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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 451 records · Page 25

Experiences in extraction of contact parameters from process-evaluation test-structures

Six-terminal-contact test structures are introduced for characterizing ohmic contacts between a metal and a heavily doped semiconductor layer. Specifically, the six-terminal test structure supplies the additional information needed in order to calculate the transmission length and eventual corrections to the characteristic resistance per unit width due to finite contact length. The essential feature of this test structure is a square contact with four taps in the lower (semiconductor) layer. Every other one of these taps is used for current injection ('front'). From the voltage drop at the opposite tap and the side taps, the 'end' resistance and the 'side' resistances are calculated. The test structures are shown to give valuable information complementary to the common front resistance measurements. The interfacial resistivity is obtained directly after proper correction for flange effects.

Lieneweg, Udo↗

A moving-window parameter adaptive control system for the F8-DFBW aircraft

This paper describes the moving-window parameter adaptive control system developed for the NASA F8-DFBW aircraft. The control system employs a parameter identification process that, iteratively, adjusts parameters of a model of the aircraft motions in a batch processing manner so that responses generated from the model fit the outputs of sensors stored in a finite record referred to as the moving window. Tests are made on the validity of the parameter estimates before using the parameters in an on-line design process. The on-line design process is an algebraic mapping of the parameters of the model into primary control system feedback and feedforward gains. The mapping was selected to satisfy specific flying quality characteristics over the range of parameter variations expected. Results are presented from simulation studies on the identification algorithm, tests for parameter validity, and the on-line design process.

Montgomery, R. C.↗

Integrated Logistics Support Analysis of the International Space Station Alpha, Background and Summary of Mathematical Modeling and Failure Density Distributions Pertaining to Maintenance Time Dependent Parameters

The process of predicting the values of maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability and maintenance support costs. There are two types of parameters in the logistics and maintenance world: a. Fixed; b. Variable Fixed parameters, such as cost per man hour, are relatively easy to predict and forecast. These parameters normally follow a linear path and they do not change randomly. However, the variable parameters subject to the study in this report such as MTBF do not follow a linear path and they normally fall within the distribution curves which are discussed in this publication. The very challenging task then becomes the utilization of statistical techniques to accurately forecast the future non-linear time dependent variable arisings and events with a high confidence level. This, in turn, shall translate in tremendous cost savings and improved availability all around.

Sepehry-Fard, F.↗

A moving window parameter adaptive control system for the F8-DFBW aircraft

This paper describes the moving window parameter adaptive control system developed for the NASA F8-DFBW aircraft. The control system employs a parameter identification process that, iteratively, adjusts parameters of a model of the aircraft motions in a batch-processing manner so that responses generated from the model fit the outputs of sensors stored in a finite record referred to as the moving window. Tests are made on the validity of the parameter estimates before using the parameters in an on-line design process. The on-line design process is an algebraic mapping of the parameters of the model into primary control system feedback and feedforward gains. The mapping was selected to satisfy specific flying quality characteristics over the range of parameter variations expected. Results are presented from simulation studies on the identification algorithm made during the development of the system.

Dunn, H. J.↗

Parameter adaptive estimation of random processes

This paper is concerned with the parameter adaptive least squares estimation of random processes. The main result is a general representation theorem for the conditional expectation of a random variable on a product probability space. Using this theorem along with the general likelihood ratio expression, the least squares estimate of the process is found in terms of the parameter conditioned estimates. The stochastic differential for the a posteriori probability and the stochastic differential equation for the a posteriori density are found by using simple stochastic calculus on the representations obtained. The results are specialized to the case when the parameter has a discrete distribution. The results can be used to construct an implementable recursive estimator for certain types of nonlinear filtering problems. This is illustrated by some simple examples.

Caglayan, A. K.↗

Nonstationary ascent wind analysis.

A statistical approach for computing launch vehicle response to inflight winds is presented. In the response analysis the zonal component of the ascent wind velocity is modeled as a nonstationary random process. Model parameters are computed by processing available measured wind data. Pertinent pitch plane response statistics are computed and their value in constructing fatigue load spectra for a reusable launch vehicle is demonstrated. A method for using the response statistics to estimate structural reliability is also discussed. The accuracy and the cost saving potential of the probabilistic structural dynamics approach are assessed by performing comparisons with digital simulation results.

