Analysis of Hybrid Laminated Composite Plates

Hybrid laminated composite plates are analyzed using a nine‐noded isoparametric plate finite element based on Mindlin's theory. The shear flexibility is included in the finite element modeling. Shear flexibility is of importance, especially when different materials are used in the laminate design. Hybrid laminates consisting of graphite∕epoxy and kevlar∕epoxy plies are considered for illustration. The study indicates that hybrid laminates provide stiffnesses that are intermediate to the values obtained for single‐material laminates. The minimum deflection is achieved at different fiber orientation for thick plates compared to thin plates. The deflection behavior of hybrid laminates seems to be less affected by outer‐ply stiffness in the case of thick plates. Thick plates show less variation in the first natural frequency with fiber orientation but hybridization changes the natural frequency considerably. The first natural frequency of the hybrid laminate can be made higher than the stiffer single‐material laminate.     

Relative positioning for team robot navigation

The research presented in this paper approaches the issue of robot team navigation using relative positioning. With this approach each robot is equipped with sensors that allow it to independently estimate the relative direction of an assigned leader. Acoustic sensor systems are used and were seen to work very effectively in environments where datum relative positioning systems (such as GPS or acoustic transponders) are typically ineffective. While acoustic sensors provide distinct advantages, the variability of the acoustic environment presents significant control challenges. To address this challenge, directional control of the robot was accomplished with a feed forward neural network trained using a genetic algorithm, and a new approach to training using recent memories was successfully implemented. The design of this controller is presented and its performance is compared with more traditional classic logic and behavior controllers. Patrick McDowell received his bachelor's degree in Computer Science in 1984 from the University of Idaho. He spent the next 15 years working as a computer scientist for a small defense contractor where he specialized in real time data acquisition, application development, and image processing. In 1999 he received his master's degree in computer science from the University of Southern Mississippi. In 2000 he began work at the Naval Research Lab where he has focused on application of machine learning techniques to autonomous underwater navigation. In 2005 he received his Ph.D. in Computer Science from Louisiana State University. His research interests include legged robotics, machine learning, and artificial intelligence. In Fall of 2006 he joined Southeastern Louisiana University as an assistant professor of Computer Science. Brian S. Bourgeois received his Ph.D. in Electrical Engineering from Tulane University located in New Orleans, LA in 1991. Since then he has worked at the Stennis Space Center, MS detachment of the Naval Research Laboratory. He has worked on research projects spanning an array of technologies including airborne survey sytems, acoustic backscattering, bathymetry and imaging sonar systems, the ORCA unmanned underwater vehicle and the development of an autonomous survey system for hydrographic survey ships. He is presently the head of the Position, Navigation and Timing team at NRL with research interests including underwater positioning and communications and autonomous navigation. Ms. McDowell received her M.S. in Applied Physics in 2002 from the University or New Orleans. She is presently a candidate for a Ph. D. in Engineering and Applied Science. She joined the Naval Research Laboratory in 1991 as a research engineer and has spent most of that time working in experimental and theoretical acoustic modeling. Ms. McDowell's specific research interest lie in the areas of sonar performance analysis. Dr. S. S. Iyengar is the Chairman and Roy Paul Daniels Chaired Professor of Computer Science at Louisiana State University and is also Satish Dhawan Chaired Professor at Indian Institute of Science. He has been involved with research in high-performance algorithms, data structures, sensor fusion, data mining, and intelligent systems since receiving his Ph.D. degree (1974) and his M.S. from the Indian Institute of Science (1970). He has been a consultant to several industrial and government organizations (JPL, NASA etc.). In 1999, Professor Iyengar won the most prestigious research award titled Distinguished Research Award and a university medal for his research contributions in optimal algorithms for sensor fusion/image processing. Dr. Jianhua Chen received her Ph.D. in computer science in 1988 from Jilin University, Chang Chun, China. In August 1988, She joined the Computer Science Department of Louisiana State University, Baton Rouge, USA, where she is currently an associate professor. Dr. Chen's research interests include Machine Learning and Data Mining, Fuzzy Sets and Systems, Knowledge Representation and Reasoning.     

Global outlook on nutrition and the environment: meeting the challenges of the next millennium

As we enter the new millennium, nearly 800 million of the World's population will remain chronically malnourished. Nearly 200 million children are moderately to severely underweight, while 70 million are severely malnourished. And those who are yet to be born will be faced with the same set of circumstances that predispose them to malnutrition and its consequences. Eradication of nutritional deficiencies among women and children on a global scale are needed to ensure improved quality of life for the next generation of citizens. Primary deficiencies in vitamin A, iron, iodine, calcium, folic acid and trace elements such as zinc are compounded by pollutants caused by human activity. Environmental lead, arsenic, mercury, and other heavy metals that enter the food chain can seriously deplete body stores of iron, vitamin C and other essential nutrients leading to decreased immune defenses, intrauterine growth retardation, impaired psycho-social faculties and other disabilities associated with malnutrition. Increased susceptibilities to communicable diseases, and those provoked by water or insect borne vectors are additional risks encountered by malnourished individuals. Migration of populations from rural to urban centers and the expansion of major metropolitan areas have had a significant and adverse impact on the quality of life of these citizens. In the next 20 years most of the growth in urban populations will be in Asia and Latin America. Urbanization and the resultant burden on limited national resources is a major contributory factor to malnutrition. There are many other lifestyle-associated disabilities such as use of tobacco (cancer) and alcoholism that require active intervention. Within the family unit, socioeconomic factors and the status of women (literacy, economic independence) are major determinants of the quality of life. In the coming century, the World will have to meet these challenges by careful planning and international cooperation.     

Test Wrapper and Test Access Mechanism Co-Optimization for System-on-Chip

Test access mechanisms (TAMs) and test wrappers are integral parts of a system-on-chip (SOC) test architecture. Prior research has concentrated on only one aspect of the TAM/wrapper design problem at a time, i.e., either optimizing the TAMs for a set of pre-designed wrappers, or optimizing the wrapper for a given TAM width. In this paper, we address a more general problem, that of carrying out TAM design and wrapper optimization in conjunction. We present an efficient algorithm to construct wrappers that reduce the testing time for cores. Our wrapper design algorithm improves on earlier approaches by also reducing the TAM width required to achieve these lower testing times. We present new mathematical models for TAM optimization that use the core testing time values calculated by our wrapper design algorithm. We further present a new enumerative method for TAM optimization that reduces execution time significantly when the number of TAMs being designed is small. Experimental results are presented for an academic SOC as well as an industrial SOC.     

Non-linear bending of antisymmetric cross-ply plates

The bending of antisymmetric cross-ply plates, based on Von-Karman plate theory, is investigated in this paper with one term approximations for the in-plane and transverse displacements. Rayleigh-Ritz solutions are presented for the non-linear response of cross-ply laminates with various modular and aspect ratios and subjected to sinusoidal transverse loading.     

X-ray studies on the thermal expansion of tellurium dioxide

Using a Unicam 19 cm high temperature powder camera, the precision lattice parameters of tellurium dioxide have been determined at different temperatures in the range 30 to 461 °C. Using this data, the coefficients of thermal expansion, and parallel and perpendicular to the principal axis respectively, have been evaluated. The temperature dependence of the coefficients of thermal expansion is represented by the following equations: =29.673×10^–6+1.552sx10^–8 T+1.069sx10^–10 T ² =9.875sx10^–6–5.440sx10^–9 T+4.572sx 10^–12 T² HereT is the temperature in °C. The thermal expansion of tellurium dioxide has been explained in terms of the interionic distances.     

A low delay 16 kb/s speech coder

A code tree generated by a stochastically populated innovations tree with a backward adaptive gain and backward adaptive synthesis filters is considered. The synthesis configuration uses a cascade of two all-pole filters: a pitch (long time delay) filter followed by a formant (short time delay) filter. Both filters are updated using backward adaptation. The formant predictor is updated using an adaptive lattice algorithm. The multipath (M, L) search algorithm is used to encode the speech. A frequency-weighted error measure is used to reduce the perceptual loudness of the quantization noise. The addition of the pitch filter gives 2-10-dB increase in segSNR (segmental signal-to-noise ratio) in the voiced segments. Subjective testing has shown that the coder attains a subjective quality equivalent to 7 b/sample log-PCM (pulse code modulation) with an encoding delay of eight samples (1 ms with an 8-kHz sampling rate)