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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Investigating Various Failure Models on Commercial Silicon Carbide

Structures and components made from ceramic materials are often brittle and can fail by the unstable growth of existing flaws such as voids and cracks. There have been several failure criteria developed for ceramics, in the past and they are broadly categorized based on their dependency on crack geometry. The present work implements eight failure criteria using an open-source software package – srlife, which predicts the lifetime or failure probability of concentrated solar power (CSP) structural components. The present work also checks the viability of building a ceramic CSP receiver, by analyzing the reliability predictions from srlife for a SiC ceramic. The reliability predictions for a biaxial loading problem indicated the Shetty Mixed-Mode criterion gives the most conservative predictions. Whereas, in case of the CSP receiver, the predictions show that the co-planar strain energy criterion gives the most conservative predictions as it is agnostic towards the type of stress, and therefore, is not recommended to be used designing ceramic receivers.

Chaugule, Pawan (ORCID:0000000275706572)↗
NASA NTRS1991

Programs For Modeling Fault-Tolerant Computing Systems

Pade Approximation with Scaling, (PAWS) and Scaling Taylor Exponential Matrix (STEM) computer programs are software tools for design and validation. Provide flexible, user-friendly, language-based interface for input of Markov mathematical methods describing behaviors of fault-tolerant computer systems. Markov models include both recovery from faults via reconfiguration and behaviors of such systems when faults occur. PAWS and STEM produce exact solutions of probability of system failure and provide conservative estimate of number of significant digits in solution. Written in PASCAL and FORTRAN.

Butler, Ricky W.↗
NASA NTRS2006

Difficult Decisions Made Easier

NASA missions are extremely complex and prone to sudden, catastrophic failure if equipment falters or if an unforeseen event occurs. For these reasons, NASA trains to expect the unexpected. It tests its equipment and systems in extreme conditions, and it develops risk-analysis tests to foresee any possible problems. The Space Agency recently worked with an industry partner to develop reliability analysis software capable of modeling complex, highly dynamic systems, taking into account variations in input parameters and the evolution of the system over the course of a mission. The goal of this research was multifold. It included performance and risk analyses of complex, multiphase missions, like the insertion of the Mars Reconnaissance Orbiter; reliability analyses of systems with redundant and/or repairable components; optimization analyses of system configurations with respect to cost and reliability; and sensitivity analyses to identify optimal areas for uncertainty reduction or performance enhancement.

Source record↗
DOE OSTI2017

A Pattern Language for High-Performance Computing Resilience

High-performance computing systems (HPC) provide powerful capabilities for modeling, simulation, and data analytics for a broad class of computational problems. They enable extreme performance of the order of quadrillion floating-point arithmetic calculations per second by aggregating the power of millions of compute, memory, networking and storage components. With the rapidly growing scale and complexity of HPC systems for achieving even greater performance, ensuring their reliable operation in the face of system degradations and failures is a critical challenge. System fault events often lead the scientific applications to produce incorrect results, or may even cause their untimely termination. The sheer number of components in modern extreme-scale HPC systems and the complex interactions and dependencies among the hardware and software components, the applications, and the physical environment makes the design of practical solutions that support fault resilience a complex undertaking. To manage this complexity, we developed a methodology for designing HPC resilience solutions using design patterns. We codified the well-known techniques for handling faults, errors and failures that have been devised, applied and improved upon over the past three decades in the form of design patterns. In this paper, we present a pattern language to enable a structured approach to the development of HPC resilience solutions. The pattern language reveals the relations among the resilience patterns and provides the means to explore alternative techniques for handling a specific fault model that may have different efficiency and complexity characteristics. Using the pattern language enables the design and implementation of comprehensive resilience solutions as a set of interconnected resilience patterns that can be instantiated across layers of the system stack.

Hukerikar, Saurabh↗
NASA NTRS1987

Simulation evaluation of the control system command monitoring concept for the NASA V/STOL research aircraft (VSRA)

A control-system monitoring concept is described that has the potential of rapidly detecting computer command failures (hardware or software) in fly-by-wire control systems. The concept has been successfully tested on the NASA Vertical/Short Takeoff and Landing Research Aircraft (VSRA) in the Ames Research Center's Vertical Motion Simulator. The test was particularly stringent, since the VSRA is required to operate in a hazardous environment. The fidelity of the aircraft model used in the simulation was verified by flying both the simulated and actual aircraft in a precision hover task using specially designed targets.

