Search NASA⌕ Search

SEARCH · Search NASA

Results for “analytical process”

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.

At least 451 records · Page 25

Ultrasonic inspection of carbon fiber reinforced plastic by means of sample-recognition methods

In the case of carbon fiber reinforced plastic (CFRP), it has not yet been possible to detect nonlocal defects and material degradation related to aging with the aid of nondestructive inspection method. An approach for overcoming difficulties regarding such an inspection involves an extension of the ultrasonic inspection procedure on the basis of a use of signal processing and sample recognition methods. The basic concept involved in this approach is related to the realization that the ultrasonic signal contains information regarding the medium which is not utilized in conventional ultrasonic inspection. However, the analytical study of the phyiscal processes involved is very complex. For this reason, an empirical approach is employed to make use of the information which has not been utilized before. This approach uses reference signals which can be obtained with material specimens of different quality. The implementation of these concepts for the supersonic inspection of CFRP laminates is discussed.

Bilgram, R.↗

A potential energy surface for the process H2 + H2O yielding H + H + H2O - Ab initio calculations and analytical representation

Extensive ab initio calculations on the ground state potential energy surface of H2 + H2O were performed using a large contracted Gaussian basis set and a high level of correlation treatment. An analytical representation of the potential energy surface was then obtained which reproduces the calculated energies with an overall root-mean-square error of only 0.64 mEh. The analytic representation explicitly includes all nine internal degrees of freedom and is also well behaved as the H2 dissociates; it thus can be used to study collision-induced dissociation or recombination of H2. The strategy used to minimize the number of energy calculations is discussed, as well as other advantages of the present method for determining the analytical representation.

Schwenke, David W.↗

Exploring the parameter space of MagLIF implosions using similarity scaling. I. Theoretical framework

Magneto-inertial fusion concepts, such as the magnetized liner inertial fusion (MagLIF) platform, constitute an alternative path for achieving ignition and significant fusion yields in the laboratory. The space of experimental input parameters defining a MagLIF load is highly multi-dimensional, and the implosion itself is a complex event involving many physical processes. In the first paper of this series, we develop a simplified analytical model that identifies the main physical processes at play during a MagLIF implosion. Using non-dimensional analysis, we determine the most important dimensionless parameters characterizing MagLIF implosions and provide estimates of such parameters using typical fielded or experimentally observed quantities for MagLIF. Here, we then show that MagLIF loads can be “incompletely” similarity scaled, meaning that the experimental input parameters of MagLIF can be varied such that many (but not all) of the dimensionless quantities are conserved. Based on similarity-scaling arguments, we can explore the parameter space of MagLIF loads and estimate the performance of the scaled loads. Then, in the follow-up papers of this series, we test the similarity-scaling theory for MagLIF loads against simulations for two different scaling “vectors,” which include current scaling and rise-time scaling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Development of Monitoring Techniques for Laser Powder Bed Additive Manufacturing of Metal Structures (Progress Report)

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear grade components to be assembled into a fully functional microreactor core. Compared to traditional manufacturing technologies, additive manufacturing technologies allow (1) observation of the manufacturing process at a much higher resolution in real time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space, and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on laser powder bed fusion in-situ process monitoring and associated data analytics results. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Balancing of high speed interconnect shafting for operation above multiple bending critical speeds

The present work first reviews the key elements of rotating system dynamics which are crucial to the control of lateral vibration levels for supercritical shafting of the type which is considered for use in advanced aircraft applications. Then the results of an analytical investigation of procedures for balancing flexible shafts designed for critical operation are discussed. Some of the conclusions made were: (1) even in undamped configuration, reasonably low vibration levels can be achieved through a sequential multiplane-multispeed balancing process; and (2) combination of analytical response and balancing prediction procedures yields a powerful tool for the dynamic analysis and design of advanced shaft-bearing systems.

Badgley, R. H.↗

Analytical Ultrasonics in Materials Research and Testing

Research results in analytical ultrasonics for characterizing structural materials from metals and ceramics to composites are presented. General topics covered by the conference included: status and advances in analytical ultrasonics for characterizing material microstructures and mechanical properties; status and prospects for ultrasonic measurements of microdamage, degradation, and underlying morphological factors; status and problems in precision measurements of frequency-dependent velocity and attenuation for materials analysis; procedures and requirements for automated, digital signal acquisition, processing, analysis, and interpretation; incentives for analytical ultrasonics in materials research and materials processing, testing, and inspection; and examples of progress in ultrasonics for interrelating microstructure, mechanical properites, and dynamic response.

Vary, A.↗

Materials analysis by ultrasonics: Metals, ceramics, composites

Research results in analytical ultrasonics for characterizing structural materials from metals and ceramics to composites are presented. General topics covered by the conference included: status and advances in analytical ultrasonics for characterizing material microstructures and mechanical properties; status and prospects for ultrasonic measurements of microdamage, degradation, and underlying morphological factors; status and problems in precision measurements of frequency-dependent velocity and attenuation for materials analysis; procedures and requirements for automated, digital signal acquisition, processing, analysis, and interpretation; incentives for analytical ultrasonics in materials research and materials processing, testing, and inspection; and examples of progress in ultrasonics for interrelating microstructure, mechanical properties, and dynamic response.

Vary, Alex↗

Development of an Atomization Methodology for Spray Combustion

In liquid rocket propulsion, the knowledge and the understanding of liquid-gas interfacial phenomena are very important. This is important for predicting the onset of cavitation occurring in swirl injection elements used in STME, as well as atomization processes in shear-induced injectors (co-axial) and impinging injector elements. From the fact that all the physical processes including droplet size distribution, droplet dispersion, mixing and combustion are controlled by atomization processes, it is expected that the successful incorporation of the volume of fraction (VOF) will greatly enhance the analytical capability of predicting spray combustion processes in liquid-fueled engines. In this paper, a methodology is developed to define and track interfaces between two fluids in non-orthogonal, body-fitted grids using a single fractional volume of fluid (VOF) variable to describe the distribution of the liquid phase in a gas-liquid flow field. This method was implemented in a mature CFD code MAST (Multiphase All-Speed Transient) utilizing the general PISO-C algorithm. For the preliminary study on the analysis of spray combustion and tracking of the interface between two phases, we will report on the progress of the simulation of the instability on the liquid column; the surface wave instability and the droplet breakup from the liquid surface.

Seung, S. P.↗

Finite Element Modeling of a Cylindrical Contact Using Hertzian Assumptions

The turbine blades in the high-pressure fuel turbopump/alternate turbopump (HPFTP/AT) are subjected to hot gases rapidly flowing around them. This flow excites vibrations in the blades. Naturally, one has to worry about resonance, so a damping device was added to dissipate some energy from the system. The foundation is now laid for a very complex problem. The damper is in contact with the blade, so now there are contact stresses (both normal and tangential) to contend with. Since these stresses can be very high, it is not all that difficult to yield the material. Friction is another non-linearity and the blade is made out of a Nickel-based single-crystal superalloy that is orthotropic. A few approaches exist to solve such a problem and computer models, using contact elements, have been built with friction, plasticity, etc. These models are quite cumbersome and require many hours to solve just one load case and material orientation. A simpler approach is required. Ideally, the model should be simplified so the analysis can be conducted faster. When working with contact problems determining the contact patch and the stresses in the material are the main concerns. Closed-form solutions for non-conforming bodies, developed by Hertz, made out of isotropic materials are readily available. More involved solutions for 3-D cases using different materials are also available. The question is this: can Hertzian1 solutions be applied, or superimposed, to more complicated problems-like those involving anisotropic materials? That is the point of the investigation here. If these results agree with the more complicated computer models, then the analytical solutions can be used in lieu of the numerical solutions that take a very long time to process. As time goes on, the analytical solution will eventually have to include things like friction and plasticity. The models in this report use no contact elements and are essentially an applied load problem using Hertzian assumptions to determine the contact patch dimensions.

Knudsen, Erik↗

Data Science Techniques, Assumptions, and Challenges in Alloy Clustering and Property Prediction

Data analytics methods have been increasingly applied to understanding materials chemistry, processing due to the manufacturing approach, and uni-axial and cyclic property relationships in the highly complex space of alloy design. There are several benefits to applying data analytics to this space, including the ability to manage non-linearities in the responses of the alloy attributes and the resulting mechanical properties. However, key difficulties in applying and understanding the results of data analytics include the often lack of reported assumptions and data processing steps necessary to improve interpretation and reproducibility in derived results. In this work, the methods used to generate clustering and correlation analyses for experimental 9% Cr ferritic-martensitic steel data were investigated and the resulting implications for mechanical property predictions were assessed. This work uses principal component analysis, partitioning around medoids, t-SNE, and k-means clustering to investigate trends in composition, processing and microstructure information with creep and tensile properties, building on work done previously using a smaller version of the same dataset. The initial assumptions, preprocessing steps and methods are investigated and outlined in order to depict the fine level of detail required to convey the steps taken to process data and produce analytical results. Here, the variations in the resulting analyses are explored due to the influence of new and more varied data.

