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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 37 records · Page 2

Parametric evaluation of ball milling of SiC in water

A statistically designed experiment was conducted to determine optimum conditions for ball milling alpha-SiC in water. The influence of pH adjustment, volume percent solids loading, and mill rotational speed on grinding effectiveness was examined. An equation defining the effect of those milling variables on specific surface area was obtained. The volume percent solids loading of the slurry had the greatest influence on the grinding effectiveness in terms of increase in specific surface area. As grinding effectiveness improved, mill and media wear also increased. Contamination was minimized by use of sintered alpha-SiC milling hardware.

Kiser, J. D.↗

Parametric evaluation of ball milling of SiC in water

A statistically designed experiment was conducted to determine optimum conditions for ball milling alpha-SiC in water. The influence of pH adjustment, volume percent solids loading, and mill rotational speed on grinding effectiveness was examined. An equation defining the effect of those milling variables on specific surface area was obtained. The volume percent solids loading of the slurry had the greatest influence on the grinding effectiveness in terms of increase in specific surface area. As grinding effectiveness improved, mill and media wear also increased. Contamination was minimized by use of sintered alpha-SiC milling hardware.

Kiser, J. D.↗

Improved silicon carbide for advanced heat engines. I - Process development for injection molding

Alternate processing methods have been investigated as a means of improving the mechanical properties of injection-molded SiC. Various mixing processes (dry, high-sheer, and fluid) were evaluated along with the morphology and particle size of the starting beta-SiC powder. Statistically-designed experiments were used to determine significant effects and interactions of variables in the mixing, injection molding, and binder removal process steps. Improvements in mechanical strength can be correlated with the reduction in flaw size observed in the injection molded green bodies obtained with improved processing methods.

Whalen, Thomas J.↗

Improved silicon carbide for advanced heat engines

This is the third annual technical report for the program entitled, Improved Silicon Carbide for Advanced Heat Engines, for the period February 16, 1987 to February 15, 1988. The objective of the original program was the development of high strength, high reliability silicon carbide parts with complex shapes suitable for use in advanced heat engines. Injection molding is the forming method selected for the program because it is capable of forming complex parts adaptable for mass production on an economically sound basis. The goals of the revised program are to reach a Weibull characteristic strength of 550 MPa (80 ksi) and a Weibull modulus of 16 for bars tested in 4-point loading. Two tasks are discussed: Task 1 which involves materials and process improvements, and Task 2 which is a MOR bar matrix to improve strength and reliability. Many statistically designed experiments were completed under task 1 which improved the composition of the batches, the mixing of the powders, the sinter and anneal cycles. The best results were obtained by an attritor mixing process which yielded strengths in excess of 550 MPa (80 ksi) and an individual Weibull modulus of 16.8 for a 9-sample group. Strengths measured at 1200 and 1400 C were equal to the room temperature strength. Annealing of machined test bars significantly improved the strength. Molding yields were measured and flaw distributions were observed to follow a Poisson process. The second iteration of the Task 2 matrix experiment is described.

Whalen, Thomas J.↗

Improved silicon carbide for advanced heat engines

The development of high strength, high reliability silicon carbide parts with complex shapes suitable for use in advanced heat engines is studied. Injection molding was the forming method selected for the program because it is capable of forming complex parts adaptable for mass production on an economically sound basis. The goals were to reach a Weibull characteristic strength of 550 MPa (80 ksi) and a Weibull modulus of 16 for bars tested in four-point loading. Statistically designed experiments were performed throughout the program and a fluid mixing process employing an attritor mixer was developed. Compositional improvements in the amounts and sources of boron and carbon used and a pressureless sintering cycle were developed which provided samples of about 99 percent of theoretical density. Strengths were found to improve significantly by annealing in air. Strengths in excess of 550 MPa (80 ksi) with Weibull modulus of about 9 were obtained. Further improvements in Weibull modulus to about 16 were realized by proof testing. This is an increase of 86 percent in strength and 100 percent in Weibull modulus over the baseline data generated at the beginning of the program. Molding yields were improved and flaw distributions were observed to follow a Poisson process. Magic angle spinning nuclear magnetic resonance spectra were found to be useful in characterizing the SiC powder and the sintered samples. Turbocharger rotors were molded and examined as an indication of the moldability of the mixes which were developed in this program.

Whalen, Thomas J.↗

Statistical design study of lunar ceramic

Fabrication of a lunar ceramic was conducted according to a statistically designed experiment. The method of cold pressing was used since the consumption of electrical energy is kept to a minimum (a priority in the lunar environment). This traditional fabrication technique also provides an initial data source on which further investigations can be based. Results obtained from using two percent binder, a cold pressing pressure of 276 MPa, and 24 hours sintering time yielded the greatest compressive strength of 247 MPa. Analysis of each variable's influence on the compressive strength is also presented.

Effinger, Mike↗

Low Temperature Unbalanced Magnetron Deposition of Hard, Wear-Resistant Coatings for Liquid-Film Bearing Applications

The original program for evaluating the tribological properties several different hard coatings for liquid film bearing applications was curtailed when the time for the program was reduced from 3 years to 1. Of the several different coatings originally planned for evaluation, we decided to concentrate on one coating, carbon nitride. At BIRL, we have been instrumental in the development of reactively sputtered carbon nitride coatings, and we have found that it is a very interesting new material with very good tribological properties. In this program, we found that the reactively sputtered carbon nitride does not bond well directly to hardened 440C stainless steel; but if an interlayer of titanium nitride is added between the carbon nitride and the 440C, the adhesion of the dual coating combination is very good. Statistically designed experiments were run with the dual layer combination, and 3 variables were chosen for the Box-Benken design, which were the titanium nitride interlayer thickness, the nitrogen partial pressure during the reactive sputtering of the carbon nitride, and the carbon nitride substrate bias voltage. Two responses were studied from these three variables; the adhesion of the dual coating combination to the 440C substrate and the friction coefficient of the carbon nitride in dry sliding contact with 52100 steel in air. The best adhesion came with the thickness interlayer thickness studied, which was 4 micrometers, and the lowest coefficient of friction was 0.1, which was achieved when the bias voltage was in the range of -80 to - 120 V and the nitrogen partial pressure was 3 mTorr.

Sproul, William D.↗

An Acoustic Charge Transport Imager for High Definition Television Applications: Reliability Modeling and Parametric Yield Prediction of GaAs Multiple Quantum Well Avalanche Photodiodes

Reliability modeling and parametric yield prediction of GaAs/AlGaAs multiple quantum well (MQW) avalanche photodiodes (APDs), which are of interest as an ultra-low noise image capture mechanism for high definition systems, have been investigated. First, the effect of various doping methods on the reliability of GaAs/AlGaAs multiple quantum well (MQW) avalanche photodiode (APD) structures fabricated by molecular beam epitaxy is investigated. Reliability is examined by accelerated life tests by monitoring dark current and breakdown voltage. Median device lifetime and the activation energy of the degradation mechanism are computed for undoped, doped-barrier, and doped-well APD structures. Lifetimes for each device structure are examined via a statistically designed experiment. Analysis of variance shows that dark-current is affected primarily by device diameter, temperature and stressing time, and breakdown voltage depends on the diameter, stressing time and APD type. It is concluded that the undoped APD has the highest reliability, followed by the doped well and doped barrier devices, respectively. To determine the source of the degradation mechanism for each device structure, failure analysis using the electron-beam induced current method is performed. This analysis reveals some degree of device degradation caused by ionic impurities in the passivation layer, and energy-dispersive spectrometry subsequently verified the presence of ionic sodium as the primary contaminant. However, since all device structures are similarly passivated, sodium contamination alone does not account for the observed variation between the differently doped APDs. This effect is explained by the dopant migration during stressing, which is verified by free carrier concentration measurements using the capacitance-voltage technique.

Hunt, W. D.↗

Non-Asbestos Insulation Testing Using a Plasma Torch

Insulation obsolescence issues are a major concern for the Reusable Solid Rocket Motor (RSRM). As old sources of raw materials disappear, new sources must be found and qualified. No simple, inexpensive test presently exists for predicting the erosion performance of a candidate insulation in the full-scale motor, Large motor tests cost million of dollars and therefore can only be used on a few very select candidates. There is a need for a simple, low cost method of screening insulation performance that can simulate some of the different erosion environments found in the RSRM. This paper describes a series of erosion tests on two different non-asbestos insulation formulations, a KEVLAR(registered) fiber-filled and a carbon fiber-filled insulation containing Ethylene-Propylene-Diene Monomer (EPDM) rubber as the binder. The test instrument was a plasma torch device. The two main variables investigated were heat flux and alumina particle impingement concentration. Statistical analysis revealed that the two different formulations had very different responses to the main variable. The results of this work indicate that there may be fundamental differences in how these insulation formulations perform in the motor operating environment. The plasma torch appears to offer a low-cost means of obtaining a fundamental understanding of insulation response to critical factors in a series of statistically designed experiments.

