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Computing and Systems
Technology: |
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Process Synthesis for Sustainable Energy Future
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Deadline to Register- 30 September 2013
DATE: Thursday, October 3rd, 2013, 2-4 PM EDT
Dial-in from the comfort of your office to hear the presentation
Abstract
In a fossil-fuel deprived world, it is likely that all the basic human needs will be met by
renewable sources like solar energy. Among the needs, transportation offers the
greatest challenges, owing to its high energy-density fuel requirements, which have
traditionally been met by liquid hydrocarbon fuels derived from fossil resources. Here,
we present a detailed systems analysis of the transportation sector, from which
emerges an energy efficient roadmap, based on the use of renewable carbon sources
like biomass, solar energy in the form of H2, heat and electricity, in conjunction with
novel processes for producing liquid fuels. In addition, some specific transition solutions
are also discussed.
In a sustainable energy future, availability of efficient hydrogen from solar energy will be
a key to the large scale production of chemicals and fuels. We present process
synthesis methodology to identify efficient processes for solar hydrogen production.
These processes, although not economical today, point us in the direction where
technical advancements are needed to enable a truly sustainable future.
Finally, a grand challenge of solar energy use is its intermittency. Synthesis of
processes to store GWhr levels of energy for uninterrupted power grid supply is also
discussed.
Biographical Sketch
Rakesh Agrawal is Winthrop E. Stone Distinguished Professor, School of
Chemical Engineering, Purdue University. Previously, he was an Air Products Fellow at
Air Products and Chemicals, Inc., where he worked until 2004.
A major thrust of his research is related to energy issues and includes novel
processes for fabrication of low-cost solar cells, biomass and liquid fuel conversion, and
energy systems analysis. His research further includes synthesis of muticomponent
separation configurations including distillation, membrane and adsorption based
processes, basic and applied research in gas separations, process development, gas
liquefaction processes and cryogenics. He was a member of the NRC Board on Energy
and Environmental Systems (BEES) and a member of the AIChE’s Board of Directors
and also its Energy Commission. He has published 116 technical papers and holds 118
U.S. and more than 500 foreign patents. These patents are used in over one hundred
chemical plants with total capital expenditure in multibillion dollars.
He is a member of the US National Academy of Engineering, a Fellow of the
American Academy of Arts and Sciences and a foreign Fellow of the Indian National
Academy of Engineering. He is currently on the Technical Advisory boards of five
chemical companies. Agrawal received the 2010 National Medal of Technology and
Innovation from the U.S. President.
Dr. Agrawal received a B. Tech. from the Indian Institute of Technology, in
Kanpur, India; a M.Ch.E. from the University of Delaware, and an Sc.D. in chemical
engineering from the MIT.
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Previous WebCASTs
Invention and Innovation in a Product-Centered Chemical Industry: General Trends and a Case Study
by Prof. George Stephanopoulos
WebCAST on Tuesday, 26 Oct 2004, 1pm-2:30pm (Eastern time)
The
entire 75 page presentation
[1470 KB] may be downloaded in pdf format.
Abstract
A profound change has taken place in the character of the chemical industry
over the last 10-15 years. The process-centered emphasis has gradually shifted
to a product-centered one. The implications are extensive and cover almost
every aspect of a company's operations; process of invention, process of
innovation, management of R&D, interactions with universities and
technology development companies, capital allocation, and the character of
business strategies and marketing efforts.
In
addition, these trends have an effect on the educational preparation of
scientists and engineers, a preparation that determines the educational and
personal profiles of professional in the chemical industry.
In
this presentation, I will discuss the development of the above shift and
outline the essential characteristics of a product-centered chemical industry
with particular emphasis on the following aspects:
· How has the process of invention and
innovation changed and what are the implications for academic
education/research and industrial research and technology development.
· The integration of R&D with marketing and
business strategy, as the pivotal element in successful industrial innovation.
· The character of R&D management and the
significance of leveraging knowledge assets across corporations, research
institutions, and other entities.
· A description of the general trends that lie
ahead.
Specific
examples from the "Reformation and Rejuvenation of R&D" in
Mitsubishi Chemical will be used for illustration, as well as examples from
analogous activities of other chemical companies.
Biographical Sketch
Professor Stephanopoulos is the Arthur D. Little Professor of Chemical
Engineering and Co-Director of the "Laboratory for Bioinformatics and
Metabolic Engineering" at the Massachusetts Institute of Technology. He
obtained his Ph.D. in chemical engineering from the University of Florida. His
first academic appointment was at the University of Minnesota (1974).
Subsequently he taught at the National Technical University of Athens (1981-84)
and he joined MIT in 1984. During the period, July 2000 to July 2002, he was
appointed as Chief Technology Officer of the Mitsubishi Chemical Corporation's
group of companies, where he presently serves as Managing Director and member
of the Board.
His
past research interests have covered a broad spectrum of problems from product
design, process development and design, to process operations
analysis-diagnosis-planning and process control. His present research interests
are in the areas of , (a) Bioinformatics (Functional Genomics and Metabolic
Engineering), and (b) Multi-Scale Modeling of Materials and processes. His
teaching interests have covered undergraduate/graduate subjects in Principles
of Chemical Engineering, Thermodynamics, Process Design, Process Control, and
Systems Engineering. He has authored, co-authored, and edited 10
books/monographs and over 190 journal papers.
He
has been honored with the A.P. Colburn Award (AIChE), C. McGraw Award (ASEE),
Dreyfus Teacher-Scholar Award, Computing in Chemical Engineering Award
(AIChE-CAST Division), and the Best Paper Award in 1987 and 1992 (Computers and
Chemical Engineering). In 1999 he was elected a member of the National Academy
of Engineering, and in 2002 he received an Honorary Doctorate of Science from
MacMaster University.
Distributed Decision Making in
Complex Organizations: The Adaptive Enterprise
by Prof. B. Erik Ydstie
WebCAST on Friday, 03 Dec 2004, 10:00am-11:30am Pacific
[1:00pm-2:30pm Eastern]
The 40
page presentation
[5.6 MB] may be downloaded in pdf format. The complete paper
is published in Computers and Chemical Engineering, Vol 29/1 pp 11-27,
Special issue: PSE 2003 - Edited by B. Chen and A. W. Westerberg.
Abstract
In this web-cast presentation I will give an overview of decision making and
portfolio management in highly distributed organizations. The business system
is modeled as a flexible network of semi-autonomous activities integrated with
the market through service, cash and product transactions. There is a positive
cost associated which each activity and transaction (the second law of
thermodynamics), whereas cash is conserved (the first law of thermodynamics).
These foundation principles allow us to develop a very rich topological
structure for finance and business decision making based on cost, cash-flow and
value analysis.
The
objective of the business decision maker is to manage the activity rates and
project portfolio so that the “intrinsic value” of the enterprise is maximized
without incurring undue risk. According to Warren Buffet, the intrinsic value
is the expected, discounted cash value of a project. A project can be a process
modification, R&D resulting in a new product or process or a merger or
acquisition. In this presentation I will explain how the dynamics of the
network of integrated activities and project portfolio can be managed using
distributed decision making and how good inventory and flow control reduce cost
and risk. Risk is modeled as a Martingale process driven by stochastic fluctuations
in the market. I also show that under certain conditions the intrinsic value is
maximized by decentralized decision making and that the policies we generate
leads to methodologies for decision making which are similar to those recently
advocated by “lean manufacture”.
By
making analogies between network thermodynamics and business decision making I
show that the network paradigm leads to organizational structures that are
agile and able to adapt to changing markets and new technologies. Industrial
examples from automotive windshield production, solar grade silicon and
aluminum production will be discussed.
Biographical Sketch
Erik Ydstie is Professor of Chemical Engineering at Carnegie Mellon University.
He received the B.Sc. and M.Sc. from the Norwegian Institute of Technology and
his Ph.D. in 1982 from Imperial College. Professor Ydstie applies control
theory to processes of practical interest to the chemical manufacturing
industries.
Crystal Engineering for Product
& Process Design
by Prof. Mike Doherty
WebCAST on Thursday, 23 June 2005, 10:00am to noon Pacific
[1:00pm-3:00pm Eastern]
The
entire 47 page presentation [2.0 MB]
may be downloaded in pdf format.
Abstract
Crystalline organic solids are ubiquitous as either final products or as
intermediates in the specialty chemical, pharmaceutical, and home &
personal care industries. Virtually all small molecular weight drugs are
isolated as crystalline materials, and over 90% of all pharmaceutical products
are formulated in particulate, generally crystalline form. Crystalline chemical
intermediates, such as adipic acid, are produced in large amounts to make
polymers and specialty products. Skin creams and other personal care product
formulations contain crystalline solids. In most cases the properties of the
crystalline solid have a major impact on the functionality of the product as
well as the design and operation of the manufacturing process.
Crystal
size (or size distribution), shape, enantiomorph, and polymorph all influence
product functionality. For example, even a 50 micron particle in a hand cream
makes the cream feel gritty. Size distribution is important in the manufacture
of beta-carotene, which is virtually insoluble in water and only sparingly
soluble in vegetable oils, and is used as a food colorant. The color shade
given to the food is determined by the narrow size distribution which must be
in the submicron range. Crystal shape and polymorph influence solubility,
dissolution rate (which influence bioavailability), compressibility (important
for tabletting), and stability. The crystal enantiomorph is of vital importance
in the manufacture of chiral materials, which has become a $100 billion/year
industry in recent years. The choice of solvent, as well as the design and
operation of the manufacturing process determine the crystal properties.
Moreover, crystal size distribution, and shape have a major impact on the
design of the manufacturing process since needle-like crystals or plate-like
crystals can be difficult to filter and dry.
In
this presentation we discuss the interactions between crystal engineering and
crystallization process & product design. We assess the current status of
knowledge in this field and identify critical areas for future research and development.
Biographical Sketch
Michael F. Doherty is Professor of Chemical Engineering at the University of
California, Santa Barbara. He received his B.Sc. in Chemical Engineering from
Imperial College, University of London in 1973, and his Ph.D. in Chemical
Engineering from Trinity College, University of Cambridge in 1977. He taught at
the Universities of Minnesota and Massachusetts (where he reached the rank of
University Distinguished Professor) before joining the faculty at UCSB. He has
held a visiting appointment at the University of Minnesota in the Spring
Quarter of 1981 and was a visiting scholar at the University of California at
Berkeley for the 1984 calendar year. His research interests include design and
synthesis of nonideal separation systems, separation with chemical reaction,
and crystal engineering of organic materials. He is the holder of four patents,
has published over 150 technical papers and delivered over 160 invited
lectures; he was awarded best paper of the year in 1993 (jointly with M.F.
Malone and Z.T. Fidkowski) and again in 2001 (jointly with M. F. Malone and S.
B. Gadewar) by the editors of Computers and Chemical Engineering.
He
is co-author of the textbook, Conceptual Design of Distillation Systems,
McGraw-Hill (2001), and editor of the distillation chapters in Perry’s
Handbook, and the Kirk-Othmer Encyclopedia of Chemical Technology.
He has received numerous honors and awards for his teaching and research,
including the Computing in Chemical Engineering Award of the CAST Division of
the AIChE (awarded jointly with M. F. Malone in 1996), the Alpha Chi Sigma
Award for Chemical Engineering Research of the AIChE (2004), the Clarence G.
Gerhold Award of the Separations Division of the AIChE (2004) and the
Excellence in Process Development Research Award of the Process Development
Division of AIChE (awarded jointly with M. F. Malone in 2004). He has served as
a consultant for many companies in the area of separations technology, and is a
member of the Corporate Technical Advisory Boards for The Dow Chemical Company
(2000-present) and Rhone–Poulenc (1997-1999).
At
the University of Massachusetts Dr. Doherty was Head of Department from
1988-1997, and served as Director of the Center for Process Design and Control
(1997-2000). He has been a Trustee of the CACHE Corporation since 1987 and
served as its president from 2000-2002. In 1993 he was Chair of the Computing
and Systems Technology Division of the AIChE. He serves as a member of the
Editorial Boards for Computers and Chemical Engineering (1997-present), Process
Systems Engineering Series, Academic Press (1997-present), Separation
and Purification Methods (1998-2002), Industrial and Engineering
Chemistry Research (1995-1998), and Transactions of the IChemE Part A:
Chemical Engineering Research & Design (2001- 2003).
Advanced Process Control in
Semiconductor Manufacturing
by Prof. Costas Spanos and Dr. Thomas Sonderman
WebCAST on Friday, 28 October 2005, 10am-noon Pacific
[1pm-3pm Eastern]
The
entire 71 page presentation
[3.3 MB] may be downloaded in pdf format.
Abstract
Semiconductor manufacturing error budgets are getting tighter and traditional
metrology and control methods cannot keep up with the ever shrinking
dimensions. In the sub-100nm generation of technologies, Critical Dimensions
(CDs) are hard to measure, let alone control, since error budgets are almost
consumed by measurement error. As a result, integrated circuit designers are
called upon to produce designs that can tolerate large amounts of variability,
and IC production facilities turn to more advanced process control schemes.
This new reality challenges the historical modes of interaction between IC
designers and producers. In this talk we will present this problem, and we will
highlight present and future cutting edge applications in metrology, control,
and design for manufacturability.
Biographical Sketches
COSTAS J. SPANOS received the EE Diploma from the National Technical University
of Athens, Greece and the M.S. and Ph.D. degrees in Electrical and Computer
Engineering from Carnegie Mellon University. In 1988 he joined the faculty at
the department of Electrical Engineering and Computer Sciences of the
University of California at Berkeley, where he is now a Professor, and the
Associate Dean for Research in the College of Engineering. Dr. Spanos was the
editor of the IEEE Transactions on Semiconductor Manufacturing, and has
published more than 130 referred publications.
His
research interests include the development of flexible manufacturing systems,
the application of statistical analysis in the design and fabrication of
integrated circuits, and the development of novel sensors and computer-aided
techniques. In 2000 he was elected Fellow of the IEEE for contributions and
leadership in semiconductor manufacturing.
THOMAS
SONDERMAN is the Director of Automated Precision Manufacturing (APM) Technology
for AMD with global responsibility for the design, development and
implementation of manufacturing technologies within AMD’s wafer fab and
assembly operations.
Thomas
has held numerous management and engineering positions during his 15-year
tenure with AMD. Prior to joining AMD, Sonderman worked as a process control
engineer for Monsanto Chemical Inc. He obtained a BS in Chemical Engineering
from the University of Missouri in 1986 and a Masters degree in Electrical
Engineering from National Technological University in 1991.
Thomas
has a broad range of experience in the area of manufacturing automation and its
application to high volume semiconductor fabrication. He is a highly
sought-after speaker at industry conferences and is member of two advisory committees
at the University of Texas: Chemical Engineering and Science, Technology and
Society. Sonderman is the author of over 40 patents/patents pending and has
published numerous articles in the area of automated control and manufacturing
technology.
Feedback: The simple and best
solution
by Prof. Sigurd Skogestad
WebCAST on Thursday, 9 Feb 2006, 9am-11am Pacific [noon-2pm
Eastern]
The
entire 66 page presentation [2863 KB]
may be downloaded in pdf format.
Abstract
Most chemical engineers are (indirectly) trained to be “feedforward
thinkers" and they immediately think of “model inversion'' when it comes
doing control. Thus, they prefer to rely on models instead of data, although
simple feedback solutions in many cases are much simpler and certainly more
robust.
The
seminar starts with a simple comparison of feedback and feedforward control and
their sensitivity to uncertainty. Then two nice applications of feedback are
considered:
1.
Implementation of optimal operation by "self-optimizing control". The
idea is to turn optimization into a setpoint control problem, and the trick is
to find the right variable to control. Applications include process control,
pizza baking, marathon running, biology and the central bank of a country.
2.
Stabilization of desired operating regimes. Here feedback control can lead to
completely new and simple solutions. One example would be stabilization of
laminar flow at conditions where we normally have turbulent flow. I the seminar
a nice application to anti-slug control in multiphase pipeline flow is
discussed.
Biographical Sketch
Sigurd
Skogestad was born in Norway in 1955. He received the Siv.Ing. degree (Diploma
Engineer) in chemical engineering from the Norwegian University of Science and
Technology (NTNU) in Trondheim in 1978. After finishing his military service at
the Norwegian Defence Research Institute, he worked from 1980 to 1983 with
Norsk Hydro in the areas of process design and simulation at their Reseach
Center in Porsgrunn, Norway. He then spent 3.5 years in the US working towards
his Ph.D. under the guidance of Manfred Morari, receiving the Ph.D. degree from
the California Institute of Technology in 1987. He has been a professor of
chemical engineering at the Norwegian University of Science and Technology
(NTNU) since 1987, and since 1999 he is Head of Department of Chemical Engineering (
Kjemisk prosessteknologi ). He was at sabattical leave at the University of
California at Berkeley in 1994-95, and at the University of California at Santa
Barbara in 2001-02.
He
has a group of
about 10 Ph.D. students and is the Head of PROST which is the strong
point center in process systems engineering in Trondheim and involves about 50
people in various departments.
The
goal of his research is to develop simple
yet rigorous methods to solve problems of engineering significance. Research
interests include the use of feedback as a tool to (1) reduce uncertainty
(including robust control), (2) change the system dynamics (including
stabilization), and (3) generallly make the system more well-behaved (including
self-optimizing control). Other interests include limitations on performance in
linear systems, control structure design and plantwide control, interactions
between process design and control, and distillation column design, control and
dynamics.
The
author of more than 100 journal publications and 150
conference publications, he is the principal author together with Ian
Postlethwaite of the book "Multivariable feedback
control" published by Wiley in 1996 (first edition) and 2005 (second
edition). In October 2000 he published a book on "Process engineering -
mass and energy balances" and a second edition came in August 2003 (In
Norwegian; , Prosessteknikk (Tapir, 2000/2003) (he is
considering writing an English edition.)
Dr.
Skogestad was awarded "Innstilling to the King" for his Siv.Ing.
degree in 1979, a Fullbright fellowship in 1983, received the Ted Peterson
Award from AIChE in 1989, the George S. Axelby Outstanding Paper Award from
IEEE in 1990, and the O. Hugo Schuck Best Paper Award from the American
Automatic Control Council in 1992. He was an Editor of Automatica during
the period 1996-2002.
In
the autumn he teaches a course on introduction to
process engineering based on his own text book. He used to teach the process control course for the 4th year students,
but more recently this has been taken over by professor Heinz Preisig. Since
1989 he taught a Ph.D. course in robust
multivariable control in the Control
Department, based on his book with Ian Postlethwaite, but the course was
given for the last time in spring 1999, and it has been replaced by an advanved
undergraduate course given by Professor Morten Hovd. The engineering degree at
NTNU has recently (first 5-year students graduated in 2002) changed from a 4.5
year program to a 5 year program and the siv.ing. degree is now considered
equivalent to a M.Sc. degree. Professor Skogestad presentlty teaches a new advanced process control module for the 5th year
students.
Computational Tools for the Analysis
and Redesign of Microbial Production Systems
by Prof. Costas D. Maranas
DATE: Friday, 12 May 2006, 10am-12noon Pacific [1pm-3pm
Eastern]
The
entire 46 page presentation [2105 KB]
may be downloaded in pdf format.
Abstract
In this talk we will describe how optimization-based computational tools can be
used to guide strain redesign leading to targeted overproductions. For example,
production of bio-ethanol or complex molecules such as terpenes. Using as a
starting point stoichiometric models of microbial metabolism, we will first
explore how optimization can be used to pinpoint which new functionalities to
add to the microbial host to endow it with new capabilities extracted from a
generated database of more than 5,700 reactions. Building on this computational
infrastructure, we will then present an integrated framework for identifying
optimal microbial strain redesign strategies allowing for (i) additions, (ii)
deletions and (iii) modulations (i.e., activations or inhibitions) of targeted
reactions in the metabolic network. Finally we will explore how optimization
can be used to analyze the topological properties of metabolic networks,
identify pathway gaps and suggest ways of filling them. The developed
computational tools will be highlighted using a number of design case-studies
and the predictions will be contrasted with experimental results.
Biographical Sketch
Costas
D. Maranas (b. 1967), Donald B. Broughton Professor, Department of Chemical
Engineering, The Pennsylvania State University, BS, Chemical Engineering,
Aristotle University, Greece, (1990); MA, Chemical Engineering, Princeton
University (1992); Ph.D. in Chemical Engineering, Princeton University (1995);
Allan P. Colburn Award for Excellence in Publication (2002), Editorial Board
for Biophysical Journal, Computers & Chemical Engineering, Journal of
Global Optimization and Metabolic Engineering; Reviewer for NSF, NIH and DOE;
Research interests: Modeling and optimization of directed evolution protocols
for protein engineering, analysis and optimization of metabolic and signaling
networks, optimal design of biological circuits and synthetic biology,
inference of gene regulatory networks, real options based optimization of
product and R&D pipelines, optimization theory and algorithms.
Modeling and Design of Multiscale
Chemical Systems
by Prof. Richard D. Braatz
DATE: Friday, 29 Sept 2006, 10am-12noon
Pacific [1pm-3pm Eastern]
The
entire 41 page presentation [2.70 MB, pdf] may be downloaded from UIUC.
Abstract
This talk describes applications of molecular simulation to chemical reacting
systems and the subsequent development of techniques for multiscale simulation
and multiscale systems engineering. The progression of applications of
simulation from macroscopic to molecular to multiscale is reviewed. Multiscale
systems are presented as an approach that incorporates molecular and multiscale
simulation to design processes that control events at the molecular scale while
simultaneously optimizing all length scales from the molecular to the
macroscopic. It is discussed how multiscale modeling and the targeted design of
processes and products at the molecular scale can be addressed using the
multiscale systems tools. In addition to addressing challenging problems in
materials, microelectronics, and biotechnology, this provides a framework for
addressing the “grand challenge” of nanotechnology: how to move nanoscale
science and technology from art to an engineering discipline.
Biographical Sketch
Richard
Braatz is Professor and Millennium Chair of Chemical and Biomolecular
Engineering at the University of Illinois at Urbana-Champaign. Before starting
at U of I he received M.S. & Ph.D. degrees from Caltech and spent a year at
DuPont. Dr. Braatz is a co-author of ~100 journal papers and 3 books, and has
consulted and/or collaborated with more than 10 companies including Merck, IBM,
and UTC Fuel Cells. Honors and awards include the AACC Donald P. Eckman Award
(2000), the ASEE Curtis W. McGraw Research Award (2004), the AIChE CAST
Outstanding Young Researcher Award (2005), and the IEEE Antonio Ruberti Young
Researcher Prize (2005). Dr. Braatz’s main research interests are in modeling,
design, and control of complex and multiscale systems, with applications in
microelectronics, pharmaceuticals, and biotechnology.
Model Predictive Control: Theory and
Practice
Jay H. Lee
Professor of Chemical and Biomolecular Engineering at Georgia Tech
DATE: Monday, 7 May 2007, 10am-12noon EST
The
entire 64 page presentation [1772
KB] may be downloaded in pdf format.
Abstract
This course will attempt to give the audience a general overview on theories
and practice of model predictive control and system identification. Fundamental
theories as well as current industrial algorithms and practice will be covered.
A short discussion on various system identification methods that are being used
to build models for MPC will also be given.
Biographical Sketch
Dr. Lee is currently Director of the Integrated Sensing, System Identification,
and Control Laboratory (ISSICL). His group is working on ways to use powerful
computers, numerical optimization methods, information processing techniques,
and novel sensors to improve the safety and efficiency of chemical and
biological processes. The cornerstone of their research is a computer-based
optimal control technique called Model Predictive Control (MPC), which has
already seen applications on many industrial processes (>3000 worldwide
applications) with some impressive results. The main components of MPC are the
model, the sensors, and the optimal control algorithm. His research group
focuses on integration - rather than mere enhancement of the individual
components of MPC. They are developing modeling and system identification tools
that allow the user to tailor the modeling efforts to specific end-goals of the
control. They are developing techniques for integrating several different types
of sensors and a process model so that accurate predictions can be made about
the whole system including the behavior of those variables that cannot be
measured as frequently or reliably as desired. They are also developing smart
control algorithms that make optimal decisions while fully accounting for
uncertainties in the model and sensed information. They are conducting a number
of fundamental studies on data-assisted modeling, sensing, and control, which
are designed to improve the integration step. In addition to the fundamental
studies, they are conducting in parallel several application studies involving
challenging industrial process control problems, including those that arise in
particulate processes, mammalian cell reactors, polymer reactors, simulated
moving bed separation systems, and pulp and paper processes.
Dr. Lee received the National Science Foundation’s Young Investigator Award and
a number of other research and teaching awards. He is also a co-author of the
forthcoming book “Model Predictive Control.” He is a member of AIChE, IEEE, and
ASEE, and participated in organizing several international conferences.
Materials Surface Engineering by Simultaneous Action of Multiple External Forces
DATE: Thursday, 20 September 2007, 2-4 PM EST
The entire 64 page presentation [1772 KB] may be downloaded in pdf format.
Abstract
Understanding the response of materials surfaces to the simultaneous action of multiple external forces is required for the systematic generation and stabilization of certain surface features and patterns that play important roles in the tailoring of materials properties and function. In this presentation, we focus on the surface morphological stability and dynamics of stressed crystalline solids, which underlies various materials processing and reliability problems in numerous technological applications ranging from aerospace to microelectronics and nanotechnology. An example of such an important problem in microelectronics is the electromigration-driven dynamics of void surfaces in mechanically confined metallic films that are used as device interconnections in modern integrated circuits. Surfaces of stressed elastic solids have been shown to undergo morphological instabilities. For example, the competition between elastic strain energy and surface energy can cause the growth of perturbations from a planar surface morphology under certain conditions and trigger the so-called Asaro-Tiller or Grinfeld instability. It has been demonstrated experimentally and computationally that a planar surface of a stressed elastic solid can evolve rapidly into a cusped surface, with smooth tops and deep crack-like grooves by surface diffusion. However, the effects of the simultaneous action of an electric field on the morphological response of a conducting stressed solid surface have not been explored systematically.
In this presentation, we explore surface morphological response to the simultaneous action of electric fields and mechanical stresses of crystalline solid conductors, such as Cu or Al, and of voids in thin films of such conductors. The analysis is based on a surface transport model that accounts for curvature-driven surface diffusion, surface electromigration, and stress-driven surface diffusion along with surface diffusional anisotropy. The computational predictions for the surface morphological evolution are based on self-consistent dynamical numerical simulations according to the fully nonlinear surface mass transport model, which is solved self-consistently with the electric field and stress field distributions on the solid (or the void) surface computed through a Galerkin boundary integral method.
First, we report results of linear stability analysis for the morphological response of a planar solid surface to the combined action of an applied electric field and mechanical stress, assuming that the solid responds elastically to stress. We derive a dispersion relation, which describes the growth or decay rate of a perturbation from the planar surface morphology of the stressed solid under the simultaneous action of the electric field. We find that application of a sufficiently strong electric field can stabilize the surface of the stressed electrically conducting solid material that would be otherwise vulnerable to surface cracking under certain thermomechanical conditions; therefore, the electric current protects the material against cracking and inhibits its damage. Furthermore, we report the effects on the surface morphological stability of key material properties, such as the strength of surface diffusional anisotropy and the material’s texture that is set by the surface crystallographic orientation. We find that the morphological response of face-centered cubic metal surfaces with <111> crystallographic orientation is easier to stabilize than that of surfaces with <100> or <110> crystallographic orientation. In addition to the linear stability analysis, we report computational results for the morphological evolution of a solid surface perturbed from an initially planar morphology under the simultaneous action of an electric field and mechanical stress. The numerical results confirm the main conclusions of the linear stability analysis. Our findings can be used toward development of systematic surface engineering strategies for improved materials reliability over a broad range of electromechanical conditions.
Next, we examine the surface morphological response of voids in metallic thin films under the combined action of electric fields and mechanical stresses. Our analysis predicts that, in the absence of stress, increasing the electric field strength, or the void size, or the strength of the diffusional anisotropy past certain critical values leads to transitions from steady states to time-periodic states; the latter states are characterized by wave propagation on the surface of the void, which migrates along the film at a constant speed. The transition onset corresponds to a Hopf bifurcation that may be either supercritical or subcritical, depending on the symmetry of the surface diffusional anisotropy that is determined by the crystallographic orientation of the film plane. We focus on low-symmetry anisotropy and analyze the current driven void surface morphological response under the simultaneous application of tensile biaxial stress starting from conditions close to the Hopf point in the stress-free case. Propagation of stable surface waves on the void is observed again as the applied stress level increases beyond a critical value. Further increase of the applied stress level leads to a period-doubling bifurcation associated with more complex surface wave propagation. Such period-doubling bifurcations continue with increasing stress level, setting the system on a route to chaos. With further increase in the stress level, the system exits from the chaotic regime to a periodic window characterized by a complex time-periodic state with three periods. Further increase in stress drives the system to another chaotic regime, through a period-doubling bifurcation sequence, and ultimately to film failure beyond a certain maximum stress level. Detailed characterization of the complex shape evolution is performed over the range of stress levels examined and the nature of the resulting chaotic state (strange attractor) is discussed. These results are used to motivate surface engineering studies toward formation of desirable surface patterns in solid material systems of interest in electronics, optoelectronics, energy technologies, and various areas of nanotechnology.
Biographical Sketch
Dr. Maroudas is currently Professor of Chemical Engineering at the
University of Massachusetts at Amherst. He received his Diploma from the
National Technical University of Athens in 1987 and PhD at the
Massachusetts Institute of Technology in 1992, both in chemical
engineering. After a postdoctoral research fellowship at IBM T.J. Watson
Research Center in 1992-1994, he was a faculty member at the University of
California at Santa Barbara before moving to his current position. His
research has been in computational materials science and electronic
materials. His honors and awards include the CAREER Award from the National
Science Foundation and the Camille Dreyfus Teacher-Scholar Award.
Dynamic Real-Time Optimization:
Concepts in Modeling, Algorithms and Properties
Lorenz T. Biegler
Carnegie Mellon University
DATE: Wednesday, 28 November 2007, 10AM-noon EST
The
entire 49 page presentation [5790 KB]
may be downloaded in pdf format.
Abstract
The webcast develops and discusses nonlinear programming (NLP) strategies for
the optimization of nonlinear dynamic models that arise in both off-line and
on-line applications in chemical process engineering. In particular, Dynamic
Real-Time Optimization can play a significant part in the decision-making
hierarchy that includes logistics, planning, scheduling and control. Its basic
components deal with estimation of the system and identification of a system
model, optimization of a system model and regulation to reject disturbances.
Moreover, the inclusion of a consistent set of nonlinear process models is
essential in order to coordinate optimization decisions made at different
levels in the hierarchy.
The webcast briefly presents and summarizes nonlinear programming methods for
dynamic optimization. In particular, it discusses simultaneous NLP formulations
along with large-scale NLP solvers for dynamic optimization and demonstrates
its effectiveness with real-world examples. Also described is the extension of
this approach to nonlinear model predictive control (NMPC). In the last few
years, these have emerged as efficient and reliable on-line NMPC strategies.
Finally, the webcast discusses the integration of dynamic models for off-line
optimization to on-line model predictive control (MPC). In particular, we will
discuss a fast sensitivity-based nonlinear MPC strategy that is not only
consistent with rigorous off-line dynamic optimization models but requires very
little on-line computation. A similar strategy will also be presented for
moving horizon estimation with nonlinear models. All of these concepts will be
illustrated with several case studies drawn from process engineering.
Biographical Sketch
Professor Larry Biegler is the Bayer Professor of Chemical Engineering at
Carnegie Mellon University. He received a BS degree from Illinois Institute of
Technology and MS and PhD degrees from University of Wisconsin, Madison, all in
chemical engineering. Prof. Biegler's research projects are in the areas of
design research and systems analysis. His research centers on the development
and application of concepts in optimization theory, operations research, and
numerical methods for process design, analysis, and control. He has received
numerous honors and awards including the Presidential Young Investigator Award
from the National Science Foundation, the Curtis McGraw Research Award from the
American Society for Engineering Education, and the Computing in Chemical
Engineering Award from the CAST Division of the American Institute of Chemical
Engineers.
When does controllability equal
profitability?
Thomas F Edgar
University of Texas
DATE: Monday, 17 March 2008, 2 PM - 4 PM EST
The
entire 68 page presentation
[1674 KB] may be downloaded in pdf format.
Abstract
The justification of process control in the context of business decision-making
may include the following economic or operating considerations: increased
product throughput, increased yield of higher valued products, decreased energy
consumption, decreased pollution, decreased off-specification product, improved
safety, extended life of equipment, improved operability, and decreased
production labor. However, identifying a direct relationship between each type
of economic benefit (profitability) and how controllers are designed or
operated (controllability) is an elusive target. Perspectives of how process
control has influenced business decision-making have changed radically over the
brief history of process control (1950 to the present). Thus it is valuable to
have an historical view of the changing role of process control in operations
and profit/loss measures. Today the influence of process control on business
decision-making is at its highest level ever, but there are still many
challenges that must be met for process control to maximize its economic impact
on an enterprise-wide scale. The opportunity to connect controllability to
profitability appears greater for batch processing than for continuous
processing.
Biographical Sketch
Thomas F. Edgar is Professor of Chemical Engineering at the University of Texas
at Austin and holds the George T. and Gladys Abell Chair in Engineering. Dr.
Edgar received his B.S. in chemical engineering from the University of Kansas
and a Ph.D. from Princeton University. For the past 35 years, he has
concentrated his academic work in process modeling, control, and optimization,
with over 200 articles and book chapters. Edgar has co-authored leading
textbooks: Optimization of Chemical Processes (McGraw-Hill, 2001) and Process
Dynamics and Control (Wiley, 2004). He has received major awards from AIChE
(Colburn, Computing in Chemical Engineering, Lewis) and ASEE (Chemical
Engineering Division, Westinghouse, and Meriam-Wiley). Recently he has carried
out modeling and control research projects jointly with a variety of companies
in the process industries under the auspices of the Texas-Wisconsin-California
Control Consortium (www.che.utexas.edu/twmcc).
Multiscale Modeling and its
Application to Catalyst Design and Portable Power Generation
Professor Dion G. Vlachos
University of Delaware
DATE: Thursday, 24 April 2008, 2 PM - 4 PM EST
The
entire 24 page presentation
[1869 KB] may be downloaded in pdf format.
Abstract
Multiscale simulation is emerging as a new scientific field in chemical,
materials, and biological sciences. The idea of multiscale modeling is
straightforward: one computes information at a smaller (finer) scale and passes
it to a model at a larger (coarser) scale by leaving out degrees of freedom as
one moves from finer to coarser scales. The obvious goal of multiscale modeling
is to predict macroscopic behavior of an engineering process from first
principles (bottom-up approach). However, the emerging fields of nanotechnology
and biotechnology impose new challenges and opportunities (top-down). For
example, the miniaturization of microchemical systems for portable and
distributed power generation imposes new challenges and opportunities than the
conventional scaling up chemical engineers have worked on. In this talk, I will
describe the development of multiscale models for catalytic reactors with a
focus on small-scale hydrogen production. Limitations in model development,
including multi-level uncertainty, will be discussed. A new multiscale and
informatics-based framework will be presented for design of experiments (DOE)
in order to enable model assessment and parameter refinement. The framework is
designed to overcome uncertainties by allowing experimental data injection into
multiscale models. Finally, I will discuss how one could use these models to
enable both catalyst design and microsystem optimization for portable and
distributed power generation.
Biographical Sketch
Dion Vlachos is a Professor at the Department of Chemical Engineering at the
University of Delaware since 2003. He is currently an associate director of the
Center for Catalytic Science and Technology. Dion obtained a five years diploma
in Chemical Engineering from the National Technical Univ. of Athens, in Greece,
in 1987. He obtained his MS and Ph.D. from the University of Minnesota in 1990
and 1992, respectively, and spent a postdoctoral year at the Army High
Performance Computing Research Center, MN, after which he joined UMass as an
Assistant Professor. He was promoted to an associate professor at UMass in
1998. Dion was a Visiting Fellow at Princeton University in the spring of 2000,
a visiting faculty at Thomas Jefferson Univ. and Hospital in spring of 2007 and
the George Pierce Distinguished Prof. of Chemical Engineering and Materials
Science at the Univ. of Minnesota in the fall of 2007. Dion is the recipient of
an ONR Young Investigator Award, a NSF Career Award, a Junior Faculty Award,
and the Best Advisor Award (twice). He is a member of the American Institute of
Chemical Engineers, American Chemical Society, The Combustion Institute, The
Catalysis Society, and SIAM. His main research thrust is multiscale modeling
and simulation along with their application to catalysis and portable
microchemical devices for power generation, nucleation and growth of
nanomaterials, microporous thin films, and molecular cell biology. He is the
corresponding author of more than 160 refereed publications and has given more
than 120 invited talks (plenary lectures, keynote lectures, etc.).
Real-Time Implementation of
Nonlinear Model Predictive Control
Professor Michael A. Henson
University of Massachusetts, Amherst
DATE: Thursday, 2 October 2008, 1 PM - 3 PM EST
The
entire 51 page presentation [1709 KB]
may be downloaded in pdf format.
Abstract
Linear model predictive control (LMPC) is well established as the industry
standard for controlling constrained multivariable processes. A major
limitation of LMPC is that plant behavior is described by linear dynamic
models. As a result, LMPC is inadequate for highly nonlinear processes and
moderately nonlinear processes with large operating regimes. This shortcoming
coupled with increasingly stringent demands on throughput and product quality
spurred the development of nonlinear model predictive control (NMPC). NMPC is
conceptually similar to its linear counterpart except that nonlinear dynamic
models are used for process prediction and optimization. The purpose of this
WebCAST is to provide an overview of current NMPC technology with a focus on
the real-time implementation issues required to obtain a computationally
efficient controller. The necessary background will be introduced by reviewing
basic concepts of nonlinear process modeling and optimization. The principles
will be illustrated with a highly nonlinear cryogenic air separation column
model.
Biographical Sketch
Dr. Michael A. Henson is a Professor of Chemical Engineering and Director of
the Process Design and Control Center at the University of Massachusetts
Amherst. He received his B.S from the University of Colorado (1985), M.S from
the University of Texas (1988), and Ph.D. from the University of California,
Santa Barbara (1991), all in Chemical Engineering. Prior to his appointment at
UMass, he held a faculty appointment at Louisiana State University and visiting
positions at DuPont and the University of Stuttgart. He serves as an Associate
Editor for Automatica and the Journal of Process Control. He has received
several awards including the Career Development Award from the National Science
Foundation and the Alexander von Humboldt Research Fellowship (Germany). His
research interests are nonlinear modeling and control of complex chemical and
biological systems.
