Lorenz Biegler

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Lorenz Biegler
EducationPhD. (Chemical Engineering 1981), MS. (1979), BS. (1977)
Alma mater University of Wisconsin, Illinois Institute of Technology
Known for IPOPT, Systematic methods for chemical process design, Nonlinear programming: concepts, algorithms, and applications to chemical processes
Awards Humboldt Prize,INFORMS Computing Society Prize, Presidential Young Investigator Award
Scientific career
Fields Optimization, Chemical engineering
Institutions Carnegie Mellon University
Doctoral advisor Dick Hughes

Lorenz Theodor Biegler is the professor of Covestro University Professor, in the Chemical Engineering department at Carnegie Mellon University. He was previously the department head of Chemical Engineering at Carnegie Mellon from 2013 to 2018. His research interests lie in optimization of differential and algebraic systems, computer aided process engineering (CAPE), reactor network synthesis, and algorithms for constrained, nonlinear process control. [1] He has written two widely used textbooks, and over 400 scientific publications.

Contents

Work

In 1985 Biegler was awarded the Presidential Young Investigator Award, which lead to him starting the Center for Advanced Process Decision-Making at Carnegie Mellon University, along with Ignacio Grossmann and Art Westerberg. [2] Biegler has played a major role in the computer aided process engineering, has received various awards including the Computing in Chemical Engineering Award from the American Institute of Chemical Engineers, an honorary doctorate from the Technical University of Berlin, the INFORMS Computing Society Prize for developing IPOPT, an open source program for large-scale nonlinear optimization. [3] [4]

Biegler was elected a member of the National Academy of Engineering in 2013 for contributing to large-scale nonlinear optimization theory and algorithms for application to process optimization, design and control.

Related Research Articles

Process engineering is the understanding and application of the fundamental principles and laws of nature that allow humans to transform raw material and energy into products that are useful to society, at an industrial level. By taking advantage of the driving forces of nature such as pressure, temperature and concentration gradients, as well as the law of conservation of mass, process engineers can develop methods to synthesize and purify large quantities of desired chemical products. Process engineering focuses on the design, operation, control, optimization and intensification of chemical, physical, and biological processes. Process engineering encompasses a vast range of industries, such as agriculture, automotive, biotechnical, chemical, food, material development, mining, nuclear, petrochemical, pharmaceutical, and software development. The application of systematic computer-based methods to process engineering is "process systems engineering".

Model predictive control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. In recent years it has also been used in power system balancing models and in power electronics. Model predictive controllers rely on dynamic models of the process, most often linear empirical models obtained by system identification. The main advantage of MPC is the fact that it allows the current timeslot to be optimized, while keeping future timeslots in account. This is achieved by optimizing a finite time-horizon, but only implementing the current timeslot and then optimizing again, repeatedly, thus differing from a linear–quadratic regulator (LQR). Also MPC has the ability to anticipate future events and can take control actions accordingly. PID controllers do not have this predictive ability. MPC is nearly universally implemented as a digital control, although there is research into achieving faster response times with specially designed analog circuitry.

Hsiang-Tsung Kung is a Taiwanese-born American computer scientist. He is the William H. Gates professor of computer science at Harvard University. His early research in parallel computing produced the systolic array in 1979, which has since become a core computational component of hardware accelerators for artificial intelligence, including Google's Tensor Processing Unit (TPU). Similarly, he proposed optimistic concurrency control in 1981, now a key principle in memory and database transaction systems, including MySQL, Apache CouchDB, Google's App Engine, and Ruby on Rails. He remains an active researcher, with ongoing contributions to computational complexity theory, hardware design, parallel computing, routing, wireless communication, signal processing, and artificial intelligence.

IPOPT, short for "Interior Point OPTimizer, pronounced I-P-Opt", is a software library for large scale nonlinear optimization of continuous systems. It is written in Fortran and C and is released under the EPL. IPOPT implements a primal-dual interior point method, and uses line searches based on Filter methods. IPOPT can be called from various modeling environments and C.

John Emory Dennis, Jr. is an American mathematician who has made major contributions in mathematical optimization. Dennis is currently a Noah Harding professor emeritus and research professor in the department of computational and applied mathematics at Rice University in Houston, Texas. His research interests include optimization in engineering design. He is the founder and editor-in-chief of the SIAM Journal on Optimization. In 2010, he was elected a Fellow of the Society for Industrial and Applied Mathematics.

Scheduling is the process of arranging, controlling and optimizing work and workloads in a production process or manufacturing process. Scheduling is used to allocate plant and machinery resources, plan human resources, plan production processes and purchase materials.

ASCEND is an open source, mathematical modelling chemical process modelling system developed at Carnegie Mellon University since late 1978. ASCEND is an acronym which stands for Advanced System for Computations in Engineering Design. Its main uses have been in the field of chemical process modelling although its capabilities are general.

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References

  1. "Lorenz T. Beigler". Carnegie Mellon University. Retrieved January 19, 2021.
  2. "History of CAPD". CAPD - Center for Advanced Process Decision-Making. Carnegie Mellon University. Retrieved October 4, 2020.
  3. "Lorenz T. Beigler". Informs. Retrieved October 4, 2020.
  4. "Computing in Chemical Engineering Award". AICHE. Retrieved January 19, 2021.