Assessment of silicone polymer composites for the trace extraction of herbicides : a tool for environmental forensics

Passive samplers are not only a versatile tool to integrate environmental concentrations of pollutants, but also to avoid the use of live sentinel organisms for environmental monitoring. This study introduced the use of magnetic silicone polymer composites (Fe-PDMS) as passive sampling media to pre-concentrate a wide range of analytes from environmental settings. The composite samplers were assessed for their accumulation properties by performing lab experiments with two model herbicides (Atrazine and Irgarol 1051) and evaluated for their uptake properties from environmental settings (waters and sediments). The Fe-PDMS composites showed good accumulation of herbicides and pesticides from both freshwater and saltwater settings and the accumulation mechanism was positively correlated with the log Kow value of individual analytes. Results from the studies show that these composites could be easily used for a wide number of applications such as monitoring, cleanup, and/or bioaccumulation modeling, and as a non-intrusive and nondestructive monitoring tool for environmental forensic purposes.

ASIC microcontroller design of a radiation monitoring system using VHDL modeling and FPGA implementation

Three new technologies have been brought together to develop a miniaturized radiation monitoring system. The research involved (1) Investigation a new HgI$\sb2$ detector. (2) VHDL modeling. (3) FPGA implementation. (4) In-circuit Verification. The packages used included an EG&G's crystal(HgI$\sb2$) manufactured at zero gravity, the Viewlogic's VHDL and Synthesis, Xilinx's technology library, its FPGA implementation tool, and a high density device (XC4003A). The results show: (1) Reduced cycle-time between Design and Hardware implementation; (2) Unlimited Re-design and implementation using the static RAM technology; (3) Customer based design, verification, and system construction; (4) Well suited for intelligent systems. These advantages excelled conventional chip design technologies and methods in easiness, short cycle time, and price in medium sized VLSI applications. It is also expected that the density of these devices will improve radically in the near future. ^

Inspection of parts with complex geometry and welds with structural health monitoring techniques

Structural Health Monitoring (SHM) systems were developed to evaluate the integrity of a system during operation, and to quickly identify the maintenance problems. They will be used in future aerospace vehicles to improve safety, reduce cost and minimize the maintenance time of a system. Many SHM systems were already developed to evaluate the integrity of plates and used in marine structures. Their implementation in manufacturing processes is still expected. The application of SHM methods for complex geometries and welds are two important challenges in this area of research. This research work started by studying the characteristics of piezoelectric actuators, and a small energy harvester was designed. The output voltages at different frequencies of vibration were acquired to determine the nonlinear characteristics of the piezoelectric stripe actuators. The frequency response was evaluated experimentally. AA battery size energy harvesting devices were developed by using these actuators. When the round and square cross section devices were excited at 50 Hz frequency, they generated 16 V and 25 V respectively. The Surface Response to Excitation (SuRE) and Lamb wave methods were used to estimate the condition of parts with complex geometries. Cutting tools and welded plates were considered. Both approaches used piezoelectric elements that were attached to the surfaces of considered parts. The variation of the magnitude of the frequency response was evaluated when the SuRE method was used. The sum of the square of the differences was calculated. The envelope of the received signal was used for the analysis of wave propagation. Bi-orthogonal wavelet (Binlet) analysis was also used for the evaluation of the data obtained during Lamb wave technique. Both the Lamb wave and SuRE approaches along with the three methods for data analysis worked effectively to detect increasing tool wear. Similarly, they detected defects on the plate, on the weld, and on a separate plate without any sensor as long as it was welded to the test plate.

Tool cutting force modeling and wear estimation of micro -end-milling operations

The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. ^ The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc. ^

Tool cutting force modeling and wear estimation of micro-end-milling operations

The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc.