GaN vs. Si for Class D Audio Applications

The demands and applications of modern power electronics are quickly moving past the maximum performance capabilities of Silicon devices. As the processing of Wide Bandgap (WBG) materials matures and the commercial availability of WBG devices grows, circuit designers are exploring many applications to exploit the performance benefits over traditional Silicon devices. This work examines the under-explored application of GaN-based Class D audio by providing a side-by-side comparison of enhancement-mode GaN devices with currently available Silicon MOSFETs. It is suggested that GaN in Class D audio will allow for lower heat radiation, smaller circuit footprints, and longer battery life as compared to Si MOSFETs with a negligible trade-off for quality of sound

Set-up of Digital Image Correlation Apparatus

Digital Image Correlation (DIC) is a valuable and customizable experimental technique employed to analyze localized strain regions on materials by tracking the displacement of points on the surface of the studied material under applied stress. To investigate materials behavior, it is vital to correctly set-up the DIC apparatus so work has been done to ready the equipment to start measurements on two distinct projects. On the first project, the fatigue crack behavior of a high-strength aluminum alloy will be studied by cyclic loading, testing necessary for the safe design of aircraft parts utilizing this novel alloy. DIC will be carried out ahead of the fatigue crack and to accomplish this, a MATLAB code was developed to synchronize the loading machine with the DIC equipment and camera, and to automate the capture of images. On the second project, electronic microscopy will be utilized to carry out DIC at high resolutions to study the relationship of the microstructure of structural alloys and the strain fields generated on the material. A gold nanoparticle speckling method was adapted from literature to create a speckle pattern on the specimens with the desired length scale and density for this study. A satisfactory conclusion of the preparatory work of the DIC equipment and protocols will enable the testing to start for the two projects aforementioned

Metamodels of Residual Stress Buildup for Machining Process Modeling

In the process of machining materials, stresses, called residual stresses, accumulate in the workpiece being machined that remain after the process is completed. These residual stresses can affect the properties of the material or cause part distortion, and it is important that they be calculated to prevent complications from arising due to the residual stresses. However, these calculations can be incredibly computationally intensive, and thus other methods are needed to predict the residual stresses in materials for quick decision-making during machining. By using metamodels - a method of representing data where few data points exist - we can achieve an accurate prediction of the residual stresses without the need for computationally intensive calculations for each process. This involves running a series of simulations and creating a response surface from this data using the Kriging Method, which smooths out the surface such that small changes in inputs result in small changes in outputs. This achieves the result of a model for predicting the relative stresses in materials after the machining processes, and allows computationally expensive simulations to be bypassed in situations where the inputs do not vary large amounts outside of the initial simulations ran. This can allow better tracking of residual stresses, and thus lead to better control of the complications that can arise from residual stress buildup

Using High Resolution Images to Investigate Fatigue Crack Initiation of Alloys at the Microstructural Level

Microstructural features within a material dictate the material’s mechanical behavior and lead to localized strains as the sample is deformed. In order to further understand structural failure, an improved understanding of how microstructural features influence failure is necessary. Fatigue is one common mode of failure for aerospace applications, and a better understanding of the conditions of crack initiation can provide information that ultimately may increase longevity of aerospace systems. This paper investigates the hypothesis that fatigue crack initiation for a cyclically loaded sample is correlated to areas of higher localized strain. The experiment was conducted using a Ti-6Al-4V sample subjected to low amplitude fatigue ratio. For sample preparation, a titanium nanopowder solution is applied to an area of interest. The titanium particles on the sample are then imaged in an optical microscope, and the displacement of each particle is measured after loading the sample. The resultant displacement field is converted into a strain field, which will indicate locations on the sample with higher localized strains. When comparing sites of crack initiation to the strain field map, there is a tendency for cracks to initiate near locations with high localized strains. This knowledge can lead to an improved ability to predict fatigue crack initiation locations, and can also be used to improve structural designs at the microstructural level

Evaluation of Strain Distortion Correction Protocol using Scanning Electron Microscopy and Digital Image Correlation

Scanning electron microscopy in combination with digital image correlation (SEM-DIC) is a useful technique for measuring strain in materials at the micro-scale. In particular, it can be used to identify micro-scale strain localizations that are the precursor to material failure. While SEM produces high resolution images of the microstructure, the images also contain a large amount of distortion that, during DIC, will result in distorted strain values that require correction. In this project, a nickel-based alloy underwent cyclic mechanical fatigue at three different high temperatures to a targeted maximum strain. Scanning electron microscopy imaging was done on a 200x150μm area sectioned into nine of the specimen before and after testing for digital image correlation, and electron backscatter diffraction (EBSD) was also used to image the grain boundaries within the sample area. Digital image correlation was done using the software Vic-2D, and corrections were done by following the protocol previously developed. The images were then stitched together and the EBSD images were overlaid the strain maps in MATLABTM. Results show that with the use of this protocol, corrected strain measurements are approximately equal to the macroscopic strain values obtained from testing, but allows for spatial strain fields relative to the microstructure. The accuracy with which this protocol is able to correct strain bias due to SEM makes it a useful tool for measuring strain value for this material, and can be used to estimate the strain values at which strain localization begin