Optimal Design and Operation of
Natural Gas Value Chains
Professor Paul I. Barton
MIT, Cambridge
DATE: Tuesday, 13 January 2009, 2 PM - 4 PM EST
The
entire 47 page presentation [1993 KB] may
be downloaded in pdf format.
A
recording of the entire 76 minute presentation
[39548 KB] (voice and slides) may be downloaded in wrf format.
In order to view this you need to install the FREE
wrf player from WebEX.
Abstract
Natural gas contributes roughly 20% of world energy consumption. Natural gas
reserves are plentiful and natural gas produces less CO2 per unit of energy
generated than any other hydrocarbon. The liquefied natural gas (LNG) segment
is growing very rapidly and is enabling the emergence of a global natural gas
market. Natural gas value chains have very distinctive features arising from
the low volumetric energy density of natural gas, and the significance of gas
quality and pressure in supply chain operations. Gas infrastructure investments
can be risky due to the high capital and specificity of the infrastructure,
leading to complex ownership and contractual agreements amongst multiple
parties to manage this risk. This talk will present two case studies applying
optimization formulations to the design and operation of natural gas value
chains. Short-term operational planning in upstream natural gas supply chains
can play an important role in ensuring reliable supplies, consistent
fulfillment of customer requirements and efficient management of production and
transportation infrastructure. A real world case study involving the Sarawak
Gas Production System (SGPS), located in East Malaysia and operated by Sarawak
Shell, is presented to demonstrate a short-term (8-12 weeks) production
allocation model and optimization framework for the upstream natural gas supply
chain. The second case study involves the design of a novel liquefied energy
chain for the exploitation of remote offshore natural gas combined with CO2
capture and sequestration with enhanced oil recovery. Here optimization is used
to design novel offshore and onshore subambient processes required to implement
the proposed supply chain.
Biographical Sketch
Paul Barton is the Lammot du Pont Professor of Chemical Engineering at MIT,
where he has been since 1992. He received his Ph.D. from the Centre for Process
Systems Engineering at Imperial College, London University in 1992. He has held
Visiting Professor appointments at CNRS-ENSIC, Nancy, France and EPFL,
Lausanne, Switzerland. He has industrial experience with BP and Air Products,
and has consulted for major corporations including Dow Chemical, Alstom Power
and Aspen Technology. In 2004 he was awarded the Outstanding Young Researcher
Award by AIChE's CAST Division. Barton's research interests include hybrid
discrete/continuous dynamic systems; numerical analysis of ordinary
differential, differential-algebraic and partial differential-algebraic
equations; sensitivity analysis and automatic differentiation; global,
mixed-integer and dynamic optimization theory and algorithms; and open process
modeling software. Some of the applications his group is currently focusing on
include energy systems engineering, continuous pharmaceutical manufacturing and
organic electronic devices. He served as Director of AIChE's CAST Division from
2001-2004 and is currently a subject editor for the journal /Optimal Control
Applications and Methods/. He is author or co-author of over 80 articles in
refereed journals. He has been very active in the design and the development of
process modeling software, having been the original author of gPROMS, and
having led the development of ABACUSS/JACOBIAN and DAEPACK at MIT, all of which
are now commercial products widely used in industry.
The Role of Process Systems
Engineering in the Quest for the Artificial Pancreas
Professor Francis J. Doyle III
University of California, Santa Barbara
DATE: Monday, 28 September 2009, 1 PM - 3 PM EST
The
entire 47 page presentation
[5460 KB] may be downloaded in pdf format.
New! A recording of the entire 101 minute presentation [194028 KB] (voice and slides) may
be downloaded in wrf format.
In order to view this you need to install the FREE
wrf player from WebEX.
Abstract
Type 1 diabetes mellitus is a disease characterized by complete pancreatic
beta-cell insufficiency. The only treatment is with subcutaneous or intravenous
insulin injections, traditionally administered in an open-loop manner. Patients
attempt to mimic normal physiology in order to prevent the complications of
hyper- and hypoglycemia (elevated glucose levels, and low glucose levels,
respectively). Even minor glucose elevations increase the risk of complications
(retinopathy, nephropathy, and peripheral vascular disease).
In recent years, sensors and pumps have become available that show great
promise for a closed-loop artificial pancreas -- however the crucial missing
component is the algorithm to connect the devices. In order to normalize the
glucose levels of insulin dependent, type 1 diabetic patients, the algorithms
for the development of an artificial pancreatic islet need to exploit all the
measured variables that the normal islet insulin secretion utilizes and quickly
increase or decrease the insulin secretory.
Our group has been working on model-based control algorithms for pump control
over the last 17 years; with clinical evaluations over the last 7 years in
collaboration with the Sansum Diabetes Research Institute. Our investigations
have addressed the critical algorithmic elements of: model identification,
disturbance estimation, model predictive controller design, event detection,
monitoring & alarming, and optimization solution. In this talk, we present
our most recent computational and clinical results in pursuit of the artificial
beta cell. Our novel contributions include the model formulation, meal detection
& estimation schemes, efficient programming formulation, and the use of
insulin-on-board constraints to ensure safety.
Biographical Sketch
Dr. FRANCIS J. DOYLE III is the
Associate Dean for Research in the College of Engineering at UC, Santa Barbara
and he is the Associate Director of the Army Institute for Collaborative
Biotechnologies. He holds the Duncan and Suzanne Mellichamp Chair in Process
Control in the Department of Chemical Engineering, as well as appointments in
the Electrical Engineering Department, and the Biomolecular Science and
Engineering Program. He received his B.S.E. from Princeton (1985), C.P.G.S.
from Cambridge (1986), and Ph.D. from Caltech (1991), all in Chemical
Engineering. Prior to his appointment at UCSB, he has held faculty appointments
at Purdue University and the University of Delaware, and held visiting
positions at DuPont, Weyerhaeuser, and Stuttgart University. He is the
recipient of several research awards (including the NSF National Young
Investigator, ONR Young Investigator, Humboldt Research Fellowship) as well as
teaching awards (including the Purdue Potter Award, and the ASEE Ray Fahien
Award). He is currently the editor-in-chief of the IEEE Transactions on Control
Systems Technology, and holds Associate Editor positions with the Journal of
Process Control, the SIAM Journal on Applied Dynamical Systems, and Royal
Society’s Interface. In 2005, he was awarded the Computing in Chemical
Engineering Award from the American Institute of Chemical Engineers for his
innovative work in systems biology. His research interests are in systems
biology, network science, modeling and analysis of circadian rhythms, drug
delivery for diabetes, model-based control, and control of particulate processes.
Advances in Mathematical Programming
Models for Enterprise-wide Optimization
Professor Ignacio E. Grossmann
Carnegie Mellon University
DATE: Thursday, April 26th, 2012, 2 PM EDT
The
presentation
may be viewed on ChemE On Demand.
Abstract
Enterprise-wide optimization (EWO) has become a major goal in the process
industries due to the increasing pressures for remaining competitive in the
global marketplace. EWO involves optimizing the operations of supply,
manufacturing and distribution activities of a company to reduce costs,
inventories and environmental impact, and to maximize profits and
responsiveness. Major operational items include planning, scheduling, real-time
optimization and control. We provide an overview of EWO in terms of a
mathematical programming framework. We first provide a brief overview of
mathematical programming techniques (mixed-integer linear and nonlinear
optimization methods), as well as decomposition methods, stochastic programming
and modeling systems. We then address some of the major issues involved in the
modeling and solution of these problems. Based on the EWO program at the Center
of Advanced Process Decision-making at Carnegie Mellon, we show the scope of
these models by describing several applications that include optimal refinery
planning, simultaneous planning and scheduling in multisite facilities for
continuous multiproduct plants, optimization of industrial gas distribution
systems, design and planning under uncertainty of offshore oil field
infrastructures, and optimization of responsive supply chain design and
planning with demand uncertainty. Finally, we close with a brief discussion of
future directions of research in the EWO area.
