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At least 829 records · Page 46

Studies of Flame Structure in Microgravity

The present research endeavor is concerned with gaining fundamental understanding of the configuration, structure, and dynamics of laminar premixed and diffusion flames under conditions of negligible effects of gravity. Of particular interest is the potential to establish and hence study the properties of spherically- and cylindrically-symmetric flames and their response to external forces not related to gravity. For example, in an earlier experimental study of the burner-stabilized cylindrical premixed flames, the possibility of flame stabilization through flow divergence was established, while the resulting one-dimensional, adiabatic, stretchless flame also allowed an accurate means of determining the laminar flame speeds of combustible mixtures. We have recently extended our studies of the flame structure in microgravity along the following directions: (1) Analysis of the dynamics of spherical premixed flames; (2) Analysis of the spreading of cylindrical diffusion flames; (3) Experimental observation of an interesting dual luminous zone structure of a steady-state, microbuoyancy, spherical diffusion flame of air burning in a hydrogen/methane mixture environment, and its subsequent quantification through computational simulation with detailed chemistry and transport; (4) Experimental quantification of the unsteady growth of a spherical diffusion flame; and (5) Computational simulation of stretched, diffusionally-imbalanced premixed flames near and beyond the conventional limits of flammability, and the substantiation of the concept of extended limits of flammability. Motivation and results of these investigations are individually discussed.

Law, C. K.↗

Measurement and Validation of Bidirectional Reflectance of Space Shuttle and Space Station Materials for Computerized Lighting Models

Task illumination has a major impact on human performance: What a person can perceive in his environment significantly affects his ability to perform tasks, especially in space's harsh environment. Training for lighting conditions in space has long depended on physical models and simulations to emulate the effect of lighting, but such tests are expensive and time-consuming. To evaluate lighting conditions not easily simulated on Earth, personnel at NASA Johnson Space Center's (JSC) Graphics Research and Analysis Facility (GRAF) have been developing computerized simulations of various illumination conditions using the ray-tracing program, Radiance, developed by Greg Ward at Lawrence Berkeley Laboratory. Because these computer simulations are only as accurate as the data used, accurate information about the reflectance properties of materials and light distributions is needed. JSC's Lighting Environment Test Facility (LETF) personnel gathered material reflectance properties for a large number of paints, metals, and cloths used in the Space Shuttle and Space Station programs, and processed these data into reflectance parameters needed for the computer simulations. They also gathered lamp distribution data for most of the light sources used, and validated the ability to accurately simulate lighting levels by comparing predictions with measurements for several ground-based tests. The result of this study is a database of material reflectance properties for a wide variety of materials, and lighting information for most of the standard light sources used in the Shuttle/Station programs. The combination of the Radiance program and GRAF's graphics capability form a validated computerized lighting simulation capability for NASA.

Fletcher, Lauren E.↗

Simulation and Flight Test Capability for Testing Prototype Sense and Avoid System Elements

NASA Langley Research Center (LaRC) and The MITRE Corporation (MITRE) have developed, and successfully demonstrated, an integrated simulation-to-flight capability for evaluating sense and avoid (SAA) system elements. This integrated capability consists of a MITRE developed fast-time computer simulation for evaluating SAA algorithms, and a NASA LaRC surrogate unmanned aircraft system (UAS) equipped to support hardware and software in-the-loop evaluation of SAA system elements (e.g., algorithms, sensors, architecture, communications, autonomous systems), concepts, and procedures. The fast-time computer simulation subjects algorithms to simulated flight encounters/ conditions and generates a fitness report that records strengths, weaknesses, and overall performance. Reviewed algorithms (and their fitness report) are then transferred to NASA LaRC where additional (joint) airworthiness evaluations are performed on the candidate SAA system-element configurations, concepts, and/or procedures of interest; software and hardware components are integrated into the Surrogate UAS research systems; and flight safety and mission planning activities are completed. Onboard the Surrogate UAS, candidate SAA system element configurations, concepts, and/or procedures are subjected to flight evaluations and in-flight performance is monitored. The Surrogate UAS, which can be controlled remotely via generic Ground Station uplink or automatically via onboard systems, operates with a NASA Safety Pilot/Pilot in Command onboard to permit safe operations in mixed airspace with manned aircraft. An end-to-end demonstration of a typical application of the capability was performed in non-exclusionary airspace in October 2011; additional research, development, flight testing, and evaluation efforts using this integrated capability are planned throughout fiscal year 2012 and 2013.

Howell, Charles T.↗

Effects of Geometric Details on Slat Noise Generation and Propagation

The relevance of geometric details to the generation and propagation of noise from leading-edge slats is considered. Typically, such details are omitted in computational simulations and model-scale experiments thereby creating ambiguities in comparisons with acoustic results from flight tests. The current study uses two-dimensional, computational simulations in conjunction with a Ffowcs Williams-Hawkings (FW-H) solver to investigate the effects of previously neglected slat "bulb" and "blade" seals on the local flow field and the associated acoustic radiation. The computations clearly show that the presence of the "blade" seal at the cusp significantly changes the slat cove flow dynamics, reduces the amplitudes of the radiated sound, and to a lesser extent, alters the directivity beneath the airfoil. Furthermore, it is demonstrated that a modest extension of the baseline "blade" seal further enhances the suppression of slat noise. As a side issue, the utility and equivalence of FW-H methodology for calculating far-field noise as opposed to a more direct approach is examined and demonstrated.

