability against analytical solutions and experimental data. Additionally, the paper showcases TMAP8’s integrated fuel cycle modeling capabilities, highlighting its applicability at various scales and levels. The TMAP8 code and documentation are openly available, promoting collaborative development and widespread adoption within the fusion community. Future work will soon expand TMAP8’s verification and validation suite to include those from TMAP7 and other recent experimental studies for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2000

SAVANT: Solar Array Verification and Analysis Tool Demonstrated

The photovoltaics (PV) industry is now being held to strict specifications, such as end-oflife power requirements, that force them to overengineer their products to avoid contractual penalties. Such overengineering has been the only reliable way to meet such specifications. Unfortunately, it also results in a more costly process than is probably necessary. In our conversations with the PV industry, the issue of cost has been raised again and again. Consequently, the Photovoltaics and Space Environment Effects branch at the NASA Glenn Research Center at Lewis Field has been developing a software tool to address this problem. SAVANT, Glenn's tool for solar array verification and analysis is in the technology demonstration phase. Ongoing work has proven that more efficient and less costly PV designs should be possible by using SAVANT to predict the on-orbit life-cycle performance. The ultimate goal of the SAVANT project is to provide a user-friendly computer tool to predict PV on-orbit life-cycle performance. This should greatly simplify the tasks of scaling and designing the PV power component of any given flight or mission. By being able to predict how a particular PV article will perform, designers will be able to balance mission power requirements (both beginning-of-life and end-of-life) with survivability concerns such as power degradation due to radiation and/or contamination. Recent comparisons with actual flight data from the Photovoltaic Array Space Power Plus Diagnostics (PASP Plus) mission validate this approach.

Chock, Ricaurte↗