Download or read book Modeling Simulation and Optimization of Complex Processes HPSC 2018 written by Hans Georg Bock and published by Springer Nature. This book was released on 2020-12-01 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume highlights a selection of papers presented at the 7th International Conference on High Performance Scientific Computing, which took place in Hanoi, Vietnam, during March 19-23, 2018. The conference has been organized by the Institute of Mathematics of the Vietnam Academy of Science and Technology, the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University and the Vietnam Institute for Advanced Study in Mathematics. The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered include numerical simulation, methods for optimization and control, machine learning, parallel computing and software development, as well as the applications of scientific computing in mechanical engineering, airspace engineering, environmental physics, decision making, hydrogeology, material science and electric circuits.

Download or read book Business Optimization Using Mathematical Programming written by Josef Kallrath and published by Springer Nature. This book was released on 2021-08-31 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a structured approach to formulate, model, and solve mathematical optimization problems for a wide range of real world situations. Among the problems covered are production, distribution and supply chain planning, scheduling, vehicle routing, as well as cutting stock, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with valid inequalities and symmetry during the modeling phase, but also data interfacing and visualization of results in a more and more digitized world. The broad range of ideas and approaches presented helps the reader to learn how to model a variety of problems from process industry, paper and metals industry, the energy sector, and logistics using mathematical optimization techniques.

Download or read book Process Modelling and Simulation written by César de Prada and published by MDPI. This book was released on 2019-09-23 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

Download or read book Rosenbrock Wanner Type Methods written by Tim Jax and published by Springer Nature. This book was released on 2021-07-24 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the development of the Rosenbrock—Wanner methods from the origins of the idea to current research with the stable and efficient numerical solution and differential-algebraic systems of equations, still in focus. The reader gets a comprehensive insight into the classical methods as well as into the development and properties of novel W-methods, two-step and exponential Rosenbrock methods. In addition, descriptive applications from the fields of water and hydrogen network simulation and visual computing are presented.

Download or read book Modeling Simulation and Optimization of Supercritical and Subcritical Fluid Extraction Processes written by Zainuddin A. Manan and published by John Wiley & Sons. This book was released on 2021-11-02 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a complete guide on tools and techniques for modeling of supercritical and subcritical fluid extraction (SSFE) processes and phenomena. It provides details for SSFE from managing the experiments to modeling and optimization. It includes the fundamentals of SSFE as well as the necessary experimental techniques to validate the models. The optimization section includes the use of process simulators, conventional optimization techniques and state-of-the-art genetic algorithm methods. Numerous practical examples and case studies on the application of the modeling and optimization techniques on the SSFE processes are also provided. Detailed thermodynamic modeling with and without co-solvent and non equilibrium system modeling is another feature of the book.

Download or read book Reinforcement Learning for Optimal Feedback Control written by Rushikesh Kamalapurkar and published by Springer. This book was released on 2018-05-10 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement Learning for Optimal Feedback Control develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. In order to achieve learning under uncertainty, data-driven methods for identifying system models in real-time are also developed. The book illustrates the advantages gained from the use of a model and the use of previous experience in the form of recorded data through simulations and experiments. The book’s focus on deterministic systems allows for an in-depth Lyapunov-based analysis of the performance of the methods described during the learning phase and during execution. To yield an approximate optimal controller, the authors focus on theories and methods that fall under the umbrella of actor–critic methods for machine learning. They concentrate on establishing stability during the learning phase and the execution phase, and adaptive model-based and data-driven reinforcement learning, to assist readers in the learning process, which typically relies on instantaneous input-output measurements. This monograph provides academic researchers with backgrounds in diverse disciplines from aerospace engineering to computer science, who are interested in optimal reinforcement learning functional analysis and functional approximation theory, with a good introduction to the use of model-based methods. The thorough treatment of an advanced treatment to control will also interest practitioners working in the chemical-process and power-supply industry.

Download or read book Modeling Simulation and Optimization written by Biplab Das and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected peer-reviewed papers presented at the International Conference on Modeling, Simulation and Optimization, organized by National Institute of Technology, Silchar, Assam, India, during 3-5 August 2020. The book covers topics of modeling, simulation and optimization, including computational modeling and simulation, system modeling and simulation, device/VLSI modeling and simulation, control theory and applications, modeling and simulation of energy system and optimization. The book disseminates various models of diverse systems and includes solutions of emerging challenges of diverse scientific fields.

