Process engineering is the branch of chemical engineering that addresses the design, synthesis and operation of chemical or manufacturing processes in which raw materials are converted into products. Chemical engineers develop new processes or modify existing ones in order to optimize facilities; reduce costs or maximize profit; improve operations with respect to flexibility, reliability, energy efficiency and safety; and ensure quality control and address environmental impact. These goals are achieved by modeling and systematically analyzing industrial processes. Process engineering research at Princeton includes projects to design new power plants; computational approaches using novel mixed-integer nonlinear optimization and deterministic global optimization frameworks where discrete and continuous decisions are modeled explicitly for process design, synthesis, scheduling and planning applications; and efforts to develop a fundamental understanding of the time-dependent behavior of phenomena such as instabilities and oscillations in the dynamics of chemical reactors, as well as transitions to turbulence and pattern formation in fluid flow.
Providing energy for the world’s population in an efficient and environmentally responsible manner is a major challenge to the world’s population for the 21st century. Chemical Engineering is at the core of developing energy sources including: improved petroleum refining, production and refining of biofuels, coal gasification and clean coal technology, and hydrogen energy technologies including fuel cells. Paralleling the efforts to develop new energy sources are the technologies for a clean environment. Chemical Engineering has led the way in clean air technology from power plants and automobiles, and is leading technology development in greenhouse gas reduction and sequestration.
Modeling and computation are a vital component of scientific research--theory, simulation and computer-aided analysis are used to understand and design phenomena that range across a dramatic range of scales in space and time, from molecules to entire chemical plants. The ongoing explosion in high-performance scientific computing, coupled with spectacular advances in algorithm development for problems in computational statistical mechanics, bioinformatics, multiscale modeling and the quantification of uncertainty, transform the role of the modeler in modern chemical engineering.
Within the department, pioneering computational and algorithm development research occurs in several areas: the development of systematic computational approaches to protein folding, the development of novel computational ensembles in statistical mechanics and the exploration of glassy landscapes and dynamics, the coarse-graining of multiphase flow equations and the development of new closures for them, the development of coarse, equation-free computation for multiscale/complex systems and the exploration of dynamic, nonlinear pattern formation in developmental biology. The University encompasses a vibrant, open and collaborative community of modeling/computational researchers and applied mathematicians across disciplines (see also the Program in Applied and Computational Mathematics).
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