36 MATERIALS SCIENCE↗

Application of LANDSAT data to monitor land reclamation progress in Belmont County, Ohio

Strip and contour mining techniques are reviewed as well as some studies conducted to determine the applicability of LANDSAT and associated digital image processing techniques to the surficial problems associated with mining operations. A nontraditional unsupervised classification approach to multispectral data is considered which renders increased classification separability in land cover analysis of surface mined areas. The approach also reduces the dimensionality of the data and requires only minimal analytical skills in digital data processing.

Bloemer, H. H. L.↗

EBR-II Driver Fuel Cladding Hull Analytical Data

Sharing EBR-II driver fuel cladding hull data with General Atomics under NDA No. 20NDA155. Data share is needed to advance discussions regarding process technologies to decontaminate separated cladding hulls

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Detonation performance experiments and modeling for the DAAF-based high explosive PBX 9701

Detonation performance experiments and modeling are reported for the explosive PBX 9701, which is composed of 97% 3,3$\acute{-}$diamino-4,4$\acute{-}$azoxyfurazan (DAAF) and 3% vinylidene uoride-chlorotriuoroethylene copolymer (Kel-F 800) binder by weight. PBX 9701 is a newly-developed reducedsensitivity explosive with increased performance relative to the triaminotrinitrobenzene or TATB-based PBX 9502 while still retaining low sensitivity to mechanical insult. The first detonation performance measurements for this formulation are presented, including front-curvature ratesticks and cylinder expansion test data. Prior shock initiation data is also reviewed. These data are used to develop programmed burn and reactive flow calibrations for existing commonly-used performance models which allow engineering calculations with PBX 9701. The calibration process involves several enhancements relative to conventional approaches including the use of an analytical scaling correlation to speed the calibration process and development of a new methodology to improve the consistency between the programmed burn and reactive model calibration process and the resulting calculations. Overall, PBX 9701 is seen to exhibit improved performance relative to insensitive explosives, with a trinitrotoluene (TNT) equivalence of 1.24. The detonation performance properties are found to be well captured by existing models.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

On the mechanics of filament winding. I - A generalized model

In this paper the filament winding process was analyzed to relate process variables to structural parameters. An analytical model has been developed for a filament wound preform by determining the necessary geometric and kinematic conditions. An equation of motion of winding was developed to predict layer by layer geometry using the mandrel shape as the initial boundary condition. This model provides the laws of motion of the traverse stroke relative to the mandrel to ensure that the filament laydown is of the predetermined geodesic path over the mandrel, that the winding density is distributed over the mandrel in the prearranged manner, and that the winding build is being formed to reproduce the preassigned shape or contour of the preform. From this analysis, the winding process parameters can be controlled accordingly to produce any given shape. The analytical model was used to produce computer simulation of the winding process. The dynamic simulation of the winding process visualizes and inspects the layer by layer path of the tow and provides process variables required to produce preforms of optimum structural parameters.

Hamouda, Hechmi↗

Design and Simulation of a MEMS Structure for Electrophoretic and Dielectrophoretic Separation of Particles by Contactless Electrodes

Rapid identification of pathogenic bacterial species is an important factor in combating public health problems such as E. coli contamination. Food and waterborne pathogens account for sickness in 76 million people annually (CDC). Diarrheagenic E. coli is a major source of gastrointestinal illness. Severe sepsis and Septicemia within the hospital environment are also major problems. 75 1,000 cases annually with a 30-50% mortality rate (Crit Care Med, July '01, Vol. 29, 1303-10). Patient risks run the continuum from fever to organ failure and death. Misdiagnosis or inappropriate treatment increases mortality. There exists a need for rapid screening of samples for identification of pathogenic species (Certain E. coli strains are essential for health). Critical to the identification process is the ability to isolate analytes of interest rapidly. This poster discusses novel devices for the separation of particles on the basis of the dielectric properties, mass and surface charge characteristics is presented. Existing designs involve contact between electrode surfaces and analyte medium resulting in contamination of the electrode bearing elements Two different device designs using different bulk micromachining MEMS processes (PolyMUMPS and a PyrexBIGold electrode design) are presented. These designs cover a range of particle sizes from small molecules through eucaryotic cells. The application of separation of bacteria is discussed in detail. Simulation data for electrostatic and microfluidic characteristics are provided. Detailed design characteristics and physical features of the as fabricated PolyMUMPS design are provided. Analysis of the simulation data relative to the expected performance of the devices will be provided and subsequent conclusions discussed.