Khorrami, Mehdi R.↗

Real-Time Simulation Clock

Fiber-optic network delivers time signals to widely separated simulator sites. Real-time digital flight simulation used to support variety of research programs. Majority of research involves man-in-the-loop simulation requiring interconnection of digital computers, simulation cockpits, control consoles, graphics subsystems, and related equipment. Real-time simulation subsystem consists of several CYBER(R) computers and over 20 simulation sites. Allows for several simultaneous simulation jobs on one CYBER(R) as well as any combination of sites in each integrated simulation job.

Bennington, Donald R.↗

Verification Of Tooling For Robotic Welding

Computer simulations, robotic inspections, and visual inspections performed to detect discrepancies. Method for verification of tooling for robotic welding involves combination of computer simulations and visual inspections. Verification process ensures accuracy of mathematical model representing tooling in off-line programming system that numerically simulates operation of robotic welding system. Process helps prevent damaging collisions between welding equipment and workpiece, ensures tooling positioned and oriented properly with respect to workpiece, and/or determines whether tooling to be modified or adjusted to achieve foregoing objectives.

Osterloh, Mark R.↗

TPSAS-NF1676L-15194-DND

Technical Motivation - 1950s: Indication of large lateral (roll/yaw) acceleration (“β-dot”) dynamic derivatives for configurations with strong vortex flows in the stall region (Lichtenstein, Campbell, Riley)! - 1960s: Increased emphasis on use of long-range missiles tempered by aircraft losses in close-in air combat - 1970s: - Effect of lateral acceleration derivatives on aircraft stability (Nguyen) - Characteristics and air combat advantages of rapid controlled large-amplitude maneuvering at low speeds near maximum lift shown in piloted simulations (Herbst) - 1980s: - Dynamic (forced-oscillation, rotary balance, curved- and rolling-flow) wind tunnel tests (Grafton, Lutze, Hultberg) - Incorporation of test data into computer simulations (Kalviste) - Technologies developed for controlled maneuvers at stall, post-stall angles of attack - Concern that conventional math modeling inadequately represented the dynamic component of these motions - Need to evaluate dependency of control laws on accurate computer simulations and motion prediction

Marilyn E Ogburn↗

Development of a Prototype Simulation Executive with Zooming in the Numerical Propulsion System Simulation

A major difficulty in designing aeropropulsion systems is that of identifying and understanding the interactions between the separate engine components and disciplines (e.g., fluid mechanics, structural mechanics, heat transfer, material properties, etc.). The traditional analysis approach is to decompose the system into separate components with the interaction between components being evaluated by the application of each of the single disciplines in a sequential manner. Here, one discipline uses information from the calculation of another discipline to determine the effects of component coupling. This approach, however, may not properly identify the consequences of these effects during the design phase, leaving the interactions to be discovered and evaluated during engine testing. This contributes to the time and cost of developing new propulsion systems as, typically, several design-build-test cycles are needed to fully identify multidisciplinary effects and reach the desired system performance. The alternative to sequential isolated component analysis is to use multidisciplinary coupling at a more fundamental level. This approach has been made more plausible due to recent advancements in computation simulation along with application of concurrent engineering concepts. Computer simulation systems designed to provide an environment which is capable of integrating the various disciplines into a single simulation system have been proposed and are currently being developed. One such system is being developed by the Numerical Propulsion System Simulation (NPSS) project. The NPSS project, being developed at the Interdisciplinary Technology Office at the NASA Lewis Research Center is a 'numerical test cell' designed to provide for comprehensive computational design and analysis of aerospace propulsion systems. It will provide multi-disciplinary analyses on a variety of computational platforms, and a user-interface consisting of expert systems, data base management and visualization tools, to allow the designer to investigate the complex interactions inherent in these systems. An interactive programming software system, known as the Application Visualization System (AVS), was utilized for the development of the propulsion system simulation. The modularity of this system provides the ability to couple propulsion system components, as well as disciplines, and provides for the ability to integrate existing, well established analysis codes into the overall system simulation. This feature allows the user to customize the simulation model by inserting desired analysis codes. The prototypical simulation environment for multidisciplinary analysis, called Turbofan Engine System Simulation (TESS), which incorporates many of the characteristics of the simulation environment proposed herein, is detailed.