Biographical Sketch
Prof. Ignacio
E. Grossmann is the Rudolph R. and Florence Dean University Professor of
Chemical Engineering, and former Department Head at Carnegie Mellon University.
He obtained his B.S. degree in Chemical Engineering at the Universidad
Iberoamericana, Mexico City, in 1974, and his M.S. and Ph.D. in Chemical
Engineering at Imperial College in 1975 and 1977, respectively. After working
as an R&D engineer at the Instituto Mexicano del Petróleo in 1978, he
joined Carnegie Mellon in 1979. He was Director of the Synthesis Laboratory
from the Engineering Design Research Center in 1988-93. He is director of the
"Center for Advanced Process Decision-making" which comprises a total
of 20 petroleum, chemical and engineering companies. Ignacio Grossmann is a member
of the National Academy of Engineering, Mexican Academy of Engineering, and
associate editor of AIChE Journal and member of editorial board of Computers
and Chemical Enginering, Journal of Global Optimization, Optimization and
Engineering, Latin American Applied Research, and Process Systems Engineering
Series. He was Chair of the Computers and Systems Technology Division of AIChE
, and co-chair of the 1989 Foundations of Computer-Aided Process Design
Conference and 2003 Foundations of Computer-Aided Process Operations
Conference. He is a member of the American Institute of Chemical Engineers,
Sigma Xi, Institute for Operations Research and Management Science, and
American Chemical Society.
Chemical Product Design: What is it?
Why is it Important? How is it done?
Prof. Michael Hill, Columbia
University
Kevin G. Joback, PhD, Molecular
Knowledge Systems, Inc.
DATE: Thursday, September 20th, 2012, 2-4 PM EDT
The 28
page presentation
from Prof. Hill [983 KB] may be downloaded in pdf format.
The 49
page presentation
from Dr. Joback [952 KB] may be downloaded in pdf format.
Abstract
Chemical products such as fuels, coatings, lubricants and cosmetics must be
designed to meet specific customer, environmental, safety and regulatory
constraints. Designing such products is a combinatorial problem that can
involve searching through thousands of candidate molecular structures and
mixture formulations. In years past, this search was conducted primarily experimentally,
a costly and time-consuming process. Today, with a global marketplace demanding
an ever-greater rate of product innovation, new approaches to chemical product
design are needed. This course will discuss what chemical product design is,
explain why it is important for chemical engineers to understand it, and
present approaches and examples of how chemical product design is done.
Biographical Sketches
Michael Hill Biography:
Michael Hill is Lecturer in Chemical Engineering Design at Columbia University
in New York City. He obtained his BS and MS degrees in Chemical Engineering
from Columbia University, and subsequently joined Unilever Research in
Edgewater, NJ in 1983. Michael remained with Unilever for 22 years, leading
R&D departments in various product categories, most notably Skin Care and
Cleansing. Michael also spent 3 years in the Unilever Research Port Sunlight
Laboratory in the U.K. He left Unilever in early 2005, and has been teaching
Chemical Product and Process Design at Columbia University ever since. In
addition to writing numerous internal Unilever Research documents, Michael has
authored several papers and book chapters on various aspects of chemical
product and process design. He is Chair of AIChE’s Process Development Division,
and has been a Fellow of AIChE since 2008.
Kevin Joback Biography:
Kevin G. Joback is president of Molecular Knowledge Systems. For more than 25
years Kevin has worked in the areas of physical property estimation and
chemical product design. He has developed a number of group contribution
estimation techniques now widely used in industry. He has designed numerous
chemical products including environmentally friendly cleaning and separation
solvents, new lubricants, enhanced thermal storage materials, improved jet and
rocket fuels, and non-hazardous aircraft deicing fluids. Kevin holds a
bachelor’s degree from Stevens Institute of Technology and a Masters and PhD
from MIT, all in chemical engineering.
Challenges and Opportunities in the
Continuous Manufacturing of Pharmaceuticals
Prof. Zoltan K Nagy, Purdue University
Prof. G V Rex Reklaitis, Purdue University
DATE: Wednesday, April 17th, 2013, 2-4 PM EDT
Abstract
The pharmaceutical industry is a large, high value added manufacturing sector,
with annual worldwide sales of nearly $1 trillion. The traditional
manufacturing mode in this sector has been batch operation. However, recent
advances in technologies, changes in the regulatory climate and continuously
drivers for cost reduction have provided a unique opportunity for the
introduction of advanced manufacturing technologies.
Continuous processing is considered to be one of the key technologies that can
provide significant innovation in the pharmaceutical sector also motivated by
the vision of developing “on demand” personalised medicines. In addition to
offering better product consistency, and overall process efficiency, continuous
manufacturing has the potential to provide more distributed and even mobile
manufacturing systems that could be located at the point of use, improving
access to novel medicines, opening new market opportunities, reducing costs,
driving innovation and speeding time to market. However, to be able to exploit
the advantages of continuous manufacturing processes in an industry
characterised by high value, high variety and low volume products obtained
through a network of distributed manufacturing systems, advances are required
in fundamental process understanding, continuous processing and equipment in
particular for chemical solids and in measurement, modeling and control
methodologies.
The presentation will provide an overview of the advantages and challenges,
including regulatory aspects, related to the continuous manufacturing of
pharmaceuticals, from synthesis to formulation of the final product. We will
provide a brief overview of aspects related to continuous production of active
pharmaceutical ingredients (API) and then focus on methodologies for the
continuous processing of slurries and solids, which present key challenges in
enabling the overall continuous manufacturing process. Crystallization is the
key unit operation that connects the primary (API synthesis) and secondary
(design of delivery form) manufacturing processes. The solid properties such as
shape and crystal size distribution (CSD) of the API obtained at the
crystallization step will strongly influence the efficiency of the secondary
manufacturing process. Modeling and control approaches for continuous
crystallization will be presented that allow better control of the product CSD.
Continuous secondary manufacturing of the final product from the API isolated
at the crystallization step has also received quite a bit of attention in the
industry and been the focus of research in the NSF Engineering Research Center
for Structured Organic Particulate Systems, a multi-university collaboration
with industry. The focus here again is on innovative use of on-line
measurement, process modelling and control, exceptional events management and
real time process management. Process configurations including the full range
of unit operations from powder feeding to tablet coating are under active
consideration. The rudiments of process flowsheet modelling for such operations
are beginning to be assembled offering the potential for design optimization.
The presentation will conclude with a brief overview of some additional
manufacturing innovations targeting small scale manufacturing configurations
suitable for delivery of individualized medicine.
Biographical Sketches
Zoltan K Nagy Biography:
Dr Nagy is a Professor of Chemical Engineering at Purdue University and also
holds a European Research Council Research Adjunct Professorship at Loughborough
University, UK, where he was a professor of process systems engineering and
Director of the Departmental Pharmaceutical Engineering Research Centre, before
joining Purdue in Fall 2012.
Dr Nagy has over 12 years of experience in advanced process control, process
analytical technologies and crystallization modeling and control approaches.
His current research focuses on the application of systems approaches and tools
in the design and robust control of batch and continuous crystallization
systems and integrated particulate manufacturing processes for pharmaceutical
applications. He has more than 200 publications in these areas, and has given
numerous invited talks at conferences, universities and companies worldwide.