Morgan, R. E.↗

Unsteady Ejector Performance: An Experimental Investigation Using a Resonance Tube Driver

A statistically designed experiment to characterize thrust augmentation for unsteady ejectors has been conducted at the NASA Glenn Research Center. The variable parameters included ejector diameter, length, and nose radius. The pulsed jet driving the ejectors was produced by a shrouded resonance (or Hartmann-Sprenger) tube. In contrast to steady ejectors, an optimum ejector diameter was found, which coincided with the diameter of the vortex ring created at the pulsed jet exit. Measurements of ejector exit velocity using a hot-wire permitted evaluation of the mass augmentation ratio, which was found to correlate to thrust augmentation following a formula derived for steady ejectors.

Wilson, Jack↗

Thermal and Pressure Characterization of a Wind Tunnel Force Balance Using the Single Vector System

Wind tunnel research at NASA Langley Research Center s 31-inch Mach 10 hypersonic facility utilized a 5-component force balance, which provided a pressurized flow-thru capability to the test article. The goal of the research was to determine the interaction effects between the free-stream flow and the exit flow from the reaction control system on the Mars Science Laboratory aeroshell during planetary entry. In the wind tunnel, the balance was exposed to aerodynamic forces and moments, steady-state and transient thermal gradients, and various internal balance cavity pressures. Historically, these effects on force measurement accuracy have not been fully characterized due to limitations in the calibration apparatus. A statistically designed experiment was developed to adequately characterize the behavior of the balance over the expected wind tunnel operating ranges (forces/moments, temperatures, and pressures). The experimental design was based on a Taylor-series expansion in the seven factors for the mathematical models. Model inversion was required to calculate the aerodynamic forces and moments as a function of the strain-gage readings. Details regarding transducer on-board compensation techniques, experimental design development, mathematical modeling, and wind tunnel data reduction are included in this paper.

Lynn, Keith C.↗

Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

Fail-safe, hybrid, flow control (HFC) is a promising technology for meeting high-speed cruise efficiency, low-noise signature, and reduced fuel-burn goals for future, Hybrid-Wing-Body (HWB) aircraft with embedded engines. This report details the development of HFC technology that enables improved inlet performance in HWB vehicles with highly integrated inlets and embedded engines without adversely affecting vehicle performance. In addition, new test techniques for evaluating Boundary-Layer-Ingesting (BLI)-inlet flow-control technologies developed and demonstrated through this program are documented, including the ability to generate a BLI-like inlet-entrance flow in a direct-connect, wind-tunnel facility, as well as, the use of D-optimal, statistically designed experiments to optimize test efficiency and enable interpretation of results. Validated improvements in numerical analysis tools and methods accomplished through this program are also documented, including Reynolds-Averaged Navier-Stokes CFD simulations of steady-state flow physics for baseline, BLI-inlet diffuser flow, as well as, that created by flow-control devices. Finally, numerical methods were employed in a ground-breaking attempt to directly simulate dynamic distortion. The advances in inlet technologies and prediction tools will help to meet and exceed "N+2" project goals for future HWB aircraft.

McMillan, Michelle L.↗

Advances in Integrally Formed Metallic Structures

NASA Langley Research Center (LaRC) is applying flow forming technology to aerospace aluminum alloys for the manufacture of integrally stiffened cylinders that meet aircraft fuselage or launch vehicle specifications. High-strength 2xxx series alloys, in various temper/product form conditions, are being compared with medium-strength, very formable AA 6061 as the benchmark. Screening of candidate materials traditionally relies on empirical forming trials, but more recently on metrics derived from constant nominal strain rate tensile testing. In this work, the established hierarchy of formability metrics is adopted as the baseline; tensile area reduction, work hardening exponent, and modulus of resilience. The suite of metrics can be expanded based on phenomenological and mechanistic considerations of plastic flow instabilities to incorporate anisotropy ratio, rate of work hardening, and dynamic strain aging effects. Separate research thrusts at LaRC are aimed at formulating a protocol for scalable production of fully formed, defect-free components: 1) quantifying the extended set of formability metrics from constant and jump strain rate tensile tests with digital image correlation (DIC); 2) using statistically designed experiments on a vertical spin/flow forming facility (WF VUD-600®) to isolate the effect of convenient process variables, such as axial feed rate and thickness reduction; and 3) predicting the effect of feed ratio (roller translation relative to mandrel rotation speeds) on material response via process modeling using the DEFORM® simulation software. Current results will be discussed in terms of correlating intrinsic material properties with the bulk workability characteristics to successfully fabricate cylinders with complex cross-sections.

Aluminum↗

Statistical considerations in design of spacelab experiments

After making an analysis of experimental error sources, statistical models were developed for the design and analysis of potential Space Shuttle experiments. Guidelines for statistical significance and/or confidence limits of expected results were also included. The models were then tested out on the following proposed Space Shuttle biomedical experiments: (1) bone density by computer tomography; (2) basal metabolism; and (3) total body water. Analysis of those results and therefore of the models proved inconclusive due to the lack of previous research data and statistical values. However, the models were seen as possible guides to making some predictions and decisions.

Robinson, J.↗

On the Use of Statistics in Design and the Implications for Deterministic Computer Experiments

Perhaps the most prevalent use of statistics in engineering design is through Taguchi's parameter and robust design -- using orthogonal arrays to compute signal-to-noise ratios in a process of design improvement. In our view, however, there is an equally exciting use of statistics in design that could become just as prevalent: it is the concept of metamodeling whereby statistical models are built to approximate detailed computer analysis codes. Although computers continue to get faster, analysis codes always seem to keep pace so that their computational time remains non-trivial. Through metamodeling, approximations of these codes are built that are orders of magnitude cheaper to run. These metamodels can then be linked to optimization routines for fast analysis, or they can serve as a bridge for integrating analysis codes across different domains. In this paper we first review metamodeling techniques that encompass design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning, and kriging. We discuss their existing applications in engineering design and then address the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes. We conclude with recommendations for the appropriate use of metamodeling techniques in given situations and how common pitfalls can be avoided.

Simpson, Timothy W.↗

Determining significant material properties: A discovery approach

The following is a laboratory experiment designed to further understanding of materials science. The experiment itself can be informative for persons of any age past elementary school, and even for some in elementary school. The preparation of the plastic samples is readily accomplished by persons with resonable dexterity in the cutting of paper designs. The completion of the statistical Design of Experiments, which uses Yates' Method, requires basic math (addition and subtraction). Interpretive work requires plotting of data and making observations. Knowledge of statistical methods would be helpful. The purpose of this experiment is to acquaint students with the seven classes of recyclable plastics, and provide hands-on learning about the response of these plastics to mechanical tensile loading.

Karplus, Alan K.↗

Statistically-driven Experimental Design to Improve Reference-free Quantification of Small Molecules by Liquid Chromatography-Mass Spectrometry

Non-targeted analysis of small molecules and metabolites in unknown, complex samples using liquid chromatography-tandem mass spectrometry remains challenging. One of the main bottlenecks is the extensive unannotated regions of metabolomics mass spectrometry data, resulting in knowledge gaps. Small molecule annotation in mass spectrometry data has conventionally relied on reference standards and libraries for compound identification and confirmation, which can constrain compound identification to those molecules already known, thus limiting the ability to discover new knowledge and new markers. Retention time prediction can facilitate and expedite unknown compound identification in non-targeted analysis of complex metabolomics samples. Additionally, accurate retention time predictions can also inform sample mixture design for LC-MS/MS analyses. However, current machine learning-based methods for retention time prediction are typically developed for specific chromatographic platforms and are not generalizable across scales. And while technologies and methods to improve reference-free metabolite identification for more comprehensive annotation of unknowns has received much attention, development of the same for quantitation without reference standards has been much more limited, despite its importance in toxicological, environmental, food safety, forensics, and clinical applications. We believe that a reference-free quantitation strategy that exploits mass spectrometry data already collected for reference-free identification can provide much more insight on unknowns, and move the metabolomics field for more complete unknowns characterization. As such, we pursue two efforts to improve upon current state-of-the-art methods in non-targeted analysis: (1) machine learning-based retention time prediction and (2) statistical design of experiments framework for reference-free quantitation. In this work, we develop and demonstrate (1) a generalizable retention time prediction capability across chromatographic conditions and scales, and (2) a statistical design-based framework for response factor contribution elucidation and reference-free quantitation. Evaluation of our retention time prediction model, PrediToR, showed approximately 24% improvement over current models, and we observed approximately 10X improvement in concentration estimation accuracy from our statistical design-based response factor model over a primarily ionization efficiency-based model. We expect that future efforts to improve upon these new capabilities will further advance non-targeted analysis of small molecules towards truly reference-free metabolomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