Machine Learning And Its Application To Reacting Flows

Author : Nedunchezhian Swaminathan,Alessandro Parente
Publisher : Springer Nature
Page : 353 pages
File Size : 41,7 Mb
Release : 2023-01-01
Category : Technology & Engineering
ISBN : 9783031162480

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Machine Learning and Its Application to Reacting Flows by Nedunchezhian Swaminathan,Alessandro Parente Pdf

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 : V. I. Naoumov,V. G. Krioukov,A. L. Abdullin,A. V. Demin
Publisher : Cambridge University Press
Page : 449 pages
File Size : 48,6 Mb
Release : 2019-08-22
Category : Science
ISBN : 9781108427043

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Chemical Kinetics in Combustion and Reactive Flows: Modeling Tools and Applications by V. I. Naoumov,V. G. Krioukov,A. L. Abdullin,A. V. Demin Pdf

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 : Mettu Srinivas,G. Sucharitha,Anjanna Matta
Publisher : John Wiley & Sons
Page : 372 pages
File Size : 55,6 Mb
Release : 2021-08-10
Category : Computers
ISBN : 9781119769248

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Machine Learning Algorithms and Applications by Mettu Srinivas,G. Sucharitha,Anjanna Matta Pdf

Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms. The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.

Author : T. Hikmet Karakoc,Soledad Le Clainche,Xin Chen,Alper Dalkiran,Ali Haydar Ercan
Publisher : Springer Nature
Page : 313 pages
File Size : 46,6 Mb
Release : 2023-11-18
Category : Technology & Engineering
ISBN : 9783031371608

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New Technologies and Developments in Unmanned Systems by T. Hikmet Karakoc,Soledad Le Clainche,Xin Chen,Alper Dalkiran,Ali Haydar Ercan Pdf

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 : Georgios Paliouras,Vangelis Karkaletsis,Constantine D. Spyropoulos
Publisher : Springer
Page : 324 pages
File Size : 55,9 Mb
Release : 2003-06-29
Category : Computers
ISBN : 9783540446736

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Machine Learning and Its Applications by Georgios Paliouras,Vangelis Karkaletsis,Constantine D. Spyropoulos Pdf

In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers. This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The first ten chapters assess the current state of the art of machine learning, from symbolic concept learning and conceptual clustering to case-based reasoning, neural networks, and genetic algorithms. The second part introduces the reader to innovative applications of ML techniques in fields such as data mining, knowledge discovery, human language technology, user modeling, data analysis, discovery science, agent technology, finance, etc.

Author : Gianluigi Rozza
Publisher : Springer Nature
Page : 265 pages
File Size : 44,6 Mb
Release : 2024-06-27
Category : Electronic
ISBN : 9783031550607

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Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators by Gianluigi Rozza Pdf

Author : Heinz Pitsch,Antonio Attili
Publisher : Springer Nature
Page : 294 pages
File Size : 50,5 Mb
Release : 2020-05-28
Category : Mathematics
ISBN : 9783030447182

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Data Analysis for Direct Numerical Simulations of Turbulent Combustion by Heinz Pitsch,Antonio Attili Pdf

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 : Miguel A. Mendez,Andrea Ianiro,Bernd R. Noack,Steven L. Brunton
Publisher : Cambridge University Press
Page : 469 pages
File Size : 47,7 Mb
Release : 2023-01-31
Category : Science
ISBN : 9781108842143

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Data-Driven Fluid Mechanics by Miguel A. Mendez,Andrea Ianiro,Bernd R. Noack,Steven L. Brunton Pdf

This is the first book dedicated to data-driven methods for fluid dynamics, with applications in analysis, modeling, control, and closures.

