Optimal design and optimization of sustainable chemical
The goal of this research project is to promote the concept of green chemistry by developing systematic tools for the optimal design, optimization and planning of sustainable chemical processes. Specifically, we will investigate the combined use of mathematical programming theory, process simulation and life cycle assessment principles to automatically generate the best process alternatives that may be implemented to achieve environmental improvements. There are ongoing collaborations with leading chemical companies and international research centers that will be used as a test bed to validate our modeling framework and solution strategy.
1. Optimization of reverse osmosis plants integrated with solar panels.
2. Design of production facilities of nanoparticles.
3. Design of supply chains for hydrogen production.
4. Design of petrochemical supply chains.
5. Design of supply chains for the production of ethanol from sugar cane.
Background and state of the art:
This research project will focus on developing novel global optimization techniques for the solution of a special type of nonlinear and mixed integer nonlinear programming problems (NLP and MINLP) arising in many industrial engineering and bioengineering applications. From the algorithmic point of view, the objective is to investigate efficient solution methods based on the outer approximation algorithm for global optimization. However, standard methods often fail to identify the global optimum in the presence of multiple local optima.
This project will develop decision-making tools based on the combined use of multi-objective optimization, life cycle assessment and stochastic programming for the design and planning of sustainable processes under uncertainty. To achieve the goals of the project, we will use multi-objective stochastic programming tools combined with life cycle assessment and dimensionality reduction methods for multi-criteria problems. Stochastic programming will assist decision-makers in the face of uncertainty. Life cycle assessment tools will be employed to assess process alternatives from an environmental perspective considering all the stages in the life cycle of the process. Finally, objective reduction techniques based on statistics and optimality criteria will allow for the identification of redundant environmental objectives that will be removed from the optimization.
We will apply these tools to different case studies that have attracted an increasing interest in the recent past. Particularly, we will focus on applications found in the energy sector, highlighting the advantages of the proposed methods as compared to traditional process design tools.
Project contribution and methodology:
(1) the explicit treatment of different sources of uncertainty that affect the
environmental impact calculations;
(2) the systematic analysis of the mathematical structure of multi-objective problems arising in environmental engineering, which will allow us to identify redundant environmental metrics that can be omitted from the optimization without changing the associated mathematical structure; and
(3) the development of algorithms to expedite the search for optimal solutions in the environmental impact minimization of process industries.
The ideal candidate:
Candidates should have a bachelor and/or a master degree on Chemical Engineering, Computer Science or Mathematics. Additional background, knowledge or experience in process modeling as well as basic knowledge of standard modeling software packages (e.g. Aspen Plus, gPROMS, Matlab, HYSYS, GAMS...) will be considered as a valuable asset. The bachelor or Masters degree must be obtained before August 31st, 2010 to be eligible.
Both positions (master and PhD level) are fully funded. The master level offer covers 10000 €/year, while the PhD covers 15000 €/years.
Interested candidates should send an electronic version of their CV and an academic expedient (subjects, credits and grades) to laureano.jimenez en urv.cat. Tel: + 34 977 55 8643
Skype accounts will be highly appreciated because they offer the possibility to have a personal on-line interview.
Finishing the project:
The SUSCAPE group is an internationally recognized leader in process systems engineering that focuses on process simulation and advanced mathematical programming techniques applied to multi-criteria problems. Our group is characterized by an inspiring environment dedicated to research on sustainable process design. The PhD program supports short stays in leading international research groups in USA (Carnegie Mellon University) and Europe (Imperial College London). Once finished the PhD, the candidate will obtain a high degree in modeling, a topic that can be applied to very broad domains.
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