Download or read book Modeling and Simulation of Large Scale Nonlinear Processes written by Nikolaos I. Xiros and published by Wiley. This book was released on 2023-03-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers a comprehensive resource that presents nonlinearity within a multi-physics context that can be applied to a wide range of engineering problems Modeling and Simulation of Large-Scale, Nonlinear Processes fills a gap in the literature for a resource that explores the formal analytical and systematic methods in the analysis of large-scale, distributed and continuous nonlinear processes. Written by experts in the field, this vital text develops and proposes techniques for dealing with nonlinearity in the same way as systems with infinite dynamical order: by reducing the nonlinearity degree to a finite level while avoiding full linearization which often leads to oversimplification which render crucial features elusive. Formulation of the dynamics of multi-physics, large-scale systems is a necessary first step towards reduced-order modeling techniques, robust against parametric uncertainty and neglected dynamics, suitable for analysis, synthesis, control and monitoring of linear and nonlinear multi-physics, and can be applied to large-scale systems such as those encountered among others in mechatronics, fluid-structure interactions, ship propulsion, marine machinery, and power-plants. This important resource: Examines nonlinearity within a multi-physics context that can be applied to engineering problems Presents the material in an integrated way and combines theory with practical applications Helps to establish a solid foundation in the theoretical aspects before looking at applications of the methods Offers a consolidated overview of systematic methods for the analysis of large-scale and continuous nonlinear processes Contains applications spanning a broad range of topics in diverse areas of engineering Designed for engineers, especially those who may be unfamiliar with nonlinearities, Modeling and Simulation of Large-Scale, Nonlinear Processes is the essential text filled with useful material for courses on dynamics, nonlinear vibrations and control.
Download or read book Process Structure Aware Machine Learning Modeling for State Estimation and Model Predictive Control of Nonlinear Processes written by Mohammed S. Alhajeri and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data is a cornerstone component of the fourth industrial revolution, which calls onengineers and researchers to fully utilize data in order to make smart decisions and enhance the efficiency of industrial processes as well as control systems. In practice, industrial process control systems typically rely on a data-driven model (often linear) with parameters that are determined by industrial/simulation data. However, in some scenarios, such as in profit-critical or quality-critical control loops, first-principles concepts that are based on the underlying physico-chemical phenomena may also need to be employed in the modeling phase to improve data-based process models. Hence, process systems engineers still face significant challenges when it comes to modeling large-scale, complicated nonlinear processes. Modeling will continue to be crucial since process models are essential components of cutting-edge model-based control systems, such as model predictive control (MPC). Machine learning models have a lot of potential based on their success in numerousapplications. Specifically, recurrent neural network (RNN) models, designed to account for every input-output interconnection, have gained popularity in providing approximation of various highly nonlinear chemical processes to a desired accuracy. Although the training error of neural networks that are dense and fully-connected may often be made sufficiently small, their accuracy can be further improved by incorporating prior knowledge in the structure development of such machine learning models. Physics-based recurrent neural networks modeling has yielded more reliable machine learning models than traditional, fully black-box, machine learning modeling methods. Furthermore, the development of systematic and rigorous approaches to integrate such machine learning techniques into nonlinear model-based process control systems is only getting started. In particular, physics-based machine learning modeling techniques can be employed to derive more accurate and well-conditioned dynamic process models to be utilized in advanced control systems such as model predictive control. Along with Lyapunov-based stability constraints, this scheme has the potential to significantly improve process operational performance and dynamics. Hence, investigating the effectiveness of this control scheme under the various long-standing challenges in the field of process systems engineering such as incomplete state measurements, and noise and uncertainty is essential. Also, a theoretical framework for constructing and assessing the generalizability of this type of machine learning models to be utilized in model predictive control systems is lacking. In light of the aforementioned considerations, this dissertation addresses the incorporation ofprior process knowledge into machine learning models for model predictive control of nonlinear chemical processes. The motivation, background and outline of this dissertation are first presented. Then, the use of machine learning modeling techniques to construct two different data-driven state observers to compensate for incomplete process measurements is presented. The closed-loop stability under Lyapunov-based model predictive controllers is then addressed. Next, the development of process-structure-based machine learning models to approximate large, nonlinear chemical processes is presented, with the improvements yielded by this approach demonstrated via open-loop and closed-loop simulations. Subsequently, the reliability of process-structure-based machine learning models is investigated in the presence of different types of industrial noise. Two novel approaches are proposed to enhance the accuracy of machine learning models in the presence of noise. Lastly, a theoretical framework that connects the accuracy of an RNN model to its structure is presented, where an upper bound on a physics-based RNN model's generalization error is established. Nonlinear chemical process examples are numerically simulated or modeled in Aspen Plus Dynamics to illustrate the effectiveness and performance of the proposed control methods throughout the dissertation.
Download or read book Modeling Simulation and Control of Nonlinear Engineering Dynamical Systems written by Jan Awrejcewicz and published by Springer Science & Business Media. This book was released on 2008-12-26 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the invited papers presented at the 9th International Conference "Dynamical Systems — Theory and Applications" held in Lódz, Poland, December 17-20, 2007, dealing with nonlinear dynamical systems. The conference brought together a large group of outstanding scientists and engineers, who deal with various problems of dynamics encountered both in engineering and in daily life. Topics covered include, among others, bifurcations and chaos in mechanical systems; control in dynamical systems; asymptotic methods in nonlinear dynamics; stability of dynamical systems; lumped and continuous systems vibrations; original numerical methods of vibration analysis; and man-machine interactions. Thus, the reader is given an overview of the most recent developments of dynamical systems and can follow the newest trends in this field of science. This book will be of interest to to pure and applied scientists working in the field of nonlinear dynamics.
Download or read book Multiscale Modeling and Simulation in Science written by Björn Engquist and published by Springer Science & Business Media. This book was released on 2009-02-11 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most problems in science involve many scales in time and space. An example is turbulent ?ow where the important large scale quantities of lift and drag of a wing depend on the behavior of the small vortices in the boundarylayer. Another example is chemical reactions with concentrations of the species varying over seconds and hours while the time scale of the oscillations of the chemical bonds is of the order of femtoseconds. A third example from structural mechanics is the stress and strain in a solid beam which is well described by macroscopic equations but at the tip of a crack modeling details on a microscale are needed. A common dif?culty with the simulation of these problems and many others in physics, chemistry and biology is that an attempt to represent all scales will lead to an enormous computational problem with unacceptably long computation times and large memory requirements. On the other hand, if the discretization at a coarse level ignoresthe?nescale informationthenthesolutionwillnotbephysicallymeaningful. The in?uence of the ?ne scales must be incorporated into the model. This volume is the result of a Summer School on Multiscale Modeling and S- ulation in Science held at Boso ¤n, Lidingo ¤ outside Stockholm, Sweden, in June 2007. Sixty PhD students from applied mathematics, the sciences and engineering parti- pated in the summer school.
Download or read book Mathematical Modeling Simulation and Optimization for Power Engineering and Management written by Simone Göttlich and published by Springer Nature. This book was released on 2021-02-02 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited monograph offers a summary of future mathematical methods supporting the recent energy sector transformation. It collects current contributions on innovative methods and algorithms. Advances in mathematical techniques and scientific computing methods are presented centering around economic aspects, technical realization and large-scale networks. Over twenty authors focus on the mathematical modeling of such future systems with careful analysis of desired properties and arising scales. Numerical investigations include efficient methods for the simulation of possibly large-scale interconnected energy systems and modern techniques for optimization purposes to guarantee stable and reliable future operations. The target audience comprises research scientists, researchers in the R&D field, and practitioners. Since the book highlights possible future research directions, graduate students in the field of mathematical modeling or electrical engineering may also benefit strongly.
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 Nonlinear Model Predictive Control written by Frank Allgöwer and published by Birkhäuser. This book was released on 2012-12-06 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland. The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonlinear model predictive control, including systems theory, computations, modeling and applications.
Download or read book Nonlinear Model Based Process Control written by R. Berber and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 883 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ASI on Nonlinear Model Based Process Control (August 10-20, 1997~ Antalya - Turkey) convened as a continuation of a previous ASI which was held in August 1994 in Antalya on Methods of Model Based Process Control in a more general context. In 1994, the contributions and discussions convincingly showed that industrial process control would increasingly rely on nonlinear model based control systems. Therefore, the idea for organizing this ASI was motivated by the success of the first one, the enthusiasm expressed by the scientific community for continuing contact, and the growing incentive for on-line control algorithms for nonlinear processes. This is due to tighter constraints and constantly changing performance objectives that now force the processes to be operated over a wider range of conditions compared to the past, and the fact that many of industrial operations are nonlinear in nature. The ASI intended to review in depth and in a global way the state-of-the-art in nonlinear model based control. The list of lecturers consisted of 12 eminent scientists leading the principal developments in the area, as well as industrial specialists experienced in the application of these techniques. Selected out of a large number of applications, there was a high quality, active audience composed of 59 students from 20 countries. Including family members accompanying the participants, the group formed a large body of92 persons. Out of the 71 participants, 11 were from industry.
Download or read book Opportunities for Breakthroughs in Large Scale Computational Simulation and Design written by and published by . This book was released on 2002 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Opportunities for breakthroughs in the large-scale computational simulation and design of aerospace vehicles are presented. Computational fluid dynamics tools to be used within multidisciplinary analysis and design methods are emphasized. The opportunities stem from speedups and robustness improvements in the underlying unit operations associated with simulation (geometry modeling, grid generation, physical modeling, analysis, etc.). Further, an improved programming environment can synergistically integrate these unit operations to leverage the gains. The speedups result from reducing the problem setup time through geometry modeling and grid generation operations, and reducing the solution time through the operation counts associated with solving the discretized equations to a sufficient accuracy. The opportunities are addressed only at a general level here, but an extensive list of references containing further details is included.
Download or read book Process Modelling and Simulation with Finite Element Methods written by William B. J. Zimmerman and published by World Scientific. This book was released on 2004 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic description and case studies of chemical engineering modelling and simulation based on the MATLAB/FEMLAB tools, in support of selected topics in undergraduate and postgraduate programmes that require numerical solution of complex balance equations (ordinary differential equations, partial differential equations, nonlinear equations, integro-differential equations). These systems arise naturally in analysis of transport phenomena, process systems, chemical reactions and chemical thermodynamics, and particle rate processes. Templates are given for modelling both state-of-the-art research topics (e.g. microfluidic networks, film drying, multiphase flow, population balance equations) and case studies of commonplace design calculations -- mixed phase reactor design, heat transfer, flowsheet analysis of unit operations, flash distillations, etc. The great strength of this book is that it makes modelling and simulating in the MATLAB/FEMLAB environment approachable to both the novice and the expert modeller.
Download or read book Nonlinear Programming written by Lorenz T. Biegler and published by SIAM. This book was released on 2010-01-01 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses modern nonlinear programming (NLP) concepts and algorithms, especially as they apply to challenging applications in chemical process engineering. The author provides a firm grounding in fundamental NLP properties and algorithms, and relates them to real-world problem classes in process optimization, thus making the material understandable and useful to chemical engineers and experts in mathematical optimization.
Download or read book Modeling Simulation and Optimization of Complex Processes written by Hans Georg Bock and published by Springer Science & Business Media. This book was released on 2008-06-19 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume covers the broad interdisciplinary spectrum of scientific computing and presents recent advances in theory, development of methods, and applications in practice.
Download or read book Large Scale Disasters written by Mohamed Gad-el-Hak and published by Cambridge University Press. This book was released on 2008-06-23 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Extreme' events - including climatic events, such as hurricanes, tornadoes, drought - can cause massive disruption to society, including large death tolls and property damage in the billions of dollars. Events in recent years have shown the importance of being prepared and that countries need to work together to help alleviate the resulting pain and suffering. This volume presents an integrated review of the broad research field of large-scale disasters. It establishes a common framework for predicting, controlling and managing both manmade and natural disasters. There is a particular focus on events caused by weather and climate change. Other topics include air pollution, tsunamis, disaster modeling, the use of remote sensing and the logistics of disaster management. It will appeal to scientists, engineers, first responders and health-care professionals, in addition to graduate students and researchers who have an interest in the prediction, prevention or mitigation of large-scale disasters.
Download or read book Direct and Large Eddy Simulation written by Bernard J. Geurts and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-12-05 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive overview of the mathematics and physics behind the simulation of turbulent flows and discusses in detail (i) the phenomenology of turbulence in fluid dynamics, (ii) the role of direct and large-eddy simulation in predicting these dynamics, (iii) the multiple considerations underpinning subgrid modelling, and, (iv) the issue of validation and reliability resulting from interacting modelling and numerical errors.
Download or read book Large Scale Inverse Problems written by Mike Cullen and published by Walter de Gruyter. This book was released on 2013-08-29 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is thesecond volume of a three volume series recording the "Radon Special Semester 2011 on Multiscale Simulation & Analysis in Energy and the Environment" that took placein Linz, Austria, October 3-7, 2011. This volume addresses the common ground in the mathematical and computational procedures required for large-scale inverse problems and data assimilation in forefront applications. The solution of inverse problems is fundamental to a wide variety of applications such as weather forecasting, medical tomography, and oil exploration. Regularisation techniques are needed to ensure solutions of sufficient quality to be useful, and soundly theoretically based. This book addresses the common techniques required for all the applications, and is thus truly interdisciplinary. Thiscollection of surveyarticlesfocusses onthe large inverse problems commonly arising in simulation and forecasting in the earth sciences. For example, operational weather forecasting models have between 107 and 108 degrees of freedom. Even so, these degrees of freedom represent grossly space-time averaged properties of the atmosphere. Accurate forecasts require accurate initial conditions. With recent developments in satellite data, there are between 106 and 107 observations each day. However, while these also represent space-time averaged properties, the averaging implicit in the measurements is quite different from that used in the models. In atmosphere and ocean applications, there is a physically-based model available which can be used to regularise the problem. We assume that there is a set of observations with known error characteristics available over a period of time. The basic deterministic technique is to fit a model trajectory to the observations over a period of time to within the observation error. Since the model is not perfect the model trajectory has to be corrected, which defines the data assimilation problem. The stochastic view can be expressed by using an ensemble of model trajectories, and calculating corrections to both the mean value and the spread which allow the observations to be fitted by each ensemble member. In other areas of earth science, only the structure of the model formulation itself is known and the aim is to use the past observation history to determine the unknown model parameters. The book records the achievements of Workshop2 "Large-Scale Inverse Problems and Applications in the Earth Sciences". Itinvolves experts in the theory of inverse problems together with experts working on both theoretical and practical aspects of the techniques by which large inverse problems arise in the earth sciences.
Download or read book Process Control written by Jean-Pierre Corriou and published by Springer. This book was released on 2017-08-17 with total page 867 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reference book can be read at different levels, making it a powerful source of information. It presents most of the aspects of control that can help anyone to have a synthetic view of control theory and possible applications, especially concerning process engineering.
Download or read book Model Development and Optimization written by V.V. Ivanov and published by Springer Science & Business Media. This book was released on 2013-11-09 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: At present, concerning intensive development of computer hardware and software, computer-based methods for modeling of difficult problems have become the main technique for theoretical and applied investigations. Many unsolved tasks for evolutionary systems (ES) are an important class of such problems. ES relate to economic systems on the whole and separate branches and businesses, scientific and art centers, ecological systems, populations, separate species of animals and plants, human organisms, different subsystems of organisms, cells of animals and plants, and soon. Available methods for modeling of complex systems have received considerable attention and led to significant results. No large-scale programs are done without methods of modeling today. Power programs, health programs, cosmos investigations, economy designs, etc. are a few examples of such programs. Nevertheless, in connection with the permanent complication of contemporary problems, existing means are in need of subsequent renovation and perfection. In the monograph, along with analysis of contemporary means, new classes of mathematical models (MM) which can be used for modeling in the most difficult cases are proposed and justified. The main peculiarities of these MM offer possibilities for the description ofES; creation and restoration processes; dynamics of elimination or reservation of obsolete technology in ES; dynamics of resources distribution for fulfillment of internal and external functions ofES; and so on. The complexity of the problems allows us to refer to the theory and applications of these MM as the mathematical theory of development. For simplicity, the title "Model Development and Optimization" was adopted.
