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At least 127 records · Page 7

Reliability analysis of single crystal NiAl turbine blades

As part of a co-operative agreement with General Electric Aircraft Engines (GEAE), NASA LeRC is modifying and validating the Ceramic Analysis and Reliability Evaluation of Structures algorithm for use in design of components made of high strength NiAl based intermetallic materials. NiAl single crystal alloys are being actively investigated by GEAE as a replacement for Ni-based single crystal superalloys for use in high pressure turbine blades and vanes. The driving force for this research lies in the numerous property advantages offered by NiAl alloys over their superalloy counterparts. These include a reduction of density by as much as a third without significantly sacrificing strength, higher melting point, greater thermal conductivity, better oxidation resistance, and a better response to thermal barrier coatings. The current drawback to high strength NiAl single crystals is their limited ductility. Consequently, significant efforts including the work agreement with GEAE are underway to develop testing and design methodologies for these materials. The approach to validation and component analysis involves the following steps: determination of the statistical nature and source of fracture in a high strength, NiAl single crystal turbine blade material; measurement of the failure strength envelope of the material; coding of statistically based reliability models; verification of the code and model; and modeling of turbine blades and vanes for rig testing.

Salem, Jonathan↗

High temperature thermoplastic elastomers synthesized by living anionic polymerization in hydrocarbon solvent at room temperature

We present the synthesis and characterization of a new class of high temperature thermoplastic elastomers composed of polybenzofulvene–polyisoprene–polybenzofulvene (FIF) triblock copolymers. All copolymers were prepared by living anionic polymerization in benzene at room temperature. Homopolymerization and effects of additives on the glass transition temperature (T g ) of polybenzofulvene (PBF) were also investigated. Among all triblock copolymers studied, FIF with 14 vol % of PBF exhibited a maximum stress of 14.3 ± 1.3 MPa and strain at break of 1390 ± 66% from tensile tests. The stress–strain curves of FIF-10 and 14 were analyzed by a statistical molecular approach using a nonaffine tube model to estimate the thermoplastic elastomer behavior. Dynamic mechanical analysis showed that the softening temperature of PBF in FIF was 145 °C, much higher than that of thermoplastic elastomers with polystyrene hard blocks. Microphase separation of FIF triblock copolymers was observed by small-angle X-ray scattering, even though long-range order was not achieved under the annealing conditions employed. Additionally, the microphase separation of the resulting triblock copolymers was examined by atomic force microscopy.

36 MATERIALS SCIENCE↗

Grid-based minimization at scale: Feldman-Cousins corrections for light sterile neutrino search

High Energy Physics (HEP) experiments generally employ sophisticated statistical methods to present results in searches of new physics. In the problem of searching for sterile neutrinos, likelihood ratio tests are applied to short-baseline neutrino oscillation experiments to construct confidence intervals for the parameters of interest. The test statistics of the form Δχ2 is often used to form the confidence intervals, however, this approach can lead to statistical inaccuracies due to the small signal rate in the region-of-interest. In this paper, we present a computational model for the computationally expensive Feldman-Cousins corrections to construct a statistically accurate confidence interval for neutrino oscillation analysis. The program performs a grid-based minimization over oscillation parameters and is written in C++. Our algorithms make use of vectorization through Eigen3, yielding a single-core speed-up of 350 compared to the original implementation, and achieve MPI data parallelism by employing DIY. We demonstrate the strong scaling of the application at High-Performance Computing (HPC) sites. We utilize HDF5 along with HighFive to write the results of the calculation to file.

Wospakrik, Marianette↗

Model Update of a Micro Air Vehicle (MAV) Flexible Wing Frame with Uncertainty Quantification

This paper describes a procedure to update parameters in the finite element model of a Micro Air Vehicle (MAV) to improve displacement predictions under aerodynamics loads. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with Multidisciplinary Design Optimization (MDO) is used to modify key model parameters. Static test data collected using photogrammetry are used to correlate with model predictions. Results show significant improvements in model predictions after parameters are updated; however, computed probabilities values indicate low confidence in updated values and/or model structure errors. Lessons learned in the areas of wing design, test procedures, modeling approaches with geometric nonlinearities, and uncertainties quantification are all documented.

Reaves, Mercedes C.↗

Simulation Evaluation of Synthetic Vision as an Enabling Technology for Equivalent Visual Operations

Enhanced Vision (EV) and synthetic vision (SV) systems may serve as enabling technologies to meet the challenges of the Next Generation Air Transportation System (NextGen) Equivalent Visual Operations (EVO) concept ? that is, the ability to achieve or even improve on the safety of Visual Flight Rules (VFR) operations, maintain the operational tempos of VFR, and even, perhaps, retain VFR procedures independent of actual weather and visibility conditions. One significant challenge lies in the definition of required equipage on the aircraft and on the airport to enable the EVO concept objective. A piloted simulation experiment was conducted to evaluate the effects of the presence or absence of Synthetic Vision, the location of this information during an instrument approach (i.e., on a Head-Up or Head-Down Primary Flight Display), and the type of airport lighting information on landing minima. The quantitative data from this experiment were analyzed to begin the definition of performance-based criteria for all-weather approach and landing operations. Objective results from the present study showed that better approach performance was attainable with the head-up display (HUD) compared to the head-down display (HDD). A slight performance improvement in HDD performance was shown when SV was added, as the pilots descended below 200 ft to a 100 ft decision altitude, but this performance was not tested for statistical significance (nor was it expected to be statistically significant). The touchdown data showed that regardless of the display concept flown (SV HUD, Baseline HUD, SV HDD, Baseline HDD) a majority of the runs were within the performance-based defined approach and landing criteria in all the visibility levels, approach lighting systems, and decision altitudes tested. For this visual flight maneuver, RVR appeared to be the most significant influence in touchdown performance. The approach lighting system clearly impacted the pilot's ability to descend to 100 ft height above touchdown based on existing Federal Aviation Regulation (FAR) 91.175 using a 200 ft decision height, but did not appear to influence touchdown performance or approach path maintenance

Kramer, Lynda J.↗

Flamelet Model Application for Non-Premixed Turbulent Combustion

The current Final Report contains results of the study which was performed in Scientific Research Center 'ECOLEN' (Moscow, Russia). The study concerns the development and verification of non-expensive approach for modeling of supersonic turbulent diffusion flames based on flamelet consideration of the chemistry/turbulence interaction (FL approach). Research work included: development of the approach and CFD tests of the flamelet model for supersonic jet flames; development of the simplified procedure for solution of the flamelet equations based on partial equilibrium chemistry assumption; study of the flame ignition/extinction predictions provided by flamelet model. The performed investigation demonstrated that FL approach allowed to describe satisfactory main features of supersonic H 2/air jet flames. Model demonstrated also high capabilities for reduction of the computational expenses in CFD modeling of the supersonic flames taking into account detailed oxidation chemistry. However, some disadvantages and restrictions of the existing version of approach were found in this study. They were: (1) inaccuracy in predictions of the passive scalar statistics by our turbulence model for one of the considered test cases; and (2) applicability of the available version of the flamelet model to flames without large ignition delay distance only. Based on the results of the performed investigation, we formulated and submitted to the National Aeronautics and Space Administration our Project Proposal for the next step research directed toward further improvement of the FL approach.

Secundov, A.↗

TH-CD-207A-07: Prediction of High Dimensional State Subject to Respiratory Motion: A Manifold Learning Approach

Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit more descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction reliability in such low dimensional manifold. The fixed-point iterative approach turns out to work well practically for the pre-image recovery. Our approach is particularly suitable to facilitate managing respiratory motion in image-guide radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.

60 APPLIED LIFE SCIENCES↗

Correlation approach for quality assurance of additive manufactured parts based on optical metrology

Surface topography and surface finish are two significant factors for evaluating the quality of products in additive manufacturing (AM). AM parts are fabricated layer by layer, which is quite different from traditional formative or subtractive methods. Despite rapid progress in additive manufacturing and associated optical metrology for quality control and in-situ monitoring, limited research has been conducted to investigate the reliability of 3D surface measurement data. The surface topologies scanned by multiple optical systems demonstrated significant differences due to varying sampling mechanisms, resolutions, system noises, etc. The 3D datasets should be trustworthy in order to extract parameters for quality assurance or feedback control from 3D surface measurements. In this paper, we set up new standards to evaluate the reliability of 3D surface measurement data and analyze the variation in the topographical profile. In this study, two non-contact optical methods based on Focus Variation Microscopy (FVM) and Structured Light System (SLS) were adopted to measure the surface topography of the target components. The two optical metrology systems generated two entirely different point cloud datasets. Statistical methods were applied to test the difference between the data obtained from the two systems. By using a data analytics approach for comparison, it was found that the surface roughness estimated from the point cloud data sets of FVM and SLS has no significant difference, though the point cloud data sets were completely different. This paper provides standard validation approach to evaluate the plausibility of metrology data from in-situ real-time surface analysis for process planning of AM.

