SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The goal of the mathematical and statistical analysis component of RICIS is to research, develop, and evaluate mathematical and statistical techniques for aerospace technology applications. Specific research areas of interest include modeling, simulation, experiment design, reliability assessment, and numerical analysis.
Described are the theoretical development and computer implementation of reliable and efficient methods for the analysis of coupled mechanical problems that involve the interaction of mechanical, thermal, phase-change and electromagnetic subproblems. The focus application has been the modeling of superconductivity and associated quantum-state phase-change phenomena. In support of this objective the work has addressed the following issues: (1) development of variational principles for finite elements, (2) finite element modeling of the electromagnetic problem, (3) coupling of thermal and mechanical effects, and (4) computer implementation and solution of the superconductivity transition problem. The main accomplishments have been: (1) the development of the theory of parametrized and gauged variational principles, (2) the application of those principled to the construction of electromagnetic, thermal and mechanical finite elements, and (3) the coupling of electromagnetic finite elements with thermal and superconducting effects, and (4) the first detailed finite element simulations of bulk superconductors, in particular the Meissner effect and the nature of the normal conducting boundary layer. The theoretical development is described in two volumes. This volume, Volume 1, describes mostly formulations for specific problems. Volume 2 describes generalization of those formulations.
Abstract Scanning X-ray fluorescence (XRF) tomography provides powerful characterization capabilities in evaluating elemental distribution and differentiating their inter- and intra-cellular interactions in a three-dimensional (3D) space. Scanning XRF tomography encounters practical challenges from the sample itself, where the range of rotation angles is limited by geometric constraints, involving sample substrates or nearby features either blocking or converging into the field of view. This study aims to develop a reliable and efficient workflow that can (1) expand the experimental window for nanoscale tomographic analysis of local areas of interest within a laterally extended specimen, and (2) bridge 3D analysis at micrometer and nanoscales on the same specimen. We demonstrate the workflow using a specimen of HeLa cells exposed to iron oxide core and titanium dioxide shell (Fe3O4/TiO2) nanocomposites. The workflow utilizes iterative and multiscale XRF data collection with intermediate sample processing by focused ion beam (FIB) sample preparation between measurements at different length scales. Initial assessment combined with precise sample manipulation via FIB allows direct removal of sample regions that are obstacles to both incident X-ray beam and outgoing XRF signals, which considerably improves the subsequent nanoscale tomography analysis. This multiscale analysis workflow has advanced bio-nanotechnology studies by providing deep insights into the interaction between nanocomposites and single cells at a subcellular level as well as statistical assessments from measuring a population of cells.
Current analytical methods are not capable of providing rapid, sensitive, and comprehensive chemical analysis of a wide range of cellular constitutes of single cells (e.g., lipids, metabolites, proteins, etc.) from dispersed cell suspensions and thin tissues. This capability is important for a number of critical applications, including discovery of cellular mechanisms for coping with chemical or environmental stress and cellular response to drug treatment, to name a few. Here we introduce an optically guided platform and methodology for rapid, automated recognition, sampling, and chemical analysis of surface confined individual cells utilizing a novel hybrid laser capture microdissection/liquid vortex capture/mass spectrometry system. The system enabled automated analysis of single cells by reliably detecting and sampling them either through laser ablation from a glass microscope slide or by cutting the entire cell out of a poly(ethylene naphthalate)-coated membrane substrate that the cellular sample is deposited on. Proof of principle experiments were performed using thin tissues of Allium cepa and cultured Euglena gracilis and Phacus cell suspensions as model systems for single cell analysis using the developed method. Reliable, hands-off laser ablation sampling coupled to liquid vortex capture/mass spectrometry analysis was conducted for hundreds of individual Allium cepa cells in connected tissue. In addition, more than 300 individual Euglena gracilis and Phacus cells were analyzed automatically and sampled using laser microdissection sampling with the same liquid vortex capture/mass spectrometry analysis system. Principal component analysis-linear discriminant analysis, applied to each mass spectral dataset, was used to determine the accuracy of differentiation of the different algae cell lines.