Validation of Long-Fiber Thermoplastic Composite Models

With increased pressure to reduce energy consumption, long-fiber reinforced thermoplastic composites (LFTs) are of interest to aerospace and automotive industries due to their light weight in combination with other desirable mechanical properties and ease of manufacturing to replace common materials such as aluminum and magnesium. However, the performance of LFTs is highly dependent on microstructural variables such as fiber length and orientation, which are heavily influenced by the manufacturing process. Accurately predicting these factors would allow for more rapid advances in LFTs by reducing the experiments needed for certification and decreasing expenses. While models that serve this purpose exist, the current models require validation to be used within related industries. A secondary objective of this project is to standardize the process by which the fibers are extracted and measured with little bias. Validation is achieved by directly comparing simulation results with experimental fiber length and orientation distribution. The fiber lengths are determined by burning off the polymer matrix and extracting fiber samples, which are then separated and measured. Fiber orientation distributions are determined by using an automated process which calculates 2D orientations from polished sample surfaces. The validation process will provide input to the model, which will be iterative to obtain 15% accuracy of the model’s predictions compared to experimental results. After the validation is complete, the models will be used for industrial purposes to optimize LFTs microstructures for component designs

Influence of microstructure variability on short crack growth behavior

Fatigue life in metals is predicted utilizing regression analysis of large sets of experimental data. Furthermore, a high variability in the short crack growth (SCG) rate has been observed in polycrystalline materials, in which the evolution and distribution of local plasticity is strongly influenced by the microstructure features. We aim to identify relationships between the crack driving force and the materials microstructure; specifically addressing variability of microstructure features and slip activity near a crack-tip as a means to account for the variability in the SCG behavior. To investigate the effects of microstructure variability on the SCG rate, sets of different microstructure realizations are constructed, in which cracks of different length are introduced to mimic quasi-static SCG. Through fatigue indicator parameters within crystal plasticity models, scatter within the SCG rates is related to variability in the microstructural features as a means to quantify uncertainty in fatigue behavior

Fiber Length and Orientation in Long Carbon Fiber Thermoplastic Composites

Carbon fiber composites have become popular in aerospace applications because of their lightweight yet strong material properties. The injection molding process can be used to produce discontinuous fiber composites using less time and resources than traditional methods, thereby broadening carbon fiber composites’ applications in different industries. Utilization of longer fibers offers more load carrying capability and superior strength properties for injected molded composites. Since the fiber length and the orientation distribution in Long Fiber Thermoplastics (LFTs) directly affects LFT composites’ material properties, there is a need to study the microstructure of LFTs and characterize fiber length and orientation distributions. Therefore, this work aims to experimentally measure fiber length and orientation in pre-manufactured carbon fiber LFT composites in order to validate computer simulations of the injection molding process, and to therefore better predict mechanical properties. Fiber orientation distribution was measured by the optimization of several grinding and polishing steps followed by microscopic imaging of a sample’s cross-section. On the other hand, fiber length distribution was measured through the development of epoxy burn-off, down-selection, and fiber separation procedures, followed by microscopic imaging and manual fiber length measurements. By specifically optimizing these procedures for the analysis of carbon fiber LFTs, a detailed method has been developed to analyze the fiber length and orientation distributions and quantify any bias in the characterization techniques. Using the methods developed in this work, computer simulations can be validated and microstructure properties can be analyzed, allowing for better material strength predictions and industry implementation of LFTs

Characterization And Modeling Of Discontinuous Fiber Composites

Composite materials, which are light and strong, are of great interest to engineers in the aerospace industry. Specifically in this work, a discontinuous short fiber reinforced polymer composite whose matrix is Polypropylene and fibers are Electric-glass oriented in different directions was studied. The performance of this material is highly dependent on its microstructure, and therefore the objective of this research is to non-destructively characterize the microstructure of the composite material. This includes characterization of its fiber orientation and length, fiber volume fraction, and void volume fraction. To do this, X-ray micro-computed tomography has been used, providing two dimensional cross-sectional images that stack to form a three-dimensional image of the microstructure. Advanced image-processing methods have been used to determine the fiber volume fraction, the void volume fraction, and the fiber length distributions. Characterization of the microstructure will help predict its mechanical properties and establish a general framework for characterizing and predicting the strength of composite materials. Through the advanced characterization and strength prediction methods discussed in this work, engineers will eventually be able to quickly and non-destructively evaluate materials and thereby reduce large scale testing in aerospace applications