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Applied Data Analysis And Modeling For Energy Engineers And Scientists
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Book Synopsis Applied Data Analysis and Modeling for Energy Engineers and Scientists by : T. Agami Reddy
Download or read book Applied Data Analysis and Modeling for Energy Engineers and Scientists written by T. Agami Reddy and published by Springer Science & Business Media. This book was released on 2011-08-09 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and confidence to work in data analysis and modeling. This volume uses numerous solved examples, published case studies from the author’s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the “processes”along with the tools.
Book Synopsis Applied Data Analysis and Modeling for Energy Engineers and Scientists by : T. Agami Reddy
Download or read book Applied Data Analysis and Modeling for Energy Engineers and Scientists written by T. Agami Reddy and published by Springer Nature. This book was released on 2023-10-18 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in a thoroughly revised and expanded second edition, this classroom-tested text demonstrates and illustrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability, statistics, experimental design, regression, optimization, parameter estimation, inverse modeling, risk analysis, decision-making, and sustainability assessment methods to energy processes and systems. It provides a formal structure that offers a broad and integrative perspective to enhance knowledge, skills, and confidence to work in applied data analysis and modeling problems. This new edition also reflects recent trends and advances in statistical modeling as applied to energy and building processes and systems. It includes numerous examples from recently published technical papers to nurture and stimulate a more research-focused mindset. How the traditional stochastic data modeling approaches are complemented by data analytic algorithmic models such as machine learning and data mining are also discussed. The important societal issues related to the sustainability of energy systems are presented, and a formal structure is proposed meant to classify the various assessment methods found in the literature. Applied Data Analysis and Modeling for Energy Engineers and Scientists is designed for senior-level undergraduate and graduate instruction in energy engineering and mathematical modeling, for continuing education professional courses, and as a self-study reference book for working professionals. In order for readers to have exposure and proficiency with performing hands-on analysis, the open-source Python and R programming languages have been adopted in the form of Jupyter notebooks and R markdown files, and numerous data sets and sample computer code reflective of real-world problems are available online.
Book Synopsis Expanding Boundaries: Systems Thinking in the Built Environment by : Guillaume Habert
Download or read book Expanding Boundaries: Systems Thinking in the Built Environment written by Guillaume Habert and published by vdf Hochschulverlag AG. This book was released on 2016-08-15 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consuming over 40% of total primary energy, the built environment is in the centre of worldwide strategies and measures towards a more sustainable future. To provide resilient solutions, a simple optimisation of individual technologies will not be sufficient. In contrast, whole system thinking reveals and exploits connections between parts. Each system interacts with others on different scales (materials, components, buildings, cities) and domains (ecology, economy and social). Whole-system designers optimize the performance of such systems by understanding interconnections and identifying synergies. The more complete the design integration, the better the result. In this book, the reader will find the proceedings of the 2016 Sustainable Built Environment (SBE) Regional Conference in Zurich. Papers have been written by academics and practitioners from all continents to bring forth the latest understanding on systems thinking in the built environment.
Book Synopsis Predictive Modelling for Energy Management and Power Systems Engineering by : Ravinesh Deo
Download or read book Predictive Modelling for Energy Management and Power Systems Engineering written by Ravinesh Deo and published by Elsevier. This book was released on 2020-09-30 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets. Presents advanced optimization techniques to improve existing energy demand system Provides data-analytic models and their practical relevance in proven case studies Explores novel developments in machine-learning and artificial intelligence applied in energy management Provides modeling theory in an easy-to-read format
Book Synopsis Numerical Analysis for Engineers and Scientists by : G. Miller
Download or read book Numerical Analysis for Engineers and Scientists written by G. Miller and published by Cambridge University Press. This book was released on 2014-05-29 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: A graduate-level introduction balancing theory and application, providing full coverage of classical methods with many practical examples and demonstration programs.