Composite Overwrapped Pressure Vessels (COPVs) are often used for storing pressurant gases on board spacecraft when mass saving is a prime requirement. Substantial weight savings can be achieved compared to all metallic pressure vessels. For example, on the space shuttle, replacement of all metallic pressure vessels with Kevlar COPVs resulted in a weight savings of about 30 percent. Mass critical space applications such as the Ares and Orion vehicles are currently being planned to use as many COPVs as possible in place of all-metallic pressure vessels to minimize the overall mass of the vehicle. Due to the fact that overwraps are subjected to sustained loads during long periods of a mission, stress rupture failure is a major concern. It is, therefore, important to ascertain the reliability of these vessels by analysis, since it is practically impossible to show by experimental testing the reliability of flight quality vessels. Also, it is a common practice to set aside flight quality vessels as "fleet leaders" in a test program where these vessels are subjected to slightly accelerated operating conditions so that they lead the actual flight vessels both in time and load. The intention of fleet leaders is to provide advanced warning if there is a serious design flaw in the vessels so that a major disaster in the flight vessels can be averted with advance warning. On the other hand, the accelerating conditions must be not so severe as to be prone to false alarms. The primary focus of the present paper is to provide an analytical basis for designing a viable fleet leader program for carbon COPVs. The analysis is based on a stress rupture behavior model incorporating Weibull statistics and power-law sensitivity of life to fiber stress level.
Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.
Clipper Windpower, in collaboration with United Technologies Research Center, the National Renewable Energy Laboratory, and Hamilton Sundstrand Corporation, developed a low-cost, deflection-compliant, reliable, and serviceable chain drive speed increaser. This chain and sprocket drivetrain design offers significant breakthroughs in the areas of cost and serviceability and addresses the key challenges of current geared and direct-drive systems. The use of gearboxes has proven to be challenging; the large torques and bending loads associated with use in large multi-MW wind applications have generally limited demonstrated lifetime to 8-10 years. The large cost of gearbox replacement and the required use of large, expensive cranes can result in gearbox replacement costs on the order of $\$$1M, representing a significant impact to overall cost of energy (COE). Direct-drive machines eliminate the gearbox, thereby targeting increased reliability and reduced life-cycle cost. However, the slow rotational speeds require very large and costly generators, which also typically have an undesirable dependence on expensive rare-earth magnet materials and large structural penalties for precise air gap control. The cost of rare-earth materials has increased 20X in the last 8 years representing a key risk to ever realizing the promised cost of energy reductions from direct-drive generators. A common challenge to both geared and direct drive architectures is a limited ability to manage input shaft deflections. The proposed Clipper drivetrain is deflection-compliant, insulating later drivetrain stages and generators from off-axis loads. The system is modular, allowing for all key parts to be removed and replaced without the use of a high capacity crane. Finally, the technology modularity allows for scalability and many possible drivetrain topologies. These benefits enable reductions in drivetrain capital cost by 10.0%, levelized replacement and O&M costs by 26.7%, and overall cost of energy by 10.2%. This design was achieved by: (1) performing an extensive optimization study that deter-mined the preliminary cost for all practical chain drive topologies to ensure the most competitive configuration; (2) conducting detailed analysis of chain dynamics, contact stresses, and wear and efficiency characteristics over the chain's life to ensure accurate physics-based predictions of chain performance; and (3) developing a final product design, including reliability analysis, chain replacement procedures, and bearing and sprocket analysis. Definition of this final product configuration was used to develop refined cost of energy estimates. Finally, key system risks for the chain drive were defined and a comprehensive risk reduction plan was created for execution in Phase 2.
Theory and techniques for design, analysis, and fault diagnosis of reliable spacecraft data systems
Validation of ultra-reliable systems decomposes into two subproblems: (1) quantification of probability of system failure due to physical failure; (2) establishing that Design Errors are not present. Methods of design, testing, and analysis of ultra-reliable software are discussed. It is concluded that a design-for-validation based on formal methods is needed for the digital flight control systems problem, and also that formal methods will play a major role in the development of future high reliability digital systems.
A hardware system's failure rate often increases over time due to wear and aging, but not always. Some systems instead show reliability growth, a decreasing failure rate with time, due to effective failure analysis and remedial hardware upgrades. Reliability grows when failure causes are removed by improved design. A mathematical reliability growth model allows the reliability growth rate to be computed from the failure data. The space shuttle was extensively maintained, refurbished, and upgraded after each flight and it experienced significant reliability growth during its operational life. In contrast, the International Space Station (ISS) is much more difficult to maintain and upgrade and its failure rate has been constant over time. The ISS Carbon Dioxide Removal Assembly (CDRA) reliability has slightly decreased. Failures on ISS and with the ISS CDRA continue to be a challenge.