Download or read book Process Modelling and Simulation written by Jose Luis Pitarch and published by . This book was released on 2019 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

Download or read book Modeling Simulation and Optimization of a Production Line written by and published by . This book was released on 2000 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling and Optimization of Process Systems for Unconventional Technologies and Feedstocks written by Calvin Tsay and published by . This book was released on 2020 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the present era, the petrochemical/chemical process industries must adapt to unconventional feedstocks and energy sources, in order to keep pace with increased competition, regulatory pressure, and changing markets. However, developing processes compatible with these changes requires deviating from traditional and accepted process design and operation paradigms. This dissertation addresses fundamental challenges related to this transition from three angles: incorporation of custom (and detailed) models into process design, integration of variable operation with process design, and optimization of transient process operations. The first part of the dissertation introduces a framework for modeling, simulation, and optimization of process flowsheets incorporating highly detailed physical models of important and complex process units, termed “multi-resolution flowsheets”. The framework relies on pseudo-transient continuation as a numerical method and allows for the robust optimization of large-scale process models. Several case studies demonstrate the method, including process flowsheets featuring both intensified (e.g., dividing-wall distillation column, multistream heat exchanger) and unconventional (e.g., quenched reactor, packed column for carbon capture) process units. Furthermore, these results reveal significant benefits of considering the added level of detail at the design stage. Finally, an avenue is presented to accelerate the convergence of the pseudo-transient method, which is especially important for the large-scale models considered. In the second part of the dissertation, the focus shifts to process design optimization for variable operation, or optimization under uncertainty. Here, I present a method for process design that considers the effect of uncertain physical parameters (assumed to follow continuous probability distributions), using a formulation that exploits the semi-infinite nature of dynamic optimization. I compare the method to traditional “scenario-based” approaches using both theoretical analyses and multiple case studies. In addition to demonstrating the effectiveness of the proposed method, these case studies also emphasize the importance of considering several practically relevant uncertainties during process design. The final part of the dissertation examines explicit consideration of process dynamics for operational optimization. First, I examine periodic (dynamically intensified) processes, which operate at a cyclic steady state. I present a pseudo-transient method for robust optimization of fully discretized dynamic process models, and I present an approach for implementing cyclic conditions based on their fundamental relation to material/energy recycle loops. Lastly, I propose a framework for optimal production scheduling in fast changing market situations. Towards this end, I show how data-driven dynamic models can represent the behavior of a set of scheduling-relevant (physical or latent) variables. A method is also given for executing scheduling calculations using these models, and the framework is demonstrated by considering the demand response operation of both simulated and real-world air separation units

Download or read book Equation oriented Modeling Simulation and Optimization of Integrated and Intensified Process and Energy Systems written by Richard C. Pattison and published by . This book was released on 2016 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Process intensification, defined as unconventional design and/or operation of processes that results in substantial performance improvements, represents a promising route toward reducing capital and operating expenses in the chemical/petrochemical process industry, while simultaneously achieving improved safety and environmental performance. In this dissertation, intensification is approached from three different angles: reactor design and control, process flowsheet design and optimization, and production scheduling and control. In the first part of the dissertation, three novel concepts for improving the controllability of intensified microchannel reactors are introduced. The first concept is a latent energy storage-based temperature controller, where a phase change material is confined within the walls of an autothermal reactor to improve local temperature control. The second concept is a segmented catalyst layer which modulates the rate of heat generation and consumption along the length of an autothermal reactor. Finally, the third concept is a thermally actuated valve, which uses small-scale bimetallic strips to modulate flow in a microchannel reactor in response to temperature changes. The second part of the dissertation introduces a novel framework for equation-oriented flowsheet modeling, simulation and optimization. The framework consists of a pseudo-transient reformulation of the steady-state material and energy balance equations of process unit operations as differential-algebraic equation (DAE) systems that are statically equivalent to the original model. I show that these pseudo-transient models improve the convergence properties of equation-oriented process flowsheet simulations by expanding the convergence basin in comparison to conventional steady state equation-oriented simulators. A library of pseudo-transient unit operation models is developed, and several case studies are presented. Models for more complex unit operations such as a pseudo-transient multistream heat exchanger and a dividing-wall distillation column are later introduced, and can easily be included in the flowsheet optimization framework. In the final part of the dissertation, a paradigm for calculating the optimal production schedule in a fast changing market situation is introduced. This is accomplished by including a model of the dynamics of a process and its control system into production scheduling calculations. The scheduling-relevant dynamic models are constructed to be of lower order than a detailed dynamic process model, while capturing the closed-loop behavior of a set of scheduling-relevant variables. Additionally, a method is given for carrying out these production scheduling calculations online and in "closed scheduling loop,"' i.e., recalculating scheduling decisions upon the advent of scheduling-relevant process or market events. An air separation unit operating in a demand response scenario is used as a representative case study.

