T. Agami Reddy

Applied Data Analysis and Modeling for Energy Engineers and Scientists (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

Applied Data Analysis and Modeling for Energy Engineers and Scientists is an ideal volume for researchers, practitioners, and senior level or graduate students working in energy engineering, mathematical modeling and other related areas.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 430
• Erscheinungstermin: 9. August 2011
• Englisch
• ISBN-13: 9781441996138
• Artikelnr.: 43799202

Autorenporträt

T Agami Reddy, PhD, is  Professor Emeritus of Energy and Environment at Arizona State University. He is a licensed mechanical engineer with about 40 years of teaching and research experience in solar energy system simulation and testing, building energy inverse data analysis and modeling, energy efficient and green building technologies, and sustainable/resilience as applied to energy infrastructure systems. He has over 190 journal publications (three of which received best paper awards), edited four conference proceedings or special journal issues, contributed to seven handbook chapters and written three textbooks: The Design and Sizing of Active Solar Systems (Oxford Univ Press, 1987), Applied Data Analysis and Modeling for Energy Engineers and Scientists (Springer, 2011), and Heating and Cooling of Buildings (3rd ed., CRC, 2016). He has completed about 50 research projects with funding from organizations such as NSF, USDOE, EPA, NIST, Homeland Security, ASHRAE and several building control companies. He is Fellow of ASME (past chair of Solar Energy Division, past Associate Editor of ASME Journal of Solar Energy Engineering, and ASME Journal of Sustainable Buildings and Cities) and Fellow of ASHRAE (past Chair of Research Advisory Committee, and past member of Research Advisory Panel). He received his PhD and MS from the Laboratoire de Thermodynamique et d'Energetique, University of Perpignan, France. Gregor P Henze, PhD, PE, is Professor and Charles V Schelke Chair of Architectural Engineering at the University of Colorado Boulder, where his teaching focuses on building and district energy systems, i.e., high-performance building design, building control and automation systems, data science for energy applications, and sustainable building design. His research emphasizes advanced building control approaches, fault detection and diagnosis, characterization of building occupant behavior, human presence detection,sensor fusion systems, as well as the integration of building energy system operations with the electric grid system. He is the primary author of more than 170 research articles, four of which have received best paper awards, and received three patents. He received the 2011 Colorado Cleantech Industry Association's Research and Commercialization Award. Prof. Henze is a professional mechanical engineer, high-performance building design professional, editorial board member for Journal Building Performance Simulation, Fellow of the Renewable and Sustainable Energy Institute, joint professor at the National Renewable Energy Laboratory, as well as co-founder and chief scientist of QCoefficient, Inc., an engineering firm developing real-time optimal control solutions for grid-interactive efficient buildings. He received his Diplom-Ingenieur from the Technical University of Berlin, Germany, his MS from Oregon State University, and his PhD from the University of Colorado Boulder.   

Inhaltsangabe

Models, data analysis and decision making.- Probability concepts and probability distributions.- Data collection and preliminary data analysis.- Making statistical inferences from samples.- Estimation of linear model parameters using least squares.- Designed experiments and analysis of non-intrusive data.- Time series models.- Topics in optimization, parameter estimation and clustering methods.- Inverse problems and illustrative examples.- Decision analysis and risk modeling.