36 MATERIALS SCIENCE↗

Neutral Networks for Subpixel Classification of Multispectral Images

In this work, the implementation and use of AVHRR (Advanced Very High Resolution Radiometer) images for subpixel analysis is studied. The work consists of two parts, the first is making training data, the second is using the training data to design a neural net subpixel analyzer. Most work on subpixel analysis has been done with images with more spectral bands. AVHRR images were chosen because of their easy acquisition, and because the five spectral bands allow investigation into the development of training data. The first step in subpixel analysis is the development of training data. This consists of image to be classified, and the classification of each pixel. In order to do the classification, a high spatial resolution image is typically needed in order to manually create a classified image. It is difficult to have both the image of interest, and a high spatial resolution image of the same area taken at the same time. Thus it was studied whether a subsampled image taken from the image of interest could serve as the training data. Statistical work has been done showing the unusefulness of this approach. In the second part of the analysis, a feedforward neural net was trained and used to classify the AVHRR images. Results of these tests, comparing the neural net with typical statistical based schemes are shown.

Figueroa, Ricardo R.↗

A Stochastic Cratering Model for Asteroid Surfaces

The observed cratering records on asteroid surfaces (four so far: Gaspra, Ida, Mathilde, and Eros [1-4]) provide us with important clues to their past bombardment histories. Previous efforts toward interpreting these records have led to two basic modeling styles for reproducing the statistics of the observed crater populations. The first, and most direct, method is to use Monte Carlo techniques [5] to stochastically populate a matrix-model test surface with craters as a function of time [6,7]. The second method is to use a more general, parameterized approach to duplicate the statistics of the observed crater population [8,9]. In both methods, several factors must be included beyond the simple superposing of circular features: (1) crater erosion by subsequent impacts, (2) infilling of craters by impact ejecta, and (3) crater degradation and era- sure due to the seismic effects of subsequent impacts. Here we present an updated Monte Carlo (stochastic) modeling approach, designed specifically with small- to medium-sized asteroids in mind.

Richardson, J. E.↗

Toward In Situ Synchrotron Mapping of Crystal Selection Processes during Crystal Growth

In this work, we present an automated and rapid method for non-destructive mapping of crystal grains in a rod-shaped sample. The approach was designed for application to in situ float-zone crystal growth experiments at an x-ray synchrotron source, but could be useful in other applications. The methods have been tested on a TiO 2 boule grown in an optical float zone furnace. The approach applies a statistical filter to polycrystalline diffraction patterns on 2D detectors to rapidly determine the degree of powder-quality 1of the signal. When larger crystals emerge in the growth, their position, size and shape can be tracked using an automated blob-tracking algorithm that follows individual Bragg peaks as a function of position in a grid-scan, even when multiple crystals are contributing spots to diffraction images. This method is found to be robust as the same crystal shape can be independently reconstructed using different sets of Bragg reflections. Image segmentation methods are then used to map out the polycrystalline grains. We also note that other information about crystal quality, such as mosaicity or strain state, may be inferred and mapped from the intensity variation of the Bragg peaks at different locations within the sample.

36 MATERIALS SCIENCE↗

Response of aerospace structures to reentry aerodynamic excitation

A bibliography on aerodynamic excitation and associated structural response is presented. Very little applicable data under actual reentry conditions was found, but many wind tunnel tests and some in-flight data were. Aerodynamic excitation and proposed space shuttle configurations and reentry trajectories were studied. Attached turbulent boundary layer, separated turbulent boundary layer, and base pressure fluctuations are the region of aerodynamic excitation most applicable to exterior panels of space shuttle-type vehicles; prediction techniques are presented for these environments. Methods for predicting the response of panel structures to acoustic excitation were investigated. A normal mode approach was developed for the low frequency response and a statistical energy approach was utilized for the high frequency response. A finite element model was made of a thermal protective system test panel. Computer programs were used to determine the natural frequencies and mode shapes of the panel and to calculate the response of the panel to a reverberant acoustic field. Power spectral densities of response displacement and acceleration are presented.