Shaw, Harry C.↗

A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data centric approach emphasizes leveraging available data throughout the production process to optimize performance. Integration of extensive data analysis provides the opportunity to improve precision, reduce waste, and enhance the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes the comprehensive description of deposition process, process parameters, in-situ collected welding characteristics, acoustic data, and X-Ray Computed Tomography analysis data for the build. Dataset A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process has arisen under UT-Battelle, LLC’s Prime Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE) to manage and operate the Oak Ridge National Laboratory. UT-Battelle, LLC will not assert any rights under United States law or under the Prime Contract it has in the dataset against any user of the dataset, including any copyrights or patent rights. UT-Battelle, LLC requests that attribution to the dataset is provided as academically appropriate.

42 ENGINEERING↗

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part I: Scheme Description

A novel framework is proposed for the bulk parameterization of rain microphysics: the Bayesian Observationally Constrained Statistical–Physical Scheme (BOSS). It is designed to facilitate direct constraint by observations using Bayesian inference. BOSS combines existing process-level microphysical knowledge with flexible process rate formulations and parameters constrained by observations within a Bayesian framework. Furthermore, using a raindrop size distribution (DSD) normalization method that relates DSD moments to one another via generalized power series, generalized multivariate power expressions are derived for the microphysical process rates as functions of a set of prognostic DSD moments. The scheme is flexible and can utilize any number and combination of prognostic moments and any number of terms in the process rate formulations. This means that both uncertainty in parameter values and structural uncertainty associated with the process rate formulations can be investigated systematically, which is not possible using traditional schemes. In this paper, BOSS is compared to two- and three-moment versions of a traditional bulk rain microphysics scheme (denoted as MORR). It is demonstrated that some process formulations in MORR are analytically equivalent to the generalized power expressions in BOSS using one or two terms, while others are not. BOSS is able to replicate the behavior of MORR in idealized one-dimensional rainshaft tests, but with a much more flexible and systematic design. Part II of this study describes the application of BOSS to derive rain microphysical process rates and posterior parameter distributions in Bayesian experiments using Markov chain Monte Carlo sampling constrained by synthetic observations.

58 GEOSCIENCES↗

Description of Sensor Assignment Optimization Method as Deployed on a Multi-Node Cluster

Data analytic methods are being developed to address the problem of how to assign a sensor set in a nuclear facility such that a requisite level of process monitoring capability is realized and that the sensor set is sufficiently rich to determine the status of the individual sensors with respect to need for calibration. There is an awareness in the nuclear industry that data analytics combined with rich sensor sets represent a means to improve operations and reduce costs. In the industry the calibration problem has been previously approached as an empirical data-driven problem with several methods having been developed. However, the experience of the utilities over the past ten years with these methods indicates that the absence of physics-based information renders the data-driven approach less reliable. Complicating factors such as the inherent variability of operation (both equipment alignment and operating condition) can confound a pure data-driven approach while there are no rigorous guidelines for determining what constitutes an adequate sensor set. The solution under development to overcome these shortcomings supplements the data analytic method with process information in a so-called process-constrained data-analytic approach. Simple balance equations are written for generic components (e.g., mechanical pump, valve, and heat exchanger). These do not require a priori knowledge of process parameters, such as heat transfer coefficients or friction factors. All that is needed on the part of the utility user is to identify the components and how they are connected. This report describes the development of a parallel computing capability for determining the optimal sensor set. The optimal sensor set problem suffers from the curse of dimensionality. Computation time increases exponentially as the size of the system grows. To overcome this difficulty a pre-conditioner algorithm is developed to find an approximate solution close the actual solution. This serves as a seed for the full-blown algorithm and acts to constrain the space that must searched. The optimization algorithms are described and the implementation on a parallel computing platform is described. The application of the method to a use case we are solving in collaboration with our utility partner served to illustrate how the default sensor set in a nuclear plant may not provide sufficient coverage to infer sensor calibration status.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