Book Synopsis Data Analysis for Scientists and Engineers by : Edward L. Robinson
Download or read book Data Analysis for Scientists and Engineers written by Edward L. Robinson and published by Princeton University Press. This book was released on 2016-10-04 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix. Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. In-depth discussion of data analysis for scientists and engineers Coverage of both frequentist and Bayesian approaches to data analysis Extensive look at analysis techniques for time-series data and images Detailed exploration of linear and nonlinear modeling of data Emphasis on error analysis Instructor's manual (available only to professors)
Book Synopsis Modeling Tools for Environmental Engineers and Scientists by : Nirmala Khandan
Download or read book Modeling Tools for Environmental Engineers and Scientists written by Nirmala Khandan and published by CRC Press. This book was released on 2001-12-20 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling Tools for Environmental Engineers and Scientists enables environmental professionals, faculty, and students with minimal computer programming skills to develop computer-based mathematical models for natural and engineered environmental systems. The author illustrates how commercially available syntax-free authoring software can be adapted to create customized, high-level models of environmental phenomena in groundwater, soil, aquatic, and atmospheric systems, and in engineered reactors. This book includes a review of mathematical modeling and fundamental concepts such as material balance, reactor configurations, and fate and transport of environmental contaminants. It illustrates, using numerous examples, how mathematical and dynamic modeling software can be applied in analyzing and simulating natural and engineered environmental systems. The tools and examples included are applicable to a wide range of problems, both in the classroom and in the field.
Book Synopsis Building Energy Modeling with OpenStudio by : Larry Brackney
Download or read book Building Energy Modeling with OpenStudio written by Larry Brackney and published by Springer. This book was released on 2018-05-15 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook teaches the fundamentals of building energy modeling and analysis using open source example applications built with the US DOE’s OpenStudio modeling platform and EnergyPlus simulation engine. Designed by researchers at US National Laboratories to support a new generation of high performance buildings, EnergyPlus and OpenStudio are revolutionizing how building energy modeling is taught in universities and applied by professional architects and engineers around the world. The authors, all researchers at National Renewable Energy Laboratory and members of the OpenStudio software development team, present modeling concepts using open source software that may be generally applied using a variety of software tools commonly used by design professionals. The book also discusses modeling process automation in the context of OpenStudio Measures—small self-contained scripts that can transform energy models and their data—to save time and effort. They illustrate key concepts through a sophisticated example problem that evolves in complexity throughout the book. The text also examines advanced topics including daylighting, parametric analysis, uncertainty analysis, design optimization, and model calibration. Building Energy Modeling with OpenStudio teaches students to become sophisticated modelers rather than simply proficient software users. It supports undergraduate and graduate building energy courses in Architecture, and in Mechanical, Civil, Architectural, and Sustainability Engineering.
Book Synopsis Applied Statistical Modeling and Data Analytics by : Srikanta Mishra
Download or read book Applied Statistical Modeling and Data Analytics written by Srikanta Mishra and published by Elsevier. This book was released on 2017-10-27 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncertainty quantification. Beginning with a foundational discussion of exploratory data analysis, probability distributions and linear regression modeling, the book focuses on fundamentals and practical examples of such key topics as multivariate analysis, uncertainty quantification, data-driven modeling, and experimental design and response surface analysis. Data sets from the petroleum geosciences are extensively used to demonstrate the applicability of these techniques. The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal. Authored by internationally renowned experts in developing and applying statistical methods for oil & gas and other subsurface problem domains Written by practitioners for practitioners Presents an easy to follow narrative which progresses from simple concepts to more challenging ones Includes online resources with software applications and practical examples for the most relevant and popular statistical methods, using data sets from the petroleum geosciences Addresses the theory and practice of statistical modeling and data analytics from the perspective of petroleum geoscience applications
Book Synopsis Experimental Statistics and Data Analysis for Mechanical and Aerospace Engineers by : James A. Middleton
Download or read book Experimental Statistics and Data Analysis for Mechanical and Aerospace Engineers written by James A. Middleton and published by CRC Press. This book was released on 2021-11-25 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops foundational concepts in probability and statistics with primary applications in mechanical and aerospace engineering. It develops the mindset a data analyst must have to interpret an ill-defined problem, operationalize it, collect or interpret data, and use this evidence to make decisions that can improve the quality of engineered products and systems. It was designed utilizing the latest research in statistics learning and in engagement teaching practices The author’s focus is on developing students’ conceptual understanding of statistical theory with the goal of effective design and conduct of experiments. Engineering statistics is primarily a form of data modeling. Emphasis is placed on modelling variation in observations, characterizing its distribution, and making inferences with regards to quality assurance and control. Fitting multivariate models, experimental design and hypothesis testing are all critical skills developed. All topics are developed utilizing real data from engineering projects, simulations, and laboratory experiences. In other words, we begin with data, we end with models. The key features are: Realistic contexts situating the learning of the statistics in actual engineering practice. A balance of rigorous mathematics, conceptual scaffolding, and real, messy data, to ensure that students learn the important concepts and can apply them in practice. The consistency of text, lecture notes, data sets, and simulations yield a coherent set of instructional resources for the instructor and a coherent set of learning experiences for the students. MatLab is used as a computational tool. Other tools are easily substituted. Table of Contents 1. Introduction 2. Dealing with Variation 3. Types of Data 4. Introduction to Probability 5. Sampling Distribution of the Mean 6. The Ten Building Blocks of Experimental Design 7. Sampling Distribution of the Proportion 8. Hypothesis Testing Using the 1-sample Statistics 9. 2-sample Statistics 10. Simple Linear Regression 11. The General Linear Model: Regression with Multiple Predictors 12. The GLM with Categorical Independent Variables: The Analysis of Variance 13. The General Linear Model: Randomized Block Factorial ANOVA 14. Factorial Analysis of Variance 15. The Bootstrap 16. Data Reduction: Principal Components Analysis Index Author Biography James A. Middleton is Professor of Mechanical and Aerospace Engineering and former Director of the Center for Research on Education in Science, Mathematics, Engineering, and Technology at Arizona State University. Previously, he held the Elmhurst Energy Chair in STEM education at the University of Birmingham in the UK. He received his Ph.D. from the University of Wisconsin-Madison. He has been Senior co-Chair of the Special Interest Group for Mathematics Education in the American Educational Research Association, and as Chair of the National Council of Teachers of Mathematics’ Research Committee. He has been a consultant for the College Board, the Rand Corporation, the National Academies, the American Statistical Association, the IEEE, and numerous school systems around the United States, the UK, and Australia. He has garnered over $30 million in grants to study and improve mathematics education in urban schools.
Book Synopsis Statistical Reliability Engineering by : Hoang Pham
Download or read book Statistical Reliability Engineering written by Hoang Pham and published by Springer Nature. This book was released on 2021-08-13 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author’s recent research and publications as well as experience of over 30 years in this field. The book covers a wide range of methods and models in reliability, and their applications, including: statistical methods and model selection for machine learning; models for maintenance and software reliability; statistical reliability estimation of complex systems; and statistical reliability analysis of k out of n systems, standby systems and repairable systems. Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field.
Book Synopsis Quantile-Based Reliability Analysis by : N. Unnikrishnan Nair
Download or read book Quantile-Based Reliability Analysis written by N. Unnikrishnan Nair and published by Springer Science & Business Media. This book was released on 2013-08-24 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a fresh approach to reliability theory, an area that has gained increasing relevance in fields from statistics and engineering to demography and insurance. Its innovative use of quantile functions gives an analysis of lifetime data that is generally simpler, more robust, and more accurate than the traditional methods, and opens the door for further research in a wide variety of fields involving statistical analysis. In addition, the book can be used to good effect in the classroom as a text for advanced undergraduate and graduate courses in Reliability and Statistics.
Book Synopsis Stratigraphic Systems by : Glenn S. Visher
Download or read book Stratigraphic Systems written by Glenn S. Visher and published by Academic Press. This book was released on 1999-12-08 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable as a primary text for undergraduate courses in sedimentology and stratigraphy."--BOOK JACKET.
Book Synopsis DPSM for Modeling Engineering Problems by : Dominique Placko
Download or read book DPSM for Modeling Engineering Problems written by Dominique Placko and published by John Wiley & Sons. This book was released on 2007-07-09 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first book on this technique; it describes the theory of DPSM in detail and covers its applications in ultrasonic, magnetic, electrostatic and electromagnetic problems in engineering. For the convenience of the users, the detailed theory of DPSM and its applications in different engineering fields are published here in one book making it easy to acquire a unified knowledge on DPSM.
Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton
Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author :United States. Congress. House. Committee on Science and Technology. Subcommittee on Energy Development and Applications Publisher : ISBN 13 : Total Pages :1698 pages Book Rating :4.:/5 (319 download)
Book Synopsis Fiscal year 1985 Department of Energy authorization by : United States. Congress. House. Committee on Science and Technology. Subcommittee on Energy Development and Applications
Download or read book Fiscal year 1985 Department of Energy authorization written by United States. Congress. House. Committee on Science and Technology. Subcommittee on Energy Development and Applications and published by . This book was released on 1984 with total page 1698 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Control with Engineering Applications by : Hans P. Geering
Download or read book Optimal Control with Engineering Applications written by Hans P. Geering and published by Springer Science & Business Media. This book was released on 2007-03-23 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a variety of problem statements in classical optimal control, in optimal estimation and filtering, and in optimal control problems with non-scalar-valued performance criteria. Many example problems are solved completely in the body of the text. All chapter-end exercises are sketched in the appendix. The theoretical part of the book is based on the calculus of variations, so the exposition is very transparent and requires little mathematical rigor.