Schroeder, J. A.↗
NASA NTRS1992

Statistical modeling of software reliability

This working paper discusses the statistical simulation part of a controlled software development experiment being conducted under the direction of the System Validation Methods Branch, Information Systems Division, NASA Langley Research Center. The experiment uses guidance and control software (GCS) aboard a fictitious planetary landing spacecraft: real-time control software operating on a transient mission. Software execution is simulated to study the statistical aspects of reliability and other failure characteristics of the software during development, testing, and random usage. Quantification of software reliability is a major goal. Various reliability concepts are discussed. Experiments are described for performing simulations and collecting appropriate simulated software performance and failure data. This data is then used to make statistical inferences about the quality of the software development and verification processes as well as inferences about the reliability of software versions and reliability growth under random testing and debugging.

Miller, Douglas R.↗
NASA NTRS2012

Sizing and Lifecycle Cost Analysis of an Ares V Composite Interstage

The Interstage Element of the Ares V launch vehicle was sized using a commercially available structural sizing software tool. Two different concepts were considered, a metallic design and a composite design. Both concepts were sized using similar levels of analysis fidelity and included the influence of design details on each concept. Additionally, the impact of the different manufacturing techniques and failure mechanisms for composite and metallic construction were considered. Significant details were included in analysis models of each concept, including penetrations for human access, joint connections, as well as secondary loading effects. The designs and results of the analysis were used to determine lifecycle cost estimates for the two Interstage designs. Lifecycle cost estimates were based on industry provided cost data for similar launch vehicle components. The results indicated that significant mass as well as cost savings are attainable for the chosen composite concept as compared with a metallic option.

Mann, Troy↗
NASA NTRSDate not supplied

Finite Element Modeling of Plastic Deformation During Spin Forming of Aluminum 6061-O

Spin and flow forming are metal deformation techniques in which a disk or tube of material is radially thinned and axially lengthened over a rotating mandrel. A finite-element continuum model (FEM) based on commercial software (DEFORM®) was developed to determine the stress/strain distribution and damage accumulation in a flow-formed, near-net-shape part. Computational validation and experimental verification of the model was leveraged to assess the effectiveness of computer simulations. Quantitative comparisons between experimental and computational results show promise for applying a FEM to the flow forming process. Experimental failure locations correlated well with computed damage gradients, and there was good agreement between the measured and predicted roller forces during forming.

Elizabeth Urig↗
DOE OSTI2014

RAVEN, a New Software for Dynamic Risk Analysis

RAVEN is a generic software driver to perform parametric and probabilistic analysis of code simulating complex systems. Initially developed to provide dynamic risk analysis capabilities to the RELAP-7 code [1] is currently being generalized with the addition of Application Programming Interfaces (APIs). These interfaces are used to extend RAVEN capabilities to any software as long as all the parameters that need to be perturbed are accessible by inputs files or directly via python interfaces. RAVEN is capable to investigate the system response probing the input space using Monte Carlo, grid strategies, or Latin Hyper Cube schemes, but its strength is its focus toward system feature discovery like limit surfaces separating regions of the input space leading to system failure using dynamic supervised learning techniques. The paper will present an overview of the software capabilities and their implementation schemes followed by same application examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Data-Driven PMU Noise Emulation Framework using Gradient-Penalty-Based Wasserstein GAN

Availability of phasor measurement unit (PMUs) data has led to research on data-driven algorithms for event monitoring, control and ensuring stability of the grid. Unavailability of infrequent critical event field PMU data with component failures is driving the need to generate realistic synthetic PMU data for research. The synthetic data from power system simulation software often neglect noise profiles of received phasors, thus creating some discrepancies between real PMU data and synthetic ones. To address this issue, this work presents an initial study on the noise characteristics of PMUs, as well as presenting models for recreating their unique noise signatures. The proposed method, utilizing the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) architecture, provides an excellent benchmark for matching the noise distribution. One can use a well-learned GAN model to draw noise signatures from a distribution that seemingly mirrors the real PMU noise distribution, while also being able to be detached from the PMU data once the training is done. Based on the observed results and employed data-driven methodology, it is expected that the proposed methods can be adapted to replicate the behavior of other sensors, providing research and other applications with a tool for data synthesis and sensor characterization.

PMU↗
NASA NTRS2023

Overview of the NASA Spacecraft Trade Modeling System (NSTRDMS), A Rapid Mission Analysis Tool

A rapid mission analysis tool is developed to support the ongoing design of the Lunar Transit trajectory of the Power and Propulsion Element (PPE). A 50-kW class electric propulsion system is envisioned to transit a massive vehicle be-tween a Medium Earth Orbit (MEO) parking orbit and a lunar L2 southern Near Rectilinear Halo Orbit (NRHO). A parameterization is developed by which the Lunar Transit can be analyzed in the context of varying vehicle mass, solar elec-tric propulsion (SEP) configurations, and solar array power output. A rapid and novel mission analysis tool enables a wide array of these trade analyses to be completed without the need for extensive computing resources or time. This tool is shown to be useful in the analysis of a reference trajectory, where changes to the baseline vehicle architecture or off-nominal operational scenarios (such as electric thruster failures) can be rapidly assessed by the mission designer.

Low thrust↗
NASA NTRS1998

CARES/Life Ceramics Durability Evaluation Software Used for Mars Microprobe Aeroshell

The CARES/Life computer program, which was developed at the NASA Lewis Research Center, predicts the probability of a monolithic ceramic component's failure as a function of time in service. The program has many features and options for materials evaluation and component design. It couples commercial finite element programs-which resolve a component's temperature and stress distribution-to-reliability evaluation and fracture mechanics routines for modeling strength-limiting defects. These routines are based on calculations of the probabilistic nature of the brittle material's strength. The capability, flexibility, and uniqueness of CARES/Life has attracted many users representing a broad range of interests and has resulted in numerous awards for technological achievements and technology transfer.

Nemeth, Noel N.↗
DOE OSTI2024

Software Quality Assurance Plan ANSYS LSDYNA Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic and electromagnetic simulation capabilities. ANSYS LS-DYNA is the most used explicit simulation program capable of simulating the response of materials to short periods of severe loading. Its many elements, contact formulations, material models, and other controls can be used to simulate complex models with control over all the details of the problem. ANSYS LS-DYNA has a vast array of capabilities to simulate extreme deformation problems using its explicit solver. Engineers can tackle simulations involving material failure and look at how the failure progresses through a part or through a system. Models with large amounts of parts or surfaces interacting with each other are also easily handled, and the interactions and load passing between complex behaviors are modeled accurately. Using computers with higher numbers of CPU cores can drastically reduce solution times. In addition, many consulting firms and hundreds of universities use ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. ANSYS has successfully passed over 100 customer quality system audits against American Society of Mechanical Engineers (ASME) NQA-1 and 10 CFR Part 50, Appendix B, since the company was founded, over 60 of which have been since 1997. ANSYS has successfully passed over 100 International Organization for Standardization (ISO) 9001 assessments. ANSYS design analysis software is the first created within a quality system with ISO 9001 certification, which is the internationally accepted quality standard. Product development, testing, maintenance, and support processes also meet the US Nuclear Regulatory Commission’s (NRC’s) quality requirements, as they have for nearly four decades. ANSYS staff perform more than 60,000 software verification tests before releasing each new product. ASME NQA-1-2012 (Subpart 2.7 is specific to software) is the industry- and NRC-accepted approach (consensus standard) for meeting 10 CFR Part 50, Appendix B, requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Computational Modeling of Graphite Degradation due to Molten Salt Infiltration and Wear

Molten-salt reactors (MSRs) represent a promising next-generation reactor design, with graphite serving as a moderator and/or reflector in several designs. However, due to limited experimental data and operational experience, a technical understanding of the structural integrity of graphite in molten salt environments remains incomplete. This report presents a modeling-based evaluation of graphite degradation in MSR environments, focusing on the effects of salt infiltration in fuel salt-based designs and surface wear in pebble bed reactor designs. The objective of this study is to enhance understanding of the structural integrity challenges posed by these degradation mechanisms and to provide a framework for assessing graphite behavior in MSRs. The first part of the report investigates the phenomenon of molten salt infiltration into graphite. This infiltration occurs when molten salt permeates the interconnected pore structure of the graphite moderator, driven by factors such as pressure differentials and the physical properties of both the salt and graphite. The infiltration process is influenced by characteristics of the pore structure, viscosity of the molten salt, and the interfacial energies between the graphite, salt, and the atmosphere within the graphite pore. Utilizing a coupled multiphysics modeling approach with Grizzly software, the study evaluates the stress induced by internal heat sources due to infiltration, which can lead to structural concerns. This evaluation is crucial for understanding how infiltration affects the mechanical integrity of graphite components in MSRs. The study considers the Molten-Salt Reactor Experiment (MSRE) graphite stringer geometry due to the availability of relevant data. Through detailed finite element analysis, the study examines stress distributions at varying infiltration percentages, revealing that stress levels increase with higher amounts of infiltration. Rare-event simulations, using the parallel subset simulation (PSS) framework, further quantify the failure probabilities under input uncertainties, with a user-specified failure metric. The PSS framework also identifies critical input parameters that significantly affect the stress values, including infiltration amount, thermal conductivity, and power density. Additionally, considering realistic reactor scenarios, the analysis was performed to account for the combined effects of radiation and infiltration, and modeling strategies on how to analyze new reactor designs or new graphite grades are discussed. The second part of the report focuses on wear mechanisms in pebble bed-based MSRs. As graphite fuel pebbles interact with the graphite reflector block, wear can result in material loss and the formation of surface defects, which may act as stress concentrators. A similar multiphysics modeling framework is employed to assess the impact of wear on the structural integrity of graphite components. This study considers a generic fluoride-cooled high-temperature reactor (gFHR) design due to the availability of comprehensive data. Worst-case scenario dimensions of the reflector blocks were analyzed under thermal and radiation conditions. Subsequently, wear in the form of idealized pits and grooves is modeled on the inner surface of the graphite block, with the maximum stress from previous simulations. The simulations show that groove-type defects are more detrimental than pits, leading to higher stress concentrations. Considering worst-case simulation scenarios and experimental wear rates, it was determined that the formation of a surface defect critical enough to affect the stress may not be possible in a gFHR design. Overall, the findings of this research contribute to the development of robust modeling tools for predicting graphite behavior under various operational conditions in MSRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Moore vs. Murphy: Tradeoffs between complexity and reliability in distributed energy system scheduling using software-as-a-service

