Research
Ongoing Projects
1. Catalytic Reforming of Heavy Hydrocarbons for the Production of Hydrogen
(funded by NASA Glenn Research Center (NCC-3-1037) under HU Aeropropulsion Center): This topic is of interest to NASA and the military. Fuel cell use is a viable alternative for applications in ground and air transportation, and power generation. The fuel of choice for fuel cells, hydrogen, can be supplied from a distribution network or, it may be produced on board for transportation applications.
2. Introduction of Nanotechnology to Undergraduate Engineering and Science Education (funded by NSF-NUE (EEC-0532472)): Although the scientific research on nanoscale phenomena has reached explosive proportions and produced the ability to measure, manipulate and organize matter at the atomic and molecular level, the conversion of nanoscience into nanotechnology is just beginning. The key to success in transforming science into useful technology is the availability of engineers and technicians prepared to work effectively in the field of nanotechnology. Contribution of this project to undergraduate education is mainly through an elective multidisciplinary and modular nanotechnology course in the senior year; the course modules and laboratory modules on nanoscience and nanotechnology in various existing undergraduate courses in the chemical engineering, physics and chemistry curricula; involvement of undergraduate students in nanotechnology research; and a seminar series.
3. Eastern Seaboard Intermodal Transportation Applications Center (funded by US Department of Transportation): to determine an air quality model for selected sections of heavily used interstates through the Hampton Roads area, and choose an appropriate method for pollution monitoring. Some of the interstate sections that are close to railway lines and shipping lanes will be monitored to study the impact of intermodal transportation on pollutant emissions.
4. Nonlinear Dynamics:
- Digital communication applications are an integral part of modern day society that has accelerated with the growth of wireless telephone technology. A problem of interest in such systems is that of detecting or accessing synchronization levels of signals (time series) arising from divergent sources where the primarily focus has centered on the statistical characterization of binary signals that maybe carrying encoded data. The Hamming distance metric has been used successfully in a variety of applications ranging from developing built-in-error code correcting device for commercial and military communication systems and in personal (iris) discrimination applications. In the present context it is used as a quantitative metric for accessing signals (time series) synchronization levels and performing statistical inferences about information reliability.
- With regard to inducing synchronization among a network of dynamic systems, two basic problems exist. The first one centers on identifying suitable control variables. The second problem centers on inducing synchronization via a minimum energy expenditure of the control variables. The current research is focuses on an investigation of the nature or type of synchronization established among a network of functional differential equations and evaluating the robustness of coupling arrangement to sporadic stochastic noise.
- There is also a focus on detection of the changeover or switch point associated with time series that undergo an abrupt change in character. The aim of this work has been to devise robust statistical metrics that accurately and quickly detect a change in the inherent nature of a time series. Such work has broad applications in medicine, process control, electrical power system design, terrorism detection and communications. The present approach employs an adaptive control fitting technique that provides statistical based parameter estimates for experimental time series where the underlying models are not known but must be coupled /synchronized dynamically in the present of stochastic noise that corrupts both time series.
- This research involves a statistical investigation of wavelet methods for analyzing data streams arising from chaotic sources. Currently extensive efforts are being directed toward devising detection algorithms that can distinguish between chaotic and random time series (signals) or detect subtle changes in a chaotic data stream. Such detection algorithms are used for image recognition, speech recognition and diagnostic detection. The focus of this work is to develop appropriate statistical metrics for such data streams as well as provide nonparametric estimates of population profiles derived fromdeterministic models that mimic random/stochastic processes.
- This effort is concern with developing several statistical metrics for assessing nonlinear time series features, a problem of general interest for complexity measurements of time series. This approach is based on using a metric that is a weighted linear combination of an order pattern statistic and a traditional distance based norm. Similar metrics have been used in the medical profession to assess brain and heart data patterns and to distinguish healthy subjects from sick ones.
5. Other research interests:
- Fischer-Tropsch synthesis for production of liquid fuels from natural gas, coal gas and syngas obtained from waste and biological feedstocks
- Development of solid materials for onboard hydrogen storage
- Simultaneous removal of oxides of nitrogen and sulfur from power plant gases
- Catalytic NO dissociation
- Catalytic wet air oxidation for waste water cleanup