Download or read book Assessing Bipedal Locomotion Towards Replicable Benchmarks for Robotic and Robot Assisted Locomotion written by Diego Torricelli and published by Frontiers Media SA. This book was released on 2019-12-24 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling and Simulation in HPC and Cloud Systems written by Joanna Kołodziej and published by Springer. This book was released on 2019-06-07 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of eight chapters, five of which provide a summary of the tutorials and workshops organised as part of the cHiPSet Summer School: High-Performance Modelling and Simulation for Big Data Applications Cost Action on “New Trends in Modelling and Simulation in HPC Systems,” which was held in Bucharest (Romania) on September 21–23, 2016. As such it offers a solid foundation for the development of new-generation data-intensive intelligent systems. Modelling and simulation (MS) in the big data era is widely considered the essential tool in science and engineering to substantiate the prediction and analysis of complex systems and natural phenomena. MS offers suitable abstractions to manage the complexity of analysing big data in various scientific and engineering domains. Unfortunately, big data problems are not always easily amenable to efficient MS over HPC (high performance computing). Further, MS communities may lack the detailed expertise required to exploit the full potential of HPC solutions, and HPC architects may not be fully aware of specific MS requirements. The main goal of the Summer School was to improve the participants’ practical skills and knowledge of the novel HPC-driven models and technologies for big data applications. The trainers, who are also the authors of this book, explained how to design, construct, and utilise the complex MS tools that capture many of the HPC modelling needs, from scalability to fault tolerance and beyond. In the final three chapters, the book presents the first outcomes of the school: new ideas and novel results of the research on security aspects in clouds, first prototypes of the complex virtual models of data in big data streams and a data-intensive computing framework for opportunistic networks. It is a valuable reference resource for those wanting to start working in HPC and big data systems, as well as for advanced researchers and practitioners.

Download or read book Simulation Strategies for Design Analysis and Optimization of Complex Chemical Processes written by Perregaard Jens and published by . This book was released on 1992 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Hierarchical Approach to Dynamic Modeling and Simulation of Complex Processes written by Hong Tu and published by . This book was released on 2004 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Integrated Modeling Simulation and Optimization of Multibody Systems written by Peter Eberhard and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stochastic Process Optimization Using Aspen Plus written by Juan Gabriel Segovia-Hernández and published by . This book was released on 2017 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Stochastic Process Optimization using Aspen® PlusBookshop Category: Chemical EngineeringOptimization can be simply defined as "choosing the best alternative among a set of feasible options". In all the engineering areas, optimization has a wide range of applications, due to the high number of decisions involved in an engineering environment. Chemical engineering, and particularly process engineering, is not an exception; thus stochastic methods are a good option to solve optimization problems for the complex process engineering models.In this book, the combined use of the modular simulator Aspen® Plus and stochastic optimization methods, codified in MATLAB, is presented. Some basic concepts of optimization are first presented, then, strategies to use the simulator linked with the optimization algorithm are shown. Finally, examples of application for process engineering are discussed.The reader will learn how to link the process simulator Aspen® Plus and stochastic optimization algorithms to solve process design problems. They will gain ability to perform multi-objective optimization in several case studies.Key Features:• The book links simulation and optimization through numerical analyses and stochastic optimization techniques • Includes use of examples to illustrate the application of the concepts and specific guidance on the use of software (Aspen® Plus, Excel, MATLB) to set up and solve models representing complex problems.• Illustrates several examples of applications for the linking of simulation and optimization software with other packages for optimization purposes.• Provides specific information on how to implement stochastic optimization with process simulators.• Enable readers to identify practical and economic solutions to problems of industrial relevance, enhancing the safety, operation, environmental, and economic performance of chemical processes."--Provided by publisher.