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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Surface and Airborne Monitoring Technology for Detecting Geologic Leakage in a CO 2 -Enhanced Oil Recovery Pilot, Anadarko Basin, Texas

Surface and airborne gas monitoring programs are becoming an important part of environmental protection in areas favorable for subsurface storage of carbon dioxide. Understanding structural architecture and its effects on the flux of fluids, specifically CO 2 and CH 4 , in the shallow subsurface and atmosphere is helping design and implement next generation monitoring technologies, including unmanned aerial vehicles (UAVs). An important aspect of this research is using subsurface fracture data to inform the design of flight pathways for UAVs in the Farnsworth Oil Unit of the Anadarko Basin. The target zone for CO 2 storage and enhanced oil recovery in the Farnsworth Oil Unit is in the upper Morrow sandstone at subsurface depths greater than 2,000 m. Field study reveals that sandstone and chert in the High Plains Aquifer contain numerous joints that provide crucial insight into aquifer architecture and subsurface flow pathways. Properties of more than 1,700 joints were measured in the field and in high-resolution satellite images. Two distinctive joint systems interpreted as a conjugate pair were identified in the study area. Joint spacing follows a log-normal statistical scaling rule. These fractures appear to be the product of an E-NE regional compressive stress and may have a significant effect on flow in the High Plains Aquifer system. Based on the results of this research, design of UAV flight paths should be oblique to fractures in a way that maximizes the likelihood of CO 2 and CH 4 flux from of systematic joints and cross joints. Detection of leaks either from subsurface seal failures or surface equipment problems is important to insure that stored CO 2 is not being lost to the atmosphere. In the case of surface leaks, costs go up and injection efficiency goes down. Surface leaks are often short term caused by seal leaks, pop off valves, or other equipment failure modes. In either case, CO 2 is released to the atmosphere. This projects primary goal was to explore the use of low cost sensors coupled with the appropriate hardware and software to produce a low cost system capable of detecting both long and short term leaks. In addition, an aerial system was designed to measure the CO 2 and CH 4 distributions above the surface. Both the ground and UAV based systems were designed, tested and deployed in the Farnsworth field.

02 PETROLEUM↗
NASA NTRS1985

Pilot interaction with automated airborne decision making systems

Progress was made in the three following areas. In the rule-based modeling area, two papers related to identification and significane testing of rule-based models were presented. In the area of operator aiding, research focused on aiding operators in novel failure situations; a discrete control modeling approach to aiding PLANT operators was developed; and a set of guidelines were developed for implementing automation. In the area of flight simulator hardware and software, the hardware will be completed within two months and initial simulation software will then be integrated and tested.

Rouse, W. B.↗
NASA NTRS1993

Advanced Information Processing System (AIPS)

Advanced Information Processing System (AIPS) is a computer systems philosophy, a set of validated hardware building blocks, and a set of validated services as embodied in system software. The goal of AIPS is to provide the knowledgebase which will allow achievement of validated fault-tolerant distributed computer system architectures, suitable for a broad range of applications, having failure probability requirements of 10E-9 at 10 hours. A background and description is given followed by program accomplishments, the current focus, applications, technology transfer, FY92 accomplishments, and funding.

Pitts, Felix L.↗
NASA NTRS1992

RICIS Symposium 1992: Mission and Safety Critical Systems Research and Applications

This conference deals with computer systems which control systems whose failure to operate correctly could produce the loss of life and or property, mission and safety critical systems. Topics covered are: the work of standards groups, computer systems design and architecture, software reliability, process control systems, knowledge based expert systems, and computer and telecommunication protocols.

Source record↗
NASA NTRS1997

CARES/Life Software for Designing More Reliable Ceramic Parts

Products made from advanced ceramics show great promise for revolutionizing aerospace and terrestrial propulsion, and power generation. However, ceramic components are difficult to design because brittle materials in general have widely varying strength values. The CAPES/Life software eases this task by providing a tool to optimize the design and manufacture of brittle material components using probabilistic reliability analysis techniques. Probabilistic component design involves predicting the probability of failure for a thermomechanically loaded component from specimen rupture data. Typically, these experiments are performed using many simple geometry flexural or tensile test specimens. A static, dynamic, or cyclic load is applied to each specimen until fracture. Statistical strength and SCG (fatigue) parameters are then determined from these data. Using these parameters and the results obtained from a finite element analysis, the time-dependent reliability for a complex component geometry and loading is then predicted. Appropriate design changes are made until an acceptable probability of failure has been reached.

Nemeth, Noel N.↗
DOE OSTI2020

Implementing Software Resiliency in HPX for Extreme Scale Computing

The DOE Office of Science Exascale Computing Project (ECP) outlines the next milestones in the supercomputing domain. The target computing systems under the project will deliver 10x performance while keeping the power budget under 30 megawatts. With such large machines, the need to make applications resilient has become paramount. The benefits of adding resiliency to mission critical and scientific applications, includes the reduced cost of restarting the failed simulation both in terms of time and power. Most of the current implementation of resiliency at the software level makes use of a Coordinated Checkpoint and Restart (C/R). This technique of resiliency generates a consistent global snapshot, also called a checkpoint. Generating snapshots involves global communication and coordination and is achieved by synchronizing all running processes. The generated checkpoint is then stored in some form of persistent storage. On failure detection, the runtime initiates a global rollback to the most recent previously saved checkpoint. This involves aborting all running processes, rolling them back to the previous state and restarting them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A software package for plasma facing component analysis and design: the Heat flux Engineering Analysis Toolkit (HEAT)

The engineering limits of plasma facing components (PFCs) constrain the allowable operational space of tokamaks. Poorly managed heat fluxes that push the PFCs beyond their limits not only degrade core plasma performance via elevated impurities, but can also result in PFC failure due to thermal stresses or melting. Simple axisymmetric assumptions fail to capture the complex interaction between 3D PFC geometry and 2D or 3D plasmas. This results in fusion systems that must either operate with increased risk or reduce PFC loads, potentially through lower core plasma performance, to maintain a nominal safety factor. High precision 3D heat flux predictions are necessary to accurately ascertain the state of a PFC given the evolution of the magnetic equilibrium. A new code, the Heat flux Engineering Analysis Toolkit (HEAT), has been developed to provide high precision 3D predictions and analysis for PFCs. HEAT couples many otherwise disparate computational tools together into a single open source python package. Magnetic equilibrium, engineering CAD, finite volume solvers, scrape off layer plasma physics, visualization, high performace computing, and more, are connected in a single web-based user interface. Linux users may use HEAT without any software prerequisites via an appImage. This manuscript introduces HEAT, discusses the software architecture, presents first HEAT results, and outlines physics modules in development.

divertor physics↗
NASA NTRS2022

Making or Breaking a Rover: System Engineering Parameters On-Board the Mars 2020 Perseverance Rover

On February 18, 2021, Perseverance, NASA’s Jet Propulsion Laboratory’s (JPL’s) Mars 2020 Rover, successfully landed on Mars with all systems nominal, despite the risk surrounding the over 200,000 internal flight parameters that had to be properly configured. The Perseverance team defines these parameters as software variables that are configurable, commandable and retrievable from Earth. In 2015, the Mars 2020 project leaders focused on improving systems engineering of parameters based on their experiences from parameter management on previous Mars rovers (Curiosity, Opportunity, Spirit, and Pathfinder) and parameter failures of past missions, such as the mission-ending parameter of the Mars Climate Orbiter. The new rigorous development process allowed for efficient certification and effective implementation of the parameters, allowing the rover to approach and land on the red planet (the most challenging phase of the mission) with zero parameter issues. Although successful, the Perseverance team learned many lessons for how to better manage parameters for the continued surface operations of the Mars 2020 mission and future missions. This paper will discuss eight parameter-management topics for the Perseverance Mission. The first is parameter definition: how we define parameters on our mission, where they are physically located on the vehicle, and why we have so many of them. The second topic is the updated parameter flight software module from Curiosity, including details on the 99% reduction in parameter commands, new bulk configuration capabilities, and improved parameter traceability. The third topic is parameter selection for different mission phases; this includes improving and tweaking our preferred parameter settings until they become certification candidates and managing parameter configurations based on test venue throughout the mission life cycle. The fourth topic is our flight certification process; this includes certification of flight values for four different epochs in the mission: Launch, Entry Decent and Landing (EDL) - 6days, Landing + 5 Sols (Martian Days, still on Cruise Flight Software), and once are on Surface Flight Software (FSW). The fifth topic covers in-flight command implementation, along with details on testing, validation, and verification of those commands. In the sixth section, we will explain our use of open-source management tools, including how we used GitHub for version control and management approvals. The seventh topic will describe the ground tools used in operations, including capabilities of the in-house built tool called Parasol. The eighth and final topic will dig into lessons learned for improving parameter management in the future of this mission and others.

Roth, Brian↗
NASA NTRS2022

Making or Breaking a Rover- Systems Engineering Parameters On-Board the Mars 2020 Perseverance Rover

On February 18, 2021, Perseverance, NASA’s Jet Propulsion Laboratory’s (JPL’s) Mars 2020 Rover, successfully landed on Mars with all systems nominal, despite the risk surrounding the over 200,000 internal flight parameters that had to be properly configured. The Perseverance team defines these parameters as software variables that are configurable, commandable and retrievable from Earth. In 2015, the Mars 2020 project leaders focused on improving systems engineering of parameters based on their experiences from parameter management on previous Mars rovers (Curiosity, Opportunity, Spirit, and Pathfinder) and parameter failures of past missions, such as the mission-ending parameter of the Mars Climate Orbiter. The new rigorous development process allowed for efficient certification and effective implementation of the parameters, allowing the rover to approach and land on the red planet (the most challenging phase of the mission) with zero parameter issues. Although successful, the Perseverance team learned many lessons for how to better manage parameters for the continued surface operations of the Mars 2020 mission and future missions. This paper will discuss eight parameter-management topics for the Perseverance Mission. The first is parameter definition: how we define parameters on our mission, where they are physically located on the vehicle, and why we have so many of them. The second topic is the updated parameter flight software module from Curiosity, including details on the 99% reduction in parameter commands, new bulk configuration capabilities, and improved parameter traceability. The third topic is parameter selection for different mission phases; this includes improving and tweaking our preferred parameter settings until they become certification candidates and managing parameter configurations based on test venue throughout the mission life cycle. The fourth topic is our flight certification process; this includes certification of flight values for four different epochs in the mission: Launch, Entry Decent and Landing (EDL) - 6days, Landing + 5 Sols (Martian Days, still on Cruise Flight Software), and once are on Surface Flight Software (FSW). The fifth topic covers in-flight command implementation, along with details on testing, validation, and verification of those commands. In the sixth section, we will explain our use of open-source management tools, including how we used GitHub for version control and management approvals. The seventh topic will describe the ground tools used in operations, including capabilities of the in-house built tool called Parasol. The eighth and final topic will dig into lessons learned for improving parameter management in the future of this mission and others.

Roth, Brian↗
DOE OSTI2018

Pattern-based Modeling of High-Performance Computing Resilience

With the growing scale and complexity of high-performance computing (HPC) systems, resilience solutions that ensure continuity of service despite frequent errors and component failures must be methodically designed to balance the reliability requirements with the overheads to performance and power. Design patterns enable a structured approach to the development of resilience solutions, providing hardware and software designers with the building block elements for the rapid development of novel solutions and for adapting existing technologies for emerging, extreme-scale HPC environments. In this paper, we develop analytical models that enable designers to evaluate the reliability and performance characteristics of the design patterns. These models are particularly useful in building a unified framework that analyzes and compares various resilience solutions built using a combination of patterns.

