A Guide To Chemical Engineering Process Design ... __TOP__
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A Guide to Chemical Engineering Process Design ...
This book is sold as a digital e-book, and is intended for teaching process design to chemical engineers in their senior undergraduate year to smooth the transition from academic to professional life. While intended for classroom use, this text is also a useful reference for any engineering professional interested in process design.
Optimization and sensitivity analysis are key aspects of successful process design. Optimizing a process maximizes project value and plant performance, minimizes project cost, and facilitates the selection of the best components (Towler and Sinnott, 2013).
Economic optimization is the process of finding the condition that maximizes financial return or, conversely, minimizes expenses. The factors affecting the economic performance of the design include the types of processing technique and equipment used, arrangement, and sequencing of the processing equipment, and the actual physical parameters for the equipment. The operating conditions are also of prime concern.
A second type of process variable is the dependent variable; a group of variables influenced by process constraints. Common examples of process constraints include process operability limits, reaction chemical species dependence, and product purity and production rate. Towler & Sinnott define equality and inequality constraints (Towler, 2012). Equality constraints are the laws of physics and chemistry, design equations, and mass/energy balances:
For example, a distillation column that is modeled with stages assumed to be in phase equilibrium often has several hundred MESH (material balance, equilibrium, summation of mole fractions, and heat balance) equations. However, in the implementation of most simulators, these equations are solved for each process unit, given equipment parameters and steam variables. Hence, when using these simulators, the equality constraints for the process units are not shown explicitly in the nonlinear program. Given values for the design variables, the simulators call upon these subroutines to solve the appropriate equations and obtain the unknowns that are needed to perform the optimization (Seider et al., 2004).
Parametric optimization deals with process operating variables and equipment design variables other than those strictly related to structural concerns. Some of the more obvious examples of such decisions are operating conditions, recycle ratios, and steam properties such as flow rates and compositions. Small changes in these conditions or equipment can have a diverse impact on the system, causing parametric optimization problems to contain hundreds of decision variables. It is therefore more efficient to analyze the more influential variables effect on the overall system. Done properly, a balance is struck between increased difficulty of high-variable-number optimization and optimization accuracy (Seider et al., 2004).
Simultaneous optimization of the many parameters present in a chemical process design can be a daunting task due to the large number of variables that can be present in both integer and continuous form, the non-linearity of the property prediction relationships and performance models, and frequent ubiquity of recycle. It is therefore common to seek out suboptimizations for some of the variables, so as to reduce the dimensionality of the problem (Seider et al., 2004). While optimizing sub-problems usually does not lead to overall optimum, there are instances for which it is valid in a practical, economic sense. Care must always be taken to ensure that subcomponents are not optimized at the expense of other parts of the plant.
The value of x is then increased or decreased by successive steps of h until the optimum is passed. In engineering design problems it is almost always possible to state upper and lower bounds for every parameter, so unrestricted search methods are not widely used in design.
Design optimization and sensitivity analysis are essential to designing and operating a successful chemical process. Optimization can be tricky due to high levels of uncertainty and magnitude of variables, but can help minimize costs and increase efficiency. Chemical engineers need to understand the optimization methods, the role of constraints in limiting designs, recognize design trade-offs, and understand the pitfalls of their analysis. In a similar respect, sensitivity analysis is a way of examining the effects of uncertainties in the forecasts on the viability of a project. If an engineer can optimize a process and perform a sensitivity analysis, the project will be cost effective and run more smoothly.
Chemical engineering is specialization concerned with the application of chemical research to the production of chemical materials and products. Many chemical engineers use this knowledge in jobs that include:
More than ever, effective design is the focal point of sound chemical engineering. Analysis, Synthesis, and Design of Chemical Processes, Fifth Edition, presents design as a creative process that integrates the big-picture and small details, and knows which to stress when and why. Realistic from start to finish, it moves readers beyond classroom exercises into open-ended, real-world problem solving. The authors introduce up-to-date, integrated techniques ranging from finance to operations, and new plant design to existing process optimization.
The fifth edition includes updated safety and ethics resources and economic factors indices, as well as an extensive, new section focused on process equipment design and performance, covering equipment design for common unit operations, such as fluid flow, heat transfer, separations, reactors, and more.
In chemical engineering, process design is the choice and sequencing of units for desired physical and/or chemical transformation of materials. Process design is central to chemical engineering, and it can be considered to be the summit of that field, bringing together all of the field's components.
Process designers typically write operating manuals on how to start-up, operate and shut-down the process. They often also develop accident plans and projections of process operation on the environment.
There are several considerations that need to be made when designing any chemical process unit. Design conceptualization and considerations can begin once product purities, yields, and throughput rates are all defined.
Designers usually do not start from scratch, especially for complex projects. Often the engineers have pilot plant data available or data from full-scale operating facilities. Other sources of information include proprietary design criteria provided by process licensors, published scientific data, laboratory experiments, and suppliers of feedstocks and utilities.
Design starts with process synthesis - the choice of technology and combinations of industrial units to achieve goals. More detailed design proceeds as other engineers and stakeholders sign off on each stage: conceptual to detailed design.
Simulation software is often used by design engineers. Simulations can identify weaknesses in designs and allow engineers to choose better alternatives. However, engineers still rely on heuristics, intuition, and experience when designing a process. Human creativity is an element in complex designs.
The chemical engineering curriculum is designed to give graduates a broad background in chemical engineering processes and to prepare them to become practicing engineers. Graduates are prepared for positions in operations, development, design, construction, and management of chemical plants, environmental processes, life sciences, and materials processing. These industries convert raw materials, such as ethylene and other organic feedstocks, via chemical and physical changes to produce economically desirable products such as plastics, detergents, paints, and adhesives. Students with this background are also prepared for graduate school in engineering and science as well as for any professional school. The Bachelor of Science in Chemical Engineering program is accredited by the Engineering Accreditation Commission of ABET, 041b061a72