Carlin, D., Jr.↗

Results of a statistical approach to rainfall estimation using Nimbus 5 6.7 micrometers and 11.5 micrometers THIR data

Nimbus 5 6.7 mm and 11.5 mm temperature humidity infrared radiometer (THIR) data were used in a simple multiple regression scheme to test the feasibility of using these data to estimate hourly rainfall. Throughout the test area (85 W to 105 W and 45 N to 30 N) subareas (8 deg x 6 deg) were chosen from which point to point and areal statistics were obtained. Four subsets of data were used. The first consisted of only those surface stations indicating precipitation whose latitude and longitude coincided with the THIR grid points. A second used surface stations 0.1 degree from the THIR grid points. The third was a combination of subsets one and two. A reciprocal distance weighting scheme was used to derive precipitation values in data sparse areas. A fourth subset was made using these data combined with the data from subsets one and two. Point estimates resulted in negative correlations between estimated and grid derived "surface" precipitation. One degree areal estimates showed a slight improvement with a correlation coefficient of approximately 0.11. Single regression areal estimates resulted in correlations of approximately 0.11 and 0.20 for the 6.7 mm and 11.5 mm data respectively. These poor results were attributed to problems which are inherent in the satellite data (location errors, short temporal span of data, wavelength of sensors, etc.) and the lack of sufficient surface data to better verify the satellite estimate.

Ormsby, J. P.↗

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗

Plackett-Burman experimental design to facilitate syntactic foam development

The use of an eight-experiment Plackett–Burman method can assess six experimental variables and eight responses in a polysiloxane-glass microsphere syntactic foam. The approach aims to decrease the time required to develop a tunable polymer composite by identifying a reduced set of variables and responses suitable for future predictive modeling. The statistical design assesses the main effects of mixing process parameters, polymer matrix composition, microsphere density and volume loading, and the blending of two grades of microspheres, using a dummy factor in statistical calculations. Responses cover rheological, physical, thermal, and mechanical properties. The cure accelerator content of the polymer matrix and the volume loading of the microspheres have the largest effects on foam properties. These factors are the most suitable for controlling the gel point of the curing foam, and the density of the cured foam. The mixing parameters introduce widespread variability and therefore should be fixed at effective levels during follow-up testing. Some responses may require greater contrast in microsphere-related factors. As a result, compared to other possible statistical approaches, the run economy of the Plackett–Burman method makes it a valuable tool for rapidly characterizing new foams.

36 MATERIALS SCIENCE↗

Plant growth modeling at the JSC variable pressure growth chamber - An application of experimental design

This paper describes the approach and results of an effort to characterize plant growth under various environmental conditions at the Johnson Space Center variable pressure growth chamber. Using a field of applied mathematics and statistics known as design of experiments (DOE), we developed a test plan for varying environmental parameters during a lettuce growth experiment. The test plan was developed using a Box-Behnken approach to DOE. As a result of the experimental runs, we have developed empirical models of both the transpiration process and carbon dioxide assimilation for Waldman's Green lettuce over specified ranges of environmental parameters including carbon dioxide concentration, light intensity, dew-point temperature, and air velocity. This model also predicts transpiration and carbon dioxide assimilation for different ages of the plant canopy.

Miller, Adam M.↗

Improved Pyrotechnic Shock Scaling Method Based on Shock Response Spectrum and Statistical Energy Analysis

It has been more than forty years since the pyrotechnic shock scaling method was introduced. The scaling method estimates the attenuation of the Shock Response Spectrum (SRS) based on the distance from the source, structural configurations, types of structural joints and interfaces, and intervening structure [1]. The method has been successfully used in the spacecraft community countless times and still is frequently used to develop pyrotechnic shock requirements at various levels of assembly of a spacecraft. However, since the method was derived empirically from a limited set of shock test data [2], the aerospace community has been looking for an alternative approach. In this paper, a computational scaling method based on Statistical Energy Analysis (SEA) is re-visited. SEA is traditionally used as a method for investigating the diffusion of acoustic and vibratory energies of a system at steady-state [3]. Previously, an approach using the SRS as an acceleration constraint condition to the SEA model was introduced to estimate the attenuation from a shock source [4,5]. In the current investigation, additional examples are provided to further validate the approach. In addition, responses in the time domain are produced by the Local Modal Phase Reconstruction (LMPR) approach which was recently introduced to the community [6].

Fernandez, Juan P.↗

Statistical Tests for Convergence in Monte Carlo Criticality Calculations

This report describes methods for using statistical tests to automatically determine convergence of Monte Carlo (MC) iterations in criticality calculations. The methods described herein are intended to replace the traditional approach used for the past 60 years: make a trial run; determine convergence based on plots of k-effective and Shannon entropy vs cycle; adjust the input parameters for controlling the iterations; make a final run to obtain results and statistics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