Precision machining of an aluminum alloy piston reinforced with a cast iron insert

Bimetallic pistons consisting of aluminum alloy reinforced with a cast iron (CI) insert are used to reduce the weight and improve the wear resistance of pistons. A major problem with machining such bimetallic pistons is producing the desired shape with minimal cutting forces and without damaging the bonding registry. The objective of this paper is to determine the optimal cutting parameters (cutting speed, feed, and depth of cut) for turning bimetallic pistons. When machining, we wish to obtain optimal values of the cutting forces and a better surface integrity while maintaining the required surface finish. Experiments were conducted following Taguchi’s parameter design approach using a cubic boron nitride tool for the machining. The results indicate that the process parameters affected the mean and variance of the cutting force at the Al-CI interface of the piston. The Al-CI interface was examined using an ultrasonic piston bond tester after machining to assure the bond quality. The surface roughness of the components was measured with a surface roughness tester. A mathematical model was developed using the Systat 12.0 software package to establish the relationship between the input quantities (speed, feed, and depth of cut) and the output data (cutting force). The output data of the mathematical model were compared with the experimental results. The results from the Taguchi robust design concept were compared with the results obtained from a nonconventional Genetic Algorithm optimization technique.     

Revealing the hidden structure of physiological states during metacognitive monitoring in collaborative learning

Using hidden Markov models (HMM), the current study looked at how learners' metacognitive monitoring is related to their physiological reactivity in the context of collaborative learning. The participants (N = 12, age 16–17 years, three females and nine males) in the study were high school students enrolled in an advanced physics course. The results show that during collaborative learning, the students engaged in monitoring in each self-regulated learning phase such as task understanding, planning and goal setting, task enactment, adaptation and reflection. The results of the HMM indicated that the learners' physiological reactivity was low when monitoring occurred. The associations between the states based on the HMM provide insights not only into how learners engage in metacognitive monitoring but also about their level of physiological reactivity in each state. In conclusion, exploring aspects of metacognitive monitoring in collaborative learning can be done with the help of physiological reactions.     

Delay and reward choice in ADHD: An experimental test of the role of delay aversion.

Children with attention deficit/hyperactivity disorder (ADHD) choose smaller sooner (SS) over larger later (LL) rewards more than controls. Here we assess the contributions of impulsive drive for immediate rewards (IDIR) and delay aversion (DAv) to this pattern. We also explore the characteristics of, and the degree of familiality in, ADHD SS responders. We had 360 ADHD probands; 349 siblings and 112 controls (aged between 6 to 17 years) chose between SS (1 point after 2 s) and LL reward (2 points after 30 s) outcomes on the Maudsley Index of Delay Aversion (Kuntsi, Oosterlaan, & Stevenson, 2001): Under one condition SS choice led to less overall trial delay under another it did not. ADHD participants chose SS more than controls under both conditions. This effect was larger when SS choice reduced trial delay. ADHD SS responders were younger, had lower IQ, more conduct disorder and had siblings who were more likely to be SS responders themselves. The results support a dual component model in which both IDIR and DAv contribute to SS choice in ADHD. SS choice may be a marker of an ADHD motivational subtype. (PsycINFO Database Record (c) 2010 APA, all rights reserved)