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This book presents a comprehensive optimization-based theory and framework that exploits the synergistic interactions and tradeoffs between process design and operational decisions that span different time scales. Conventional methods in the process industry often isolate decision making mechanisms with a hierarchical information flow to achieve tractable problems, risking suboptimal, even infeasible operations. In this book, foundations of a systematic model-based strategy for simultaneous process design, scheduling, and control optimization is detailed to achieve reduced cost and improved energy consumption in process systems. The material covered in this book is well suited for the use of industrial practitioners, academics, and researchers. In Chapter 1, a historical perspective on the milestones in model-based design optimization techniques is presented along with an overview of the state-of-the-art mathematical tools to solve the resulting complex problems. Chapters 2 and 3 discuss two fundamental concepts that are essential for the reader. These concepts are (i) mixed integer dynamic optimization problems and two algorithms to solve this class of optimization problems, and (ii) developing a model based multiparametric programming model predictive control. These tools are used to systematically evaluate the tradeoffs between different time-scale decisions based on a single high-fidelity model, as demonstrated on (i) design and control, (ii) scheduling and control, and (iii) design, scheduling, and control problems. We present illustrative examples on chemical processing units, including continuous stirred tank reactors, distillation columns, and combined heat and power regeneration units, along with discussions of other relevant work in the literature for each class of problems.
This book introduces models and methodologies that can be employed towards making the Industry 4.0 vision a reality within the process industries, and at the same time investigates the impact of uncertainties in such highly integrated settings. Advances in computing power along with the widespread availability of data have led process industries to consider a new paradigm for automated and more efficient operations. The book presents a theoretically proven optimal solution to multi-parametric linear and mixed-integer linear programs and efficient solutions to problems such as process scheduling and design under global uncertainty. It also proposes a systematic framework for the uncertainty-aware integration of planning, scheduling and control, based on the judicious coupling of reactive and proactive methods. Using these developments, the book demonstrates how the integration of different decision-making layers and their simultaneous optimisation can enhance industrial process operations and their economic resilience in the face of uncertainty.
Synthesis and Operability Strategies for Computer-Aided Modular Process intensification presents state-of-the-art methodological developments and real-world applications for computer-aided process modeling, optimization and control, with a particular interest on process intensification systems. Each chapter consists of basic principles, model formulation, solution algorithm, and step-by-step implementation guidance on key procedures. Sections cover an overview on the current status of process intensification technologies, including challenges and opportunities, detail process synthesis, design and optimization, the operation of intensified processes under uncertainty, and the integration of design, operability and control. Advanced operability analysis, inherent safety analysis, and model-based control strategies developed in the community of process systems engineering are also introduced to assess process operational performance at the early design stage. - Includes a survey of recent advances in modeling, optimization and control of process intensification systems - Presents a modular synthesis approach for process design, integration and material selection in intensified process systems - Provides advanced process operability, inherent safety tactics, and model-based control analysis approaches for the evaluation of process operational performance at the conceptual design stage - Highlights a systematic framework for multiscale process design intensification integrated with operability and control - Includes real-word application examples on intensified reaction and/or separation systems with targeted cost, energy and sustainability improvements
Introduction to Engineering Design is a practical, straightforward workbook designed to systematize the often messy process of designing solutions to open-ended problems. IFrom learning about the problem to prototyping a solution, this workbook guides developing engineers and designers through the iterative steps of the engineering design process. Created in a freshman engineering design course over ten years, this workbook has been refined to clearly guide students and teams to success. Together with a series of instructional videos and short project examples, the workbook has space for teams to execute the engineering design process on a challenge of their choice. Designed for university students as well as motivated learners, the workbook supports creative students as they tackle important problems. IIntroduction to Engineering Design is designed for educators looking to use project-based engineering design in their classroom.
While more and more undergraduate engineering programs are moving toward a multi-disciplinary capstone experience, there remains a need for a suitable textbook. The present text seeks to meet that need by providing a student friendly step by step template for this important and culminating academic journey beginning with the student design team's first meeting with the client to the final report and presentation. The text provides a wide range of design tools, a discussion of various design methodologies, a brief history of modern engineering, and a substantive consideration of engineering ethics. In addition, chapters are included on communication, team building and dealing with the inevitable obstacles that students encounter. Throughout the text, emphasis is placed upon the issues of environmental impact and the importance of diversity.
As the existence of all life forms on our planet is currently in grave danger from the climate emergency caused by Homo sapiens, the words "sustainability" and "eco-responsibility" have entered the daily-use vocabularies of scientists, engineers, economists, business managers, industrialists, capitalists, and policy makers. Normal activities undertaken for the design of products and systems in industrialisms must be revamped. As the bioworld is a great resource for eco-responsible design activities, an overview of biologically inspired design is presented in this book in simple terms for anyone with even high-school education. Beginning with an introduction to the process of design in industry, the book presents the bioworld as a design resource along with the rationale for biologically inspired design. Problem-driven and solution-driven approaches for biologically inspired design are described next. The last chapter is focused on biologically inspired design for environment.
The intention of this book is to demonstrate that curriculum design is a profoundly philosophical exercise that stems from perceptions of the mission of higher education. Since the curriculum is the formal mechanism through which intended aims are achieved, philosophy has a profound role to play in the determination of aims. It is argued that the curriculum is far more than a list of subjects and syllabi, or that it is the addition, and subtraction, of items from a syllabus, or whether this subject should be added and that subject taken away. This book explores how curricular aims and objectives are developed by re-examining the curriculum of higher education and how it is structured in the light of its increasing costs, rapidly changing technology, and the utilitarian philosophy that currently governs the direction of higher education. It is concluded that higher education should be a preparation for and continuing support for life and work, a consequence of which is that it has to equip graduates with skill in independent learning (and its planning), and reflective practice. A transdisciplinary curriculum with technology at its core is deduced that serves the four realities of the person, the job, technology, and society.
All educators bring to their work preconceived ideas of what the curriculum should be and how students learn. Seldom are they thought through. Since without an adequate philosophical base it is difficult to bring about desirable changes in policy and practice, it is necessary that educators have defensible philosophies of engineering education. This point is illustrated by recent debates on educational outcomes which can be analysed in terms of competing curriculum ideologies. While these ideologies inform the development of a philosophy of engineering education they do so in light of a philosophy of engineering for such a philosophy focuses on what engineering is, and in particular how it differs from science. This is addressed in this study through consideration of the differences in the modes of abstraction required for the pursuit of science on the one hand, and the pursuit of engineering design, on the other hand. It is shown that a philosophy of engineering is not a philosophy of science or a philosophy of engineering education, but it is from a philosophy of engineering that a philosophy of engineering education is drawn. Uncertainty is shown to be a key characteristic of engineering practice. A way of formulating a philosophy of engineering is to consider it through the classical prism that splits the subject into five divisions, namely epistemology, metaphysics, logic, ethics aesthetics. Additionally, "behaviour" also characterizes the practice of engineering.
As long as humans have existed on the planet, they have looked at the world around them and wondered about much of what they saw. This book covers 21 different phenomena that have been observed in nature and puzzled about for decades.Only recently, with the development of the microscopes and other tools that allow us to study, evaluate, and test these observed phenomena at the molecular and atomic scale, have researchers been able to understand the science behind these observations. From the strength of a marine sponge found at the depths of the oceans, to the insect-hydroplaning surface of the edge of a plant, to the intricacies of the eyes of a moth, nanotechnology has allowed science to define and understand these amazing capabilities. In many cases, this new understanding has been applied to products and applications that benefit humans and the environment. For each of the five ecosystems— the ocean, insects, flora, fauna, and humans—the observations, study and understanding, and applications will be covered. The relationship between the more easily observed macro level and understanding what is found at the nanoscale will also be discussed.
This book is aimed to help instructional designers, science game designers, science faculty, lab designers, and content developers in designing interactive learning experiences using emerging technologies and cyberlearning. The proposed solutions are for undergraduate and graduate scientific communication, engineering courses, scientific research communication, and workforce training. Reviewing across the science education literature reveals various aspects of unresolved challenges or inabilities in the visualization of scientific concepts. Visuospatial thinking is the fundamental part of learning sciences; however, promoting spatial thinking has not been emphasized enough in the educational system (Hegarty, 2014). Cognitive scientists distinguish between the multiple aspects of spatial ability and stresse that various problems or disciplines require different types of spatial skills. For example, the spatial ability to visualize anatomy cross-sections is significantly associated with mental rotation skills. The same is true for physical problems that often deal with spatial representations. However, most of the physics problems are marked by dynamicity, and visualizing dynamicity is inferred by the integrations of different participating components in the system. Therefore, what is needed for learning dynamicity is visualizing the mental animation of static episodes. This book is a leap into designing framework for using mixed reality (XR) technologies and cyberlearning in communicating advanced scientific concepts. The intention is to flesh out the cognitive infrastructure and visuospatial demands of complex systems and compare them in various contexts and disciplines. The practical implementation of emerging technology can be achieved by foreseeing each XR technology’s affordances and mapping those out to the cognitive infrastructure and visuospatial demands of the content under development.