Applied Data Analysis and Modeling for Energy Engineers and Scientists [Paperback]

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 authors own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the processesalong with the tools.

Focusing on the analysis and modeling of thermal systems in engineering, this volume covers the mathematics, data interpretation and decision analysis required for researchers and engineers to scrutinize their methodologies and arrive at robust conclusions.

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.

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, probl³«