Hukerikar, Saurabh↗
DOE OSTI2016

Developing radiation tolerant polymer nanocomposites using C 60 as an additive

In nuclear facilities utilizing plutonium, polymeric materials are subjected to long-term, close-contact, and continuous α radiation exposure, which can lead to compounding material degradation and eventual failure. Herein we model the attenuation of α particles by linear-low-density polyethylene (LLDPE), polyvinyl alcohol (PVA) thin films, and C 60 using Monte Carlo N-Particle Extended (MCNPX) software. The degradation of these materials was investigated experimentally by irradiating them with a beam of α particles of 5.8 MeV energy at a tandem Van de Graaff accelerator delivering a dose rate of 2.95 × 10 6 rad s –1 over a 7.1 mm 2 sample area. Our development of a method to test α particle-induced material degradation using a tandem accelerator is significant as degradation from naturally occurring α sources (i.e. Pu, Am) occurs too slowly for these sources to be used in practical experiments. Our results show that PVA nanocomposites containing 5 wt% C 60 were found to withstand about 7 times the α dose of undoped PVA films before a puncture in the film was detected. When these films were adhered to a LLDPE sheet the dual layer polymer was capable of withstanding about 13 times the dose of LLDPE and nearly twice the dose of the doped PVA thin film alone. Doping polymers with C 60 is an attractive way to generate more durable, radiation tolerant materials without increasing the thickness of the material which would lead to greater waste for disposal. Furthermore, the results herein help to resolve a prevalent technical challenge faced in nuclear facilities that utilize polymeric materials for nuclear processing and disposal.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Seismic Contingency Auto Generator

This code takes in premade earthquake scenario XML files from USGS, power grid data, and converts them into a contingency file (.con file) that can be used by power grid solvers. Within the .con file are a number (Specified by the user) of contingencies that have randomly failed power transformers based on their likelihood of failure and peak ground acceleration (PGA) value around the transformer. The transformers' likelihood of failure was calculated based on a variety of finite element modeling on various transformer designed for specific transformer voltage classes. Parameters from these FEM were used to create generic fragility curves for transformers within a specific voltage class, which correspond with earthquake PGA values to produced a probability of failure for a given earthquake scenario. More refined versions of this process, such as specifying specific transformer design categories within a voltage class, could also be applied in future iterations of the software.

Vaagensmith, Bjorn [Idaho National Laboratory (INL↗
DOE OSTI2014

Pervasive Restart In MOOSE-based Applications

Multiphysics applications are inherently complicated. Solving for multiple, interacting physical phenomena involves the solution of multiple equations, and each equation has its own data dependencies. Feeding the correct data to these equations at exactly the right time requires extensive effort in software design. In an ideal world, multiphysics applications always run to completion and produce correct answers. Unfortunately, in reality, there can be many reasons why a simulation might fail: power outage, system failure, exceeding a runtime allotment on a supercomputer, failure of the solver to converge, etc. A failure after many hours spent computing can be a significant setback for a project. Therefore, the ability to “continue” a solve from the point of failure, rather than starting again from scratch, is an essential component of any high-quality simulation tool. This process of “continuation” is commonly termed “restart” in the computational community. While the concept of restarting an application sounds ideal, the aforementioned complexities and data dependencies present in multiphysics applications make its implementation decidedly non-trivial. A running multiphysics calculation accumulates an enormous amount of “state”: current time, solution history, material properties, status of mechanical contact, etc. This “state” data comes in many different forms, including scalar, tensor, vector, and arbitrary, application-specific data types. To be able to restart an application, you must be able to both store and retrieve this data, effectively recreating the state of the application before the failure. When utilizing the Multiphysics Object Oriented Simulation Environment (MOOSE) framework developed at Idaho National Laboratory, this state data is stored both internally within the framework itself (such as solution vectors and the current time) and within the applications that use the framework. In order to implement restart in MOOSE-based applications, the total state of the system (both within the framework and without) must be stored and retrieved. To this end, the MOOSE team has implemented a “pervasive” restart capability which allows any object within MOOSE (or within a MOOSE-based application) to be declared as “state” data, and handles the storage and retrieval of said data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Orthoimagery and Shapefiles Documenting Pre- and Post-August 2019 Slope Disturbances, Teller Road Site, Seward Peninsula, Alaska, 2018-2019

This dataset was derived from UAS aerial photos and dGPS data collected at the Teller mile marker 47 site in 2018 and 2019 and used to support research quantifying the timing and rate of surface movements and analyze soil transport process in Arctic landscapes. In July 2018, a Phantom uncrewed aerial system (UAS) collected >6800 high resolution aerial photos of the lower portion of the Teller 47 watershed (see for raw photos; pending archive NGA281). During the UAS survey, 25 x 25 cm tile ground control points (GCPs) were laid out and secured with one rebar rod in the center. The four corners and rebar tops were surveyed with differential GPS, and these coordinates were used to construct and validate an orthomosaic of the site. These points were resurveyed in August 2019 and used to track annual movement. Changes in position between the two surveys are reported in (Lathrop et al. 2022; NGA254). Agisoft Metashape photogrammetry software was used to construct a georeferenced orthomosaic image (*.tif file) of a portion (0.68 km2) of the watershed with a final resolution of ~1 cm. Manual delineation of the perimeters of failures visible in the UAS imagery (*.tif files) was conducted to create shapefile polygons (two *.zip files). The failures were identified by the exposure of bare mineral soils, which were made visible by disruption of the overlying tundra vegetation. The shapefiles were then used to analyse the topographic distribution and sizes of the failures. In August 2019 an additional ~300 georeferenced UAS images of slope instability features were collected (data pending submission) and compared with the 2018 orthomosaic. Overview maps of the failure locations included as a *.pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Develop advanced nonlinear signal analysis topographical mapping system

This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an advanced nonlinear signal analysis topographical mapping system (ATMS) of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbopump families.

Jong, Jen-Yi↗
NASA NTRS2006

Control of Technology Transfer at JPL

Controlled Technology: 1) Design: preliminary or critical design data, schematics, technical flow charts, SNV code/diagnostics, logic flow diagrams, wirelist, ICDs, detailed specifications or requirements. 2) Development: constraints, computations, configurations, technical analyses, acceptance criteria, anomaly resolution, detailed test plans, detailed technical proposals. 3) Production: process or how-to: assemble, operated, repair, maintain, modify. 4) Manufacturing: technical instructions, specific parts, specific materials, specific qualities, specific processes, specific flow. 5) Operations: how-to operate, contingency or standard operating plans, Ops handbooks. 6) Repair: repair instructions, troubleshooting schemes, detailed schematics. 7) Test: specific procedures, data, analysis, detailed test plan and retest plans, detailed anomaly resolutions, detailed failure causes and corrective actions, troubleshooting, trended test data, flight readiness data. 8) Maintenance: maintenance schedules and plans, methods for regular upkeep, overhaul instructions. 9) Modification: modification instructions, upgrades kit parts, including software

Jet Propulsion Laboratory (JPL)↗
NASA NTRS2012

Rotorcraft Diagnostics

Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer decision support for optimal maintenance.

Haste, Deepak↗
NASA NTRS2012

Methods for Assessing Honeycomb Sandwich Panel Wrinkling Failures

Efficient closed-form methods for predicting the facesheet wrinkling failure mode in sandwich panels are assessed. Comparisons were made with finite element model predictions for facesheet wrinkling, and a validated closed-form method was implemented in the HyperSizer structure sizing software.

Zalewski, Bart F.↗