Author : Srivastava, Pramod Kumar,Yadav, Ashok Kumar
Publisher : IGI Global
Page : 315 pages
File Size : 54,5 Mb
Release : 2024-03-22
Category : Computers
ISBN : 9798369310632

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Methodologies, Frameworks, and Applications of Machine Learning by Srivastava, Pramod Kumar,Yadav, Ashok Kumar Pdf

Technology is constantly evolving, and machine learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest machine learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. Academic scholars seeking to unlock the potential of machine learning in the context of Industry 5.0 and advanced IoT applications will find that the groundbreaking book, Methodologies, Frameworks, and Applications of Machine Learning, introduces an unmissable opportunity to delve into the forefront of modern research and application. This book offers a wealth of knowledge and practical insights across a wide array of topics, ranging from conceptual frameworks and methodological approaches to the application of probability theory, statistical techniques, and machine learning in domains as diverse as e-government, healthcare, cyber-physical systems, and sustainable development, this comprehensive guide equips you with the tools to navigate the complexities of Industry 5.0 and the Internet of Things (IoT).

Author : Robert Klöfkorn,Eirik Keilegavlen,Florin A. Radu,Jürgen Fuhrmann
Publisher : Springer Nature
Page : 727 pages
File Size : 47,6 Mb
Release : 2020-06-09
Category : Computers
ISBN : 9783030436513

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Finite Volumes for Complex Applications IX - Methods, Theoretical Aspects, Examples by Robert Klöfkorn,Eirik Keilegavlen,Florin A. Radu,Jürgen Fuhrmann Pdf

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 : United States. Superintendent of Documents
Publisher : Unknown
Page : 1084 pages
File Size : 48,6 Mb
Release : 1993
Category : Government publications
ISBN : MINN:31951P00437078X

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Monthly Catalog of United States Government Publications by United States. Superintendent of Documents Pdf

February issue includes Appendix entitled Directory of United States Government periodicals and subscription publications; September issue includes List of depository libraries; June and December issues include semiannual index

Author : Heike Jagode,Hartwig Anzt,Hatem Ltaief,Piotr Luszczek
Publisher : Springer Nature
Page : 515 pages
File Size : 41,6 Mb
Release : 2021-11-12
Category : Computers
ISBN : 9783030905392

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High Performance Computing by Heike Jagode,Hartwig Anzt,Hatem Ltaief,Piotr Luszczek Pdf

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.

Author : Shuvajit Bhattacharya,Haibin Di
Publisher : Elsevier
Page : 378 pages
File Size : 43,5 Mb
Release : 2022-05-18
Category : Computers
ISBN : 9780128223086

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Advances in Subsurface Data Analytics by Shuvajit Bhattacharya,Haibin Di Pdf

Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume. Covers fundamentals of simple machine learning and deep learning algorithms, and physics-based approaches written by practitioners in academia and industry Presents detailed case studies of individual machine learning algorithms and optimal strategies in subsurface characterization around the world Offers an analysis of future trends in machine learning in geosciences

Author : Marcio Ferreira Martins,Rogério Ramos,Humberto Belich
Publisher : Springer Nature
Page : 342 pages
File Size : 40,5 Mb
Release : 2022-04-01
Category : Technology & Engineering
ISBN : 9783030934569

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Multiphase Flow Dynamics by Marcio Ferreira Martins,Rogério Ramos,Humberto Belich Pdf

This book presents isothermal and non-isothermal multiphase flows with and without phase change or chemical reactions. Six main axes of multiphase flow are covered in a strategic order: Multiphase Flow in Industry, Multiphase Flow Measurement and Instrumentation, Multiphase Flow With Phase Change & Chemical Reactions, Multiphase Flow Modeling, Experimental Multiphase Flow, and Wet and Dry Particulate Systems. Each part is opened by mini-reviews written by internationally prominent researchers from the academy and industry. The content is of interest to researchers and engineers working in mining, oil and gas, power, nuclear, chemical process, space, food, biomedical, micro and nanotechnology, and other industries.

Author : Uma N. Dulhare,Khaleel Ahmad,Khairol Amali Bin Ahmad
Publisher : John Wiley & Sons
Page : 544 pages
File Size : 40,5 Mb
Release : 2020-09-01
Category : Computers
ISBN : 9781119654742

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Machine Learning and Big Data by Uma N. Dulhare,Khaleel Ahmad,Khairol Amali Bin Ahmad Pdf

This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.