Shielded gloveboxes are currently being constructed to facilitate dilution and disposal of many tons of excess plutonium oxide. Measuring holdup in these gloveboxes is expected to be challenging because of the limited available lines of sight through the glovebox shielding. A system of gamma-ray imagers is being developed to provide localization and quantification for holdup. The system will be mounted above the glovebox, where there is minimal shielding. Multiple imagers with overlapping coded-aperture fields of view are employed to enable three-dimensional reconstruction. Compton reconstruction is also available to localize sources outside the coded-aperture field of view. Improved uncertainties with respect to current techniques are expected by virtue of the fixed installation, spectroscopic performance of the detectors, and iterative image reconstruction techniques. Measurement campaigns have been undertaken at an active glovebox at Savannah River Site to test the gamma-ray imaging system in an operational environment, providing a simple test of a single imager that mimics the geometry of the installation proposed for future shielded gloveboxes. Data taken during quiescent periods in the glovebox were used to measure the buildup of material on an outlet filter and record a trend over time. Calibration data was taken with known sources to simplify analysis and provide a reliable assay of the filter. Resulting images make it possible to isolate the filter from other sources and recognize compromised data. This paper will present details of the measurement and analysis methods.
In the third generation light source, photon beam position stability is critical issue on user experiment. Generally photon beam position monitors have been developed for the detection of the real photon beam position and the position is controlled by feedback system in order to keep the reference photon beam position. In the PLS-II, photon beam position stability for front end of particular beam line, in which photon beam position monitor is installed, has been obtained less than rms 1μm for user service period. Nevertheless, detail analysis for photon beam position data in order to demonstrate the performance of photon beam position monitor is necessary, since it can be suffers from various unknown noises. (for instance, a back ground contamination due to upstream or downstream dipole radiation, undulator gap dependence, etc.) In this paper, we will describe the start to end study for photon beam position stability and the Singular Value Decomposition (SVD) analysis to demonstrate the reliability on photon beam position data.
As the design of Micro-Electro-Mechanical System (MEMS) devices matures and their application extends to critical areas, the issues of reliability and long-term survivability become increasingly important. This paper reviews some general approaches to addressing the reliability and qualification of MEMS devices for space applications.
Systematic summary of factors which are involved in optimization of given structural configuration is part of report resulting from study of analysis of objective function. Predicted reliability of performance of finished structure is sharply dependent upon results of coupon tests. Optimization analysis developed by study also involves expected cost of proof testing.
Internal gas pressure in hermetic wet tantalum capacitors is created by air, electrolyte vapor, and gas generated by electrochemical reactions at the electrodes. This pressure increases substantially with temperature and time of operation due to excessive leakage currents. Deformation of the case occurs when the internal pressure exceeds pressure of the environments and can raise significantly when a part operates in space. Contrary to the cylinder case wet tantalum capacitors that have external sealing by welding and internal sealing provided by the Teflon bushing and crimping of the case, no reliable internal sealing exists in the button case capacitors. Single seal design capacitors are used for high capacitance value wet tantalum capacitors manufactured per DLA L&M drawings #04003, 04005, and 10011, and require additional analysis to assure their reliable application in space systems. In this work, leakage currents and case deformation of button case capacitors were measured during different environmental test conditions. Recommendations for derating, screening and qualification testing are given. This work is a continuation of a series of NEPP reports related to quality and reliability of wet tantalum capacitors.
During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.
Projected increases in electricity demand in the U.S. highlight the urgent need for effective load management to ensure grid reliability. As the building sector accounts for approximately 75% of electricity usage, enhancing energy efficiency and flexibility in this sector is crucial. Adopting district-level approaches offers significant advantages over traditional individual building analyses by enabling shared infrastructure and economies of scale. To navigate the data and computational challenges associated with modeling energy at the district level, prototype district models have been proposed as holistic, system-level solutions that capture complex interactions within typical configurations. This study presents these models as a reference tool for analyzing district-scale energy systems across various climate zones in the U.S. Developed with input from stakeholders, these models integrate varied building characteristics, inter-building connections, and energy system interactions. A case study utilizing the Urban Edge prototype district model, implemented on the URBANopt™ platform, evaluates multiple demand scenarios and the impact of distributed energy resources such as fuel-fired backup generators, photovoltaic systems, and batteries. Findings suggest that while new electric systems can significantly reduce annual energy use, they may also elevate peak electricity loads, with a notable 43% increase in heating-dominant climate zone 5B. The optimal backup power solutions vary based on location, influenced by factors such as utility rates and incentives. For example, PV and batteries perform well in high-cost regions like New York City, while diesel backup generators are more suitable for backup needs in climate zone 3A, such as Atlanta. Thus, this research highlights the importance of prototype district models for future district-scale energy planning.
A ball and cylindrical roller bearing technical specification which incorporates the latest state-of-the-art advancements was prepared for the purpose of improving bearing reliability in U.S. Army aircraft. The current U.S. Army aviation bearing designs and applications, including life analyses, were analyzed. A bearing restoration and refurbishment specification was prepared to improve bearing availability.