Machine Learning and Its Application to Reacting Flows PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Machine Learning and Its Application to Reacting Flows PDF full book. Access full book title Machine Learning and Its Application to Reacting Flows by Nedunchezhian Swaminathan. Download full books in PDF and EPUB format.
Author: Nedunchezhian Swaminathan
Publisher: Springer Nature
ISBN: 303116248X
Category : Technology & Engineering
Languages : en
Pages : 353
Get Book Here
Book Description
This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows. These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world’s total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and “greener” combustion systems that are friendlier to the environment can be designed. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.
Author: Nedunchezhian Swaminathan
Publisher: Springer Nature
ISBN: 303116248X
Category : Technology & Engineering
Languages : en
Pages : 353
Get Book Here
Book Description
This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows. These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world’s total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and “greener” combustion systems that are friendlier to the environment can be designed. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.
Author: Heinz Pitsch
Publisher: Springer Nature
ISBN: 3030447189
Category : Mathematics
Languages : en
Pages : 294
Get Book Here
Book Description
This book presents methodologies for analysing large data sets produced by the direct numerical simulation (DNS) of turbulence and combustion. It describes the development of models that can be used to analyse large eddy simulations, and highlights both the most common techniques and newly emerging ones. The chapters, written by internationally respected experts, invite readers to consider DNS of turbulence and combustion from a formal, data-driven standpoint, rather than one led by experience and intuition. This perspective allows readers to recognise the shortcomings of existing models, with the ultimate goal of quantifying and reducing model-based uncertainty. In addition, recent advances in machine learning and statistical inferences offer new insights on the interpretation of DNS data. The book will especially benefit graduate-level students and researchers in mechanical and aerospace engineering, e.g. those with an interest in general fluid mechanics, applied mathematics, and the environmental and atmospheric sciences.
Author: Robert Klöfkorn
Publisher: Springer Nature
ISBN: 3030436519
Category : Computers
Languages : en
Pages : 727
Get Book Here
Book Description
The proceedings of the 9th conference on "Finite Volumes for Complex Applications" (Bergen, June 2020) are structured in two volumes. The first volume collects the focused invited papers, as well as the reviewed contributions from internationally leading researchers in the field of analysis of finite volume and related methods. Topics covered include convergence and stability analysis, as well as investigations of these methods from the point of view of compatibility with physical principles. Altogether, a rather comprehensive overview is given on the state of the art in the field. The properties of the methods considered in the conference give them distinguished advantages for a number of applications. These include fluid dynamics, magnetohydrodynamics, structural analysis, nuclear physics, semiconductor theory, carbon capture utilization and storage, geothermal energy and further topics. The second volume covers reviewed contributions reporting successful applications of finite volume and related methods in these fields. The finite volume method in its various forms is a space discretization technique for partial differential equations based on the fundamental physical principle of conservation. Many finite volume methods preserve further qualitative or asymptotic properties, including maximum principles, dissipativity, monotone decay of free energy, and asymptotic stability, making the finite volume methods compatible discretization methods, which preserve qualitative properties of continuous problems at the discrete level. This structural approach to the discretization of partial differential equations becomes particularly important for multiphysics and multiscale applications. The book is a valuable resource for researchers, PhD and master’s level students in numerical analysis, scientific computing and related fields such as partial differential equations, as well as engineers working in numerical modeling and simulations.
Author: V. I. Naoumov
Publisher: Cambridge University Press
ISBN: 1108427049
Category : Science
Languages : en
Pages : 449
Get Book Here
Book Description
Introduces advanced mathematical tools for the modeling, simulation, and analysis of chemical non-equilibrium phenomena in combustion and flows, following a detailed explanation of the basics of thermodynamics and chemical kinetics of reactive mixtures. Researchers, practitioners, lecturers, and graduate students will find this work valuable.