Howell, L. J.↗

Earth Survey Applications Division

Accomplishments of research and data analysis conducted to study physical parameters and processes inside the Earth and on the Earth's surface, to define techniques and systems for remotely sensing the processes and measuring the parameters of scientific and applications interest, and the transfer of promising operational applications techniques to the user community of Earth resources monitors, managers, and decision makers are described. Research areas covered include: geobotany, magnetic field modeling, crustal studies, crustal dynamics, sea surface topography, land resources, remote sensing of vegetation and soils, and hydrological sciences. Major accomplishments include: production of global maps of magnetic anomalies using Magsat data; computation of the global mean sea surface using GEOS-3 and Seasat altimetry data; delineation of the effects of topography on the interpretation of remotely-sensed data; application of snowmelt runoff models to water resources management; and mapping of snow depth over wheat growing areas using Nimbus microwave data.

Carpenter, L.↗

Variations in density and chemical composition at 120 km from chemical and dynamical processes.

Atmospheric parameters show both systematic and random patterns of behavior at 120 km altitude. Variations in density, temperature, pressure, and especially atomic oxygen concentration are important. The variations are particularly significant because constant boundary conditions at this altitude have commonly been assumed in atmospheric model making. It is surprising how well the assumption of constant boundary conditions has served over the past decade. However, their use has probably introduced erroneous concepts into the field of atmospheric structure, or at least held off the recognition and introduction of important new concepts. The variations at 120 km are caused by changes in energy input into the upper atmosphere, including internal gravity waves and tidal energy from below, and changes in the transport processes within the atmosphere.

Johnson, F. S.↗

Taguchi Method Applied in Optimization of Shipley SJR 5740 Positive Resist Deposition

Taguchi Methods of Robust Design presents a way to optimize output process performance through an organized set of experiments by using orthogonal arrays. Analysis of variance and signal-to-noise ratio is used to evaluate the contribution of each of the process controllable parameters in the realization of the process optimization. In the photoresist deposition process, there are numerous controllable parameters that can affect the surface quality and thickness of the final photoresist layer.

Taguchi Method Shipley SJR 5740 orthogonal arrays ↗

L'Ralph's Advanced Thermal Model Correlation Using Veritrek

Thermal model correlation uses data from thermal balance tests to better estimate uncertain input parameter values. During the correlation process, input parameters are modified in an iterative manner which can become computationally expensive since this requires that the high-fidelity thermal model be run for each iteration. Depending on the number of thermal balance test points there can be many sets of correlation parameters that satisfy correlation criteria; and having enough data to ascertain the best set of correlation parameters to use, further increases the computational expense. Reduced-order models (ROMs) provide computationally efficient surrogates of high-fidelity models and are often built to reduce development cycle times and cost. By leveraging the speed of reduced-order models and the Correlation Analysis feature in the Veritrek software, the typical computational expense of a traditional thermal model correlation process can be significantly reduced and having access to hundreds of thousands of iteration results provides an advanced means of intelligently determining the best set of correlation parameters to use. The L’Ralph thermal team at NASA Goddard Space Flight Center explored the use of the Veritrek software for their thermal model correlation efforts. The ROM that was created allowed for the variation of 15 input parameters to match 70 temperature sensor readouts from 3 thermal balance plateus and required 125 runs of the high-fidelity Thermal Desktop® model to generate a ROM that could predict the detailed model’s results to within 0.2 K (RMS). The ROM was then used to find dozens of plausible correlation parameter values based on L’Ralph instrument test data within a few seconds. By providing several plausible correlation parameter combinations, Veritrek allowed the thermal team to explore different uncertain parameter value combinations and provided insight into how deterministic each input parameter was. This allowed for a more confident decision on the best set of correlation parameters to use, compared to traditional model correlation techniques. In this presentation, the L’Ralph thermal team will be presenting their experience with the Veritrek software and how the software was utilized to provide additional insights during the correlation process.

Daniel Bae↗

L'Ralph's Advanced Thermal Model Correlation Using Veritrek

Thermal model correlation uses data from thermal balance tests to better estimate uncertain input parameter values. During the correlation process, input parameters are modified in an iterative manner which can become computationally expensive since this requires that the high-fidelity thermal model be run for each iteration. Depending on the number of thermal balance test points there can be many sets of correlation parameters that satisfy correlation criteria; and having enough data to ascertain the best set of correlation parameters to use, further increases the computational expense. Reduced-order models (ROMs) provide computationally efficient surrogates of high-fidelity models and are often built to reduce development cycle times and cost. By leveraging the speed of reduced-order models and the Correlation Analysis feature in the Veritrek software, the typical computational expense of a traditional thermal model correlation process can be significantly reduced and having access to hundreds of thousands of iteration results provides an advanced means of intelligently determining the best set of correlation parameters to use. The L’Ralph thermal team at NASA Goddard Space Flight Center explored the use of the Veritrek software for their thermal model correlation efforts. The ROM that was created allowed for the variation of 15 input parameters to match 70 temperature sensor readouts from 3 thermal balance plateus and required 125 runs of the high-fidelity Thermal Desktop® model to generate a ROM that could predict the detailed model’s results to within 0.2 K (RMS). The ROM was then used to find dozens of plausible correlation parameter values based on L’Ralph instrument test data within a few seconds. By providing several plausible correlation parameter combinations, Veritrek allowed the thermal team to explore different uncertain parameter value combinations and provided insight into how deterministic each input parameter was. This allowed for a more confident decision on the best set of correlation parameters to use, compared to traditional model correlation techniques. In this presentation, the L’Ralph thermal team will be presenting their experience with the Veritrek software and how the software was utilized to provide additional insights during the correlation process. "

Daniel Bae↗

A Gaussian Process Enhancement to Linear Parameter Varying Models

Simulation and analysis for modern engineering systems now routinely requires the merging of multiple disciplines, physical-domains, time-scales, and data sets — all at ever increasing levels. These capabilities are especially needed in the domain of Advanced Air Mobility, where rapidly emerging vehicle designs are significantly more complex, while having to be both cost-effective and safe. To meet these engineering challenges, machine learning methods are an attractive option for merging models and data across multiple areas while providing uncertainty quantification and maintaining computational efficiency. This paper examines the use of Gaussian process machine learning to generalize and enhance the commonly used class of quasi-Linear Parameter Varying models for fast full-envelope simulation while also supporting control system design and analysis with model uncertainty. Gaussian process machine learning is selected because it: can fuse multiple data sets, enables an easy trade-off between data fitting and smoothing, provides model uncertainty quantification, scales well with increasing complexity, and does not generally require starting from a large training data set. To demonstrate the benefits of the approach, a robust stability analysis with Gaussian process uncertainty is shown for a NASA reference design of an electric quad-rotor air-taxi concept vehicle with motor parameter uncertainty.

Gaussian Process↗

Friction Stir Welding at MSFC: Kinematics

In 1991 The Welding Institute of the United Kingdom patented the Friction Stir Welding (FSW) process. In FSW a rotating pin-tool is inserted into a weld seam and literally stirs the faying surfaces together as it moves up the seam. By April 2000 the American Welding Society International Welding and Fabricating Exposition featured several exhibits of commercial FSW processes and the 81st Annual Convention devoted a technical session to the process. The FSW process is of interest to Marshall Space Flight Center (MSFC) as a means of avoiding hot-cracking problems presented by the 2195 aluminum-lithium alloy, which is the primary constituent of the Lightweight Space Shuttle External Tank. The process has been under development at MSFC for External Tank applications since the early 1990's. Early development of the FSW process proceeded by cut-and-try empirical methods. A substantial and complex body of data resulted. A theoretical model was wanted to deal with the complexity and reduce the data to concepts serviceable for process diagnostics, optimization, parameter selection, etc. A first step in understanding the FSW process is to determine the kinematics, i.e., the flow field in the metal in the vicinity of the pin-tool. Given the kinematics, the dynamics, i.e., the forces, can be targeted. Given a completed model of the FSW process, attempts at rational design of tools and selection of process parameters can be made.

Nunes, A. C., Jr.↗

Educational Experiences of Embry-Riddle Students through NASA Research Collaboration

NASA's educational. programs benefit students and faculty while increasing the overall productivity of the organization. The NASA Graduate Student Research Program (GSRP) awards fellowships for graduate study leading to both masters and doctoral degrees in several technical fields. GSRP participants have the option to utilize NASA Centers andlor university research facilities. In addition, GSRP students can serve as mentors for undergrad students to provide a truly unique learning experience. NASA's Cooperative Education Program allows undergraduate students the chance to gain "real-world" work experience in the field. It also gives NASA a no risk capability to evaluate the true performance of a prospective new hire without relying solely on a "paper resume" while providing the students with a greater hiring potential upon graduation, at NASA or elsewhere. University faculty can also benefit by participating in the NASA Faculty Fellowship Program (NFFP). This program gives the faculty an opportunity to work with NASA peers. The Mission Analysis Branch of the Expendable Launch Vehicles Division at NASA Kennedy Space Center has utilized these two programs with students from Embry-Riddle Aeronautical University (ERAU) to conduct research in modeling and developing a parameter estimation method for spacecraft fuel slosh using simple pendulum analogs. Simple pendulum models are used to understand complicated spacecraft fuel slosh behavior. A robust parameter estimation process will help to identif' the parameters that will predict the response fairly accurately during the initial stages of design. These programs provide students with a unique opportunity to work on "real-world" aerospace problems, like spacecraft fuel slosh,. This in turn reinforces their problem solving abilities and their communication skills such as interviewing, resume writing, technical writing, and presentation. Faculty benefits by applying what they have learned to the classroom. Through university collaborations with NASA and industry help students to acquire skills that are vital for their success upon entering the workforce.

