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Author: Hans Georg Bock Publisher: Springer Nature ISBN: 3030552403 Category : Mathematics Languages : en Pages : 402
Book Description
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.
Author: Hans Georg Bock Publisher: Springer Nature ISBN: 3030552403 Category : Mathematics Languages : en Pages : 402
Book Description
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.
Author: Josef Kallrath Publisher: Springer Nature ISBN: 3030732371 Category : Business & Economics Languages : en Pages : 653
Book Description
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.
Author: César de Prada Publisher: MDPI ISBN: 3039214551 Category : Technology & Engineering Languages : en Pages : 298
Book Description
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.
Author: Tim Jax Publisher: Springer Nature ISBN: 3030768104 Category : Mathematics Languages : en Pages : 125
Book Description
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.
Author: Zainuddin A. Manan Publisher: John Wiley & Sons ISBN: 1119303206 Category : Technology & Engineering Languages : en Pages : 290
Book Description
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.
Author: Rushikesh Kamalapurkar Publisher: Springer ISBN: 331978384X Category : Technology & Engineering Languages : en Pages : 305
Book Description
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.
Author: Jose Luis Pitarch Publisher: ISBN: 9783039214563 Category : Electronic books Languages : en Pages : 1
Book Description
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.
Author: Biplab Das Publisher: ISBN: 9789811598302 Category : Languages : en Pages : 0
Book Description
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.
Author: Calvin Tsay Publisher: ISBN: Category : Languages : en Pages : 834
Book Description
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
Author: Hans Georg Bock
Author: Hans Georg Bock
Author: Josef Kallrath
Author: César de Prada
Author: Tim Jax
Author: Zainuddin A. Manan
Author: Rushikesh Kamalapurkar
Author: Jose Luis Pitarch
Author: Biplab Das
Author: 
Author: Calvin Tsay