Page 17 - Sustainability in the Process Industry Integration and Optimization
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                     important tool: balancing and flowsheeting simulation as a basis for
                     optimization. It is on this basis that an integrated approach to
                     optimization, Process Integration, is introduced. This approach is then
                     connected to optimal process synthesis and combinatorial graphs.
                     The important question of how to apply the Process Integration and
                     Optimization Technology arises and is dealt with. This is further
                     tackled and analyzed in the following chapters.
                        Chapter 2 deals with the basic outline and definitions of Process
                     Integration (PI). It begins with a historical and methodological
                     introduction, briefly reviewing refinements and extensions of PI over
                     its years of development. The thermodynamic roots of the Pinch
                     Technology and of targeting heat recovery are introduced, followed
                     by one of the key graphical constructions in the PI methodology:
                     Composite Curves (CCs) for targeting process heat recovery.
                     Supertargeting, or targeting for a full-fledged Heat Exchanger
                     Network (HEN), is the next logical step. These tools are used to assess
                     modifications of the Pinch idea for HEN retrofitting. Although PI
                     was initially based on Heat Integration, an important spin-off was
                     the development of integration for mass exchange and water
                     networks. The chapter concludes with remarks on the role of PI in
                     making industry sustainable.
                        Chapter 3 introduces the other key methodology used for
                     sustainable process design and synthesis: optimization. It presents a
                     general framework and workflow of model building and follow-up
                     optimization, including models that incorporate “black boxes” or
                     “gray boxes.” It is critical to understand both the meaning and the
                     mathematical formulation of optimization. Toward this end, the
                     following questions are answered: What is optimization? What are
                     the main classes of optimization problems? How are optimization
                     problems formulated mathematically? What are the conditions for
                     local or global optimality? This is followed by introducing
                     deterministic algorithms for solving continuous linear and nonlinear,
                     constrained and unconstrained, optimization problems. The most
                     popular optimization methods and algorithms that employ stochastic
                     search are also reviewed. The middle part of Chapter 3 is devoted to
                     model creation. It includes a detailed description of conceptual
                     modeling: extracting data about the operating units, identifying
                     network and topology data, constructing equations to represent the
                     processes, and finally choosing a right objective function. The last
                     part of this chapter discusses how to handle complexity and
                     nonlinearity as well as how to apply process insight when evaluating
                     model adequacy and precision.
                        Chapter 4 covers the core topic from which the development of PI
                     began: improving the energy efficiency of individual processes and
                     the PI extension into Total Sites. The chapter starts by introducing
                     heat exchange, heat recovery, and heat exchange matches so that
                     readers will be prepared for the remaining chapter content. The
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