Schlee, Keith↗

Educational Experiences of Embry-Riddle Students through NASA Research Collaboration

NASA's educational programs benefit students while increasing the overall productivity of the organization. The NASA Graduate Student Research Program (GSRP) awards fellowships for graduate study leading to both masters and doctoral degrees in several technical fields, while the Cooperative Education program allows undergraduate and graduate students the chance to gain work experience in the field. The Mission Analysis Branch of the Expendable Launch Vehicles Division at NASA Kennedy Space Center has utilized these two programs with students from Embry-Riddle Aeronautical University to conduct research in modeling and developing a parameter estimation method for spacecraft fuel slosh using simple pendulum analogs. Simple pendulum models are used to understand complicated spacecraft fuel slosh behavior. A robust parameter estimation process will help to identiFy the parameters that will predict the response fairly accurately during the initial stages of design. NASA's Cooperative Education Program trains the next wave of new hires while allowing graduate and undergraduate college students to gain valuable "real-world" work experience. It gives NASA a no risk capability to evaluate the true performance of a prospective new hire without relying solely on a paper resume, while providing the students with a greater hiring potential upon graduation, at NASA or elsewhere. In addition, graduate students serve as mentors for undergrad students and provide a unique learning environment. Providing students with a unique opportunity to work on "real-world" aerospace problems ultimately reinforces their problem solving abilities and their communication skills (in terms of interviewing, resume writing, technical writing, presentation, and peer review) that are vital for the workforce to succeed.

Schlee, Keith↗

Robust Metal Additive Manufacturing Process Selection and Development for Aerospace Components

Metal additive manufacturing (AM) is a generic term that captures a variety of fabrication techniques. Each of these manufacturing process has unique advantages, applications for use, and challenges. The most common AM processes in use include Powder Bed Fusion (PBF) and Directed Energy Deposition (DED) as well as many solid state processes. While detailed research has been conducted among many of the processes including parameters and material properties, navigating which processes are best to select is difficult as it is based on component requirements. The focus of this presentation is to provide an overview of considerations for each of metal AM process selection for aerospace components based on various attributes. These attributes include geometric considerations, metallurgical characteristics, cost basis, post-processing and maturity of the processes. The data for these trade selections are based on studies that NASA as performed internally and with academic and industry partners. These studies include multiple AM build experiments to evaluate (1) geometric variations and constraints within the processes, (2) alloy characterization and mechanical testing, (3) pathfinder component development and hotfire evaluations, and (4) certification approaches. This presentation summarizes these results and meant to introduce various considerations when designing a metal AM component.

Additive Manufacturing↗

Friction Pull Plug Welding in Aluminum Alloys

NASA's Marshall Space Flight Center (MSFC) has recently invested much time and effort into the process development of Friction Pull Plug Welding (FPPW). FPPW, is a welding process similar to Friction Push Plug Welding in that, there is a small rotating part (plug) being spun and simultaneously pulled (forged) into a larger part. These two processes differ, in that push plug welding requires an internal reaction support, while pull plug welding reacts to the load externally. FPPW was originally conceived as a post proof repair technique for the Space Shuttle fs External Tank. FPPW was easily selected as the primary weld process used to close out the termination hole on the Constellation Program's ARES I Upper Stage circumferential Self-Reacting Friction Stir Welds (SR-FSW). The versatility of FPPW allows it to also be used as a repair technique for both SR-FSW and Conventional Friction Stir Welds. To date, all MSFC led development has been concentrated on aluminum alloys (2195, 2219, and 2014). Much work has been done to fully understand and characterize the process's limitations. A heavy emphasis has been spent on plug design, to match the various weldland thicknesses and alloy combinations. This presentation will summarize these development efforts including weld parameter development, process control, parameter sensitivity studies, plug repair techniques, material properties including tensile, fracture and failure analysis.

Brooke, Shane A.↗