Paul I. Barton mainly focuses on Mathematical optimization, Process engineering, Nonlinear system, Optimization problem and Algorithm. The various areas that Paul I. Barton examines in his Mathematical optimization study include Upper and lower bounds and Bounding overwatch. His research integrates issues of Natural gas, Mixing and Coal in his study of Process engineering.
His Nonlinear system study deals with Numerical analysis intersecting with Sequence and Approximation algorithm. In general Optimization problem study, his work on Discrete optimization often relates to the realm of Convexity and Population, thereby connecting several areas of interest. In the subject of general Algorithm, his work in Computational complexity theory is often linked to Cost comparison, thereby combining diverse domains of study.
His scientific interests lie mostly in Mathematical optimization, Applied mathematics, Global optimization, Nonlinear system and Process engineering. Paul I. Barton regularly links together related areas like Nonlinear programming in his Mathematical optimization studies. Paul I. Barton works mostly in the field of Applied mathematics, limiting it down to topics relating to Ordinary differential equation and, in certain cases, Ode, as a part of the same area of interest.
His Global optimization research incorporates themes from Function, Interval arithmetic and Integer. His work carried out in the field of Nonlinear system brings together such families of science as Upper and lower bounds and Interval. His work deals with themes such as Batch processing, Heat exchanger and Process, which intersect with Process engineering.
Paul I. Barton mostly deals with Mathematical optimization, Applied mathematics, Sensitivity, Global optimization and Process engineering. His Mathematical optimization study incorporates themes from Process modeling, Interval, Bounding overwatch and Nonlinear system. His Applied mathematics research includes themes of Interval arithmetic, Semidefinite programming and Ordinary differential equation.
His work in Sensitivity addresses subjects such as Optimal control, which are connected to disciplines such as Discretization. In Global optimization, Paul I. Barton works on issues like Differentiable function, which are connected to Function. His Process engineering research is multidisciplinary, relying on both Heat exchanger, Refrigerant and Nonlinear programming.
His primary scientific interests are in Mathematical optimization, Optimization problem, Implicit function, Differential algebraic equation and Process engineering. His Mathematical optimization research integrates issues from Applied mathematics, Hybrid system, Ordinary differential equation and Sensitivity. The study incorporates disciplines such as Dynamic simulation, Robustness, Control theory and Time horizon in addition to Optimization problem.
The concepts of his Implicit function study are interwoven with issues in Automatic differentiation, Differentiable function, Smoothness and Differential equation. His Differential algebraic equation study integrates concerns from other disciplines, such as Differential, Algebraic equation and Lipschitz continuity. His study looks at the relationship between Process engineering and fields such as Heat exchanger, as well as how they intersect with chemical problems.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
End‐to‐End Continuous Manufacturing of Pharmaceuticals: Integrated Synthesis, Purification, and Final Dosage Formation
Salvatore Mascia;Patrick L. Heider;Haitao Zhang;Richard Lakerveld.
Angewandte Chemie (2013)
Economic Analysis of Integrated Continuous and Batch Pharmaceutical Manufacturing: A Case Study
Spencer D. Schaber;Dimitrios I. Gerogiorgis;Rohit Ramachandran;James M. B. Evans.
Industrial & Engineering Chemistry Research (2011)
Modeling of combined discrete/continuous processes
P. I. Barton;C. C. Pantelides.
Aiche Journal (1994)
Efficient sensitivity analysis of large-scale differential-algebraic systems
William F. Feehery;John E. Tolsma;Paul I. Barton.
Applied Numerical Mathematics (1997)
Optimally-reduced kinetic models: reaction elimination in large-scale kinetic mechanisms
Binita Bhattacharjee;Douglas A. Schwer;Paul I. Barton;William H. Green.
Combustion and Flame (2003)
McCormick-Based Relaxations of Algorithms
Alexander Mitsos;Benoit Chachuat;Paul I. Barton.
Siam Journal on Control and Optimization (2009)
State event location in differential-algebraic models
Taeshin Park;Paul I. Barton.
ACM Transactions on Modeling and Computer Simulation (1996)
Modeling, simulation, sensitivity analysis, and optimization of hybrid systems
Paul I. Barton;Cha Kun Lee.
ACM Transactions on Modeling and Computer Simulation (2002)
The modelling and simulation of combined discrete/continuous processes
Paul Inigo Barton.
Parametric sensitivity functions for hybrid discrete/continuous systems
Santos Galán;William F. Feehery;Paul I. Barton.
Applied Numerical Mathematics (1999)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: