Author :
Publisher :
Page : 7 pages
File Size : 22,95 MB
Release : 2011
Category :
ISBN :
[PDF] Feature Based Statistical Analysis Of Combustion Simulation Data eBook
Feature Based Statistical Analysis Of Combustion Simulation Data Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Feature Based Statistical Analysis Of Combustion Simulation Data book. This book definitely worth reading, it is an incredibly well-written.
Data Analysis for Direct Numerical Simulations of Turbulent Combustion
Heinz Pitsch
Author : Heinz Pitsch
Publisher : Springer Nature
Page : 294 pages
File Size : 50,79 MB
Release : 2020-05-28
Category : Mathematics
ISBN : 3030447189
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.
In Situ Visualization for Computational Science
Hank Childs
Author : Hank Childs
Publisher : Springer Nature
Page : 464 pages
File Size : 50,46 MB
Release : 2022-05-04
Category : Mathematics
ISBN : 3030816273
This book provides an overview of the emerging field of in situ visualization, i.e. visualizing simulation data as it is generated. In situ visualization is a processing paradigm in response to recent trends in the development of high-performance computers. It has great promise in its ability to access increased temporal resolution and leverage extensive computational power. However, the paradigm also is widely viewed as limiting when it comes to exploration-oriented use cases. Furthermore, it will require visualization systems to become increasingly complex and constrained in usage. As research efforts on in situ visualization are growing, the state of the art and best practices are rapidly maturing. Specifically, this book contains chapters that reflect state-of-the-art research results and best practices in the area of in situ visualization. Our target audience are researchers and practitioners from the areas of mathematics computational science, high-performance computing, and computer science that work on or with in situ techniques, or desire to do so in future.
Modeling and Simulation of Turbulent Combustion
Santanu De
Author : Santanu De
Publisher : Springer
Page : 663 pages
File Size : 15,90 MB
Release : 2017-12-12
Category : Science
ISBN : 9811074100
This book presents a comprehensive review of state-of-the-art models for turbulent combustion, with special emphasis on the theory, development and applications of combustion models in practical combustion systems. It simplifies the complex multi-scale and nonlinear interaction between chemistry and turbulence to allow a broader audience to understand the modeling and numerical simulations of turbulent combustion, which remains at the forefront of research due to its industrial relevance. Further, the book provides a holistic view by covering a diverse range of basic and advanced topics—from the fundamentals of turbulence–chemistry interactions, role of high-performance computing in combustion simulations, and optimization and reduction techniques for chemical kinetics, to state-of-the-art modeling strategies for turbulent premixed and nonpremixed combustion and their applications in engineering contexts.
Topological Methods in Data Analysis and Visualization
Valerio Pascucci
Author : Valerio Pascucci
Publisher : Springer Science & Business Media
Page : 265 pages
File Size : 41,76 MB
Release : 2010-11-23
Category : Mathematics
ISBN : 3642150144
Topology-based methods are of increasing importance in the analysis and visualization of datasets from a wide variety of scientific domains such as biology, physics, engineering, and medicine. Current challenges of topology-based techniques include the management of time-dependent data, the representation of large and complex datasets, the characterization of noise and uncertainty, the effective integration of numerical methods with robust combinatorial algorithms, etc. . The editors have brought together the most prominent and best recognized researchers in the field of topology-based data analysis and visualization for a joint discussion and scientific exchange of the latest results in the field. This book contains the best 20 peer-reviewed papers resulting from the discussions and presentations at the third workshop on "Topological Methods in Data Analysis and Visualization", held 2009 in Snowbird, Utah, US. The 2009 "TopoInVis" workshop follows the two successful workshops in 2005 (Slovakia) and 2007 (Germany).
