Data Analysis for Direct Numerical Simulations of Turbulent Combustion:From Equation-Based Analysis to Machine Learning

图书简介

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.

Partial A-Posteriori LES of DNS Data of Turbulent Combustion.- Application of the Optimal Estimator Analysis to Turbulent Combustion Modeling.- Reduced Order Modeling of Rocket Combustion Flows.- Dynamic Mode Decompositions: A Tool to Extract Structure Hidden in Massive Dataset.- Analysis of Combustion-Modes Through Structural and Dynamic Technique.- Analysis of the Impact of Combustion On Turbulence: Triadic Analysis, Wavelets, Structure Functions, Spectra.- Analysis of Flame Topology and Burning Rates.- Dissipation Element Analysis of Turbulent Combustion.- Higher Order Tensors for DNS Data Analysis and Compression.- Covariant Lyapunov Vector Analysis of Turbulent Reacting Flows.- CEMA Analysis Applied to DNS Data.- Combined Computational Singular Perturbation-Tangential Stretching Rate Diagnostics of Large.- Scale Simulations of Reactive Turbulent Flows: Feature Tracking, Time Scale Characterization, and Cause/Effect Identification.- Genetic Algorithms Applied to LES Model Development.- Sub-grid Scale Signal Reconstruction: From Discrete and Iterative Deconvolution Operators to Convolutional Neural Networks.- Machine Learning for Combustion Rate Shaping.- Machine Learning of Combustion LES Models from DNS.- Developing Artificial Neural Networks Based Models for Complex Turbulent Flow by Utilizing DNS Database

Trade Policy 买家须知

关于产品：
● 正版保障：本网站隶属于中国国际图书贸易集团公司，确保所有图书都是100%正版。
● 环保纸张：进口图书大多使用的都是环保轻型张，颜色偏黄，重量比较轻。
● 毛边版：即书翻页的地方，故意做成了参差不齐的样子，一般为精装版，更具收藏价值。
关于退换货：
由于预订产品的特殊性，采购订单正式发订后，买方不得无故取消全部或部分产品的订购。
由于进口图书的特殊性，发生以下情况的，请直接拒收货物，由快递返回：
● 外包装破损/发错货/少发货/图书外观破损/图书配件不全（例如：光盘等）
并请在工作日通过电话400-008-1110联系我们。
签收后，如发生以下情况，请在签收后的5个工作日内联系客服办理退换货：
● 缺页/错页/错印/脱线
关于发货时间：
一般情况下：
●【现货】下单后48小时内由北京（库房）发出快递。
●【预订】【预售】下单后国外发货，到货时间预计5-8周左右，店铺默认中通快递，如需顺丰快递邮费到付。
● 需要开具发票的客户，发货时间可能在上述基础上再延后1-2个工作日（紧急发票需求，请联系010-68433105/3213）；
● 如遇其他特殊原因，对发货时间有影响的，我们会第一时间在网站公告，敬请留意。
关于到货时间：
由于进口图书入境入库后，都是委托第三方快递发货，所以我们只能保证在规定时间内发出，但无法为您保证确切的到货时间。
● 主要城市一般2-4天
● 偏远地区一般4-7天
关于接听咨询电话的时间：
010-68433105/3213正常接听咨询电话的时间为：周一至周五上午8：30～下午5：00，周六、日及法定节假日休息，将无法接听来电，敬请谅解。
其它时间您也可以通过邮件联系我们：customer@readgo.cn,工作日会优先处理。
关于快递：
● 已付款订单：主要由中通、宅急送负责派送，订单进度查询请拨打010-68433105/3213。

Data Analysis for Direct Numerical Simulations of Turbulent Combustion:From Equation-Based Analysis to Machine Learning 机械史

Data Analysis for Direct Numerical Simulations of Turbulent Combustion:From Equation-Based Analysis to Machine Learning
机械史