(6am) Multi-Scale Process Systems Engineering

In this poster session, I
will discuss my Ph.D. work in the area of Process Systems Engineering (PSE) at
Carnegie Mellon University (advisor: Dr. Ignacio E. Grossmann), the research topics
and projects I am proposing to pursue, and my teaching interests and
experience. For more information, please visit my website: http://bacalfa.com/.

Research

Figure 1. Multiple scales in Process
Systems Engineering (PSE) research.

My Ph.D. research focused on
the "large" scale top blocks in Figure 1. I integrated and efficiently
solved planning and scheduling models for a network of batch plants, and
developed data-driven approaches for
modeling uncertainty in Enterprise-wide Optimization (EWO) problems [1-8]. I am
interested in developing PSE methods (modeling, simulation, optimization, and
control) to solve multi-scale problems of practical importance.

á      
Large Scale: novel data-driven models for uncertainty in sales and operations
planning; multilevel optimization with contracts and pricing.

á      
Intermediate Scale: reduced-order modeling and
optimization; analysis of sustainable
technologies (e.g., solar fuels); material and energy integration through water
and wastewater network optimization (e.g, water desalination, renewables).

á       Small Scale: property
prediction and computer-aided material
design (e.g., crystals) via optimal inverse problems; microkinetics and
optimal catalyst design.

I received the 2015 Ken
Meyer Award for Excellence in Graduate Research, which is given by the
Department of Chemical Engineering at CMU in which the faculty base their
selection of the student on research quality, productivity, recognition, and
impact.

Teaching

I had extensive teaching
experience as a TA at CMU. I prepared several teaching materials, and gave
guest lectures and tutorials. I am particularly interested in enhancing the
students' exposure to computing, as well as helping them develop teamwork and
communication skills. In addition to process design, I am also very interested
in teaching introduction to chemical engineering, numerical methods, thermodynamics,
and unit operations.

I received the 2012 Mark
Dennis Karl Outstanding Graduate Teaching Award, which is given by the
Department of Chemical Engineering at CMU to a student judged by the faculty to
have done an outstanding job as a teaching assistant.

References

[1] B. A.
Calfa, A. Agarwal, S. J. Bury, J. M. Wassick, and I. E. Grossmann. "Data-Driven
Simulation and Optimization Approaches to Incorporate Production Variability in
Sales and Operations Planning". In: Industrial & Engineering Chemistry
Research. (2015). Just Accepted. DOI: 10.1021/acs.iecr.5b01273.

[2] B. A.
Calfa and I. E. Grossmann. "Optimal Procurement Contract Selection with Price
Optimization under Uncertainty for Process Networks". In: Computers &
Chemical Engineering. (2015). Submitted.

[3] B. A.
Calfa, I. E. Grossmann, A. Agarwal, S. J. Bury, and J. M. Wassick. "Data-Driven
Individual and Joint Chance-Constrained Optimization via Kernel Smoothing". In:
Computers & Chemical Engineering. 78.1 (2015), pp. 51–69.

[4] I. E.
Grossmann, R. M. Apap, B. A. Calfa, P. García-Herreros, and Q. Zhang.
"Recent Advances in Mathematical Programming Techniques for the Optimization of
Process Systems under Uncertainty". In: 12th International Symposium on Process
Systems Engineering and 25th European Symposium on Computer Aided Process
Engineering. Ed. by Jakob K. Huusom Krist V. Gernaey and Rafiqul Gani. To
appear in Proceedings. . 2015.

[5] B. A.
Calfa. A Memory-Efficient Implementation of Multi-Period Two- and Multi-Stage
Stochastic Programming Models. Carnegie Mellon University. Technical Report,
2014. URL: http://repository.cmu.edu/cheme/246/.

[6] B. A.
Calfa, A. Agarwal, I. E. Grossmann, and J. M. Wassick. "Data-Driven Multi-Stage
Scenario Tree Generation via Statistical Property and Distribution Matching".
In: Computers & Chemical Engineering. 68.1 (2014), pp. 7–23.

[7] I. E.
Grossmann, B. A. Calfa, and P. García-Herreros. "Evolution of Concepts
and Models for Quantifying Resiliency and Flexibility of Chemical Processes".
In: Computers & Chemical Engineering. 70 (2014), pp. 22–34.

[8] B. A.
Calfa, A. Agarwal, I. E. Grossmann, and J. M. Wassick. "Hybrid
Bilevel-Lagrangean Decomposition Scheme for the Integration of Planning and
Scheduling of a Network of Batch Plants". In: Industrial & Engineering
Chemistry Research. 52.5 (2013), pp. 2152–2167.