Physical Modeling for Virtual Manufacturing Systems and Processes
Jan C. Aurich
Author : Jan C. Aurich
Publisher : Trans Tech Publications Ltd
Page : 274 pages
File Size : 45,53 MB
Release : 2017-08-30
Category : Technology & Engineering
ISBN : 3035731861
The 1st Conference on Physical Modeling for Virtual Manufacturing Systems and Processes is the result of the International Research Training Group (IRTG) 2057 "Physical Modeling for Virtual Manufacturing Systems and Processes", funded by the German Research Foundation (DFG). The IRTG began on 01 July 2014. Partner University of the University of Kaiserslautern, is the University of California, with its locations in Berkeley and Davis. At the conference the progress and the results of the first cohort of PhD students was presented. The conference was complemented by talks of international guest speakers from computer science and manufacturing engineering. The proceedings contain 22 peer-reviewed papers on Physical Modeling for Virtual Manufacturing Systems and Processes.
Machine Learning and Its Application to Reacting Flows
Nedunchezhian Swaminathan
Author : Nedunchezhian Swaminathan
Publisher : Springer Nature
Page : 353 pages
File Size : 19,48 MB
Release : 2023-01-01
Category : Technology & Engineering
ISBN : 303116248X
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.
Modeling of Combustion Systems
Joseph Colannino
Author : Joseph Colannino
Publisher : CRC Press
Page : 675 pages
File Size : 39,66 MB
Release : 2006-03-24
Category : Science
ISBN : 1420005030
Increasing competitive pressure for improved quality and efficiency on one hand and tightening emissions and operating requirements on the other leave the modern process engineer squeezed in the middle. While effective modeling can help balance these demands, the current literature offers overly theoretical treatments on modeling that do not transl
Statistical Analysis of Steady State Combustion of Nonmetallized Composite Solid Propellants
R. L. Glick
Author : R. L. Glick
Publisher :
Page : 56 pages
File Size : 31,39 MB
Release : 1977
Category :
ISBN :
The combustion model including aluminum and iron oxide was employed to correlate data bases of Miller and Maykut. Results for additive free formulations were excellent for both rate and exponent; results for formulations with aluminum and aluminum plus iron oxide were poor. A new method for extracting particle size dependent information from rate/response function/formulation data was developed from the statistical methodology itself and employed to process the aforementioned data bases. Results were encouraging; Miller's additive free and aluminum plus iron oxide data correlated very well; Miller's aluminum data showed that the increasing aluminum particle size increases interactions between oxidizer modes; Maykut's data base showed that aluminum induced interactions among oxidizer modes are decreased as iron content increases. Results elucidate mechanisms for rate, exponent, and response function control and show that the equal rate hypothesis employed in much combustion modeling is incorrect. A new approach for including the effects of transients introduced by particle size dependent rates in both steady and nonsteady combustion modeling was conceived. (Author).
Turbulent Combustion Modeling
Tarek Echekki
Author : Tarek Echekki
Publisher : Springer Science & Business Media
Page : 496 pages
File Size : 49,93 MB
Release : 2010-12-25
Category : Technology & Engineering
ISBN : 9400704127
Turbulent combustion sits at the interface of two important nonlinear, multiscale phenomena: chemistry and turbulence. Its study is extremely timely in view of the need to develop new combustion technologies in order to address challenges associated with climate change, energy source uncertainty, and air pollution. Despite the fact that modeling of turbulent combustion is a subject that has been researched for a number of years, its complexity implies that key issues are still eluding, and a theoretical description that is accurate enough to make turbulent combustion models rigorous and quantitative for industrial use is still lacking. In this book, prominent experts review most of the available approaches in modeling turbulent combustion, with particular focus on the exploding increase in computational resources that has allowed the simulation of increasingly detailed phenomena. The relevant algorithms are presented, the theoretical methods are explained, and various application examples are given. The book is intended for a relatively broad audience, including seasoned researchers and graduate students in engineering, applied mathematics and computational science, engine designers and computational fluid dynamics (CFD) practitioners, scientists at funding agencies, and anyone wishing to understand the state-of-the-art and the future directions of this scientifically challenging and practically important field.