ALBERT

Description: In 1939, W. Weibull developed what is now commonly known as the "Weibull Distribution Function" primarily to determine the cumulative strength distribution of small sample sizes of elemental fracture specimens. In 1947, G. Lundberg and A. Palmgren, using the Weibull Distribution Function developed a probabilistic lifing protocol for ball and roller bearings. In 1987, E. V. Zaretsky using the Weibull Distribution Function modified the Lundberg and Palmgren approach to life prediction. His method incorporates the results of coupon fatigue testing to compute the life of elemental stress volumes of a complex machine element to predict system life and reliability. This paper examines the Zaretsky method to determine the probabilistic life and reliability of a model gas turbine disk using experimental data from coupon specimens. The predicted results are compared to experimental disk endurance data.

Description: The two estimation methods, individual data and arithmetic mean methods, were used to determine the slow crack growth (SCG) parameters (n and D) of advanced ceramics and glass from a large number of room- and elevated-temperature constant stress-rate ('dynamic fatigue') test data. For ceramic materials with Weibull modulus greater than 10, the difference in the SCG parameters between the two estimation methods was negligible; whereas, for glass specimens exhibiting Weibull modulus of about 3, the difference was amplified, resulting in a maximum difference of 16 and 13 %, respectively, in n and D. Of the two SCG parameters, the parameter n was more sensitive to the estimation method than the other. The coefficient of variation in n was found to be somewhat greater in the individual data method than in the arithmetic mean method.

Description: The goal of this project is to use a sandwich structure design, consisting of two stainlesssteel face sheets and a stainless-steel-foam core, to fabricate engine fan and propeller blades. Current fan blades are constructed either of polymer matrix composites (PMCs) or hollow titanium alloys. The PMC blades are expensive and have poor impact resistance on their leading edges, thereby requiring a metallic leading edge to satisfy the Federal Aviation Administration s impact requirements relating to bird strikes. Hollow titanium blades cost more to fabricate because of the intrinsically difficult fabrication issues associated with titanium alloys. However, both these current concepts produce acceptable lightweight fan blades.

Description: Modern engineering design practices are tending more toward the treatment of design parameters as random variables as opposed to fixed, or deterministic, values. The probabilistic design approach attempts to account for the uncertainty in design parameters by representing them as a distribution of values rather than as a single value. The motivations for this effort include preventing excessive overdesign as well as assessing and assuring reliability, both of which are important for aerospace applications. However, the determination of the probability distribution is a fundamental problem in reliability analysis. A random variable is often defined by the parameters of the theoretical distribution function that gives the best fit to experimental data. In many cases the distribution must be assumed from very limited information or data. Often the types of information that are available or reasonably estimated are the minimum, maximum, and most likely values of the design parameter. For these situations the beta distribution model is very convenient because the parameters that define the distribution can be easily determined from these three pieces of information. Widely used in the field of operations research, the beta model is very flexible and is also useful for estimating the mean and standard deviation of a random variable given only the aforementioned three values. However, an assumption is required to determine the four parameters of the beta distribution from only these three pieces of information (some of the more common distributions, like the normal, lognormal, gamma, and Weibull distributions, have two or three parameters). The conventional method assumes that the standard deviation is a certain fraction of the range. The beta parameters are then determined by solving a set of equations simultaneously. A new method developed in-house at the NASA Glenn Research Center assumes a value for one of the beta shape parameters based on an analogy with the normal distribution (ref.1). This new approach allows for a very simple and direct algebraic solution without restricting the standard deviation. The beta parameters obtained by the new method are comparable to the conventional method (and identical when the distribution is symmetrical). However, the proposed method generally produces a less peaked distribution with a slightly larger standard deviation (up to 7 percent) than the conventional method in cases where the distribution is asymmetric or skewed. The beta distribution model has now been implemented into the Fast Probability Integration (FPI) module used in the NESSUS computer code for probabilistic analyses of structures (ref. 2).

Description: High temperature thermomechanical and bithermal fatigue behavior was investigated for two superalloys: cast nickel-base B1900+Hf and wrought cobalt-base Haynes 188. Experimental results were generated to support development of an advanced thermal fatigue life prediction method. Strain controlled thermomechanical and load-controlled, strain-limited, bithermal fatigue tests were used to determine the fatigue crack initiation and cyclic stress-strain response characteristics of superalloys. Bithermal temperatures of 483 and 871 C were used for B1900+Hf, and 316 and 760 C for Haynes 188. Thermomechanical fatigue tests were conducted by using maximum and minimum temperatures corresponding to those for the bithermal experiments. Lives cover the range from about 10 to 3000 cycles to failure. Isothermal fatigue results obtained previously are also discussed.

Description: The goal of this project at the NASA Glenn Research Center is to provide fan materials that are safer, weigh less, and cost less than the currently used titanium alloy or polymer matrix composite fans. The proposed material system is a sandwich fan construction made up of thin solid face sheets and a lightweight metal foam core. The stiffness of the sandwich structure is increased by separating the two face sheets by the foam layer. The resulting structure has a high stiffness and lighter weight in comparison to the solid facesheet material alone. The face sheets carry the applied in-plane and bending loads (ref. 1). The metal foam core must resist the transverse shear and transverse normal loads, as well as keep the facings supported and working as a single unit. Metal foams have ranges of mechanical properties, such as light weight, impact resistance, and vibration suppression (ref. 2), which makes them more suitable for use in lightweight fan structures. Metal foams have been available for decades (refs. 3 and 4), but the difficulties in the original processes and high costs have prevented their widespread use. However, advances in production techniques and cost reduction have created a new interest in this class of materials (ref. 5). The material chosen for the face sheet and the metal foam for this study was the aerospace-grade stainless steel 17-4PH. This steel was chosen because of its attractive mechanical properties and the ease with which it can be made through the powder metallurgy process (ref. 6). The advantages of a metal foam core, in comparison to a typical honeycomb core, are material isotropy and the ease of forming complex geometries, such as fan blades. A section of a 17-4PH sandwich structure is shown in the following photograph. Part of process of designing any blade is to determine the natural frequencies of the particular blade shape. A designer needs to predict the resonance frequencies of a new blade design to properly identify a useful operating range. Operating a blade at or near the resonance frequencies leads to high-cycle fatigue, which ultimately limits the blade's durability and life. So the aim of this study is to determine the variation of the resonance frequencies for an idealized sandwich blade as a function of its face-sheet thickness, core thickness, and foam density. The finite element method is used to determine the natural frequencies for an idealized rectangular sandwich blade. The proven Lanczos method (ref. 7) is used in the study to extract the natural frequency.

Description: The quest for cheap, low density and high performance materials in the design of aircraft and rotorcraft engine fan and propeller blades poses immense challenges to the materials and structural design engineers. The present study investigates the use of a sandwich foam fan blade mae up of solid face sheets and a metal foam core. The face sheets and the metal foam core material were an aerospace grade precipitation hardened 17-4 PH stainless steel with high strength and high toughness. The resulting structures possesses a high stiffness while being lighter than a similar solid construction. The material properties of 17-4 PH metal foam are reviewed briefly to describe the characteristics of sandwich structure for a fan blade application. A vibration analysis for natural frequencies and a detailed stress analysis on the 17-4 PH sandwich foam blade design for different combinations of kin thickness and core volume are presented with a comparison to a solid titanium blade.

Description: Designing reliable structures requires an estimate of the maximum and minimum values (i.e., strength and load) that may be encountered in service. Yet designs based on very extreme values (to insure safety) can result in extra material usage and hence, uneconomic systems. In aerospace applications, severe over-design cannot be tolerated making it almost mandatory to design closer to the assumed limits of the design random variables. The issue then is predicting extreme values that are practical, i.e. neither too conservative or non-conservative. Obtaining design values by employing safety factors is well known to often result in overly conservative designs and. Safety factor values have historically been selected rather arbitrarily, often lacking a sound rational basis. To answer the question of how safe a design needs to be has lead design theorists to probabilistic and statistical methods. The so-called three-sigma approach is one such method and has been described as the first step in utilizing information about the data dispersion. However, this method is based on the assumption that the random variable is dispersed symmetrically about the mean and is essentially limited to normally distributed random variables. Use of this method can therefore result in unsafe or overly conservative design allowables if the common assumption of normality is incorrect.

Description: With the increased emphasis on reducing the cost and time to market of new materials, the need for robust automated materials information management system(s) enabling sophisticated data mining tools is increasing, as evidenced by the emphasis on Integrated Computational Materials Engineering (ICME) and the recent establishment of the Materials Genome Initiative (MGI). This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Further, the use of increasingly sophisticated nonlinear, anisotropic and or multi-scale models requires both the processing of large volumes of test data and complex materials data necessary to establish processing-microstructure-property-performance relationships. Fortunately, material information management systems have kept pace with the growing user demands and evolved to enable: (i) the capture of both point wise data and full spectra of raw data curves, (ii) data management functions such as access, version, and quality controls;(iii) a wide range of data import, export and analysis capabilities; (iv) data pedigree traceability mechanisms; (v) data searching, reporting and viewing tools; and (vi) access to the information via a wide range of interfaces. This paper discusses key principles for the development of a robust materials information management system to enable the connections at various length scales to be made between experimental data and corresponding multiscale modeling toolsets to enable ICME. In particular, NASA Glenn's efforts towards establishing such a database for capturing constitutive modeling behavior for both monolithic and composites materials