Richard D. Sisson

Bio: Richard D. Sisson is an academic researcher from Worcester Polytechnic Institute. The author has contributed to research in topics: Thermal barrier coating & Carburizing. The author has an hindex of 25, co-authored 108 publications receiving 1647 citations. Previous affiliations of Richard D. Sisson include Purdue University & Tiffany & Co..

Environmental degradation of engineering materials

Abstract: This book is the proceedings of the Third International Conference on Environmental Degradation of Engineering Materials. The conference was held at the Keller Conference Center of The Pennsylvania State University on April 13-15, 1987. The primary goal of the conference was to provide a forum for presentation, discussion, and publication of the ''State of the Art'' in understanding the adverse effects of various environments on the behavior and performance of engineering materials. The conference planning included a rather strong attempt to bring together a wide based diverse group of scientists, engineers and even academic types. Topics discussed include concrete, polymers, metals, ceramics and composites. The specific reasoning behind the selection of a wide range of topics was the hope that say investigators in the area of degradation of bridge decks might learn from investigators in hydrogen embrittlement and vice versa.

The effect of carbon content on the c/a ratio of as-quenched martensite in Fe-C alloys

Abstract: The as-quenched martensite crystal structure is widely accepted as body-centered tetragonal. The classical Honda & Nishiyama model, c/a = 1 + 0.045 wt%C, was obtained based only on the experimental results for steels containing more than 0.6 wt% of carbon. This model was used to predict that steels containing less than 0.6 wt% of carbon would follow the same relation. However, it was reported by Sherby that the steel with less than 0.6 wt% of carbon is body-centered cubic, and c/a ratio equals to 1. This debate is caused by highly overlapped martensite (002) and (200) peaks when the carbon content of steel is less than 0.6 wt%. In this paper, the martensite lattice parameters of the as-quenched steels with different carbon contents were measured using high-resolution X-ray diffractometer. Rietveld refinement was used to deconvolute overlapped martensite peaks. For the steel with less than 0.6 wt% of carbon, the structure is proved to be body-centered tetragonal. It was found that the relationship between c/a ratio and carbon content follows as c/a = 1 + 0.031 wt%C.

Environmental degradation of engineering materials in hydrogen

Abstract: This book is one volume of the proceedings of the second conference on Environmental Degradation of Engineering Materials held at Virginia Polytechnic Institute on September 21-23, 1981. Papers in this volume describe hydrogen uptake and transport by metals, hydrogen adsorption and evolution from metals and hydrogen embrittlement of metals. These papers represent about one third of the presentations at the conference and reflect the importance currently attached to the development of an understanding of hydrogen embrittlement processes. Thirty-nine papers have been abstracted and indexed for the Energy Data Base.

Microstructural characterization of thermal barrier coatings on high pressure turbine blades

Abstract: Thermal barrier coated high pressure turbine blades were characterized before and after the service by microstructural analysis and Cr3+ photostimulated luminescence piezo-spectroscopy. Thermal barrier coatings, in this study, consisted of electron beam physical vapor deposited yttria partially stabilized zirconia (YSZ; ZrO2–8 wt.% Y2O3), vapor-deposited aluminide bond coat and Ni-base superalloy. Compressive residual stress in thermally grown oxide, measured by Cr3+ photostimulated luminescence piezo-spectroscopy, was observed to be in the order of 2.5∼3.0 GPa and varied slightly as a function of substrate geometry. X-Ray diffraction and scanning electron microscopy equipped with energy dispersive X-ray spectroscopy were utilized to investigate the microstructural development of thermal barrier coatings. The as-deposited non-equilibrium tetragonal (t′) phase in the YSZ coatings was observed to decompose after the service, but the monoclinic (m) phase was only found in the YSZ coatings with concave substrate curvature on the pressure side of the HPT blade. Also, a significant sintering of ZrO2–8 wt.% Y2O3 coating after the service was observed in the microstructure. Localized spallation of YSZ occurred within the thermally grown oxide (mostly α-Al2O3) and within the ZrO2–8 wt.% Y2O3 coating for pressure and suction sides of the serviced high pressure turbine blade near the tip, respectively.

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Thermal Barrier Coatings for Gas-Turbine Engine Applications

Abstract: Hundreds of different types of coatings are used to protect a variety of structural engineering materials from corrosion, wear, and erosion, and to provide lubrication and thermal insulation. Of all these, thermal barrier coatings (TBCs) have the most complex structure and must operate in the most demanding high-temperature environment of aircraft and industrial gas-turbine engines. TBCs, which comprise metal and ceramic multilayers, insulate turbine and combustor engine components from the hot gas stream, and improve the durability and energy efficiency of these engines. Improvements in TBCs will require a better understanding of the complex changes in their structure and properties that occur under operating conditions that lead to their failure. The structure, properties, and failure mechanisms of TBCs are herein reviewed, together with a discussion of current limitations and future opportunities.