Software-based optimization of building control strategies, including scheduling, has the potential to improve the performance of existing complex heating, ventilation, and air conditioning (HVAC), storage, and other systems—especially if temporally variable energy production, such as solar thermal or photovoltaics, is included. If reductions in energy bills can be achieved using optimized control strategies that take advantage of cost-saving opportunities, such as time-of-use pricing, the additional bill savings can cover further efficiency investment costs. As computer processing becomes cheaper over time (Moore's Law), opportunities to perform complex control optimization become more abundant, and these can be performed remotely as software-as-a-service (SaaS). However, by “perfecting” our control strategies, we run an increased risk that when something unexpected happens (Murphy's Law), the consequences of failure are greater. This study used simulation to explore the potential benefits of HVAC schedule optimization, delivery, and implementation using a SaaS paradigm, at various levels of complexity. Implementing optimal schedules in a model of an efficient building's HVAC system, the study predicts energy cost savings of up to 10% compared to the naïve reference control strategy. Optimizing more system control variables increases the potential energy cost savings; however, these savings could be compromised by failures in communication inherent in delivering schedules via SaaS. The additional cost of energy resulting from the risk of increased demand charges generally increased with increased communication failure to a much larger extent than the risk of increased energy use charges. This work suggests that moderate improvements in performance, achieved at low cost by simple means, may be more effective than highly optimized schemes, which are more susceptible to failure due to their dependence on complex interactions between systems.

42 ENGINEERING↗
NASA NTRS1981

Measurement of fault latency in a digital avionic miniprocessor

The results of fault injection experiments utilizing a gate-level emulation of the central processor unit of the Bendix BDX-930 digital computer are presented. The failure detection coverage of comparison-monitoring and a typical avionics CPU self-test program was determined. The specific tasks and experiments included: (1) inject randomly selected gate-level and pin-level faults and emulate six software programs using comparison-monitoring to detect the faults; (2) based upon the derived empirical data develop and validate a model of fault latency that will forecast a software program's detecting ability; (3) given a typical avionics self-test program, inject randomly selected faults at both the gate-level and pin-level and determine the proportion of faults detected; (4) determine why faults were undetected; (5) recommend how the emulation can be extended to multiprocessor systems such as SIFT; and (6) determine the proportion of faults detected by a uniprocessor BIT (built-in-test) irrespective of self-test.

Mcgough, J. G.↗
NASA NTRS2010

Optimization Testbed Cometboards Extended into Stochastic Domain

COMparative Evaluation Testbed of Optimization and Analysis Routines for the Design of Structures (CometBoards) is a multidisciplinary design optimization software. It was originally developed for deterministic calculation. It has now been extended into the stochastic domain for structural design problems. For deterministic problems, CometBoards is introduced through its subproblem solution strategy as well as the approximation concept in optimization. In the stochastic domain, a design is formulated as a function of the risk or reliability. Optimum solution including the weight of a structure, is also obtained as a function of reliability. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to 50 percent probability of success, or one failure in two samples. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponded to unity for reliability. Weight can be reduced to a small value for the most failure-prone design with a compromised reliability approaching zero. The stochastic design optimization (SDO) capability for an industrial problem was obtained by combining three codes: MSC/Nastran code was the deterministic analysis tool, fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life airframe component made of metallic and composite materials.

Patnaik, Surya N.↗
DOE OSTI2014

HyRAM (Hydrogen Risk Assessment Models) v. 1.0 (alpha)

HyRAM is a software toolkit that integrates data and methods relevant to assessing the safety of hydrogen fueling and storage infrastructure. The HyRAM toolkit integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing the impact of hydrogen hazards (thermal effects from jet fires, thermal pressure effects from deflagrations) on people and structures. HyRAM incorporates generic probabilities for equipment failures for nine types of components, and probabilistic models for the impact of heat flux on humans and structures, with computationally and experimentally validated models of hydrogen release and flame physics. Version 1.0.0.280 can be used to quantify the likelihood and thermal consequences associated with gaseous hydrogen releases from user-defined hydrogen installations.

Groth, Katrina M.↗