Author: T. Hikmet Karakoc
Publisher: Springer Nature
ISBN: 3031371607
Category : Technology & Engineering
Languages : en
Pages : 313
Get Book Here
Book Description
Unmanned systems are one of the fastest-growing and widely developing technologies in the world, offering many possibilities for a variety of research fields. This book comprises the proceedings of the 2022 International Symposium on Unmanned Systems and the Defense Industry (ISUDEF), a multi-disciplinary conference on a broad range of current research and issues in areas such as autonomous technology, unmanned aircraft technologies, avionics, radar systems, air defense, aerospace robotics and mechatronics, and aircraft technology design. ISUDEF allows researchers, scientists, engineers, practitioners, policymakers, and students to exchange information, present new technologies and developments, and discuss future direction, strategies, and priorities in the field of autonomous vehicles and unmanned aircraft technologies.
Author: Gianluigi Rozza
Publisher: Springer Nature
ISBN: 3031550609
Category :
Languages : en
Pages : 265
Get Book Here
Book Description
Author: Zambri Harun
Publisher: BoD – Books on Demand
ISBN: 183769835X
Category : Science
Languages : en
Pages : 146
Get Book Here
Book Description
Fluid mechanics is a branch of physics with important applications in daily life. The calculation of flow drag on automobiles and high-speed trains benefits from theories in fluid mechanics. Moreover, many mechanical-based devices such as fluid pumps contribute to efficiency, and thus, to the modernization of society. This book highlights the experimental and theoretical aspects of wall-bounded flows to provide important information about related theories and applications. Boundary layer flow experimentation, modelling, and simulation must be considered together to obtain accurate calculations of parameters such as velocity profiles, pressure distribution, and turbulence level. This book is organized into three sections on the structure of the boundary layer, drag reduction initiatives using active control, and the verification and applications of flow mechanics. Chapters discuss the boundary layer type of different pressure gradients, Reynolds number, and speeds from 5 m/s to Mach 3. They also present the results of research on the active control technique for drag reduction initiatives to achieve efficient turbulence in high-speed applications, flow meter devices, and turbulence-generated noise mitigation initiatives.
Author: Miguel A. Mendez
Publisher: Cambridge University Press
ISBN: 1108842143
Category : Science
Languages : en
Pages : 469
Get Book Here
Book Description
This is the first book dedicated to data-driven methods for fluid dynamics, with applications in analysis, modeling, control, and closures.
Author:
Publisher: Academic Press
ISBN: 0128150971
Category : Technology & Engineering
Languages : en
Pages : 204
Get Book Here
Book Description
Bridging Scales in Modelling and Simulating Reacting Flows, Part I , Volume 52 presents key methods to bridge scales in the simulation of reacting single phase flows. New sections in the updated release include topics such as quadrature-based moment methods for multiphase chemically reacting flows, the collaboration of experiments and simulations for the development of predictive models, a simulation of turbulent coalescence and breakage of bubbles and droplets in the presence of surfactants, a section on salts and contaminants, and information on the numerical simulation of reactive flows. - Contains reviews by leading authorities in their respective areas - Presents up-to-date reviews of the latest techniques in the modeling of catalytic processes - Includes a broad mix of US and European authors, as well as academic, industrial and research institute perspectives - Provides discussions on the connections between computational and experimental methods
Author: Heike Jagode
Publisher: Springer Nature
ISBN: 303090539X
Category : Computers
Languages : en
Pages : 515
Get Book Here
Book Description
This book constitutes the refereed post-conference proceedings of 9 workshops held at the 35th International ISC High Performance 2021 Conference, in Frankfurt, Germany, in June-July 2021: Second International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics and Solid Mechanics Simulations and Analysis; HPC-IODC: HPC I/O in the Data Center Workshop; Compiler-assisted Correctness Checking and Performance Optimization for HPC; Machine Learning on HPC Systems;4th International Workshop on Interoperability of Supercomputing and Cloud Technologies;2nd International Workshop on Monitoring and Operational Data Analytics;16th Workshop on Virtualization in High-Performance Cloud Computing; Deep Learning on Supercomputers; 5th International Workshop on In Situ Visualization. The 35 papers included in this volume were carefully reviewed and selected. They cover all aspects of research, development, and application of large-scale, high performance experimental and commercial systems. Topics include high-performance computing (HPC), computer architecture and hardware, programming models, system software, performance analysis and modeling, compiler analysis and optimization techniques, software sustainability, scientific applications, deep learning.