Reed, John A.↗

Ductile Fracture - Gradient Regularization

Nuclear weapons alteration (ALT) and life extension programs (LEP) are of primary interest to the mission of Sandia National Laboratories. These programs continue to require experimental exploration and computational simulation of ductile failure scenarios to address qualification. Therefore, we invest in generating understanding about ductile failure as demonstrated though experimental procedures and computational simulation of engineering environments. In particular, we study an approach to ductile failure that incorporates the notion of phase-field fracture into our models of inelasticity appropriate for structural alloys. This report covers the formulations of the constitutive model and fracture models used within the phase-field approach and provides some numerical examples highlighting features and the state of the capability.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Decoding Oxyanion Aqueous Solvation Structure: A Potassium Nitrate Example at Saturation

We present that the ability to probe the structure of a salt solution at the atomic scale is fundamentally important for our understanding of many chemical reactions and their mechanisms. The capability of neutron diffraction to “see” hydrogen (or deuterium) and other light isotopes is exceptional for resolving the structural complexity around the dissolved solutes in aqueous electrolytes. We have made measurements using oxygen isotopes on aqueous nitrate to reveal a small hydrogen-bonded water coordination number (3.9 ± 1.2) around a nitrate oxyanion. This is compared to estimates made using the existing method of nitrogen isotope substitution and those of computational simulations (>5–6 water molecules). The low water coordination number, combined with a comparison to classical molecular dynamics simulations, suggests that ion-pair formation is significant. Finally, this insight demonstrates the utility of experimental diffraction data for benchmarking atomistic computer simulations, enabling the development of more accurate intermolecular potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗

Geometry Modeling and Grid Generation for Computational Aerodynamic Simulations Around Iced Airfoils and Wings

Issues associated with analysis of 'icing effects' on airfoil and wing performances are discussed, along with accomplishments and efforts to overcome difficulties with ice. Because of infinite variations of ice shapes and their high degree of complexity, computational 'icing effects' studies using available software tools must address many difficulties in geometry acquisition and modeling, grid generation, and flow simulation. The value of each technology component needs to be weighed from the perspective of the entire analysis process, from geometry to flow simulation. Even though CFD codes are yet to be validated for flows over iced airfoils and wings, numerical simulation, when considered together with wind tunnel tests, can provide valuable insights into 'icing effects' and advance our understanding of the relationship between ice characteristics and their effects on performance degradation.

Choo, Yung K.↗

Helium bubble flow visualization of the spanwise separation on a NACA 0012 with simulated glaze ice

Research was performed to experimentally visualize and document the flow separation due to simulated glaze ice accretion on a NACA 0012 semispan with 30 deg sweep using helium bubbles as flow tracers. Results are compared to Navier-Stokes computational simulations for different angles of attack. Prior to acquiring data for the semispan model, a two dimensional experiment was conducted to determine the accuracy of using the helium bubbles as flow tracers. Results from the three dimensional experiment compare well to the computational simulations.

Kerho, M.↗

Helium bubble flow visualization of the spanwise separation on a NACA 0012 with simulated glaze ice

Research has been performed to experimentally visualize and document the flow separation due to simulated glaze ice accretion on a NACA 0012 semispan with 30-deg sweep using helium bubbles as flow tracers. Results are compared to Navier-Stokes computational simulations for different angles of attack. Prior to acquiring data for the semispan model, a two-dimensional experiment was conducted to determine the accuracy of using the helium bubbles as flow tracers. Results from the 3D experiment compare well to the computational simulations.

Kerho, M.↗

Classification of computed thermal tomography images with deep learning convolutional neural network

Thermal tomography (TT) is a computational method for the reconstruction of depth profile of the internal material defects from Pulsed Infrared Thermography (PIT) nondestructive evaluation. Here, the PIT method consists of recording material surface temperature transients with a fast frame infrared camera, following thermal pulse deposition on the material surface with a flashlamp and heat diffusion into material bulk. TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of the subsurface internal defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to the heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify the size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. The performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shapes imported from scanning electron microscopy images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on the TT images of elliptical defects is capable of classifying the shape and orientation of irregular defects.

42 ENGINEERING↗

Chemical Reactivity Through Adaptive Quantum Mechanics/Many-Body Representations: Theoretical Development, Software Implementation, and Applications (Final Report)

The main objective of this research project was the development and application of a new theoretical/computational framework to model chemical transformations and electronic excitations in fluid mixtures across different phases. Our theoretical/computational framework combines our data-driven many-body (DD-MB) potentials representing molecular interactions with adaptive schemes for modeling chemical reactions in solution. The combination of these two components resulted in an adaptive quantum mechanics/many-body (adQM/MB) method that largely suppresses discontinuities between QM and MM regions, which affect existing QM/MM methods, and thus provides an accurate representation of both quantum mechanical and environmental effects through a rigorous description of mutual polarization between QM and MM regions. The implementation of our DD-MB potentials and adQM/MB method in popular software enabled computer simulations of solvation phenomena, reactive processes, and electronic excitations in fluid mixtures with chemical and spectroscopic accuracy, representing a major step toward realistic computer simulations of a wide range of molecular systems relevant to the DOE mission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