Dr Nagy is the Founding Editor of the Pharmaceutical Engineering Subject area
of Chemical Engineering Research and Design, and associate editor for several
other three journals in the area of process control. Dr Nagy is member of the
stirring committee of the American Association for Crystallization
Technologies, and the Crystallization Working Party of the European Federation
of Chemical Engineers. He received major awards and best paper prizes from
IEEE, IFAC, European Federation of Chemical Engineering, Institute of Chemical
Engineering, Council of Chemical Research, Royal Academy of Engineering and the
European Research Council.
G.V. Rex Reklaitis Biography:
G.V. Rex Reklaitis is Burton and Kathryn Gedge Distinguished Professor of
Chemical Engineering at Purdue University and currently deputy director of the
ERC on Structured Organic Particulate Systems. At Purdue he has served as the
Head of the School of Chemical Engineering and Director of the Computer
Integrated Process Operations Center. His expertise lies in process systems engineering,
the application of information and computing technologies to process and
product design, process operations and supply chain management. Current
research interests include applications of process systems methodology to
improve pharmaceutical product design, development, manufacture and
administration as well as systems studies of integrated energy networks. He was
educated at the Illinois Institute of Technology (BS ChE), received MS and PhD
degrees from Stanford University, has held an NSF Postdoctoral fellowship
(Zurich, Switzerland) and Senior Fulbright Lectureship (Vilnius, Lithuania). He
is a member of the US National Academy of Engineering, fellow of AIChE, and
past Editor-in-Chief of Computers & Chemical Engineering. He has received
the Computing in Chemical Engineering Award (AICHE), the ChE Lectureship Award
(ASEE), the George Lappin and Van Antwerpen Awards (AIChE) and the Long Term
Achievements in Computer Aided Process Engineering Award of the European
Federation of Chemical Engineering and the Illinois Institute of Technology
Professional Achievement Award. He has served on the Board of Directors of
AICHE, the Council for Chemical Research and the CACHE Corporation. He has
published over 240 papers and book chapters and edited/authored eight books.
Multi-scale Approaches for
Optimizing Novel Hybrid Feedstock Energy Processes
Professor Christodoulos A. Floudas, Department of
Chemical and Biological Engineering, Princeton University
DATE: Tuesday, May 7th, 2013, 2-4 PM EDT
Abstract
Heavy dependence on petroleum and high greenhouse gas (GHG) emissions from the
production, distribution, and consumption of hydrocarbon fuels pose serious
challenges for the United States (US) transportation sector. Depletion of
domestic petroleum sources combined with a volatile global oil market prompt
the need to discover alternative fuel-producing technologies that utilize
domestically abundant sources. The primary aim in the discovery of hybrid
energy processes is to combine coal, biomass, and natural gas to meet the
United States transportation fuel demand.
The first part of this presentation will outline the needs and introduce novel
hybrid feedstock coal, biomass, and natural gas to liquids (CBGTL) process
alternatives. The second part will address important decisions at the process
design and process synthesis level. A thermochemical based process
superstructure, its mixed-integer nonlinear optimization (MINLP) model, and
systematic approaches for its global optimization will be discussed. The third
part will introduce a novel framework for the optimal energy supply chain of
CBGTL processes. The optimal network topology provides information on (i) the
optimal plant locations throughout the country, (ii) the locations of feedstock
sources, (iii) the interconnectivity between the feedstock source locations,
CBGTL plants locations, and the demand locations, (iv) the modes of
transportation used in each connection, and (v) the flow rate amounts of each
feedstock and product type. Life cycle analysis on the nationwide energy supply
chain shows that at least 50% reduction of GHG emissions is attainable.
Biographical Sketch
Dr. Floudas is the Stephen C. Macaleer ’63 Professor in Engineering and Applied
Science, Professor of Chemical and Biological Engineering at Princeton
University, Faculty in the Center for Quantitative Biology at Princeton University’s
Lewis-Sigler Institute, Associated Faculty in the Program of Computational and
Applied Mathematics at Princeton University, Department of Operations Research
and Financial Engineering at Princeton University, and the Andlinger Center for
Energy and the Environment. He earned his B.S.E. in 1982 at Aristotle
University of Thessaloniki, Greece, completed his Ph.D. in December 1985 at
Carnegie Mellon University. Professor Floudas is the author of two graduate
textbooks, Nonlinear Mixed-Integer Optimization (Oxford University Press,
1995), and Deterministic Global Optimization (Kluwer Academic Publishers,
2000). He has co-edited ten monographs/books, has over 270 refereed
publications, and is the chief co-editor of the Encyclopedia of Optimization
(Kluwer Academic Publishers, 2001; 2nd edition, Springer, 2008). He is the
recipient of numerous awards and honors for teaching and research that include
the NSF Presidential Young Investigator Award, 1988; the Engineering Council
Teaching Award, Princeton University, 1995; the Bodossaki Foundation Award in
Applied Sciences, 1997; the Best Paper Award in Computers and Chemical
Engineering, 1998; the Aspen Tech Excellence in Teaching Award, 1999; the 2001
AIChE Professional Progress Award for Outstanding Progress in Chemical
Engineering; the 2006 AIChE Computing in Chemical Engineering Award; the 2007
Graduate Mentoring Award, Princeton University; and Member of National Academy
of Engineering, 2011.
Process Synthesis for Sustainable
Energy Future
Professor Rakesh Agrawal, School of Chemical
Engineering, Purdue University
DATE: Thursday, October 3rd, 2013, 2-4 PM EDT
The
entire 70 page presentation
[2894 KB] may be downloaded in pdf format.
New! Listen to a recording of the entire presentation
(voice and slides).
Abstract
In a fossil-fuel deprived world, it is likely that all the basic human needs
will be met by renewable sources like solar energy. Among the needs,
transportation offers the greatest challenges, owing to its high energy-density
fuel requirements, which have traditionally been met by liquid hydrocarbon
fuels derived from fossil resources. Here, we present a detailed systems
analysis of the transportation sector, from which emerges an energy efficient
roadmap, based on the use of renewable carbon sources like biomass, solar
energy in the form of H2, heat and electricity, in conjunction with novel
processes for producing liquid fuels. In addition, some specific transition
solutions are also discussed.
In a sustainable energy future, availability of efficient hydrogen from solar
energy will be a key to the large scale production of chemicals and fuels. We
present process synthesis methodology to identify efficient processes for solar
hydrogen production. These processes, although not economical today, point us
in the direction where technical advancements are needed to enable a truly sustainable
future.
Finally, a grand challenge of solar energy use is its intermittency. Synthesis
of processes to store GWhr levels of energy for uninterrupted power grid supply
is also discussed.
Biographical Sketch
Rakesh Agrawal is Winthrop E. Stone Distinguished Professor, School of Chemical
Engineering, Purdue University. Previously, he was an Air Products Fellow at
Air Products and Chemicals, Inc., where he worked until 2004.
A major thrust of his research is related to energy issues and includes novel
processes for fabrication of low-cost solar cells, biomass and liquid fuel
conversion, and energy systems analysis. His research further includes
synthesis of muticomponent separation configurations including distillation,
membrane and adsorption based processes, basic and applied research in gas
separations, process development, gas liquefaction processes and cryogenics. He
was a member of the NRC Board on Energy and Environmental Systems (BEES) and a
member of the AIChE’s Board of Directors and also its Energy Commission. He has
published 116 technical papers and holds 118 U.S. and more than 500 foreign
patents. These patents are used in over one hundred chemical plants with total
capital expenditure in multibillion dollars.
He is a member of the US National Academy of Engineering, a Fellow of the
American Academy of Arts and Sciences and a foreign Fellow of the Indian
National Academy of Engineering. He is currently on the Technical Advisory
boards of five chemical companies. Agrawal received the 2010 National Medal of
Technology and Innovation from the U.S. President.
Dr. Agrawal received a B. Tech. from the Indian Institute of Technology, in
Kanpur, India; a M.Ch.E. from the University of Delaware, and an Sc.D. in
chemical engineering from the MIT.