Design of a dynamic e-commerce system with engineering applications

The primary purpose of this thesis was to design and develop a prototype e-commerce system where dynamic parameters are included in the decision-making process and execution of an online transaction. The system developed and implemented takes into account previous usage history, priority and associated engineering capabilities. The system was developed using three-tiered client server architecture. The interface was the Internet browser. The middle tiered web server was implemented using Active Server Pages, which form a link between the client system and other servers. A relational database management system formed the data component of the three-tiered architecture. It includes a capability for data warehousing which extracts needed information from the stored data of the customers as well as their orders. The system organizes and analyzes the data that is generated during a transaction to formulate a client's behavior model during and after a transaction. This is used for making decisions like pricing, order rescheduling during a client's forthcoming transaction. The system helps among other things to bring about predictability to a transaction execution process, which could be highly desirable in the current competitive scenario.

Identification and characterization of interfering products in fire debris analysis

The purpose of this research was to study interfering products in fire debris analysis, including their identification and characterization. Different substrates were classified, burned, extracted and analyzed in order to identify all the interfering products that they may release. It has been shown that these products come from three different sources: substrate background products, pyrolysis products and possibly combustion products. Different parameters in the creation of these products were evaluated such as the extinguishment process as well as the weathering of the sample prior to the analysis. It has been shown that the presence of these products is not always constant and thus, makes it difficult to extrapolate data to similar cases. Furthermore, some of these products are similar to the ones found in ignitable liquids. Finally, it shows one more time how important it is to collect and analyze control samples in fire debris analysis. ^

Physical dynamic simulation of shipboard power system components in a distributed computational environment

Shipboard power systems have different characteristics than the utility power systems. In the Shipboard power system it is crucial that the systems and equipment work at their peak performance levels. One of the most demanding aspects for simulations of the Shipboard Power Systems is to connect the device under test to a real-time simulated dynamic equivalent and in an environment with actual hardware in the Loop (HIL). The real time simulations can be achieved by using multi-distributed modeling concept, in which the global system model is distributed over several processors through a communication link. The advantage of this approach is that it permits the gradual change from pure simulation to actual application. In order to perform system studies in such an environment physical phase variable models of different components of the shipboard power system were developed using operational parameters obtained from finite element (FE) analysis. These models were developed for two types of studies low and high frequency studies. Low frequency studies are used to examine the shipboard power systems behavior under load switching, and faults. High-frequency studies were used to predict abnormal conditions due to overvoltage, and components harmonic behavior. Different experiments were conducted to validate the developed models. The Simulation and experiment results show excellent agreement. The shipboard power systems components behavior under internal faults was investigated using FE analysis. This developed technique is very curial in the Shipboard power systems faults detection due to the lack of comprehensive fault test databases. A wavelet based methodology for feature extraction of the shipboard power systems current signals was developed for harmonic and fault diagnosis studies. This modeling methodology can be utilized to evaluate and predicate the NPS components future behavior in the design stage which will reduce the development cycles, cut overall cost, prevent failures, and test each subsystem exhaustively before integrating it into the system.

Improved dynamic headspace sampling and detection using capillary microextraction of volatiles coupled to gas chromatography mass spectrometry

Sampling and preconcentration techniques play a critical role in headspace analysis in analytical chemistry. My dissertation presents a novel sampling design, capillary microextraction of volatiles (CMV), that improves the preconcentration of volatiles and semivolatiles in a headspace with high throughput, near quantitative analysis, high recovery and unambiguous identification of compounds when coupled to mass spectrometry. The CMV devices use sol-gel polydimethylsiloxane (PDMS) coated microglass fibers as the sampling/preconcentration sorbent when these fibers are stacked into open-ended capillary tubes. The design allows for dynamic headspace sampling by connecting the device to a hand-held vacuum pump. The inexpensive device can be fitted into a thermal desorption probe for thermal desorption of the extracted volatile compounds into a gas chromatography-mass spectrometer (GC-MS). The performance of the CMV devices was compared with two other existing preconcentration techniques, solid phase microextraction (SPME) and planar solid phase microextraction (PSPME). Compared to SPME fibers, the CMV devices have an improved surface area and phase volume of 5000 times and 80 times, respectively. One (1) minute dynamic CMV air sampling resulted in similar performance as a 30 min static extraction using a SPME fiber. The PSPME devices have been fashioned to easily interface with ion mobility spectrometers (IMS) for explosives or drugs detection. The CMV devices are shown to offer dynamic sampling and can now be coupled to COTS GC-MS instruments. Several compound classes representing explosives have been analyzed with minimum breakthrough even after a 60 min. sampling time. The extracted volatile compounds were retained in the CMV devices when preserved in aluminum foils after sampling. Finally, the CMV sampling device were used for several different headspace profiling applications which involved sampling a shipping facility, six illicit drugs, seven military explosives and eighteen different bacteria strains. Successful detection of the target analytes at ng levels of the target signature volatile compounds in these applications suggests that the CMV devices can provide high throughput qualitative and quantitative analysis with high recovery and unambiguous identification of analytes.

Large-Scale Testing to Study the Effects of Critical Parameters on the Aerodynamic Behavior of Long Span Bridges

Long-span bridges are flexible and therefore are sensitive to wind induced effects. One way to improve the stability of long span bridges against flutter is to use cross-sections that involve twin side-by-side decks. However, this can amplify responses due to vortex induced oscillations. Wind tunnel testing is a well-established practice to evaluate the stability of bridges against wind loads. In order to study the response of the prototype in laboratory, dynamic similarity requirements should be satisfied. One of the parameters that is normally violated in wind tunnel testing is Reynolds number. In this dissertation, the effects of Reynolds number on the aerodynamics of a double deck bridge were evaluated by measuring fluctuating forces on a motionless sectional model of a bridge at different wind speeds representing different Reynolds regimes. Also, the efficacy of vortex mitigation devices was evaluated at different Reynolds number regimes. One other parameter that is frequently ignored in wind tunnel studies is the correct simulation of turbulence characteristics. Due to the difficulties in simulating flow with large turbulence length scale on a sectional model, wind tunnel tests are often performed in smooth flow as a conservative approach. The validity of simplifying assumptions in calculation of buffeting loads, as the direct impact of turbulence, needs to be verified for twin deck bridges. The effects of turbulence characteristics were investigated by testing sectional models of a twin deck bridge under two different turbulent flow conditions. Not only the flow properties play an important role on the aerodynamic response of the bridge, but also the geometry of the cross section shape is expected to have significant effects. In this dissertation, the effects of deck details, such as width of the gap between the twin decks, and traffic barriers on the aerodynamic characteristics of a twin deck bridge were investigated, particularly on the vortex shedding forces with the aim of clarifying how these shape details can alter the wind induced responses. Finally, a summary of the issues that are involved in designing a dynamic test rig for high Reynolds number tests is given, using the studied cross section as an example.

Investigation of particle identification methods for the analysis of the photoproduction of neutral kaons on a liquid deuterium target

The Photoproduction of neutral kaons off a deuteron target has been investigated at the Tohoku University Laboratory of Nuclear Science. The PID methods investigated incorporated a combination of momentum, velocity (β=v/c), and energy deposition per unit length (dE/dx) measurements. The analysis demonstrates that energy deposition and time of flight are exceedingly useful. A higher signal to background ratio was achieved for hard cuts in combination. A probabilistic likelihood estimation approach (LE) as a method for PID was also explored. The probability of a particle being correctly identified by this LE method and the preliminary results denote the need for highly precise limitations on the distributions from which the parameters would be extracted. It was confirmed that these PID are applicable approaches to properly identify pions for the analysis of this experiment. However, the background evident in the mass spectra points to the need for a higher level of proton identification.

Physical dynamic simulation of shipboard power system components in a distributed computational environment

Shipboard power systems have different characteristics than the utility power systems. In the Shipboard power system it is crucial that the systems and equipment work at their peak performance levels. One of the most demanding aspects for simulations of the Shipboard Power Systems is to connect the device under test to a real-time simulated dynamic equivalent and in an environment with actual hardware in the Loop (HIL). The real time simulations can be achieved by using multi-distributed modeling concept, in which the global system model is distributed over several processors through a communication link. The advantage of this approach is that it permits the gradual change from pure simulation to actual application. In order to perform system studies in such an environment physical phase variable models of different components of the shipboard power system were developed using operational parameters obtained from finite element (FE) analysis. These models were developed for two types of studies low and high frequency studies. Low frequency studies are used to examine the shipboard power systems behavior under load switching, and faults. High-frequency studies were used to predict abnormal conditions due to overvoltage, and components harmonic behavior. Different experiments were conducted to validate the developed models. The Simulation and experiment results show excellent agreement. The shipboard power systems components behavior under internal faults was investigated using FE analysis. This developed technique is very curial in the Shipboard power systems faults detection due to the lack of comprehensive fault test databases. A wavelet based methodology for feature extraction of the shipboard power systems current signals was developed for harmonic and fault diagnosis studies. This modeling methodology can be utilized to evaluate and predicate the NPS components future behavior in the design stage which will reduce the development cycles, cut overall cost, prevent failures, and test each subsystem exhaustively before integrating it into the system.

Improved Dynamic Headspace Sampling and Detection using Capillary Microextraction of Volatiles Coupled to Gas Chromatography Mass Spectrometry

Sampling and preconcentration techniques play a critical role in headspace analysis in analytical chemistry. My dissertation presents a novel sampling design, capillary microextraction of volatiles (CMV), that improves the preconcentration of volatiles and semivolatiles in a headspace with high throughput, near quantitative analysis, high recovery and unambiguous identification of compounds when coupled to mass spectrometry. The CMV devices use sol-gel polydimethylsiloxane (PDMS) coated microglass fibers as the sampling/preconcentration sorbent when these fibers are stacked into open-ended capillary tubes. The design allows for dynamic headspace sampling by connecting the device to a hand-held vacuum pump. The inexpensive device can be fitted into a thermal desorption probe for thermal desorption of the extracted volatile compounds into a gas chromatography-mass spectrometer (GC-MS). The performance of the CMV devices was compared with two other existing preconcentration techniques, solid phase microextraction (SPME) and planar solid phase microextraction (PSPME). Compared to SPME fibers, the CMV devices have an improved surface area and phase volume of 5000 times and 80 times, respectively. One (1) minute dynamic CMV air sampling resulted in similar performance as a 30 min static extraction using a SPME fiber. The PSPME devices have been fashioned to easily interface with ion mobility spectrometers (IMS) for explosives or drugs detection. The CMV devices are shown to offer dynamic sampling and can now be coupled to COTS GC-MS instruments. Several compound classes representing explosives have been analyzed with minimum breakthrough even after a 60 min. sampling time. The extracted volatile compounds were retained in the CMV devices when preserved in aluminum foils after sampling. Finally, the CMV sampling device were used for several different headspace profiling applications which involved sampling a shipping facility, six illicit drugs, seven military explosives and eighteen different bacteria strains. Successful detection of the target analytes at ng levels of the target signature volatile compounds in these applications suggests that the CMV devices can provide high throughput qualitative and quantitative analysis with high recovery and unambiguous identification of analytes.