NSF Org:	CBET Division of Chemical, Bioengineering, Environmental, and Transport Systems
Recipient:	UNIVERSITY OF CONNECTICUT
Initial Amendment Date:	August 22, 2001
Latest Amendment Date:	August 22, 2001
Award Number:	0112822
Award Instrument:	Standard Grant
Program Manager:	Alfonso Ortega CBET  Division of Chemical, Bioengineering, Environmental, and Transport Systems ENG  Directorate for Engineering
Start Date:	September 1, 2001
End Date:	August 31, 2005 (Estimated)
Total Intended Award Amount:	$409,140.00
Total Awarded Amount to Date:	$409,140.00
Funds Obligated to Date:	FY 2001 = $409,140.00
History of Investigator:	Ranga Pitchumani (Principal Investigator) pitchu@vt.edu Luke Achenie (Co-Principal Investigator) Eugene Santos (Co-Principal Investigator)
Recipient Sponsored Research Office:	University of Connecticut 438 WHITNEY RD EXTENSION UNIT 1133 STORRS CT  US  06269-9018 (860)486-3622
Sponsor Congressional District:	02
Primary Place of Performance:	University of Connecticut 438 WHITNEY RD EXTENSION UNIT 1133 STORRS CT  US  06269-9018
Primary Place of Performance Congressional District:	02
Unique Entity Identifier (UEI):	WNTPS995QBM7
Parent UEI:
NSF Program(s):	SSA-Special Studies & Analysis, TTP-Thermal Transport Process, ITR SMALL GRANTS
Primary Program Source:	01000102DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):	0000, 1385, 1652, 1686, OTHR
Program Element Code(s):	138500, 140600, 168600
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.041

ABSTRACT

Advanced materials form the backbone of our everyday life, including the hardware that supports the information technology (IT) enterprise. Thermal manufacturing of these materials involves strongly coupled transport phenomena that occur at multiple temporal and spatial scales. Process simulation models, based on description of the governing physical phenomena, play an important role in guiding process understanding and development. However, their complete potential remains unrealized in practice, for two principal reasons. First, a fundamental gap exists between simulation capabilities and practice in that whereas practical processes are carried out amidst a cloud of impreciseness and uncertainty, the simulation models are deterministic in the way they treat the process variables. Secondly, process simulations are often computationally tedious owing to the need for a rigorous resolution of the physical phenomena at multiple scales. The computational demands are tremendously intensified when the ability to account for process uncertainty is embedded in the simulation framework, and further, when the simulation models are used in an optimization endeavor.

The research seeks to develop advanced computational methods aimed at addressing the foregoing challenges. A stochastic modeling framework will be developed for incorporating the effects of process uncertainties in the simulations. Towards addressing the challenge of enabling rapid and efficient computations, agent-based computing strategies in a heterogeneous environment and an innovative portfolio-based technique for large-scale optimization under uncertainty will be developed. The advanced computational methods will be applied to an optical fiber manufacturing process, which is an important process in the optical networking industry and typifies the complexities of the multiscale physical phenomena involved in general thermal manufacturing processes. The methodologies may be readily applied to other materials processing applications.

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