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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 883 records · Page 49

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NASA NTRS1975

System reliability analysis through corona testing

In the Reliability and Quality Engineering Test Laboratory at the NASA Lewis Research Center a nondestructive, corona-vacuum test facility for testing power system components was developed using commercially available hardware. The test facility was developed to simulate operating temperature and vacuum while monitoring corona discharges with residual gases. This facility is being used to test various high voltage power system components.

Lalli, V. R.↗

NASA NTRS1980

Modified aerospace reliability and quality assurance method for wind turbines

The safety, reliability, and quality assurance (SR&QA) approach developed for the first large wind turbine generator project is described. The SR&QA approach was used to assure that the machine would not be hazardous to the public or operating personnel, would operate unattended on a utility grid, would demonstrate reliable operation and would help establish the quality assurance and maintainability requirements for future wind turbine projects. A modified failure modes and effects analysis during the design phase, minimal hardware inspections during parts fabrication, and three simple documents to control activities during machine construction and operation were presented.

Klein, W. E.↗

NASA NTRS1982

Stress analysis and design considerations for Shuttle pointed autonomous research tool for astronomy /SPARTAN/

The Shuttle Pointed Autonomous Research Tool for Astronomy (SPARTAN) family of spacecraft are intended to operate with minimum interfaces with the U.S. Space Shuttle in order to increase flight opportunities. The SPARTAN I Spacecraft was designed to enhance structural capabilities and increase reliability. The approach followed results from work experience which evolved from sounding rocket projects. Structural models were developed to do the analyses necessary to satisfy safety requirements for Shuttle hardware. A loads analysis must also be performed. Stress analysis calculations will be performed on the main structural elements and subcomponents. Attention is given to design considerations and program definition, the schematic representation of a finite element model used for SPARTAN I spacecraft, details of loads analysis, the stress analysis, and fracture mechanics plan implications.

Ferragut, N. J.↗

NASA NTRS1989

A performance assessment of a byzantine resilient fault-tolerant computer

This report presents the results of a performance analysis of a quad-redundant Fault-Tolerant Processor (FTP). The FTP is a computing system specifically designed for applications where very high reliability is required. Examples of such applications are flight control systems, nuclear power systems, and spacecraft control systems. The FTP performance was analyzed in a hierarchical manner encompassing the hardware, the operating system, and the application. At the hardware level, the hardware organization and design was assessed in relation to system throughput and response. Analysis at the operating system level revealed that the scheduler took only 3.2 percent of each 40ms frame, while the redundancy management software took 10.4 percent. The application level performance was analyzed via a synthetic workload and a representative flight control model. The estimated throughput for this application was found to be 317.6 KIPS if not exercising the voter. Exercising the voter to ensure fault tolerance will diminish this number linearly as the number of votes is increased. This performance analysis method was proven effective by uncovering undesirable behavior and anomalies in the FTP system.

Young, Steven D.↗

NASA NTRS1999

A New Compendium of Unsteady Aerodynamic Test Cases for CFD: Summary of AVT WG-003 Activities

With the continuous progress in hardware and numerical schemes, Computational Unsteady Aerodynamics (CUA), that is, the application of Computational Fluid Dynamics (CFD) to unsteady flowfields, is slowly finding its way as a useful and reliable tool (turbulence and transition modeling permitting) in the aircraft, helicopter, engine and missile design and development process. Before a specific code may be used with confidence it is essential to validate its capability to describe the physics of the flow correctly, or at least to the level of approximation required, for which purpose a comparison with accurate experimental data is needed. Unsteady wind tunnel testing is difficult and expensive; two factors which dramatically limit the number of organizations with the capability and/or resources to perform it. Thus, unsteady experimental data is scarce, often classified and scattered in diverse documents. Additionally, access to the reports does not necessarily assure access to the data itself. The collaborative effort described in this paper was conceived with the aim of collecting into a single easily accessible document as much quality data as possible. The idea is not new. In the early 80's NATO's AGARD (Advisory Group for Aerospace Research & Development) Structures and Material Panel (SMP) produced AGARD Report No. 702 "Compendium of Unsteady Aerodynamic Measurements", which has found and continues to find extensive use within the CUA Community. In 1995 AGARD's Fluid Dynamics Panel (FDP) decided to update and expand the former database with new geometries and physical phenomena, and launched Working Group WG-22 on "Validation Data for Computational Unsteady Aerodynamic Codes". Shortly afterwards AGARD was reorganized as the RTO (Research and Technology Organization) and the WG was renamed as AVT (Applied Vehicle Technolology) WG-003. Contributions were received from AEDC, BAe, DLR, DERA, Glasgow University, IAR, NAL, NASA, NLR, and ONERA. The final publication with the results of the exercise is expected in the second part of 1999. The aim of the present paper is to announce and present the new database to the Aeroelasticity community. It is also intended to identify, together with one of the groups of end users it targets, deficiencies in the compendium that should be addressed by means of new wind tunnel tests or by obtaining access to additionally existing data.

Ruiz-Calavera, Luis P.↗

NASA NTRS2013

Performance Measurement of Advanced Stirling Convertors (ASC-E3)

NASA Glenn Research Center (GRC) has been supporting development of the Advanced Stirling Radioisotope Generator (ASRG) since 2006. A key element of the ASRG project is providing life, reliability, and performance testing data of the Advanced Stirling Convertor (ASC). The latest version of the ASC (ASC-E3, to represent the third cycle of engineering model test hardware) is of a design identical to the forthcoming flight convertors. For this generation of hardware, a joint Sunpower and GRC effort was initiated to improve and standardize the test support hardware. After this effort was completed, the first pair of ASC-E3 units was produced by Sunpower and then delivered to GRC in December 2012. GRC has begun operation of these units. This process included performance verification, which examined the data from various tests to validate the convertor performance to the product specification. Other tests included detailed performance mapping that encompassed the wide range of operating conditions that will exist during a mission. These convertors were then transferred to Lockheed Martin for controller checkout testing. The results of this latest convertor performance verification activity are summarized here.

Stirling Cycle↗

NASA NTRS2017

Practical Applications of Cables and Ropes in the ISS Countermeasures System

As spaceflight durations have increased over the last four decades, the effects of weightlessness on the human body are far better understood, as are the countermeasures. A combination of aerobic and resistive exercise devices contribute to countering the losses in muscle strength, aerobic fitness, and bone strength of today's astronauts and cosmonauts that occur during their missions on the International Space Station. Creation of these systems has been a dynamically educational experience for designers and engineers. The ropes and cables in particular have experienced a wide range of challenges, providing a full set of lessons learned that have already enabled improvements in on-orbit reliability by initiating system design improvements. This paper examines the on-orbit experience of ropes and cables in several exercise devices and discusses the lessons learned from these hardware items, with the goal of informing future system design.

Moore, Cherice↗

NASA NTRS2019

Radar Detection of High Concentrations of Ice Particles - Methodology and Preliminary Flight Test Results

High Ice Water Content (HIWC) has been identified as a primary causal factor in numerous engine events over the past two decades. Previous attempts to develop a remote detection process utilizing modern commercial radars have failed to produce reliable results. This paper discusses the reasons for previous failures and describes a new technique that has shown very encouraging accuracy and range performance without the need for any hardware modifications to industry’s current radar designs. The performance of this new process was evaluated during the joint NASA/FAA HIWC RADAR II Flight Campaign in August of 2018. Results from that evaluation are discussed, along with the potential for commercial application, and development of minimum operational performance standards for a future commercial radar product.

Harrah, Steven D.↗

NASA NTRSDate not supplied

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. This was expected to accelerate development and provide more cost-effective, time-saving solutions. This work was selected for a NASA Crowdsourcing project through an agency-wide solicitation. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation and an execution crowdsourcing platform partner to solicit framework developments from external contenders. NASA provided contenders with video clips of spacesuits and simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy (weighted combination of scoring metrics). Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA simulation environments such as the Neutral Buoyancy Lab (NBL). However, 3D joint identification is less reliable when parts of the suit were obstructed in the image. After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗

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↗

DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Quantum Readout Signals Using Adaptive Hardware Filters on FPGA

This research presents an innovative approach to improving the Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals, utilizing FPGA-based adaptive filtering on the control board. Our solution aims to bolster quantum computations' reliability by providing a more accurate and precise way to obtain our readout traces and achieve a higher discernability between excitation states in real-time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Test Points for Online Monitoring of Quantum Circuits

Noisy Intermediate-Scale Quantum (NISQ) computers consisting of tens of inherently noisy quantum bits (qubits) suffer from reliability problems. Qubits and their gates are susceptible to various types of errors. Due to limited numbers of qubits and high error rates, quantum error correction cannot be applied. Physical constraints of quantum hardware including the error rates are used to guide the design and the layout of quantum circuits. The error rates determine the selection of qubits and their operations. The resulting circuit is executed on the quantum computer. This study explores the risk of unexpected changes in the error rates of NISQ computers post-calibration. We show that unexpected changes in error rates can alter the output state of a quantum circuit. To detect these changes, we propose the insertion of test points into the quantum circuit to enable online monitoring of the physical qubit behavior. We utilize classical, superposition, and uncompute test points. Furthermore, we use a gate error coverage metric to assess the quality of the tests. We verify the effectiveness of the proposed scheme on different IBM quantum computers (IBM Q), in addition to a noisy simulation that shows the scalability of the proposed approach.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Enhancing the Quality and Reliability of Machine Learning Interatomic Potentials through Better Reporting Practices

Recent developments in machine learning interatomic potentials (MLIPs) have empowered even nonexperts in machine learning to train MLIPs for accelerating materials simulations. However, reproducibility and independent evaluation of presented MLIP results is hindered by a lack of clear standards in current literature. In this Perspective, we aim to provide guidance on best practices for documenting MLIP use while walking the reader through the development and deployment of MLIPs including hardware and software requirements, generating training data, training models, validating predictions, and MLIP inference. We also suggest useful plotting practices and analyses to validate and boost confidence in the deployed models. Finally, we provide a step-by-step checklist for practitioners to use directly before publication to standardize the information to be reported. Altogether, we hope that our work will encourage the reliable and reproducible use of these MLIPs, which will accelerate their ability to make a positive impact in various disciplines including materials science, chemistry, and biology, among others.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Highly Reliable Multi-Port Smart Inverter Modules for PV-Based Energy Systems

Generally, large electrolytic capacitors (E-caps) are required to decouple the double-line frequency power fluctuation inherent in all single-phase dc-ac or ac-dc converters. These E-caps pose the weak link in the photovoltaic (PV) inverter because they have poor reliability as a result of short life expectancy and higher equivalent series resistance (ESR) which leads to lower system efficiency. In this paper, multiport smart dual-inverter modules are proposed for residential PV inverter systems with balanced outputs to eliminate the requirement of large decoupling capacitors, thus leading to more reliable and highly efficient inverter modules. The balanced dual outputs are controlled in phase quadrature such that the double frequency current is completely eliminated. One phase supports the standalone residential loads, and the other phase interfaces with the grid, which is synchronized to the utility grid. Also, the proposed modular configuration is scalable to accommodate higher power rating by stacking and paralleling multiple modules. Simulation results for the dual-inverter modules rated for 1 kW each are presented to validate the proposed concept. Experimental results from a controller hardware-in-the-loop (CHIL) platform also verify its feasibility.

14 SOLAR ENERGY↗

NASA NTRS2014

Portable Load Measurement Device for Use During ARED Exercise on ISS

The Advanced Resistive Exercise Device (ARED) (Fig.1) is unique countermeasure hardware available to crewmembers aboard the International Space Station (ISS) used for resistance exercise training to protect against bone and muscle loss during long duration space missions. ARED instrumentation system was designed to measure and record exercise load data, but: - Reliably accurate data has not been available due to a defective force platform. - No ARED data has been recorded since mid-2011 due to failures in the instrumentation power system. ARED load data supports on-going HRP funded research, and is available to extramural researchers through LSDA-Repository. Astronaut Strength, Conditioning, and Rehabilitation specialists (ASCRs) use ARED data to track training progress and advance exercise prescriptions. ARED load data is necessary to fulfill medical requirements. HRP directed task intends to reduce to program risk (HRP IRMA Risk 1735), and evaluate the XSENS ForceShoeTM as a means of obtaining ARED load data during exercise sessions. The XSENS ForceShoes"TM" will fly as a hardware demonstration to ISS in May 2014 (39S). Additional portable load monitoring devices (PLMDs) are under evaluation in the ExPC Lab. PLMDs are favored over platform redesign as they support future exploration needs.

Hanson, A.↗

DOE OSTI2016

Nondisruptive Dissolution of Hyperpolarized 129 Xe into Viscous Aqueous and Organic Liquid Crystalline Environments

Studies of hyperpolarized xenon-129 (hp- 129 Xe) in media such as liquid crystals and cell suspensions are in demand for applications ranging from biomedical imaging to materials engineering but have been hindered by the inability to bubble Xe through the desired media as a result of viscosity or perturbations caused by bubbles. In this paper a device is reported that can be reliably used to dissolve hp- 129 Xe into viscous aqueous and organic samples without bubbling. This method is robust, requires small sample volumes (<60 μL), is compatible with existing NMR hardware, and is made from readily available materials. Experiments show that Xe can be introduced into viscous and aligned media without disrupting molecular order. We detected dissolved xenon in an aqueous liquid crystal that is disrupted by the shear forces of bubbling, and we observed liquid-crystal phase transitions in (MBBA). This tool allows an entirely new class of samples to be investigated by hyperpolarized-gas NMR spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Validation of Microgrid Algorithms using At-Scale Simulation and Emulation Real-Time (ASSERT) Framework

This paper presents a novel framework for validating microgrid algorithms using a At-Scale Simulation and Emulation Real-Time (ASSERT) setup. The proposed universal microgrid validation framework was developed at Advanced Research on Integrated Energy Systems (ARIES) platform at National Renewable Energy Laboratory in Golden, Colorado, USA. As the number of intercommunicating devices grow in power systems, along with more integration of inverter-based resources, developing and validating microgrid operation and control algorithms is becoming complex and time-consuming task. The ASSERT framework is designed to provide a comprehensive, accurate, and efficient solution for validating microgrid algorithms. It combines at-scale simulations and real-time emulation to create a virtual environment that closely mimics the behavior of a physical microgrids which are characteristic of future smart distribution systems, such as: (1) increasing variability in the physical size of new energy technologies; (2) requiring control large numbers of interconnected devices, and (3) integrating diverse technologies that have not previously worked together. The paper describes the technical details of the ASSERT framework, its validation process, and its benefits over traditional validation methods. The framework's ability to validate the performance of various algorithms is demonstrated through a case study, which shows that it can effectively identify the weaknesses of an algorithm and optimize its performance. Overall, the ASSERT framework is a promising tool that can significantly enhance the development and validation of microgrid algorithms, leading to more reliable and efficient microgrid operation.

at-scale↗

DOE OSTI2023

Measurement and applications: Exploring the challenges and opportunities of hierarchical federated learning in sensor applications

Sensor applications have become ubiquitous in modern society as the digital age continues to advance. AI-based techniques (e.g., machine learning) are effective at extracting actionable information from large amounts of data. An example would be an automated water irrigation system that uses AI-based techniques on soil quality data to decide how to best distribute water. However, these AI-based techniques are costly in terms of hardware resources, and Internet-of-Things (IoT) sensors are resource-constrained with respect to processing power, energy, and storage capacity. These limitations can compromise the security, performance, and reliability of sensor-driven applications. To address these concerns, cloud computing services can be used by sensor applications for data storage and processing. Unfortunately, cloud-based sensor applications that require real-time processing, such as medical applications (e.g., fall detection and stroke prediction), are vulnerable to issues such as network latency due to the sparse and unreliable networks between the sensor nodes and the cloud server [1]. As users approach the edge of the communications network, latency issues become more severe and frequent. A promising alternative is edge computing, which provides cloud-like capabilities at the edge of the network by pushing storage and processing capabilities from centralized nodes to edge devices that are closer to where the data are gathered, resulting in reduced network delays [2], [3].

Po-Leen Ooi, Melanie↗