A method to study the history of a double oxide film defect in liquid aluminum alloys

Entrained double oxide films have been held responsible for reductions in mechanical properties in aluminum casting alloys. However, their behavior in the liquid metal, once formed, has not been studied directly. It has been proposed that the atmosphere entrapped in the double oxide film defect will continue to react with the liquid metal surrounding it, perhaps leading to its elimination as a significant defect. A silicon-nitride rod with a hole in one end was plunged into liquid aluminum to hold a known volume of air in contact with the liquid metal at a constant temperature. The change in the air volume with time was recorded by real-time X-ray radiography to determine the reaction rates of the trapped atmosphere with the liquid aluminum, creating a model for the behavior of an entrained double oxide film defect. The results from this experiment showed that first oxygen, and then nitrogen, was consumed by the aluminum alloy, to form aluminum oxide and aluminum nitride, respectively. The effect of adding different elements to the liquid aluminum and the effect of different hydrogen contents were also studied. This article is based on a presentation made in the John Campbell Symposium on Shape Casting, held during the TMS Annual Meeting, February 13–17, 2005, in San Francisco, CA.     

A Platform-Based Taxonomy for ESL Design

This article presents a taxonomy for ESL tools and methodologies that combines UC Berkeley's platform-based design terminologies with Dan Gajski's Y-chart work. This is timely and necessary because in the ESL world we seem to be building tools without first establishing an appropriate design flow or methodology, thereby creating a lot of confusion. This taxonomy can help stem the tide of confusion.     

The effects of deep zones on wetland nitrogen processing.

Twelve research wetlands were operated under varying conditions at a site west of the city of Phoenix. These were constructed as a triplicated design, with zero, one, two and three internal deep zones, all containing an inlet distribution and an outlet collection deep zone, together comprising 12.5-35% of the wetland areas. The water supply was partially nitrified effluent from a city wastewater treatment plant. Total nitrogen was reduced by about 50%, from inflow concentrations between 6 and 8 mg/L. Speciation of the inflow was approximately 25% organic nitrogen, 25% ammonium nitrogen and 50% nitrate nitrogen. Typical outflow concentrations were about 1.2 mg/L organic, 0.5 mg/L ammonium and 0.0-2.5 mg/L nitrate. Rate constants for total nitrogen were 15-20 m/year at 20 degrees C, and 20-30 m/year for nitrate, which agree well with other project reports. Temperature factors averaged 1.100 for total nitrogen, and 1.184 for nitrate. There were no differences in the internal hydraulics with deep zone numbers. Deep zone numbers in the wetlands did not affect nitrogen treatment performance. No differences with deep zone numbers were found for temperature, dissolved oxygen, pH, or nitrogen removals or rate constants. In conjunction with other reported results, there appears to be no large treatment benefit or detriment of incorporating internal deep zones in free water surface wetlands.     

A systematic approach for product families formation in Reconfigurable Manufacturing Systems

The aim of this work is to establish a methodology for an effective working of Reconfigurable Manufacturing Systems (RMSs). These systems are the next step in manufacturing, allowing the production of any quantity of highly customised and complex products together with the benefits of mass production. In RMSs, products are grouped into families, each of which requires a system configuration. The system is configured to produce the first family of products. Once it is finished, the system is reconfigured in order to produce the second family, and so forth. Therefore, the effectiveness of a RMS depends on the formation of the best set of product families. Therefore, a methodology for grouping products into families, which takes into account the requirements of products in RMSs, is an issue of core importance. These requirements are modularity, commonality, compatibility, reusability, and product demand. The methodology starts by calculating, for each product requirement, a matrix that summarises the similarity between pairs of products. Then, through the use of the AHP methodology, a unique matrix that comprises the similarity values between products is obtained. The Average Linkage Clustering algorithm is applied to this matrix in order to obtain a dendogram that shows the diverse sets of product families that may be formed.     

Gigabit pulse position bistability in semiconductor lasers

The paper briefly reviews the major forms of optical bistability in active optical devices compatible for use in gigabit optical communication systems, and reports an entirely new optical bistability for the first time. Unlike previous devices, the two bistable states of the optical device are each a series of picosecond optical pulses at 1 GHz or greater repetition rates, and are distinguished by a half period temporal shift between their temporal positions in relation to a clock pulse. The bistable device is based on a gain switched semiconductor laser. Theoretical studies suggest 100-ps switching speeds might be achieved, and experimental results are reported indicating optically triggered switching times of 500 ps.     

FACTORS AFFECTING THE HARDNESS OF FAT ON SIDES OF CHILLED BEEF

The influence of some factors on the hardness of subcutaneous fat on sides of chilled beef as measured by the average force resisting movement of a cutting pin (Ff) was investigated. Values of Ff determined at a fat temperature of 10°C on grass-fed animals denied water 24 h preslaughter were not significantly influenced by moisture content (5-11%) or fat depth (2-27 mm). There was a quadratic relationship (P<0.001) between the age of animals at slaughter (31-141 months) and Ff, and a linear one (P<0.001) between saturated fatty acid content (35-50%) and Ff. Values of Ffat a fat temperature of 5°C were not significantly related to moisture content (1-22%) but there was a linear relationship (P<0.01) with fat depth (5-13 mm). This had a common slope for the three feeding patterns: (1) grass-fed animals denied water 24 h preslaughter; (2) grass-fed animals given access to water 24 h preslaughter, and; (3) lot-fed animals given access to water 24 h preslaughter.     

Inverse controller design for fuzzy interval systems

This paper aims at designing and analyzing an inverse controller for stable inversible (minimum phase) fuzzy interval linear and/or multilinear systems. The controller is designed from the fuzzy interval ranges of the system parameters using an /spl alpha/-cut methodology. Indeed, for a given /spl alpha/-cut of the fuzzy system parameters representing an uncertainty level, the control objective can be viewed as maintaining the system output within a tolerance envelope, around the exact trajectory, specified by the degree of preference /spl alpha/ on the fuzzy trajectory. The stability is ensured in the way that the controller restricts the system output divergence within the tolerance envelope. The validity of the proposed method is illustrated by simulation examples.     

Modeling the tensile properties in β-processed α/β Ti alloys

The development of a set of computational tools that permit microstructurally based predictions for the tensile properties of commercially important titanium alloys, such as Ti-6Al-4V, is a valuable step toward the accelerated maturation of materials. This paper will discuss the development of neural network models based on a Bayesian framework to predict the yield and ultimate tensile strengths of Ti-6Al-4V at room temperature. The development of such rules-based model requires the population of extensive databases, which in the present case are microstructurally based. The steps involved in database development include producing controlled variations of the microstructure using novel approaches to heat treatments, the use of standardized stereology protocols to characterize and quantify microstructural features rapidly, and mechanical testing of the heat-treated specimens. These databases have been used to train and test neural network models for prediction of tensile properties. In addition, these models have been used to identify the influence of individual microstructural features on the tensile properties, consequently guiding the efforts toward development of more robust mechanistically based models. Based on the neural network model, it is possible to investigate the influence of individual microstructural features on the tensile properties, and in certain cases these dependencies can point toward unrecognized phenomena. For example, the apparently unexpected trend of increase in tensile strength with increasing prior β-grain size has led to the determination of the pronounced role of the basketweave microstructure in strengthening these alloys, especially in case of larger prior β grains. This article is based on a presentation made in the symposium “Computational Aspects of Mechanical Properties of Materials,” which occurred at the 2005 TMS Annual Meeting, February 13–17, 2005, in San Francisco, CA, under the auspices of the MPMD-Computational Materials Science & Engineering (Jt. ASM-MSCTS) Committee.